Clinical study on the guidance of the time for the second positioning of radiotherapy for cervical cancer based on ADC values combined with tumor volume regression

Clinical study on the guidance of the time for the second positioning of radiotherapy for cervical cancer based on ADC values combined with tumor volume regression | 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 Clinical study on the guidance of the time for the second positioning of radiotherapy for cervical cancer based on ADC values combined with tumor volume regression yuqian ma, jiaxu yan, wenfei li, defeng liu, liyan cao, yu mao, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8697059/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 15 You are reading this latest preprint version Abstract Objective To explore the correlation between ADC value and tumor volume regression in concurrent chemo-radiotherapy for cervical cancer, and to investigate the feasibility of early secondary localization. Methods Retrospective analysis: 66 patients with locally advanced cervical cancer were collected. The correlations between clinical pathological factors and ADC-related parameters and tumor volume regression were analyzed. Nine patients with radiotherapy sensitivity were selected based on previous studies, and the volume and dosimeter differences of the target area and organs at risk were analyzed to explore the feasibility of early secondary localization. Results At the 20th radiotherapy session, the median tumor volume was significantly reduced compared to before treatment (4.33 cm³vs 27.55 cm³, P < 0.05), and the ADC value significantly increased (1.163×10 − ³mm²/s vs 0.860×10 − ³mm²/s, P 2.7 ng/ml, and hemoglobin ≥ 110 g/L were related factors for tumor volume regression (χ 2 = 15.64, 4.19, 4.364, P < 0.05); △ADC was an independent risk factor (OR = 9.751, P < 0.05), and the ROC curve showed that the optimal cutoff value of △ADC was 38.7%; The GTV volume of Plan1, Plan2, and Plan3 gradually decreased (F = 14.173, P < 0.05), the conformity index (CI) and homogeneity index (HI) of PTV significantly decreased (F = 10.75, 16.20, P < 0.05), and bladder V40 significantly increased (F = 17.932, P < 0.05). Conclusion △ADC can be used as an important indicator for predicting the sensitivity of cervical cancer to radiotherapy, and a cutoff value of 38.7% has clinical value. For patients with radiotherapy sensitivity (△ADC ≥ 38.7%), early secondary localization can improve the conformity and dose uniformity of the target area, reduce the bladder irradiated volume, and provide a new strategy for precise radiotherapy. Cervical cancer Apparent diffusion coefficient Radiotherapy Plan adjustment Secondary position Figures Figure 1 Highlights 1.Explored the multi-parameter combined imaging features for evaluating the early efficacy prediction index of tumor shrinkage, this study adopted the delta ADC as an independent predictor of the sensitivity to concurrent chemo-radiotherapy in cervical cancer, providing objective and quantitative imaging evidence for early clinical identification of radiotherapy-sensitive patients. 2.Explored a novel strategy of "individualized secondary localization" for precision radiotherapy, and for the first time, proposed the feasibility and advantages of secondary localization in advance for patients with radiotherapy sensitivity. 3.The integrated analysis of △ADC with tumor volume reduction, target area dosimeter parameters (CI, HI), and radiation dose/volume of at-risk organs provides personalized strategies for precision radiotherapy. 1. Introduction Cervical cancer is the fourth most common malignant tumor among women worldwide and the second most common malignant tumor among women in China. Most patients are diagnosed at locally advanced stage, and concurrent chemo-radiotherapy is the preferred treatment[ 1 – 3 ].Although Intensity-Modulated Radiation Therapy(IMRT) has become a standard treatment technique[ 4 ],cervical cancer is highly radiation-sensitive,so during radiotherapy, the tumor volume often shrinks significantly, rendering the original treatment plan inapplicable and necessitating repositioning and plan adjustment[ 5 ].However, the sensitivity of different patients to radiotherapy and chemotherapy is significantly different, and the optimal time for secondary localization is still uncertain.The apparent diffusion coefficient (ADC) in magnetic resonance diffusion-weighted imaging (DWI) quantifies the diffusion constraints of water molecules, indirectly reflecting changes in the tumor micro-environment, and holds potential for evaluating tumor treatment response[ 6 – 8 ].This study analyzed the correlation between ADC values and tumor volume shrinkage to identify radiotherapy-sensitive patients, and explored the feasibility of early secondary localization to optimize precision radiotherapy strategies for cervical cancer. 2. Materials and Methods 2.1 General Information Part I: This study enrolled 66 patients with locally advanced cervical cancer (age 23–77 years) from Qinhuangdao First Hospital between January 2022 and May 2024. Patients were categorized into two groups based on Tumor Volume Regression Rate (TVRR): a significant regression group (33 patients) and a non-significant regression group (33 patients). Inclusion criteria included: (1) Histopathologically confirmed cervical squamous cell carcinoma with FIGO staging IB3-IVA; (2) No prior radiotherapy, chemotherapy, or other anti-tumor treatments; (3) Complete clinical, pathological, and imaging data before and during treatment; (4) Capacity to sign informed consent and cooperate with examinations and treatment. Exclusion criteria were: (1) Concurrent presence of other malignancies or major systemic diseases; (2) Prolonged radiotherapy interruption or failure to complete concurrent radiotherapy and chemotherapy on schedule. Part II: Based on the findings from Part I, patients deemed sensitive to radiotherapy were screened between June and December 2024. The feasibility of advanced secondary localization was evaluated through volumetric and dosimeter analysis, with the same inclusion and exclusion criteria as Part I. 2.2 Method (1) Positioning and CT localization: Instruct the patient to empty the bladder and rectum one hour before positioning, then drink 500-800mL of water as needed to maintain bladder fullness. The patient lies supine during positioning, with a thermoplastic fixed film securing the position. The scanning range covers from the second lumbar vertebra to 3cm below the ischial tuberosity, using 5mm slice thickness. Preparations and procedures for repositioning follow the same protocol as the initial positioning. (2) Target delineation: According to ICRU Report No.83, delineate the GTV, CTV, PTV, and at-risk organs (bladder, rectum). (3) Radiotherapy protocol: All patients received 3D conformal intensity-modulated radiotherapy (IMRT) using 6 MV X-rays from linear accelerators, with a prescribed dose of 50Gy /25f, combined with cisplatin chemotherapy (30–40 mg/m², once weekly). (4) Simulation Plan Design: The initial radiotherapy plan for the patient is designated as Plan1. During the second CT localization scan (radiation session 15, P2), the target area and at-risk organs are delineated, and a new plan is formulated to continue the treatment. The transverse T2WI image from the 20th radiation session (P3) is uploaded to the TPS system, where the target area and at-risk organs are again delineated. The initial CT localization image (P1) is then fused with P2 and P3 in the TPS system. Plan1 is replicated onto P2 and P3 to generate simulation plans, which are subsequently designated as Plan2 and Plan3. (5) MRI-DWI examination and ADC measurement: The first group of patients underwent pelvic MRI + DWI scans 2 weeks before treatment and during the routine secondary localization (20th radiotherapy session), while the second group underwent these examinations at the 15th and 20th radiotherapy sessions, with diffusion sensitivity coefficient (b value) set at 0 and 1000 s/mm². An experienced radiologist performs image analysis and data measurement on the patient's imaging without knowledge of the clinical and pathological information of the tumor. The region of interest (ROI) is manually delineated along the tumor margins in three layers: the maximum cross-section and the upper and lower planes above and below the tumor. The ADC value of each ROI is measured, and the average ADC value across the three layers is recorded as the final result. The ROI should cover at least two-thirds of the tumor area and avoid areas with cystic changes, hemorrhage, or necrosis. The pre-treatment ADC value (ADC1) and the ADC value at the 20th dose of radiotherapy (ADC2) are measured separately, and the change in ADC (△ADC) is calculated. △ADC =(ADC2–ADC1)/ ADC1×100% 2.3 Observation Indicators ADC parameters: pre-treatment ADC value (ADC1), ADC value at the 20th dose of radiotherapy (ADC2), and △ADC. Clinical factors: age, FIGO stage, parametrial invasion, SCC-Ag (serum squamous cell carcinoma antigen), hemoglobin level, NLR (neutrophil-to-lymphocyte ratio), PLR (platelet-to-lymphocyte ratio), tumor volume before treatment (V1), and tumor volume at the 20th dose of radiotherapy (V2). Pathological factors: tumor differentiation degree. Target volume and risk organ volume: GTV, CTV, PTV, bladder, rectum. Dose parameters: D2 (approximate maximum dose), Dmean (mean dose), CI (conformity index), HI (dose uniformity index), and V40, V50 (percentages of volume receiving 40 and 50Gy of radiation). CI=VPTV,ref 2 /(VPTV×Vref). CI value closer to 1 indicates better conformality of the target region. HI=D5/D95. HI value closer to 1, the better the dose distribution uniformity of the target area. * VPTV,ref: Volume of the Planned Treatment Volume (PTV) enclosed by 95% of the prescribed dose *D5 and D95 represent the irradiation doses received by 5% and 95% of the target volume, respectively. 