Radiomics for Predicting Response of Neoadjuvant Chemotherapy in Nasopharyngeal Carcinoma: A Systematic Review and Meta-Analysis - Yang, Chao; Jiang, Zekun; Cheng, Tingting; Zhou, Rongrong; Wang, Guangcan; Jing, Di; Bo, Linlin; Huang, Pu; Wang, Jianbo; Zhang, Daizhou; Jiang, Jianwei; Wang, Xing; et al. (Frontiers in Oncology, 2022)
Purpose: This study examined the methodological quality of radiomics to predict the effectiveness of neoadjuvant chemotherapy in nasopharyngeal carcinoma (NPC). We performed a meta-analysis of radiomics studies evaluating the bias risk and treatment response estimation. Methods: Our study was conducted through a literature review as per the Preferred Reporting Items for Systematic Reviews and Meta-analysis guidelines. We included radiomics-related paper, published prior to 31 January 2022, in our analysis to examine the effectiveness of neoadjuvant chemotherapy in NPC. The methodological quality was assessed using the Radiomics Quality Score. The intra-class correlation coefficient (ICC) was employed to evaluate inter-reader reproducibility. Pooled area under the curve (AUC), pooled sensitivity and pooled specificity were used to assess the ability of radiomics to predict response to neoadjuvant chemotherapy in NPC. Lastly, the Quality Assessment of Diagnostic Accuracy Studies technique was used to analyze the bias risk. Results: A total of 12 studies were eligible for our systematic review, and 6 papers were included in our meta-analysis. The radiomics quality score was set from 7 to 21 (maximum score: 36). There was satisfactory intra-class correlation coefficient (ICC = 0.987) and 95% confidence intervals (95% CI = 0.957 - 0.996, P<0.001). The pooled sensitivity and specificity were 0.88 (95% CI: 0.71 - 0.95) and 0.82 (95% CI: 0.68 - 0.91), respectively. The overall AUC was 0.91 (95% CI: 0.88 - 0.93). Conclusion: Prediction response of neoadjuvant chemotherapy in NPC using machine learning and radiomics is beneficial in improving and standardization and methodological quality before applying it to clinical practice.