Assessment of the Accuracy of Biparametric MRI/TRUS Fusion-Guided Biopsy for Index Tumor Evaluation using Postoperative Pathology Specimens

Assessment of the Accuracy of Biparametric MRI/TRUS Fusion-Guided Biopsy for Index Tumor Evaluation using Postoperative Pathology Specimens | 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 Assessment of the Accuracy of Biparametric MRI/TRUS Fusion-Guided Biopsy for Index Tumor Evaluation using Postoperative Pathology Specimens Ryutaro Shimizu, Shuichi Morizane, Atsushi Yamamoto, Hiroshi Yamane, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2916106/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Multiparametric MRI (mpMRI) is widely used for prostate cancer diagnosis, surveillance, and staging; however, it has some limitations, including higher cost, longer examination time, and the use of gadolinium-based contrast agents. This study aimed to investigate the accuracy of index tumor (IT) assessed preoperatively using biparametric MRI (bpMRI)/transrectal ultrasound (TRUS) fusion prostate biopsy with radical prostatectomy (RP) specimens. Methods We included 69 patients diagnosed with prostate cancer through bpMRI/TRUS fusion-guided biopsy of lesions with Prostate Imaging Reporting & Data System (PI-RADS) category ≥ 3 and underwent robot-assisted laparoscopic radical prostatectomy (RARP) at our institution between July 2017 and December 2021. The localization of preoperative and postoperative IT, highest Gleason score (GS), and tumor diameter were examined in these patients. Results The preoperative cT stage matched the postoperative pT stage in 34 cases (48%), while 20 cases (30%) were upstaged, and 15 cases (22%) were downstaged (Weighted Kappa = 0.236). The preoperative and postoperative IT localization were consistent in 59 cases (85.5%). The concordance rate between Gleason groups in targeted biopsy and RP specimens was 48%, with an upgrade in 17 cases (24%) and a downgrade in 29 cases (28%) (Weighted Kappa = 0.424). The IT maximum diameter and maximum cancer core length on biopsy were correlated with RP tumor maximum diameter (p = 0.007, p = 0.008). Conclusion In conclusion, the diagnostic accuracy of bpMRI/TRUS fusion biopsy is comparable to that of previous reports using mpMRI. The findings suggest that bpMRI/TRUS fusion biopsy can be a cost-effective and time-saving alternative. Prostate cancer biparametric MRI MRI/transrectal ultrasound fusion prostate biopsy Figures Figure 1 Introduction Prostate cancer (PCa) diagnosis is primarily based on prostate-specific antigen (PSA), imaging, and histology results. Based on this diagnostic information, a risk classification is established, and treatment is determined. However, issues such as image quality and biopsy sampling errors can lead to diagnostic inaccuracies. Especially in prostate cancer surgery, we often experience discrepancies between the preoperative evaluation and the radical prostatectomy specimen. Prostate cancer surgery, including nerve sparing and lymph node dissection, is planned based on preoperative assessments of lesion localization and grade using MRI images and biopsy results. However, there are cases in which preoperative assessments underestimate the extent of cancer, leading to positive margins in postoperative pathology, or overestimate it, resulting in missed opportunities for nerve-sparing [ 1 , 2 ]. Multiparametric MRI (mpMRI) is a widely used technique for prostate cancer diagnosis, surveillance, and staging [ 3 ]. Accurate tumor localization with mpMRI and fusion of MR and transrectal ultrasound (TRUS) images for biopsy may provide a more accurate preoperative evaluation [ 4 ]. This technique, known as mpMRI/TRUS fusion-guided biopsy, has become increasingly common, and its accuracy has been validated in several studies using postoperative pathology specimens [ 5 , 6 ]. However, mpMRI has limitations, including higher cost, longer examination time, and the use of gadolinium-based contrast agents. Our institution uses biparametric MRI (bpMRI), including the T2W and DW MRI series, for the diagnosis of prostate cancer. Several studies have shown that bpMRI provides similar results to mpMRI in detecting and localizing PCa [ 7 , 8 ]. However, no studies have compared bpMRI with radical prostatectomy (RP) specimens. In the present study, we examined the accuracy of index tumor (IT) assessed preoperatively using bpMRI-TRUS fusion prostate biopsy with RP specimens. MATERIALS AND METHODS This study was approved by the Ethics Committee of Tottori University Faculty of Medicine, Yonago, Japan (approval number: 20A016), and was conducted in accordance with the ethical guidelines set by the government. As this study involved only medical data and did not involve direct patient contact, informed consent was waived by the ethics committee. The study details were disclosed on the website in advance to ensure transparency and adherence to ethical standards. Patients Between July 2017 and December 2021, 69 patients who were diagnosed with prostate cancer through bpMRI/TRUS fusion-guided biopsy of lesions with Prostate Imaging Reporting & Data System (PI-RADS) category ≥ 3 and underwent robot-assisted laparoscopic radical prostatectomy (RARP) at our institution were included. MRI and registration analysis All male patients underwent a 1.5T or 3T bpMRI. PI-RADS guidelines state that both 1.5 T and 3.0 T can provide adequate and reliable diagnostic examinations [9]. MRI imaging conditions were in accordance with the PI-RADS [9]. Prior to biopsy, all suspicious lesions found on prostate MRI were scored by a single board-certified radiologist with expertise in prostate imaging. If MRI was initially conducted and read by a third-party radiologist, a second reading was performed at our institution, and scoring was based on the PI-RADS guideline recommendations. Additionally, during the imaging evaluation, the radiologist was informed about patients’ PSA levels, age, and other clinical information. Preoperative IT localization, highest Gleason score (GS), and tumor diameter were examined in these patients. IT localization was determined by the radiologist using a