Quantitative Predictive Dosimetry for Curative Transarterial Radioembolization

/ SUMMARY Transarterial Radioembolization (TARE) is growing in interest as a viable curative radiation therapy treatment, particularly for liver tumors such as hepatocellular carcinoma (HCC). Taking advantage of the dual blood supply in the liver, a microcatheter is used to perfuse radioactive yttrium-90 (Y-90) microspheres into the branches of the hepatic artery with a twofold objective: to cut off the tumor nutrients supply by embolizing the tumor-feeding vasculature and kill the tumor cells by emitting ionizing beta radiation. Increasing the radioactivity leads to a higher dose and, therefore, a greater effect. In this context, recent clinical trials have shown promising results associated with a personalized tumor-absorbed dose. However, current clinical dosimetric methods do not address quantitative predictive dosimetry. They use inaccurate surrogates to predict the spatial distribution of Y- 90 after administration and ignore the non-uniformity pattern to calculate the absorbed dose. The main goal of this proposal is to overcome the current clinical limitations by designing a novel quantitative TARE dosimetry framework capable of predicting realistic Y-90 dose distributions. To achieve this goal, I will work on the following specific aims: (1) to develop a patient-specific liver vasculature model; (2) to develop an HCC-specific uptake model; (3) to design a TARE dosimetry schema including the previous models. A retrospective cohort of treatment-naïve HCC patients who presented a solitary liver-confined lesion ≤ 8 cm, treated with the radiation segmentectomy technique at Massachusetts General Hospital, will be used. Routine pre-treatment vasculature studies will be employed to extract liver patient-specific vasculature. This will guide an in-house algorithm to create a patient-specific liver vasculature model. Pre-treatment uptake evaluations will be utilized to inform the HCC-specific uptake model. Lastly, these models will be integrated into a robust dosimetry schema alongside our recently developed TARE simulator, which predicts the activity distribution within the tumor and normal liver as compartments. Finally, a Monte Carlo toolkit will be used to transform the activity predicted into patient-specific dose distributions. The principal investigator will use the experience and expertise of his mentoring team (Dr. Alejandro Bertolet, Dr. Harald Paganetti, Dr. Eric Wehrenberg-Klee, and Dr. Ted Hong) to learn the skills and abilities necessary to accomplish the proposed research. He will also attend seminars, coursework, and conferences on liver cancer, radiobiology, medical physics/nuclear medicine, clinical trials design, grant writing, and leadership skills. This plan will prepare the principal investigator to lead an independent research program and establish a lab with a unique expertise. Project Number: 1K99CA312830-01 | Fiscal Year: 2026 | NIH Institute/Center: National Cancer Institute (NCI) | Principal Investigator: Carlos Huesa-Berral | Institution: MASSACHUSETTS GENERAL HOSPITAL, BOSTON, MA | Award Amount: $161,460 | Activity Code: K99 | Study Section: Special Emphasis Panel[ZRG1 CDPT-P (56)] View on NIH RePORTER: https://reporter.nih.gov/project-details/11353174