Technologies that can provide new prognostic information and/or help make accurate, objective and automated decisions that aid the pathologist are sorely needed in prostate healthcare. The major goal of this project is to provide a chemical imaging instrument for clinical and research use that can be operated by any trained person in pathology laboratories. First, novel instrumentation and analytical methods for high-resolution Fourier transform infrared (FT-IR) spectroscopic imaging will be developed. Second, both structural (morphologic) and biochemical transformations that are characteristic of slow and rapidly growing tumors will be quantified. Third, analytical methods will be developed to relate the extracted information to aggressive potential of the tumor. Predictions will be compared to the clinical standard today (Kattan nomogram). A systems analysis approach is proposed to examine important histologic and chemical transformations that characterize aggressive lesions. New biochemical insight is expected from these models that will lead ultimately to an explanation of why we are able to define aggressive lesions accurately. If the project is successful, it has the potential to transform therapy decisions for patients and alter the standard practice in histologic assessment of research.
The major goal of this project is to leverage novel chemical imaging technology to identify those truly at risk of death from prostate cancer. To achieve this goal, we develop novel chemical imaging technology that can measure the spatial and molecular content of tissue as without the use of dyes or labels. Analytical methods will be developed to extract information from the measurements and relate it to biochemical knowledge of the prostate. A systems pathology approach, finally, is presented to predict those at risk. The project has the potential to transform therapy decisions for patients by identifying aggressive and indolent lesions accurately. This would enable focusing of resources on ~40,000 patients who have lethal disease and avoid wasteful expenditures on ~200,000 people. If successful, establishment of the instrumentation and analytical methods here would alter the standard practice in clinical histologic assessment of research in prostate cancer.
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| Tiwari, Saumya; Bhargava, Rohit (2015) Extracting knowledge from chemical imaging data using computational algorithms for digital cancer diagnosis. Yale J Biol Med 88:131-43 |
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| Kwak, Jin Tae; Kajdacsy-Balla, André; Macias, Virgilia et al. (2015) Improving prediction of prostate cancer recurrence using chemical imaging. Sci Rep 5:8758 |
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| Mayerich, David; van Dijk, Thomas; Walsh, Michael J et al. (2014) On the importance of image formation optics in the design of infrared spectroscopic imaging systems. Analyst 139:4031-6 |
| Holton, Sarah E; Bergamaschi, Anna; Katzenellenbogen, Benita S et al. (2014) Integration of molecular profiling and chemical imaging to elucidate fibroblast-microenvironment impact on cancer cell phenotype and endocrine resistance in breast cancer. PLoS One 9:e96878 |
| Mayerich, David; Walsh, Michael; Schulmerich, Matthew et al. (2013) Real-time interactive data mining for chemical imaging information: application to automated histopathology. BMC Bioinformatics 14:156 |
| Reddy, Rohith K; Walsh, Michael J; Schulmerich, Matthew V et al. (2013) High-definition infrared spectroscopic imaging. Appl Spectrosc 67:93-105 |
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