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Personalized dosimetry has been shown to improve overall survival (OS) in patients with hepatocellular carcinoma (HCC) treated with glass Yttrium-90 radioembolization (Y90-RE). This study evaluated personalized tumor dose as a predictor of OS, progression free survival (PFS) and local duration of response (DOR) in patients with surgically unresectable HCC treated with resin Y90-RE. This prospective, single-center, single arm clinical trial (NCT04172714) evaluated the efficacy of scout activity of resin Y90 versus Tc99-MAA for treatment planning. A secondary aim of this study was to evaluate personalized dosimetry as a predictor of OS, PFS and DOR. Partition dosimetry model was utilized for non-segmental therapies with targeted of tumor dose (TD) >200 Gy and non-tumoral liver dose (NTLD) < 70 Gy. Single compartment dose of 200 Gy was used for segmentectomies. OS, PFS, and local DOR from Y90 was estimated using Kaplan-Meier estimation with log-rank analysis used to determine predictors of prolonged survival. 30 patients with treatment-naïve HCC and 33 tumors (19 segmental and 14 non-segmental) were included. Mean Y90 TD was 493 Gy. Median follow-up since enrollment into the study was 37 months. Mean OS was 32.2 months for the entire cohort. A total of 5 patients underwent orthotopic liver transplantation post Y90 and were excluded from further survival analysis. Mean OS for the remainder of the cohort was 30 months (median not reached). Mean tumor dose >250 Gy resulted in prolonged mean OS and PFS. Additionally, Child-Pugh status and achieving objective or complete response predicted prolonged mean OS and PFS. Furthermore, ALBI score predicted prolonged OS and Barcelona Liver Cancer Clinic staging predicted prolonged PFS. Median local DOR was 32.7 months with mean TD 330 Gy predicting prolonged DOR. For patients with surgically unresectable HCC treated with resin Y90, there is mean tumor dose threshold predicting prolonged OS, PFS and local DOR. Therefore, there should be further emphasis on personalized dosimetry for optimization of patient outcomes.
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Kokabi et al. (2024) studied this question.
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