Identification of Novel Features to Assess Risk and Improve Therapeutic Decision Making for Prostate Cancer Through a Novel High-Parameter Imaging System

Abstract

About 15 percent of men will be diagnosed with prostate cancer and many will face difficult treatment decisions. This projects goal is to develop and apply a novel imaging strategy that increases the information and potential clinical utility from prostate biopsy samples. Combining two high-dimensional imaging methods: antibody-based imaging mass cytometry (IMC), and mass spectroscopy imaging (MSI) that are layered together, the goal is to generate exceptionally detailed maps of the cells, molecules, and structures from tumor samples. These layered multi-modal images can be used to identify markers that improve assessments of risk and may ultimately inform clinical decisions. In the first year of the project, despite challenges resulting from the COVID 19 pandemic, we are nearing completion of method development and optimization studies, generated a tissue microarray containing (TMA) more than 80 prostate cancer biopsy samples, and have nearly completed imaging of the TMA by MSI. Work on applying the IMC platform to the TMA is ongoing. However, using data generated to date, significant progress was made in developing a novel computational workflow to integrate and analyze high-parameter imaging data.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2022
Accession Number
AD1180697

Entities

People

  • Patrick M. Reeves

Organizations

  • Massachusetts General Hospital

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Biomedical Research
  • Cells
  • Chemistry
  • Computational Biology
  • Computational Science
  • Correlation Analysis
  • Data Analysis
  • Data Compression
  • Data Transmission
  • Dimensionality Reduction
  • Health Services
  • Image Processing
  • Information Science
  • Lymphocytes
  • Machine Learning
  • Mass Spectrometry
  • Medical Personnel

Fields of Study

  • Medicine

Readers

  • Distributed Systems and Data Platform Development
  • Oncology
  • Oncology and Biomarker-Based Cancer Detection.