2.4 Statistical Analysis According to the data characteristics, the measurement data conform to the normal distribution with the mean±standard deviation, and the non-normal distribution with the median and quartile. The categorical data or grade data are expressed by the rate or the proportion. The changes in tumor volume and ADC values before and after treatment were analyzed using t-tests or non-parametric tests. The correlation between ADC1, ADC2, △ADC, and clinical/pathological factors with tumor volume reduction was assessed via chi-square tests. Binary Logistic regression was employed to identify independent risk factors affecting tumor volume reduction. The predictive power of tumor volume reduction was evaluated by constructing receiver operating characteristic (ROC) curves, with the optimal cutoff value determined and the area under the curve (AUC) calculated. The differences of target volume, volume of organs at risk and dose parameters between different treatment plans were analyzed by t-test / ANOVA or nonparametric test. SPSS27.0 software was used to analyze the data. 3. Conclusion 3.1Changes of Cervical Tumor Volume and ADC in Cervical Cancer Patients Undergoing Synchronous Chemo-radiotherapy At the 20th radiation therapy session, the median tumor volume in the cervix (cm 3 ) showed a statistically significant reduction from pre-treatment levels (4.33vs.27.55, z=-7.06, P < 0.05). The ADC value also increased markedly from baseline (1.163 ± 0.074vs.0.860 ± 0.071, t= -49.11, P < 0.05). The median TVRR (%) was calculated as 85.6 (76.5, 89.1), with a △ADC of (35.62 ± 7.04)%. 3.2 Single factor analysis of tumor volume shrinkage The results of single-factor analysis on ADC values, △ADC, and related clinical pathological factors in concurrent chemo-radiotherapy for cervical cancer showed that patients with △ADC ≥ 35.62%, baseline SCC-Ag > 2.7 ng/ml, and hemoglobin level ≥ 110 g/L had more significant tumor shrinkage, which was statistically significant (χ 2 = 15.64,4.19,4.364, P 0.05). △ADC ≥ 35.62%, baseline SCC-Ag > 2.7 ng/ml, and hemoglobin ≥ 110 g/L were associated with tumor shrinkage ( P < 0.05). See Table 1 . 3.3 Single-factor analysis and ROC curve of tumor volume shrinkage: The binary Logistic regression analysis with the single-factor results showed that △ADC was an independent risk factor for tumor volume reduction in concurrent chemo-radiotherapy for cervical cancer patients (OR = 9.751, P < 0.05). This indicates that patients with △ADC ≥ 35.62% had a 9.751 times higher probability of significant tumor shrinkage during concurrent chemo-radiotherapy compared to those with △ADC < 35.62%. See Table 2 . The ROC curve analysis demonstrated that the area under the curve (AUC) of △ADC was 0.842, with a 95% confidence interval ranging from 0.742 to 0.941 ( P < 0.05). The optimal cutoff value for △ADC was 38.7%, and a △ADC ≥ 38.7% indicated higher sensitivity to radiotherapy and chemotherapy in cervical tumors. The sensitivity and specificity values were 0.758 and 0.879, respectively, with a Youden Index of 0.637. See Fig. 1 . Table 1 Single factor analysis of the factors affecting tumor volume reduction in concurrent chemo-radiotherapy for cervical cancer variable Reduction of Tumor Volume N χ 2 P group with significant regression TVRR ≥ 85.6% The group with no significant regression TVRR0.86 13 16 29 ADC2 ≥ 1.163 18 13 31 1.521 1.218 <1.163 15 20 35 △ADC ≥ 35.62% 26 10 36 15.64 <0.05 56 years old 17 19 36 0.244 0.621 ≤ 56 years old 16 14 30 Paracapsular Infiltration Yes 20 22 42 0.262 0.609 No 13 11 24 Grade Low 22 14 36 3.885 0.125 Middle 8 13 21 High 3 6 9 Base line SCC-Ag >2.7ng/mL 25 17 42 4.190 0.041 ≤ 2.7ng/mL 8 16 24 Hemoglobin ≥ 110g/L 26 18 44 4.364 0.037 2.77 15 17 32 0.243 0.622 ≤ 2.77 18 16 34 PLR >161.55 17 16 33 0.061 0.806 ≤ 161.55 16 17 33 V1 ≥ 27.55cm3 16 17 33 0.061 0.806 <27.55cm3 17 16 33 0.061 0.806 Table 2 Logistic regression analysis of tumor volume shrinkage in concurrent chemo-radiotherapy Variable B price Standard error Wald P Exp(B) 95% confidence interval Superior limit Lower limit △ADC 2.277 0.612 13.849 <0.05 9.751 2.939 32.354 base line SCC-Ag 0.432 0.635 0.463 0.496 1.541 0.444 5.35 hemoglobin 1.221 0.656 3.462 0.063 3.391 0.937 12.278 3.4 Feasibility Analysis of Secondary Positioning 3.4.1 Differences in target volume and risked organ volume among different plans at various time points The volume of GTV, CTV, PTV and bladder volume decreased in all three groups, but the difference of GTV volume was statistically significant (F = 14.173, P < 0.05), while the volume of rectum had no obvious rule. 3.4.2 Differing Dose Parameters of Each Plan at Different Time Points In Groups 1, 2, and 3, the PTV dose (D2) and target conformity/dose uniformity showed significant reductions. While the difference in D2 between Plan2 and Plan3 was not statistically significant, all other parameters exhibited statistically significant inter-group differences (F = 8.93,10.75,16.20, P 0.05). See Table 4 . In the three treatment groups (Plan 1, 2, and 3), bladder dosimeter parameters D2, V40, and V50 showed significant increases. Notably, only V40 exhibited statistically significant differences among the groups (F = 17.932, P < 0.05). While D2 and V50 showed no statistically significant differences between Plan2 and Plan 3, all other groups demonstrated statistically significant differences (F = 12.761,4.39, P 0.05). See Table 5 . The rectal dosimeter parameters D2 and V40 showed significant increases in Groups 1, 2, and 3. While no statistically significant difference was observed between Groups 2 and 3, statistically significant differences were found among the other groups (F = 2.681,5.053, P 0.05). See Table 6 . Table 3 Differences in target volume and volume of at-risk organs between different plans Radiotherapy plan Target volume and volume of at-risk organs (cm3) across different plans GTV CTV PTV rectum bladder plan1 70.78 ± 25.41 661.28 ± 112.41 985.63 ± 73.81 44.63 ± 10.26 322.68 ± 90.34 plan2 30.99 ± 11.27 644.90 ± 124.19 981.33 ± 94.48 40.58 ± 17.12 285.91 ± 74.76 plan3 17.03 ± 7.69 632.08 ± 129.48 968.04 ± 64.67 46.31 ± 17.29 252.93 ± 58.40 Table 4 Differences in PTV Dosimeter Parameters Between Different Plans Radiotherapy plan PTV dosimeter parameters D2(Gy) Dmean(Gy) CI HI plan1 51.42 ± 0.31 50.00(50.00, 50.00) 0.952 ± 0.001 1.07(1.06, 1.11) plan2 49.95 ± 0.66 49.30(48.91, 50.34) 0.938 ± 0.013 1.12(1.09, 1.20) plan3 49.17 ± 0.70 49.21(49.06, 50.00) 0.924 ± 0.015 1.15(1.12, 1.22) Table 5 Differences in bladder Dosimeter parameters between different plans Radiotherapy plan Bladder Dosimeter parameters D2(Gy) Dmean(Gy) V40(%) V50(%) plan1 51.05 ± 0.25 40.42 ± 1.23 39.04 ± 2.10 22.79 ± 2.29 plan2 52.03 ± 0.57 41.45 ± 1.18 42.30 ± 1.68 25.30 ± 2.93 plan3 52.05 ± 0.55 42.11 ± 1.20 44.65 ± 2.18 27.16 ± 2.22 Table 6 Differences in rectal Dosimeter parameters between different plans Radiotherapy plan Rectal Dosimeter parameters D2(Gy) Dmean(Gy) V40(%) V50(%) plan1 50.14 ± 0.48 38.52 ± 2.29 35.98 ± 1.9 14.76 ± 2.09 plan2 51.07 ± 0.67 38.60 ± 3.15 37.30 ± 2.11 15.42 ± 1.80 plan3 51.41 ± 0.50 39.72 ± 3.60 38.00 ± 2.19 15.62 ± 1.93 Discussion In recent years, the incidence of cervical cancer has been increasing, and the patients are getting younger, which is a serious threat to women's health[ 9 ].Cervical cancer demonstrates high sensitivity to radiotherapy. Under continuous radiation therapy, the tumor undergoes significant shrinkage, which alters its relative position to surrounding organs. This change may reduce tumor localization control rates and increase the risk of OAR complications[ 10 ], necessitating a reevaluation of the radiotherapy plan[ 11 ].But every repositioning is bound to consume more medical resources and increase the medical costs of patients. Therefore, it is particularly important to explore the best time for repositioning. Pelvic MRI is a key diagnostic