An Observational Retrospective Study to See the Accuracy of Post-Neoadjuvant Radiotherapy MRI Staging in Cases of Rectal Cancers

An Observational Retrospective Study to See the Accuracy of Post-Neoadjuvant Radiotherapy MRI Staging in Cases of Rectal Cancers | 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 An Observational Retrospective Study to See the Accuracy of Post-Neoadjuvant Radiotherapy MRI Staging in Cases of Rectal Cancers Dr Gopal Goyal, Dr Manoj Mulchandani, Dr Yukta Malani This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7691356/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Accurate restaging of rectal cancer following neoadjuvant radiotherapy (NART) is critical for determining appropriate surgical intervention. Magnetic resonance imaging (MRI) is widely used for this purpose, although its accuracy post-radiation is debated due to treatment-induced tissue changes. This is among the few Indian study validating MRI accuracy in post-NART rectal cancer staging. Aim To evaluate the diagnostic accuracy of MRI in restaging rectal cancer (T and N staging) post-NART by comparing it with postoperative histopathology. Methods This retrospective observational study included 28 patients treated with NART for rectal cancer between January 2020 and December 2024. MRI staging (6–8 weeks post-NART) was compared with final histopathology. T staging was dichotomized (T0–T2 vs T3–T4), and N staging as node-negative (N0) vs node-positive (N1–N2). Diagnostic measures (sensitivity, specificity, PPV, NPV) were calculated using histopathology as the reference standard. Results MRI accurately staged T in 11/28 (39.3%) and N in 10/27 (37.0%). T overstaging occurred in 53.6% and N overstaging in 40.7% of cases. Sensitivity was 48.1% (PPV 86.7%) for T staging and 52.2% (PPV 66.7%) for N staging. Specificity and NPV could not be reliably calculated due to the absence of true negatives in the cohort. Conclusion MRI demonstrates moderate sensitivity and high PPV for detecting residual tumor but frequently overestimates staging. MRI alone should not guide clinical decision-making post-NART. These findings reinforce the need for multimodal assessment rather than sole reliance on MRI. Oncology Nuclear Medicine & Medical Imaging Gastrointestinal Surgery Rectal cancer MRI neoadjuvant radiotherapy staging accuracy histopathology Introduction Colorectal cancer is the third most commonly diagnosed malignancy and the second leading cause of cancer-related deaths globally. Among its subtypes, rectal cancer comprises a significant portion and has unique anatomical and management considerations. In India, rectal cancer accounts for an increasing number of gastrointestinal cancer cases, particularly in urban regions. Early detection and accurate staging are critical to determine the best treatment strategy and to avoid over- or under-treatment. Locally advanced rectal cancer (LARC) is typically managed with neoadjuvant chemoradiotherapy (NART) followed by surgical resection. This approach has improved local control rates and allows for sphincter preservation in select cases. The accuracy of restaging post-NART, however, remains suboptimal, largely due to treatment-induced tissue changes. MRI is the imaging modality of choice for both primary and restaging due to its excellent soft tissue contrast and ability to delineate the mesorectal fascia, involvement of adjacent structures, and lymph nodes. Yet, the post-treatment fibrosis, mucin pools, and inflammation can mimic residual tumor, complicating radiologic assessment [ 1 – 3 ]. International data, including the MERCURY study, have demonstrated that MRI can predict circumferential resection margin (CRM) involvement and correlate with histopathological findings, but its reliability in post-treatment restaging remains debated [ 4 – 6 ]. There is a lack of data from Indian populations on the diagnostic accuracy of MRI post-NART, particularly comparing radiological findings with gold-standard histopathology. This study seeks to address this gap. Materials and Methods Study Design and Setting A retrospective observational study was conducted in a tertiary care center in Western India from January 2020 to December 2024. Ethics Approval This retrospective study was approved by the Institutional Ethics Committee (IEC-A Code: 20/2025; Approval date: 09 August 2025). A waiver of individual informed consent was granted. The study was conducted in accordance with the Declaration of Helsinki and relevant national guidelines. Patient Selection Inclusion Criteria: Patients aged 18 and above with biopsy-proven rectal adenocarcinoma Completed NART followed by curative intent surgical resection Available pre-operative