Kunichika, Hideki, Minamiguchi, Kiyoyuki, Tachiiri, Tetsuya, Shimizu, Kozo, Taiji, Ryosuke, Yamada, Aya, Nakano, Ryota, Irizato, Mariko, Yamauchi, Satoshi, Marugami, Aki, Marugami, Nagaaki, Kishida, Hayato, Nakagawa, Hiroyuki, Takewa, Megumi, Kageyama, Ken, Yamamoto, Akira, Ueshima, Eisuke, Sofue, Keitaro, Kita, Ryuichi, and Kurakami, Hiroyuki
Simple Summary: Atezolizumab/bevacizumab (AB) therapy is currently one of the first-line drugs for patients with unresectable hepatocellular carcinoma (u-HCC). Predicting early progressive disease before AB therapy may be beneficial for selecting alternative treatments for patients with u-HCC. Coefficient of variation (CV), as one of the quantitative indicators of signal heterogeneity, in the hepatobiliary phase of Gd-EOB-DTPA-MRI was an independent predictive factor for tumor progression (p = 0.043). Patients with a high CV tended to have shorter PFS than those with a low CV (3.5 vs. 6.7 months, p = 0.071). Quantitative analysis using CV may be useful for predicting tumor progression for AB therapy, contributing to the individualization of therapeutic strategies for patients with u-HCC. Background: This study aimed to examine whether the coefficient of variation (CV) in the hepatobiliary-phase (HBP) of Gd-EOB-DTPA-MRI could be an independent predictive factor for tumor progression. Methods: Patients who underwent Gd-EOB-DTPA-MRI before Atezolizumab/bevacizumab therapy at six affiliated institutions between 2018 and 2022 were included. CV for each patient was calculated as the mean value for up to five tumors larger than 10 mm, and CV of the whole tumor was calculated using LIFEx software. The tumor response was evaluated within 6–10 weeks. The primary endpoint was to investigate the predictive factors, including CV, related to tumor progression using logistic regression analysis. The secondary endpoints were tumor response rate and progression-free survival (PFS) based on CV. Results: Of the 46 enrolled patients, 13 (28.3%) underwent early progressive disease. Multivariate analysis revealed that a high CV (≥0.22) was an independent predictive factor for tumor progression (p = 0.043). Patients with a high CV had significantly frequent PD than those with a low CV (43.5 vs. 13.0%, p = 0.047). Patients with a high CV tended to have shorter PFS than those with a low CV (3.5 vs. 6.7 months, p = 0.071). Conclusion: Quantitative analysis using CV in the HBP of Gd-EOB-DTPA-MRI may be useful for predicting tumor progression for atezolizumab/bevacizumab therapy. [ABSTRACT FROM AUTHOR]