Randomized Trial of Surveillance with Abbreviated MRI in Women with a Personal History of Breast Cancer– Impact on Patient Anxiety and Cancer Detection

Randomized Trial of Surveillance with Abbreviated MRI in Women with a Personal History of Breast Cancer– Impact on Patient Anxiety and Cancer Detection | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Randomized Trial of Surveillance with Abbreviated MRI in Women with a Personal History of Breast Cancer– Impact on Patient Anxiety and Cancer Detection Marina Mohallem Fonseca, Tasneen Alhassan, Yashmin Nisha, Diana Koszycki, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-944603/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract Background : Abbreviated breast MRI (A-MRI) substantially reduces the image acquisition and reading times and has been reported to have similar diagnostic accuracy as a full diagnostic protocol but has not been evaluated prospectively with respect to impact on psychological distress in women with a prior history of breast cancer (PHBC). This study aimed to determine if surveillance mammography (MG) plus A-MRI reduced psychological distress and if A-MRI improved cancer detection rates (CDR) as compared to MG alone. Methods: This prospective controlled trial of parallel design was performed at a tertiary cancer center on asymptomatic women with PHBC who were randomized into two groups: routine surveillance with MG or intervention of MG plus A-MRI in a 1:1 ratio. Primary outcome was anxiety measured by four validated questionnaires at three different time-points during the study. Other parameters including CDR and positive predictive value for biopsy (PPV3) were compared between imaging modalities of MG and A-MRI. Tissue diagnoses or 1 year of follow-up were used to establish the reference standard. Linear mixed models were used to analyze anxiety measures and Fisher’s exact test to compare imaging outcomes. Results: 198 patients were allocated to either MG alone (94) or MG plus A-MRI (104). No significant group difference emerged for improvement in trait anxiety, worry and perceived health status (all Time-by-surveillance group interaction ps>.05). There was some advantage of A-MRI in reducing state anxiety at Time 2 (p0.05) and did not change over time. A-MRI detected 5 invasive cancers and 1 ductal carcinoma in situ (DCIS), and MG detected 1 DCIS. A-MRI had higher incremental CDR (48/1000(5/104) vs MG 5/1000(1/198, p=0.01)) with no difference in PPV3 (A-MRI 28.6% (6/21) vs MG 16.7% (1/6, p>.05). Conclusion: Compared to MG alone, A-MRI had significantly higher incremental cancer detection in PHBC. Despite a higher rate of biopsies, A-MRI had no demonstrable impact on anxiety, worry, and perceived health status. Trial registration: ClinicalTrials.gov (NCT02244593). Prospectively registered on Sept. 14, 2014. Breast cancer MRI anxiety abbreviated mammography Figures Figure 1 Figure 2 Background Women with a prior personal history of breast cancer (PHBC) often have a high level of anxiety related to breast cancer surveillance[ 1 ]. Their actual recurrence rates are estimated in the order of 1-5% per year[ 2 , 3 ], and can be as high as 11% at 5 years and 20% at 10 years after completion of adjuvant chemotherapy[ 4 , 5 ]. Early detection decreases mortality for women with breast cancer[ 6 – 8 ]. In women with PHBC, the survival benefit is improved if new or recurrent breast cancer is found on surveillance mammography (MG) instead of physical examination[ 9 ]. However, MG has been shown to be less sensitive in women with PHBC, with sensitivity of 65.4% compared with 76.5% in women with no PHBC[ 10 ]. Breast MRI is the most sensitive test for detecting breast cancer[ 11 ]. Breast MRI is currently recommended for women with PHBC and dense tissue or those diagnosed by age 50, as per American College of Radiology (ACR) guidelines[ 12 ]. Compliance with MRI screening has been shown to be low, on the order of 25%, due both to lack of availability and high costs associated with lengthy acquisition times[ 4 ][ 13 ]. Abbreviated breast MRI (A-MRI), which substantially reduces the image acquisition and reading times, has been reported to have similar diagnostic accuracy as a full diagnostic protocol[ 4 , 14 – 18 ]. Currently, A-MRI has not been adopted as the standard for screening for breast cancer and more studies are required to evaluate outcomes. Prior studies demonstrated that supplementary MRI surveillance in women at high risk of breast cancer does not impact anxiety, cancer-specific distress or health-related quality of life[ 1 , 19 ]. This is the first study to our knowledge to evaluate the psychological effect of adding abbreviated MRI to MG surveillance in women with PHBC. The primary purpose of the current study was to determine if the intervention of adding A-MRI to MG surveillance was more effective than MG alone in reducing patient anxiety and, secondarily, if A-MRI improved cancer detection in women with PHBC. Methods Study subjects This prospective randomized controlled trial of parallel design was performed at a large tertiary care academic medical center and was approved by the hospital’s institutional review board. Our study adheres to the CONSORT guidelines. Patients at a single tertiary care cancer center were approached by their treating oncologists or surgeons during routine clinical appointments if they met the eligibility criteria and their scheduled appointment time allowed. The patients’ oncologists or surgeons obtained written informed consent. Eight oncologists and three breast surgeons recruited patients between 2/1/2015 and 4/30/2019. Patients were followed for a minimum of 12 months. The eligibility criteria included: (a) female patients 18 years or older; (b) PHBC (including DCIS and invasive ductal or lobular carcinoma); (c) prior unilateral mastectomy or breast conservation surgery; (d) treatment for breast cancer completed; and (e) no symptoms of breast cancer. Patients were excluded if they were considered high-risk (lifetime risk ≥25%)[ 20 ], were unable to undergo an MRI due to either physical or mental issues (i.e.: severe claustrophobia, allergy to gadolinium, severe renal failure), had bilateral mastectomies, were pregnant or breastfeeding, or had undergone a breast MRI within the last 6 months. Regular surveillance imaging consisted of annual surveillance MG, irrespective of breast tissue density. All patients had undergone prior mammographic imaging, and some (<50%) had undergone prior breast MRI imaging. Eligible patients were randomized in a 1:1 allocation ratio to one of the two arms of the study: 1) surveillance with MG or 2) MG plus A-MRI, with use of permuted blocks of variable length (2, 4, and 6) to ensure that recruiting physicians remained unaware of the randomization. Researchers or study participants were not blinded to their allocation. Patients could only participate once in the study. Imaging Technique and Interpretation All mammographic examinations were performed using a full-field digital technique (Hologic, Bedford, MA, USA) in accordance with national guidelines. Standard two-dimensional craniocaudal (CC) and mediolateral oblique (MLO) views were obtained. All abbreviated dynamic contrast material-enhanced breast MRIs were performed with one 3T system (Magnetom TrioTim Syngo, Siemens). The standardized protocol consisted of 8-channel breast coil (Sentinelle Medical Inc.), T1 localizer, T1 dynamic contrast-enhanced fat-suppressed with one precontrast and one 2 min postcontrast (3D transverse, phase encoding direction right to left, phase resolution of 60%, phase partial Fourier 6/8, no interpolation, FA 10 degrees, TR 4.07 msec and TE 1.96 msec, no IR, NEX 1, Voxel size: 1x1x1 mm, acceleration factor 4, no interpolation, base resolution 448,1:01 min, slice thickness 1 mm). Post-processing axial subtracted sequences and axial and sagittal maximum intensity projection were generated of the subtracted images. No T2-weighted sequences were obtained. For all examinations, gadolinium contrast material (Gadovist) was power injected (0.1 mmol/kg at 2mL/s) followed by a 20mL saline flush. The entire protocol took 3 minutes. Surveillance MG and A-MRI were reviewed by one of two breast radiologists independently (the first with 8 years of experience reading mammography and breast MRI and the second reader with 20 years reading mammography and breast MRI) using ACR Breast Imaging-Reporting Data System (BI-RADS) lexicon[ 21 ]. For patients in the A-MRI group, MG and A-MRI studies were performed on the same day according to the protocol. Radiologists were not blinded but reported each modality separately according to the imaging modality findings, with the mammograms interpreted first. Based on the imaging findings, additional mammographic images, including diagnostic tomosynthesis, or targeted ultrasound were requested at the discretion of the interpreting radiologist. Findings and management were communicated to the patient by telephone by the reporting radiologist. Subsequent imaging was performed on separate visits, within 3 weeks of the MG or A-MRI. Histologic samples for pathologic diagnosis were obtained under ultrasound (14G, 5-6 cores), stereotactic (10G, 6-12 cores) or MRI (10G, 6-12 cores) guidance. Anxiety Measures Patients in both groups were asked to fill out four validated self-report questionnaires that measure anxiety level and overall health[ 22 – 25 ])(see supplemental materials). The primary outcome was the State-Trait Anxiety Inventory (STAI)[ 22 ]. This 40-item scale includes 20 items that assess state anxiety (S-Anxiety) (i.e., how the person feels at this moment) and 20-items that assess trait anxiety (T-Anxiety) (i.e., how the personal generally feels). Items are rated on a 1 to 4 scale. The range of scores for each subscale is 20-80, with cut-off scores of ≥32.2 and ≥31.8 indicating elevated levels of state and trait anxiety, respectively. Both STAI subscales have solid psychometric properties and are sensitive to assessment of longitudinal change. There are no validated cutoff scores for the STAI in women with PHBC, however a cutoff score of 41 on the trait form of the STAI has been used in previous research to identify clinical levels of anxiety in women with breast cancer [ 26 ]. Other psychological measures included the Penn State Worry Questionnaire (PSWQ)[ 23 ], Breast Cancer Worry Scale (BCWS)[ 24 ], and the Health Status Questionnaire 12 (HSQ-12)[ 25 ]. The PSWQ[ 23 ] is a 16-item self-report questionnaire which measures frequency and intensity of worry symptoms. Items are rated on a 5-point scale, with total scores ranging from 16-80. A score between 16-39 indicates low worry, 40-59 moderate worry and 60-80 high worry. The BCWS[ 24 ] is a 3-item scale which measures frequency of breast cancer worry and the impact of worrying on mood and ability to perform daily activities. Higher scores indicate greater cancer worry. The HSQ-12[ 25 ] assesses the impact of health on social, emotional and physical functioning over the past four weeks. Depending on the item, questions are rated of a 3-point, 5-point and 6-point scale, with higher scores indicating poorer health status. The questionnaires were completed upon enrolment during consultation (T1), upon receipt of the MG and/or MRI results (T2), and then 6 months later (T3). T3 questionnaires were mailed to patients and returned to the study coordination center. Data Collection and Statistical Analysis Medical records were reviewed to determine patient age, family history of breast and/or ovarian cancer in a first-degree relative, surgery modality, initial breast tumor stage (TNM), histology, hormone receptor status, months since diagnosis of breast cancer and breast density. Results were compared between the two groups. For malignant or atypical/high-risk lesions, surgical pathologic results were reviewed when available. Imaging and clinical follow-up were determined by review of the hospital picture archiving system (PACS) and medical records as well as the digital imaging repository which includes all clinics and hospitals that serve the region’s population of 1.2 million. The emigration rate in the region is < 0.5% per year[ 27 ]. Imaging follow-up for all patients with benign imaging or pathology was documented with the date of the most recent negative mammogram. The anxiety measures were analyzed using SPSS Statistics version 25. Analysis was based on intent-to-treat (ITT) principles. Data were analyzed using linear mixed models, with surveillance groups (MG only versus MG plus A-MRI), time of assessment (T1, T2, T3), and Intervention by Time interaction as fixed factors. Models were estimated using Restricted Maximum Likelihood (REML) with an unstructured covariance structure to account for correlations among repeated measures over time. A significant Time by surveillance group interaction would suggest that changes in measures over time were different between the surveillance method; significant interactions were further analyzed with pairwise least