Details

Autor(en) / Beteiligte

• Hotta, Masatoshi
• Minamimoto, Ryogo
• Gohda, Yoshimasa
• Miwa, Kenta
• Otani, Kensuke
• Kiyomatsu, Tomomichi
• Yano, Hideaki

Titel

Prognostic value of 18F-FDG PET/CT with texture analysis in patients with rectal cancer treated by surgery

Ist Teil von

• Annals of nuclear medicine, 2021-07, Vol.35 (7), p.843-852

Ort / Verlag

Singapore: Springer Singapore

Erscheinungsjahr

2021

Quelle

SpringerLink

Beschreibungen/Notizen

• Purpose The aim of this study was to evaluate the ability of texture analysis using pretreatment 18 F-FDG PET/CT to predict prognosis in patients with surgically treated rectal cancer. Methods We analyzed 94 patients with pathologically proven rectal cancer who underwent pretreatment 18 F-FDG PET/CT and were subsequently treated with surgery. The volume of interest of the primary tumor was defined using a threshold of 40% of the maximum standardized uptake value (SUVmax), and conventional (SUVmax, metabolic tumor volume [MTV], total lesion glycolysis [TLG]) and textural PET features were extracted. Harmonization of PET features was performed with the ComBat method. The study endpoints were overall survival (OS) and progression-free survival (PFS), and the prognostic value of PET features was evaluated by Cox regression analysis. Results In the follow-up period (median 41.7 [interquartile range, 30.5–60.4] months), 21 (22.3%) and 30 (31.9%) patients had cancer-related death or disease progression, respectively. Univariate analysis revealed a significant association of (1) MTV, TLG, and gray-level co-occurrence matrix (GLCM) entropy with OS; and (2) SUVmax, MTV, TLG, and GLCM entropy with PFS. In multivariate analysis including clinical characteristics, GLCM entropy (≥ 2.13) was the only relevant prognostic PET feature for poor OS (hazard ratio [HR]: 4.16, p  = 0.035) and PFS (HR: 2.70, p  = 0.046). Conclusion GLCM entropy, which indicates metabolic intratumoral heterogeneity, was an independent prognostic factor in patients with surgically treated rectal cancer. Compared with conventional PET features, GLCM entropy has better predictive value and shows potential to facilitate precision medicine.