CLIFTON PARK, N.Y., Aug. 20 — In cancer drug research, existing imaging technologies used to assess treatment response are expensive, time consuming, and difficult to operate. To overcome these challenges, the National Institutes of Health (NIH) has funded a $1.26 million small-business research project, led by Kitware, to develop a low-cost and widely applicable system for assessing cancer treatment efficacy.
The research project is centered on a novel approach to cancer detection and diagnosis that is based on using acoustic angiography to measure small changes in the microvessels that feed tumors. Acoustic angiography is a contrast-enhanced ultrasound imaging technique that is being developed by Dr. Paul Dayton at The University of North Carolina at Chapel Hill (UNC), who is a principal investigator on the project. The technique can provide unprecedented clarity in visualizing microvascular abnormalities associated with malignant cancers that resolve when those cancers respond to treatment. Although acoustic angiography is promising, manually measuring the microvessel changes that it reveals can be time consuming and prone to error. For the research project, acoustic angiography is combined with automated vessel modeling and computer-aided diagnosis methods developed at Kitware to provide a low-cost, fast, and accurate cancer treatment monitoring system.
“The characterization of microvascular features for the diagnosis and monitoring of cancer has shown great promise, but the application of this technique has traditionally involved costly imaging equipment and highly constrained conditions,” Dr. Stephen Aylward, a principal investigator on the project and Senior Director of Medical Research at Kitware, said. “Combining computer-aided diagnosis of microvasculature with acoustic angiography creates a powerful and practical diagnostic tool for preclinical and clinical cancer research.”
During Phase I of the project, Kitware and the Dayton Lab at UNC confirmed that the novel ultrasound-based approach can distinguish benign tumors from malignant tumors and track vascular changes throughout disease development. The team also optimized the methods for modeling and analyzing vessels so that they run in minutes, rather than hours, and offer significantly improved accuracy.
For Phase II, the team will partner with SonoVol to integrate the proposed approach into a commercial ultrasound imaging system for preclinical research. The system will provide cancer researchers with an innovative tool for studying animal models of malignancies in nearly any organ in the body. It will enable rapid alignment of images taken over time for observing longitudinal vascular remodeling and present substantial benefits over existing technologies. For example, the system will cost less than half of what traditional systems cost; it will be suitable for users who do not have expertise in imaging physics; and it will be benchtop, user agnostic, and noninvasive.
“An equivalently fast, accurate, noninvasive, low-cost, and quantitative tumor micro-environment imaging instrument does not exist,” Aylward said. “As a result, most researchers have to reserve time and expert support on shared instruments at facilities that charge extremely high fees. The proposed system will provide affordable and easy-to-use technology that could accelerate the pace of cancer research, bringing life-saving therapeutics to the patient’s bedside sooner and with a lower development cost.”
As part of the Phase II effort, Kitware will release algorithms for vessel modeling and analysis as open-source software, building on the Insight Segmentation and Registration Toolkit (ITK) and the 3D Slicer application for medical data visualization. Both ITK and 3D Slicer are freely available. They are developed and supported by Kitware and are used in medical image analysis research and commercial products throughout the world.
In addition to participating in the collaborative research effort, Kitware provides consulting services to groups that seek to build commercial systems using ITK and 3D Slicer, as well as Kitware’s expertise in low-cost ultrasound applications, vessel quantification, and other medical technologies. To learn more about leveraging Kitware’s expertise, please contact Stephen Aylward at kitware(at)kitware.com.
Kitware is an advanced technology, research, and open-source solutions provider for research facilities, government institutions, and corporations worldwide. Founded in 1998, Kitware specializes in research and development in the areas of HPC and visualization, medical imaging, computer vision, data and analytics, and quality software process. Among its services, Kitware offers consulting and support for high-quality software solutions. Kitware is headquartered in Clifton Park, NY, with offices in Carrboro, NC; Santa Fe, NM; and Lyon, France. More information can be found on http://www.kitware.com.