post-NART MRI and post-operative histopathology Exclusion Criteria: Incomplete records (missing MRI or histopathology) History of synchronous or metachronous malignancy Palliative resections or non-standard treatment pathways Imaging Protocol All patients underwent high-resolution MRI 6–8 weeks after completing NART. T2-weighted axial images perpendicular to the tumor plane, sagittal, and coronal sequences were obtained, along with diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) mapping. MRI staging was assessed using the TNM classification (8th edition AJCC) by dedicated colorectal specialist radiologist. Histopathology Surgical specimens were analyzed using standardized pathology protocols. Data Analysis MRI-based T and N staging were compared with final histopathological staging (ypT and ypN). Staging was categorized as accurate, over-, or understaged. For sensitivity, specificity, PPV, and NPV calculations, calculated with 95% CI, T and N categories were dichotomized: T staging: T0–T2 vs T3–T4 N staging: N0 vs N1–N2 Results Patient Demographics and Tumor Characteristics Total patients: 28 Median age: 56.5 years (range: 38–75) Male: 18 (64.3%); Female: 10 (35.7%) Tumor location: Lower rectum (n = 12), mid rectum (n = 10), upper rectum (n = 6) T Staging Concordance (n = 28) Accurate: 11 (39.3%) Overstaged: 15 (53.6%) Understaged: 2 (7.1%) N Staging Concordance (n = 27) Accurate: 10 (37.0%) Overstaged: 11 (40.7%) Understaged: 6 (22.2%) One case was excluded due to missing nodal data on histopathology. Table 1 Patient Demographics Parameter Value Total patients 28 Median age (years) 56.5 Gender (M/F) 18 / 10 Table 2 Accuracy of T staging on MRI compared with HPE (n = 28) Outcome Number of Patients Percentage Accurate 11 39.3% Overstaged 15 53.6% Understaged 2 7.1% Table 3 Accuracy of N staging on MRI compared with HPE (n = 27) Outcome Number of Patients Percentage Accurate 10 37.0% Overstaged 11 40.7% Understaged 6 22.2% Table 4 Diagnostic Accuracy Metric T Staging N Staging Sensitivity 48.1% 52.2% Specificity 0% * 0% * PPV 86.7% 66.7% NPV 0%* 0%* * Note: Specificity and NPV values appear as 0% because no true negatives existed in the dataset Table 5 Flowchart of Inclusion Step Patients Rectal cancer patients diagnosed 36 Received neoadjuvant therapy 31 MRI and HPE available 28 Included in final analysis 28 Discussion Our findings indicate that MRI tends to overstage rectal tumors following NART, particularly in T staging. Overstaging in our cohort (53.6%) aligns with published international data, where fibrosis and desmoplastic reaction are often indistinguishable from residual tumor on conventional T2-weighted sequences [3,7,8]. Mucinous tumors posed additional challenges due to their characteristic high-signal on T2-weighted images. Nodal staging was also suboptimal, with MRI sensitivity of 52.2%, slightly higher than previous meta-analyses that reported pooled sensitivity of ~40–50% [9,10]. Morphological features like border irregularity and signal heterogeneity, though recommended, have subjective variability. The 0% specificity in both T and N staging is a reflection of cohort composition, where no true negatives existed. This limitation is inherent in restaging studies where all patients are initially diagnosed with advanced disease. Comparison with the MERCURY study and Patel et al. confirms that while MRI remains a robust tool for primary staging, its performance in restaging is highly variable and requires adjunctive tools. Techniques like diffusion-weighted imaging (DWI), which reflect tumor cellularity, and PET-MRI have shown promise in recent studies to better discriminate viable tumor from treatment-induced changes [11–15]. Our findings are consistent with global data [16-18] but represent one of the first Indian single-center datasets validating MRI performance post-NART. This study is limited by modest sample size, typical of single-center retrospective designs, which warrants validation in larger cohorts. While adequate for pilot-level analysis, results should be interpreted with caution. Future multicenter collaborations with larger cohorts and incorporation of functional imaging or AI-driven radiomics may improve accuracy. Clinical Implications: Overstaging may lead to unnecessary radical surgery in patients who might otherwise be candidates for local excision or 'watch-and-wait' [19,20]. Understaging, though less frequent, risks undertreatment. Thus, MRI should be interpreted in conjunction with clinical examination, endoscopy, and multidisciplinary consensus. Conclusion MRI following neoadjuvant chemoradiotherapy in rectal cancer demonstrates moderate sensitivity but poor specificity for both T and N staging. It