Prostate cancer is a leading cause of male mortality worldwide, for which radical prostatectomy (removal of the entire prostate) is the standard-of-care. After surgery, the excised prostate is submitted for histopathology, a process that is time-consuming and expensive due to the large volume of the whole RP specimen. A large number of these prostate slices do not contain any abnormal tissue, for which the laborious downstream histopathology processes of chemical fixation, tissue embedding, sectioning, staining, slide mounting, and microscopic evaluation are unnecessary and wasteful. As a result, nearly 90% of all US prostate pathologists utilize partial-sampling strategies (in contrast to a total-sampling of all slices) to reduce the histopathology workload. Currently these methods are ?blind?, and consist of simply attempting to identify prostate slices with grossly identifiable tumor (for which less than a third are visible), or simply analyzing every other prostate slice. While these methods reduce time and labor costs, they yield less accurate pathological results than a total- sampling of the entire prostate, and have been shown to lead to inferior patient outcomes. Therefore, there is great interest and value in an ?intelligent? method of triaging the number of normal prostate slices sent for a full pathological work up while maintaining the same pathological quality provided by a total-sampling. Our proposed solution is to enable intelligent pathology by rapidly imaging the surfaces of each prostate slice using a novel light-sheet microscopy (LSM) approach, which will accurately triage normal prostate slices with no tumor tissue from the full pathological makeup (primary goal) and also enable a preliminary estimate of tumor size, location, grade, and margin status (secondary goals). Previous microscopy systems with a narrow depth of focus have had limited clinical adoption due to the need for elaborate tissue- flattening and alignment procedures when imaging the irregular surfaces of freshly excised tissues. In contrast, the proposed LSM system will have a wide depth of focus that will enable high-resolution imaging of this irregular surface over a large field of view without the need for time-consuming flattening and alignment. The system performance will initially be characterized and validated with tissue phantoms, including comparisons with Monte Carlo simulations. In addition, we will image freshly excised prostate slices, which will be compared with conventional H&E histopathology in a pilot study to obtain a preliminary assessment of the sensitivity and specificity of the LSM system. Our project team has a diverse set of expertise that includes the development of novel microscopes and contrast agents for the assessment of diseased tissues, as well as prostate pathology and research. This team will ensure the successful development of a wide-area LSM system for rapid imaging and pathology of freshly excised prostate tissues. Finally, with the help of a comprehensive mentoring committee, the candidate will be trained in all aspects of this work to succeed in a biomedical optics and cancer imaging research career.
This project aims to design, fabricate, validate, and translate a new light sheet microscopy system to help improve the efficiency of the current prostate pathology workflow. The proposed system has the potential to greatly reduce the number of normal prostate slices sent for full pathological makeup, as well as enable a preliminary estimate of tumor size, location, grade, and margin status. This will allow pathologists to more intelligently sample the total number of prostate slices and closely assess only those which contain diseased tissue, as well as more accurately examine the surgical specimen to guide subsequent adjuvant therapies, thereby resulting in significant healthcare savings and improved patient outcomes.
| Glaser, Adam K; Chen, Ye; Yin, Chengbo et al. (2018) Multidirectional digital scanned light-sheet microscopy enables uniform fluorescence excitation and contrast-enhanced imaging. Sci Rep 8:13878 |
| Glaser, Adam K; Reder, Nicholas P; Chen, Ye et al. (2017) Light-sheet microscopy for slide-free non-destructive pathology of large clinical specimens. Nat Biomed Eng 1: |
