{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T00:30:47Z","timestamp":1792715447915,"version":"4.5.0"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2024,9,14]],"date-time":"2024-09-14T00:00:00Z","timestamp":1726272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,9,14]],"date-time":"2024-09-14T00:00:00Z","timestamp":1726272000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Abdom Radiol"],"DOI":"10.1007\/s00261-024-04588-y","type":"journal-article","created":{"date-parts":[[2024,9,14]],"date-time":"2024-09-14T06:02:42Z","timestamp":1726293762000},"page":"1105-1116","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Predictive value of mono-exponential and multiple mathematical models in locally advanced rectal cancer response to neoadjuvant chemoradiotherapy"],"prefix":"10.1007","volume":"50","author":[{"given":"Mi","family":"Zhou","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengyuan","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meining","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xu","family":"Yan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guang","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongyun","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,9,14]]},"reference":[{"key":"4588_CR1","doi-asserted-by":"publisher","first-page":"17","DOI":"10.3322\/caac.21763","volume":"73","author":"RL Siegel","year":"2023","unstructured":"Siegel RL, Miller KD, Wagle NS, Jemal A (2023) Cancer statistics, 2023. CA Cancer J Clin 73:17\u201348 doi:https:\/\/doi.org\/10.3322\/caac.21763.","journal-title":"CA Cancer J Clin"},{"key":"4588_CR2","doi-asserted-by":"publisher","first-page":"209","DOI":"10.3322\/caac.21660","volume":"71","author":"H Sung","year":"2021","unstructured":"Sung H, Ferlay J, Siegel RL et al (2021) Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin 71:209\u2013249 doi:https:\/\/doi.org\/10.3322\/caac.21660.","journal-title":"CA Cancer J Clin"},{"key":"4588_CR3","doi-asserted-by":"publisher","first-page":"198","DOI":"10.3322\/caac.21661","volume":"71","author":"A Bigness","year":"2021","unstructured":"Bigness A, Imanirad I, Sahin IH et al (2021) Locally advanced rectal adenocarcinoma: Treatment sequences, intensification, and rectal organ preservation. CA Cancer J Clin 71:198\u2013208 doi:https:\/\/doi.org\/10.3322\/caac.21661.","journal-title":"CA Cancer J Clin"},{"key":"4588_CR4","doi-asserted-by":"publisher","first-page":"e1555-e1566","DOI":"10.1002\/onco.13824","volume":"26","author":"S Liu","year":"2021","unstructured":"Liu S, Jiang T, Xiao L et al (2021) Total Neoadjuvant Therapy (TNT) versus Standard Neoadjuvant Chemoradiotherapy for Locally Advanced Rectal Cancer: A Systematic Review and Meta-Analysis. Oncologist 26:e1555-e1566 doi:https:\/\/doi.org\/10.1002\/onco.13824.","journal-title":"Oncologist"},{"key":"4588_CR5","doi-asserted-by":"publisher","first-page":"903","DOI":"10.1097\/DCR.0000000000001135","volume":"61","author":"S Liu","year":"2018","unstructured":"Liu S, Zhong GX, Zhou WX et al (2018) Can Endorectal Ultrasound, MRI, and Mucosa Integrity Accurately Predict the Complete Response for Mid-Low Rectal Cancer After Preoperative Chemoradiation? A Prospective Observational Study from a Single Medical Center. Dis Colon Rectum 61:903\u2013910 doi:https:\/\/doi.org\/10.1097\/DCR.0000000000001135.","journal-title":"Dis Colon Rectum"},{"key":"4588_CR6","doi-asserted-by":"publisher","first-page":"1003","DOI":"10.3348\/kjr.2018.0611","volume":"20","author":"N Seo","year":"2019","unstructured":"Seo N, Kim H, Cho MS, Lim JS (2019) Response Assessment