frequently overestimates residual disease, especially in mucinous and lower rectal tumors. A multimodal approach combining imaging, pathology, endoscopy, and emerging AI technologies is essential to enhance post-treatment decision-making and personalize rectal cancer management. Declarations Ethical consideration This retrospective study was approved by the Institutional Ethics Committee (IEC-A Code: 20/2025; Approval date: 09 August 2025). A waiver of individual informed consent was granted. The study was conducted in accordance with the Declaration of Helsinki and relevant national guidelines. References Sauer R, Becker H, Hohenberger W, et al. Preoperative chemoradiotherapy for rectal cancer. N Engl J Med. 2004;351(17):1731–1740. Beets-Tan RGH, Beets GL. Rectal cancer: review with emphasis on MR imaging. Radiology. 2004;232(2):335–346. Maas M, Lambregts DM, Nelemans PJ, et al. Prediction of pathological complete response after chemoradiation for rectal cancer with MRI. Lancet Oncol. 2010;11(9):865–872. MERCURY Study Group. Diagnostic accuracy of preoperative magnetic resonance imaging in predicting curative resection of rectal cancer: prospective observational study. Lancet. 2006;368(9532):707–713. Taylor FG, Quirke P, Heald RJ, et al. Preoperative magnetic resonance imaging assessment of circumferential resection margin predicts disease-free survival and local recurrence: 5-year follow-up results of the MERCURY study. J Clin Oncol. 2014;32(1):34–43. Patel UB, Taylor F, Blomqvist L, et al. Magnetic resonance imaging–detected tumor response for locally advanced rectal cancer predicts survival outcomes: MERCURY experience. AJR Am J Roentgenol. 2012;199(4):W486–W495. Brown G, Richards CJ, Bourne MW, et al. Morphologic predictors of lymph node status in rectal cancer with use of high-spatial-resolution MR imaging with histopathologic comparison. Radiology. 2003;227(2):371–377. Horvat N, Carlos Tavares Rocha C, Mok T, et al. MRI of rectal cancer: restaging after chemoradiotherapy. Radiographics. 2012;32(2):389–409. Lambregts DM, Beets GL, Maas M, et al. Accuracy of MRI and diffusion-weighted MRI for restaging rectal cancer after chemoradiotherapy. Eur Radiol. 2011;21(12):2587–2594. Kang J, Hur H, Min BS, et al. Prognostic impact of pathologic and radiologic complete response after neoadjuvant chemoradiotherapy in rectal cancer. J Surg Oncol. 2017;115(4):402–408. Delli Pizzi A, Chiacchiaretta P, D’Orazio A, et al. Radiomics and magnetic resonance imaging in rectal cancer: current applications and future perspectives. J Oncol. 2019;2019:1–10. Glynne-Jones R, Wyrwicz L, Tiret E, et al. Rectal cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2017;28(suppl_4):iv22–iv40. Wong JC, Heriot AG, Koh DM. MRI for restaging rectal cancer after chemoradiotherapy: current status. Br J Radiol. 2020;93(1107):20190967. Bhoday J, Wong J, Siddiqui MR. Functional imaging in rectal cancer. World J Gastroenterol. 2021;27(6):436–450. van Griethuysen JJ, Lambregts DM, Trebeschi S, et al. Computed diffusion-weighted imaging for improved characterization of rectal cancer response to therapy. Eur Radiol. 2020;30(4):2228–2236. Bhatti ABH, Nazir SA, Qureshi S. Diagnostic performance of MRI in restaging of rectal cancer after neoadjuvant chemoradiotherapy: a study from Pakistan. Indian J Radiol Imaging. 2021;31(3):401–406. Mehta S, Godbole C, Shet T, et al. Imaging challenges in rectal cancer: a practical approach for the Indian setting. Indian J Surg Oncol. 2020;11(1):110–117. Chandramohan A, Natarajan R, Rajendran K. MRI in post-treatment evaluation of rectal cancer: observations from a tertiary center in South India. South Asian J Cancer. 2019;8(1):28–32. Habr-Gama A, Perez RO, Nadalin W, et al. Operative versus nonoperative treatment for stage 0 distal rectal cancer following chemoradiation therapy: long-term results. Int J Radiat Oncol Biol Phys. 2008;71(4):1181–1188. Perez RO, Habr-Gama A, Lynn PB, et al. Transanal endoscopic microsurgery for residual rectal cancer after chemoradiotherapy. Dis Colon Rectum. 2013;56(9):1096–1103. Additional Declarations The authors declare no competing interests. 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Cancers\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eColorectal cancer is the third most commonly diagnosed malignancy and the second leading cause of cancer-related deaths globally. Among its subtypes, rectal cancer comprises a significant portion and has unique anatomical and management considerations. In India, rectal cancer accounts for an increasing number of gastrointestinal cancer cases, particularly in urban regions. Early detection and accurate staging are critical to determine the best treatment strategy and to avoid over- or under-treatment.