tool in cervical cancer management, playing a pivotal role in predicting treatment efficacy and assessing patient prognosis[ 12 ].MRI-DWI is a non-invasive imaging technique that utilizes magnetic resonance imaging to observe the microscopic diffusion of water molecules. The ADC value serves as a key metric for quantifying the extent of water molecule diffusion limitation, reflecting the diffusion capacity of water molecules over a given time and distance .In the treatment response of cervical cancer, early studies by numerous scholars indicated that pre-treatment ADC values have predictive value for the efficacy of concurrent chemo-radiotherapy [ 13 – 15 ]. In this study, although the ADC values before treatment in the group with significant tumor shrinkage were significantly lower than those in the group with no significant shrinkage, the univariate analysis results suggested no significant correlation between pre-treatment ADC values and tumor volume reduction, which is consistent with the results of Li et al[ 16 ].The contradictory findings are likely attributable to the complexity of microcirculatory perfusion, which significantly compromises the accuracy and consistency of the results. Therefore, treatment outcomes should not be predicted solely by pre-treatment ADC values, as these may be influenced by multiple factors, potentially introducing bias.However, ADC values show a marked increase during treatment. A retrospective study by Gu et al. [ 17 ]found that significant changes in tumor ADC values before and after treatment may indicate greater tumor sensitivity to therapy.This study also investigated the changes in ADC values during treatment and found that △ADC was also associated with tumor volume shrinkage and was an independent risk factor affecting tumor volume shrinkage. Furthermore, by plotting the ROC curve, △ADC showed strong predictive value for tumor volume shrinkage, indicating that △ADC could be used as an important indicator to distinguish tumor shrinkage sensitivity and provide important diagnostic basis for individualized treatment.[ 18 ] Based on the results of the first part, the second part of the study was conducted. By comparing the target volumes of Plan1, Plan2, and Plan3, it was found that the volumes of GTV, CTV, and PTV all decreased gradually, but only the GTV volume showed a significant difference.In patients with bladder and rectal cancer, the bladder volume typically decreases with cumulative radiation and chemotherapy doses, while the rectal volume shows similar changes without a clear pattern[ 19 ].However, studies [ 20 , 21 ] indicate that maintaining bladder volume consistency during radiotherapy is challenging. As the number of treatment sessions increases, patients' urinary retention capacity declines, which consequently elevates the dose received by the bladder. If the dose is increased, late adverse events such as rectal bleeding and cystitis may occur, which will affect the quality of life of the patient. Many patients with cervical cancer are young, so it is important to reposition in time to reduce the occurrence of late adverse events[ 22 ]. During radiotherapy, as the tumor shrinks, the target area and surrounding organs at risk may shift, increasing treatment risks and uncertainties. Stewart et al. [ 23 ] found that weekly adjustments to the radiation therapy plan for cervical cancer not only optimized the dose distribution of target areas, improving precision, but also effectively reduced the incidence of acute toxic side effects during treatment. Lebret et al. [ 24 ]conducted daily adaptive radiotherapy, acquired CBCT images, and analyzed the volumes and Dosimeter of the target area, bladder, and rectum. Their findings indicated that for patients undergoing non-adaptive radiotherapy, the treatment plan might require three or more adjustments to minimize radiation exposure to OARs. This aligns with our findings: For radiotherapy-sensitive patients, both 15 and 20 sessions of radiotherapy showed that repositioning could reduce radiation doses to target areas and adjacent organs. Notably, 15 re-positions outperformed 20, confirming the feasibility of early repositioning.This is consistent with the results of Wang et al. [ 25 ]: significant organ motion occurred after 15 treatments, manual adaptive planning improved dose coverage and reduced OAR dose, and adaptive strategies are highly recommended for patients with large masses or paracervical infiltration. Conclusion The ADC value of cervical cancer patients during concurrent chemo-radiotherapy was significantly increased compared with that before treatment, and the △ADC was an independent risk factor affecting tumor volume reduction. It was of great clinical value to predict the sensitivity of cervical cancer patients to chemo-radiotherapy with 38.7% as the boundary value. For patients with chemo-radiotherapy sensitive cervical cancer, early repositioning has certain value in improving the conformity of PTV target area, dose uniformity and reducing the irradiated volume of bladder. Early repositioning or multiple repositioning may be the precise treatment strategy for patients with chemo-radiotherapy sensitive. Declarations Consent to publish: All participants consent to participate and consent to publish. Funding Declaration: No funding was received for conducting this study. Ethics declarations: This retrospective cohort study was conducted at the First Hospital of Qinhuangdao from January 2022 and May 2024,The protocol was approved by the Institutional Review Board (IRB )Approval No. :2024YY081 and complied with the Declaration of Helsinki. Consent to participate: Not applicable Author Contribution We declare that this manuscript is original, has not been published before and isnot currently being considered for publication elsewhere.We confirm that the manuscript has been read and approved by all named authors and that thereare no other persons who satisfied the criteria for authorship but are not listed. We furtherconfirm that the order of authors listed in the manuscript has been approved by all of us.We understand that the Corresponding Author is the sole contact for the Editorial process.He/she is responsible for communicating with the other authors about progress, submissions ofrevisions and final approval of proofs.All authors as follows:Yuqian Ma: Conceptualization, Data Curation, Investigation,Methodology,Writing-Original Draft Writing-Review & Editing.Jiaxu Yan、Wenfei Li:Methodology,Supervision,Fomal Analysis.Liyan Cao、Defeng Liu :Data Curation. Investigation.Yu Mao:Supervision.Validation.Tao Gu、Lijie Liu(Corresponding Author):Conceptualization, Funding Acquisition.Resources, Supervision, Validation, Writing-Original Draft, Writing-Review &Editing. 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MRI guided online adaptive radiotherapy and the dosimetric impact of inter- and intrafractional motion in patients with cervical cancer. Clin Transl Radiat Oncol. 2025;50:100881. https://doi.org/10.1016/j.ctro.2024.100881 . Spampinato S, Fokdal LU, Pötter R, Haie-Meder C, Lindegaard JC, Schmid MP, et al. Risk factors and dose-effects for bladder fistula, bleeding and cystitis after radiotherapy with imaged-guided adaptive brachytherapy for cervical cancer: An EMBRACE analysis. Radiother Oncol J Eur Soc Ther Radiol Oncol. 2021;158:312–20. https://doi.org/10.1016/j.radonc.2021.01.019 . Soejima T. Radiation therapy of cancer in the adolescent and young adult (AYA) generation. Jpn J Radiol. 2023;41:1331–4. https://doi.org/10.1007/s11604-023-01461-8 . Stewart J, Lim K, Kelly V, Xie J, Brock KK, Moseley J, et al. Automated Weekly Replanning for Intensity-Modulated Radiotherapy of Cervix Cancer. Int J Radiat Oncol Biol Phys. 2010;78:350–8. https://doi.org/10.1016/j.ijrobp.2009.07.1699 . Lebret D, Lafond C, Leseur J, Barateau A, Chan Sock Line D, Peignaux K, et al. Prospective multi-institutional study of library‐based adaptive radiotherapy for cervical cancer: Evaluation of plan‐of‐the‐day selection and population analysis. J Appl Clin Med Phys. 2025;26:e70356. https://doi.org/10.1002/acm2.70356 . Wang Y-W, Chen M, Shen W-T, Xu H-P. The clinical practice and dosimetric outcome of the manual adaptive planning during definitive radiotherapy for cervical cancer. J Cancer Res Clin Oncol. 2024;150:280. https://doi.org/10.1007/s00432-024-05809-z . Additional Declarations No competing interests reported. 