sector map adapted from the European Consensus Conference and ESUR Prostate MRI Guidelines 2012 to PI-RADS v2 [10]. For this study, preoperative IT was defined as a positive target biopsy with a PI-RADS category ≥ 3 and the largest lesion. Prostate biopsy The TRINITYTM system (Koelis, La Tronche, France) was utilized for all biopsy procedures, with the patient under spinal epidural anesthesia in the lithotripsy position. Initially, we visualized three-dimensional (3D) volume data obtained from MRI and real-time TRUS images. Elastic image fusion was conducted by semi-automatically contouring the MRI image of the entire prostate and suspected lesions on 3D TRUS images. The biopsy procedure involved a two-core biopsy targeted to each suspicious lesion identified on MRI, followed by a 10–14 core systematic biopsy (SB). If there were three or more MRI lesions, two MRI-targeted biopsies (TBs) were performed. In this case, one MRI-TB was conducted on the index lesion and another on the next suspected lesion. All biopsy cores were obtained by experienced urologists (T.S., S.R.). Surgery and pathology for registration analysis Robotic RP was performed on all patients, and the surgical specimens were fixed in 10% neutral-buffered formalin, embedded in paraffin blocks, and stained with hematoxylin and eosin. The inferior-most 5–7-mm portion of the gland was defined as the apex of the prostate, while the superior-most 5–7-mm portion of the gland was defined as the base of the prostate; the remainder was defined as the mid-gland. The apex and the base of the prostate were divided into 3–5-mm sagittal sections and the mid-gland into 3–5-mm horizontal sections. Pathologists at our institution obtained IT localization from pathology reports. In RP specimens, an IT lesion was defined as the lesion with extraprostatic extension or the largest volume. To assess concordance rates for pathology assessment, we utilized the revised prostate cancer grading system, Grade Group (GG), released by the International Society of Urologic Pathology (ISUP) in 2014 [11]. Statistical analyses A t-test was used to evaluate the difference between MR-estimated IT diameter and histological-IT diameter. To assess agreement between biopsies and RP specimens in GG, as well as between cTstage and pTstage, we used weighted Kappa statistics (k). For all tests, P values<0.05, were considered statistically significant. Statistical analyses were conducted using SPSS Statistics software version 24.0 (SPSS Inc., ). RESULT Patients Table 1 displays the patient characteristics before prostate biopsy. The mean age of the 69 patients with preoperative IT was 70 years (range: 45–78 years). The median PSA was 8.68 ng/ml (range: 4.17–19.28 ng/ml) and the median prostate volume was 26.4 ml (range: 14.0–84.0 ml). The median waiting time from biopsy to surgery was 116 days (range: 467–347). MRI was conducted at 3.0T and 1.5T in 55 and 14 patients, respectively. The PI-RADS rating of IT on pre-biopsy MRI evaluation was 3, 4, and 5 in 13 (26%), 28 (56%), and 9 patients (18%), respectively. Table 1 Patient characteristics Age, median (range) 69 (45–78) PSA, ng/ml, median (range) 8.68 (4.17–19.50) prostate volume, ml, median (range) 26.4 (14.0–84.0) median waiting time, day, median (range) 122 (43–347) Pre-operative IT PI-RADS 3, n (%) PI-RADS 4, n (%) PI-RADS 5, n (%) 17 (24.6%) 39 (56.5%) 13 (18.8%) cT stage cT2a, n (%) cT2b, n (%) cT2c, n (%) cT3a, n (%) cT3b, n (%) 19 (27.5%) 1 (1.4%) 28 (40.6%) 20 (29.0%) 1 (1.4%) Abbreviations: PSA, prostate-specific antigen Table 2 Accuracy of MRI T-stage diagnosis pT2a pT2b pT2c pT3a pT3b total cT2a 5 0 13 1 0 19 cT2b 0 0 1 0 0 1 cT2c 0 0 23 3 2 28 cT3a 0 1 13 6 0 20 cT3b 1 0 0 0 0 1 Total 6 1 50 10 2 69 Table 3 Accuracy of IT localization and radial margin (RM) positive rate Concordance Discordance Localization, n (%) 59(85.5%) 10(14.5%) RM+, n/all (%) 7/54(13%) 3/10(30%) Abbreviation: RM, radial margin Accuracy of bpMRI Tstage Diagnosis The distribution of cTstage was as follows: T2a in 13 cases (26%), T2b in 1 case (2%), T2c in 22 cases (44%), T3a in 13 cases (26%), and T3b in 1 case (2%). The pTstage was T2a in 19 cases (26%), T2b in 1 case (2%), T2c in 22 cases (44%), T3a in 13 cases (26%), and T3b in 1 case (2%). Of the cTstage cases, 20 (30%) were underestimated, 15 (22%) were overestimated, and 34 (48%) were concordant, resulting in a weighted kappa coefficient of 0.236 (Table. 2). Accuracy of IT localization and size diagnosis The agreement between the localization of IT assessed by bpMRI and biopsy with that in the RP specimen was 84% (Table. 3). The diagnostic accuracy of IT localization was not affected by the magnet strengths of the MRI (1.5T or 3.0T) (p = 0.674). The mean diameter of IT assessed by bpMRI was 10.7 mm (range: 4–24 mm), while that in the RP specimen was 16.3 mm (range: 4–35 mm). Grade Group (GG) concordance between biopsy and RP specimens Table 4 and Fig. 1 present the GG concordance between systematic biopsy (SB), targeted biopsy (TB), SB + TB, and RP specimens. Table 4 Pathology concordance of biopsy schemes and radical prostatectomy specimen final pathology Abbreviations: SB, Systematic biopsy; TB, Target biopsy; GG, Gleason grade Radical prostatectomy specimens (GG) biopsy specimens 1 2 3 4 5 SB (n = 63) 0 19 20 8 16 GG1 (n = 8) 0 4 4 0 0 GG2 (n = 8) 0 3 2 0 3 GG3 (n = 14) 0 6 2 4 2 GG4 (n = 17) 0 3 6 4 4 GG5 (n = 16) 0 3 6 0 7 TB (n = 69) 0 23 20 8 18 GG1 (n = 2) 0 1 0 0 1 GG2 (n = 15) 0 11 4 0 0 GG3 (n = 16) 0 4 8 3 1 GG4 (n = 22) 0 5 5 5 7 GG5 (n = 14) 0 2 3 0 9 SB + TB (n = 69) 0 23 20 8 18 GG1 (n = 0) 0 0 0 0 0 GG2 (n = 7) 0 6 1 0 0 GG3 (n = 13) 0 6 4 3 0 GG4 (n = 23) 0 7 6 5 5 GG5 (n = 26) 0 4 9 0 13 GG concordance between SB and RP specimens was observed in 16 cases (16%), with 23 (37%) and 24 cases (38%) being underestimated and overestimated, respectively (weighted kappa coefficient: 0.169). Grade concordance between TB and RP specimens was found in 33 cases (48%), with 17 (24%) and 19 cases (28%) being underestimated and overestimated, respectively (weighted kappa coefficient: 0.424). Grade concordance between SB + TB and RP specimens was found in 28 cases (41%), with 9 (13%) and 32 cases (46%) being underestimated and overestimated, respectively (weighted kappa coefficient: 0.307). DISCUSSION In the diagnosis of prostate cancer, it is crucial to identify clinically significant prostate cancers that would benefit from treatment [ 12 ]. Several reports have suggested that MRI-TRUS fusion biopsy is superior in detecting clinically significant prostate cancer (csPCa) because it can accurately assess lesions noted on MRI [ 13 – 16 ]. PI-RADS evaluation has become standard to interpret MRI and multiparametric MRI (mpMRI) is used, which combines anatomic T2W imaging with functional and physiologic assessment, including diffusion-weighted imaging (DWI) and its derivative apparent-diffusion coefficient (ADC) maps, dynamic contrast-enhanced (DCE) MRI [ 17 , 9 ]. High detection rates of csPCa have been reported for PI-RADS category 4 and 5 lesions, making them suitable candidates for targeted biopsy. However, the detection rate of cancer in category 3 lesions varies from 5–26%, depending on the report, and management of these lesions has not been established [ 18 – 21 ]. At our institution, PI-RADS category ≥ 3 is the target for targeted biopsy. Due to the growing demand for prostate diagnostics, it is imperative to address the long waiting time for mpMRI and the burden on radiologists [ 22 , 23 ]. Additionally, cost reduction is necessary where possible. To tackle these challenges, one potential solution is MRI without gadolinium-based contrast agents (bpMRI). Nonenhanced MRI can improve patient throughput by reducing examination time and the amount of MRI preparation required prior to the examination, including precautions regarding contrast media. Additionally, MRI protocols that do not require the injection of contrast agents are preferred by patients, which can reduce patient discomfort and side effects (e.g., hematoma, contrast extravasation, allergic reactions, nephrogenic systemic fibrosis in patients with impaired renal function, intracranial gadolinium deposition), while also reducing time in the scanner [ 24 ]. Most MRI studies of suspected cancer can also be identified using only T2-weighted MRI and DWI criteria, as can a significant proportion of large tumors and PI-RADS 4 lesions, especially those assigned to the PI-RADS 5 category. DCE-MRI can be useful in detecting small cancers that are less prominent or occult on T2-weighted images and DWI, or when DW images are affected by prostheses [ 9 , 25 ]. Local contrast enhancement increases the confidence of the reader and helps inexperienced readers find MRI-positive scans [ 26 – 28 ]. A UK-based study reported that the addition of DCE-MRI to T2W and DWI led to a significant increase in overall cost, approximately 70%, due to the inclusion of contrast media, syringes, scanner time, and reading times. However, the clinical benefit of this additional cost is not clear, and further research is needed to determine whether the added benefit justifies the extra expense [ 29 ]. Schoots et al. reported that the PI-RADS committee needs better quality data to make evidence-based recommendations for contrast-free MRI as an initial diagnostic approach to prostate cancer screening [ 30 ]. In this study, we examined the accuracy of bpMRI-TRUS fusion biopsy by evaluating postoperative pathology specimens. The reported sensitivity of mpMRI for detecting IT ranged from 75.9–93.3% [ 31 , 32 ]. Baco et al. reported the accuracy of histologically confirmed IT detection with mpMRI-TRUS fusion biopsy as 95% (n = 135), while Francesco et al. reported it as 82.2% (n = 152) [ 5 , 33 ]. In this study, which used bpMRI-TRUS fusion biopsy, the accuracy of IT assessment was 85.5% (59/69), which we considered to be comparable to previous mpMRI reports. Furthermore, Baco et al. reported that mpMRI-assessed IT underestimates tumor volume by 5.9% [ 5 ], and the maximum IT diameter assessed by bpMRI in our study was underestimated, with a mean of 10.9 mm on MRI and 18.5 mm on RP specimens (no figure). In the T stage, bpMRI and RP specimens were consistent in about half of the cases. Ct2a cases were upgraded to Ct2c in 13 of 19 cases, while Ct3a cases were downgraded to Ct2 in 14 of 20 cases. This finding suggests that RP specimens may reveal micro lesions that are undetectable on MRI, and that it can be challenging to evaluate micro extracapsular invasion. Ploussard et al. reported that the concordance rate of GS between TB alone and RP samples in mpMRI/TRUS fusion biopsy was 45.2% [ 34 ], which is similar to the 48.0% concordance rate for TB alone in this study. However, one difference is that the GS concordance rate between SB + TB and RP specimens was 41% in this study, whereas it was 51.7% in Ploussard et al. In this study, TB alone had the highest accuracy of GS concordance with the RP specimen, but the addition of SB reduced the preoperative underestimation from 24–13%. Although the reason for this is unclear, the results suggest that bpMRI does not confer inferiority in GS evaluation, at least in the case of TB alone. A limitation of this study is that the cohort included only patients who had PI-RADS category ≥ 3 lesions detected by bpMRI and who underwent radical prostatectomy. In addition, the quality of radiological interpretation and the technique of the biopsy physician was not verified, and therefore cannot be directly compared with previous reports. Nevertheless, our study provides insight into the usefulness and limitations of bpMRI in the era of increasing MRI/TRUS fusion biopsy in the future. Conclusion The diagnostic accuracy of bpMRI/TRUS fusion biopsy is not comparable to that of previous reports using mpMRI. Furthermore, the results suggest that bpMRI/TRUS fusion biopsy is useful in terms of saving time and cost. Further research is necessary to verify the cases in which there is no disadvantage in using bpMRI. Declarations Acknowledgments I would like to thank the radiology and urology doctors who were involved in the preparation of the paper. 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Anticancer Res 38(5):3043–3047. 