with MRI after Chemoradiotherapy in Rectal Cancer: Current Evidences. Korean J Radiol 20:1003\u20131018 doi:https:\/\/doi.org\/10.3348\/kjr.2018.0611.","journal-title":"Korean J Radiol"},{"key":"4588_CR7","doi-asserted-by":"publisher","first-page":"1848","DOI":"10.1007\/s00330-016-4529-6","volume":"27","author":"J Yu","year":"2017","unstructured":"Yu J, Xu Q, Song JC et al (2017) The value of diffusion kurtosis magnetic resonance imaging for assessing treatment response of neoadjuvant chemoradiotherapy in locally advanced rectal cancer. Eur Radiol 27:1848\u20131857 doi:https:\/\/doi.org\/10.1007\/s00330-016-4529-6.","journal-title":"Eur Radiol"},{"key":"4588_CR8","doi-asserted-by":"publisher","first-page":"285","DOI":"10.1615\/CritRevBiomedEng.2020033925","volume":"48","author":"RL Magin","year":"2020","unstructured":"Magin RL, Hall MG, Karaman MM, Vegh V (2020) Fractional Calculus Models of Magnetic Resonance Phenomena: Relaxation and Diffusion. Crit Rev Biomed Eng 48:285\u2013326 doi:https:\/\/doi.org\/10.1615\/CritRevBiomedEng.2020033925.","journal-title":"Crit Rev Biomed Eng"},{"key":"4588_CR9","first-page":"2659","volume":"10","author":"X Chen","year":"2018","unstructured":"Chen X, Jiang J, Shen N et al (2018) Stretched-exponential model diffusion-weighted imaging as a potential imaging marker in preoperative grading and assessment of proliferative activity of gliomas. Am J Transl Res 10:2659\u20132668","journal-title":"Am J Transl Res"},{"key":"4588_CR10","doi-asserted-by":"publisher","first-page":"1834","DOI":"10.1002\/jmri.28211","volume":"56","author":"H Guo","year":"2022","unstructured":"Guo H, Liu J, Hu J et al (2022) Diagnostic performance of gliomas grading and IDH status decoding A comparison between 3D amide proton transfer APT and four diffusion-weighted MRI models. J Magn Reson Imaging 56:1834\u20131844 doi:https:\/\/doi.org\/10.1002\/jmri.28211.","journal-title":"J Magn Reson Imaging"},{"key":"4588_CR11","doi-asserted-by":"publisher","first-page":"1149","DOI":"10.1002\/mrm.26012","volume":"76","author":"MM Karaman","year":"2016","unstructured":"Karaman MM, Sui Y, Wang H, Magin RL, Li Y, Zhou XJ (2016) Differentiating low- and high-grade pediatric brain tumors using a continuous-time random-walk diffusion model at high b-values. Magn Reson Med 76:1149\u20131157 doi:https:\/\/doi.org\/10.1002\/mrm.26012.","journal-title":"Magn Reson Med"},{"key":"4588_CR12","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1002\/jmri.28010","volume":"56","author":"Z Huang","year":"2022","unstructured":"Huang Z, Li X, Wang Z et al (2022) Application of Simultaneous (18) F-FDG PET With Monoexponential, Biexponential, and Stretched Exponential Model-Based Diffusion-Weighted MR Imaging in Assessing the Proliferation Status of Lung Adenocarcinoma. J Magn Reson Imaging 56:63\u201374 doi:https:\/\/doi.org\/10.1002\/jmri.28010.","journal-title":"J Magn Reson Imaging"},{"key":"4588_CR13","doi-asserted-by":"publisher","first-page":"907860","DOI":"10.3389\/fonc.2022.907860","volume":"12","author":"Y Luo","year":"2022","unstructured":"Luo Y, Jiang H, Meng N et al (2022) A comparison study of monoexponential and fractional order calculus diffusion models and (18)F-FDG PET in differentiating benign and malignant solitary pulmonary lesions and their pathological types. Front Oncol 12:907860 doi:https:\/\/doi.org\/10.3389\/fonc.2022.907860.","journal-title":"Front Oncol"},{"key":"4588_CR14","doi-asserted-by":"publisher","first-page":"110646","DOI":"10.1016\/j.ejrad.2022.110646","volume":"159","author":"C Wang","year":"2023","unstructured":"Wang