{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T11:24:56Z","timestamp":1789471496524,"version":"build-2803163510"},"reference-count":108,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2025,5,31]],"date-time":"2025-05-31T00:00:00Z","timestamp":1748649600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,5,31]],"date-time":"2025-05-31T00:00:00Z","timestamp":1748649600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100010211","name":"Department of Education of Jilin Province","doi-asserted-by":"crossref","award":["2024L5LS6XQ0001"],"award-info":[{"award-number":["2024L5LS6XQ0001"]}],"id":[{"id":"10.13039\/501100010211","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Case database of professional degree postgraduates of Jilin University","award":["2024ALK025"],"award-info":[{"award-number":["2024ALK025"]}]},{"name":"Jilin Province higher education research topic","award":["JGJX24D0041"],"award-info":[{"award-number":["JGJX24D0041"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Abdom Radiol"],"DOI":"10.1007\/s00261-025-04965-1","type":"journal-article","created":{"date-parts":[[2025,5,31]],"date-time":"2025-05-31T04:42:44Z","timestamp":1748666564000},"page":"5677-5689","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Research progress in multimodal radiomics of rectal cancer tumors and peritumoral regions in MRI"],"prefix":"10.1007","volume":"50","author":[{"given":"Tingting","family":"Gong","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Gao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"He","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianqiu","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zili","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qinghai","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,5,31]]},"reference":[{"issue":"1","key":"4965_CR1","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1016\/j.annonc.2022.10.003","volume":"34","author":"A Cervantes","year":"2023","unstructured":"Cervantes, A., et al., Metastatic colorectal cancer: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up. Ann Oncol, 2023. 34(1): p. 10\u201332.https:\/\/doi.org\/10.1016\/j.annonc.2022.10.003","journal-title":"Ann Oncol"},{"issue":"3","key":"4965_CR2","doi-asserted-by":"publisher","first-page":"233","DOI":"10.3322\/caac.21772","volume":"73","author":"RL Siegel","year":"2023","unstructured":"Siegel, R.L., et al., Colorectal cancer statistics, 2023. CA Cancer J Clin, 2023. 73(3): p. 233\u2013254.https:\/\/doi.org\/10.3322\/caac.21772","journal-title":"CA Cancer J Clin"},{"issue":"1","key":"4965_CR3","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1038\/s41572-023-00432-7","volume":"9","author":"MCW Spaander","year":"2023","unstructured":"Spaander, M.C.W., et al., Young-onset colorectal cancer. Nat Rev Dis Primers, 2023. 9(1): p. 21.https:\/\/doi.org\/10.1038\/s41572-023-00432-7","journal-title":"Nat Rev Dis Primers"},{"issue":"4","key":"4965_CR4","doi-asserted-by":"publisher","first-page":"222","DOI":"10.1016\/j.tips.2023.01.003","volume":"44","author":"AE Shin","year":"2023","unstructured":"Shin, A.E., F.G. Giancotti, and A.K. Rustgi, Metastatic colorectal cancer: mechanisms and emerging therapeutics. Trends Pharmacol Sci, 2023. 44(4): p. 222\u2013236.https:\/\/doi.org\/10.1016\/j.tips.2023.01.003","journal-title":"Trends Pharmacol Sci"},{"issue":"1","key":"4965_CR5","doi-asserted-by":"publisher","first-page":"7","DOI":"10.3322\/caac.21708","volume":"72","author":"RL Siegel","year":"2022","unstructured":"Siegel, R.L., et al., Cancer statistics, 2022. CA Cancer J Clin, 2022. 72(1): p. 7\u201333.https:\/\/doi.org\/10.3322\/caac.21708","journal-title":"CA Cancer J Clin"},{"issue":"4","key":"4965_CR6","doi-asserted-by":"publisher","first-page":"372","DOI":"10.3322\/caac.21728","volume":"72","author":"F Ciardiello","year":"2022","unstructured":"Ciardiello, F., et al., Clinical management of metastatic colorectal cancer in the era of precision medicine. CA Cancer J Clin, 2022. 72(4): p. 372\u2013401.https:\/\/doi.org\/10.3322\/caac.21728","journal-title":"CA Cancer J Clin"},{"issue":"12","key":"4965_CR7","doi-asserted-by":"publisher","first-page":"749","DOI":"10.1038\/nrclinonc.2017.141","volume":"14","author":"P Lambin","year":"2017","unstructured":"Lambin, P., et al., Radiomics: the bridge between medical imaging and personalized medicine. Nat Rev Clin Oncol, 2017. 14(12): p. 749\u2013762.https:\/\/doi.org\/10.1038\/nrclinonc.2017.141","journal-title":"Nat Rev Clin Oncol"},{"issue":"1","key":"4965_CR8","doi-asserted-by":"publisher","first-page":"426","DOI":"10.1002\/med.21846","volume":"42","author":"J Guiot","year":"2022","unstructured":"Guiot, J., et al., A review in radiomics: Making personalized medicine a reality via routine imaging. Medicinal Research Reviews, 2022. 42(1): p. 426\u2013440.https:\/\/doi.org\/10.1002\/med.21846","journal-title":"Medicinal Research Reviews"},{"key":"4965_CR9","doi-asserted-by":"publisher","unstructured":"Liu, X., et al., Deep learning radiomics-based prediction of distant metastasis in patients with locally advanced rectal cancer after neoadjuvant chemoradiotherapy: A multicentre study. EBioMedicine, 2021. 69: p. 103442https:\/\/doi.org\/10.1016\/j.ebiom.2021.103442","DOI":"10.1016\/j.ebiom.2021.103442"},{"key":"4965_CR10","doi-asserted-by":"publisher","unstructured":"Chen, F., et al., MRI-Based Radiomics of Rectal Cancer: Assessment of the Local Recurrence at the Site of Anastomosis. Acad Radiol, 2021. 28 Suppl 1: p. S87https:\/\/doi.org\/10.1016\/j.acra.2020.09.024","DOI":"10.1016\/j.acra.2020.09.024"},{"issue":"2","key":"4965_CR11","doi-asserted-by":"publisher","first-page":"351","DOI":"10.1148\/radiol.211986","volume":"303","author":"J Shin","year":"2022","unstructured":"Shin, J., et al., MRI Radiomics Model Predicts Pathologic Complete Response of Rectal Cancer Following Chemoradiotherapy. Radiology, 2022. 