10.21873/anticanres.12560 Ploussard G, Dubosq F, Soliman H, Verine J, Desgrandchamps F, De Thé H, Mongiat-Artus P (2010) Prognostic value of loss of heterozygosity at chromosome 9p in non-muscle-invasive bladder cancer. Urology 76(2):513e513–513e518. 10.1016/j.urology.2010.03.037 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-2916106","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":201608693,"identity":"5b282ac7-766e-477d-9ebc-1d79c6633447","order_by":0,"name":"Ryutaro Shimizu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCUlEQVRIie2RP2rDMBSHn3kgL26yqjSQKzwoxBhMzqIgqqnQjhk8eFKWHCC9hXsDB4MmHcCli0PXQOnmpVCZBLpUSbOVom/U49Pv/QEIBP4ghFiDoGIOcXl4YccKepVYC+iWRkLSANTiN0piKeosRiWXB+UsKVd31UIzHD+9b98++vxhBAlBX0CcepRsI0270JMRf5VItVCZdkq0NoBZ6WmsVaodUuhGMl6Lhth0T3BVgvvAp9zPnIJRdd0clSHl85Ri7awVbvyK47eCp1KylVatcEvmVt6SVcop7LGZGO6dJUU0L7075Xi13XXLPKdpic+7fZFL38Z+xrXEJV2kDMwvVwKBQOCf8gV20Vb5k4vQwQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-3766-2131","institution":"Tottori University Faculty of Medicine: Tottori Daigaku Igakubu","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Ryutaro","middleName":"","lastName":"Shimizu","suffix":""},{"id":201608694,"identity":"42011907-f57a-491a-888b-1c36bf3d14d2","order_by":1,"name":"Shuichi Morizane","email":"","orcid":"","institution":"Tottori University Faculty of Medicine: Tottori Daigaku Igakubu","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shuichi","middleName":"","lastName":"Morizane","suffix":""},{"id":201608695,"identity":"81cf1f95-3640-4c4a-b2f3-9b1bd02f28ba","order_by":2,"name":"Atsushi Yamamoto","email":"","orcid":"","institution":"Tottori University Faculty of Medicine: Tottori Daigaku Igakubu","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Atsushi","middleName":"","lastName":"Yamamoto","suffix":""},{"id":201608696,"identity":"b515f7ed-15ee-4b7e-9848-ea194cb3f0fe","order_by":3,"name":"Hiroshi Yamane","email":"","orcid":"","institution":"Tottori University Faculty of Medicine: Tottori Daigaku Igakubu","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hiroshi","middleName":"","lastName":"Yamane","suffix":""},{"id":201608697,"identity":"0a336a0c-40c7-4870-9b29-ee1358fb2441","order_by":4,"name":"Ryoma Nishikawa","email":"","orcid":"","institution":"Tottori University Faculty of Medicine: Tottori Daigaku Igakubu","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ryoma","middleName":"","lastName":"Nishikawa","suffix":""},{"id":201608698,"identity":"5574d66e-aa23-4698-a2a0-bf7718f5c853","order_by":5,"name":"Yusuke Kimura","email":"","orcid":"","institution":"Tottori University Faculty of Medicine: Tottori Daigaku Igakubu","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yusuke","middleName":"","lastName":"Kimura","suffix":""},{"id":201608699,"identity":"6c6becb0-55a8-4bf5-8548-a6ca64d8d76a","order_by":6,"name":"Noriya Yamaguchi","email":"","orcid":"","institution":"Tottori University Faculty of Medicine: Tottori Daigaku Igakubu","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Noriya","middleName":"","lastName":"Yamaguchi","suffix":""},{"id":201608700,"identity":"805223b3-7595-4d94-aa3c-d29b7108875c","order_by":7,"name":"Katsuya Hikita","email":"","orcid":"","institution":"Tottori University Faculty of Medicine: Tottori Daigaku Igakubu","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Katsuya","middleName":"","lastName":"Hikita","suffix":""},{"id":201608701,"identity":"e21407e5-be64-43ae-9fd9-e83bc993d238","order_by":8,"name":"Masashi Honda","email":"","orcid":"","institution":"Tottori University Faculty of Medicine: Tottori Daigaku Igakubu","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Masashi","middleName":"","lastName":"Honda","suffix":""},{"id":201608702,"identity":"7f6971d1-a15e-4b5a-abd3-f1e4f307ca3b","order_by":9,"name":"Atsushi Takenaka","email":"","orcid":"","institution":"Tottori University Faculty of Medicine: Tottori Daigaku Igakubu","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Atsushi","middleName":"","lastName":"Takenaka","suffix":""}],"badges":[],"createdAt":"2023-05-10 12:35:02","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2916106/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2916106/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":37328735,"identity":"e5d22773-0b2f-4181-a478-ba1726b0003b","added_by":"auto","created_at":"2023-05-22 14:51:21","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":145810,"visible":true,"origin":"","legend":"\u003cp\u003eRelative rates of biopsy and radical prostatectomy specimen downgrading (blue bars), concordance (orange bars), and upgrading (gray bars) by systematic biopsy (SB), target biopsy (TB), and SB plus TB.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2916106/v1/68029133eb1a8ec876cbfed8.jpg"},{"id":38363387,"identity":"2a65c44d-31cd-4ce7-8be1-72864e3c02d4","added_by":"auto","created_at":"2023-06-12 00:55:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":399145,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2916106/v1/e092be70-c7d4-4156-a17a-afd60caa784e.pdf"}],"financialInterests":"","formattedTitle":"Assessment of the Accuracy of Biparametric MRI/TRUS Fusion-Guided Biopsy for Index Tumor Evaluation using Postoperative Pathology Specimens","fulltext":[{"header":"Introduction","content":"\u003cp\u003eProstate cancer (PCa) diagnosis is primarily based on prostate-specific antigen (PSA), imaging, and histology results. Based on this diagnostic information, a risk classification is established, and treatment is determined. However, issues such as image quality and biopsy sampling errors can lead to diagnostic inaccuracies. Especially in prostate cancer surgery, we often experience discrepancies between the preoperative evaluation and the radical prostatectomy specimen. Prostate cancer surgery, including nerve sparing and lymph node dissection, is planned based on preoperative assessments of lesion localization and grade using MRI images and biopsy results. However, there are cases in which preoperative assessments underestimate the extent of cancer, leading to positive margins in postoperative pathology, or overestimate it, resulting in missed opportunities for nerve-sparing [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMultiparametric MRI (mpMRI) is a widely used technique for prostate cancer diagnosis, surveillance, and staging [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Accurate tumor localization with mpMRI and fusion of MR and transrectal ultrasound (TRUS) images for biopsy may provide a more accurate preoperative evaluation [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. This technique, known as mpMRI/TRUS fusion-guided biopsy, has become increasingly common, and its accuracy has been validated in several studies using postoperative pathology specimens [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. However, mpMRI has limitations, including higher cost, longer examination time, and the use of gadolinium-based contrast agents. Our institution uses biparametric MRI (bpMRI), including the T2W and DW MRI series, for the diagnosis of prostate cancer. Several studies have shown that bpMRI provides similar results to mpMRI in detecting and localizing PCa [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, no studies have compared bpMRI with radical prostatectomy (RP) specimens.\u003c/p\u003e \u003cp\u003eIn the present study, we examined the accuracy of index tumor (IT) assessed preoperatively using bpMRI-TRUS fusion prostate biopsy with RP specimens.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003eThis study was approved by the Ethics Committee of Tottori University Faculty of Medicine, Yonago, Japan (approval number: 20A016), and was conducted in accordance with the ethical guidelines set by the government. As this study involved only medical data and did not involve direct patient contact, informed consent was waived by the ethics committee. The study details were disclosed on the website in advance to ensure transparency and adherence to ethical standards.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBetween July 2017 and December 2021, 69 patients who were diagnosed with prostate cancer through bpMRI/TRUS fusion-guided biopsy of lesions with Prostate Imaging Reporting \u0026amp; Data System (PI-RADS) category \u0026ge; 3 and underwent robot-assisted laparoscopic radical prostatectomy (RARP) at our institution were included.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMRI and registration analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll male patients underwent a 1.5T or 3T bpMRI. PI-RADS guidelines state that both 1.5 T and 3.0 T can provide adequate and reliable diagnostic examinations\u0026nbsp;[9]. MRI imaging conditions were in accordance with the PI-RADS\u0026nbsp;[9]. Prior to biopsy, all suspicious lesions found on prostate MRI were scored by a single board-certified radiologist with expertise in prostate imaging. If MRI was initially conducted and read by a third-party radiologist, a second reading was performed at our institution, and scoring was based on the PI-RADS guideline recommendations. Additionally, during the imaging evaluation, the radiologist was informed about patients\u0026rsquo; PSA levels, age, and other clinical information.\u003c/p\u003e\n\u003cp\u003ePreoperative IT localization, highest Gleason score (GS), and tumor diameter were examined in these patients. IT localization was determined by the radiologist using a sector map adapted from the European Consensus Conference and ESUR Prostate MRI Guidelines 2012 to PI-RADS v2\u0026nbsp;[10]. For this study, preoperative IT was defined as a positive target biopsy with a PI-RADS category \u0026ge; 3 and the largest lesion.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProstate biopsy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe TRINITYTM system (Koelis, La Tronche, France) was utilized for all biopsy procedures, with the patient under spinal epidural anesthesia in the lithotripsy position. Initially, we visualized three-dimensional (3D) volume data obtained from MRI and real-time TRUS images. Elastic image fusion was conducted by semi-automatically contouring the MRI image of the entire prostate and suspected lesions on 3D TRUS images. The biopsy procedure involved a two-core biopsy targeted to each suspicious lesion identified on MRI, followed by a 10\u0026ndash;14 core systematic biopsy (SB). If there were three or more MRI lesions, two MRI-targeted biopsies (TBs) were performed. In this case, one MRI-TB was conducted on the index lesion and another on the next suspected lesion. All biopsy cores were obtained by experienced urologists (T.S., S.R.).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSurgery and pathology for registration analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRobotic RP was performed on all patients, and the surgical specimens were fixed in 10% neutral-buffered formalin, embedded in paraffin blocks, and stained with hematoxylin and eosin. The inferior-most 5\u0026ndash;7-mm portion of the gland was defined as the apex of the prostate, while the superior-most 5\u0026ndash;7-mm portion of the gland was defined as the base of the prostate; the remainder was defined as the mid-gland. The apex and the base of the prostate were divided into 3\u0026ndash;5-mm sagittal sections and the mid-gland into 3\u0026ndash;5-mm horizontal sections. Pathologists at our institution obtained IT localization from pathology reports. In RP specimens, an IT lesion was defined as the lesion with extraprostatic extension or the largest volume. To assess concordance rates for pathology assessment, we utilized the revised prostate cancer grading system, Grade Group (GG), released by the International Society of Urologic Pathology (ISUP) in 2014\u0026nbsp;[11].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA t-test was used to evaluate the difference between MR-estimated IT diameter and histological-IT diameter. To assess agreement between biopsies and RP specimens in GG, as well as between cTstage and pTstage, we used weighted Kappa statistics (k). For all tests, P values\u0026lt;0.05, were considered statistically significant. Statistical analyses were conducted using SPSS Statistics software version 24.0 (SPSS Inc., ).