C, Wang G, Zhang Y et al (2023) Differentiation of benign and malignant breast lesions using diffusion-weighted imaging with a fractional-order calculus model. Eur J Radiol 159:110646 doi:https:\/\/doi.org\/10.1016\/j.ejrad.2022.110646.","journal-title":"Eur J Radiol"},{"key":"4588_CR15","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1002\/jmri.28474","volume":"58","author":"Y Qin","year":"2023","unstructured":"Qin Y, Tang C, Hu Q, Yi J, Yin T, Ai T (2023) Assessment of Prognostic Factors and Molecular Subtypes of Breast Cancer With a Continuous-Time Random-Walk MR Diffusion Model: Using Whole Tumor Histogram Analysis. J Magn Reson Imaging 58:93\u2013105 doi:https:\/\/doi.org\/10.1002\/jmri.28474.","journal-title":"J Magn Reson Imaging"},{"key":"4588_CR16","doi-asserted-by":"publisher","first-page":"2812","DOI":"10.1007\/s00330-017-5292-z","volume":"28","author":"N Seo","year":"2018","unstructured":"Seo N, Chung YE, Park YN, Kim E, Hwang J, Kim MJ (2018) Liver fibrosis: stretched exponential model outperforms mono-exponential and bi-exponential models of diffusion-weighted MRI. Eur Radiol 28:2812\u20132822 doi:https:\/\/doi.org\/10.1007\/s00330-017-5292-z.","journal-title":"Eur Radiol"},{"key":"4588_CR17","doi-asserted-by":"publisher","first-page":"2740","DOI":"10.1007\/s00261-020-02903-x","volume":"46","author":"G Liu","year":"2021","unstructured":"Liu G, Lu Y, Dai Y et al (2021) Comparison of mono-exponential, bi-exponential, kurtosis, and fractional-order calculus models of diffusion-weighted imaging in characterizing prostate lesions in transition zone. Abdom Radiol (NY) 46:2740\u20132750 doi:https:\/\/doi.org\/10.1007\/s00261-020-02903-x.","journal-title":"Abdom Radiol (NY)"},{"key":"4588_CR18","doi-asserted-by":"publisher","first-page":"890","DOI":"10.1007\/s00330-021-08203-2","volume":"32","author":"C Feng","year":"2022","unstructured":"Feng C, Wang Y, Dan G et al (2022) Evaluation of a fractional-order calculus diffusion model and bi-parametric VI-RADS for staging and grading bladder urothelial carcinoma. Eur Radiol 32:890\u2013900 doi:https:\/\/doi.org\/10.1007\/s00330-021-08203-2.","journal-title":"Eur Radiol"},{"key":"4588_CR19","doi-asserted-by":"publisher","first-page":"1737","DOI":"10.1007\/s00330-022-09191-7","volume":"33","author":"S Lian","year":"2023","unstructured":"Lian S, Liu H, Meng T, Ma L, Zeng W, Xie C (2023) Quantitative synthetic MRI for predicting locally advanced rectal cancer response to neoadjuvant chemoradiotherapy. Eur Radiol 33:1737\u20131745 doi:https:\/\/doi.org\/10.1007\/s00330-022-09191-7.","journal-title":"Eur Radiol"},{"key":"4588_CR20","doi-asserted-by":"publisher","first-page":"109622","DOI":"10.1016\/j.ejrad.2021.109622","volume":"138","author":"P Wang","year":"2021","unstructured":"Wang P, Weng L, Xie S et al (2021) Primary application of mean apparent propagator-MRI diffusion model in the grading of diffuse glioma. European journal of radiology 138:109622 doi:https:\/\/doi.org\/10.1016\/j.ejrad.2021.109622.","journal-title":"European journal of radiology"},{"key":"4588_CR21","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1016\/j.neuroimage.2014.10.026","volume":"105","author":"A Daducci","year":"2015","unstructured":"Daducci A, Canales-Rodr\u00edguez EJ, Zhang H, Dyrby TB, Alexander DC, Thiran JP (2015) Accelerated Microstructure Imaging via Convex Optimization (AMICO) from diffusion MRI data. NeuroImage 105:32\u201344 doi:https:\/\/doi.org\/10.1016\/j.neuroimage.2014.10.026.","journal-title":"NeuroImage"},{"key":"4588_CR22","doi-asserted-by":"publisher","first-page":"109504","DOI":"10.1016\/j.ejrad.2020.109504","volume":"136","author":"L