Clinical and radiomics prediction of complete response in rectal cancer pre-chemoradiotherapy
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Authors
Mbanu, PeterSaunders, Mark P
Mistry, Hitesh
Mercer, Joe
Malcomson, Lee
Yousif, S.
Price, Gareth J
Kochhar, Rohit
Renehan, Andrew G
van Herk, Marcel
Vasquez Osorio, Eliana
Affiliation
Department of Clinical Oncology, Christie Hospital NHS Foundation Trust, Manchester, United KingdomIssue Date
2022
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Background and purpose: Patients with rectal cancer could avoid major surgery if they achieve clinical complete response (cCR) post neoadjuvant treatment. Therefore, prediction of treatment outcomes before treatment has become necessary to select the best neo-adjuvant treatment option. This study investigates clinical and radiomics variables' ability to predict cCR in patients pre chemoradiotherapy. Materials and methods: Using the OnCoRe database, we recruited a matched cohort of 304 patients (152 with cCR; 152 without cCR) deriving training (N = 200) and validation (N = 104) sets. We collected pre-treatment MR (magnetic resonance) images, demographics and blood parameters (haemoglobin, neutrophil, lymphocyte, alkaline phosphate and albumin). We segmented the gross tumour volume on T2 Weighted MR Images and extracted 1430 stable radiomics features per patient. We used principal component analysis (PCA) and receiver operating characteristic area under the curve (ROC AUC) to reduce dimensionality and evaluate the models produced. Results: Using Logistic regression analysis, PCA-derived combined model (radiomics plus clinical variables) gave a ROC AUC of 0.76 (95% CI: 0.69-0.83) in the training set and 0.68 (95% CI 0.57-0.79) in the validation set. The clinical only model achieved an AUC of 0.73 (95% CI 0.66-0.80) and 0.62 (95% CI 0.51-0.74) in the training and validation set, respectively. The radiomics model had an AUC of 0.68 (95% CI 0.61-0.75) and 0.66 (95% CI 0.56-0.77) in the training and validation sets. Conclusion: The predictive characteristics of both clinical and radiomics variables for clinical complete response remain modest but radiomics predictability is improved with addition of clinical variables.Citation
Mbanu P, Saunders MP, Mistry H, Mercer J, Malcomson L, Yousif S, et al. Clinical and radiomics prediction of complete response in rectal cancer pre-chemoradiotherapy. Physics and imaging in radiation oncology. 2022 Jul;23:48-53. PubMed PMID: 35800297. Pubmed Central PMCID: PMC9253904. Epub 2022/07/09. eng.Journal
Physics and Imaging in Radiation OncologyDOI
10.1016/j.phro.2022.06.010PubMed ID
35800297Additional Links
https://dx.doi.org/10.1016/j.phro.2022.06.010Type
ArticleLanguage
enae974a485f413a2113503eed53cd6c53
10.1016/j.phro.2022.06.010
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