303(2): p. 351\u2013358.https:\/\/doi.org\/10.1148\/radiol.211986","journal-title":"Radiology"},{"issue":"2","key":"4965_CR12","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1038\/s41416-022-01786-7","volume":"127","author":"M Song","year":"2022","unstructured":"Song, M., et al., MRI radiomics independent of clinical baseline characteristics and neoadjuvant treatment modalities predicts response to neoadjuvant therapy in rectal cancer. Br J Cancer, 2022. 127(2): p. 249\u2013257.https:\/\/doi.org\/10.1038\/s41416-022-01786-7","journal-title":"Br J Cancer"},{"key":"4965_CR13","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1016\/j.phro.2022.06.010","volume":"23","author":"P Mbanu","year":"2022","unstructured":"Mbanu, P., et al., Clinical and radiomics prediction of complete response in rectal cancer pre-chemoradiotherapy. Phys Imaging Radiat Oncol, 2022. 23: p. 48\u201353.https:\/\/doi.org\/10.1016\/j.phro.2022.06.010","journal-title":"Phys Imaging Radiat Oncol"},{"issue":"1","key":"4965_CR14","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1186\/s13014-023-02368-4","volume":"18","author":"H Huang","year":"2023","unstructured":"Huang, H., et al., Multiphase and multiparameter MRI-based radiomics for prediction of tumor response to neoadjuvant therapy in locally advanced rectal cancer. Radiat Oncol, 2023. 18(1): p. 179.https:\/\/doi.org\/10.1186\/s13014-023-02368-4","journal-title":"Radiat Oncol"},{"issue":"1","key":"4965_CR15","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1007\/s00330-024-10958-3","volume":"35","author":"Y Hao","year":"2025","unstructured":"Hao, Y., et al., Ultra-high b-value DWI in rectal cancer: image quality assessment and regional lymph node prediction based on radiomics. Eur Radiol, 2025. 35(1): p. 49\u201360.https:\/\/doi.org\/10.1007\/s00330-024-10958-3","journal-title":"Eur Radiol"},{"issue":"1","key":"4965_CR16","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1186\/s13244-024-01795-5","volume":"15","author":"Y Zhu","year":"2024","unstructured":"Zhu, Y., et al., Different radiomics annotation methods comparison in rectal cancer characterisation and prognosis prediction: a two-centre study. Insights Imaging, 2024. 15(1): p. 211.https:\/\/doi.org\/10.1186\/s13244-024-01795-5","journal-title":"Insights Imaging"},{"issue":"11","key":"4965_CR17","doi-asserted-by":"publisher","first-page":"7561","DOI":"10.1007\/s00330-023-09723-9","volume":"33","author":"H Li","year":"2023","unstructured":"Li, H., et al., MRI-based multiregional radiomics for preoperative prediction of tumor deposit and prognosis in resectable rectal cancer: a bicenter study. Eur Radiol, 2023. 33(11): p. 7561\u20137572.https:\/\/doi.org\/10.1007\/s00330-023-09723-9","journal-title":"Eur Radiol"},{"issue":"8","key":"4965_CR18","doi-asserted-by":"publisher","first-page":"5106","DOI":"10.1007\/s00330-022-08717-3","volume":"32","author":"Y Yuan","year":"2022","unstructured":"Yuan, Y., et al., The application of apparent diffusion coefficients derived from intratumoral and peritumoral zones for assessing pathologic prognostic factors in rectal cancer. Eur Radiol, 2022. 32(8): p. 5106\u20135118.https:\/\/doi.org\/10.1007\/s00330-022-08717-3","journal-title":"Eur Radiol"},{"issue":"3","key":"4965_CR19","doi-asserted-by":"publisher","first-page":"403","DOI":"10.1038\/modpathol.2014.104","volume":"28","author":"L Harbaum","year":"2015","unstructured":"Harbaum, L., et al., Peritumoral eosinophils predict recurrence in colorectal cancer. Mod Pathol, 2015. 28(3): p. 403\u201313.https:\/\/doi.org\/10.1038\/modpathol.2014.104","journal-title":"Mod Pathol"},{"key":"4965_CR20","doi-asserted-by":"publisher","first-page":"110047","DOI":"10.1016\/j.ejrad.2021.110047","volume":"145","author":"H Ahn","year":"2021","unstructured":"Ahn, H., et al., Prognostic significance of imaging features of peritumoral adipose tissue in FDG PET\/CT of patients with colorectal cancer. Eur J Radiol, 2021. 145: p. 110047https:\/\/doi.org\/10.1016\/j.ejrad.2021.110047","journal-title":"Eur J Radiol"},{"issue":"4","key":"4965_CR21","doi-asserted-by":"publisher","first-page":"1367","DOI":"10.1016\/j.acra.2023.09.007","volume":"31","author":"R Zhao","year":"2024","unstructured":"Zhao, R., et al., MRI-based Multiregional Radiomics for Pretreatment Prediction of Distant Metastasis After Neoadjuvant Chemoradiotherapy in Patients with Locally Advanced Rectal Cancer. Acad Radiol, 2024. 31(4): p. 1367\u20131377.https:\/\/doi.org\/10.1016\/j.acra.2023.09.007","journal-title":"Acad Radiol"},{"issue":"1","key":"4965_CR22","doi-asserted-by":"publisher","first-page":"452","DOI":"10.1002\/jmri.29396","volume":"61","author":"X Guo","year":"2025","unstructured":"Guo, X., et al., Association Analysis Between Intratumoral and Peritumoral MRI Radiomics Features and Overall Survival of Neoadjuvant Therapy in Rectal Cancer. J Magn Reson Imaging, 2025. 61(1): p. 452\u2013465.https:\/\/doi.org\/10.1002\/jmri.29396","journal-title":"J Magn Reson Imaging"},{"issue":"17","key":"4965_CR23","doi-asserted-by":"publisher","first-page":"2095","DOI":"10.1101\/gad.1204904","volume":"18","author":"DA Nelson","year":"2004","unstructured":"Nelson, D.A., et al., Hypoxia and defective apoptosis drive genomic instability and tumorigenesis. Genes Dev, 2004. 18(17): p. 2095\u2013\u2009107.https:\/\/doi.org\/10.1101\/gad.1204904","journal-title":"Genes Dev"},{"issue":"8","key":"4965_CR24","doi-asserted-by":"publisher","first-page":"609","DOI":"10.1016\/j.trecan.2023.04.004","volume":"9","author":"S Zhang","year":"2023","unstructured":"Zhang, S., et al., The peritumor microenvironment: physics and immunity. Trends Cancer, 2023. 9(8): p. 609\u2013623.https:\/\/doi.org\/10.1016\/j.trecan.2023.04.004","journal-title":"Trends Cancer"},{"issue":"6","key":"4965_CR25","doi-asserted-by":"publisher","first-page":"760","DOI":"10.1016\/j.annonc.2020.03.295","volume":"31","author":"Y Jiang","year":"2020","unstructured":"Jiang, Y., et al., Noninvasive imaging evaluation of tumor immune microenvironment to predict outcomes in gastric cancer. Ann Oncol, 2020. 31(6): p. 760\u2013768.https:\/\/doi.org\/10.1016\/j.annonc.2020.03.295","journal-title":"Ann Oncol"},{"issue":"9","key":"4965_CR26","doi-asserted-by":"publisher","first-page":"1475","DOI":"10.3348\/kjr.2021.0560","volume":"22","author":"KL Gormly","year":"2021","unstructured":"Gormly, K.L., High-Resolution T2-Weighted MRI to Evaluate Rectal Cancer: Why Variations Matter. Korean J Radiol, 2021. 