New Imaging Technique for Improved Prostate Cancer Detection and Treatment

Science Highlights
March 9, 2015
Thomas M Johnson

A research team including NIBIB-funded scientists has developed an improved MRI technique with the potential to provide more precise and effective treatment for prostate cancer. The imaging technique improves upon standard MRI to obtain clearer images of the extent of the tumor and its exact location. A sharper image can provide more accurate biopsies, enable better treatment planning, and help surgeons pinpoint the tumor while sparing surrounding healthy tissue. 

RSI-MRI image of pelvic region showing prostate cancer
RSI-MRI image shows high grade cancer extending from prostate (purple) into the right seminal vesicle (orange) and a bony metastasis in the right hip (upper left, orange). Source: David Karow, UCSD

The work addresses a critical men’s health issue, given that prostate cancer is the most frequently diagnosed cancer in men aside from skin cancer. For 2015, the American Cancer Society estimates about 220,800 new cases of prostate cancer and about 27,540 deaths from the disease.1 The research team, from the University of California, San Diego, and the University of California, Los Angeles describe their findings in the January 6 online issue of the journal Prostate Cancer and Prostatic Disease.2 Their new technique of restriction spectrum imaging MRI (RSI-MRI) improves on the currently used diffusion MRI technique by correcting for magnetic field distortion to give a more exact image of tumor position.

Senior author Anders Dale, PhD., Professor of Radiology at UCSD, explains how RSI-MRI results in a better image. “Current imaging of prostate cancer is done with contrast-enhanced MRI. Unfortunately, some tumors fail to show a marked difference from surrounding healthy tissue due to lack of uptake of the contrast agent.” The technique of diffusion MRI improves on standard contrast MRI, but magnetic field artifacts often distort tumor location with that technique. “RSI-MRI corrects for this distortion, improving the accuracy of MRI to localize tumors,” says Nate White, PhD, Assistant Professor of Radiology at UCSD.

The work described in the publication includes a pilot clinical study in which RSI-MRI was compared with standard MRI in nine prostate cancer patients. The RSI-MRI technique successfully identified extraprostatic extension (EPE) in eight of the nine patients studied, while standard MRI identified only two of the nine patients as having EPE. This is a significant result because EPE indicates that the tumor has grown beyond the boundary of the prostate into surrounding tissue – a condition that indicates a more severe form of the disease that requires more aggressive treatment.

Although further clinical testing on a larger group of patients is needed, this is an encouraging result indicating the RSI-MRI may provide a valuable clinical imaging tool that can identify those patients with less severe disease, thus sparing them unnecessary treatment. Conversely, the ability to identify EPE will allow for more appropriate treatment plans for those with aggressive cancers. “And, in cases where surgery is warranted, the accurate RSI-MRI image will also guide a more discriminating surgery to completely remove the tumor while sparing surrounding healthy tissues; this is an important consideration for allowing patients to maintain sexual function and urinary control following surgery,” says David S. Karow, MD, PhD, corresponding author and Assistant Professor of Radiology at UCSD.

Image of prostate cancer using different MRI techniques
RSI-MRI identifies area of high grade tumor confirmed after prostate removal.
A. Blue areas of tumor identified by perfusion MRI.
B. Image from RSI-MRI identified areas of tumor (green) plus region suspected of being an area of high grade tumor (dark orange).
C. 3D rendering shows area of suspected high grade tumor in yellow as predicted by RSI-MRI.
D. Histological staining of prostate after removal showing the actual boundary of tumor outlined in blue.
Source: David Karow, UCSD.

 

Project funding was provided, in part, by the National Institute of Biomedical Imaging and Bioengineering award # EB000790 of the National Institutes of Health, the Department of Defense’s Prostate Cancer Research Program, the American Cancer Society and the UC San Diego Clinician Scientist Program.

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