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Qinhuangdao","correspondingAuthor":false,"prefix":"","firstName":"jiaxu","middleName":"","lastName":"yan","suffix":""},{"id":600110462,"identity":"4139c4e9-6522-43e3-9be9-7301cbf63cdf","order_by":2,"name":"wenfei li","email":"","orcid":"","institution":"First Hospital of Qinhuangdao","correspondingAuthor":false,"prefix":"","firstName":"wenfei","middleName":"","lastName":"li","suffix":""},{"id":600110465,"identity":"6a1a16b7-dbbf-4b9a-8b95-af19b6b629c8","order_by":3,"name":"defeng liu","email":"","orcid":"","institution":"First Hospital of Qinhuangdao","correspondingAuthor":false,"prefix":"","firstName":"defeng","middleName":"","lastName":"liu","suffix":""},{"id":600110466,"identity":"00e445eb-9dae-4244-af91-5e5d672bbded","order_by":4,"name":"liyan cao","email":"","orcid":"","institution":"First Hospital of Qinhuangdao","correspondingAuthor":false,"prefix":"","firstName":"liyan","middleName":"","lastName":"cao","suffix":""},{"id":600110467,"identity":"32b2684e-696d-47ad-b6ce-40423ced6bae","order_by":5,"name":"yu mao","email":"","orcid":"","institution":"First Hospital of Qinhuangdao","correspondingAuthor":false,"prefix":"","firstName":"yu","middleName":"","lastName":"mao","suffix":""},{"id":600110468,"identity":"1e9c6374-cc26-4497-9870-ed3fe7677be2","order_by":6,"name":"lijie liu","email":"","orcid":"","institution":"First Hospital of Qinhuangdao","correspondingAuthor":false,"prefix":"","firstName":"lijie","middleName":"","lastName":"liu","suffix":""},{"id":600110469,"identity":"62033b27-77c0-4629-aba7-451aab7782ad","order_by":7,"name":"tao gu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAqklEQVRIiWNgGAWjYFAC/ocPPlRIyMkTr4ONh9lwxhkLY8MGErSwSfO2VSQyHCBWh3x87wFp3nkSCYwNzA8f3SBGi+ExvgTDudsk8tgZ2IyNc4jS0sZgkPB2m0QxYwPQhURrOcA7RyKx4QCxWuTZeAwbeRtI0WLAlpbMOOOYhLFhM7F+kW8+fPzHh5o6OXn25oePibPlAIzFTIxysC0NxKocBaNgFIyCkQsAo/gt6KFbHGkAAAAASUVORK5CYII=","orcid":"","institution":"First Hospital of Qinhuangdao","correspondingAuthor":true,"prefix":"","firstName":"tao","middleName":"","lastName":"gu","suffix":""}],"badges":[],"createdAt":"2026-01-26 06:23:40","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8697059/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8697059/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104167028,"identity":"66dcbc0c-91fd-4a74-ae77-fe9841547bfa","added_by":"auto","created_at":"2026-03-08 14:22:00","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":108708,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve of △ADC in assessing tumor volume reduction during concurrent chemo-radiotherapy for cervical cancer\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8697059/v1/16e2ce0b8f2f6d1f044a1f50.jpeg"},{"id":104403360,"identity":"6d87d605-e5a0-495a-a744-5770449ccb39","added_by":"auto","created_at":"2026-03-11 12:18:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1285410,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8697059/v1/e6953b57-cb12-4e16-93d6-c5c4024f8d33.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Clinical study on the guidance of the time for the second positioning of radiotherapy for cervical cancer based on ADC values combined with tumor volume regression","fulltext":[{"header":"Highlights","content":"\u003cp\u003e1.Explored the multi-parameter combined imaging features for evaluating the early efficacy prediction index of tumor shrinkage, this study adopted the delta ADC as an independent predictor of the sensitivity to concurrent chemo-radiotherapy in cervical cancer, providing objective and quantitative imaging evidence for early clinical identification of radiotherapy-sensitive patients.\u003c/p\u003e\u003cp\u003e 2.Explored a novel strategy of \"individualized secondary localization\" for precision radiotherapy, and for the first time, proposed the feasibility and advantages of secondary localization in advance for patients with radiotherapy sensitivity.\u003c/p\u003e\u003cp\u003e3.The integrated analysis of △ADC with tumor volume reduction, target area dosimeter parameters (CI, HI), and radiation dose/volume of at-risk organs provides personalized strategies for precision radiotherapy.\u003c/p\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eCervical cancer is the fourth most common malignant tumor among women worldwide and the second most common malignant tumor among women in China. Most patients are diagnosed at locally advanced stage, and concurrent chemo-radiotherapy is the preferred treatment[\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].Although Intensity-Modulated Radiation Therapy(IMRT) has become a standard treatment technique[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e],cervical cancer is highly radiation-sensitive,so during radiotherapy, the tumor volume often shrinks significantly, rendering the original treatment plan inapplicable and necessitating repositioning and plan adjustment[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].However, the sensitivity of different patients to radiotherapy and chemotherapy is significantly different, and the optimal time for secondary localization is still uncertain.The apparent diffusion coefficient (ADC) in magnetic resonance diffusion-weighted imaging (DWI) quantifies the diffusion constraints of water molecules, indirectly reflecting changes in the tumor micro-environment, and holds potential for evaluating tumor treatment response[\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].This study analyzed the correlation between ADC values and tumor volume shrinkage to identify radiotherapy-sensitive patients, and explored the feasibility of early secondary localization to optimize precision radiotherapy strategies for cervical cancer.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 General Information\u003c/h2\u003e \u003cp\u003e Part I: This study enrolled 66 patients with locally advanced cervical cancer (age 23\u0026ndash;77 years) from Qinhuangdao First Hospital between January 2022 and May 2024. Patients were categorized into two groups based on Tumor Volume Regression Rate (TVRR): a significant regression group (33 patients) and a non-significant regression group (33 patients). Inclusion criteria included: (1) Histopathologically confirmed cervical squamous cell carcinoma with FIGO staging IB3-IVA; (2) No prior radiotherapy, chemotherapy, or other anti-tumor treatments; (3) Complete clinical, pathological, and imaging data before and during treatment; (4) Capacity to sign informed consent and cooperate with examinations and treatment. Exclusion criteria were: (1) Concurrent presence of other malignancies or major systemic diseases; (2) Prolonged radiotherapy interruption or failure to complete concurrent radiotherapy and chemotherapy on schedule.\u003c/p\u003e \u003cp\u003ePart II: Based on the findings from Part I, patients deemed sensitive to radiotherapy were screened between June and December 2024. The feasibility of advanced secondary localization was evaluated through volumetric and dosimeter analysis, with the same inclusion and exclusion criteria as Part I.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Method\u003c/h2\u003e \u003cp\u003e(1) Positioning and CT localization: Instruct the patient to empty the bladder and rectum one hour before positioning, then drink 500-800mL of water as needed to maintain bladder fullness. The patient lies supine during positioning, with a thermoplastic fixed film securing the position. The scanning range covers from the second lumbar vertebra to 3cm below the ischial tuberosity, using 5mm slice thickness. Preparations and procedures for repositioning follow the same protocol as the initial positioning.\u003c/p\u003e \u003cp\u003e(2) Target delineation: According to ICRU Report No.83, delineate the GTV, CTV, PTV, and at-risk organs (bladder, rectum).\u003c/p\u003e \u003cp\u003e(3) Radiotherapy protocol: All patients received 3D conformal intensity-modulated radiotherapy (IMRT) using 6 MV X-rays from linear accelerators, with a prescribed dose of 50Gy /25f, combined with cisplatin chemotherapy (30\u0026ndash;40 mg/m\u0026sup2;, once weekly).\u003c/p\u003e \u003cp\u003e(4) Simulation Plan Design: The initial radiotherapy plan for the patient is designated as Plan1. During the second CT localization scan (radiation session 15, P2), the target area and at-risk organs are delineated, and a new plan is formulated to continue the treatment. The transverse T2WI image from the 20th radiation session (P3) is uploaded to the TPS system, where the target area and at-risk organs are again delineated. The initial CT localization image (P1) is then fused with P2 and P3 in the TPS system. Plan1 is replicated onto P2 and P3 to generate simulation plans, which are subsequently designated as Plan2 and Plan3.\u003c/p\u003e \u003cp\u003e(5) MRI-DWI examination and ADC measurement: The first group of patients underwent pelvic MRI\u0026thinsp;+\u0026thinsp;DWI scans 2 weeks before treatment and during the routine secondary localization (20th radiotherapy session), while the second group underwent these examinations at the 15th and 20th radiotherapy sessions, with diffusion sensitivity coefficient (b value) set at 0 and 1000 s/mm\u0026sup2;.