22(9): p. 1475\u20131480.https:\/\/doi.org\/10.3348\/kjr.2021.0560","journal-title":"Korean J Radiol"},{"issue":"4","key":"4965_CR27","doi-asserted-by":"publisher","first-page":"967","DOI":"10.1002\/jmri.25814","volume":"47","author":"Y Peng","year":"2018","unstructured":"Peng, Y., et al., Comparison of reduced field-of-view diffusion-weighted imaging (DWI) and conventional DWI techniques in the assessment of rectal carcinoma at 3.0T: Image quality and histological T staging. J Magn Reson Imaging, 2018. 47(4): p. 967\u2013975.https:\/\/doi.org\/10.1002\/jmri.25814","journal-title":"J Magn Reson Imaging"},{"issue":"2","key":"4965_CR28","doi-asserted-by":"publisher","first-page":"418","DOI":"10.1148\/radiol.2016151908","volume":"282","author":"IM Blazic","year":"2017","unstructured":"Blazic, I.M., G.B. Lilic, and M.M. Gajic, Quantitative Assessment of Rectal Cancer Response to Neoadjuvant Combined Chemotherapy and Radiation Therapy: Comparison of Three Methods of Positioning Region of Interest for ADC Measurements at Diffusion-weighted MR Imaging. Radiology, 2017. 282(2): p. 418\u2013428.https:\/\/doi.org\/10.1148\/radiol.2016151908","journal-title":"Radiology"},{"issue":"1","key":"4965_CR29","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1148\/radiol.2341031403","volume":"234","author":"RF Vliegen","year":"2005","unstructured":"Vliegen, R.F., et al., Rectal cancer: MR imaging in local staging\u2013is gadolinium-based contrast material helpful? Radiology, 2005. 234(1): p. 179\u2013\u200988.https:\/\/doi.org\/10.1148\/radiol.2341031403","journal-title":"Radiology"},{"issue":"8","key":"4965_CR30","doi-asserted-by":"publisher","first-page":"e128","DOI":"10.1016\/j.acra.2021.11.024","volume":"29","author":"Y Cui","year":"2022","unstructured":"Cui, Y., et al., Radiomics Features at Multiparametric MRI Predict Disease-Free Survival in Patients With Locally Advanced Rectal Cancer. Acad Radiol, 2022. 29(8): p. e128-https:\/\/doi.org\/10.1016\/j.acra.2021.11.024","journal-title":"Acad Radiol"},{"issue":"4","key":"4965_CR31","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1016\/j.ejca.2011.11.036","volume":"48","author":"P Lambin","year":"2012","unstructured":"Lambin, P., et al., Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer, 2012. 48(4): p. 441\u20136.https:\/\/doi.org\/10.1016\/j.ejca.2011.11.036","journal-title":"Eur J Cancer"},{"issue":"19","key":"4965_CR32","doi-asserted-by":"publisher","first-page":"2888","DOI":"10.3748\/wjg.v29.i19.2888","volume":"29","author":"R Inchingolo","year":"2023","unstructured":"Inchingolo, R., et al., Radiomics in colorectal cancer patients. World J Gastroenterol, 2023. 29(19): p. 2888\u20132904.https:\/\/doi.org\/10.3748\/wjg.v29.i19.2888","journal-title":"World J Gastroenterol"},{"issue":"1","key":"4965_CR33","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1186\/s12885-023-10534-w","volume":"23","author":"P Tong","year":"2023","unstructured":"Tong, P., et al., Biparametric magnetic resonance imaging-based radiomics features for prediction of lymphovascular invasion in rectal cancer. BMC Cancer, 2023. 23(1): p. 61.https:\/\/doi.org\/10.1186\/s12885-023-10534-w","journal-title":"BMC Cancer"},{"issue":"4","key":"4965_CR34","doi-asserted-by":"publisher","first-page":"1158","DOI":"10.1007\/s12029-022-00909-w","volume":"54","author":"J Miranda","year":"2023","unstructured":"Miranda, J., et al., The Role of Radiomics in Rectal Cancer. J Gastrointest Cancer, 2023. 54(4): p. 1158\u20131180.https:\/\/doi.org\/10.1007\/s12029-022-00909-w","journal-title":"J Gastrointest Cancer"},{"issue":"5","key":"4965_CR35","doi-asserted-by":"publisher","first-page":"1303","DOI":"10.7150\/thno.30309","volume":"9","author":"Z Liu","year":"2019","unstructured":"Liu, Z., et al., The Applications of Radiomics in Precision Diagnosis and Treatment of Oncology: Opportunities and Challenges. Theranostics, 2019. 9(5): p. 1303\u20131322.https:\/\/doi.org\/10.7150\/thno.30309","journal-title":"Theranostics"},{"issue":"10","key":"4965_CR36","doi-asserted-by":"publisher","first-page":"1296","DOI":"10.1007\/s11547-021-01389-x","volume":"126","author":"C Scapicchio","year":"2021","unstructured":"Scapicchio, C., et al., A deep look into radiomics. Radiol Med, 2021. 126(10): p. 1296\u20131311.https:\/\/doi.org\/10.1007\/s11547-021-01389-x","journal-title":"Radiol Med"},{"issue":"1","key":"4965_CR37","doi-asserted-by":"publisher","first-page":"426","DOI":"10.1002\/med.21846","volume":"42","author":"J Guiot","year":"2022","unstructured":"Guiot, J., et al., A review in radiomics: Making personalized medicine a reality via routine imaging. Med Res Rev, 2022. 42(1): p. 426\u2013440.https:\/\/doi.org\/10.1002\/med.21846","journal-title":"Med Res Rev"},{"issue":"3","key":"4965_CR38","doi-asserted-by":"publisher","first-page":"873","DOI":"10.1007\/s00261-020-02733-x","volume":"46","author":"YS Yang","year":"2021","unstructured":"Yang, Y.S., et al., High-resolution MRI-based radiomics analysis to predict lymph node metastasis and tumor deposits respectively in rectal cancer. Abdom Radiol (NY), 2021. 46(3): p. 873\u2013884.https:\/\/doi.org\/10.1007\/s00261-020-02733-x","journal-title":"Abdom Radiol (NY)"},{"key":"4965_CR39","doi-asserted-by":"publisher","unstructured":"Yuan, Y., et al., Is rectal filling optimal for MRI-based radiomics in preoperative T staging of rectal cancer? Abdom Radiol (NY), 2022. 47(5): p. 1741\u20131749.https:\/\/doi.org\/10.1007\/s00261-022-03477-6","DOI":"10.1007\/s00261-022-03477-6"},{"issue":"3","key":"4965_CR40","doi-asserted-by":"publisher","first-page":"1211","DOI":"10.1007\/s00330-018-5683-9","volume":"29","author":"Y Cui","year":"2019","unstructured":"Cui, Y., et al., Radiomics analysis of multiparametric MRI for prediction of pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. Eur Radiol, 2019. 