Spandidos Publications Logo
  • About
    • About Spandidos
    • Aims and Scopes
    • Abstracting and Indexing
    • Editorial Policies
    • Reprints and Permissions
    • Job Opportunities
    • Terms and Conditions
    • Contact
  • Journals
    • All Journals
    • Oncology Letters
      • Oncology Letters
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
    • International Journal of Oncology
      • International Journal of Oncology
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
    • Molecular and Clinical Oncology
      • Molecular and Clinical Oncology
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
    • Experimental and Therapeutic Medicine
      • Experimental and Therapeutic Medicine
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
    • International Journal of Molecular Medicine
      • International Journal of Molecular Medicine
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
    • Biomedical Reports
      • Biomedical Reports
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
    • Oncology Reports
      • Oncology Reports
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
    • Molecular Medicine Reports
      • Molecular Medicine Reports
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
    • World Academy of Sciences Journal
      • World Academy of Sciences Journal
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
    • International Journal of Functional Nutrition
      • International Journal of Functional Nutrition
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
    • International Journal of Epigenetics
      • International Journal of Epigenetics
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
    • Medicine International
      • Medicine International
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
  • Articles
  • Information
    • Information for Authors
    • Information for Reviewers
    • Information for Librarians
    • Information for Advertisers
    • Conferences
  • Language Editing
Spandidos Publications Logo
  • About
    • About Spandidos
    • Aims and Scopes
    • Abstracting and Indexing
    • Editorial Policies
    • Reprints and Permissions
    • Job Opportunities
    • Terms and Conditions
    • Contact
  • Journals
    • All Journals
    • Biomedical Reports
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
    • Experimental and Therapeutic Medicine
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
    • International Journal of Epigenetics
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
    • International Journal of Functional Nutrition
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
    • International Journal of Molecular Medicine
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
    • International Journal of Oncology
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
    • Medicine International
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
    • Molecular and Clinical Oncology
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
    • Molecular Medicine Reports
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
    • Oncology Letters
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
    • Oncology Reports
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
    • World Academy of Sciences Journal
      • Information for Authors
      • Editorial Policies
      • Editorial Board
      • Aims and Scope
      • Abstracting and Indexing
      • Bibliographic Information
      • Archive
  • Articles
  • Information
    • For Authors
    • For Reviewers
    • For Librarians
    • For Advertisers
    • Conferences
  • Language Editing
Login Register Submit
  • This site uses cookies
  • You can change your cookie settings at any time by following the instructions in our Cookie Policy. To find out more, you may read our Privacy Policy.

    I agree
Search articles by DOI, keyword, author or affiliation
Search
Advanced Search
presentation
Oncology Letters
Join Editorial Board Propose a Special Issue
Print ISSN: 1792-1074 Online ISSN: 1792-1082
Journal Cover
November-2025 Volume 30 Issue 5

Full Size Image

Sign up for eToc alerts
Recommend to Library

Journals

International Journal of Molecular Medicine

International Journal of Molecular Medicine

International Journal of Molecular Medicine is an international journal devoted to molecular mechanisms of human disease.

International Journal of Oncology

International Journal of Oncology

International Journal of Oncology is an international journal devoted to oncology research and cancer treatment.

Molecular Medicine Reports

Molecular Medicine Reports

Covers molecular medicine topics such as pharmacology, pathology, genetics, neuroscience, infectious diseases, molecular cardiology, and molecular surgery.

Oncology Reports

Oncology Reports

Oncology Reports is an international journal devoted to fundamental and applied research in Oncology.

Experimental and Therapeutic Medicine

Experimental and Therapeutic Medicine

Experimental and Therapeutic Medicine is an international journal devoted to laboratory and clinical medicine.

Oncology Letters

Oncology Letters

Oncology Letters is an international journal devoted to Experimental and Clinical Oncology.

Biomedical Reports

Biomedical Reports

Explores a wide range of biological and medical fields, including pharmacology, genetics, microbiology, neuroscience, and molecular cardiology.

Molecular and Clinical Oncology

Molecular and Clinical Oncology

International journal addressing all aspects of oncology research, from tumorigenesis and oncogenes to chemotherapy and metastasis.

World Academy of Sciences Journal

World Academy of Sciences Journal

Multidisciplinary open-access journal spanning biochemistry, genetics, neuroscience, environmental health, and synthetic biology.

International Journal of Functional Nutrition

International Journal of Functional Nutrition

Open-access journal combining biochemistry, pharmacology, immunology, and genetics to advance health through functional nutrition.

International Journal of Epigenetics

International Journal of Epigenetics

Publishes open-access research on using epigenetics to advance understanding and treatment of human disease.

Medicine International

Medicine International

An International Open Access Journal Devoted to General Medicine.

