Diagnostic Value of F-FDG PET/CT Radiomics in Lymphoma: A Systematic Review and Meta-Analysis - Chaoying Liu MD; Jun Zhao PhD; Heng Zhang PhD; Xinye Ni PhD (Technology in Cancer Research & Treatment)
Introduction Various machine learning models and features have been proposed for lymphoma diagnosis using 18 F-fluorodeoxyglucose ( 18 F-FDG) PET/CT radiomics. This research aimed to systematically evaluate the diagnostic value of 18 F-FDG PET/CT radiomics in lymphoma by conducting a meta-analysis. Methods Data from published studies regarding the diagnosis of lymphoma using 18 F-FDG PET/CT radiomics, from January 2010 to July 2024, were gathered from PubMed, Web of Science, and the Cochrane Library. Following their separate searches and screenings of the literature, two researchers extracted data and assessed the caliber of all the included studies. The quality assessment involved the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2), the Radiomics Quality Score (RQS), and the METhodological RadiomICs Score (METRICS). The meta-analysis was conducted by using RevMan 5.4.1, R 4.4.0, and Stata 17.0 software. Six meta-regressions were conducted on study performance, considering sample size, image modality, region of interest (ROI) selection, ROI segmentation, radiomics mode, and algorithms. Results In total, 20 studies classified as type 2a or above according to the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) statement were included for this systematic review and meta-analysis. The studies achieved an average RQS of 13 (ranging from 10 to 17), accounting for 36.1% of the total points. The average METRICS score was 69.3% (ranging from 54.8% to 80.9%). The quality category of the studies is mainly “good”. The results of our meta-analysis showed that the pooled sensitivity (SEN), specificity (SPE), positive likelihood ratio, negative likelihood ratio and diagnostic odds ratio with 95% confidence interval ( CI ) were 0.82 (0.78, 0.88), 0.83 (0.76, 0.87), 4.7 (3.4, 6.6), 0.20 (0.15, 0.28) and 23 (13, 42), respectively. The area under the curve of the summary receiver operating characteristic curve was 0.90 (0.87, 0.92). The results of Spearman correlation analysis revealed no threshold effect among the studies ( P  = .423). Significant heterogeneity was observed among the studies (overall I 2  = 83.7%; 95% CI : 76.0, 88.9; P  < .01). Meta-regressions indicated that sample size and ROI selection contributed to the heterogeneity in SEN, while algorithms affected the heterogeneity in SPE ( P  < .05). Deeks’ test confirmed there was no significant publication bias in all the included studies. The Fagan nomogram showed an absolute increase of 34% in the post-test probability following a positive test result. Conclusion The results supported that 18 F-FDG PET/CT radiomics has high diagnostic value for lymphoma. However, there is high heterogeneity among different studies. In the future, clinical practicality needs to be substantiated by more prospective studies with rigorous adherence to existing guidelines and multicentric validation.