PROJECT SUMMARY Liver cancer is the 4th leading cause of cancer death worldwide. For intermediate-stage disease, intra-arterial therapies, such as transarterial chemoembolization (TACE), are the mainstay treatment. In TACE, targeted delivery of chemotherapeutic agents and embolic particles block tumor feeding arteries to increase both drug delivery and cause tumor necrosis. TACE can prolong survival, palliate symptoms, or serve as a bridge to liver transplantation. During TACE, angiographic monitoring of residual tumoral blood flow is critical and the degree of stasis achieved directly impacts patient outcomes, including survival. Currently, there are no objective, standardized intra-procedural methods for determining the optimal embolization endpoint. Instead, interventional radiologists rely on visual assessment of blood flow stasis and decreased perfusion to determine when to end an embolization. This subjective assessment is not reproducible and can lead to underembolization (insufficient tumor necrosis) or overembolization (damage to surrounding liver tissue), which can ultimately increase mortality. The objective of this proposal is to develop an intraprocedural quantitative digital subtraction angiography (qDSA) technique that can characterize hepatic perfusion changes in response to embolization. The proposed technique extracts blood flow information from DSA images that are routinely acquired during a TACE procedure. In our first aim, we will develop an optimized qDSA method that characterizes changes in hepatic arterial blood flow and perfusion in response to embolization. This will be done using in vitro phantom models and in vivo porcine models to identify optimal imaging parameters to characterize the nature of flow reduction in response to embolization. We will then perform embolizations in an in vivo porcine model to partial and complete stasis endpoints, and correlate the flow reduction using qDSA with the degree of perfusion changes using histopathology. In the second aim, we will use a rabbit liver tumor model to correlate flow reduction using qDSA with the degree of intratumoral perfusion changes and tissue response on histopathology. Successful demonstration of such a technique would serve as the first objective, standardized, and intra-procedural method for determining TACE endpoints. This would significantly improve the safety and efficacy of the procedure in the treatment of liver tumors.