\u003c/p\u003e \u003cp\u003eAn experienced radiologist performs image analysis and data measurement on the patient's imaging without knowledge of the clinical and pathological information of the tumor. The region of interest (ROI) is manually delineated along the tumor margins in three layers: the maximum cross-section and the upper and lower planes above and below the tumor. The ADC value of each ROI is measured, and the average ADC value across the three layers is recorded as the final result. The ROI should cover at least two-thirds of the tumor area and avoid areas with cystic changes, hemorrhage, or necrosis. The pre-treatment ADC value (ADC1) and the ADC value at the 20th dose of radiotherapy (ADC2) are measured separately, and the change in ADC (△ADC) is calculated.\u003c/p\u003e \u003cp\u003e△ADC =(ADC2\u0026ndash;ADC1)/ ADC1\u0026times;100%\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Observation Indicators\u003c/h2\u003e \u003cp\u003eADC parameters: pre-treatment ADC value (ADC1), ADC value at the 20th dose of radiotherapy (ADC2), and △ADC.\u003c/p\u003e \u003cp\u003eClinical factors: age, FIGO stage, parametrial invasion, SCC-Ag (serum squamous cell carcinoma antigen), hemoglobin level, NLR (neutrophil-to-lymphocyte ratio), PLR (platelet-to-lymphocyte ratio), tumor volume before treatment (V1), and tumor volume at the 20th dose of radiotherapy (V2).\u003c/p\u003e \u003cp\u003ePathological factors: tumor differentiation degree.\u003c/p\u003e \u003cp\u003eTarget volume and risk organ volume: GTV, CTV, PTV, bladder, rectum.\u003c/p\u003e \u003cp\u003eDose parameters: D2 (approximate maximum dose), Dmean (mean dose), CI (conformity index), HI (dose uniformity index), and V40, V50 (percentages of volume receiving 40 and 50Gy of radiation).\u003c/p\u003e \u003cp\u003eCI=VPTV,ref\u003csup\u003e2\u003c/sup\u003e/(VPTV\u0026times;Vref). CI value closer to 1 indicates better conformality of the target region.\u003c/p\u003e \u003cp\u003eHI=D5/D95. HI value closer to 1, the better the dose distribution uniformity of the target area.\u003c/p\u003e \u003cp\u003e* VPTV,ref: Volume of the Planned Treatment Volume (PTV) enclosed by 95% of the prescribed dose\u003c/p\u003e \u003cp\u003e*D5 and D95 represent the irradiation doses received by 5% and 95% of the target volume, respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Statistical Analysis\u003c/h2\u003e \u003cp\u003eAccording to the data characteristics, the measurement data conform to the normal distribution with the mean\u0026plusmn;standard deviation, and the non-normal distribution with the median and quartile. The categorical data or grade data are expressed by the rate or the proportion.\u003c/p\u003e \u003cp\u003eThe changes in tumor volume and ADC values before and after treatment were analyzed using t-tests or non-parametric tests. The correlation between ADC1, ADC2, △ADC, and clinical/pathological factors with tumor volume reduction was assessed via chi-square tests. Binary Logistic regression was employed to identify independent risk factors affecting tumor volume reduction. The predictive power of tumor volume reduction was evaluated by constructing receiver operating characteristic (ROC) curves, with the optimal cutoff value determined and the area under the curve (AUC) calculated.\u003c/p\u003e \u003cp\u003eThe differences of target volume, volume of organs at risk and dose parameters between different treatment plans were analyzed by t-test / ANOVA or nonparametric test.\u003c/p\u003e \u003cp\u003eSPSS27.0 software was used to analyze the data.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Conclusion","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1Changes of Cervical Tumor Volume and ADC in Cervical Cancer Patients Undergoing Synchronous Chemo-radiotherapy\u003c/h2\u003e \u003cp\u003eAt the 20th radiation therapy session, the median tumor volume in the cervix (cm\u003csup\u003e3\u003c/sup\u003e) showed a statistically significant reduction from pre-treatment levels (4.33vs.27.55, z=-7.06, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The ADC value also increased markedly from baseline (1.163\u0026thinsp;\u0026plusmn;\u0026thinsp;0.074vs.0.860\u0026thinsp;\u0026plusmn;\u0026thinsp;0.071, t= -49.11, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The median TVRR (%) was calculated as 85.6 (76.5, 89.1), with a △ADC of (35.62\u0026thinsp;\u0026plusmn;\u0026thinsp;7.04)%.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Single factor analysis of tumor volume shrinkage\u003c/h2\u003e \u003cp\u003eThe results of single-factor analysis on ADC values, △ADC, and related clinical pathological factors in concurrent chemo-radiotherapy for cervical cancer showed that patients with △ADC\u0026thinsp;\u0026ge;\u0026thinsp;35.62%, baseline SCC-Ag\u0026thinsp;\u0026gt;\u0026thinsp;2.7 ng/ml, and hemoglobin level\u0026thinsp;\u0026ge;\u0026thinsp;110 g/L had more significant tumor shrinkage, which was statistically significant (χ\u003csup\u003e 2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;15.64,4.19,4.364,\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). However, age, paracervical invasion, differentiation degree, baseline NLR, PLR, pre-treatment cervical tumor volume (V1), ADC1, and ADC2 were not associated with tumor shrinkage (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). △ADC\u0026thinsp;\u0026ge;\u0026thinsp;35.62%, baseline SCC-Ag\u0026thinsp;\u0026gt;\u0026thinsp;2.7 ng/ml, and hemoglobin\u0026thinsp;\u0026ge;\u0026thinsp;110 g/L were associated with tumor shrinkage (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). See Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Single-factor analysis and ROC curve of tumor volume shrinkage:\u003c/h2\u003e \u003cp\u003eThe binary Logistic regression analysis with the single-factor results showed that △ADC was an independent risk factor for tumor volume reduction in concurrent chemo-radiotherapy for cervical cancer patients (OR\u0026thinsp;=\u0026thinsp;9.751, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This indicates that patients with △ADC\u0026thinsp;\u0026ge;\u0026thinsp;35.62% had a 9.751 times higher probability of significant tumor shrinkage during concurrent chemo-radiotherapy compared to those with △ADC\u0026thinsp;\u0026lt;\u0026thinsp;35.62%. See Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe ROC curve analysis demonstrated that the area under the curve (AUC) of △ADC was 0.842, with a 95% confidence interval ranging from 0.742 to 0.941 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The optimal cutoff value for △ADC was 38.7%, and a △ADC\u0026thinsp;\u0026ge;\u0026thinsp;38.7% indicated higher sensitivity to radiotherapy and chemotherapy in cervical tumors. The sensitivity and specificity values were 0.758 and 0.879, respectively, with a Youden Index of 0.637. See Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\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\u003eSingle factor analysis of the factors affecting tumor volume reduction in concurrent chemo-radiotherapy for cervical cancer\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\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003evariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eReduction of Tumor Volume\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eχ 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003egroup with significant regression\u003c/p\u003e \u003cp\u003eTVRR\u0026thinsp;\u0026ge;\u0026thinsp;85.6%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe group with no significant regression\u003c/p\u003e \u003cp\u003eTVRR\u0026lt;85.6%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADC1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.457\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADC2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;1.163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.521\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.218\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;1.163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e△ADC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;35.62%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e15.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;35.62%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\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\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;56 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17\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\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.621\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;56 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParacapsular Infiltration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.609\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\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\u003e24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e3.885\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\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\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBase line SCC-Ag\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;2.7ng/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4.190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;2.7ng/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;110g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4.364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;110g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;2.