Pathologists Use Spatial Light Interference Microscopy to Predict Risk of Prostate Cancer Recurrence Prior to Biopsy or Surgery

SLIM uses a commercial phase contrast microscope and white light illumination, resulting in nanometer scale sensitivity to optical path-length shifts. In essence, SLIM combines phase contrast microscopy with holography.

Investigators at the University of Illinois (Urbana, USA) have introduced a new instrument for SLIM imaging. Their real-time fast SLIM technique could image at a maximum rate of 50 frames per second and provided real-time quantitative phase images at 12.5 frames per second. They were able to achieve this fast rate by combining rapid LCPM (linear pulse-code modulation) and a fast sCMOS camera. In addition, they developed the software to perform phase reconstruction and display the quantitative phase images in real-time.

In the current study, the investigators used the SLIM technique to examine 181 tissue samples obtained from the [US] National Cancer Institute-sponsored Cooperative Prostate Tissue Resource (CPCTR), The specimens were taken from individuals who had a prostatectomy, approximately half who had no recurrence and half who did.

The instrument was programmed to scan microscope slides containing 320–360 individual cores. The resulting SLIM image contained rich information about tissue morphology, with the glandular epithelium and stroma structures clearly resolved. This allowed the investigators to interrogate scattering changes specific to prostate stroma.

Results suggested that SLIM showed promise in assisting pathologists to improve prediction of prostate cancer recurrence. The data revealed that a lower value of anisotropy corresponded to a higher risk for recurrence, meaning that the stroma adjoining the glands of recurrent patients was more fractionated than in non-recurrent patients. Anisotropy is the property of being directionally dependent, as opposed to isotropy, which implies identical properties in all directions. It can be defined as a difference, when measured along different axes, in a material's physical or mechanical properties.

"For every 20 surgery procedures to take out the prostate, it is estimated that only one life is saved," said senior author Dr. Gabriel Popescu, associate professor of electrical and computer engineering at the University of Illinois. "For the other 19 people, they would be better left alone, because with removing the prostate, the quality of life goes down dramatically. So if you had a tool that could tell which patient will actually be more likely to have a bad outcome, then you could more aggressively treat that case."

"What SLIM is very good at is to make invisible objects visible with nanoscale sensitivity," said Dr. Popescu. "So we pick these structural details without the need for staining, which can introduce new variables into the specimen. Our dream is for everyone to have SLIM capabilities in their labs. One can imagine that a SLIM-based tissue imager will scan biopsies in a clinic and, paired with software that is intelligent enough to look for these specific markers, will provide the pathologist with valuable new information. This additional information will translate into more accurate diagnosis and prognosis."

The paper describing the use of SLIM to predict prostate cancer recurrence was published in the May 15, 2015, online edition of the journal Scientific Reports.

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