\u003c/p\u003e\u003cp\u003eLocally advanced rectal cancer (LARC) is typically managed with neoadjuvant chemoradiotherapy (NART) followed by surgical resection. This approach has improved local control rates and allows for sphincter preservation in select cases. The accuracy of restaging post-NART, however, remains suboptimal, largely due to treatment-induced tissue changes. MRI is the imaging modality of choice for both primary and restaging due to its excellent soft tissue contrast and ability to delineate the mesorectal fascia, involvement of adjacent structures, and lymph nodes. Yet, the post-treatment fibrosis, mucin pools, and inflammation can mimic residual tumor, complicating radiologic assessment [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eInternational data, including the MERCURY study, have demonstrated that MRI can predict circumferential resection margin (CRM) involvement and correlate with histopathological findings, but its reliability in post-treatment restaging remains debated [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. There is a lack of data from Indian populations on the diagnostic accuracy of MRI post-NART, particularly comparing radiological findings with gold-standard histopathology. This study seeks to address this gap.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cb\u003eStudy Design and Setting\u003c/b\u003e A retrospective observational study was conducted in a tertiary care center in Western India from January 2020 to December 2024.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthics Approval\u003c/strong\u003e\u003cp\u003eThis retrospective study was approved by the Institutional Ethics Committee (IEC-A Code: 20/2025; Approval date: 09 August 2025). A waiver of individual informed consent was granted. The study was conducted in accordance with the Declaration of Helsinki and relevant national guidelines.\u003c/p\u003e\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003ePatient Selection\u003c/h2\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eInclusion Criteria:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003ePatients aged 18 and above with biopsy-proven rectal adenocarcinoma\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eCompleted NART followed by curative intent surgical resection\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eAvailable pre-operative post-NART MRI and post-operative histopathology\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eExclusion Criteria:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eIncomplete records (missing MRI or histopathology)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eHistory of synchronous or metachronous malignancy\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003ePalliative resections or non-standard treatment pathways\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eImaging Protocol\u003c/b\u003e All patients underwent high-resolution MRI 6\u0026ndash;8 weeks after completing NART. T2-weighted axial images perpendicular to the tumor plane, sagittal, and coronal sequences were obtained, along with diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) mapping. MRI staging was assessed using the TNM classification (8th edition AJCC) by dedicated colorectal specialist radiologist.\u003c/p\u003e\u003cp\u003e\u003cb\u003eHistopathology\u003c/b\u003e Surgical specimens were analyzed using standardized pathology protocols.\u003c/p\u003e\u003cp\u003e\u003cb\u003eData Analysis\u003c/b\u003e MRI-based T and N staging were compared with final histopathological staging (ypT and ypN). Staging was categorized as accurate, over-, or understaged. For sensitivity, specificity, PPV, and NPV calculations, calculated with 95% CI, T and N categories were dichotomized:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eT staging: T0\u0026ndash;T2 vs T3\u0026ndash;T4\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eN staging: N0 vs N1\u0026ndash;N2\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec5\"\u003e\n \u003ch2\u003ePatient Demographics and Tumor Characteristics\u003c/h2\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eTotal patients: 28\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eMedian age: 56.5 years (range: 38–75)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eMale: 18 (64.3%); Female: 10 (35.7%)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eTumor location: Lower rectum (n = 12), mid rectum (n = 10), upper rectum (n = 6)\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n\u003c/div\u003e\n\u003ch3\u003eT Staging Concordance (n = 28)\u003c/h3\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eAccurate: 11 (39.3%)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eOverstaged: 15 (53.6%)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eUnderstaged: 2 (7.1%)\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003ch3\u003eN Staging Concordance (n = 27)\u003c/h3\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eAccurate: 10 (37.0%)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eOverstaged: 11 (40.7%)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eUnderstaged: 6 (22.2%)\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eOne case was excluded due to missing nodal data on histopathology.