\u003c/p\u003e"},{"header":"RESULT","content":"\n\u003ch3\u003ePatients\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e displays the patient characteristics before prostate biopsy. The mean age of the 69 patients with preoperative IT was 70 years (range: 45\u0026ndash;78 years). The median PSA was 8.68 ng/ml (range: 4.17\u0026ndash;19.28 ng/ml) and the median prostate volume was 26.4 ml (range: 14.0\u0026ndash;84.0 ml). The median waiting time from biopsy to surgery was 116 days (range: 467\u0026ndash;347). MRI was conducted at 3.0T and 1.5T in 55 and 14 patients, respectively. The PI-RADS rating of IT on pre-biopsy MRI evaluation was 3, 4, and 5 in 13 (26%), 28 (56%), and 9 patients (18%), respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge, median (range)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69 (45\u0026ndash;78)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePSA, ng/ml, median (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.68 (4.17\u0026ndash;19.50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eprostate volume, ml, median (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.4 (14.0\u0026ndash;84.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003emedian waiting time, day, median (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e122 (43\u0026ndash;347)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-operative IT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePI-RADS 3, n (%)\u003c/p\u003e \u003cp\u003ePI-RADS 4, n (%)\u003c/p\u003e \u003cp\u003ePI-RADS 5, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (24.6%)\u003c/p\u003e \u003cp\u003e39 (56.5%)\u003c/p\u003e \u003cp\u003e13 (18.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecT stage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecT2a, n (%)\u003c/p\u003e \u003cp\u003ecT2b, n (%)\u003c/p\u003e \u003cp\u003ecT2c, n (%)\u003c/p\u003e \u003cp\u003ecT3a, n (%)\u003c/p\u003e \u003cp\u003ecT3b, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (27.5%)\u003c/p\u003e \u003cp\u003e1 (1.4%)\u003c/p\u003e \u003cp\u003e28 (40.6%)\u003c/p\u003e \u003cp\u003e20 (29.0%)\u003c/p\u003e \u003cp\u003e1 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eAbbreviations: PSA, prostate-specific antigen\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAccuracy of MRI T-stage diagnosis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003epT2a\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003epT2b\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003epT2c\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003epT3a\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003epT3b\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003etotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecT2a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecT2b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecT2c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecT3a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecT3b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAccuracy of IT localization and radial margin (RM) positive rate\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConcordance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDiscordance\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocalization, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59(85.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(14.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRM+, n/all (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7/54(13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3/10(30%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eAbbreviation: RM, radial margin\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eAccuracy of bpMRI Tstage Diagnosis\u003c/h3\u003e\n\u003cp\u003eThe distribution of cTstage was as follows: T2a in 13 cases (26%), T2b in 1 case (2%), T2c in 22 cases (44%), T3a in 13 cases (26%), and T3b in 1 case (2%). The pTstage was T2a in 19 cases (26%), T2b in 1 case (2%), T2c in 22 cases (44%), T3a in 13 cases (26%), and T3b in 1 case (2%). Of the cTstage cases, 20 (30%) were underestimated, 15 (22%) were overestimated, and 34 (48%) were concordant, resulting in a weighted kappa coefficient of 0.236 (Table. 2).\u003c/p\u003e\n\u003ch3\u003eAccuracy of IT localization and size diagnosis\u003c/h3\u003e\n\u003cp\u003eThe agreement between the localization of IT assessed by bpMRI and biopsy with that in the RP specimen was 84% (Table. 3). The diagnostic accuracy of IT localization was not affected by the magnet strengths of the MRI (1.5T or 3.0T) (p\u0026thinsp;=\u0026thinsp;0.674). The mean diameter of IT assessed by bpMRI was 10.7 mm (range: 4\u0026ndash;24 mm), while that in the RP specimen was 16.3 mm (range: 4\u0026ndash;35 mm).\u003c/p\u003e\n\u003ch3\u003eGrade Group (GG) concordance between biopsy and RP specimens\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e present the GG concordance between systematic biopsy (SB), targeted biopsy (TB), SB\u0026thinsp;+\u0026thinsp;TB, and RP specimens.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePathology concordance of biopsy schemes and radical prostatectomy specimen final pathology Abbreviations: SB, Systematic biopsy; TB, Target biopsy; GG, Gleason grade\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eRadical prostatectomy specimens (GG)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ebiopsy specimens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSB (n\u0026thinsp;=\u0026thinsp;63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGG1 (n\u0026thinsp;=\u0026thinsp;8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGG2 (n\u0026thinsp;=\u0026thinsp;8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGG3 (n\u0026thinsp;=\u0026thinsp;14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGG4 (n\u0026thinsp;=\u0026thinsp;17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGG5 (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTB (n\u0026thinsp;=\u0026thinsp;69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGG1 (n\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGG2 (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGG3 (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGG4 (n\u0026thinsp;=\u0026thinsp;22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGG5 (n\u0026thinsp;=\u0026thinsp;14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSB\u0026thinsp;+\u0026thinsp;TB (n\u0026thinsp;=\u0026thinsp;69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGG1 (n\u0026thinsp;=\u0026thinsp;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGG2 (n\u0026thinsp;=\u0026thinsp;7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGG3 (n\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGG4 (n\u0026thinsp;=\u0026thinsp;23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGG5 (n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eGG concordance between SB and RP specimens was observed in 16 cases (16%), with 23 (37%) and 24 cases (38%) being underestimated and overestimated, respectively (weighted kappa coefficient: 0.169). Grade concordance between TB and RP specimens was found in 33 cases (48%), with 17 (24%) and 19 cases (28%) being underestimated and overestimated, respectively (weighted kappa coefficient: 0.424). Grade concordance between SB\u0026thinsp;+\u0026thinsp;TB and RP specimens was found in 28 cases (41%), with 9 (13%) and 32 cases (46%) being underestimated and overestimated, respectively (weighted kappa coefficient: 0.307).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn the diagnosis of prostate cancer, it is crucial to identify clinically significant prostate cancers that would benefit from treatment [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Several reports have suggested that MRI-TRUS fusion biopsy is superior in detecting clinically significant prostate cancer (csPCa) because it can accurately assess lesions noted on MRI [\u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. PI-RADS evaluation has become standard to interpret MRI and multiparametric MRI (mpMRI) is used, which combines anatomic T2W imaging with functional and physiologic assessment, including diffusion-weighted imaging (DWI) and its derivative apparent-diffusion coefficient (ADC) maps, dynamic contrast-enhanced (DCE) MRI [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. High detection rates of csPCa have been reported for PI-RADS category 4 and 5 lesions, making them suitable candidates for targeted biopsy. However, the detection rate of cancer in category 3 lesions varies from 5\u0026ndash;26%, depending on the report, and management of these lesions has not been established [\u003cspan additionalcitationids=\"CR19 CR20\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. At our institution, PI-RADS category\u0026thinsp;\u0026ge;\u0026thinsp;3 is the target for targeted biopsy.\u003c/p\u003e \u003cp\u003eDue to the growing demand for prostate diagnostics, it is imperative to address the long waiting time for mpMRI and the burden on radiologists [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Additionally, cost reduction is necessary where possible. To tackle these challenges, one potential solution is MRI without gadolinium-based contrast agents (bpMRI). Nonenhanced MRI can improve patient throughput by reducing examination time and the amount of MRI preparation required prior to the examination, including precautions regarding contrast media. Additionally, MRI protocols that do not require the injection of contrast agents are preferred by patients, which can reduce patient discomfort and side effects (e.g., hematoma, contrast extravasation, allergic reactions, nephrogenic systemic fibrosis in patients with impaired renal function, intracranial gadolinium deposition), while also reducing time in the scanner [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Most MRI studies of suspected cancer can also be identified using only T2-weighted MRI and DWI criteria, as can a significant proportion of large tumors and PI-RADS 4 lesions, especially those assigned to the PI-RADS 5 category. DCE-MRI can be useful in detecting small cancers that are less prominent or occult on T2-weighted images and DWI, or when DW images are affected by prostheses [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Local contrast enhancement increases the confidence of the reader and helps inexperienced readers find MRI-positive scans [\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. A UK-based study reported that the addition of DCE-MRI to T2W and DWI led to a significant increase in overall cost, approximately 70%, due to the inclusion of contrast media, syringes, scanner time, and reading times. However, the clinical benefit of this additional cost is not clear, and further research is needed to determine whether the added benefit justifies the extra expense [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Schoots et al. reported that the PI-RADS committee needs better quality data to make evidence-based recommendations for contrast-free MRI as an initial diagnostic approach to prostate cancer screening [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In this study, we examined the accuracy of bpMRI-TRUS fusion biopsy by evaluating postoperative pathology specimens. The reported sensitivity of mpMRI for detecting IT ranged from 75.9\u0026ndash;93.3% [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Baco et al. reported the accuracy of histologically confirmed IT detection with mpMRI-TRUS fusion biopsy as 95% (n\u0026thinsp;=\u0026thinsp;135), while Francesco et al. reported it as 82.2% (n\u0026thinsp;=\u0026thinsp;152) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In this study, which used bpMRI-TRUS fusion biopsy, the accuracy of IT assessment was 85.5% (59/69), which we considered to be comparable to previous mpMRI reports. Furthermore, Baco et al. reported that mpMRI-assessed IT underestimates tumor volume by 5.9% [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], and the maximum IT diameter assessed by bpMRI in our study was underestimated, with a mean of 10.9 mm on MRI and 18.5 mm on RP specimens (no figure). In the T stage, bpMRI and RP specimens were consistent in about half of the cases. Ct2a cases were upgraded to Ct2c in 13 of 19 cases, while Ct3a cases were downgraded to Ct2 in 14 of 20 cases. This finding suggests that RP specimens may reveal micro lesions that are undetectable on MRI, and that it can be challenging to evaluate micro extracapsular invasion. Ploussard et al. reported that the concordance rate of GS between TB alone and RP samples in mpMRI/TRUS fusion biopsy was 45.2% [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], which is similar to the 48.0% concordance rate for TB alone in this study. However, one difference is that the GS concordance rate between SB\u0026thinsp;+\u0026thinsp;TB and RP specimens was 41% in this study, whereas it was 51.7% in Ploussard et al. In this study, TB alone had the highest accuracy of GS concordance with the RP specimen, but the addition of SB reduced the preoperative underestimation from 24\u0026ndash;13%. Although the reason for this is unclear, the results suggest that bpMRI does not confer inferiority in GS evaluation, at least in the case of TB alone.