Journal Cover
November-2025 Volume 30 Issue 5

Full Size Image

Sign up for eToc alerts
Recommend to Library

  • Article
  • Citations
    • Cite This Article
    • Download Citation
    • Create Citation Alert
    • Remove Citation Alert
    • Cited By
  • Similar Articles
    • Related Articles (in Spandidos Publications)
    • Similar Articles (Google Scholar)
    • Similar Articles (PubMed)
  • Download PDF
  • Download XML
  • View XML
Article Open Access

Progress of MRI‑based radiomics and deep learning for predicting the prognosis of locally advanced rectal cancer (Review)

  • Authors:
    • Yuting Shi
    • Qiuhan Huang
    • Jiali Lyu
    • Tianjie Dong
    • Jihong Sun
  • View Affiliations / Copyright

    Affiliations: School of Medicine, Shaoxing University, Shaoxing, Zhejiang 312000, P.R. China, Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310016, P.R. China
    Copyright: © Shi et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Article Number: 536
    |
    Published online on: September 19, 2025
       https://doi.org/10.3892/ol.2025.15282
  • Expand metrics +
Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )
Metrics: Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )
Cited By (CrossRef): 0 citations Loading Articles...

This article is mentioned in:



Abstract

Rectal cancer (RC) ranks among the most common malignant tumors worldwide, with ~30% of patients presenting at a locally advanced stage at the time of diagnosis. The standard treatment for locally advanced RC (LARC) combines neoadjuvant chemoradiotherapy (nCRT) with total mesorectal excision. While this treatment paradigm has been effective in reducing the local recurrence rate, its efficacy in enhancing overall survival and disease‑free survival is still limited. Consequently, the identification of adverse prognostic factors in patients with LARC is crucial for improving long‑term survival outcomes. Traditional imaging methods offer limited predictive power for early diagnosis, treatment efficacy assessment and prognosis in LARC. Recent advancements in MRI‑based radiomics and deep learning (DL), leveraging high‑dimensional feature extraction and nonlinear modeling, have markedly enhanced prognostic predictive performance. Single‑sequence MRI radiomics models derived from pre‑nCRT imaging demonstrate areas under the curve (AUC) of 0.79‑0.87 for predicting local recurrence and distant metastasis. Multiparametric radiomic models further improve predictive accuracy, achieving AUCs of 0.81‑0.83. Delta radiomics, which captures temporal‑spatial heterogeneity evolution in tumors during therapy, elevates AUC performance to 0.77‑0.89. Notably, DL‑based models exhibit superior and more stable predictive capabilities, with concordance indices (C‑indices) ranging from 0.82 to 0.94. This paper reviews recent progress in MRI‑based radiomics and DL for predicting the prognosis of patients with LARC subjected to nCRT.
View Figures
View References

1 

Siegel RL, Wagle NS, Cercek A, Smith RA and Jemal A: Colorectal cancer statistics, 2023. CA Cancer J Clin. 73:233–254. 2023.PubMed/NCBI

2 

Morgan E, Arnold M, Gini A, Lorenzoni V, Cabasag CJ, Laversanne M, Vignat J, Ferlay J, Murphy N and Bray F: Global burden of colorectal cancer in 2020 and 2040: Incidence and mortality estimates from GLOBOCAN. Gut. 72:338–344. 2023. View Article : Google Scholar : PubMed/NCBI

3 

Staal FCR, van der Reijd DJ, Taghavi M, Lambregts DMJ, Beets-Tan RGH and Maas M: Radiomics for the prediction of treatment outcome and survival in patients with colorectal cancer: A systematic review. Clin Colorectal Cancer. 20:52–71. 2021.PubMed/NCBI

4 

Aklilu M and Eng C: The current landscape of locally advanced rectal cancer. Nat Rev Clin Oncol. 8:649–659. 2011. View Article : Google Scholar : PubMed/NCBI

5 

Benson AB, Venook AP, Al-Hawary MM, Arain MA, Chen YJ, Ciombor KK, Cohen S, Cooper HS, Deming D, Garrido-Laguna I, et al: NCCN guidelines insights: Rectal cancer, version 6.2020. J Natl Compr Canc Netw. 18:806–815. 2020. View Article : Google Scholar : PubMed/NCBI

6 

van der Valk MJM, Hilling DE, Bastiaannet E, Kranenbarg EMK, Beets GL, Figueiredo NL, Habr-Gama A, Perez RO, Renehan AG and van de Velde CJH; IWWD Consortium, : Long-term outcomes of clinical complete responders after neoadjuvant treatment for rectal cancer in the International watch & wait database (IWWD): An international multicentre registry study. Lancet. 391:2537–2545. 2018. View Article : Google Scholar : PubMed/NCBI

7 

Gauci C, Ravindran P, Pillinger S and Lynch AC: Robotic surgery for multi-visceral resection in locally advanced colorectal cancer: Techniques, benefits and future directions. Laparoscopic, Endoscopic and Robotic Surgery. 6:123–126. 2023. View Article : Google Scholar

