Nomogram Based on Clinical and Radiomics Data for Predicting Radiation-induced Temporal Lobe Injury in Patients with Non-metastatic Stage T4 Nasopharyngeal Carcinoma

X Bin; C Zhu; Y Tang; R Li; Q Ding; W Xia; Y Tang; X Tang; D Yao; A Tang

doi:10.1016/j.clon.2022.07.007

Nomogram Based on Clinical and Radiomics Data for Predicting Radiation-induced Temporal Lobe Injury in Patients with Non-metastatic Stage T4 Nasopharyngeal Carcinoma

Clin Oncol (R Coll Radiol). 2022 Dec;34(12):e482-e492. doi: 10.1016/j.clon.2022.07.007. Epub 2022 Aug 23.

Authors

X Bin¹, C Zhu², Y Tang³, R Li⁴, Q Ding⁵, W Xia¹, Y Tang⁶, X Tang¹, D Yao¹, A Tang⁷

Affiliations

¹ Department of Otolaryngology-Head and Neck Surgery, First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi, China.
² Department of Radiation Oncology, People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.
³ Department of Neurology, First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi, China.
⁴ Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University Hangzhou, Zhejiang Province, China; Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
⁵ Institute of Natural Sciences, Shanghai Jiao Tong University, Shanghai, China.
⁶ Department of Radiology, First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi, China.
⁷ Department of Otolaryngology-Head and Neck Surgery, First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi, China. Electronic address: tanganzhou@gxmu.edu.cn.

PMID: 36008245
DOI: 10.1016/j.clon.2022.07.007

Abstract

Aims: To use pre-treatment magnetic resonance imaging-based radiomics data with clinical data to predict radiation-induced temporal lobe injury (RTLI) in nasopharyngeal carcinoma (NPC) patients with stage T4/N0-3/M0 within 5 years after radiotherapy.

Materials and methods: This study retrospectively examined 98 patients (198 temporal lobes) with stage T4/N0-3/M0 NPC. Participants were enrolled into a training cohort or a validation cohort in a ratio of 7:3. Radiomics features were extracted from pre-treatment magnetic resonance imaging that were T1-and T2-weighted. Spearman rank correlation, the t-test and the least absolute shrinkage and selection operator (LASSO) algorithm were used to select significant radiomics features; machine-learning models were used to generate radiomics signatures (Rad-Scores). Rad-Scores and clinical factors were integrated into a nomogram for prediction of RTLI. Nomogram discrimination was evaluated using receiver operating characteristic analysis and clinical benefits were evaluated using decision curve analysis.

Results: Participants were enrolled into a training cohort (n = 139) or a validation cohort (n = 59). In total, 3568 radiomics features were initially extracted from T1-and T2-weighted images. Age, D_max, D_1cc and 16 stable radiomics features (six from T1-weighted and 10 from T2-weighted images) were identified as independent predictive factors. A greater Rad-Score was associated with a greater risk of RTLI. The nomogram showed good discrimination, with a C-index of 0.85 (95% confidence interval 0.79-0.92) in the training cohort and 0.82 (95% confidence interval 0.71-0.92) in the validation cohort.

Conclusion: We developed models for the prediction of RTLI in patients with stage T4/N0-3/M0 NPC using pre-treatment radiomics data and clinical data. Nomograms from these pre-treatment data improved the prediction of RTLI. These results may allow the selection of patients for earlier clinical interventions.

Keywords: MRI-based radiomics; T4/N0-3/M0 nasopharyngeal carcinoma; nomogram; temporal lobe injury.

MeSH terms

Humans
Magnetic Resonance Imaging / methods
Nasopharyngeal Carcinoma / radiotherapy
Nasopharyngeal Neoplasms* / diagnostic imaging
Nasopharyngeal Neoplasms* / drug therapy
Nasopharyngeal Neoplasms* / radiotherapy
Nomograms
Radiation Injuries* / diagnostic imaging
Radiation Injuries* / etiology
Retrospective Studies
Temporal Lobe