square mean comparisons. Data from missing questionnaires were not imputed because our analytical strategy using REML allowed the estimation of reliable parameters without the need for imputation of the data under an assumption of missing at random (MAR)[ 28 ]. Descriptive statistics were calculated using a spreadsheet software program (Excel, Version 2013, Microsoft). Screening outcomes were compared between groups using Fisher’s exact test. Sample size calculation was based on primary outcome the STAI. There is no generally accepted minimal clinically important difference in the STAI subscales and a 4-point difference was selected to be a minimal clinically important difference. This was based on consensus with the research team and the experience of the psychologist researcher. In order to have 80% power to detect a 4-point difference between the groups, we planned 134 patients per group. Recruitment stopped early due to differences in cancer detection rates (CDR). Results were considered significant if p<0.05. Imaging modalities (MG, A-MRI), and BI-RADS final assessment categories for each modality were noted. Imaging findings and outcomes were documented for all BI-RADS 3, 4 and 5 lesions, including suspicious extra-mammary findings. Results were compared between MG and A-MRI. A screening examination was considered as positive when additional diagnostic imaging was recommended prior to the next routine screening examination and included BI-RADS 0, 3, 4 and 5. True positive findings were defined as a cancer diagnosis within 12 months of a positive screening examination. Imaging studies were considered false negatives if there was a tissue diagnosis of cancer within 12 months of a negative study, or in the surveillance groups if there was a tissue diagnosis of cancer in the follow-up period. The following performance metrics were calculated for each modality: CDR, AIR, biopsy rate, positive predictive value for biopsy recommendations (PPV2), positive predictive value for biopsies performed (PPV3), sensitivity and specificity. Results A total of 202 of 1000 patients fulfilled the eligibility criteria (Fig. 1 ) between 2/1/2015 and 4/30/2019. At enrollment, 94 were randomized to surveillance with MG alone and 108 to MG plus A-MRI. Of these, four patients from MG plus A-MRI group withdrew from the study a few days before undergoing the imaging for different reasons: two patients were discovered to have breast cancer metastases on separate imaging done prior to undergoing the surveillance imaging, one patient developed sepsis before the imaging was performed and her doctor decided to postpone contrast injection and one patient opted to withdraw from the study before undergoing the imaging. Accordingly, the study population consisted of 198 patients: 47.5% (94/198) randomized to regular surveillance with MG and 52.5% (104/198) to surveillance with MG plus A-MRI. All patients completed the imaging to which they were randomized and there were no patient crossovers from the MG only group to A-MRI. Among the 104 patients who had MG plus A-MRI, 82.7% (86/104) had both imaging exams the same day and 17.3% (18/104) on different days (average 33.2 days (range: 1-147)) due to various scheduling conflicts. Baseline demographic and clinical characteristics Patients’ demographic and clinical characteristics are presented in Table 1 . No important differences in age, family history of breast and/or ovarian cancer, surgery modality, months since diagnosis, breast density, initial tumor histology, stage, or hormone receptor status were noted between the two groups, although a nonsignificant higher number of patient with triple negative cancers was observed in the group that received A-MRI. Table 1 Patient demographics according to group (MG versus A-MRI + MG) Group 1-MG (n=94) Group 2- A-MRI + MG (n=104) p value Age (years) Mean 59.0 58.2 0.44 Median 58.5 58 Range 35-80 38-83 Family history breast and/ or ovarian cancer Yes 26 32 0.63 No 68 71 0.53 Unknown 0 1 0.34 Surgery modality Lumpectomy 52 69 0.11 Mastectomy 42 35* 0.11 Months since diagnosis <24 42 44 0.73 24 <x 120 2 6 0.19 Unknown 0 1 0.34 Breast density ACR BI-RADS A 4 7 0.45 ACR BI-RADS B 45 46 0.61 ACR BI-RADS C 44 45 0.50 ACR BI-RADS D 1 6 0.73 Tumor histology Ductal carcinoma in situ 2 7 0.12 Invasive ductal carcinoma 84 89 0.31 Invasive lobular carcinoma 6 8 0.74 Mucinous carcinoma 1 0 NA Unknown 1 0 NA Tumor stage of initial invasive cancer T1 51 44 0.19 T2 27 38 0.14 T3 5 8 0.43 T4 8 5 0.35 NA 1 2 0.59 N0, NX 51 54 0.92 N1 31 33 0.92 M0 94 104 NA Hormone receptor status invasive ca ER positive Her2 negative 69 66 0.33 Her2 positive 12 19 0.21 Triple negative 6 12 0.16 Unknown 4 0 NA * two patients had mastectomy and contralateral lumpectomy Results regarding anxiety The observed means (± standard deviations) for the self-report questionnaires and least square mean difference between the surveillance groups at T2 and T3 are displayed in Table 2 . 197 participants completed questionnaires at T1 (Baseline), 92 patients in MG only and 105 in MG plus A-MRI groups. At Time 2, data were available for 143 participants; 60 in MG and 83 in MG plus A-MRI groups. At T3 data were available for 102 participants; 38 women in MG and 64 in MG plus A-MRI groups. The surveillance groups did not differ significantly on any of the baseline measures. Linear mixed models revealed that our primary outcome STAI-Trait Anxiety did not change over time (Time main effect p=.51) and did not differ between the groups (Time x Surveillance Group interaction p=.20). However, there was a significant Time main effect (p<.001) and Time x Surveillance Group interaction (p=.022) for the STAI-State Anxiety. Post-hoc tests revealed that for both groups, state anxiety decreased significantly between T1 and T2 (estimated mean change = -6.80 [95% CI, -8.58 to -5.02] for MG only (p<.001) and -8.17 [95% CI , -9.70 to -6.34] for MG plus A-MR (p<.001), and increased significantly from T2 to T3 (estimated mean change 5.86 [95% CI , 3.97 to 7.76] for MG only (p<.001) and 8.12 [95% CI , 7.23 to 10.40] for MG plus A-MRI (p<.001). Between groups comparisons indicated that state anxiety at T2 was significantly lower in the MG plus A-MRI group (p=.03), but less than a 4-point difference. Levels of worry did not significantly change over time (Time main effect p=.14 and p=.73 for the PSWQ and BCWQ, respectively) and did not differ between the groups (Time x Surveillance Group interaction p =.57 and p=.48 for the PSWQ and BCWQ, respectively). There was a significant Time main effect for self-report health status (p=.008), but no significant Time x Surveillance Group interaction (p=.10). Overall, HSQ-12 scores increased from T1 to T2 (estimated mean change 0.81 [95% CI,0.14 to 1.49], p=.019) and from T1 to T3 (estimated mean change 1.03, [95% CI , [0.29 to 1.76], p=.006. Using the STAI cutoff score of 41, the percentage of women with anxiety in the clinical range was 100% at T1 and T2 and T3 for both the MG and the MG+A-MRI groups. Table 2. Effect of Surveillance Method on Self-Report Measures *p<.05 MG alone vs MG + A- MRI Note : Analysis is based on the intent-to-treat sample. Questionnaires were completed upon enrolment during consultation (T1; n=92 MG alone and n=103 MG + A-MRI), upon receipt of the MG and/or MRI results (T2; n=61 MG alone and n=84 MG + A-MRI), and 6- months later (T3; n=49 MG alone n=73 MG + A-MRI). For all questionnaires, higher scores represent higher anxiety or worry. STAI=State Trait Anxiety Trait (i.e., how the personal generally feels) and State (i.e., how the person feels at this moment); PSWQ= Penn State Worry Questionnaire; BCWQ= Breast Cancer Worry Scale; HSQ=Health Status Questionnaire Outcomes according to surveillance groups There was 1 cancer (DCIS) detected in the MG group during the study, and 3 cancers (2 invasive and 1 DCIS) were diagnosed at follow-up. In the MG plus A-MRI surveillance group, 5 breast cancers (1 DCIS and 4 invasive cancers) and 1 breast cancer metastasis to the lung were detected, with no cancers diagnosed at follow-up. The outcomes for each group are provided in Table 3 . Although there were significantly more recalls and biopsies performed in the MG plus A-MRI than the MG group (recalls of 27/104 (26%) vs 4/94 (4.26%) (p<0.05) and biopsies of 20/104 (19.2%) vs 2/94 (2.13%)(p=0.001) respectively), with lower specificity (77.8% MG+A-MRI vs 96.7% MG (p=0.0001), the sensitivity for the MG plus A-MRI group was higher 5/5(100%) than the MG group 1/4 (25%)(p=0.048) and there was a higher CDR in the MG plus A-MRI group (5/104 (48.1/1000)) than the MG group (1/94 (10.6/1000)(p= 0.215)). Table 3. Outcomes according to surveillance group Notes: ^False negatives includes breast cancers found at follow-up *In the MG plus A-MRI surveillance group, 1 false positive was found with mammography and 2 false positives were found with both MG and A-MRI. All other false positives were found with A-MRI only. ** p values were obtained comparing the MG group with the MG+A-MRI surveillance groups for intramammary findings only. Findings according to imaging modality Outcomes according to imaging modality are presented in Table 4 . Among the 302 imaging examinations performed (198 MG and 104 A-MRI), 9 MG and 29 A-MRI were interpreted as abnormal (17%) (Fig. 2 ). Table 4 Main imaging findings, BI-RADS category and outcomes according to imaging modality Mammography (n=198) A- MRI (n=104) p value Normal 189 (95.5) 75 (72.1) 0.00001 Recall / abnormal interpretation rate 9 (4.5%) 29 (27.9) 0.00001 Mass 1/9 15/29 Calcifications 6/9 0 Asymmetry 2/9 0 Non mass enhancement 0 9/29 Mass/non mass enhancement 0 1/29 Extra-mammary finding* 0 3/29 Motion artifact 0 1/29 BI-RADS category after work-up/ full MRI diagnostic protocol 0.84 2 2/9 (22.2%) 2/29 (6.9%) 3 1/9 (11.1%) 4/29 (13.8%) 4A 3/9 (33.3%) 10/29 (34.5%) 4B 3/9 (33.3%) 8/29 (27.6%) 5 0 (0%) 2/29 (6.9%) N/A (extra-mammary findings) 0 (0%) 3/29 (10.3%) Outcome (abnormal) 0.49 Work-up (>benign) 2/9 (22.2%) 2/29 (6.9%) Stable on follow-up 1/9 (11.1%) 6/29 (20.7%) Biopsied* 6/9 (66.7%) (6/198=3.0%) 21/29 (72.4%) (21/104=20.2%) Outcome of biopsied lesions 0.99 Benign 5/6 (83.3%) 15/21 (71.4%) Atypical/high risk 0 (0%) 0 (0%) Malignant 1/6 (16.7%) 6/21(28.6%) Note: Unless otherwise indicated, data are numbers of patients and data in parentheses are percentages * Extra-mammary lesions: 2 benign sternal masses (1 biopsied and 1 stable on follow-up) and 1 malignant lung mass (biopsied) ** 1 suspicious A-MRI finding was less conspicuous the day of the biopsy, for which follow-up was performed and showed stability. Mammography There were 198 mammographic examinations performed: 94 MG alone and 104 MG with A-MRI; 95.5% (189/198) were negative or benign (BI-RADS 1 and 2), 4.5% (9/198) were recalled (BI-RADS 0) and 3.0% (6/198) presented findings suspicious for malignancy (BI-RADS 4) and underwent biopsy. One cancer was detected (Table 5 ) and no high-risk lesions were identified. Table 5 Surveillance detected cancer characteristics Study ID Age Breast density (ACR) Months since dx Group Abnormality Detected by BI-RADS Histology TNM ER PR HER 2 neu 1 58 C 25 1 Ca+ MG only 4A DCIS, intermediate nuclear grade Initial ca: IDC, ER-Her+ - 2 80 B 216 2 Mass A-MRI only 4B DCIS, high nuclear grade Initial ca: DCIS - 3 45 C 37 2 Mass A-MRI only 4B IDC, grade 2/3 Initial ca: IDC, ER+ Her- T1c N0 M0 + + - 4 67 C 144 2 NME A-MRI only 4B Microinvasive lobular carcinoma, Pleomorphic lobular carcinoma in situ Initial cancer: IDC, TN T1miN0 M0 5 38 C 7 2 Mass A-MRI only 5 IDC, grade 3/3 Initial ca: IDC, ER+Her+ T3 N2 M0 - - + 6 73 C 120 2 Mass A-MRI only 5 IDC, grade 2/3, DCIS Initial Ca: IDC, TN T2 Nx + - - 7 58 B 33 2 Mass (lung) A-MRI only N/A Adenocarcinoma consistent with breast cancer Initial ca: IDC, ER+ Her- - + + - Group 1: MG Group 2: MG plus A-MRI DCIS: ductal carcinoma in situ IDC: invasive ductal carcinoma TN: triple negative ER: estrogen receptor Her: Herceptin receptor NME: nonmass enhancement NA: not applicable Table 6 Diagnostic indicators of imaging modalities Mammography A-MRI* P value* A-MRI** P value** False negative 6 0 0 True negative 183 75 78 False positive 8 23 21 True positive 1 6 5 Recall rate 9/198 (4.5%) 29/104 (27.9%) 0.00001 25/104 (25%) <0.00001 Biopsy rate 6/198 (3.0%) 21/104 (20.2%) 0.00001 19/104 (18.3%) <0.00001 CDR 1/198 (0.5%) 6/104 (5.8%) 0.003 5/104 (4.8%) 0.0109 PPV2 (recommended) 1/6 (16.7%) 6/22 (27.3%) 0.59 5/20 (25%) 0.59 PPV3 (performed) 1/6 (16.7%) 6/21 (28.6%) 0.55 5/19 (26.3%) 0.557 Sensitivity (%, CI) 1/7 (14.2%, 0.36-57.8) 6/6 (100%) 0.004 5/5 (100%) 0.004 Specificity (%, CI) 183/191 (95.8%, 91.9-98) 75/98 (76.5%,66.9-84.5) 0.00001 78/99 (78.8%) 0.00001 CI: 95% confidence intervals A-MRI: Abbreviated breast MRI CDR: Cancer detection rate (per 1000 women) PPV2: positive predictive value for biopsies recommended PPV3: positive predictive value for biopsies performed CI: confidence interval *including extra-mammary findings, **excluding extra-mammary findings MRI 104 