8 

Valentini V, van Stiphout RG, Lammering G, Gambacorta MA, Barba MC, Bebenek M, Bonnetain F, Bosset JF, Bujko K, Cionini L, et al: Selection of appropriate end-points (pCR vs 2yDFS) for tailoring treatments with prediction models in locally advanced rectal cancer. Radiother Oncol. 114:302–309. 2015. View Article : Google Scholar : PubMed/NCBI

9 

Fokas E, Liersch T, Fietkau R, Hohenberger W, Beissbarth T, Hess C, Becker H, Ghadimi M, Mrak K, Merkel S, et al: Tumor regression grading after preoperative chemoradiotherapy for locally advanced rectal carcinoma revisited: Updated results of the CAO/ARO/AIO-94 trial. J Clin Oncol. 32:1554–1562. 2014. View Article : Google Scholar : PubMed/NCBI

10 

van Gijn W, Marijnen CA, Nagtegaal ID, Kranenbarg EM, Putter H, Wiggers T, Rutten HJ, Påhlman L, Glimelius B and van de Velde CJ; Dutch Colorectal Cancer Group, : Preoperative radiotherapy combined with total mesorectal excision for resectable rectal cancer: 12-year follow-up of the multicentre, randomised controlled TME trial. Lancet Oncol. 12:575–582. 2011. View Article : Google Scholar : PubMed/NCBI

11 

Glynne-Jones R, Wyrwicz L, Tiret E, Brown G, Rödel C, Cervantes A and Arnold D; ESMO Guidelines Committee, : Rectal cancer: ESMO clinical practice guidelines for diagnosis, treatment and follow-up. Ann Oncol. 28:iv22–iv40. 2017. View Article : Google Scholar : PubMed/NCBI

12 

Cabezón-Gutiérrez L, Custodio-Cabello S, Palka-Kotlowska M, Díaz-Pérez D, Mateos-Dominguez M and Galindo-Jara P: Neoadjuvant immunotherapy for dMMR/MSI-H locally advanced rectal cancer: The future new standard approach? Eur J Surg Oncol. 49:323–328. 2023. View Article : Google Scholar : PubMed/NCBI

13 

Cercek A, Lumish M, Sinopoli J, Weiss J, Shia J, Lamendola-Essel M, El Dika IH, Segal N, Shcherba M, Sugarman R, et al: PD-1 blockade in mismatch repair-deficient, locally advanced rectal cancer. N Engl J Med. 386:2363–2376. 2022. View Article : Google Scholar : PubMed/NCBI

14 

Yang R, Wu T, Yu J, Cai X, Li G, Li X, Huang W, Zhang Y, Wang Y, Yang X, et al: Locally advanced rectal cancer with dMMR/MSI-H may be excused from surgery after neoadjuvant anti-PD-1 monotherapy: A multiple-center, cohort study. Front Immunol. 14:11822992023. View Article : Google Scholar : PubMed/NCBI

15 

Bahadoer RR, Dijkstra EA, van Etten B, Marijnen CAM, Putter H, Kranenbarg EM, Roodvoets AGH, Nagtegaal ID, Beets-Tan RGH, Blomqvist LK, et al: Short-course radiotherapy followed by chemotherapy before total mesorectal excision (TME) versus preoperative chemoradiotherapy, TME, and optional adjuvant chemotherapy in locally advanced rectal cancer (RAPIDO): A randomised, open-label, phase 3 trial. Lancet Oncol. 22:29–42. 2021. View Article : Google Scholar : PubMed/NCBI

16 

Conroy T, Bosset JF, Etienne PL, Rio E, François É, Mesgouez-Nebout N, Vendrely V, Artignan X, Bouché O, Gargot D, et al: Neoadjuvant chemotherapy with FOLFIRINOX and preoperative chemoradiotherapy for patients with locally advanced rectal cancer (UNICANCER-PRODIGE 23): A multicentre, randomised, open-label, phase 3 trial. Lancet Oncol. 22:702–715. 2021. View Article : Google Scholar : PubMed/NCBI

17 

Zwart WH, Temmink SJD, Hospers GAP, Marijnen CAM, Putter H, Nagtegaal ID, Blomqvist L, Kranenbarg EM, Roodvoets AGH, Martling A, et al: Oncological outcomes after a pathological complete response following total neoadjuvant therapy or chemoradiotherapy for high-risk locally advanced rectal cancer in the RAPIDO trial. Eur J Cancer. 204:1140442024. View Article : Google Scholar : PubMed/NCBI

18 

Conroy T, Castan F, Etienne PL, Rio E, Mesgouez-Nebout N, Evesque L, Vendrely V, Artignan X, Bouché O, Gargot D, et al: Total neoadjuvant therapy with mFOLFIRINOX versus preoperative chemoradiotherapy in patients with locally advanced rectal cancer: Long-term results of the UNICANCER-PRODIGE 23 trial. Ann Oncol. 35:873–881. 2024. View Article : Google Scholar : PubMed/NCBI