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.622\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;2.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;161.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.806\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;161.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;27.55cm3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.806\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;27.55cm3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.806\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=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic regression analysis of tumor volume shrinkage in concurrent chemo-radiotherapy\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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 \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eB price\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStandard error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWald\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eExp(B)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e95% confidence interval\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSuperior limit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLower limit\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e△ADC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.939\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e32.354\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ebase line SCC-Ag\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.463\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.496\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.444\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehemoglobin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.656\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.937\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e12.278\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 \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Feasibility Analysis of Secondary Positioning\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e3.4.1 Differences in target volume and risked organ volume among different plans at various time points\u003c/h2\u003e \u003cp\u003eThe volume of GTV, CTV, PTV and bladder volume decreased in all three groups, but the difference of GTV volume was statistically significant (F\u0026thinsp;=\u0026thinsp;14.173, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while the volume of rectum had no obvious rule.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e3.4.2 Differing Dose Parameters of Each Plan at Different Time Points\u003c/h2\u003e \u003cp\u003eIn Groups 1, 2, and 3, the PTV dose (D2) and target conformity/dose uniformity showed significant reductions. While the difference in D2 between Plan2 and Plan3 was not statistically significant, all other parameters exhibited statistically significant inter-group differences (F\u0026thinsp;=\u0026thinsp;8.93,10.75,16.20, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Although Dmean showed a decreasing trend, the difference was not statistically significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). See Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eIn the three treatment groups (Plan 1, 2, and 3), bladder dosimeter parameters D2, V40, and V50 showed significant increases. Notably, only V40 exhibited statistically significant differences among the groups (F\u0026thinsp;=\u0026thinsp;17.932, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). While D2 and V50 showed no statistically significant differences between Plan2 and Plan 3, all other groups demonstrated statistically significant differences (F\u0026thinsp;=\u0026thinsp;12.761,4.39, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Although Dmean showed an upward trend, the difference was not statistically significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). See Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe rectal dosimeter parameters D2 and V40 showed significant increases in Groups 1, 2, and 3. While no statistically significant difference was observed between Groups 2 and 3, statistically significant differences were found among the other groups (F\u0026thinsp;=\u0026thinsp;2.681,5.053, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Although Dmean and V50 exhibited an upward trend, the differences were not statistically significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). See Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\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\u003eDifferences in target volume and volume of at-risk organs between different plans\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=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRadiotherapy plan\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eTarget volume and volume of at-risk organs (cm3) across different plans\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGTV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePTV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003erectum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ebladder\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eplan1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e70.78\u0026thinsp;\u0026plusmn;\u0026thinsp;25.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e661.28\u0026thinsp;\u0026plusmn;\u0026thinsp;112.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e985.63\u0026thinsp;\u0026plusmn;\u0026thinsp;73.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e44.63\u0026thinsp;\u0026plusmn;\u0026thinsp;10.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e322.68\u0026thinsp;\u0026plusmn;\u0026thinsp;90.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eplan2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e30.99\u0026thinsp;\u0026plusmn;\u0026thinsp;11.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e644.90\u0026thinsp;\u0026plusmn;\u0026thinsp;124.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e981.33\u0026thinsp;\u0026plusmn;\u0026thinsp;94.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e40.58\u0026thinsp;\u0026plusmn;\u0026thinsp;17.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e285.91\u0026thinsp;\u0026plusmn;\u0026thinsp;74.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eplan3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e17.03\u0026thinsp;\u0026plusmn;\u0026thinsp;7.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e632.08\u0026thinsp;\u0026plusmn;\u0026thinsp;129.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e968.04\u0026thinsp;\u0026plusmn;\u0026thinsp;64.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e46.31\u0026thinsp;\u0026plusmn;\u0026thinsp;17.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e252.93\u0026thinsp;\u0026plusmn;\u0026thinsp;58.40\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=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDifferences in PTV Dosimeter Parameters Between Different Plans\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" 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=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRadiotherapy plan\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003ePTV dosimeter parameters\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD2(Gy)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDmean(Gy)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eplan1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e51.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.00(50.00, 50.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.952\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.07(1.06, 1.11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eplan2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e49.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49.30(48.91, 50.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.938\u0026thinsp;\u0026plusmn;\u0026thinsp;0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.12(1.09, 1.20)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eplan3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e49.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49.21(49.06, 50.