One of the most respected prostate cancer research facilities is the National Cancer Institute:
The National Cancer Institute (NCI) is the federal government’s principal agency for cancer research and training. Established under the National Cancer Institute Act of 1937, NCI is part of the National Institutes of Health (NIH), one of 11 agencies that make up the Department of Health and Human Services (HHS).
As a branch of HHS, our tax dollars support it. However, as the “principal agency for cancer research” it is not unusual for a study conducted under NCI auspices to be funded by a public-private partnership. In addition to federal funding, contributions come from foundations, industry and other private donors. This is testimony to the importance of the quest to cure and prevent prostate cancer (PCa).
An essential element in that quest is multiparametric MRI (mpMRI) of the prostate. When done before a biopsy, it can rule out unnecessary needle biopsies provided that the imaging and interpretation are done on state-of-the-art magnets by experienced mpMRI teams. In addition, the reporting of scan results must be accurate and standardized.
PI-RADS standardizes mpMRI reporting
To report suspected PCa seen on mpMRI, we use the Prostate Imaging Reporting and Data and System (PI-RADS). As a standardized prostate MRI guideline, PI-RADS was first released in 2012 as PI-RADSv1.0 (version 1). It was revised in 2015 and released as PI-RADSv2.0 (version 2). This version recognized that the individual parameters (imaging sequences) have certain strengths in each anatomic prostate zone:
- Diffusion weighted imaging (DWI) is dominant in the peripheral zone
- T2-weighted (T2W) is dominant in the transition zone
- Dynamic contrast enhanced (DCE) MRI may clarify that a lesion in the peripheral zone which appears as PI-RADS score 3 is actually a score 4 lesion.
Thus, integrating each result provides a detailed, individualized, high resolution prostate portrait.
After being used for a number of years, PI-RADSv2.0 was found to lack sufficient agreement among readers. So, changes in descriptions and definitions were implemented “to help radiologists make more accurate and reproducible interpretations.”[i] In 2019, PI-RADSv2.1 (version 2.1) was born.
As with its predecessors, after all parameters are interpreted, PI-RADSv2.1 culminates in a final overall score for each suspicious lesion. Scores range from 1 (least probability of being PCa) to 5 (greatest probability). However, v2.1 is based in a richer “vocabulary” so the overall scores should be more accurate, and achieve greater interobserver agreement. Does it improve cancer detection? A team of NCI researchers designed an imaging/biopsy study to put PI-RADSv2.1 to the test.
I mentioned funding partnerships for NCI studies, and such an alliance was formed to support this study. Not only NIH resources, but contributions also came from charitable foundations, Genentech, the American Association for Dental Research, the Colgate-Palmolive Company, and others–an impressive commitment to PCa research!
The NCI study design
To put PI-RADSv2.1 through its paces to determine if it has better cancer detection rates than its older sibling, the NCI study included 110 men with suspected prostate cancer (PCa) who had not yet had any treatment. Each participant underwent mpMRI on a powerful 3T magnet. A total of 171 suspicious lesions were identified (average 1.56 lesions per participant). Using the standards laid out in PI-RADSv2.1, “Each lesion was assigned an overall PI-RADSv2.1 score (1–5). Negative mpMRI findings [no MRI evidence of PCa] were assigned to PI-RADS category 1.”[ii]
Patients were then assigned to biopsy as follows:
Study findings
One important result of this study was that cancer detection rate increased as PI-RADS scores got higher. This was true of a similar 2017study of PI-RADSv2.0. The difference between the two studies, however, is a better overall detection rate with PI-RADSv2.1. The authors discuss how the updates in definitions and descriptions leave less room for subjective interpretations by readers. However, of the 16 men with PI-RADS 1 (negative for PCa), 8 were found to have cancer based on systematic TRUS biopsy—and 3 of those were significant. This raises an unsettling question about the sensitivity of mpMRI for detecting significant disease. However, the authors are optimistic about the growing ability of Artificial Intelligence (AI) to identify suspicious sites that may not be visible to the human eye.
The Sperling Prostate Center is experienced with the PI-RADSv2.1 standardized reporting system, and we are rapidly incorporating AI in our PCa detection and diagnosis technology. We send a shout-out to the NCI team for their diligent studies, and we share their optimism about the future of AI in PCa.
NOTE: This content is solely for purposes of information and does not substitute for diagnostic or medical advice. Talk to your doctor if you are experiencing pelvic pain, or have any other health concerns or questions of a personal medical nature.
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About Dr. Dan Sperling
Dan Sperling, MD, DABR, is a board certified radiologist who is globally recognized as a leader in multiparametric MRI for the detection and diagnosis of a range of disease conditions. As Medical Director of the Sperling Prostate Center, Sperling Medical Group and Sperling Neurosurgery Associates, he and his team are on the leading edge of significant change in medical practice. He is the co-author of the new patient book Redefining Prostate Cancer, and is a contributing author on over 25 published studies. For more information, contact the Sperling Prostate Center.
