Interstitial Optical Diagnosis and Treatment of Breast Cancer

Abstract

Spectral analysis of white light reflected from tissue provides a rapid, non-invasive, diagnostic technique. We have collected paired optical and conventional histologic measurements from 647 sites in breast tissue and axillary lymph nodes and looked for spectral features to identify cancer. Spectral analysis techniques known as model based analysis (MIBA) have been developed using artificial intelligence techniques such as neural networks and hierarchical cluster analysis coupled with innovative spectral processing that we are in the process of patenting. Our latest results show a sensitivity and specificity for detecting cancer in breast tissue or lymph nodes as given in the table. Therapy aims for complete ablation of small cancers using MR guided Interstitial Laser Photocoagulation (ILP). We have shown that ILP can ablate small cancers and that contrast enhanced MR can detect untreated areas of cancer as small as 2mm. Although the number of suitable patients for study is still small an additional year of research as agreed in a revised statement of work should increase the numbers treated significantly. ILP to 58 fibroadenomas confirmed that laser necrosed tissue is resorbed and the treated area heals safely. This makes ILP a promising treatment for fibroadenomas.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2001
Accession Number
ADA398292

Entities

People

  • Stephen Brown

Organizations

  • University College London

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Breast Cancer
  • Carcinoma
  • Data Analysis
  • Diseases And Disorders
  • General Surgery
  • Health Services
  • Laser Therapy
  • Lymph Nodes
  • Medical Personnel
  • Neoplasms
  • Neural Networks
  • Oncology
  • Optical Absorption
  • Pattern Recognition
  • Physicians
  • Surgery

Readers

  • Medical Imaging.
  • Oncology and Biomarker-Based Cancer Detection.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks
  • Directed Energy