Multiphoton Microscopy for Identifying Collagen Signatures Associated with Biochemical Recurrence in Prostate Cancer Patients

Abstract

Prostate cancer is a heterogeneous disease that remains dormant for long periods or acts aggressively with poor clinical outcomes. Identifying aggressive prostate tumor behavior using current glandular-focused histopathological criteria is challenging. Recent evidence has implicated the stroma in modulating prostate tumor behavior and in predicting post-surgical outcomes. However, the emergence of stromal signatures has been limited, due in part to the lack of adoption of imaging modalities for stromal-specific profiling. Herein, label-free multiphoton microscopy (MPM), with its ability to image tissue with stromal-specific contrast, is used to identify prostate stromal features associated with aggressive tumor behavior and clinical outcome. MPM was performed on unstained prostatectomy specimens from 59 patients and on biopsy specimens from 17 patients with known post-surgery recurrence status. MPM-identified collagen content, organization, and morphological tumor signatures were extracted for each patient and screened for association with recurrent disease. Compared to tumors from patients whose disease did not recur, tumors from patients with recurrent disease exhibited higher MPM-identified collagen amount and collagen fiber intensity signal and width. Our study shows an association between MPM-identified stromal collagen features of prostate tumors and post-surgical disease recurrence, suggesting their potential for prostate cancer risk assessment.

Label‐free detection of invasive micropapillary carcinoma of the breast using multiphoton microscopy

“…MPM not only has the advantage of resolution comparable to digital histopathology, but also has the advantages of label-free, low photobleaching and photodamage, and a high imaging contrast. Therefore, MPM has been receiving a lot of attention in the field of basic and applied research in medical pathology diagnosis, especially in the clinical translation of tumor pathological diagnosis [40][41][42][43]. In this study, our results demonstrate that MPM can be used to detect the different morphologies of IMPC cell clusters, and to identify stromal pathological changes in tumor microenvironment such as collagen changes, TILs, lymphatic vascular invasion.…”

Prostate cancer tissue classification by multiphoton imaging, automated image analysis and machine learning

“…The first reports showed that there is an increase on the collagen alignment with the increase of the Gleason grade [33, 34]. In addition, recent results [36] for 64 patients showed that the collagen morphology characteristics are associated with biochemical recurrence.…”