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003ePatient Demographics\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eValue\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal patients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedian age (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender (M/F)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 / 10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eAccuracy of T staging on MRI compared with HPE (n = 28)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOutcome\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber of Patients\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePercentage\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccurate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOverstaged\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnderstaged\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eAccuracy of N staging on MRI compared with HPE (n = 27)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOutcome\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber of Patients\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePercentage\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccurate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOverstaged\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnderstaged\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eDiagnostic Accuracy\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMetric\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eT Staging\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN Staging\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0% *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0% *\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePPV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNPV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0%*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0%*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003e\u003cstrong\u003e*\u003c/strong\u003e \u003cem\u003eNote: Specificity and NPV values appear as 0% because no true negatives existed in the dataset\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 5\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eFlowchart of Inclusion\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStep\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePatients\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRectal cancer patients diagnosed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReceived neoadjuvant therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMRI and HPE available\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncluded in final analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur findings indicate that MRI tends to overstage rectal tumors following NART, particularly in T staging. Overstaging in our cohort (53.6%) aligns with published international data, where fibrosis and desmoplastic reaction are often indistinguishable from residual tumor on conventional T2-weighted sequences [3,7,8]. Mucinous tumors posed additional challenges due to their characteristic high-signal on T2-weighted images.\u003c/p\u003e\n\u003cp\u003eNodal staging was also suboptimal, with MRI sensitivity of 52.2%, slightly higher than previous meta-analyses that reported pooled sensitivity of ~40\u0026ndash;50% [9,10]. Morphological features like border irregularity and signal heterogeneity, though recommended, have subjective variability.\u003c/p\u003e\n\u003cp\u003eThe 0% specificity in both T and N staging is a reflection of cohort composition, where no true negatives existed. This limitation is inherent in restaging studies where all patients are initially diagnosed with advanced disease.\u003c/p\u003e\n\u003cp\u003eComparison with the MERCURY study and Patel et al. confirms that while MRI remains a robust tool for primary staging, its performance in restaging is highly variable and requires adjunctive tools. Techniques like diffusion-weighted imaging (DWI), which reflect tumor cellularity, and PET-MRI have shown promise in recent studies to better discriminate viable tumor from treatment-induced changes [11\u0026ndash;15].