In an upcoming presentation on September 24, 2010 at the world's premier medical image analysis conference, Rutgers State University of New Jersey (New Brunswick, NJ, USA) biomedical engineers are said to be able to report that they achieved over 90% accuracy in distinguishing low-grade from high-grade prostate cancers by running computer analyses of the images and spectra made on 19 patients in an early research study. "The breakthrough we've had in the last few months is that we see image signatures that distinguish aggressive cancers from less aggressive ones,” said Dr. Anant Madabhushi, associate professor of biomedical engineering at Rutgers and a member of The Cancer Institute of New Jersey (CINJ; New Brunswick, NJ, USA).
These studies build on earlier research at Rutgers and elsewhere to identify prostate cancer using powerful, high-resolution MRI technology. "Now we're getting beyond merely identifying whether a person has cancer or not,” Dr. Madabhushi said. "This could lead to better patient management and cost savings.”
Biomedical engineering graduate student Pallavi Tiwari will present research results and describe image analysis techniques at the Medical Image Computing and Computer Assisted Intervention (MICCAI) Conference in Bejing, China, on September 24, 2010.
Mr. Tiwari and Dr. Madabhushi worked with Dr. John Kurhanewicz, professor of radiology and biomedical imaging at the University of California, San Francisco (USA), to obtain prostate gland images from 19 patients who later had radical prostatectomies. They evaluated both traditional MR images, which provide two-dimensional pictures of the gland's cellular structure, and MR spectroscopy, which maps concentrations of certain chemicals to locations in the prostate gland. Alteration in concentrations of these chemical metabolites--citrate, choline, and creatine--indicate the presence of cancer.
The researchers compared the MR images and spectra to digital images of the actual excised glands, which pathologists identified as having high-grade (aggressive) or low-grade (indolent) tumors using the established Gleason grading system. They used pattern recognition techniques to recognize characteristics of areas in the MR images and spectra that corresponded to the cancerous tissue in the excised samples. This involved utilizing computerized tools to align the MR views with digitized images of tissue slices, and to match the different resolutions of the images and spectra.
The objective is to "teach” the computer system to recognize effectively and consistently image patterns that correspond to various grades of cancerous tissue without having the tissue samples available to verify manually. Dr. Madabhushi noted that the techniques would have to be assessed on more people before they can be considered for clinical use. However, he is encouraged by the early results.
Each year, there are more than 27,000 deaths from prostate cancer in the United States and 190,000 new cases diagnosed. Most clinical diagnoses today are based on prostate-specific antigen (PSA) levels in blood, physical examinations, and needle biopsies. While one in six men might expect to get prostate cancer in their lifetimes, only one in 34 will die of it. Recent studies, including one at CINJ, suggest that men with low-risk cancers are receiving aggressive treatment. Improved diagnostic methods such as the Rutgers research could help patients with low-risk cancers and their physicians feel more confident with watchful waiting.
Also collaborating with the Rutgers researchers was Dr. Mark Rosen, associate professor of radiology at the Hospital of the University of Pennsylvania (Philadelphia, PA, USA).
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Rutgers State University of New Jersey
Hospital of the University of Pennsylvania
