Skip to main content

ORIGINAL RESEARCH article

Front. Oncol.
Sec. Cancer Imaging and Image-directed Interventions
Volume 14 - 2024 | doi: 10.3389/fonc.2024.1418252

CT-based Habitat Radiomics for Predicting Treatment Response to Neoadjuvant Chemoimmunotherapy in Oesophageal Cancer Patients

Provisionally accepted
Weibo Kong Weibo Kong Junrui Xu Junrui Xu Yunlong Huang Yunlong Huang Kun Zhu Kun Zhu Long Yao Long Yao Kaiming Wu Kaiming Wu Hanlin Wang Hanlin Wang Yuhang Ma Yuhang Ma Qi Zhang Qi Zhang Renquan Zhang Renquan Zhang *
  • First Affiliated Hospital of Anhui Medical University, Hefei, China

The final, formatted version of the article will be published soon.

    We used habitat radiomics as an innovative tumour biomarker to predict the outcome of neoadjuvant therapy for oesophageal cancer. This was a two-centre retrospective clinical study in which pretreatment CT scans of 112 patients with oesophageal cancer treated with neoadjuvant chemoimmunotherapy and surgery between November 2020 and July 2023 were retrospectively collected from two institutions. For training (n = 85) and external testing (n = 27), patients from both institutions were allocated. We employed unsupervised methods to delineate distinct heterogeneous regions within the tumour area.To represent the prediction effect of different models, we plotted the AUC curves. The AUCs of the habitat models were 0.909 (0.8418-0.9758, 95% CI) and 0.829 (0.6423-1.0000, 95% CI) in the training and external test cohorts, respectively. The AUCs of the nomogram models were 0.914 (0.8483-0.9801, 95% CI) and 0.849 (0.6752-1.0000, 95% CI) in the training and external test cohorts, respectively. The results revealed that the model based on habitat data outperforms traditional radiomic analysis models. In addition, when the model is combined with clinical features, it improves the predictive accuracy of pathological complete response in patients undergoing neoadjuvant chemoimmunotherapy.

    Keywords: ：oesophageal cancer, habitat, Radiomics, neoadjuvant chemoimmunotherapy, Pathologic complete response

    Received: 16 Apr 2024; Accepted: 14 Nov 2024.

    Copyright: © 2024 Kong, Xu, Huang, Zhu, Yao, Wu, Wang, Ma, Zhang and Zhang. 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: Renquan Zhang, First Affiliated Hospital of Anhui Medical University, Hefei, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.