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Acute hematologic toxicity prediction using dosimetric and radiomics features in patients with cervical cancer: does the treatment regimen matter?

Authors :
Haizhen Yue
Xiaofan Li
Jing You
Pujie Feng
Yi Du
Ruoxi Wang
Hao Wu
Jinsheng Cheng
Kuke Ding
Bin Jing
Source :
Frontiers in Oncology; 2024, p1-11, 11p
Publication Year :
2024

Abstract

Background: Acute hematologic toxicity (HT) is a prevalent adverse tissue reaction observed in cervical cancer patients undergoing chemoradiotherapy (CRT), which may lead to various negative effects such as compromised therapeutic efficacy and prolonged treatment duration. Accurate prediction of HT occurrence prior to CRT remains challenging. Methods: A discovery dataset comprising 478 continuous cervical cancer patients (140 HT patients) and a validation dataset consisting of 205 patients (52 HT patients) were retrospectively enrolled. Both datasets were categorized into the CRT group and radiotherapy (RT)-alone group based on the treatment regimen, i.e., whether chemotherapy was administeredwithin the focused RT duration. Radiomics features were derived by contouring three regions of interest (ROIs)--bone marrow (BM), femoral head (FH), and clinical target volume (CTV)--on the treatment planning CT images before RT. A comprehensivemodel combining the radiomics features aswell as the demographic, clinical, and dosimetric features was constructed to classify patients exhibiting acute HT symptoms in the CRT group, RT group, and combination group. Furthermore, the time-to-event analysis of the discriminative ROI was performed on all patients with acute HT to understand the HT temporal progression. Results: Among three ROIs, BM exhibited the best performance in classifying acute HT, which was verified across all patient groups in both discovery and validation datasets. Among different patient groups in the discovery dataset, acute HT was more precisely predicted in the CRT group [area under the curve (AUC) = 0.779, 95% CI: 0.657-0.874] than that in the RT-alone (AUC = 0.686, 95% CI: 0.529-0.817) or combination group (AUC = 0.748, 95% CI: 0.655-0.827). The predictive results in the validation dataset similarly coincided with those in the discovery dataset: CRT group (AUC = 0.802, 95% CI: 0.669-0.914), RT-alone group (AUC = 0.737, 95% CI: 0.612-0.862), and combination group (AUC = 0.793, 95% CI: 0.713-0.874). In addition, distinct feature sets were adopted for different patient groups. Moreover, the predicted HT risk of BM was also indicative of the HT temporal progression. Conclusions: HT prediction in cervical patients is dependent on both the treatment regimen and ROI selection, and BM is closely related to the occurrence and progression of HT, especially for CRT patients. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
2234943X
Database :
Complementary Index
Journal :
Frontiers in Oncology
Publication Type :
Academic Journal
Accession number :
177684506
Full Text :
https://doi.org/10.3389/fonc.2024.1365897