Radiomics Model Based on Vertebral Calcium-Suppressed CT Images for Predicting Chemotherapy-Induced Myelosuppression in Nasopharyngeal Carcinoma

Yanhui Yang^1,2,3Jing Hou¹Yi Zhang^1,2Yan Sun^1,2Yi Fu⁴Qiang Lu¹Tao Luo¹Zhijie Huang⁵Xiaoping Yu^1,2*

• ¹Department of Diagnostic Radiology, the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital, Changsha 410013, Hunan, China, Changsha, China
• ²Department of Diagnostic Radiology, Graduate Collaborative Training Base of Hunan Cancer Hospital, Hengyang Medical School, University of South China, Hengyang 421001, Hunan, China, Hengyang, China
• ³The First Affiliated Hospital, Department of Radiology, Hengyang Medical School, University of South China, Hengyang, China., Hengyang, China
• ⁴Medical Department, the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital, Changsha 410013, Hunan, China, Changsha, China
• ⁵Philips Healthcare, Guangzhou, China, Guangzhou, China

Objective: To develop and validate a radiomics model based on vertebral calcium-suppressed (CaSupp) images derived from dual-layer computed tomography (DLCT) for predicting chemotherapy-induced myelosuppression in patients with locally advanced nasopharyngeal carcinoma (LANPC).Methods: This retrospective study included 150 LANPC patients treated with induction chemotherapy (IC). Radiomics features were extracted from lumbar vertebral CaSupp obtained from baseline DLCT scans. Models were developed to predict myelosuppression after the first chemotherapy cycle (IC-1) and entire chemotherapy cycles (IC-n). The clinics, radiomics, and combined models were conducted via multivariate logistic regression. Models’ performance was evaluated by the area under the receiver operating characteristic curve (AUC). Clinical utility was analyzed with decision curve analysis.Results: For predict myelosuppression after IC-1, the clinics, radiomics, and combined models had AUC values of 0.716, 0.825 and 0.859 in the train cohort, respectively; and AUC of 0.687, 0.752 and 0.790 in the test cohort, respectively. And for IC-n, the clinics, radiomics, and combined models exhibited AUC values of 0.771, 0.824, and 0.889 in the train cohort, respectively; and AUC of 0.652, 0.740 and 0.806 in the test cohort, respectively. For predicting myelosuppression after both IC-1 and IC-n ,the combined models demonstrated significantly higher AUC values than the clinics models for both IC-1 and IC-n (all P＜0.05). Conclusions: Radiomics model based on vertebral CaSupp images from DLCT could predict chemotherapy-induced myelosuppression in LANPC patients. This study highlights the potential of DLCT technology to provide quantitative bone marrow assessments and aid in personalized treatment planning. External validation and comparison with other imaging modalities are warranted in the future.