Hyo Sang Lee1, Jungsu S Oh1, Young Soo Park2, Se Jin Jang2, Ik Soo Choi3, Jin-Sook Ryu4. 1. Departments of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Republic of Korea. 2. Departments of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea. 3. Team of Medical Informatics, Asan Medical Center, Seoul, Republic of Korea. 4. Departments of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Republic of Korea. jsryu2@amc.seoul.kr.
Abstract
OBJECTIVE: We aimed to explore the ability of textural heterogeneity indices determined by (18)F-FDG PET/CT for grading the malignancy of thymic epithelial tumors (TETs). METHODS: We retrospectively enrolled 47 patients with pathologically proven TETs who underwent pre-treatment (18)F-FDG PET/CT. TETs were classified by pathological results into three subgroups with increasing grades of malignancy: low-risk thymoma (LRT; WHO classification A, AB and B1), high-risk thymoma (B2 and B3), and thymic carcinoma (TC). Using (18)F-FDG PET/CT, we obtained conventional imaging indices including SUVmax and 20 intratumoral heterogeneity indices: i.e., four local-scale indices derived from the neighborhood gray-tone difference matrix (NGTDM), eight regional-scale indices from the gray-level run-length matrix (GLRLM), and eight regional-scale indices from the gray-level size zone matrix (GLSZM). Area under the receiver operating characteristic curve (AUC) was used to demonstrate the abilities of the imaging indices for differentiating subgroups. Multivariable logistic regression analysis was performed to show the independent significance of the textural indices. Combined criteria using optimal cutoff values of the SUVmax and a best-performing heterogeneity index were applied to investigate whether they improved differentiation between the subgroups. RESULTS: Most of the GLRLM and GLSZM indices and the SUVmax showed good or fair discrimination (AUC >0.7) with best performance for some of the GLRLM indices and the SUVmax, whereas the NGTDM indices showed relatively inferior performance. The discriminative ability of some of the GLSZM indices was independent from that of SUVmax in multivariate analysis. Combined use of the SUVmax and a GLSZM index improved positive predictive values for LRT and TC. CONCLUSIONS: Texture analysis of (18)F-FDG PET/CT scans has the potential to differentiate between TET tumor grades; regional-scale indices from GLRLM and GLSZM perform better than local-scale indices from the NGTDM. The SUVmax and heterogeneity indices may have complementary value in differentiating TET subgroups.
OBJECTIVE: We aimed to explore the ability of textural heterogeneity indices determined by (18)F-FDG PET/CT for grading the malignancy of thymic epithelial tumors (TETs). METHODS: We retrospectively enrolled 47 patients with pathologically proven TETs who underwent pre-treatment (18)F-FDG PET/CT. TETs were classified by pathological results into three subgroups with increasing grades of malignancy: low-risk thymoma (LRT; WHO classification A, AB and B1), high-risk thymoma (B2 and B3), and thymic carcinoma (TC). Using (18)F-FDG PET/CT, we obtained conventional imaging indices including SUVmax and 20 intratumoral heterogeneity indices: i.e., four local-scale indices derived from the neighborhood gray-tone difference matrix (NGTDM), eight regional-scale indices from the gray-level run-length matrix (GLRLM), and eight regional-scale indices from the gray-level size zone matrix (GLSZM). Area under the receiver operating characteristic curve (AUC) was used to demonstrate the abilities of the imaging indices for differentiating subgroups. Multivariable logistic regression analysis was performed to show the independent significance of the textural indices. Combined criteria using optimal cutoff values of the SUVmax and a best-performing heterogeneity index were applied to investigate whether they improved differentiation between the subgroups. RESULTS: Most of the GLRLM and GLSZM indices and the SUVmax showed good or fair discrimination (AUC >0.7) with best performance for some of the GLRLM indices and the SUVmax, whereas the NGTDM indices showed relatively inferior performance. The discriminative ability of some of the GLSZM indices was independent from that of SUVmax in multivariate analysis. Combined use of the SUVmax and a GLSZM index improved positive predictive values for LRT and TC. CONCLUSIONS: Texture analysis of (18)F-FDG PET/CT scans has the potential to differentiate between TET tumor grades; regional-scale indices from GLRLM and GLSZM perform better than local-scale indices from the NGTDM. The SUVmax and heterogeneity indices may have complementary value in differentiating TET subgroups.
Authors: Jose Arimateia Batista Araujo-Filho; Maria Mayoral; Junting Zheng; Kay See Tan; Peter Gibbs; Annemarie Fernandes Shepherd; Andreas Rimner; Charles B Simone; Gregory Riely; James Huang; Michelle S Ginsberg Journal: Ann Thorac Surg Date: 2021-04-09 Impact factor: 5.102
Authors: Lorenzo Fantini; Maria Luisa Belli; Irene Azzali; Emiliano Loi; Andrea Bettinelli; Giacomo Feliciani; Emilio Mezzenga; Anna Fedeli; Silvia Asioli; Giovanni Paganelli; Anna Sarnelli; Federica Matteucci Journal: Front Oncol Date: 2021-06-24 Impact factor: 6.244