29(3): p. 1211\u20131220.https:\/\/doi.org\/10.1007\/s00330-018-5683-9","journal-title":"Eur Radiol"},{"issue":"1","key":"4965_CR41","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1007\/s11701-024-01978-8","volume":"18","author":"Z Liu","year":"2024","unstructured":"Liu, Z., et al., MRI-based radiomics feature combined with tumor markers to predict TN staging of rectal cancer. J Robot Surg, 2024. 18(1): p. 229.https:\/\/doi.org\/10.1007\/s11701-024-01978-8","journal-title":"J Robot Surg"},{"issue":"4","key":"4965_CR42","doi-asserted-by":"publisher","first-page":"1465","DOI":"10.1007\/s00330-017-5026-2","volume":"28","author":"RGH Beets-Tan","year":"2018","unstructured":"Beets-Tan, R.G.H., et al., Magnetic resonance imaging for clinical management of rectal cancer: Updated recommendations from the 2016 European Society of Gastrointestinal and Abdominal Radiology (ESGAR) consensus meeting. Eur Radiol, 2018. 28(4): p. 1465\u20131475.https:\/\/doi.org\/10.1007\/s00330-017-5026-2","journal-title":"Eur Radiol"},{"issue":"23","key":"4965_CR43","doi-asserted-by":"publisher","first-page":"7253","DOI":"10.1158\/1078-0432.Ccr-17-1038","volume":"23","author":"Z Liu","year":"2017","unstructured":"Liu, Z., et al., Radiomics Analysis for Evaluation of Pathological Complete Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer. Clin Cancer Res, 2017. 23(23): p. 7253\u20137262.https:\/\/doi.org\/10.1158\/1078-0432.Ccr-17-1038","journal-title":"Clin Cancer Res"},{"issue":"6","key":"4965_CR44","doi-asserted-by":"publisher","first-page":"1805","DOI":"10.1007\/s00261-024-04204-z","volume":"49","author":"Y Meng","year":"2024","unstructured":"Meng, Y., et al., Clinical development of MRI-based multi-sequence multi-regional radiomics model to predict lymph node metastasis in rectal cancer. Abdom Radiol (NY), 2024. 49(6): p. 1805\u20131815.https:\/\/doi.org\/10.1007\/s00261-024-04204-z","journal-title":"Abdom Radiol (NY)"},{"issue":"6","key":"4965_CR45","doi-asserted-by":"publisher","first-page":"1676","DOI":"10.1245\/s10434-019-07300-3","volume":"26","author":"X Zhou","year":"2019","unstructured":"Zhou, X., et al., Radiomics-Based Pretherapeutic Prediction of Non-response to Neoadjuvant Therapy in Locally Advanced Rectal Cancer. Ann Surg Oncol, 2019. 26(6): p. 1676\u20131684.https:\/\/doi.org\/10.1245\/s10434-019-07300-3","journal-title":"Ann Surg Oncol"},{"issue":"2","key":"4965_CR46","doi-asserted-by":"publisher","first-page":"1002","DOI":"10.1007\/s00330-021-08242-9","volume":"32","author":"Z Shu","year":"2022","unstructured":"Shu, Z., et al., Multiparameter MRI-based radiomics for preoperative prediction of extramural venous invasion in rectal cancer. Eur Radiol, 2022. 32(2): p. 1002\u20131013.https:\/\/doi.org\/10.1007\/s00330-021-08242-9","journal-title":"Eur Radiol"},{"issue":"21","key":"4965_CR47","doi-asserted-by":"publisher","first-page":"5256","DOI":"10.1158\/1078-0432.Ccr-15-2997","volume":"22","author":"K Nie","year":"2016","unstructured":"Nie, K., et al., Rectal Cancer: Assessment of Neoadjuvant Chemoradiation Outcome based on Radiomics of Multiparametric MRI. Clin Cancer Res, 2016. 22(21): p. 5256\u20135264.https:\/\/doi.org\/10.1158\/1078-0432.Ccr-15-2997","journal-title":"Clin Cancer Res"},{"issue":"3","key":"4965_CR48","doi-asserted-by":"publisher","first-page":"1835","DOI":"10.1007\/s00330-022-09160-0","volume":"33","author":"Z Li","year":"2023","unstructured":"Li, Z., et al., Development and external validation of a multiparametric MRI-based radiomics model for preoperative prediction of microsatellite instability status in rectal cancer: a retrospective multicenter study. Eur Radiol, 2023. 33(3): p. 1835\u20131843.https:\/\/doi.org\/10.1007\/s00330-022-09160-0","journal-title":"Eur Radiol"},{"issue":"1","key":"4965_CR49","doi-asserted-by":"publisher","first-page":"11760","DOI":"10.1038\/s41598-024-62584-0","volume":"14","author":"X Xing","year":"2024","unstructured":"Xing, X., et al., A combinatorial MRI sequence-based radiomics model for preoperative prediction of microsatellite instability status in rectal cancer. Sci Rep, 2024. 14(1): p. 11760.https:\/\/doi.org\/10.1038\/s41598-024-62584-0","journal-title":"Sci Rep"},{"issue":"7","key":"4965_CR50","doi-asserted-by":"publisher","first-page":"874","DOI":"10.6004\/jnccn.2018.0061","volume":"16","author":"AB Benson","year":"2018","unstructured":"Benson, A.B., et al., Rectal Cancer, Version 2.2018, NCCN Clinical Practice Guidelines in Oncology. J Natl Compr Canc Netw, 2018. 16(7): p. 874\u2013901.https:\/\/doi.org\/10.6004\/jnccn.2018.0061","journal-title":"J Natl Compr Canc Netw"},{"issue":"7","key":"4965_CR51","doi-asserted-by":"publisher","first-page":"909","DOI":"10.6004\/jnccn.2018.7032","volume":"16","author":"CA Smith","year":"2018","unstructured":"Smith, C.A. and L.A. Kachnic, Evolving Treatment Paradigm in the Treatment of Locally Advanced Rectal Cancer. J Natl Compr Canc Netw, 2018. 16(7): p. 909\u2013915.https:\/\/doi.org\/10.6004\/jnccn.2018.7032","journal-title":"J Natl Compr Canc Netw"},{"key":"4965_CR52","doi-asserted-by":"publisher","first-page":"101739","DOI":"10.1016\/j.suronc.2022.101739","volume":"43","author":"MC Fernandes","year":"2022","unstructured":"Fernandes, M.C., M.J. Gollub, and G. Brown, The importance of MRI for rectal cancer evaluation. Surg Oncol, 2022. 43: p. 101739.https:\/\/doi.org\/10.1016\/j.suronc.2022.101739","journal-title":"Surg Oncol"},{"issue":"6","key":"4965_CR53","doi-asserted-by":"publisher","first-page":"1282","DOI":"10.2214\/ajr.21.25556","volume":"217","author":"H Kaur","year":"2021","unstructured":"Kaur, H., et al., MRI Staging in an Evolving Management Paradigm for Rectal Cancer, From the AJR Special Series on Cancer Staging. AJR Am J Roentgenol, 2021. 217(6): p. 1282\u20131293.https:\/\/doi.org\/10.2214\/ajr.21.25556","journal-title":"AJR Am J Roentgenol"},{"key":"4965_CR54","doi-asserted-by":"publisher","unstructured":"Lu, H., et al., Assessment of MRI-Based Radiomics in Preoperative T Staging of Rectal Cancer: Comparison between Minimum and Maximum Delineation Methods. Biomed Res Int, 2021. 