A-MRI studies were performed; 72.1% (75/104) were negative or benign (BI-RADS 1 and 2); 27.9% (29/104) were abnormal including extra-mammary findings, of which 19.2% (20/104) had suspicious breast lesions (BI-RADS 4 or 5); and 18.2% (19/104) underwent breast biopsy. One breast mass detected by A-MRI was not seen at the time of MRI-guided biopsy and showed stability on 6-month follow-up MRI. Breast cancers were detected in 5 patients; 4 invasive carcinomas and one DCIS (Table 4 ). All five cancers were only detected with A-MRI, 2 of which were in patients with original triple negative breast cancers (Fig. 2 ). Three patients had suspicious extra mammary findings: one lung mass seen in the right middle lobe on the A-MRI, and two bone lesions seen in the sternum and manubrium, respectively. The lung mass was confirmed to be a metastatic carcinoma from breast primary on CT guided transthoracic lung biopsy, the manubrial lesion was confirmed to be a hemangioma on bone scan and the sternal lesion was confirmed to be a hibernoma on CT guided biopsy. Of the MRI detected breast cancers, none was identified on mammography, even in retrospect. No high-risk lesions were detected. The mammographic CDR of 5/1000 (1/98) was significantly lower than the CDR of 58/1000 (6/104, p= 0.003) for A-MRI including the extramammary findings, and CDR of 48/1000 (5/104, p=0.0109) for MRI including only the breast findings. The diagnostic indicators for both modalities are presented in Table 5 . Sensitivity for MG 14.2% (1/6)) was lower than A-MRI 100% (5/5)(p<0.004); specificity for MG 95.8% (183/191) higher than MRI 76.5% (78/99) (p<0.00001) and PPV3 for MG 16.7% (1/6) was lower than MRI 28.6% (5/19) (p=0.55). Necessity for full diagnostic or repeat MRI Three patients required further investigation requiring diagnostic full MRI based on the radiologist’s uncertainty of the findings seen on the A-MRI: 1 had a mass which was benign on assessment (fat necrosis) determined by the full protocol, one was a BI-RADS 3 lesion which showed stability on 12- month follow-up and one had BI-RADS 4B lesion that led to a benign MRI-guided biopsy of Pseudoangiomatous hyperplasia. A fourth patient had motion artifact and required a repeat abbreviated MRI that was normal and of high technical quality. Follow-up All 191 patients with benign imaging or pathology results underwent clinical and imaging follow-up at the same center, for an average 24 months (10-56 months). There were no cancers found retrospectively as false negatives on follow-up. 1.57% (3/191) had breast cancer on follow-up, all from the surveillance MG only group. Of the 3 cancers diagnosed on subsequent surveillance imaging with MG, two were diagnosed at 26 & 27 months with MG (DCIS and invasive ductal carcinoma (IDC), T1N0M0) and one was diagnosed at 50 months on MRI IDC, T2N0M0). Two were new cancers in the contralateral breast and one DCIS was in the ipsilateral breast; no cancer was seen retrospectively on initial MG and/or MRI. Of the remaining 188 patients with no cancer diagnosed on follow-up, 98.9 % (186/188) had follow up of 12 months or longer and 1.06 % (2/188) had follow-up of shorter than 12 months. There were no patients lost to follow-up. Discussion This prospective randomized controlled trial showed that undergoing A-MRI had no demonstrable impact on psychological well-being in women with a history of breast cancer. Our primary outcome trait anxiety was moderately high in all patients at baseline and did not change significantly over time; the average score of trait anxiety at the 6-month follow-up was 50.99+/-4.6 with MG vs 51.73+/-2.56 with A-MRI, p>0.05. Similarly, self-report worry, including worry of breast cancer recurrence, did not change over time for both conditions. Although there was some benefit of A-MRI over MG alone in reducing state anxiety when participants received their results (T2), which may reflect a higher confidence in women undergoing A-MRI, the difference was not considered clinically meaningful. Despite higher rates of biopsies and abnormal interpretations with A-MRI, it is notable that breast A-MRI was not associated with an increase in psychological distress. Considering the sustained elevated levels of anxiety and worsening in quality of health in these patients, ongoing consideration and monitoring of mental health issues is recommended. PHBC patients may benefit from psychologist counselling and ongoing support. Our results support other studies on the impact of breast MRI on anxiety. The Dutch MRI screening (MRISC) study of patients at high risk for breast cancer found that the addition of breast MRI did not affect quality of life or anxiety[ 19 ]. In a more recent prospective non-randomized multicentre study, 1561 women at intermediate and high breast cancer risk were noted to have similar moderate distress levels, and there were no more harmful psychological effects observed between standard MG plus ultrasound as compared with the addition of MRI to standard imaging[ 29 ]. A significantly higher CDR was noted in the patients who underwent A-MRI as compared with MG only, despite similar baseline demographic and clinical characteristics. We expected a recurrence rate of 1-2% per year after breast cancer diagnosis[ 30 , 31 ]. Eighty percent of patients were within 5 years of their breast cancer diagnosis, and 9 in-breast recurrences and 1 lung metastasis were observed, within the expected range. Our study demonstrated A-MRI had a sensitivity of 100% and CDR 48/1000 as compared to mammography’s sensitivity of 14.2% and CDR 5/1000. The low sensitivity of mammography of 14% may be attributed to an early stage of diagnosis of breast cancer in most patients with A-MRI as well as the fact that 49% of women had dense breast tissue, which lowers mammographic sensitivity, with four patients with invasive carcinomas found with A-MRI in women with dense breast tissue (Table 5 ). The abnormal interpretation and biopsy rates were significantly higher for A-MRI than MG, 25% and 18.3% for A-MRI and 4.5% and 3% for MG, respectively. PPV3 was higher with A-MRI than MG, 26.3% vs 16.7%, although this difference did not reach statistical significance. When extra-mammary findings were included, A-MRI offered the benefit of detecting an incidental lung metastasis. There have been multiple studies of A-MRI since Dr. Kuhl published her landmark study[ 4 , 14 – 18 , 32 – 34 ]. In a similar study of 725 women with PHBC, Choi et al found 12 cancers using A-MRI, for a CDR 15 per 1000 [ 33 ], with comparable sensitivity of 100% and specificity of 89.2%. The results of A-MRI in our study are comparable to reported sensitivities (86-100%) and specificities (45-95.3%). However, our specificity of 76.5% was lower than the ACR benchmark for screening breast MRI 85-90%[ 21 ]. PPV3 26.3% was in the reported range for A-MRI (9.2-70.2%) and met the ACR benchmark of 20-50%[ 21 ]. In 2020, Park et al retrospectively compared abbreviated to full MRI in 1200 women with PHBC, 656 with A-MRI vs 656 patients with full protocol and found no significant differences in sensitivity (70% vs 100%) or specificity (98% vs 96.9%), Negative predictive values (99.5 and 100%) and PPV (35% vs 23%) (all p>0.05)[ 35 ]. We recognize some limitations of our study. Patients were recruited by their oncologists or treating surgeons, which could have introduced a bias in patient selection. This may have partly explained the CDR in the MG plus A-MRI group. Nonetheless, the fact that randomization was blinded mitigated any potential bias of intervention arm selection and there were no clinical differences between the two surveillance groups. As well, in follow-up, similar numbers of cancers were detected in each surveillance group. This may indicate earlier detection of cancers with A-MRI than interval cancers in the MG group. Because of the CDRs and minimal effect on anxiety in the MRI group we stopped the clinical trial early. Additionally, some patients could have developed breast cancer after the follow up period, which might have been missed with mammography. Given that the majority patients were followed for over 24 months, this is less likely. Another limitation is that the radiologists were not blinded to the allocation arm, which could have influenced their reporting of the mammogram, if they knew that an MRI would be done. However, given similar recall rates for mammography within both groups, this is unlikely to have been present. The high biopsy rate in the MRI group may be perceived as a limitation, but this was related to the high CDR with an acceptable PPV3. However, more research is required to find ways to further reduce the rate of false positives. There is likely a learning curve with A-MRI and the addition of T2 sequences may help to improve PPV3 without significant time cost[ 15 ]. We have subsequently adapted an abbreviated protocol to include T2 sequence and two more post contrast sequences to improve the specificity of MRI[ 36 ]. Another limitation is that assessment of anxiety was based on self-report questionnaires and limited by the time points in which it is measured. There was also a loss of data of the primary outcome for participants over time, which could have led to underestimation of the effect of the surveillance group on levels of anxiety. A more objective measure would be to evaluate adherence to follow-up rounds of screening, which may address poor compliance with MRI screening[ 13 ]. This is recommended for future study. Also, our study lacked the sample size and enough long-term follow-up to be able to say whether the earlier detection in the A-MRI group led to any difference in survival. In conclusion, the addition of A- MRI to surveillance mammography did not impact patient anxiety in women with PHBC, regardless of the significantly higher recall and biopsy rates. A-MRI showed significantly higher cancer detection rate compared to mammography alone, which is consistent with recent recommendations. Although further study with larger cohorts is warranted, an abbreviated protocol may be considered for surveillance in this population. Abbreviations Abbreviated breast magnetic resonance imaging (A-MRI) Mammography (MG) Cancer detection rate (CDR) Ductal carcinoma in situ (DCIS) Invasive ductal carcinoma (IDC) Prior (personal) history of breast cancer (PHBC) Breast Imaging-Reporting Data System (BI-RADS) Cancer detection rate (CDR) Abnormal interpretation rate (AIR) Positive predictive value (PPV) Declarations - Ethics approval and consent to participate: All procedures performed in this study were in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The study was approved by the Institutional Ethics Board “Ottawa Hospital Research Institute (REB approval number: 20140103-01H) with each participant providing written consent. All modifications in the protocol were transmitted to the Ethics Board. - Consent to publish: not applicable. - Availability of data and materials: The data will be deposited in the uOttawa - Dataverse (Université d'Ottawa / University of Ottawa): https://learn.scholarsportal.info/all-guides/dataverse/ and data are available upon request. - Competing interests: The author(s) declare(s) that they have no competing interests. - Funding: Support for this study provided by The Ottawa Hospital Cancer Program to perform the Abbreviated MRI and cover the costs of the contrast injections (Cost no. 717602446). The funding body had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript. - Authors' Contributions: JS, DK, TR and BS participated in the conception and design of the study, and in drafting the manuscript. MF, TA, JL, AA, RS, and YN participated in the conception and design of the study, and in revising the manuscript critically for important intellectual content. All authors read and approved the final manuscript and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. - Acknowledgements: Not applicable References Bredart A, Kop JL, Fall M, et al. Anxiety and specific distress in women at intermediate and high risk of breast cancer before and after surveillance by magnetic resonance imaging and mammography versus standard mammography. Psychooncology. 2012;21:1185–94. Saphner T, Tormey DC, Gray R. Annual hazard rates of recurrence for breast cancer after primary therapy. J Clin Oncol. 1996;14:2738–46. Davies C, Godwin J, Gray R, et al. Relevance of breast cancer hormone receptors and other factors to the efficacy of adjuvant tamoxifen: patient-level meta-analysis of randomised trials. Lancet. 2011;378:771–84. Kuhl CK, Schrading S, Strobel K, Schild HH, Hilgers RD, Bieling HB. Abbreviated breast magnetic resonance imaging (MRI): first postcontrast subtracted images and maximum-intensity projection-a novel approach to breast cancer screening with MRI. J Clin Oncol. 2014;32:2304–10. Brewster AM, Hortobagyi GN, Broglio KR, et al. Residual risk of breast cancer recurrence 5 years after adjuvant therapy. J Natl Cancer Inst. 2008;100:1179–83. Tabar L, Vitak B, Chen TH, et al. Swedish two-county trial: impact of mammographic screening on breast cancer mortality during 3 decades. Radiology. 