Yang","year":"2021","unstructured":"Yang L, Xia C, Zhao J, Zhou X, Wu B (2021) The value of intravoxel incoherent motion and diffusion kurtosis imaging in the assessment of tumor regression grade and T stages after neoadjuvant chemoradiotherapy in patients with locally advanced rectal cancer. European journal of radiology 136:109504 doi:https:\/\/doi.org\/10.1016\/j.ejrad.2020.109504.","journal-title":"European journal of radiology"},{"key":"4588_CR23","volume-title":"Classification of Tumours of the Digestive System. 5thed","author":"WHO Classification of Tumours Editorial BoardWHO","year":"2019","unstructured":"WHO Classification of Tumours Editorial BoardWHO Classification of Tumours of the Digestive System. 5thed, vol. 1, IARC Press, Lyon, 2019."},{"key":"4588_CR24","doi-asserted-by":"publisher","first-page":"e780-e793","DOI":"10.1002\/onco.13707","volume":"26","author":"HY Chen","year":"2021","unstructured":"Chen HY, Feng LL, Li M et al (2021) College of American Pathologists Tumor Regression Grading System for Long-Term Outcome in Patients with Locally Advanced Rectal Cancer. Oncologist 26:e780-e793 doi:https:\/\/doi.org\/10.1002\/onco.13707.","journal-title":"Oncologist"},{"key":"4588_CR25","unstructured":"NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines). Rectal Cancer. Version 4.2023, National Comprehensive Cancer Network, Fort Washington, 2023."},{"key":"4588_CR26","doi-asserted-by":"publisher","first-page":"1471","DOI":"10.1245\/s10434-010-0985-4","volume":"17","author":"SB Edge","year":"2010","unstructured":"Edge SB, Compton CC (2010) The American Joint Committee on Cancer: the 7th edition of the AJCC cancer staging manual and the future of TNM. Ann Surg Oncol 17:1471\u20131474 doi:https:\/\/doi.org\/10.1245\/s10434-010-0985-4.","journal-title":"Ann Surg Oncol"},{"key":"4588_CR27","doi-asserted-by":"publisher","first-page":"837","DOI":"10.2307\/2531595","volume":"44","author":"ER DeLong","year":"1988","unstructured":"DeLong ER, DeLong DM, Clarke-Pearson DL (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44:837\u2013845","journal-title":"Biometrics"},{"key":"4588_CR28","doi-asserted-by":"publisher","first-page":"3664","DOI":"10.1007\/s00261-019-02012-4","volume":"44","author":"M Napoletano","year":"2019","unstructured":"Napoletano M, Mazzucca D, Prosperi E et al (2019) Locally advanced rectal cancer: qualitative and quantitative evaluation of diffusion-weighted magnetic resonance imaging in restaging after neoadjuvant chemo-radiotherapy. Abdom Radiol (NY) 44:3664\u20133673 doi:https:\/\/doi.org\/10.1007\/s00261-019-02012-4.","journal-title":"Abdom Radiol (NY)"},{"key":"4588_CR29","doi-asserted-by":"publisher","first-page":"734","DOI":"10.1148\/radiol.11102467","volume":"260","author":"L Curvo-Semedo","year":"2011","unstructured":"Curvo-Semedo L, Lambregts DM, Maas M et al (2011) Rectal cancer: assessment of complete response to preoperative combined radiation therapy with chemotherapy\u2013conventional MR volumetry versus diffusion-weighted MR imaging. Radiology 260:734\u2013743 doi:https:\/\/doi.org\/10.1148\/radiol.11102467.","journal-title":"Radiology"},{"key":"4588_CR30","doi-asserted-by":"publisher","first-page":"214","DOI":"10.1016\/s0720-048x(02)00231-0","volume":"45","author":"PA Hein","year":"2003","unstructured":"Hein PA, Kremser C, Judmaier W et al (2003) Diffusion-weighted magnetic resonance imaging for monitoring diffusion changes in rectal carcinoma during combined, preoperative chemoradiation: preliminary results of a prospective