19 

Dijkstra EA, Nilsson PJ, Hospers GAP, Bahadoer RR, Kranenbarg EMK, Roodvoets AGH, Putter H, Berglund Å, Cervantes A, Crolla R, et al: Locoregional failure during and after short-course radiotherapy followed by chemotherapy and surgery compared with long-course chemoradiotherapy and surgery: A 5-year follow-up of the RAPIDO trial. Ann Surg. 278:e766–e772. 2023. View Article : Google Scholar : PubMed/NCBI

20 

Valentini V, van Stiphout RG, Lammering G, Gambacorta MA, Barba MC, Bebenek M, Bonnetain F, Bosset JF, Bujko K, Cionini L, et al: Nomograms for predicting local recurrence, distant metastases, and overall survival for patients with locally advanced rectal cancer on the basis of European randomized clinical trials. J Clin Oncol. 29:3163–3172. 2011. View Article : Google Scholar : PubMed/NCBI

21 

Sun Y, Lin H, Lu X, Huang Y, Xu Z, Huang S, Wang X and Chi P: A nomogram to predict distant metastasis after neoadjuvant chemoradiotherapy and radical surgery in patients with locally advanced rectal cancer. J Surg Oncol. 115:462–469. 2017. View Article : Google Scholar : PubMed/NCBI

22 

Merkel S, Weber K, Schellerer V, Göhl J, Fietkau R, Agaimy A, Hohenberger W and Hermanek P: Prognostic subdivision of ypT3 rectal tumours according to extension beyond the muscularis propria. Br J Surg. 101:566–572. 2014. View Article : Google Scholar : PubMed/NCBI

23 

Park IJ, You YN, Agarwal A, Skibber JM, Rodriguez-Bigas MA, Eng C, Feig BW, Das P, Krishnan S, Crane CH, et al: Neoadjuvant treatment response as an early response indicator for patients with rectal cancer. J Clin Oncol. 30:1770–1776. 2012. View Article : Google Scholar : PubMed/NCBI

24 

Bera K, Katz I and Madabhushi A: Reimagining T staging through artificial intelligence and machine learning image processing approaches in digital pathology. JCO Clin Cancer Inform. 4:1039–1050. 2020. View Article : Google Scholar : PubMed/NCBI

25 

Patel UB, Taylor F, Blomqvist L, George C, Evans H, Tekkis P, Quirke P, Sebag-Montefiore D, Moran B, Heald R, et al: Magnetic resonance imaging-detected tumor response for locally advanced rectal cancer predicts survival outcomes: MERCURY experience. J Clin Oncol. 29:3753–3760. 2011. View Article : Google Scholar : PubMed/NCBI

26 

De Mattia E, Polesel J, Mezzalira S, Palazzari E, Pollesel S, Toffoli G and Cecchin E: Predictive and prognostic value of oncogene mutations and microsatellite instability in locally-advanced rectal cancer treated with neoadjuvant radiation-based therapy: A systematic review and meta-analysis. Cancers (Basel). 15:14692023. View Article : Google Scholar : PubMed/NCBI

27 

Watanabe T, Kobunai T, Yamamoto Y, Matsuda K, Ishihara S, Nozawa K, Iinuma H, Shibuya H and Eshima K: Heterogeneity of KRAS status may explain the subset of discordant KRAS status between primary and metastatic colorectal cancer. Dis Colon Rectum. 54:1170–1178. 2011. View Article : Google Scholar : PubMed/NCBI

28 

Ciocan RA, Ciocan A, Mihăileanu FV, Ursu CP, Ursu Ș, Bodea C, Cordoș AA, Chiș BA, Al Hajjar N, Dîrzu N and Dîrzu DS: Metabolic signatures: Pioneering the frontier of rectal cancer diagnosis and response to neoadjuvant treatment with biomarkers-a systematic review. Int J Mol Sci. 25:23812024. View Article : Google Scholar : PubMed/NCBI

29 

Raman SP, Chen Y and Fishman EK: Evolution of imaging in rectal cancer: Multimodality imaging with MDCT, MRI, and PET. J Gastrointest Oncol. 6:172–184. 2015.PubMed/NCBI

30 

Kinkel K, Lu Y, Both M, Warren RS and Thoeni RF: Detection of hepatic metastases from cancers of the gastrointestinal tract by using noninvasive imaging methods (US, CT, MR imaging, PET): A meta-analysis. Radiology. 224:748–756. 2002. View Article : Google Scholar : PubMed/NCBI

31 

Horvat N, Rocha CC, Oliveira BC, Petkovska I and Gollub MJ: MRI of rectal cancer: Tumor staging, imaging techniques, and management. Radiographics. 39:367–387. 2019. View Article : Google Scholar : PubMed/NCBI