2011;260:658–63. Coldman A, Phillips N, Wilson C, et al. Pan-Canadian study of mammography screening and mortality from breast cancer. J Natl Cancer Inst 2014; 106. Duffy SW, Tabar L, Chen HH, et al. The impact of organized mammography service screening on breast carcinoma mortality in seven Swedish counties. Cancer. 2002;95:458–69. Lu WLJL, Post WJ, Bonnema J, Van de Velde JC, De Bock GH. Impact on survival of early detection of isolated breast recurrences after the primary treatment for breast cancer: a meta-analysis. Breast Cancer Res Treat. 2009;Apr;114(3):403–12. Houssami NAL, Miglioretti DL, Sickles EA, Kerlikowske K, Buist DS, Geller BM, Muss HB, Irwig L. Accuracy and outcomes of screening mammography in women with a personal history of early-stage breast cancer. JAMA. 2011;305(8):790–9. Feb 23. Houssami N, Ciatto S, Macaskill P, et al. Accuracy and surgical impact of magnetic resonance imaging in breast cancer staging: systematic review and meta-analysis in detection of multifocal and multicentric cancer. J Clin Oncol. 2008;26:3248–58. Monticciolo DL, Newell MS, Moy L, Niell B, Monsees B, Sickles EA. Breast Cancer Screening in Women at Higher-Than-Average Risk: Recommendations From the ACR. J Am Coll Radiol. 2018;15:408–14. Do WSWJ, McGregor HF, Forte DM, Sheldon RR, Sohn VY. Poor compliance despite equal access: Military experience with screening breast MRI in high risk women. Am J Surg. 2019 May;217(5):843–7. Mango VL, Morris EA, David Dershaw D, et al. Abbreviated protocol for breast MRI: are multiple sequences needed for cancer detection? Eur J Radiol. 2015;84:65–70. Grimm LJ, Soo MS, Yoon S, Kim C, Ghate SV, Johnson KS. Abbreviated screening protocol for breast MRI: a feasibility study. Acad Radiol. 2015;22:1157–62. Harvey SC, Di Carlo PA, Lee B, Obadina E, Sippo D, Mullen L. An Abbreviated Protocol for High-Risk Screening Breast MRI Saves Time and Resources. J Am Coll Radiol. 2016;13:374–80. Heacock L, Melsaether AN, Heller SL, et al. Evaluation of a known breast cancer using an abbreviated breast MRI protocol: Correlation of imaging characteristics and pathology with lesion detection and conspicuity. Eur J Radiol. 2016;85:815–23. Moschetta M, Telegrafo M, Rella L, Stabile Ianora AA, Angelelli G. Abbreviated Combined MR Protocol: A New Faster Strategy for Characterizing Breast Lesions. Clin Breast Cancer. 2016;16:207–11. Rijnsburger AJ, Essink-Bot ML, van Dooren S, et al. Impact of screening for breast cancer in high-risk women on health-related quality of life. Br J Cancer. 2004;91:69–76. Lee AJ, Cunningham AP, Kuchenbaecker KB, et al. BOADICEA breast cancer risk prediction model: updates to cancer incidences, tumour pathology and web interface. Br J Cancer. 2014;110:535–45. D’Orsi C, Sickles E, Mendelson E, Morris E, et al ACR BI-RADS® Atlas, Breast Imaging Reporting and Data System. 2013. Spielberger CD, Gorsuch RL, Lushene R, Vagg PR, Jacobs GA. Manual for the State-Trait Anxiety Inventory. Palo Alto: Consulting Psychologists Press; 1983. Meyer TJ, Miller ML, Metzger RL, Borkovec TD. Development and validation of the Penn State Worry Questionnaire. Behav Res Ther. 1990;28:487–95. Lerman C, Trock B, Rimer BK, Jepson C, Brody D, Boyce A. Psychological side effects of breast cancer screening. Health Psychol. 1991;10:259–67. Barry TL, Kaiser KL, Atwood JR. Reliability, validity, and scoring of the Health Status Questionnaire-12 version 2.0. J Nurs Meas. 2007;15:24–35. Keyzer-Dekker CM, de Vries J, Mertens MC, Roukema JA, van der Steeg AF. Cancer or no cancer: the influence of trait anxiety and diagnosis on quality of life with breast cancer and benign disease: a prospective, longitudinal study. World J Surg. 2013;37:2140–7. Ontario TGo. Ontario Demographic Quarterly: Highlights of first quarter. https://www.ontario.ca/page/ontario-demographic-quarterly-highlights-first-quarter . 2021. Rubin RAL GD. Statistical Analysis with Missing Data , Second Edition ed. Hoboken, New Jersey: John Wiley & Sons, Inc, 2002. Bredart A, Kop JL, Fall M, et al. Anxiety and specific distress in women at intermediate and high risk of breast cancer before and after surveillance by magnetic resonance imaging and mammography versus standard mammography. Psychooncology. 2012;21:1185–94. Cuzick J, Sestak I, Pinder SE, et al. Effect of tamoxifen and radiotherapy in women with locally excised ductal carcinoma in situ: long-term results from the UK/ANZ DCIS trial. The lancet oncology. 2011;12:21–9. Darby S, McGale P, Correa C, et al. Effect of radiotherapy after breast-conserving surgery on 10-year recurrence and 15-year breast cancer death: meta-analysis of individual patient data for 10,801 women in 17 randomised trials. Lancet. 2011;378:1707–16. Chen SQ, Huang M, Shen YY, Liu CL, Xu CX. Abbreviated MRI Protocols for Detecting Breast Cancer in Women with Dense Breasts. Korean J Radiol. 2017;18:470–5. Choi BH, Choi N, Kim MY, Yang JH, Yoo YB, Jung HK. Usefulness of abbreviated breast MRI screening for women with a history of breast cancer surgery. Breast Cancer Res Treat. 2018;167:495–502. Petrillo A, Fusco R, Sansone M, et al. Abbreviated breast dynamic contrast-enhanced MR imaging for lesion detection and characterization: the experience of an Italian oncologic center. Breast Cancer Res Treat. 2017;164:401–10. Park KW, Han SB, Han BK, et al. MRI surveillance for women with a personal history of breast cancer: comparison between abbreviated and full diagnostic protocol. Br J Radiol. 2020;93:20190733. Lukaszewicz A, Lamb L, Healey P, Alie E, Seely J. RC215-04 Abbreviated Screening Breast MRI Protocol: Impact on Cancer Detection and Biopsy Rates. Magn Reson Imaging 2019. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-944603","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":84540033,"identity":"ab40d47b-388b-4101-9cd4-ea88fb3cbd9e","order_by":0,"name":"Marina Mohallem Fonseca","email":"","orcid":"","institution":"University of Ottawa Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Marina","middleName":"Mohallem","lastName":"Fonseca","suffix":""},{"id":84540034,"identity":"2fc7316a-3735-4f55-9428-37fa88ffe00e","order_by":1,"name":"Tasneen Alhassan","email":"","orcid":"","institution":"University of Ottawa Faculty of 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Research Institute: Ottawa Hospital Research Institute","correspondingAuthor":true,"prefix":"","firstName":"Jean","middleName":"Morag","lastName":"Seely","suffix":""}],"badges":[],"createdAt":"2021-09-28 10:15:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-944603/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-944603/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":18442791,"identity":"4687cbc8-8d9c-4e3d-bc78-5e671f4ad5ea","added_by":"auto","created_at":"2022-02-21 15:34:32","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":25809,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCONSORT Flow diagram of trial\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-944603/v1/1901775c4b1dfe4b5ba300de.png"},{"id":18442794,"identity":"ed2029c9-cfc5-442c-9836-1d0f11c65e53","added_by":"auto","created_at":"2022-02-21 15:34:33","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":13134916,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e67-year-old woman with PHBC treated by right mastectomy 12 years prior to study.\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eA. MLO and B. CC Left surveillance mammograms show heterogeneously dense breast tissue (BI-RADS C) with normal, stable findings. C. Axial 3D MIP at 2 min post contrast performed after mammograms shows right mastectomy with no chest wall abnormalities and an irregular 4.5 cm enhancing mass in the medial left breast reported as BI-RADS 4B. The second circumscribed mass in the lateral breast corresponded with a benign fibroadenoma. D. Axial 2 min post contrast subtracted image demonstrates the spiculated enhancing mass in the upper medial quadrant of the left breast. E. Axial image from MRI biopsy demonstrates the needle sampling the mass, diagnostic for pleomorphic lobular carcinoma in situ, which was confirmed at surgical excision to be associated with invasive lobular carcinoma.\u003c/p\u003e","description":"","filename":"fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-944603/v1/8bdc794539677ac8dbbf8d44.png"},{"id":18442795,"identity":"69405983-65be-4f8d-a02c-ff7ec15c5a5c","added_by":"auto","created_at":"2022-02-21 15:34:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":545983,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-944603/v1/2c6a93c3-8ac4-486f-afb8-cc9e1cd89d3b.pdf"},{"id":18442793,"identity":"6e2df78c-738d-4c9e-88ba-cb8a2c713874","added_by":"auto","created_at":"2022-02-21 15:34:33","extension":"doc","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":379904,"visible":true,"origin":"","legend":"","description":"","filename":"CONSORT2010Checklist.doc","url":"https://assets-eu.researchsquare.com/files/rs-944603/v1/20c552958cd1fe74aa6da40a.doc"},{"id":18442792,"identity":"02b30014-45e6-405a-adc9-d36eeb2dffc1","added_by":"auto","created_at":"2022-02-21 15:34:33","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":459926,"visible":true,"origin":"","legend":"","description":"","filename":"PDFofQuestionnaireswithoutSTAI.pdf","url":"https://assets-eu.researchsquare.com/files/rs-944603/v1/349218d9488279b1fdab6f35.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eRandomized Trial of Surveillance with Abbreviated MRI in Women with a Personal History of Breast Cancer– Impact on Patient Anxiety and Cancer Detection \u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eWomen with a prior personal history of breast cancer (PHBC) often have a high level of anxiety related to breast cancer surveillance[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Their actual recurrence rates are estimated in the order of 1-5% per year[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], and can be as high as 11% at 5 years and 20% at 10 years after completion of adjuvant chemotherapy[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Early detection decreases mortality for women with breast cancer[\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In women with PHBC, the survival benefit is improved if new or recurrent breast cancer is found on surveillance mammography (MG) instead of physical examination[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, MG has been shown to be less sensitive in women with PHBC, with sensitivity of 65.4% compared with 76.5% in women with no PHBC[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Breast MRI is the most sensitive test for detecting breast cancer[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Breast MRI is currently recommended for women with PHBC and dense tissue or those diagnosed by age 50, as per American College of Radiology (ACR) guidelines[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Compliance with MRI screening has been shown to be low, on the order of 25%, due both to lack of availability and high costs associated with lengthy acquisition times[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e][\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Abbreviated breast MRI (A-MRI), which substantially reduces the image acquisition and reading times, has been reported to have similar diagnostic accuracy as a full diagnostic protocol[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan additionalcitationids=\"CR15 CR16 CR17\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Currently, A-MRI has not been adopted as the standard for screening for breast cancer and more studies are required to evaluate outcomes.\u003c/p\u003e \u003cp\u003ePrior studies demonstrated that supplementary MRI surveillance in women at high risk of breast cancer does not impact anxiety, cancer-specific distress or health-related quality of life[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This is the first study to our knowledge to evaluate the psychological effect of adding abbreviated MRI to MG surveillance in women with PHBC.\u003c/p\u003e \u003cp\u003eThe primary purpose of the current study was to determine if the intervention of adding A-MRI to MG surveillance was more effective than MG alone in reducing patient anxiety and, secondarily, if A-MRI improved cancer detection in women with PHBC.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy subjects\u003c/h2\u003e \u003cp\u003e This prospective randomized controlled trial of parallel design was performed at a large tertiary care academic medical center and was approved by the hospital\u0026rsquo;s institutional review board. Our study adheres to the CONSORT guidelines. Patients at a single tertiary care cancer center were approached by their treating oncologists or surgeons during routine clinical appointments if they met the eligibility criteria and their scheduled appointment time allowed. The patients\u0026rsquo; oncologists or surgeons obtained written informed consent. Eight oncologists and three breast surgeons recruited patients between 2/1/2015 and 4/30/2019. Patients were followed for a minimum of 12 months.