2021: p. 5566885.https:\/\/doi.org\/10.1155\/2021\/5566885","DOI":"10.1155\/2021\/5566885"},{"issue":"6","key":"4965_CR55","doi-asserted-by":"publisher","first-page":"1850","DOI":"10.1007\/s00261-023-04164-w","volume":"49","author":"B Deng","year":"2024","unstructured":"Deng, B., et al., A nomogram based on MRI radiomics features of mesorectal fat for diagnosing T2- and T3-stage rectal cancer. Abdom Radiol (NY), 2024. 49(6): p. 1850\u20131860.https:\/\/doi.org\/10.1007\/s00261-023-04164-w","journal-title":"Abdom Radiol (NY)"},{"issue":"1","key":"4965_CR56","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1016\/j.immuni.2022.12.008","volume":"56","author":"J Park","year":"2023","unstructured":"Park, J., et al., Microenvironment-driven metabolic adaptations guiding CD8(+) T cell anti-tumor immunity. Immunity, 2023. 56(1): p. 32\u201342.https:\/\/doi.org\/10.1016\/j.immuni.2022.12.008","journal-title":"Immunity"},{"key":"4965_CR57","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2015151169","author":"RJ Gillies","year":"2016","unstructured":"Gillies, R.J., P.E. Kinahan, and H. Hricak, Radiomics: Images Are More than Pictures, They Are Data. Radiology, 2016. 278(2): p. 563\u2013\u200977.https:\/\/doi.org\/10.1148\/radiol.2015151169"},{"issue":"18","key":"4965_CR58","doi-asserted-by":"publisher","first-page":"2157","DOI":"10.1200\/jco.2015.65.9128","volume":"34","author":"YQ Huang","year":"2016","unstructured":"Huang, Y.Q., et al., Development and Validation of a Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer. J Clin Oncol, 2016. 34(18): p. 2157\u201364https:\/\/doi.org\/10.1200\/jco.2015.65.9128","journal-title":"J Clin Oncol"},{"issue":"6","key":"4965_CR59","doi-asserted-by":"publisher","first-page":"3795","DOI":"10.1097\/js9.0000000000001239","volume":"110","author":"E Abbaspour","year":"2024","unstructured":"Abbaspour, E., et al., Application of radiomics for preoperative prediction of lymph node metastasis in colorectal cancer: a systematic review and meta-analysis. Int J Surg, 2024. 110(6): p. 3795\u20133813.https:\/\/doi.org\/10.1097\/js9.0000000000001239","journal-title":"Int J Surg"},{"issue":"3","key":"4965_CR60","doi-asserted-by":"publisher","first-page":"658","DOI":"10.1002\/jmri.28068","volume":"56","author":"H Jia","year":"2022","unstructured":"Jia, H., et al., A Nomogram of Combining IVIM-DWI and MRI Radiomics From the Primary Lesion of Rectal Adenocarcinoma to Assess Nonenlarged Lymph Node Metastasis Preoperatively. J Magn Reson Imaging, 2022. 56(3): p. 658\u2013667.https:\/\/doi.org\/10.1002\/jmri.28068","journal-title":"J Magn Reson Imaging"},{"key":"4965_CR61","doi-asserted-by":"publisher","unstructured":"Li, H., et al., MRI-based multiregional radiomics for predicting lymph nodes status and prognosis in patients with resectable rectal cancer. Front Oncol, 2022. 12: p. 1087882https:\/\/doi.org\/10.3389\/fonc.2022.1087882","DOI":"10.3389\/fonc.2022.1087882"},{"issue":"1","key":"4965_CR62","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1186\/s13244-024-01625-8","volume":"15","author":"H Li","year":"2024","unstructured":"Li, H., et al., T2WI-based MRI radiomics for the prediction of preoperative extranodal extension and prognosis in resectable rectal cancer. Insights Imaging, 2024. 15(1): p. 57.https:\/\/doi.org\/10.1186\/s13244-024-01625-8","journal-title":"Insights Imaging"},{"key":"4965_CR63","doi-asserted-by":"publisher","first-page":"585767","DOI":"10.3389\/fonc.2020.585767","volume":"10","author":"X Liu","year":"2020","unstructured":"Liu, X., et al., Multiregional-Based Magnetic Resonance Imaging Radiomics Combined With Clinical Data Improves Efficacy in Predicting Lymph Node Metastasis of Rectal Cancer. Front Oncol, 2020. 10: p. 585767https:\/\/doi.org\/10.3389\/fonc.2020.585767","journal-title":"Front Oncol"},{"issue":"1","key":"4965_CR64","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1159\/000454687","volume":"33","author":"JW Holch","year":"2017","unstructured":"Holch, J.W., et al., Pattern and Dynamics of Distant Metastases in Metastatic Colorectal Cancer. Visc Med, 2017. 33(1): p. 70\u201375.https:\/\/doi.org\/10.1159\/000454687","journal-title":"Visc Med"},{"issue":"11","key":"4965_CR65","doi-asserted-by":"publisher","first-page":"1495","DOI":"10.1016\/j.acra.2018.12.019","volume":"26","author":"M Liang","year":"2019","unstructured":"Liang, M., et al., Machine Learning-based Analysis of Rectal Cancer MRI Radiomics for Prediction of Metachronous Liver Metastasis. Acad Radiol, 2019. 26(11): p. 1495\u20131504.https:\/\/doi.org\/10.1016\/j.acra.2018.12.019","journal-title":"Acad Radiol"},{"issue":"10","key":"4965_CR66","doi-asserted-by":"publisher","first-page":"613","DOI":"10.1002\/bjs.1800691019","volume":"69","author":"RJ Heald","year":"1982","unstructured":"Heald, R.J., E.M. Husband, and R.D. Ryall, The mesorectum in rectal cancer surgery\u2013the clue to pelvic recurrence? Br J Surg, 1982. 69(10): p. 613\u20136.https:\/\/doi.org\/10.1002\/bjs.1800691019","journal-title":"Br J Surg"},{"issue":"8496","key":"4965_CR67","doi-asserted-by":"publisher","first-page":"1479","DOI":"10.1016\/s0140-6736(86)91510-2","volume":"1","author":"RJ Heald","year":"1986","unstructured":"Heald, R.J. and R.D. Ryall, Recurrence and survival after total mesorectal excision for rectal cancer. Lancet, 1986. 1(8496): p. 1479\u201382.https:\/\/doi.org\/10.1016\/s0140-6736(86)91510-2","journal-title":"Lancet"},{"issue":"11","key":"4965_CR68","doi-asserted-by":"publisher","first-page":"108641","DOI":"10.1016\/j.ejso.2024.108641","volume":"50","author":"S Kim","year":"2024","unstructured":"Kim, S., et al., Risk factors and treatment strategies for local recurrence of locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy followed by total mesorectal excision. Eur J Surg Oncol, 2024. 50(11): p. 108641https:\/\/doi.org\/10.1016\/j.ejso.2024.108641","journal-title":"Eur J Surg Oncol"},{"issue":"11","key":"4965_CR69","doi-asserted-by":"publisher","first-page":"2057","DOI":"10.1016\/j.ejso.2020.07.019","volume":"46","author":"Z Zheng","year":"2020","unstructured":"Zheng, Z., et al., Defining and predicting early recurrence in patients with locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy. Eur J Surg Oncol, 2020. 