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.924\u0026thinsp;\u0026plusmn;\u0026thinsp;0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.15(1.12, 1.22)\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=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDifferences in bladder Dosimeter parameters between different plans\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRadiotherapy plan\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eBladder Dosimeter parameters\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD2(Gy)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDmean(Gy)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eV40(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eV50(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eplan1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e51.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e40.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e39.04\u0026thinsp;\u0026plusmn;\u0026thinsp;2.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e22.79\u0026thinsp;\u0026plusmn;\u0026thinsp;2.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eplan2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e52.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e41.45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e42.30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e25.30\u0026thinsp;\u0026plusmn;\u0026thinsp;2.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eplan3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e52.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e42.11\u0026thinsp;\u0026plusmn;\u0026thinsp;1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e44.65\u0026thinsp;\u0026plusmn;\u0026thinsp;2.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e27.16\u0026thinsp;\u0026plusmn;\u0026thinsp;2.22\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=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDifferences in rectal Dosimeter parameters between different plans\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRadiotherapy plan\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eRectal Dosimeter parameters\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD2(Gy)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDmean(Gy)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eV40(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eV50(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eplan1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e50.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e38.52\u0026thinsp;\u0026plusmn;\u0026thinsp;2.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e35.98\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e14.76\u0026thinsp;\u0026plusmn;\u0026thinsp;2.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eplan2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e51.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e38.60\u0026thinsp;\u0026plusmn;\u0026thinsp;3.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e37.30\u0026thinsp;\u0026plusmn;\u0026thinsp;2.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e15.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eplan3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e51.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e39.72\u0026thinsp;\u0026plusmn;\u0026thinsp;3.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e38.00\u0026thinsp;\u0026plusmn;\u0026thinsp;2.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e15.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn recent years, the incidence of cervical cancer has been increasing, and the patients are getting younger, which is a serious threat to women's health[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].Cervical cancer demonstrates high sensitivity to radiotherapy. Under continuous radiation therapy, the tumor undergoes significant shrinkage, which alters its relative position to surrounding organs. This change may reduce tumor localization control rates and increase the risk of OAR complications[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], necessitating a reevaluation of the radiotherapy plan[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].But every repositioning is bound to consume more medical resources and increase the medical costs of patients. Therefore, it is particularly important to explore the best time for repositioning.\u003c/p\u003e \u003cp\u003ePelvic MRI is a key diagnostic tool in cervical cancer management, playing a pivotal role in predicting treatment efficacy and assessing patient prognosis[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].MRI-DWI is a non-invasive imaging technique that utilizes magnetic resonance imaging to observe the microscopic diffusion of water molecules. The ADC value serves as a key metric for quantifying the extent of water molecule diffusion limitation, reflecting the diffusion capacity of water molecules over a given time and distance .In the treatment response of cervical cancer, early studies by numerous scholars indicated that pre-treatment ADC values have predictive value for the efficacy of concurrent chemo-radiotherapy [\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In this study, although the ADC values before treatment in the group with significant tumor shrinkage were significantly lower than those in the group with no significant shrinkage, the univariate analysis results suggested no significant correlation between pre-treatment ADC values and tumor volume reduction, which is consistent with the results of Li et al[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].The contradictory findings are likely attributable to the complexity of microcirculatory perfusion, which significantly compromises the accuracy and consistency of the results. Therefore, treatment outcomes should not be predicted solely by pre-treatment ADC values, as these may be influenced by multiple factors, potentially introducing bias.However, ADC values show a marked increase during treatment. A retrospective study by Gu et al. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]found that significant changes in tumor ADC values before and after treatment may indicate greater tumor sensitivity to therapy.This study also investigated the changes in ADC values during treatment and found that △ADC was also associated with tumor volume shrinkage and was an independent risk factor affecting tumor volume shrinkage. Furthermore, by plotting the ROC curve, △ADC showed strong predictive value for tumor volume shrinkage, indicating that △ADC could be used as an important indicator to distinguish tumor shrinkage sensitivity and provide important diagnostic basis for individualized treatment.[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eBased on the results of the first part, the second part of the study was conducted. By comparing the target volumes of Plan1, Plan2, and Plan3, it was found that the volumes of GTV, CTV, and PTV all decreased gradually, but only the GTV volume showed a significant difference.In patients with bladder and rectal cancer, the bladder volume typically decreases with cumulative radiation and chemotherapy doses, while the rectal volume shows similar changes without a clear pattern[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].However, studies [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] indicate that maintaining bladder volume consistency during radiotherapy is challenging. As the number of treatment sessions increases, patients' urinary retention capacity declines, which consequently elevates the dose received by the bladder. If the dose is increased, late adverse events such as rectal bleeding and cystitis may occur, which will affect the quality of life of the patient. Many patients with cervical cancer are young, so it is important to reposition in time to reduce the occurrence of late adverse events[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDuring radiotherapy, as the tumor shrinks, the target area and surrounding organs at risk may shift, increasing treatment risks and uncertainties. Stewart et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] found that weekly adjustments to the radiation therapy plan for cervical cancer not only optimized the dose distribution of target areas, improving precision, but also effectively reduced the incidence of acute toxic side effects during treatment. Lebret et al. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]conducted daily adaptive radiotherapy, acquired CBCT images, and analyzed the volumes and Dosimeter of the target area, bladder, and rectum. Their findings indicated that for patients undergoing non-adaptive radiotherapy, the treatment plan might require three or more adjustments to minimize radiation exposure to OARs. This aligns with our findings: For radiotherapy-sensitive patients, both 15 and 20 sessions of radiotherapy showed that repositioning could reduce radiation doses to target areas and adjacent organs. Notably, 15 re-positions outperformed 20, confirming the feasibility of early repositioning.This is consistent with the results of Wang et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]: significant organ motion occurred after 15 treatments, manual adaptive planning improved dose coverage and reduced OAR dose, and adaptive strategies are highly recommended for patients with large masses or paracervical infiltration.