\u003c/p\u003e \u003cp\u003eThe eligibility criteria included: (a) female patients 18 years or older; (b) PHBC (including DCIS and invasive ductal or lobular carcinoma); (c) prior unilateral mastectomy or breast conservation surgery; (d) treatment for breast cancer completed; and (e) no symptoms of breast cancer. Patients were excluded if they were considered high-risk (lifetime risk \u0026ge;25%)[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], were unable to undergo an MRI due to either physical or mental issues (i.e.: severe claustrophobia, allergy to gadolinium, severe renal failure), had bilateral mastectomies, were pregnant or breastfeeding, or had undergone a breast MRI within the last 6 months. Regular surveillance imaging consisted of annual surveillance MG, irrespective of breast tissue density. All patients had undergone prior mammographic imaging, and some (\u0026lt;50%) had undergone prior breast MRI imaging.\u003c/p\u003e \u003cp\u003eEligible patients were randomized in a 1:1 allocation ratio to one of the two arms of the study: 1) surveillance with MG or 2) MG plus A-MRI, with use of permuted blocks of variable length (2, 4, and 6) to ensure that recruiting physicians remained unaware of the randomization. Researchers or study participants were not blinded to their allocation. Patients could only participate once in the study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eImaging Technique and Interpretation\u003c/h2\u003e \u003cp\u003e All mammographic examinations were performed using a full-field digital technique (Hologic, Bedford, MA, USA) in accordance with national guidelines. Standard two-dimensional craniocaudal (CC) and mediolateral oblique (MLO) views were obtained.\u003c/p\u003e \u003cp\u003eAll abbreviated dynamic contrast material-enhanced breast MRIs were performed with one 3T system (Magnetom TrioTim Syngo, Siemens). The standardized protocol consisted of 8-channel breast coil (Sentinelle Medical Inc.), T1 localizer, T1 dynamic contrast-enhanced fat-suppressed with one precontrast and one 2 min postcontrast (3D transverse, phase encoding direction right to left, phase resolution of 60%, phase partial Fourier 6/8, no interpolation, FA 10 degrees, TR 4.07 msec and TE 1.96 msec, no IR, NEX 1, Voxel size: 1x1x1 mm, acceleration factor 4, no interpolation, base resolution 448,1:01 min, slice thickness 1 mm). Post-processing axial subtracted sequences and axial and sagittal maximum intensity projection were generated of the subtracted images. No T2-weighted sequences were obtained. For all examinations, gadolinium contrast material (Gadovist) was power injected (0.1 mmol/kg at 2mL/s) followed by a 20mL saline flush. The entire protocol took 3 minutes.\u003c/p\u003e \u003cp\u003eSurveillance MG and A-MRI were reviewed by one of two breast radiologists independently (the first with 8 years of experience reading mammography and breast MRI and the second reader with 20 years reading mammography and breast MRI) using ACR Breast Imaging-Reporting Data System (BI-RADS) lexicon[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. For patients in the A-MRI group, MG and A-MRI studies were performed on the same day according to the protocol. Radiologists were not blinded but reported each modality separately according to the imaging modality findings, with the mammograms interpreted first. Based on the imaging findings, additional mammographic images, including diagnostic tomosynthesis, or targeted ultrasound were requested at the discretion of the interpreting radiologist. Findings and management were communicated to the patient by telephone by the reporting radiologist. Subsequent imaging was performed on separate visits, within 3 weeks of the MG or A-MRI. Histologic samples for pathologic diagnosis were obtained under ultrasound (14G, 5-6 cores), stereotactic (10G, 6-12 cores) or MRI (10G, 6-12 cores) guidance.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eAnxiety Measures\u003c/h2\u003e \u003cp\u003ePatients in both groups were asked to fill out four validated self-report questionnaires that measure anxiety level and overall health[\u003cspan additionalcitationids=\"CR23 CR24\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e])(see supplemental materials). The primary outcome was the State-Trait Anxiety Inventory (STAI)[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This 40-item scale includes 20 items that assess state anxiety (S-Anxiety) (i.e., how the person feels at this moment) and 20-items that assess trait anxiety (T-Anxiety) (i.e., how the personal generally feels). Items are rated on a 1 to 4 scale. The range of scores for each subscale is 20-80, with cut-off scores of \u0026ge;32.2 and \u0026ge;31.8 indicating elevated levels of state and trait anxiety, respectively. Both STAI subscales have solid psychometric properties and are sensitive to assessment of longitudinal change. There are no validated cutoff scores for the STAI in women with PHBC, however a cutoff score of 41 on the trait form of the STAI has been used in previous research to identify clinical levels of anxiety in women with breast cancer [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Other psychological measures included the Penn State Worry Questionnaire (PSWQ)[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], Breast Cancer Worry Scale (BCWS)[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], and the Health Status Questionnaire 12 (HSQ-12)[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The PSWQ[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] is a 16-item self-report questionnaire which measures frequency and intensity of worry symptoms. Items are rated on a 5-point scale, with total scores ranging from 16-80. A score between 16-39 indicates low worry, 40-59 moderate worry and 60-80 high worry. The BCWS[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] is a 3-item scale which measures frequency of breast cancer worry and the impact of worrying on mood and ability to perform daily activities. Higher scores indicate greater cancer worry. The HSQ-12[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] assesses the impact of health on social, emotional and physical functioning over the past four weeks. Depending on the item, questions are rated of a 3-point, 5-point and 6-point scale, with higher scores indicating poorer health status. The questionnaires were completed upon enrolment during consultation (T1), upon receipt of the MG and/or MRI results (T2), and then 6 months later (T3). T3 questionnaires were mailed to patients and returned to the study coordination center.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData Collection and Statistical Analysis\u003c/h2\u003e \u003cp\u003eMedical records were reviewed to determine patient age, family history of breast and/or ovarian cancer in a first-degree relative, surgery modality, initial breast tumor stage (TNM), histology, hormone receptor status, months since diagnosis of breast cancer and breast density. Results were compared between the two groups. For malignant or atypical/high-risk lesions, surgical pathologic results were reviewed when available. Imaging and clinical follow-up were determined by review of the hospital picture archiving system (PACS) and medical records as well as the digital imaging repository which includes all clinics and hospitals that serve the region\u0026rsquo;s population of 1.2 million. The emigration rate in the region is \u0026lt; 0.5% per year[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Imaging follow-up for all patients with benign imaging or pathology was documented with the date of the most recent negative mammogram.\u003c/p\u003e \u003cp\u003eThe anxiety measures were analyzed using SPSS Statistics version 25. Analysis was based on intent-to-treat (ITT) principles. Data were analyzed using linear mixed models, with surveillance groups (MG only versus MG plus A-MRI), time of assessment (T1, T2, T3), and Intervention by Time interaction as fixed factors. Models were estimated using Restricted Maximum Likelihood (REML) with an unstructured covariance structure to account for correlations among repeated measures over time. A significant Time by surveillance group interaction would suggest that changes in measures over time were different between the surveillance method; significant interactions were further analyzed with pairwise least square mean comparisons. Data from missing questionnaires were not imputed because our analytical strategy using REML allowed the estimation of reliable parameters without the need for imputation of the data under an assumption of missing at random (MAR)[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Descriptive statistics were calculated using a spreadsheet software program (Excel, Version 2013, Microsoft). Screening outcomes were compared between groups using Fisher\u0026rsquo;s exact test. Sample size calculation was based on primary outcome the STAI. There is no generally accepted minimal clinically important difference in the STAI subscales and a 4-point difference was selected to be a minimal clinically important difference. This was based on consensus with the research team and the experience of the psychologist researcher. In order to have 80% power to detect a 4-point difference between the groups, we planned 134 patients per group. Recruitment stopped early due to differences in cancer detection rates (CDR). Results were considered significant if p\u0026lt;0.05.\u003c/p\u003e \u003cp\u003eImaging modalities (MG, A-MRI), and BI-RADS final assessment categories for each modality were noted. Imaging findings and outcomes were documented for all BI-RADS 3, 4 and 5 lesions, including suspicious extra-mammary findings. Results were compared between MG and A-MRI. A screening examination was considered as positive when additional diagnostic imaging was recommended prior to the next routine screening examination and included BI-RADS 0, 3, 4 and 5. True positive findings were defined as a cancer diagnosis within 12 months of a positive screening examination. Imaging studies were considered false negatives if there was a tissue diagnosis of cancer within 12 months of a negative study, or in the surveillance groups if there was a tissue diagnosis of cancer in the follow-up period. The following performance metrics were calculated for each modality: CDR, AIR, biopsy rate, positive predictive value for biopsy recommendations (PPV2), positive predictive value for biopsies performed (PPV3), sensitivity and specificity.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 202 of 1000 patients fulfilled the eligibility criteria (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e) between 2/1/2015 and 4/30/2019. At enrollment, 94 were randomized to surveillance with MG alone and 108 to MG plus A-MRI. Of these, four patients from MG plus A-MRI group withdrew from the study a few days before undergoing the imaging for different reasons: two patients were discovered to have breast cancer metastases on separate imaging done prior to undergoing the surveillance imaging, one patient developed sepsis before the imaging was performed and her doctor decided to postpone contrast injection and one patient opted to withdraw from the study before undergoing the imaging. Accordingly, the study population consisted of 198 patients: 47.5% (94/198) randomized to regular surveillance with MG and 52.5% (104/198) to surveillance with MG plus A-MRI. All patients completed the imaging to which they were randomized and there were no patient crossovers from the MG only group to A-MRI. Among the 104 patients who had MG plus A-MRI, 82.7% (86/104) had both imaging exams the same day and 17.3% (18/104) on different days (average 33.2 days (range: 1-147)) due to various scheduling conflicts.\u003c/p\u003e\n\u003cdiv class=\"Section2\" id=\"Sec8\"\u003e\n \u003ch2\u003eBaseline demographic and clinical characteristics\u003c/h2\u003e\n \u003cp\u003ePatients\u0026rsquo; demographic and clinical characteristics are presented in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. No important differences in age, family history of breast and/or ovarian cancer, surgery modality, months since diagnosis, breast density, initial tumor histology, stage, or hormone receptor status were noted between the two groups, although a nonsignificant higher number of patient with triple negative cancers was observed in the group that received A-MRI.