\u003c/p\u003e \u003cp\u003eA limitation of this study is that the cohort included only patients who had PI-RADS category\u0026thinsp;\u0026ge;\u0026thinsp;3 lesions detected by bpMRI and who underwent radical prostatectomy. In addition, the quality of radiological interpretation and the technique of the biopsy physician was not verified, and therefore cannot be directly compared with previous reports. Nevertheless, our study provides insight into the usefulness and limitations of bpMRI in the era of increasing MRI/TRUS fusion biopsy in the future.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe diagnostic accuracy of bpMRI/TRUS fusion biopsy is not comparable to that of previous reports using mpMRI. Furthermore, the results suggest that bpMRI/TRUS fusion biopsy is useful in terms of saving time and cost. Further research is necessary to verify the cases in which there is no disadvantage in using bpMRI.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eI would like to thank the radiology and urology doctors who were involved in the preparation of the paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest Disclosure Statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflict of interest.\u003cbr\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMorizane S, Yumioka T, Makishima K, Tsounapi P, Iwamoto H, Hikita K, Honda M, Umekita Y, Takenaka A (2021) Impact of positive surgical margin status in predicting early biochemical recurrence after robot-assisted radical prostatectomy. Int J Clin Oncol 26(10):1961\u0026ndash;1967. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10147-021-01977-x\u003c/span\u003e\u003cspan address=\"10.1007/s10147-021-01977-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYumioka T, Honda M, Kimura Y, Yamaguchi N, Iwamoto H, Morizane S, Hikita K, Takenaka A (2018) Influence of multinerve-sparing, robot-assisted radical prostatectomy on the recovery of erection in Japanese patients. 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Urology 76(2):513e513\u0026ndash;513e518. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.urology.2010.03.037\u003c/span\u003e\u003cspan address=\"10.1016/j.urology.2010.03.037\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Prostate cancer, biparametric MRI, MRI/transrectal ultrasound fusion prostate biopsy","lastPublishedDoi":"10.21203/rs.3.rs-2916106/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2916106/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMultiparametric MRI (mpMRI) is widely used for prostate cancer diagnosis, surveillance, and staging; however, it has some limitations, including higher cost, longer examination time, and the use of gadolinium-based contrast agents. This study aimed to investigate the accuracy of index tumor (IT) assessed preoperatively using biparametric MRI (bpMRI)/transrectal ultrasound (TRUS) fusion prostate biopsy with radical prostatectomy (RP) specimens.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe included 69 patients diagnosed with prostate cancer through bpMRI/TRUS fusion-guided biopsy of lesions with Prostate Imaging Reporting \u0026amp; Data System (PI-RADS) category\u0026thinsp;\u0026ge;\u0026thinsp;3 and underwent robot-assisted laparoscopic radical prostatectomy (RARP) at our institution between July 2017 and December 2021. The localization of preoperative and postoperative IT, highest Gleason score (GS), and tumor diameter were examined in these patients.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe preoperative cT stage matched the postoperative pT stage in 34 cases (48%), while 20 cases (30%) were upstaged, and 15 cases (22%) were downstaged (Weighted Kappa\u0026thinsp;=\u0026thinsp;0.236). The preoperative and postoperative IT localization were consistent in 59 cases (85.5%). The concordance rate between Gleason groups in targeted biopsy and RP specimens was 48%, with an upgrade in 17 cases (24%) and a downgrade in 29 cases (28%) (Weighted Kappa\u0026thinsp;=\u0026thinsp;0.424). The IT maximum diameter and maximum cancer core length on biopsy were correlated with RP tumor maximum diameter (p\u0026thinsp;=\u0026thinsp;0.007, p\u0026thinsp;=\u0026thinsp;0.008).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIn conclusion, the diagnostic accuracy of bpMRI/TRUS fusion biopsy is comparable to that of previous reports using mpMRI. The findings suggest that bpMRI/TRUS fusion biopsy can be a cost-effective and time-saving alternative.\u003c/p\u003e","manuscriptTitle":"Assessment of the Accuracy of Biparametric MRI/TRUS Fusion-Guided Biopsy for Index Tumor Evaluation using Postoperative Pathology Specimens","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-05-22 14:51:16","doi":"10.21203/rs.3.rs-2916106/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"070d0c25-3ba1-44f6-9046-e3ea3013f67e","owner":[],"postedDate":"May 22nd, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-07-26T07:59:27+00:00","versionOfRecord":[],"versionCreatedAt":"2023-05-22 14:51:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2916106","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2916106","identity":"rs-2916106","version":["v1"]},"buildId":"-HB7Z8yhvgn0wM9Nzuekk","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}