JMP2024 – An exploratory deep learning approach to investigate tuberculosis pathogenesis in nonhuman primate model

Faisal Yaseen, Murtaza Taj, Resmi Ravindran, Fareed Zaffar, Paul A. Luciw, Aamer Ikram, Saerah Iffat Zafar, Tariq Gill, Michael Hogarth and Imran H. Khan

Abstract:

Background
Tuberculosis (TB) kills approximately 1.6 million people yearly despite the fact anti-TB drugs are generally curative. Therefore, TB-case detection and monitoring of therapy, need a comprehensive approach. Automated radiological analysis, combined with clinical, microbiological, and immunological data, by machine learning (ML), can help achieve it.

Methods
Six rhesus macaques were experimentally inoculated with pathogenic Mycobacterium tuberculosis in the lung. Data, including Computed Tomography (CT), were collected at 0, 2, 4, 8, 12, 16, and 20 weeks.

Results
Our ML-based CT analysis (TB-Net) efficiently and accurately analyzed disease progression, performing better than standard deep learning model (LLM OpenAI’s CLIP Vi4). TB-Net based results were more consistent than, and confirmed independently by, blinded manual disease scoring by two radiologists and exhibited strong correlations with blood biomarkers, TB-lesion volumes, and disease-signs during disease pathogenesis.

Conclusion
The proposed approach is valuable in early disease detection, monitoring efficacy of therapy, and clinical decision making.

Text Reference:

 F. Yaseen, M. Taj, R. Ravindran, F. Zaffar, P. A. Luciw, A. Ikram, S. I. Zafar, T. Gill, M. Hogarth, and I. H Khan, "An exploratory deep learning approach to investigate tuberculosis pathogenesis in nonhuman primate model: Combining automated radiological analysis with clinical and biomarkers data," in Journal of Medical Primatology, 2024

Bibtex Reference:

@ARTICLE{JMP2024,
  author={F. Yaseen, M. Taj, R. Ravindran, F. Zaffar, P. A. Luciw, A. Ikram, S. I. Zafar, T. Gill, M. Hogarth, and I. H Khan},
  journal={Journal of Medical Primatology}, 
  title={An exploratory deep learning approach to investigate tuberculosis pathogenesis in nonhuman primate model: Combining automated radiological analysis with clinical and biomarkers data}, 
  year={2024},,
  doi={10.1111/jmp.12722}}