32 

Nahas SC, Nahas CS, Marques CF, Ribeiro U Jr, Cotti GC, Imperiale AR, Capareli FC, Chen AT, Hoff PM and Cecconello I: Pathologic complete response in rectal cancer: Can we detect it? Lessons learned from a proposed randomized trial of watch-and-wait treatment of rectal cancer. Dis Colon Rectum. 59:255–263. 2016. View Article : Google Scholar : PubMed/NCBI

33 

Smith JJ and Garcia-Aguilar J: Advances and challenges in treatment of locally advanced rectal cancer. J Clin Oncol. 33:1797–1808. 2015. View Article : Google Scholar : PubMed/NCBI

34 

Park H: Predictive factors for early distant metastasis after neoadjuvant chemoradiotherapy in locally advanced rectal cancer. World J Gastrointest Oncol. 13:252–264. 2021. View Article : Google Scholar : PubMed/NCBI

35 

Joo JI, Lim SW and Oh BY: Prognostic impact of carcinoembryonic antigen levels in rectal cancer patients who had received neoadjuvant chemoradiotherapy. Ann Coloproctol. 37:179–185. 2021. View Article : Google Scholar : PubMed/NCBI

36 

Smith N and Brown G: Preoperative staging of rectal cancer. Acta Oncol. 47:20–31. 2008. View Article : Google Scholar : PubMed/NCBI

37 

Smith NJ, Barbachano Y, Norman AR, Swift RI, Abulafi AM and Brown G: Prognostic significance of magnetic resonance imaging-detected extramural vascular invasion in rectal cancer. Br J Surg. 95:229–236. 2008. View Article : Google Scholar : PubMed/NCBI

38 

Nougaret S, Reinhold C, Mikhael HW, Rouanet P, Bibeau F and Brown G: The use of MR imaging in treatment planning for patients with rectal carcinoma: have you checked the ‘DISTANCE’? Radiology. 268:330–344. 2013. View Article : Google Scholar : PubMed/NCBI

39 

Nougaret S, Gormly K, Lambregts DMJ, Reinhold C, Goh V, Korngold E, Denost Q and Brown G: MRI of the rectum: A decade into DISTANCE, moving to DISTANCED. Radiology. 314:e2328382025. View Article : Google Scholar : PubMed/NCBI

40 

Hosny A, Parmar C, Quackenbush J, Schwartz LH and Aerts H: Artificial intelligence in radiology. Nat Rev Cancer. 18:500–510. 2018. View Article : Google Scholar : PubMed/NCBI

41 

Bi WL, Hosny A, Schabath MB, Giger ML, Birkbak NJ, Mehrtash A, Allison T, Arnaout O, Abbosh C, Dunn IF, et al: Artificial intelligence in cancer imaging: Clinical challenges and applications. CA Cancer J Clin. 69:127–157. 2019.PubMed/NCBI

42 

Wang J, Shen L, Zhong H, Zhou Z, Hu P, Gan J, Luo R, Hu W and Zhang Z: Radiomics features on radiotherapy treatment planning CT can predict patient survival in locally advanced rectal cancer patients. Sci Rep. 9:153462019. View Article : Google Scholar : PubMed/NCBI

43 

Bundschuh RA, Dinges J, Neumann L, Seyfried M, Zsótér N, Papp L, Rosenberg R, Becker K, Astner ST, Henninger M, et al: Textural parameters of tumor heterogeneity in 18F-FDG PET/CT for therapy response assessment and prognosis in patients with locally advanced rectal cancer. J Nucl Med. 55:891–897. 2014. View Article : Google Scholar : PubMed/NCBI

44 

Bang JI, Ha S, Kang SB, Lee KW, Lee HS, Kim JS, Oh HK, Lee HY and Kim SE: Prediction of neoadjuvant radiation chemotherapy response and survival using pretreatment [(18)F]FDG PET/CT scans in locally advanced rectal cancer. Eur J Nucl Med Mol Imaging. 43:422–431. 2016. View Article : Google Scholar : PubMed/NCBI

45 

Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, Shamseer L, Tetzlaff JM, Akl EA, Brennan SE, et al: The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ. 372:n712021. View Article : Google Scholar : PubMed/NCBI

46 

Lambin P, Rios-Velazquez E, Leijenaar R, Carvalho S, van Stiphout RG, Granton P, Zegers CM, Gillies R, Boellard R, Dekker A and Aerts HJ: Radiomics: Extracting more information from medical images using advanced feature analysis. Eur J Cancer. 48:441–446. 2012. View Article : Google Scholar : PubMed/NCBI

47 

Scapicchio C, Gabelloni M, Barucci A, Cioni D, Saba L and Neri E: A deep look into radiomics. Radiol Med. 126:1296–1311. 2021. View Article : Google Scholar : PubMed/NCBI

