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Introduction Immune checkpoint inhibitor (ICI) combinations extend overall survival (OS) while anti-PD-1/L1 monotherapy is non-inferior to sorafenib in treatment-naïve, patients with advanced hepatocellular carcinoma (HCC). Clinicogenomic features are posited to influence patient outcomes. Methods The primary objective of this retrospective study was to define the clinical, pathologic, and genomic factors associated with outcomes to ICI therapy in patients with HCC. Patients with histologically confirmed advanced HCC treated with ICI at Memorial Sloan Kettering Cancer Center from 2012 to 2022 were included. Association between clinical, pathological, and genomic characteristics were assessed with univariable and multivariable Cox regression model for progression-free survival (PFS) and OS. Results Two-hundred and forty-two patients were treated with ICI-based therapy. Patients were predominantly male (82%) with virally mediated HCC (53%) and Child Pugh A score (70%). Median follow-up was 28 months (0.5-78.4). Median PFS for those treated in 1st line, 2nd line and ≥ 3rd line was 4.9 (range: 2.9-6.2), 3.1 (2.3-4.0), and 2.5 (2.1-4.0) months, respectively. Median OS for those treated in 1st line, 2nd line, and ≥ 3rd line was 16 (11-22), 7.5 (6.4-11), and 6.4 (4.6-26) months, respectively. Poor liver function and performance status associated with worse PFS and OS, while viral hepatitis C was associated with favorable outcome. Genetic alterations were not associated with outcomes. Conclusion Clinicopathologic factors were the major determinates of outcomes for patients with advanced HCC treated with ICI. Molecular profiling did not aid in stratification of ICI outcomes. Future studies should explore alternative biomarkers such as the level of immune activation or the pretreatment composition of the immune tumor microenvironment. [ABSTRACT FROM AUTHOR]

Purpose: To enable free‐breathing and high isotropic resolution liver quantitative susceptibility mapping (QSM) using 3D multi‐echo UTE cones acquisition and respiratory motion‐resolved image reconstruction. Methods: Using 3D multi‐echo UTE cones MRI, a respiratory motion was estimated from the k‐space center of the imaging data. After sorting the k‐space data with estimated motion, respiratory motion state‐resolved reconstruction was performed for multi‐echo data followed by nonlinear least‐squares fitting for proton density fat fraction (PDFF), R2*$$ {\mathrm{R}}_2^{\ast } $$, and fat‐corrected B0 field maps. PDFF and B0 field maps were subsequently used for QSM reconstruction. The proposed method was compared with motion‐averaged (gridding) reconstruction and conventional 3D multi‐echo Cartesian MRI in moving gadolinium phantom and in vivo studies. Region of interest (ROI)‐based linear regression analysis was performed on these methods to investigate correlations between gadolinium concentration and QSM in the phantom study and between R2*$$ {\mathrm{R}}_2^{\ast } $$ and QSM in in vivo study. Results: Cones with motion‐resolved reconstruction showed sharper image quality compared to motion‐averaged reconstruction with a substantial reduction of motion artifacts in both moving phantom and in vivo studies. For ROI‐based linear regression analysis of the phantom study, susceptibility values from cones with motion‐resolved reconstruction (QSMppm$$ {\mathrm{QSM}}_{\mathrm{ppm}} $$ = 0.31 ×gadoliniummM+$$ \times {\mathrm{gadolinium}}_{\mathrm{mM}}+ $$ 0.05, R2$$ {R}^2 $$ = 0.999) and Cartesian without motion (QSMppm$$ {\mathrm{QSM}}_{\mathrm{ppm}} $$ = 0.32 ×gadoliniummM+$$ \times {\mathrm{gadolinium}}_{\mathrm{mM}}+ $$ 0.04, R2$$ {R}^2 $$ = 1.000) showed linear relationships with gadolinium concentrations and showed good agreement with each other. For in vivo, motion‐resolved reconstruction showed higher goodness of fit (QSMppm$$ {\mathrm{QSM}}_{\mathrm{ppm}} $$ = 0.00261 ×R2s−1*−$$ \times {\mathrm{R}}_{2_{{\mathrm{s}}^{-1}}}^{\ast }- $$ 0.524, R2$$ {R}^2 $$ = 0.977) compared to motion‐averaged reconstruction (QSMppm$$ {\mathrm{QSM}}_{\mathrm{ppm}} $$ = 0.0021 ×R2s−1*−$$ \times {\mathrm{R}}_{2_{{\mathrm{s}}^{-1}}}^{\ast }- $$ 0.572, R2$$ {R}^2 $$= 0.723) in ROI‐based linear regression analysis between R2*$$ {\mathrm{R}}_2^{\ast } $$ and QSM. Conclusion: Feasibility of free‐breathing liver QSM was demonstrated with motion‐resolved 3D multi‐echo UTE cones MRI, achieving high isotropic resolution currently unachievable in conventional Cartesian MRI. [ABSTRACT FROM AUTHOR]