MRI radiomics prediction modelling for pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a systematic review and meta-analysis.
Purpose: Predicting response to neoadjuvant therapy in locally advanced rectal cancer (LARC) is challenging. Organ preservation strategies can be offered to patients with complete clinical response. We aim to evaluate MRI-derived radiomics models in predicting complete pathological response (pCR). M...
| Publicado en: | Abdominal Radiology Vol. 50; no. 11; pp. 5103 - 5124 |
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| Autores principales: | , , , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Nov2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=188952012&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 188952012 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 2366004X JT14 jtl: Abdominal Radiology issn: 2366004X maglogo: N pubinfo: dt: Nov2025 vid: 50 iid: 11 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 188952012 184781544 10.1007/s00261-025-04953-5 188952012 ppf: 5103 ppct: 21 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: MRI radiomics prediction modelling for pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a systematic review and meta-analysis. aug: au: Rai, Jason Mai, Dinh V. C. Drami, Ioanna Pring, Edward T. Gould, Laura E. Lung, Phillip F. C. Glover, Thomas Shur, Joshua D. Whitcher, Brandon Athanasiou, Thanos Jenkins, John T. affil: https://ror.org/05am5g719 BiCyCLE Research Group, St Mark's the National Bowel Hospital, London, UK sug: ab: Purpose: Predicting response to neoadjuvant therapy in locally advanced rectal cancer (LARC) is challenging. Organ preservation strategies can be offered to patients with complete clinical response. We aim to evaluate MRI-derived radiomics models in predicting complete pathological response (pCR). Methods: Search included MEDLINE, Embase and Cochrane Central Register of Controlled Trials (CENTRAL) and Cochrane Database of Systematic Reviews (CDSR) for studies published before 1st February 2024. The Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) and Radiomics Quality Score (RQS) tools were used to assess quality of included study. The research protocol was registered in PROSPERO (CRD42024512865). We calculated pooled area under the receiver operating characteristic curve (AUC) using a random-effects model. To compare AUC between subgroups the Hanley & McNeil test was performed. Results: Forty-four eligible studies (12,714 patients) were identified for inclusion in the systematic review. We selected thirty-five studies including 10,543 patients for meta-analysis. The pooled AUC for MRI radiomics predicted pCR in LARC was 0.87 (95% CI 0.84–0.89). In the subgroup analysis 3 T MRI field intensity had higher pooled AUC 0.9 (95% CI 0.87–0.94) than 1.5 T pooled AUC 0.82 (95% CI 0.80–0.83) p < 0.001. Asian ethnicity had higher pooled AUC 0.9 (95% CI 0.87–0.93) than non-Asian pooled AUC 0.8 (95% CI 0.75–0.84) p < 0.001. Conclusion: We have demonstrated that 3 T MRI field intensity provides a superior predictive performance. The role of ethnicity on radiomics features needs to be explored in future studies. Further research in the field of MRI radiomics is important as accurate prediction for pCR can lead to organ preservation strategy in LARC. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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