Fully automated deep learning based auto-contouring of liver segments and spleen on contrast-enhanced CT images.

Manual delineation of liver segments on computed tomography (CT) images for primary/secondary liver cancer (LC) patients is time-intensive and prone to inter/intra-observer variability. Therefore, we developed a deep-learning-based model to auto-contour liver segments and spleen on contrast-enhanced CT (CECT) images. We trained two models using 3d patch-based attention U-Net ([Formula: see text] and 3d full resolution of nnU-Net ([Formula: see text] to determine the best architecture ([Formula: see text]. BA was used with vessels ([Formula: see text] and spleen ([Formula: see text] to assess the impact on segment contouring. Models were trained, validated, and tested on 160 ([Formula: see text]), 40 ([Formula: see text]), 33 ([Formula: see text]), 25 (CCH) and 20 (CPVE) CECT of LC patients. [Formula: see text] outperformed [Formula: see text] across all segments with median differences in Dice similarity coefficients (DSC) ranging 0.03-0.05 (p < 0.05). [Formula: see text], and [Formula: see text] were not statistically different (p > 0.05), however, both were slightly better than [Formula: see text] by DSC up to 0.02. The final model, [Formula: see text], showed a mean DSC of 0.89, 0.82, 0.88, 0.87, 0.96, and 0.95 for segments 1, 2, 3, 4, 5-8, and spleen, respectively on entire test sets. Qualitatively, more than 85% of cases showed a Likert score [Formula: see text] 3 on test sets. Our final model provides clinically acceptable contours of liver segments and spleen which are usable in treatment planning.

Salvage Locoregional Therapy Following Progression After Radiotherapy for Hepatocellular Carcinoma Is Associated with Improved Outcomes.

PURPOSE: To evaluate the impact of salvage locoregional therapy (salvage-LT) on survival of hepatocellular carcinoma (HCC) patients presenting with intrahepatic tumor progression following radiotherapy. METHODS: This single-institution retrospective analysis included consecutive HCC patients having intrahepatic tumor progression following radiotherapy during 2015-2019. Overall survival (OS) was calculated from the date of intrahepatic tumor progression after initial radiotherapy by using the Kaplan-Meier method. Log-rank tests and Cox regression models were used for univariable and multivariable analyses. An inverse probability weighting was used to estimate treatment effect of salvage-LT considering confounding factors. RESULTS: A total of 123 patients (mean age ± SD, 70 years ± 10; 97 men) were evaluated. Among those, 35 patients underwent 59 sessions of salvage-LT, including transarterial embolization/chemoembolization (n = 33), ablation (n = 11), selective internal radiotherapy (n = 7), and external beam radiotherapy (n = 8). At a median follow-up of 15.1 months (range, 3.4-54.5 months), the median OS was 23.3 months in patients who received salvage-LT and 6.6 months who did not. At multivariate analysis, ECOG performance status, Child-Pugh class, albumin-bilirubin grade, extrahepatic disease, and lack of salvage-LT were independent predictors of worse OS. After inverse probability weighting, salvage-LT was associated with a survival benefit of 8.9 months (95% CI: 1.1, 16.7 months; p = 0.03). CONCLUSIONS: Salvage locoregional therapy is associated with increased survival in HCC patients suffering from intrahepatic tumor progression following initial radiotherapy.