Researchers from University of Illinois at Urbana-Champaign have developed a quantitative phase imaging technology which is used to predict the prostate cancer recurrence. This study was published on Scientific Reports.

It is estimated that while 233,000 men will be diagnosed with prostate cancer in2014 in USA alone accounting for 14.0% of all cancer cases, the number of men who will die of the disease is 29,480 accounting for 5.0% of all cancer deaths. Because most prostate cancers are not lethal, active surveillance is a desirable treatment option for patients presenting with localized prostate cancer, low prostate specific antigen(PSA) levels, and low risk.

However, radical prostatectomy reduces the risk of bone metastasis and mortality among patients in the intermediate and high risk categories. Clearly, a method capable of forecasting recurrence is highly desirable. The commonly used tools to predict biochemical prostate cancer recurrence after prostatectomy.

In this study, researchers used a label-free method, spatial light interference microscopy, to perform localized measurements of light scattering in prostatectomy tissue microarrays. For the first time, they show that anisotropy of light scattering in the stroma immediately adjoining cancerous glands can be used to identify patients at higher risk for recurrence. Their data show that lower value of anisotropy corresponds to a higher risk for recurrence, meaning that stroma adjoining the glands of recurrent patients is more fractionated that in non-recurrent patients.

Their method outperformed the widely accepted clinical tool CAPRA-S in the cases we interrogated irrespective of Gleason grade, prostate-specific antigen (PSA) levels and pathological tumor-node-metastasis (pTNM) stage. These results suggest that QPI shows promise in assisting pathologists to improve prediction of prostate cancer recurrence.

Reference:Sridharan S, Macias V, Tangella K, et al. Prediction of Prostate Cancer Recurrence Using Quantitative Phase Imaging[J]. Scientific Reports, 2015, 5.