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePatient demographics according to group (MG \u003cem\u003eversus\u003c/em\u003e A-MRI + MG)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGroup 1-MG\u003c/p\u003e\n \u003cp\u003e(n=94)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGroup 2- A-MRI + MG\u003c/p\u003e\n \u003cp\u003e(n=104)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35-80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38-83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFamily history breast and/ or ovarian cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSurgery modality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLumpectomy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMastectomy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMonths since diagnosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u003cspan class=\"Underline\" name=\"Emphasis\" type=\"Underline\"\u003e\u0026lt;x\u003c/span\u003e\u0026lt;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u003cspan class=\"Underline\" name=\"Emphasis\" type=\"Underline\"\u003e\u0026le;\u003c/span\u003ex\u003cspan class=\"Underline\" name=\"Emphasis\" type=\"Underline\"\u003e\u0026le;\u003c/span\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBreast density\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACR BI-RADS A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACR BI-RADS B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACR BI-RADS C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACR BI-RADS D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor histology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDuctal carcinoma in situ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInvasive ductal carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInvasive lobular carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMucinous carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor stage of initial invasive cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN0, NX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHormone receptor status invasive ca\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eER positive Her2 negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHer2 positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTriple negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e* two patients had mastectomy and contralateral lumpectomy\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec9\"\u003e\n \u003ch2\u003eResults regarding anxiety\u003c/h2\u003e\n \u003cp\u003eThe observed means (\u0026plusmn; standard deviations) for the self-report questionnaires and least square mean difference between the surveillance groups at T2 and T3 are displayed in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. 197 participants completed questionnaires at T1 (Baseline), 92 patients in MG only and 105 in MG plus A-MRI groups. At Time 2, data were available for 143 participants; 60 in MG and 83 in MG plus A-MRI groups. At T3 data were available for 102 participants; 38 women in MG and 64 in MG plus A-MRI groups. The surveillance groups did not differ significantly on any of the baseline measures. Linear mixed models revealed that our primary outcome STAI-Trait Anxiety did not change over time (Time main effect p=.51) and did not differ between the groups (Time x Surveillance Group interaction p=.20). However, there was a significant Time main effect (p\u0026lt;.001) and Time x Surveillance Group interaction (p=.022) for the STAI-State Anxiety. Post-hoc tests revealed that for both groups, state anxiety decreased significantly between T1 and T2 (estimated mean change = -6.80 [95% CI, -8.58 to -5.02] for MG only (p\u0026lt;.001) and -8.17 [95% \u003cem\u003eCI\u003c/em\u003e, -9.70 to -6.34] for MG plus A-MR (p\u0026lt;.001), and increased significantly from T2 to T3 (estimated mean change 5.86 [95% \u003cem\u003eCI\u003c/em\u003e, 3.97 to 7.76] for MG only (p\u0026lt;.001) and 8.12 [95% \u003cem\u003eCI\u003c/em\u003e, 7.23 to 10.40] for MG plus A-MRI (p\u0026lt;.001). Between groups comparisons indicated that state anxiety at T2 was significantly lower in the MG plus A-MRI group (p=.03), but less than a 4-point difference. Levels of worry did not significantly change over time (Time main effect p=.14 and p=.73 for the PSWQ and BCWQ, respectively) and did not differ between the groups (Time x Surveillance Group interaction p =.57 and p=.48 for the PSWQ and BCWQ, respectively). There was a significant Time main effect for self-report health status (p=.008), but no significant Time x Surveillance Group interaction (p=.10). Overall, HSQ-12 scores increased from T1 to T2 (estimated mean change 0.81 [95% CI,0.14 to 1.49], p=.019) and from T1 to T3 (estimated mean change 1.03, [95% \u003cem\u003eCI\u003c/em\u003e, [0.29 to 1.76], p=.006. Using the STAI cutoff score of 41, the percentage of women with anxiety in the clinical range was 100% at T1 and T2 and T3 for both the MG and the MG+A-MRI groups.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2. \u0026nbsp; Effect of Surveillance Method on Self-Report Measures\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e*p\u0026lt;.05 MG alone vs MG + A- MRI\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote\u003c/em\u003e: Analysis is based on the intent-to-treat sample. \u0026nbsp;Questionnaires were completed upon enrolment during consultation (T1; n=92 MG alone and n=103 MG + A-MRI), upon receipt of the MG and/or MRI results (T2; n=61 MG alone and n=84 MG + A-MRI), and 6- months later (T3; n=49 MG alone n=73 MG + A-MRI).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor all questionnaires, higher scores represent higher anxiety or worry.\u003c/p\u003e\n\u003cp\u003eSTAI=State Trait Anxiety Trait (i.e., how the personal generally feels) and State (i.e., how the person feels at this moment); PSWQ= Penn State Worry Questionnaire; BCWQ= Breast Cancer Worry Scale; HSQ=Health Status Questionnaire\u0026nbsp;\u003c/p\u003e\n \u003cdiv class=\"Section2\" id=\"Sec10\"\u003e\n \u003ch2\u003eOutcomes according to surveillance groups\u003c/h2\u003e\n \u003cp\u003eThere was 1 cancer (DCIS) detected in the MG group during the study, and 3 cancers (2 invasive and 1 DCIS) were diagnosed at follow-up. In the MG plus A-MRI surveillance group, 5 breast cancers (1 DCIS and 4 invasive cancers) and 1 breast cancer metastasis to the lung were detected, with no cancers diagnosed at follow-up. The outcomes for each group are provided in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. Although there were significantly more recalls and biopsies performed in the MG plus A-MRI than the MG group (recalls of 27/104 (26%) vs 4/94 (4.26%) (p\u0026lt;0.05) and biopsies of 20/104 (19.2%) vs 2/94 (2.13%)(p=0.001) respectively), with lower specificity (77.8% MG+A-MRI vs 96.7% MG (p=0.0001), the sensitivity for the MG plus A-MRI group was higher 5/5(100%) than the MG group 1/4 (25%)(p=0.048) and there was a higher CDR in the MG plus A-MRI group (5/104 (48.1/1000)) than the MG group (1/94 (10.6/1000)(p= 0.215)).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3. Outcomes according to surveillance group\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003cp\u003eNotes:\u003c/p\u003e\n\u003cp\u003e^False negatives includes breast cancers found at follow-up\u003c/p\u003e\n\u003cp\u003e*In the MG plus A-MRI surveillance group, 1 false positive was found with mammography and 2 false positives were found with both MG and A-MRI. All other false positives were found with A-MRI only.\u003c/p\u003e\n\u003cp\u003e**\u003cem\u003ep\u003c/em\u003e values were obtained comparing the MG group with the MG+A-MRI surveillance groups for intramammary findings only.\u003c/p\u003e\n \u003cdiv class=\"Section2\" id=\"Sec11\"\u003e\n \u003ch2\u003eFindings according to imaging modality\u003c/h2\u003e\n \u003cp\u003eOutcomes according to imaging modality are presented in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. Among the 302 imaging examinations performed (198 MG and 104 A-MRI), 9 MG and 29 A-MRI were interpreted as abnormal (17%) (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003ctable border=\"1\" id=\"Tab4\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMain imaging findings, BI-RADS category and outcomes according to imaging modality\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMammography (n=198)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eA- MRI (n=104)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e189 (95.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75 (72.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRecall / abnormal interpretation rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (4.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (27.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15/29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCalcifications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6/9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAsymmetry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2/9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon mass enhancement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9/29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMass/non mass enhancement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExtra-mammary finding*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3/29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMotion artifact\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBI-RADS category after work-up/ full MRI diagnostic protocol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2/9 (22.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2/29 (6.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/9 (11.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4/29 (13.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3/9 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10/29 (34.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3/9 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8/29 (27.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2/29 (6.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN/A (extra-mammary findings)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3/29 (10.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOutcome (abnormal)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWork-up (\u0026gt;benign)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2/9 (22.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2/29 (6.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStable on follow-up\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/9 (11.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6/29 (20.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiopsied*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6/9 (66.7%) (6/198=3.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21/29 (72.4%) (21/104=20.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOutcome of biopsied lesions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBenign\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5/6 (83.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15/21 (71.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAtypical/high risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMalignant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/6 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6/21(28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eNote: Unless otherwise indicated, data are numbers of patients and data in parentheses are percentages\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e* Extra-mammary lesions: 2 benign sternal masses (1 biopsied and 1 stable on follow-up) and 1 malignant lung mass (biopsied)\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e** 1 suspicious A-MRI finding was less conspicuous the day of the biopsy, for which follow-up was performed and showed stability.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv class=\"Section2\" id=\"Sec12\"\u003e\n \u003ch2\u003eMammography\u003c/h2\u003e\n \u003cp\u003eThere were 198 mammographic examinations performed: 94 MG alone and 104 MG with A-MRI; 95.5% (189/198) were negative or benign (BI-RADS 1 and 2), 4.5% (9/198) were recalled (BI-RADS 0) and 3.0% (6/198) presented findings suspicious for malignancy (BI-RADS 4) and underwent biopsy. One cancer was detected (Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e) and no high-risk lesions were identified.