Noninvasive Spatially Offset and Transmission Raman Mapping of Breast Tissue: A Multimodal Approach toward the in Vivo Assessment of Tissue Pathology
Abstract
The purpose of this research project is to develop new approaches that can impact early diagnosis of breast cancer, post-biopsy analysis, lymph node examinations, and drug delivery studies. The scope of this training involves optimizing Raman instrumentation and methods for efficient illumination and collection of Raman scattered light originating from deep within breast tissue. Experiments encompass designing tissue phantoms using Intralipid, dyes/pigments, inclusions, and agarose gel to quantitatively characterize the instruments' capabilities and performance. Additionally, we conduct spectroscopy on tissue biopsies to correlate spectral bands with healthy and diseased breast tissue. Observed spectral changes are compared to infrared images and H&E/HIS-stained images to relate observed biochemical changes to histology. The Raman data will be used to generate and train classification algorithms for automated histopathology as a starting point for in vivo work at the culmination of this training program. This report outlines progress for year 1 of the 3 year training program. In the approved statement of work 5 tasks were stated. All 5 tasks were successfully completed. We now have a working relationship with local clinicians. We have built-up a comprehensive database consisting of micrographs and IR spectral images for identify breast tissue histology and tissue chemistry. We have acquired Raman measurements on biopsied tissue. We have identified Raman spectral bands that can be used for distinguishing between different tissue types and have applied those Raman spectral bands to achieve cell-level contrast in Raman spectral images. Additionally, we have used clinical observations and interaction with clinicians to develop a conceptual design for a Raman Tomography instrument aimed at breast cancer screening. Finally for Raman tomographic reconstruction, we have evaluated existing diffuse optical tomography algorithms specifically for
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 01, 2012
- Accession Number
- ADA565856
Entities
People
- Matthew Schulmerich
Organizations
- University of Illinois Urbana–Champaign