ORIGINAL RESEARCH article
Front. Oncol.
Sec. Cancer Imaging and Image-directed Interventions
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1551224
Baseline MRI habitat imaging for predicting treatment response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer
Provisionally accepted
- 1Department of Radiology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, China
- 2Department of Gastrointestinal Surgery, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, China
- 3MR Scientific Markerting, Siemens Healthineers Ltd, Shanghai, China
- 4Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China
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Purpose: This study was to assess whether baseline magnetic resonance habitat imaging can predict the efficacy of neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC).Methods: This retrospective study analyzed data from 181 patients with locally advanced rectal cancer, including 60 who exhibited a good treatment response. The cohort was randomly divided into a training set (127 patients, 42 with good response) and a validation set (54 patients, 18 with good response). Five models were developed: ModelClinic, ModelRadiomics, ModelHabitat, ModelClinic+Radiomics, and ModelClinic+Habitat.Model performance was assessed using the area under the receiver operating characteristic (ROC) curve (AUC) for both training and validation sets.The AUC values for predicting the efficacy of LARC neoadjuvant therapy were as follows: in the training set, ModelClinic achieved 0.788, ModelRadiomics 0.827, ModelHabitat 0.815, ModelClinic+Radiomics 0.938, and ModelClinic+Habitat 0.896; in the test set, the corresponding AUCs were 0.656, 0.619, 0.636, 0.532, and 0.710, respectively.Decision curve analysis demonstrated that the clinical combined habitat model (ModelClinic+Habitat) provided higher net benefits than other models within a threshold probability range of 20% to 80%.The habitat model we developed, which integrates first-order and clinical features, demonstrates potential for predicting the efficacy of nCRT clinically interpretable spatial heterogeneity information. This model may aid in personalized treatment decision-making for LARC.
Keywords: habitat, Locally advanced rectal cancer (LARC), Neoadjuvant chemoradiotherapy (NCRT), Radiomics, magnetic resonance imaging (MRI)
Received: 25 Dec 2024; Accepted: 25 Jun 2025.
Copyright: © 2025 He, Chen, Wu, Xu, Lin, Song, Yang, Ma and Xue. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Fangqin Xue, Department of Gastrointestinal Surgery, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, China
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