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u003ctable border=\"1\" id=\"Tab5\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSurveillance detected cancer characteristics\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStudy ID\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBreast density (ACR)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMonths since dx\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAbnormality\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDetected by\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBI-RADS\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHistology\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTNM\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eER\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHER 2 neu\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCa+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMG only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDCIS, intermediate nuclear grade\u003c/p\u003e\n \u003cp\u003eInitial ca: IDC, ER-Her+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA-MRI only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDCIS, high nuclear grade\u003c/p\u003e\n \u003cp\u003eInitial ca: DCIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA-MRI only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIDC, grade 2/3\u003c/p\u003e\n \u003cp\u003eInitial ca: IDC, ER+ Her-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT1c N0 M0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNME\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA-MRI only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMicroinvasive lobular carcinoma, Pleomorphic lobular carcinoma in situ\u003c/p\u003e\n \u003cp\u003eInitial cancer: IDC, TN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT1miN0 M0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA-MRI only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIDC, grade 3/3\u003c/p\u003e\n \u003cp\u003eInitial ca: IDC, ER+Her+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT3 N2 M0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA-MRI only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIDC, grade 2/3, DCIS\u003c/p\u003e\n \u003cp\u003eInitial Ca: IDC, TN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT2 Nx\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMass (lung)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA-MRI only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdenocarcinoma consistent with breast cancer\u003c/p\u003e\n \u003cp\u003eInitial ca: IDC, ER+ Her-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\"\u003eGroup 1: MG\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\"\u003eGroup 2: MG plus A-MRI\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\"\u003eDCIS: ductal carcinoma in situ\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\"\u003eIDC: invasive ductal carcinoma\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\"\u003eTN: triple negative\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\"\u003eER: estrogen receptor\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\"\u003eHer: Herceptin receptor\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\"\u003eNME: nonmass enhancement\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\"\u003eNA: not applicable\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003ctable border=\"1\" id=\"Tab6\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDiagnostic indicators of imaging modalities\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMammography\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eA-MRI*\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value*\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eA-MRI**\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value**\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFalse negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTrue negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFalse positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTrue positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRecall rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9/198 (4.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e29/104 (27.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25/104 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiopsy rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6/198 (3.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e21/104 (20.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19/104 (18.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCDR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/198 (0.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e6/104 (5.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5/104 (4.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0109\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePPV2 (recommended)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/6 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e6/22 (27.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5/20 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePPV3 (performed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/6 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e6/21 (28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5/19 (26.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.557\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSensitivity (%, CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/7 (14.2%, 0.36-57.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e6/6 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5/5 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpecificity (%, CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e183/191 (95.8%, 91.9-98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e75/98 (76.5%,66.9-84.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e78/99 (78.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eCI: 95% confidence intervals\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eA-MRI: Abbreviated breast MRI\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eCDR: Cancer detection rate (per 1000 women)\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003ePPV2: positive predictive value for biopsies recommended\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003ePPV3: positive predictive value for biopsies performed\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eCI: confidence interval\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003e*including extra-mammary findings, **excluding extra-mammary findings\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cdiv class=\"Section3\" id=\"Sec13\"\u003e\n \u003ch2\u003eMRI\u003c/h2\u003e\n \u003cp\u003e104 A-MRI studies were performed; 72.1% (75/104) were negative or benign (BI-RADS 1 and 2); 27.9% (29/104) were abnormal including extra-mammary findings, of which 19.2% (20/104) had suspicious breast lesions (BI-RADS 4 or 5); and 18.2% (19/104) underwent breast biopsy. One breast mass detected by A-MRI was not seen at the time of MRI-guided biopsy and showed stability on 6-month follow-up MRI. Breast cancers were detected in 5 patients; 4 invasive carcinomas and one DCIS (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). All five cancers were only detected with A-MRI, 2 of which were in patients with original triple negative breast cancers (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Three patients had suspicious extra mammary findings: one lung mass seen in the right middle lobe on the A-MRI, and two bone lesions seen in the sternum and manubrium, respectively. The lung mass was confirmed to be a metastatic carcinoma from breast primary on CT guided transthoracic lung biopsy, the manubrial lesion was confirmed to be a hemangioma on bone scan and the sternal lesion was confirmed to be a hibernoma on CT guided biopsy. Of the MRI detected breast cancers, none was identified on mammography, even in retrospect. No high-risk lesions were detected.\u003c/p\u003e\n \u003cp\u003eThe mammographic CDR of 5/1000 (1/98) was significantly lower than the CDR of 58/1000 (6/104, p= 0.003) for A-MRI including the extramammary findings, and CDR of 48/1000 (5/104, p=0.0109) for MRI including only the breast findings. The diagnostic indicators for both modalities are presented in Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e. Sensitivity for MG 14.2% (1/6)) was lower than A-MRI 100% (5/5)(p\u0026lt;0.004); specificity for MG 95.8% (183/191) higher than MRI 76.5% (78/99) (p\u0026lt;0.00001) and PPV3 for MG 16.7% (1/6) was lower than MRI 28.6% (5/19) (p=0.55).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv class=\"Section2\" id=\"Sec14\"\u003e\n \u003ch2\u003eNecessity for full diagnostic or repeat MRI\u003c/h2\u003e\n \u003cp\u003eThree patients required further investigation requiring diagnostic full MRI based on the radiologist\u0026rsquo;s uncertainty of the findings seen on the A-MRI: 1 had a mass which was benign on assessment (fat necrosis) determined by the full protocol, one was a BI-RADS 3 lesion which showed stability on 12- month follow-up and one had BI-RADS 4B lesion that led to a benign MRI-guided biopsy of Pseudoangiomatous hyperplasia. A fourth patient had motion artifact and required a repeat abbreviated MRI that was normal and of high technical quality.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv class=\"Section2\" id=\"Sec15\"\u003e\n \u003ch2\u003eFollow-up\u003c/h2\u003e\n \u003cp\u003eAll 191 patients with benign imaging or pathology results underwent clinical and imaging follow-up at the same center, for an average 24 months (10-56 months). There were no cancers found retrospectively as false negatives on follow-up. 1.57% (3/191) had breast cancer on follow-up, all from the surveillance MG only group. Of the 3 cancers diagnosed on \u003cem\u003esubsequent\u003c/em\u003e surveillance imaging with MG, two were diagnosed at 26 \u0026amp; 27 months with MG (DCIS and invasive ductal carcinoma (IDC), T1N0M0) and one was diagnosed at 50 months on MRI IDC, T2N0M0). Two were new cancers in the contralateral breast and one DCIS was in the ipsilateral breast; no cancer was seen retrospectively on initial MG and/or MRI. Of the remaining 188 patients with no cancer diagnosed on follow-up, 98.9 % (186/188) had follow up of 12 months or longer and 1.06 % (2/188) had follow-up of shorter than 12 months. There were no patients lost to follow-up.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis prospective randomized controlled trial showed that undergoing A-MRI had no demonstrable impact on psychological well-being in women with a history of breast cancer. Our primary outcome trait anxiety was moderately high in all patients at baseline and did not change significantly over time; the average score of trait anxiety at the 6-month follow-up was 50.99+/-4.6 with MG vs 51.73+/-2.56 with A-MRI, p\u0026gt;0.05. Similarly, self-report worry, including worry of breast cancer recurrence, did not change over time for both conditions. Although there was some benefit of A-MRI over MG alone in reducing state anxiety when participants received their results (T2), which may reflect a higher confidence in women undergoing A-MRI, the difference was not considered clinically meaningful. Despite higher rates of biopsies and abnormal interpretations with A-MRI, it is notable that breast A-MRI was not associated with an increase in psychological distress. Considering the sustained elevated levels of anxiety and worsening in quality of health in these patients, ongoing consideration and monitoring of mental health issues is recommended. PHBC patients may benefit from psychologist counselling and ongoing support.\u003c/p\u003e \u003cp\u003eOur results support other studies on the impact of breast MRI on anxiety. The Dutch MRI screening (MRISC) study of patients at high risk for breast cancer found that the addition of breast MRI did not affect quality of life or anxiety[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In a more recent prospective non-randomized multicentre study, 1561 women at intermediate and high breast cancer risk were noted to have similar moderate distress levels, and there were no more harmful psychological effects observed between standard MG plus ultrasound as compared with the addition of MRI to standard imaging[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA significantly higher CDR was noted in the patients who underwent A-MRI as compared with MG only, despite similar baseline demographic and clinical characteristics. We expected a recurrence rate of 1-2% per year after breast cancer diagnosis[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Eighty percent of patients were within 5 years of their breast cancer diagnosis, and 9 in-breast recurrences and 1 lung metastasis were observed, within the expected range. Our study demonstrated A-MRI had a sensitivity of 100% and CDR 48/1000 as compared to mammography\u0026rsquo;s sensitivity of 14.2% and CDR 5/1000. The low sensitivity of mammography of 14% may be attributed to an early stage of diagnosis of breast cancer in most patients with A-MRI as well as the fact that 49% of women had dense breast tissue, which lowers mammographic sensitivity, with four patients with invasive carcinomas found with A-MRI in women with dense breast tissue (Table \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The abnormal interpretation and biopsy rates were significantly higher for A-MRI than MG, 25% and 18.3% for A-MRI and 4.5% and 3% for MG, respectively. PPV3 was higher with A-MRI than MG, 26.3% vs 16.7%, although this difference did not reach statistical significance. When extra-mammary findings were included, A-MRI offered the benefit of detecting an incidental lung metastasis.