46(11): p. 2057\u20132063.https:\/\/doi.org\/10.1016\/j.ejso.2020.07.019","journal-title":"Eur J Surg Oncol"},{"issue":"32","key":"4965_CR70","doi-asserted-by":"publisher","first-page":"5227","DOI":"10.3748\/wjg.v19.i32.5227","volume":"19","author":"JY Peng","year":"2013","unstructured":"Peng, J.Y., Z.N. Li, and Y. Wang, Risk factors for local recurrence following neoadjuvant chemoradiotherapy for rectal cancers. World J Gastroenterol, 2013. 19(32): p. 5227\u201337https:\/\/doi.org\/10.3748\/wjg.v19.i32.5227","journal-title":"World J Gastroenterol"},{"issue":"3","key":"4965_CR71","doi-asserted-by":"publisher","first-page":"386","DOI":"10.1200\/jco.2005.02.0826","volume":"24","author":"F Rodr\u00edguez-Moranta","year":"2006","unstructured":"Rodr\u00edguez-Moranta, F., et al., Postoperative surveillance in patients with colorectal cancer who have undergone curative resection: a prospective, multicenter, randomized, controlled trial. J Clin Oncol, 2006. 24(3): p. 386\u2013\u200993.https:\/\/doi.org\/10.1200\/jco.2005.02.0826","journal-title":"J Clin Oncol"},{"issue":"7341","key":"4965_CR72","doi-asserted-by":"publisher","first-page":"813","DOI":"10.1136\/bmj.324.7341.813","volume":"324","author":"AG Renehan","year":"2002","unstructured":"Renehan, A.G., et al., Impact on survival of intensive follow up after curative resection for colorectal cancer: systematic review and meta-analysis of randomised trials. Bmj, 2002. 324(7341): p. 813https:\/\/doi.org\/10.1136\/bmj.324.7341.813","journal-title":"Bmj"},{"issue":"4","key":"4965_CR73","doi-asserted-by":"publisher","first-page":"644","DOI":"10.1093\/annonc\/mdu543","volume":"26","author":"S Pita-Fern\u00e1ndez","year":"2015","unstructured":"Pita-Fern\u00e1ndez, S., et al., Intensive follow-up strategies improve outcomes in nonmetastatic colorectal cancer patients after curative surgery: a systematic review and meta-analysis. Ann Oncol, 2015. 26(4): p. 644\u2013656.https:\/\/doi.org\/10.1093\/annonc\/mdu543","journal-title":"Ann Oncol"},{"issue":"12","key":"4965_CR74","doi-asserted-by":"publisher","first-page":"3065","DOI":"10.1111\/codi.15919","volume":"23","author":"MS Davey","year":"2021","unstructured":"Davey, M.S., et al., The use of radiomic analysis of magnetic resonance imaging in predicting distant metastases of rectal carcinoma following surgical resection: A systematic review and meta-analysis. Colorectal Dis, 2021. 23(12): p. 3065\u20133072.https:\/\/doi.org\/10.1111\/codi.15919","journal-title":"Colorectal Dis"},{"issue":"5","key":"4965_CR75","doi-asserted-by":"publisher","first-page":"580","DOI":"10.1002\/bjs.11478","volume":"107","author":"EA Agger","year":"2020","unstructured":"Agger, E.A., et al., Risk of local recurrence of rectal cancer and circumferential resection margin: population-based cohort study. Br J Surg, 2020. 107(5): p. 580\u2013585.https:\/\/doi.org\/10.1002\/bjs.11478","journal-title":"Br J Surg"},{"issue":"1","key":"4965_CR76","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1200\/jco.2012.45.3258","volume":"32","author":"FG Taylor","year":"2014","unstructured":"Taylor, F.G., 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): p. 34\u201343.https:\/\/doi.org\/10.1200\/jco.2012.45.3258","journal-title":"J Clin Oncol"},{"issue":"2","key":"4965_CR77","doi-asserted-by":"publisher","first-page":"971","DOI":"10.1007\/s00330-021-08144-w","volume":"32","author":"VS Jayaprakasam","year":"2022","unstructured":"Jayaprakasam, V.S., et al., MRI radiomics features of mesorectal fat can predict response to neoadjuvant chemoradiation therapy and tumor recurrence in patients with locally advanced rectal cancer. Eur Radiol, 2022. 32(2): p. 971\u2013980.https:\/\/doi.org\/10.1007\/s00330-021-08144-w","journal-title":"Eur Radiol"},{"issue":"1","key":"4965_CR78","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1186\/s12876-024-03274-z","volume":"24","author":"H Liang","year":"2024","unstructured":"Liang, H., et al., Comparison of conventional MRI analysis versus MRI-based radiomics to predict the circumferential margin resection involvement of rectal cancer. BMC Gastroenterol, 2024. 24(1): p. 209.https:\/\/doi.org\/10.1186\/s12876-024-03274-z","journal-title":"BMC Gastroenterol"},{"key":"4965_CR79","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1016\/j.ejca.2017.05.027","volume":"82","author":"AC Lord","year":"2017","unstructured":"Lord, A.C., et al., Significance of extranodal tumour deposits in colorectal cancer: A systematic review and meta-analysis. Eur J Cancer, 2017. 82: p. 92\u2013102.https:\/\/doi.org\/10.1016\/j.ejca.2017.05.027","journal-title":"Eur J Cancer"},{"issue":"11","key":"4965_CR80","doi-asserted-by":"publisher","first-page":"3310","DOI":"10.1007\/s00261-023-04013-w","volume":"48","author":"F Feng","year":"2023","unstructured":"Feng, F., et al., Multiregional-based magnetic resonance imaging radiomics model for predicting tumor deposits in resectable rectal cancer. Abdom Radiol (NY), 2023. 48(11): p. 3310\u20133321.https:\/\/doi.org\/10.1007\/s00261-023-04013-w","journal-title":"Abdom Radiol (NY)"},{"issue":"11","key":"4965_CR81","doi-asserted-by":"publisher","first-page":"1178","DOI":"10.1093\/bjs\/znac298","volume":"109","author":"K Pang","year":"2022","unstructured":"Pang, K., et al., Adding immune checkpoint blockade to neoadjuvant chemoradiation in locally advanced rectal cancer. Br J Surg, 2022. 109(11): p. 1178\u20131179.https:\/\/doi.org\/10.1093\/bjs\/znac298","journal-title":"Br J Surg"},{"issue":"10","key":"4965_CR82","doi-asserted-by":"publisher","first-page":"1139","DOI":"10.6004\/jnccn.2022.0051","volume":"20","author":"AB Benson","year":"2022","unstructured":"Benson, A.B., et al., Rectal Cancer, Version 2.2022, NCCN Clinical Practice Guidelines in Oncology. J Natl Compr Canc Netw, 2022. 20(10): p. 1139\u20131167.https:\/\/doi.org\/10.6004\/jnccn.2022.0051","journal-title":"J Natl Compr Canc Netw"},{"issue":"15","key":"4965_CR83","doi-asserted-by":"publisher","first-page":"1770","DOI":"10.1200\/jco.2011.39.7901","volume":"30","author":"IJ Park","year":"2012","unstructured":"Park, I.J., et al., Neoadjuvant treatment response as an early response indicator for patients with rectal cancer. J Clin Oncol, 2012. 