Q&A with Lawrence Schwartz, M.D., Columbia University Medical Center: Vol-PACT Project Expansion Initiates Analysis of Cancer Tumor Growth with Novel Measurement Technique

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Lawrence SchwartzMay 8, 2018 — Since 2017, the Foundation for the National Institutes of Health (FNIH) Biomarkers Consortium (BC) has been developing new methods for analyzing digital images that can help track a patient’s response to cancer therapy. Housed within the BC’s Cancer Steering Committee, the project called “Advanced metrics and modeling with Volumetric CT for Precision Analysis of Clinical Trial results” (Vol-PACT) has the potential to accelerate the creation of cancer therapies and to improve treatment options for patients.

With a team comprised of experts from the public and private sectors, including the National Cancer Institute and U.S. Food and Drug Administration, the project is the first to use imaging data from completed phase II/III clinical trials sponsored by industry to measure characteristics of cancer progression and to generate potential biological markers to track the disease. As this initial project continued, the sponsors recognized the Vol-PACT team’s unique capabilities and have now provided additional financial and data-sharing support to advance even more cutting-edge techniques in the field of image analysis.

The expanded project will enhance the scope of Vol-PACT by utilizing the sponsors’ valuable trial data sets to pioneer a novel measurement technique called kinetic modeling. This technique allows cancer researchers to use dynamic changes in tumor growth to predict treatment response and patient outcomes. The project team also will use radiomic assessment to provide a more detailed analysis of tumor images using computer algorithms, revealing information undetected by standard human review. In the following Q&A, project Principal Investigator Lawrence Schwartz, M.D., James Picker Professor and Chairman for the Department of Radiology at Columbia University Medical Center, discussed the significance of the project’s expansion.

1. How is the project expanding?
The original Vol-PACT project plan intended to augment the tools radiologists use to recognize tumor growth by adding multi-dimensional tumor measurement to their arsenal. Moving beyond tumor measurement, the extension will use kinetic modeling to look deeper into the portions of tumors that are growing, or at those portions that are being effectively managed through treatment, to gain a greater understanding of treatment effect. In addition, radiomics utilizes artificial intelligence to identify and assess features unrecognized by the human eye, enabling the project team to make valuable contributions to the development of metrics for drug development.

2. Why is the project expansion important?
Through data analysis of 10 different completed trials provided by the sponsors thus far, the project team has recognized that identifying a primary lesion and tracking its growth is a relatively simplistic way of understanding patient treatment effect. With these additional tools, the project team will now be exploring ways to incorporate the review of multiple lesions to more completely assess the effect of treatment on the patient.

The team is incorporating advanced metrics, such as reviewing all of a patient’s tumors (e.g. total tumor burden), in addition to capturing volumetric measurements of the entire tumor. In this project extension, we will analyze parts of the Vol-PACT data sets and provide new metrics that will more accurately predict patient outcomes.

3. How will this project help patients in the future?
Using kinetic modeling and radiomics the team hopes to develop new metrics that identify tumor progression in patients earlier during treatment. If outcomes can be assessed earlier with these metrics, fewer patients are needed in phase III drug trials, and trial duration can be shortened, bringing life-saving drugs to market faster. Ultimately, we hope these new methodologies designed to assess a patient’s tumor burden and a change in that burden, will help to personalize cancer therapy and make important changes for a patient to help prolong life in a meaningful way.

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