study. European journal of radiology 45:214\u2013222 doi:https:\/\/doi.org\/10.1016\/s0720-048x(02)00231-0.","journal-title":"European journal of radiology"},{"key":"4588_CR31","doi-asserted-by":"publisher","first-page":"698","DOI":"10.1002\/nbm.1518","volume":"23","author":"JH Jensen","year":"2010","unstructured":"Jensen JH, Helpern JA (2010) MRI quantification of non-Gaussian water diffusion by kurtosis analysis. NMR Biomed 23:698\u2013710 doi:https:\/\/doi.org\/10.1002\/nbm.1518.","journal-title":"NMR Biomed"},{"key":"4588_CR32","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1016\/j.ejrad.2018.12.005","volume":"110","author":"CY Liang","year":"2019","unstructured":"Liang CY, Chen MD, Zhao XX, Yan CG, Mei YJ, Xu YK (2019) Multiple mathematical models of diffusion-weighted magnetic resonance imaging combined with prognostic factors for assessing the response to neoadjuvant chemotherapy and radiation therapy in locally advanced rectal cancer. Eur J Radiol 110:249\u2013255 doi:https:\/\/doi.org\/10.1016\/j.ejrad.2018.12.005.","journal-title":"Eur J Radiol"},{"key":"4588_CR33","doi-asserted-by":"publisher","first-page":"446","DOI":"10.1148\/radiol.2016150702","volume":"280","author":"S Nougaret","year":"2016","unstructured":"Nougaret S, Vargas HA, Lakhman Y et al (2016) Intravoxel Incoherent Motion-derived Histogram Metrics for Assessment of Response after Combined Chemotherapy and Radiation Therapy in Rectal Cancer: Initial Experience and Comparison between Single-Section and Volumetric Analyses. Radiology 280:446\u2013454 doi:https:\/\/doi.org\/10.1148\/radiol.2016150702.","journal-title":"Radiology"},{"key":"4588_CR34","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1016\/j.mri.2021.09.003","volume":"95","author":"J Chen","year":"2023","unstructured":"Chen J, Guo Y, Guo Y et al (2023) Preoperative assessment of microvascular invasion of hepatocellular carcinoma using non-Gaussian diffusion-weighted imaging with a fractional order calculus model: A pilot study. Magn Reson Imaging 95:110\u2013117 doi:https:\/\/doi.org\/10.1016\/j.mri.2021.09.003.","journal-title":"Magn Reson Imaging"},{"key":"4588_CR35","doi-asserted-by":"publisher","first-page":"489","DOI":"10.1148\/radiol.2015142156","volume":"277","author":"Y Sui","year":"2015","unstructured":"Sui Y, Wang H, Liu G et al (2015) Differentiation of Low- and High-Grade Pediatric Brain Tumors with High b-Value Diffusion-weighted MR Imaging and a Fractional Order Calculus Model. Radiology 277:489\u2013496 doi:https:\/\/doi.org\/10.1148\/radiol.2015142156.","journal-title":"Radiology"},{"key":"4588_CR36","doi-asserted-by":"publisher","first-page":"348","DOI":"10.3390\/math7040348","volume":"7","author":"RL Magin","year":"2019","unstructured":"Magin RL, Karani H, Wang S, Liang Y (2019) Fractional Order Complexity Model of the Diffusion Signal Decay in MRI. Mathematics 7:348","journal-title":"Mathematics"},{"key":"4588_CR37","doi-asserted-by":"publisher","first-page":"2726","DOI":"10.1007\/s00330-016-4630-x","volume":"27","author":"R Bedair","year":"2017","unstructured":"Bedair R, Priest AN, Patterson AJ et al (2017) Assessment of early treatment response to neoadjuvant chemotherapy in breast cancer using non-mono-exponential diffusion models: a feasibility study comparing the baseline and mid-treatment MRI examinations. Eur Radiol 27:2726\u20132736 doi:https:\/\/doi.org\/10.1007\/s00330-016-4630-x.","journal-title":"Eur Radiol"},{"key":"4588_CR38","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1148\/radiol.2019181042","volume":"291","author":"Z Zhong","year":"2019","unstructured":"Zhong