Monitoring breast cancer treatment using a Fourier transform infrared spectroscopy-based computational model

Area of Science:

• Biomedical Engineering
• Medical Physics
• Oncology

Background:

• Breast cancer impacts many women, necessitating advanced diagnostic and therapeutic monitoring tools.
• Current chemotherapy lacks effective methods for real-time efficacy assessment during treatment.
• Vibrational spectroscopy, specifically FTIR, offers insights into tissue chemical composition.

Purpose of the Study:

• To develop and validate a physics-based computational model for monitoring breast cancer chemotherapy efficacy.
• To utilize Fourier transform infrared (FTIR) spectroscopy to analyze spectral differences in breast tissues.
• To correlate spectral data with patient outcomes to assess treatment effectiveness.

Main Methods:

• Collected and analyzed FTIR spectra from healthy, cancerous, and post-chemotherapy breast tissues.
• Applied Kramers-Kronig transformation and Lorentz function fitting to extract characteristic spectral parameters.
• Developed a physics-based computational model using Lorentz function parameters to predict chemotherapy efficacy.

Main Results:

• Significant spectral differences were observed between healthy, cancerous, and post-chemotherapy tissues.
• Post-chemotherapy spectra mirrored healthy tissue spectra with effective treatment and cancerous tissue spectra with ineffective treatment.
• The computational model accurately reflected actual patient treatment outcomes from medical records.

Conclusions:

• The developed computational model, based on FTIR spectral analysis, shows promise for monitoring breast cancer chemotherapy efficacy.
• This approach provides a non-invasive method to assess treatment response, aiding clinical decision-making.
• The model's ability to correlate spectral data with patient outcomes highlights its potential as a valuable clinical tool.