\u003c/p\u003e\n\u003cp\u003eOur findings are consistent with global data [16-18] but represent one of the first Indian single-center datasets validating MRI performance post-NART. This study is limited by modest sample size, typical of single-center retrospective designs, which warrants validation in larger cohorts. While adequate for pilot-level analysis, results should be interpreted with caution. Future multicenter collaborations with larger cohorts and incorporation of functional imaging or AI-driven radiomics may improve accuracy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Implications:\u003c/strong\u003e Overstaging may lead to unnecessary radical surgery in patients who might otherwise be candidates for local excision or \u0026apos;watch-and-wait\u0026apos; [19,20]. Understaging, though less frequent, risks undertreatment. Thus, MRI should be interpreted in conjunction with clinical examination, endoscopy, and multidisciplinary consensus.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eMRI following neoadjuvant chemoradiotherapy in rectal cancer demonstrates moderate sensitivity but poor specificity for both T and N staging. It frequently overestimates residual disease, especially in mucinous and lower rectal tumors. A multimodal approach combining imaging, pathology, endoscopy, and emerging AI technologies is essential to enhance post-treatment decision-making and personalize rectal cancer management.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical consideration\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis retrospective study was approved by the Institutional Ethics Committee (IEC-A Code: 20/2025; Approval date: 09 August 2025). A waiver of individual informed consent was granted. The study was conducted in accordance with the Declaration of Helsinki and relevant national guidelines.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eSauer R, Becker H, Hohenberger W, et al. Preoperative chemoradiotherapy for rectal cancer. N Engl J Med. 2004;351(17):1731\u0026ndash;1740.\u003c/li\u003e\n \u003cli\u003eBeets-Tan RGH, Beets GL. Rectal cancer: review with emphasis on MR imaging. Radiology. 2004;232(2):335\u0026ndash;346.\u003c/li\u003e\n \u003cli\u003eMaas M, Lambregts DM, Nelemans PJ, et al. Prediction of pathological complete response after chemoradiation for rectal cancer with MRI. Lancet Oncol. 2010;11(9):865\u0026ndash;872.\u003c/li\u003e\n \u003cli\u003eMERCURY Study Group. Diagnostic accuracy of preoperative magnetic resonance imaging in predicting curative resection of rectal cancer: prospective observational study. Lancet. 2006;368(9532):707\u0026ndash;713.\u003c/li\u003e\n \u003cli\u003eTaylor FG, Quirke P, Heald RJ, et al. Preoperative magnetic resonance imaging assessment of circumferential resection margin predicts disease-free survival and local recurrence: 5-year follow-up results of the MERCURY study. J Clin Oncol. 2014;32(1):34\u0026ndash;43.\u003c/li\u003e\n \u003cli\u003ePatel UB, Taylor F, Blomqvist L, et al. Magnetic resonance imaging\u0026ndash;detected tumor response for locally advanced rectal cancer predicts survival outcomes: MERCURY experience. AJR Am J Roentgenol. 2012;199(4):W486\u0026ndash;W495.\u003c/li\u003e\n \u003cli\u003eBrown G, Richards CJ, Bourne MW, et al. Morphologic predictors of lymph node status in rectal cancer with use of high-spatial-resolution MR imaging with histopathologic comparison. Radiology. 2003;227(2):371\u0026ndash;377.\u003c/li\u003e\n \u003cli\u003eHorvat N, Carlos Tavares Rocha C, Mok T, et al. MRI of rectal cancer: restaging after chemoradiotherapy. Radiographics. 2012;32(2):389\u0026ndash;409.\u003c/li\u003e\n \u003cli\u003eLambregts DM, Beets GL, Maas M, et al. Accuracy of MRI and diffusion-weighted MRI for restaging rectal cancer after chemoradiotherapy. Eur Radiol. 2011;21(12):2587\u0026ndash;2594.\u003c/li\u003e\n \u003cli\u003eKang J, Hur H, Min BS, et al. Prognostic impact of pathologic and radiologic complete response after neoadjuvant chemoradiotherapy in rectal cancer. J Surg Oncol. 2017;115(4):402\u0026ndash;408.\u003c/li\u003e\n \u003cli\u003eDelli Pizzi A, Chiacchiaretta P, D\u0026rsquo;Orazio A, et al. Radiomics and magnetic resonance imaging in rectal cancer: current applications and future perspectives. J Oncol. 2019;2019:1\u0026ndash;10.\u003c/li\u003e\n \u003cli\u003eGlynne-Jones R, Wyrwicz L, Tiret E, et al. Rectal cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2017;28(suppl_4):iv22\u0026ndash;iv40.\u003c/li\u003e\n \u003cli\u003eWong JC, Heriot AG, Koh DM. MRI for restaging rectal cancer after chemoradiotherapy: current status. Br J Radiol. 