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe ADC value of cervical cancer patients during concurrent chemo-radiotherapy was significantly increased compared with that before treatment, and the △ADC was an independent risk factor affecting tumor volume reduction. It was of great clinical value to predict the sensitivity of cervical cancer patients to chemo-radiotherapy with 38.7% as the boundary value.\u003c/p\u003e \u003cp\u003eFor patients with chemo-radiotherapy sensitive cervical cancer, early repositioning has certain value in improving the conformity of PTV target area, dose uniformity and reducing the irradiated volume of bladder. Early repositioning or multiple repositioning may be the precise treatment strategy for patients with chemo-radiotherapy sensitive.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eConsent to publish:\u003c/strong\u003e \u003cp\u003e All participants consent to participate and consent to publish.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eFunding Declaration: No funding was received for conducting this study.\u003c/p\u003e \u003cp\u003eEthics declarations: This retrospective cohort study was conducted at the First Hospital of Qinhuangdao from January 2022 and May 2024,The protocol was approved by the Institutional Review Board (IRB )Approval No. :2024YY081 and complied with the Declaration of Helsinki.\u003c/p\u003e\u003cp\u003e \u003ch2\u003eConsent to participate:\u003c/h2\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eWe declare that this manuscript is original, has not been published before and isnot currently being considered for publication elsewhere.We confirm that the manuscript has been read and approved by all named authors and that thereare no other persons who satisfied the criteria for authorship but are not listed. We furtherconfirm that the order of authors listed in the manuscript has been approved by all of us.We understand that the Corresponding Author is the sole contact for the Editorial process.He/she is responsible for communicating with the other authors about progress, submissions ofrevisions and final approval of proofs.All authors as follows:Yuqian Ma: Conceptualization, Data Curation, Investigation,Methodology,Writing-Original Draft Writing-Review \u0026amp; Editing.Jiaxu Yan、Wenfei Li:Methodology,Supervision,Fomal Analysis.Liyan Cao、Defeng Liu :Data Curation. Investigation.Yu Mao:Supervision.Validation.Tao Gu、Lijie Liu(Corresponding Author):Conceptualization, Funding Acquisition.Resources, Supervision, Validation, Writing-Original Draft, Writing-Review \u0026amp;Editing.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and analysed during the current study are not publicly available due to the lack of informed consent from the participants, but are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. 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J Cancer Res Clin Oncol. 2024;150:280. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00432-024-05809-z\u003c/span\u003e\u003cspan address=\"10.1007/s00432-024-05809-z\" 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":false,"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":"discover-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dion","sideBox":"Learn more about [Discover Oncology](https://www.springer.com/12672)","snPcode":"","submissionUrl":"","title":"Discover Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Cervical cancer, Apparent diffusion coefficient, Radiotherapy, Plan adjustment, Secondary position","lastPublishedDoi":"10.21203/rs.3.rs-8697059/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8697059/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo explore the correlation between ADC value and tumor volume regression in concurrent chemo-radiotherapy for cervical cancer, and to investigate the feasibility of early secondary localization.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eRetrospective analysis: 66 patients with locally advanced cervical cancer were collected. The correlations between clinical pathological factors and ADC-related parameters and tumor volume regression were analyzed. Nine patients with radiotherapy sensitivity were selected based on previous studies, and the volume and dosimeter differences of the target area and organs at risk were analyzed to explore the feasibility of early secondary localization.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAt the 20th radiotherapy session, the median tumor volume was significantly reduced compared to before treatment (4.33 cm\u0026sup3;vs 27.55 cm\u0026sup3;, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and the ADC value significantly increased (1.163\u0026times;10\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup3;mm\u0026sup2;/s vs 0.860\u0026times;10\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup3;mm\u0026sup2;/s, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The TVRR was 85.6%, and △ADC was 35.62%\u0026plusmn;7.04%; △ADC\u0026thinsp;\u0026ge;\u0026thinsp;35.62%, baseline SCC-Ag\u0026thinsp;\u0026gt;\u0026thinsp;2.7 ng/ml, and hemoglobin\u0026thinsp;\u0026ge;\u0026thinsp;110 g/L were related factors for tumor volume regression (χ\u003csup\u003e 2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;15.64, 4.19, 4.364, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05); △ADC was an independent risk factor (OR\u0026thinsp;=\u0026thinsp;9.751, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and the ROC curve showed that the optimal cutoff value of △ADC was 38.7%; The GTV volume of Plan1, Plan2, and Plan3 gradually decreased (F\u0026thinsp;=\u0026thinsp;14.173, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), the conformity index (CI) and homogeneity index (HI) of PTV significantly decreased (F\u0026thinsp;=\u0026thinsp;10.75, 16.20, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and bladder V40 significantly increased (F\u0026thinsp;=\u0026thinsp;17.932, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003e△ADC can be used as an important indicator for predicting the sensitivity of cervical cancer to radiotherapy, and a cutoff value of 38.7% has clinical value. For patients with radiotherapy sensitivity (△ADC\u0026thinsp;\u0026ge;\u0026thinsp;38.7%), early secondary localization can improve the conformity and dose uniformity of the target area, reduce the bladder irradiated volume, and provide a new strategy for precise radiotherapy.\u003c/p\u003e","manuscriptTitle":"Clinical study on the guidance of the time for the second positioning of radiotherapy for cervical cancer based on ADC values combined with tumor volume regression","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-08 14:21:55","doi":"10.21203/rs.3.rs-8697059/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-12T06:28:40+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-01T22:44:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-01T17:28:44+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-01T08:29:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"107279343846567798580267985589416208747","date":"2026-02-27T11:23:04+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-24T17:19:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"279139893887526827990783282992165432534","date":"2026-02-24T10:35:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"301643796259394781446611084288664810380","date":"2026-02-23T22:52:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"86473746300725938313541676480031001815","date":"2026-02-21T16:46:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"211602614727140800998419555757702803830","date":"2026-02-18T16:22:22+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-18T07:28:40+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-11T12:07:49+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-10T13:27:19+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-02T13:55:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Oncology","date":"2026-02-02T13:30:16+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dion","sideBox":"Learn more about [Discover Oncology](https://www.springer.com/12672)","snPcode":"","submissionUrl":"","title":"Discover Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"144865cf-ebee-4ecd-90be-aa75d81d81c7","owner":[],"postedDate":"March 8th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-13T03:38:46+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-08 14:21:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8697059","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8697059","identity":"rs-8697059","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}