With our research in Interventional Oncology, we aspire to improve the detection, characterization, and treatment of neoplastic disease in the liver. This includes the full breadth of translational research in:
- Basic Science
- Translational Pre-Clinical Research
- Clinical Research
- Machine Learning
Since the advent of interventional oncology, a radiological discipline which uses image-guided procedures to deliver anti-cancer agents directly to the tumor, the search for new and effective agents for the treatment of cancer has been an organizing principle of research in this field. In an effort to combine minimally-invasive, image-guided approaches to target tumor metabolism, our team has demonstrated the efficacy of the first anti-glycolytic agent 3-Bromopyruvate (3-BrPA) in several animal models.
Translational Pre-clinical Research:
Translational research is a fast-evolving field in Interventional Oncology. Our group has a long-standing interest in translating cutting-edge technical innovations into clinical practice. Over the last decade, we have developed an expertise in bench-to-bedside translational projects. Our research focuses on image-guided locoregional therapies including trans-arterial chemoembolization (TACE). TACE is the only palliative treatment that can extend survival for liver cancer patients ineligible for curative surgical treatment. This technique allows chemotherapy to be locally delivered at higher concentrations than what can be safely administered systemically. One of the central missions is to improve embolic materials used for TACE. Within this framework, we partner with Boston Scientific to explore the effects of different types of drug-eluting microspheres on the tumor microenvironment and to understand the role of bead diameter on tumor penetration and drug elution. Within this framework, we utilize the VX2 liver tumor model, which was selected because it mimics human liver cancer in its blood supply and vascularization. This animal model provides an ideal platform to study the tumor microenvironment including parameters such as hypoxia, acidosis, and angiogenesis.
One of the highlights of our research work has been the awarding of an NIH RO1 grant in 2016 to our lab to improve liver cancer treatment. This 5-year project bridges basic, translational and clinical research aspects and will eventually result in an improved assessment of the tumor microenvironment with the ultimate goal of a better TACE procedure. As such, changes in the tumor energy metabolism are reflected in the pH of the tumor and its microenvironment; even slight deviations are believed to be early warnings signs of a premalignant state. Biosensor imaging of redundant deviation in shifts (BIRDS) is a highly innovative and unique imaging technique in magnetic resonance imaging (MRI) that can detect changes in temperature, pH, and metabolites. As part of both the NIH RO1 grant as well as our academic-industrial partnership with Boston Scientific, we are examining the change in pH variances in tumor microenvironment by applying BIRDS imaging and other molecular imaging methodologies to liver cancer.
Our clinical research focuses on improving intra and post-procedural imaging for intra-arterial therapies such as transarterial chemoembolization (TACE) and Yttrium (Y) 90 radioembolization (Y90). This happens in close partnership with Philips Research North America within the framework of an academic-industry partnership. One of the highlights is the awarding of an NIH RO1 grant to more optimally treat liver cancer. The goals of this partnership are to see, reach, and treat the tumor by 1) removing the subjectivity in catheter placement, 2) optimizing the drug delivery protocol, and 3) quantifying treatment success. The main tool that we use to realize these goals is the x-ray C-arm cone-beam CT (CBCT), to which based on our findings and development, helped with the adoption of CBCT into routine clinical workflow as standard of practice.
We have been greatly expanding the limited role CBCT currently plays in the TACE procedure. The methods have been developed and validated in pre-clinical and clinical environments and the results translated to commercial products. Specifically, we can provide intra-procedural assessment of tumor characteristics such as blood supply and localization, provide improved catheter navigation guidance through the use of image fusion and registration techniques, and most importantly, provide direct, immediate and quantitative feedback of embolization and drug delivery success. The activities include developing new 3D quantitative, modality-independent approaches (quantitative European Association of the Study of the Liver [qEASL]) for tumor response assessment, which will potentially replace out-dated techniques (i.e. Response Evaluation Criteria in Solid Tumors).
Given the increasing amount of data gathered and processed with electronic health records, the field of interventional oncology must utilize this resource to create the next generation of medical technologies applied to cancer treatment. Our lab aims to be at the forefront of this movement, using machine learning to combine imaging and clinical parameters to create powerful predictive algorithms that can be applied to the diagnosis and treatment of liver cancer. Machine learning models use algorithms that self-improve by learning from patterns in large datasets. Current projects in our lab include the application of machine learning techniques to accurately diagnose primary hepatic liver cancers. Through our partnership with Philips Research North America, we are also developing a platform to process and visualize large volumes of data, advancing the research process of training and testing machine learning algorithms.
The following experimental calculator implements a machine-learning based algorithm for the prediction of tumor response after transarterial chemoembolization of patients with primary liver cancer based on the most predictive clinical and imaging parameters assessed before therapy (as published by Abajian A et al, JVIR February 2018). Follow the link to test the calculator with your own data: TACE response prediction
Our clinical studies range from collaborative, multicenter, federally (NCI) and industry-sponsored studies to independent, single site, physician-sponsored studies. Some of these studies are closely supervised by the FDA (IDE or IND).
Over the last decade, we have reported on the feasibility, safety, and efficacy of radioembolization (delivery of high doses of radiation to liver tumors), drug eluting bead chemoembolization (DEB-TACE) using beads designed to maximize drug concentrations, concurrent DEB-TACE with sorafenib (an agent given systemically with strong anti-angiogenic properties), and concurrent conventional chemoembolization (TACE) and bevacizumab (an anti-angiogenic biologic). These treatments were tested in both primary and secondary liver cancer, and the resulting studies have been published in various journals, including Journal of Clinical Oncology (JCO), Cancer, CVIR, JVIR and Radiology.https://medicine.yale.edu/cancer/patient/trials/
- Doxorubicin-eluting LC Bead M1 (DEBDOX) for patients with hepatocellular carcinoma – HIC# 1507016214
- Irinotecan Drug-Eluting Bead (DEBIRI) Therapy for Patients with Liver Metastases from Colorectal Cancer – HIC# 1507016214
- Lipiodol as an imaging biomarker of tumor necrosis after transcatheter chemoembolization therapy in patients with primary and metastatic liver cancer – HIC# 1601017054
- Pharmacokinetics of doxorubicin in cTACE of primary and secondary liver cancer – HIC# 1506016008
- A Phase II Trial of Systemic Chemotherapy (Gemcitabine and Cisplatin) in Combination with Conventional Transarterial Chemoembolization (cTACE) in Patients with Advanced Intra-Hepatic Cholangiocarcinoma (ICC)