30(15): p. 1770\u20136https:\/\/doi.org\/10.1200\/jco.2011.39.7901","journal-title":"J Clin Oncol"},{"issue":"16","key":"4965_CR84","doi-asserted-by":"publisher","first-page":"1797","DOI":"10.1200\/jco.2014.60.1054","volume":"33","author":"JJ Smith","year":"2015","unstructured":"Smith, J.J. and J. Garcia-Aguilar, Advances and challenges in treatment of locally advanced rectal cancer. J Clin Oncol, 2015. 33(16): p. 1797\u2013808https:\/\/doi.org\/10.1200\/jco.2014.60.1054","journal-title":"J Clin Oncol"},{"issue":"46","key":"4965_CR85","doi-asserted-by":"publisher","first-page":"17279","DOI":"10.3748\/wjg.v20.i46.17279","volume":"20","author":"R Berardi","year":"2014","unstructured":"Berardi, R., et al., Locally advanced rectal cancer: the importance of a multidisciplinary approach. World J Gastroenterol, 2014. 20(46): p. 17279\u201387.https:\/\/doi.org\/10.3748\/wjg.v20.i46.17279","journal-title":"World J Gastroenterol"},{"issue":"12","key":"4965_CR86","doi-asserted-by":"publisher","first-page":"1448","DOI":"10.1007\/s11604-024-01630-3","volume":"42","author":"W Zhu","year":"2024","unstructured":"Zhu, W., et al., Multi-parametric MRI radiomics for predicting response to neoadjuvant therapy in patients with locally advanced rectal cancer. Jpn J Radiol, 2024. 42(12): p. 1448\u20131457.https:\/\/doi.org\/10.1007\/s11604-024-01630-3","journal-title":"Jpn J Radiol"},{"key":"4965_CR87","doi-asserted-by":"publisher","first-page":"552","DOI":"10.3389\/fonc.2019.00552","volume":"9","author":"X Yi","year":"2019","unstructured":"Yi, X., et al., MRI-Based Radiomics Predicts Tumor Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer. Front Oncol, 2019. 9: p. 552https:\/\/doi.org\/10.3389\/fonc.2019.00552","journal-title":"Front Oncol"},{"key":"4965_CR88","doi-asserted-by":"publisher","unstructured":"Petresc, B., et al., Pre-Treatment T2-WI Based Radiomics Features for Prediction of Locally Advanced Rectal Cancer Non-Response to Neoadjuvant Chemoradiotherapy: A Preliminary Study. Cancers (Basel), 2020. 12(7)https:\/\/doi.org\/10.3390\/cancers12071894","DOI":"10.3390\/cancers12071894"},{"issue":"1","key":"4965_CR89","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1186\/s13014-023-02352-y","volume":"18","author":"X Zhou","year":"2023","unstructured":"Zhou, X., et al., Attention mechanism based multi-sequence MRI fusion improves prediction of response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. Radiat Oncol, 2023. 18(1): p. 175.https:\/\/doi.org\/10.1186\/s13014-023-02352-y","journal-title":"Radiat Oncol"},{"issue":"1","key":"4965_CR90","doi-asserted-by":"publisher","first-page":"21927","DOI":"10.1038\/s41598-024-72916-9","volume":"14","author":"S Qin","year":"2024","unstructured":"Qin, S., et al., Prediction of pathological response and lymph node metastasis after neoadjuvant therapy in rectal cancer through tumor and mesorectal MRI radiomic features. Sci Rep, 2024. 14(1): p. 21927.https:\/\/doi.org\/10.1038\/s41598-024-72916-9","journal-title":"Sci Rep"},{"issue":"6","key":"4965_CR91","doi-asserted-by":"publisher","first-page":"1911","DOI":"10.1007\/s00261-023-03898-x","volume":"48","author":"J Miranda","year":"2023","unstructured":"Miranda, J., et al., MRI-based radiomic score increased mrTRG accuracy in predicting rectal cancer response to neoadjuvant therapy. Abdom Radiol (NY), 2023. 48(6): p. 1911\u20131920.https:\/\/doi.org\/10.1007\/s00261-023-03898-x","journal-title":"Abdom Radiol (NY)"},{"key":"4965_CR92","doi-asserted-by":"publisher","first-page":"801743","DOI":"10.3389\/fonc.2022.801743","volume":"12","author":"BY Chen","year":"2022","unstructured":"Chen, B.Y., et al., MRI-Based Radiomics Features to Predict Treatment Response to Neoadjuvant Chemotherapy in Locally Advanced Rectal Cancer: A Single Center, Prospective Study. Front Oncol, 2022. 12: p. 801743.https:\/\/doi.org\/10.3389\/fonc.2022.801743","journal-title":"Front Oncol"},{"issue":"11","key":"4965_CR93","doi-asserted-by":"publisher","first-page":"6263","DOI":"10.1007\/s00330-020-06968-6","volume":"30","author":"H Shaish","year":"2020","unstructured":"Shaish, H., et al., Radiomics of MRI for pretreatment prediction of pathologic complete response, tumor regression grade, and neoadjuvant rectal score in patients with locally advanced rectal cancer undergoing neoadjuvant chemoradiation: an international multicenter study. Eur Radiol, 2020. 30(11): p. 6263\u20136273.https:\/\/doi.org\/10.1007\/s00330-020-06968-6","journal-title":"Eur Radiol"},{"key":"4965_CR94","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics13121987","author":"S Qin","year":"2023","unstructured":"Qin, S., et al., Radiomics from Mesorectal Blood Vessels and Lymph Nodes: A Novel Prognostic Predictor for Rectal Cancer with Neoadjuvant Therapy. Diagnostics (Basel), 2023. https:\/\/doi.org\/10.3390\/diagnostics13121987","journal-title":"Diagnostics (Basel)"},{"issue":"2","key":"4965_CR95","doi-asserted-by":"publisher","first-page":"367","DOI":"10.1148\/rg.2019180114","volume":"39","author":"N Horvat","year":"2019","unstructured":"Horvat, N., et al., MRI of Rectal Cancer: Tumor Staging, Imaging Techniques, and Management. Radiographics, 2019. 39(2): p. 367\u2013387.https:\/\/doi.org\/10.1148\/rg.2019180114","journal-title":"Radiographics"},{"issue":"2","key":"4965_CR96","doi-asserted-by":"publisher","first-page":"496","DOI":"10.1007\/s00330-017-4978-6","volume":"28","author":"ES Lee","year":"2018","unstructured":"Lee, E.S., et al., Magnetic Resonance Imaging-Detected Extramural Venous Invasion in Rectal Cancer before and after Preoperative Chemoradiotherapy: Diagnostic Performance and Prognostic Significance. Eur Radiol, 2018. 28(2): p. 496\u2013505.https:\/\/doi.org\/10.1007\/s00330-017-4978-6","journal-title":"Eur Radiol"},{"issue":"3","key":"4965_CR97","doi-asserted-by":"publisher","first-page":"355","DOI":"10.1002\/bjs.4034","volume":"90","author":"G Brown","year":"2003","unstructured":"Brown, G., et al., Preoperative assessment of prognostic factors in rectal cancer using high-resolution magnetic resonance imaging. Br J Surg, 2003. 