48 

Floca R, Bohn J, Haux C, Wiestler B, Zöllner FG, Reinke A, Weiß J, Nolden M, Albert S, Persigehl T, et al: Radiomics workflow definition & challenges-German priority program 2177 consensus statement on clinically applied radiomics. Insights Imaging. 15:1242024. View Article : Google Scholar : PubMed/NCBI

49 

Lin M, Tang X, Cao L, Liao Y, Zhang Y and Zhou J: Using ultrasound radiomics analysis to diagnose cervical lymph node metastasis in patients with nasopharyngeal carcinoma. Eur Radiol. 33:774–783. 2023. View Article : Google Scholar : PubMed/NCBI

50 

Ghosh A, Yekeler E, Teixeira SR, Dalal D and States L: Role of MRI radiomics for the prediction of MYCN amplification in neuroblastomas. Eur Radiol. 33:6726–6735. 2023. View Article : Google Scholar : PubMed/NCBI

51 

Xie F, Zhao Q, Li S, Wu S, Li J, Li H, Chen S, Jiang W, Dong A, Wu L, et al: Establishment and validation of novel MRI radiomic feature-based prognostic models to predict progression-free survival in locally advanced rectal cancer. Front Oncol. 12:9012872022. View Article : Google Scholar : PubMed/NCBI

52 

Chiloiro G, Cusumano D, Romano A, Boldrini L, Nicolì G, Votta C, Tran HE, Barbaro B, Carano D, Valentini V, et al: Delta radiomic analysis of mesorectum to predict treatment response and prognosis in locally advanced rectal cancer. Cancers (Basel). 15:30822023. View Article : Google Scholar : PubMed/NCBI

53 

Steyerberg EW and Harrell FE Jr: Prediction models need appropriate internal, internal-external, and external validation. J Clin Epidemiol. 69:245–247. 2016. View Article : Google Scholar : PubMed/NCBI

54 

Jayaprakasam VS, Paroder V, Gibbs P, Bajwa R, Gangai N, Sosa RE, Petkovska I, Pernicka JS, Fuqua JL III, Bates DDB, 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. 32:971–980. 2022. View Article : Google Scholar : PubMed/NCBI

55 

Cui Y, Yang W, Ren J, Li D, Du X, Zhang J and Yang X: Prognostic value of multiparametric MRI-based radiomics model: Potential role for chemotherapeutic benefits in locally advanced rectal cancer. Radiother Oncol. 154:161–169. 2021. View Article : Google Scholar : PubMed/NCBI

56 

Huang H, Han L, Guo J, Zhang Y, Lin S, Chen S, Lin X, Cheng C, Guo Z and Qiu Y: Pretreatment MRI-based radiomics for prediction of rectal cancer outcome: A discovery and validation study. Acad Radiol. 31:1878–1888. 2024. View Article : Google Scholar : PubMed/NCBI

57 

Liu Z, Meng X, Zhang H, Li Z, Liu J, Sun K, Meng Y, Dai W, Xie P, Ding Y, et al: Predicting distant metastasis and chemotherapy benefit in locally advanced rectal cancer. Nat Commun. 11:43082020. View Article : Google Scholar : PubMed/NCBI

58 

Wei Q, Chen L, Hou X, Lin Y, Xie R, Yu X, Zhang H, Wen Z, Wu Y, Liu X and Chen W: Multiparametric MRI-based radiomic model for predicting lymph node metastasis after neoadjuvant chemoradiotherapy in locally advanced rectal cancer. Insights Imaging. 15:1632024. View Article : Google Scholar : PubMed/NCBI

59 

Tibermacine H, Rouanet P, Sbarra M, Forghani R, Reinhold C and Nougaret S; GRECCAR Study Group, : Radiomics modelling in rectal cancer to predict disease-free survival: Evaluation of different approaches. Br J Surg. 108:1243–1250. 2021. View Article : Google Scholar : PubMed/NCBI

60 

Jalil O, Afaq A, Ganeshan B, Patel UB, Boone D, Endozo R, Groves A, Sizer B and Arulampalam T: Magnetic resonance based texture parameters as potential imaging biomarkers for predicting long-term survival in locally advanced rectal cancer treated by chemoradiotherapy. Colorectal Dis. 19:349–362. 2017. View Article : Google Scholar : PubMed/NCBI

61 

Dinapoli N, Barbaro B, Gatta R, Chiloiro G, Casà C, Masciocchi C, Damiani A, Boldrini L, Gambacorta MA, Dezio M, et al: Magnetic resonance, vendor-independent, intensity histogram analysis predicting pathologic complete response after radiochemotherapy of rectal cancer. Int J Radiat Oncol Biol Phys. 102:765–774. 2018. View Article : Google Scholar : PubMed/NCBI