Z, Merkitch D, Karaman MM et al (2019) High-Spatial-Resolution Diffusion MRI in Parkinson Disease: Lateral Asymmetry of the Substantia Nigra. Radiology 291:149\u2013157 doi:https:\/\/doi.org\/10.1148\/radiol.2019181042.","journal-title":"Radiology"},{"key":"4588_CR39","doi-asserted-by":"publisher","first-page":"5171","DOI":"10.21037\/qims-22-145","volume":"12","author":"J Xu","year":"2022","unstructured":"Xu J, Ren Y, Zhao X et al (2022) Incorporating multiple magnetic resonance diffusion models to differentiate low- and high-grade adult gliomas: a machine learning approach. Quant Imaging Med Surg 12:5171\u20135183 doi:https:\/\/doi.org\/10.21037\/qims-22-145.","journal-title":"Quant Imaging Med Surg"},{"key":"4588_CR40","doi-asserted-by":"publisher","first-page":"109913","DOI":"10.1016\/j.ejrad.2021.109913","volume":"143","author":"Z Li","year":"2021","unstructured":"Li Z, Dan G, Tammana V et al (2021) Predicting the aggressiveness of peripheral zone prostate cancer using a fractional order calculus diffusion model. Eur J Radiol 143:109913 doi:https:\/\/doi.org\/10.1016\/j.ejrad.2021.109913.","journal-title":"Eur J Radiol"},{"key":"4588_CR41","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1002\/jmri.25567","volume":"46","author":"HB Zhu","year":"2017","unstructured":"Zhu HB, Zhang XY, Zhou XH et al (2017) Assessment of pathological complete response to preoperative chemoradiotherapy by means of multiple mathematical models of diffusion-weighted MRI in locally advanced rectal cancer: A prospective single-center study. J Magn Reson Imaging 46:175\u2013183 doi:https:\/\/doi.org\/10.1002\/jmri.25567.","journal-title":"J Magn Reson Imaging"},{"key":"4588_CR42","doi-asserted-by":"publisher","unstructured":"Zhou M, Pu H, Chen MN, Wang YT (2023) Feasibility of Simultaneous Multislice Acceleration Technique in Readout-Segmented Echo-Planar Diffusion-Weighted Imaging for Assessing Rectal Cancer. Diagnostics (Basel) 13: doi:https:\/\/doi.org\/10.3390\/diagnostics13030474.","DOI":"10.3390\/diagnostics13030474"},{"key":"4588_CR43","doi-asserted-by":"publisher","first-page":"458","DOI":"10.1097\/sla.0000000000000368","volume":"263","author":"F Petrelli","year":"2016","unstructured":"Petrelli F, Sgroi G, Sarti E, Barni S (2016) Increasing the Interval Between Neoadjuvant Chemoradiotherapy and Surgery in Rectal Cancer: A Meta-analysis of Published Studies. Annals of surgery 263:458\u2013464 doi:https:\/\/doi.org\/10.1097\/sla.0000000000000368.","journal-title":"Annals of surgery"}],"container-title":["Abdominal Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00261-024-04588-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00261-024-04588-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00261-024-04588-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,13]],"date-time":"2025-02-13T13:23:55Z","timestamp":1739453035000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00261-024-04588-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,14]]},"references-count":43,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2025,3]]}},"alternative-id":["4588"],"URL":"https:\/\/doi.org\/10.1007\/s00261-024-04588-y","relation":{},"ISSN":["2366-0058"],"issn-type":[{"value":"2366-0058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,14]]},"assertion":[{"value":"10 August 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 September 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 September 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 September 2024","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"}}]}}