2020;93(1107):20190967.\u003c/li\u003e\n \u003cli\u003eBhoday J, Wong J, Siddiqui MR. Functional imaging in rectal cancer. World J Gastroenterol. 2021;27(6):436\u0026ndash;450.\u003c/li\u003e\n \u003cli\u003evan Griethuysen JJ, Lambregts DM, Trebeschi S, et al. Computed diffusion-weighted imaging for improved characterization of rectal cancer response to therapy. Eur Radiol. 2020;30(4):2228\u0026ndash;2236.\u003c/li\u003e\n \u003cli\u003eBhatti ABH, Nazir SA, Qureshi S. Diagnostic performance of MRI in restaging of rectal cancer after neoadjuvant chemoradiotherapy: a study from Pakistan. Indian J Radiol Imaging. 2021;31(3):401\u0026ndash;406.\u003c/li\u003e\n \u003cli\u003eMehta S, Godbole C, Shet T, et al. Imaging challenges in rectal cancer: a practical approach for the Indian setting. Indian J Surg Oncol. 2020;11(1):110\u0026ndash;117.\u003c/li\u003e\n \u003cli\u003eChandramohan A, Natarajan R, Rajendran K. MRI in post-treatment evaluation of rectal cancer: observations from a tertiary center in South India. South Asian J Cancer. 2019;8(1):28\u0026ndash;32.\u003c/li\u003e\n \u003cli\u003eHabr-Gama A, Perez RO, Nadalin W, et al. Operative versus nonoperative treatment for stage 0 distal rectal cancer following chemoradiation therapy: long-term results. Int J Radiat Oncol Biol Phys. 2008;71(4):1181\u0026ndash;1188.\u003c/li\u003e\n \u003cli\u003ePerez RO, Habr-Gama A, Lynn PB, et al. Transanal endoscopic microsurgery for residual rectal cancer after chemoradiotherapy. Dis Colon Rectum. 2013;56(9):1096\u0026ndash;1103.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Kokilaben Dhirubhai Ambani Hospital","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Rectal cancer, MRI, neoadjuvant radiotherapy, staging accuracy, histopathology","lastPublishedDoi":"10.21203/rs.3.rs-7691356/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7691356/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eAccurate restaging of rectal cancer following neoadjuvant radiotherapy (NART) is critical for determining appropriate surgical intervention. Magnetic resonance imaging (MRI) is widely used for this purpose, although its accuracy post-radiation is debated due to treatment-induced tissue changes. This is among the few Indian study validating MRI accuracy in post-NART rectal cancer staging.\u003c/p\u003e\u003ch2\u003eAim\u003c/h2\u003e\u003cp\u003eTo evaluate the diagnostic accuracy of MRI in restaging rectal cancer (T and N staging) post-NART by comparing it with postoperative histopathology.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis retrospective observational study included 28 patients treated with NART for rectal cancer between January 2020 and December 2024. MRI staging (6\u0026ndash;8 weeks post-NART) was compared with final histopathology. T staging was dichotomized (T0\u0026ndash;T2 vs T3\u0026ndash;T4), and N staging as node-negative (N0) vs node-positive (N1\u0026ndash;N2). Diagnostic measures (sensitivity, specificity, PPV, NPV) were calculated using histopathology as the reference standard.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eMRI accurately staged T in 11/28 (39.3%) and N in 10/27 (37.0%). T overstaging occurred in 53.6% and N overstaging in 40.7% of cases. Sensitivity was 48.1% (PPV 86.7%) for T staging and 52.2% (PPV 66.7%) for N staging. Specificity and NPV could not be reliably calculated due to the absence of true negatives in the cohort.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eMRI demonstrates moderate sensitivity and high PPV for detecting residual tumor but frequently overestimates staging. MRI alone should not guide clinical decision-making post-NART. These findings reinforce the need for multimodal assessment rather than sole reliance on MRI.\u003c/p\u003e","manuscriptTitle":"An Observational Retrospective Study to See the Accuracy of Post-Neoadjuvant Radiotherapy MRI Staging in Cases of Rectal Cancers","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-24 06:23:24","doi":"10.21203/rs.3.rs-7691356/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8fab90d8-e4a5-40b3-ad0d-6fa6d810e5cb","owner":[],"postedDate":"September 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":55171736,"name":"Oncology"},{"id":55171737,"name":"Nuclear Medicine \u0026 Medical Imaging"},{"id":55171738,"name":"Gastrointestinal Surgery"}],"tags":[],"updatedAt":"2025-09-24T06:23:24+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-24 06:23:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7691356","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7691356","identity":"rs-7691356","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}