62 

Jeon SH, Song C, Chie EK, Kim B, Kim YH, Chang W, Lee YJ, Chung JH, Chung JB, Lee KW, et al: Delta-radiomics signature predicts treatment outcomes after preoperative chemoradiotherapy and surgery in rectal cancer. Radiat Oncol. 14:432019. View Article : Google Scholar : PubMed/NCBI

63 

Chiloiro G, Rodriguez-Carnero P, Lenkowicz J, Casà C, Masciocchi C, Boldrini L, Cusumano D, Dinapoli N, Meldolesi E, Carano D, et al: Delta radiomics can predict distant metastasis in locally advanced rectal cancer: The challenge to personalize the cure. Front Oncol. 10:5950122020. View Article : Google Scholar : PubMed/NCBI

64 

Chiloiro G, Boldrini L, Preziosi F, Cusumano D, Yadav P, Romano A, Placidi L, Lenkowicz J, Dinapoli N, Bassetti MF, et al: A predictive model of 2yDFS during MR-Guided RT Neoadjuvant chemoradiotherapy in locally advanced rectal cancer patients. Front Oncol. 12:8317122022. View Article : Google Scholar : PubMed/NCBI

65 

Park H, Kim KA, Jung JH, Rhie J and Choi SY: MRI features and texture analysis for the early prediction of therapeutic response to neoadjuvant chemoradiotherapy and tumor recurrence of locally advanced rectal cancer. Eur Radiol. 30:4201–4211. 2020. View Article : Google Scholar : PubMed/NCBI

66 

Miles KA, Ganeshan B and Hayball MP: CT texture analysis using the filtration-histogram method: What do the measurements mean? Cancer Imaging. 13:400–406. 2013. View Article : Google Scholar : PubMed/NCBI

67 

Hocquelet A, Auriac T, Perier C, Dromain C, Meyer M, Pinaquy JB, Denys A, Trillaud H, Senneville BD and Vendrely V: Pre-treatment magnetic resonance-based texture features as potential imaging biomarkers for predicting event free survival in anal cancer treated by chemoradiotherapy. Eur Radiol. 28:2801–2811. 2018. View Article : Google Scholar : PubMed/NCBI

68 

Wang C, Chen J, Zheng N, Zheng K, Zhou L, Zhang Q and Zhang W: Predicting the risk of distant metastasis in patients with locally advanced rectal cancer using model based on pre-treatment T2WI-based radiomic features plus postoperative pathological stage. Front Oncol. 13:11095882023. View Article : Google Scholar : PubMed/NCBI

69 

Meng Y, Zhang Y, Dong D, Li C, Liang X, Zhang C, Wan L, Zhao X, Xu K, Zhou C, et al: Novel radiomic signature as a prognostic biomarker for locally advanced rectal cancer. J Magn Reson Imaging. 13:doi: 10.1002/jmri.25968. 2018.

70 

Trebeschi S, van Griethuysen JJM, Lambregts DMJ, Lahaye MJ, Parmar C, Bakers FCH, Peters N, Beets-Tan RGH and Aerts H: Deep learning for fully-automated localization and segmentation of rectal cancer on multiparametric MR. Sci Rep. 7:53012017. View Article : Google Scholar : PubMed/NCBI

71 

Shen D, Wu G and Suk HI: Deep learning in medical image analysis. Annu Rev Biomed Eng. 19:221–248. 2017. View Article : Google Scholar : PubMed/NCBI

72 

Shin J, Seo N, Baek SE, Son NH, Lim JS, Kim NK, Koom WS and Kim S: MRI radiomics model predicts pathologic complete response of rectal cancer following chemoradiotherapy. Radiology. 303:351–358. 2022. View Article : Google Scholar : PubMed/NCBI

73 

Liu Z, Zhang XY, Shi YJ, Wang L, Zhu HT, Tang Z, Wang S, Li XT, Tian J and Sun YS: Radiomics analysis for evaluation of pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. Clin Cancer Res. 23:7253–7262. 2017. View Article : Google Scholar : PubMed/NCBI

74 

Liu X, Zhang D, Liu Z, Li Z, Xie P, Sun K, Wei W, Dai W, Tang Z, Ding Y, et al: Deep learning radiomics-based prediction of distant metastasis in patients with locally advanced rectal cancer after neoadjuvant chemoradiotherapy: A multicentre study. EBioMedicine. 69:1034422021. View Article : Google Scholar : PubMed/NCBI

75 

Jiang X, Zhao H, Saldanha OL, Nebelung S, Kuhl C, Amygdalos I, Lang SA, Wu X, Meng X, Truhn D, et al: An mri deep learning model predicts outcome in rectal cancer. Radiology. 307:e2222232023. View Article : Google Scholar : PubMed/NCBI

76 

Zhang S, Cai G, Xie P, Sun C, Li B, Dai W, Liu X, Qiu Q, Du Y, Li Z, et al: Improving prognosis and assessing adjuvant chemotherapy benefit in locally advanced rectal cancer with deep learning for MRI: A retrospective, multi-cohort study. Radiother Oncol. 188:1098992023. View Article : Google Scholar : PubMed/NCBI

