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CT-based delta-radiomics for predicting pathological response to neoadjuvant immunochemotherapy in esophageal squamous cell carcinoma: a multicenter study

Authors :
Yuting Zheng
Peiyuan Mei
Mingliang Wang
Qinyue Luo
Hanting Li
Chengyu Ding
Kailu Zhang
Leqing Chen
Jin Gu
Yumin Li
Tingting Guo
Chi Zhang
Wenjian Yao
Li Wei
Yongde Liao
Xiaoyu Han
Heshui Shi
Source :
BMC Medical Imaging, Vol 24, Iss 1, Pp 1-12 (2024)
Publication Year :
2024
Publisher :
BMC, 2024.

Abstract

Abstract Background The study aimed to investigate the predictive value of delta-radiomics derived from computed tomography (CT) for pathological complete response (pCR) to neoadjuvant immunochemotherapy (NICT) among patients with esophageal squamous cell carcinoma (ESCC), helping clinicians determine whether to modify the neoadjuvant treatment strategy, proceed to surgery, or forgo surgery altogether. Methods A total of 140 ESCC patients from two institutions (Database 1 = 93; Database 2 = 47) who underwent NICT and surgery were retrospectively included in the study. The training set consisted of patients from Database 1, while the testing set included patients from Database 2. All patients underwent contrast-enhanced CT scans before the start of the treatment and prior to the operation. The delta-radiomics features were calculated as the relative net change of radiomics features between the two-time points. Feature selection was conducted using Pearson correlation analysis, intraclass correlation coefficients, and the fivefold cross-validation with least absolute shrinkage and selection analysis. Four models were established, comprising a clinical model, a pre-treatment radiomics model, a delta-radiomics model, and a mixed model. Area under the curve (AUC) and decision curve analysis were used to assess the performance and the clinical value of the models. Results Less than half of the tumors (40/140, 28.6%) showed pCR following NICT. The delta-radiomics model displayed AUC of 0.827 and 0.790 in the training and testing set for predicting pCR, which was superior to the clinical model based on age and clinical tumor node metastasis (cTNM) stage (0.758 and 0.615) and the pre-treatment radiomics model (0.787 and 0.621). Furthermore, the delta-radiomics model demonstrated a more excellent AUC value in the testing set than the mixed model (0.847 and 0.719), which integrated clinical and delta-radiomics features. Conclusions The delta-radiomics model exhibited better diagnostic performance in preoperative prediction of pCR for NICT in ESCC patients compared to the clinical, pre-treatment radiomics, and mixed models.

Details

Language :
English
ISSN :
14712342
Volume :
24
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Medical Imaging
Publication Type :
Academic Journal
Accession number :
edsdoj.408fc8f8ae394f6a8bef6b07d27b7573
Document Type :
article
Full Text :
https://doi.org/10.1186/s12880-024-01503-1