\u003c/p\u003e \u003cp\u003eThere have been multiple studies of A-MRI since Dr. Kuhl published her landmark study[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan additionalcitationids=\"CR15 CR16 CR17\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In a similar study of 725 women with PHBC, Choi et al found 12 cancers using A-MRI, for a CDR 15 per 1000 [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], with comparable sensitivity of 100% and specificity of 89.2%. The results of A-MRI in our study are comparable to reported sensitivities (86-100%) and specificities (45-95.3%). However, our specificity of 76.5% was lower than the ACR benchmark for screening breast MRI 85-90%[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. PPV3 26.3% was in the reported range for A-MRI (9.2-70.2%) and met the ACR benchmark of 20-50%[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In 2020, Park et al retrospectively compared abbreviated to full MRI in 1200 women with PHBC, 656 with A-MRI vs 656 patients with full protocol and found no significant differences in sensitivity (70% vs 100%) or specificity (98% vs 96.9%), Negative predictive values (99.5 and 100%) and PPV (35% vs 23%) (all p\u0026gt;0.05)[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe recognize some limitations of our study. Patients were recruited by their oncologists or treating surgeons, which could have introduced a bias in patient selection. This may have partly explained the CDR in the MG plus A-MRI group. Nonetheless, the fact that randomization was blinded mitigated any potential bias of intervention arm selection and there were no clinical differences between the two surveillance groups. As well, in follow-up, similar numbers of cancers were detected in each surveillance group. This may indicate earlier detection of cancers with A-MRI than interval cancers in the MG group. Because of the CDRs and minimal effect on anxiety in the MRI group we stopped the clinical trial early. Additionally, some patients could have developed breast cancer after the follow up period, which might have been missed with mammography. Given that the majority patients were followed for over 24 months, this is less likely. Another limitation is that the radiologists were not blinded to the allocation arm, which could have influenced their reporting of the mammogram, if they knew that an MRI would be done. However, given similar recall rates for mammography within both groups, this is unlikely to have been present. The high biopsy rate in the MRI group may be perceived as a limitation, but this was related to the high CDR with an acceptable PPV3. However, more research is required to find ways to further reduce the rate of false positives. There is likely a learning curve with A-MRI and the addition of T2 sequences may help to improve PPV3 without significant time cost[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. We have subsequently adapted an abbreviated protocol to include T2 sequence and two more post contrast sequences to improve the specificity of MRI[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Another limitation is that assessment of anxiety was based on self-report questionnaires and limited by the time points in which it is measured. There was also a loss of data of the primary outcome for participants over time, which could have led to underestimation of the effect of the surveillance group on levels of anxiety. A more objective measure would be to evaluate adherence to follow-up rounds of screening, which may address poor compliance with MRI screening[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This is recommended for future study. Also, our study lacked the sample size and enough long-term follow-up to be able to say whether the earlier detection in the A-MRI group led to any difference in survival.\u003c/p\u003e \u003cp\u003eIn conclusion, the addition of A- MRI to surveillance mammography did not impact patient anxiety in women with PHBC, regardless of the significantly higher recall and biopsy rates. A-MRI showed significantly higher cancer detection rate compared to mammography alone, which is consistent with recent recommendations. Although further study with larger cohorts is warranted, an abbreviated protocol may be considered for surveillance in this population.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003eAbbreviated breast magnetic resonance imaging (A-MRI)\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eMammography (MG)\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eCancer detection rate (CDR)\u003c/li\u003e\n \u003cli\u003eDuctal carcinoma in situ (DCIS)\u003c/li\u003e\n \u003cli\u003eInvasive ductal carcinoma (IDC)\u003c/li\u003e\n \u003cli\u003ePrior (personal) history of breast cancer (PHBC)\u003c/li\u003e\n \u003cli\u003eBreast Imaging-Reporting Data System (BI-RADS)\u003c/li\u003e\n \u003cli\u003eCancer detection rate (CDR)\u003c/li\u003e\n \u003cli\u003eAbnormal interpretation rate (AIR)\u003c/li\u003e\n \u003cli\u003ePositive predictive value (PPV)\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e- Ethics approval and consent to participate: \u003c/strong\u003eAll procedures performed in this study were in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The study was approved by the Institutional Ethics Board \u0026ldquo;Ottawa Hospital Research Institute (REB approval number: \u003cstrong\u003e20140103-01H) \u003c/strong\u003ewith each participant providing written consent. All modifications in the protocol were transmitted to the Ethics Board.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e- Consent to publish: \u003c/strong\u003enot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e - Availability of data and materials: \u003c/strong\u003eThe data will be deposited in the uOttawa - Dataverse (Universit\u0026eacute; d\u0026apos;Ottawa / University of Ottawa): https://learn.scholarsportal.info/all-guides/dataverse/ and data are available upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e - Competing interests: \u003c/strong\u003eThe author(s) declare(s) that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e - Funding: \u003c/strong\u003eSupport for this study provided by The Ottawa Hospital Cancer Program to perform the Abbreviated MRI and cover the costs of the contrast injections (Cost no. 717602446). The funding body had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e - Authors\u0026apos; Contributions: \u003c/strong\u003eJS, DK, TR and BS participated in the conception and design of the study, and in drafting the manuscript. MF, TA, JL, AA, RS, and YN participated in the conception and design of the study, and in revising the manuscript critically for important intellectual content. All authors read and approved the final manuscript and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e - Acknowledgements: Not applicable\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBredart A, Kop JL, Fall M, et al. Anxiety and specific distress in women at intermediate and high risk of breast cancer before and after surveillance by magnetic resonance imaging and mammography versus standard mammography. Psychooncology. 2012;21:1185\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaphner T, Tormey DC, Gray R. Annual hazard rates of recurrence for breast cancer after primary therapy. J Clin Oncol. 1996;14:2738\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavies C, Godwin J, Gray R, et al. Relevance of breast cancer hormone receptors and other factors to the efficacy of adjuvant tamoxifen: patient-level meta-analysis of randomised trials. Lancet. 2011;378:771\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKuhl CK, Schrading S, Strobel K, Schild HH, Hilgers RD, Bieling HB. 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Hoboken, New Jersey: John Wiley \u0026amp; Sons, Inc, 2002.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBredart A, Kop JL, Fall M, et al. Anxiety and specific distress in women at intermediate and high risk of breast cancer before and after surveillance by magnetic resonance imaging and mammography versus standard mammography. Psychooncology. 2012;21:1185\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCuzick J, Sestak I, Pinder SE, et al. Effect of tamoxifen and radiotherapy in women with locally excised ductal carcinoma in situ: long-term results from the UK/ANZ DCIS trial. The lancet oncology. 2011;12:21\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDarby S, McGale P, Correa C, et al. Effect of radiotherapy after breast-conserving surgery on 10-year recurrence and 15-year breast cancer death: meta-analysis of individual patient data for 10,801 women in 17 randomised trials. 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MRI surveillance for women with a personal history of breast cancer: comparison between abbreviated and full diagnostic protocol. Br J Radiol. 2020;93:20190733.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLukaszewicz A, Lamb L, Healey P, Alie E, Seely J. RC215-04 Abbreviated Screening Breast MRI Protocol: Impact on Cancer Detection and Biopsy Rates. \u003cem\u003eMagn Reson Imaging\u003c/em\u003e 2019.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Breast cancer, MRI, anxiety, abbreviated, mammography","lastPublishedDoi":"10.21203/rs.3.rs-944603/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-944603/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003eBackground\u003c/em\u003e: Abbreviated breast MRI (A-MRI) substantially reduces the image acquisition and reading times and has been reported to have similar diagnostic accuracy as a full diagnostic protocol but has not been evaluated prospectively with respect to impact on psychological distress in women with a prior history of breast cancer (PHBC). This study aimed to determine if surveillance mammography (MG) plus A-MRI reduced psychological distress and if A-MRI improved cancer detection rates (CDR) as compared to MG alone.\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cem\u003eMethods:\u003c/em\u003e This prospective controlled trial of parallel design was performed at a tertiary cancer center on asymptomatic women\u003cstrong\u003e \u003c/strong\u003ewith PHBC who were randomized into two groups: routine surveillance with MG or intervention of MG plus A-MRI in a 1:1 ratio. Primary outcome was anxiety measured by four validated questionnaires at three different time-points during the study. Other parameters including CDR and positive predictive value for biopsy (PPV3) were compared between imaging modalities of MG and A-MRI. Tissue diagnoses or 1 year of follow-up were used to establish the reference standard. Linear mixed models were used to analyze anxiety measures and Fisher’s exact test to compare imaging outcomes.\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cem\u003eResults:\u003c/em\u003e 198 patients were allocated to either MG alone (94) or MG plus A-MRI (104). No significant group difference emerged for improvement in trait anxiety, worry and perceived health status (all Time-by-surveillance group interaction ps\u0026gt;.05). There was some advantage of A-MRI in reducing state anxiety at Time 2 (p\u0026lt;.05). Anxiety scores in all questionnaires were similarly elevated in both groups (50.99+/-4.6 with MG alone vs 51.73+/-2.56 with MG plus A-MRI, p\u0026gt;0.05) and did not change over time. A-MRI detected 5 invasive cancers and 1 ductal carcinoma in situ (DCIS), and MG detected 1 DCIS. A-MRI had higher incremental CDR (48/1000(5/104) vs MG 5/1000(1/198, p=0.01)) with no difference in PPV3 (A-MRI 28.6% (6/21) vs MG 16.7% (1/6, p\u0026gt;.05).\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cem\u003eConclusion:\u003c/em\u003e Compared to MG alone, A-MRI had significantly higher incremental cancer detection in PHBC. Despite a higher rate of biopsies, A-MRI had no demonstrable impact on anxiety, worry, and perceived health status. \u0026nbsp;\u003c/p\u003e\u003cp\u003eTrial registration: ClinicalTrials.gov (NCT02244593). Prospectively registered on Sept. 14, 2014.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"Randomized Trial of Surveillance with Abbreviated MRI in Women with a Personal History of Breast Cancer– Impact on Patient Anxiety and Cancer Detection","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-02-21 15:34:31","doi":"10.21203/rs.3.rs-944603/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2022-02-23T06:09:48+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-02-23T05:15:27+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2021-10-03T20:21:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a09bd781-ce81-4f20-a3a3-7c64cb2c8a20","owner":[],"postedDate":"February 21st, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2022-06-18T01:57:12+00:00","versionOfRecord":[],"versionCreatedAt":"2022-02-21 15:34:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-944603","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-944603","identity":"rs-944603","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}