77 

Najjar R: Redefining radiology: A review of artificial intelligence integration in medical imaging. Diagnostics (Basel). 13:27602023. View Article : Google Scholar : PubMed/NCBI

78 

Li ZY, Wang XD, Li M, Liu XJ, Ye Z, Song B, Yuan F, Yuan Y, Xia CC, Zhang X and Li Q: Multi-modal radiomics model to predict treatment response to neoadjuvant chemotherapy for locally advanced rectal cancer. World J Gastroenterol. 26:2388–2402. 2020. View Article : Google Scholar : PubMed/NCBI

79 

Shahzadi I, Zwanenburg A, Lattermann A, Linge A, Baldus C, Peeken JC, Combs SE, Diefenhardt M, Rödel C, Kirste S, et al: Analysis of MRI and CT-based radiomics features for personalized treatment in locally advanced rectal cancer and external validation of published radiomics models. Sci Rep. 12:101922022. View Article : Google Scholar : PubMed/NCBI

80 

Zhou B, Khosla A, Lapedriza A, Oliva A and Torralba A: Learning deep features for discriminative localization. Computer Vision and Pattern Recognition (cs.CV). 2015.https://doi.org/10.48550/arXiv.1512.04150

81 

Kazerooni AF, Kraya A, Rathi KS, Kim MC, Vossough A, Khalili N, Familiar AM, Gandhi D, Khalili N, Kesherwani V, et al: Multiparametric MRI along with machine learning predicts prognosis and treatment response in pediatric low-grade glioma. Nat Commun. 16:3402025. View Article : Google Scholar

82 

Bando H, Ohtsu A and Yoshino T: Therapeutic landscape and future direction of metastatic colorectal cancer. Nat Rev Gastroenterol Hepatol. 20:306–322. 2023. View Article : Google Scholar : PubMed/NCBI

83 

Dayde D, Tanaka I, Jain R, Tai MC and Taguchi A: Predictive and prognostic molecular biomarkers for response to neoadjuvant chemoradiation in rectal cancer. Int J Mol Sci. 18:5732017. View Article : Google Scholar : PubMed/NCBI

Related Articles

  • Abstract
  • View
  • Download
  • Twitter
Copy and paste a formatted citation
Spandidos Publications style
Shi Y, Huang Q, Lyu J, Dong T and Sun J: Progress of MRI‑based radiomics and deep learning for predicting the prognosis of locally advanced rectal cancer (Review). Oncol Lett 30: 536, 2025.
APA
Shi, Y., Huang, Q., Lyu, J., Dong, T., & Sun, J. (2025). Progress of MRI‑based radiomics and deep learning for predicting the prognosis of locally advanced rectal cancer (Review). Oncology Letters, 30, 536. https://doi.org/10.3892/ol.2025.15282
MLA
Shi, Y., Huang, Q., Lyu, J., Dong, T., Sun, J."Progress of MRI‑based radiomics and deep learning for predicting the prognosis of locally advanced rectal cancer (Review)". Oncology Letters 30.5 (2025): 536.
Chicago
Shi, Y., Huang, Q., Lyu, J., Dong, T., Sun, J."Progress of MRI‑based radiomics and deep learning for predicting the prognosis of locally advanced rectal cancer (Review)". Oncology Letters 30, no. 5 (2025): 536. https://doi.org/10.3892/ol.2025.15282
Copy and paste a formatted citation
x
Spandidos Publications style
Shi Y, Huang Q, Lyu J, Dong T and Sun J: Progress of MRI‑based radiomics and deep learning for predicting the prognosis of locally advanced rectal cancer (Review). Oncol Lett 30: 536, 2025.
APA
Shi, Y., Huang, Q., Lyu, J., Dong, T., & Sun, J. (2025). Progress of MRI‑based radiomics and deep learning for predicting the prognosis of locally advanced rectal cancer (Review). Oncology Letters, 30, 536. https://doi.org/10.3892/ol.2025.15282
MLA
Shi, Y., Huang, Q., Lyu, J., Dong, T., Sun, J."Progress of MRI‑based radiomics and deep learning for predicting the prognosis of locally advanced rectal cancer (Review)". Oncology Letters 30.5 (2025): 536.
Chicago
Shi, Y., Huang, Q., Lyu, J., Dong, T., Sun, J."Progress of MRI‑based radiomics and deep learning for predicting the prognosis of locally advanced rectal cancer (Review)". Oncology Letters 30, no. 5 (2025): 536. https://doi.org/10.3892/ol.2025.15282
Follow us
  • Twitter
  • LinkedIn
  • Facebook
About
  • Spandidos Publications
  • Careers
  • Cookie Policy
  • Privacy Policy
How can we help?
  • Help
  • Live Chat
  • Contact
  • Email to our Support Team