90(3): p. 355\u2013\u200964.https:\/\/doi.org\/10.1002\/bjs.4034","journal-title":"Br J Surg"},{"issue":"4","key":"4965_CR98","doi-asserted-by":"publisher","first-page":"428","DOI":"10.1111\/codi.16032","volume":"24","author":"A Chandramohan","year":"2022","unstructured":"Chandramohan, A., et al., Prognostic significance of MR identified EMVI, tumour deposits, mesorectal nodes and pelvic side wall disease in locally advanced rectal cancer. Colorectal Dis, 2022. 24(4): p. 428\u2013438.https:\/\/doi.org\/10.1111\/codi.16032","journal-title":"Colorectal Dis"},{"issue":"6","key":"4965_CR99","doi-asserted-by":"publisher","first-page":"1088","DOI":"10.1038\/s41416-020-01222-8","volume":"124","author":"H Ueno","year":"2021","unstructured":"Ueno, H., et al., Prognostic value of desmoplastic reaction characterisation in stage II colon cancer: prospective validation in a Phase 3 study (SACURA Trial). Br J Cancer, 2021. 124(6): p. 1088\u20131097.https:\/\/doi.org\/10.1038\/s41416-020-01222-8","journal-title":"Br J Cancer"},{"issue":"11","key":"4965_CR100","doi-asserted-by":"publisher","first-page":"1506","DOI":"10.1097\/pas.0000000000000946","volume":"41","author":"H Ueno","year":"2017","unstructured":"Ueno, H., et al., Desmoplastic Pattern at the Tumor Front Defines Poor-prognosis Subtypes of Colorectal Cancer. Am J Surg Pathol, 2017. 41(11): p. 1506\u20131512.https:\/\/doi.org\/10.1097\/pas.0000000000000946","journal-title":"Am J Surg Pathol"},{"issue":"2","key":"4965_CR101","doi-asserted-by":"publisher","first-page":"252","DOI":"10.1111\/his.14211","volume":"78","author":"IA Gonz\u00e1lez","year":"2021","unstructured":"Gonz\u00e1lez, I.A., et al., Intraepithelial tumour infiltrating lymphocytes are associated with absence of tumour budding and immature\/myxoid desmoplastic reaction, and with better recurrence-free survival in stages I-III colorectal cancer. Histopathology, 2021. 78(2): p. 252\u2013264.https:\/\/doi.org\/10.1111\/his.14211","journal-title":"Histopathology"},{"key":"4965_CR102","doi-asserted-by":"publisher","first-page":"111888","DOI":"10.1016\/j.ejrad.2024.111888","volume":"183","author":"S Fan","year":"2025","unstructured":"Fan, S., et al., MRI-based multiregional radiomics for desmoplastic reaction classification and prognosis stratification in stage II rectal cancer: A bicenter study. Eur J Radiol, 2025. 183: p. 111888https:\/\/doi.org\/10.1016\/j.ejrad.2024.111888","journal-title":"Eur J Radiol"},{"issue":"12","key":"4965_CR103","doi-asserted-by":"publisher","first-page":"8889","DOI":"10.1007\/s00330-023-09920-6","volume":"33","author":"NW Schurink","year":"2023","unstructured":"Schurink, N.W., et al., Development and multicenter validation of a multiparametric imaging model to predict treatment response in rectal cancer. Eur Radiol, 2023. 33(12): p. 8889\u20138898.https:\/\/doi.org\/10.1007\/s00330-023-09920-6","journal-title":"Eur Radiol"},{"issue":"4","key":"4965_CR104","doi-asserted-by":"publisher","first-page":"2272","DOI":"10.1007\/s00330-020-07284-9","volume":"31","author":"F Orlhac","year":"2021","unstructured":"Orlhac, F., et al., How can we combat multicenter variability in MR radiomics? Validation of a correction procedure. Eur Radiol, 2021. 31(4): p. 2272\u20132280.https:\/\/doi.org\/10.1007\/s00330-020-07284-9","journal-title":"Eur Radiol"},{"issue":"9","key":"4965_CR105","doi-asserted-by":"publisher","first-page":"1029","DOI":"10.1177\/0284185116681040","volume":"58","author":"Z Koc","year":"2017","unstructured":"Koc, Z., G. Erbay, and E. Karadeli, Internal comparison standard for abdominal diffusion-weighted imaging. Acta Radiol, 2017. 58(9): p. 1029\u20131036.https:\/\/doi.org\/10.1177\/0284185116681040","journal-title":"Acta Radiol"},{"issue":"5","key":"4965_CR106","doi-asserted-by":"publisher","first-page":"1878","DOI":"10.1016\/j.acra.2023.10.055","volume":"31","author":"H Huang","year":"2024","unstructured":"Huang, H., et al., Pretreatment MRI-Based Radiomics for Prediction of Rectal Cancer Outcome: A Discovery and Validation Study. Acad Radiol, 2024. 31(5): p. 1878\u20131888.https:\/\/doi.org\/10.1016\/j.acra.2023.10.055","journal-title":"Acad Radiol"},{"issue":"1","key":"4965_CR107","doi-asserted-by":"publisher","first-page":"5301","DOI":"10.1038\/s41598-017-05728-9","volume":"7","author":"S Trebeschi","year":"2017","unstructured":"Trebeschi, S., et al., Deep Learning for Fully-Automated Localization and Segmentation of Rectal Cancer on Multiparametric MR. Sci Rep, 2017. 7(1): p. 5301.https:\/\/doi.org\/10.1038\/s41598-017-05728-9","journal-title":"Sci Rep"},{"issue":"5","key":"4965_CR108","doi-asserted-by":"publisher","first-page":"3326","DOI":"10.1007\/s00330-020-07403-6","volume":"31","author":"C Cai","year":"2021","unstructured":"Cai, C., et al., Multiparametric MRI-based radiomics signature for preoperative estimation of tumor-stroma ratio in rectal cancer. Eur Radiol, 2021. 31(5): p. 3326\u20133335https:\/\/doi.org\/10.1007\/s00330-020-07403-6","journal-title":"Eur Radiol"}],"container-title":["Abdominal Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00261-025-04965-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00261-025-04965-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00261-025-04965-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,11]],"date-time":"2025-11-11T17:08:09Z","timestamp":1762880889000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00261-025-04965-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,31]]},"references-count":108,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["4965"],"URL":"https:\/\/doi.org\/10.1007\/s00261-025-04965-1","relation":{"references":[{"id-type":"doi","id":"10.1148\/radiol.2015151169","asserted-by":"subject"}]},"ISSN":["2366-0058"],"issn-type":[{"value":"2366-0058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5,31]]},"assertion":[{"value":"23 March 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 April 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 April 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 May 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}