title: Prediction of prostate cancer recurrence using quantitative phase imaging: Validation on a general population.
abstract: Prediction of biochemical recurrence risk of prostate cancer following radical prostatectomy is critical for determining whether the patient would benefit from adjuvant treatments. Various nomograms exist today for identifying individuals at higher risk for recurrence; however, an optimistic under-estimation of recurrence risk is a common problem associated with these methods. We previously showed that anisotropy of light scattering measured using quantitative phase imaging, in the stromal layer adjacent to cancerous glands, is predictive of recurrence. That nested-case controlled study consisted of specimens specifically chosen such that the current prognostic methods fail. Here we report on validating the utility of optical anisotropy for prediction of prostate cancer recurrence in a general population of 192 patients, with 17% probability of recurrence. Our results show that our method can identify recurrent cases with 73% sensitivity and 72% specificity, which is comparable to that of CAPRA-S, a current state of the art method, in the same population. However, our results show that optical anisotropy outperforms CAPRA-S for patients with Gleason grades 7-10. In essence, we demonstrate that anisotropy is a better biomarker for identifying high-risk cases, while Gleason grade is better suited for selecting non-recurrence. Therefore, we propose that anisotropy and current techniques be used together to maximize prediction accuracy.
authors.affiliation: Quantitative Light Imaging Laboratory, Department of Bioengineering, Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, 405N. Matthews Avenue, Urbana, IL 61801, USA.
authors.forename: Shamira
authors.initials: S
authors.lastname: Sridharan
authors.affiliation: Department of Pathology, University of Illinois at Chicago, 840S. Wood Street, Chicago, IL 60612, USA.
authors.forename: Virgilia
authors.initials: V
authors.lastname: Macias
authors.affiliation: Department of Pathology, Christie Clinic, University of Illinois at Urbana-Champaign, 1400W. Park Street, Urbana, IL 61801, USA.
authors.forename: Krishnarao
authors.initials: K
authors.lastname: Tangella
authors.affiliation: Department of Pathology, New York University Langone Medical Center, 462 First Avenue, New York, NY 10016, USA.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Melamed
authors.affiliation: Department of Pathology, New York University Langone Medical Center, 462 First Avenue, New York, NY 10016, USA.
authors.forename: Emily
authors.initials: E
authors.lastname: Dube
authors.affiliation: Department of Pathology, New York University Langone Medical Center, 462 First Avenue, New York, NY 10016, USA.
authors.forename: Max Xiangtian
authors.initials: MX
authors.lastname: Kong
authors.affiliation: Department of Pathology, University of Illinois at Chicago, 840S. Wood Street, Chicago, IL 60612, USA.
authors.forename: André
authors.initials: A
authors.lastname: Kajdacsy-Balla
authors.affiliation: Quantitative Light Imaging Laboratory, Department of Electrical and Computer Engineering, Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, 405N. Matthews Avenue, Urbana, IL 61801, USA.
authors.forename: Gabriel
authors.initials: G
authors.lastname: Popescu