Faisal Yaseen, Murtaza Taj, Resmi Ravindran, Fareed Zaffar, Paul A. Luciw, Aamer Ikram, Saerah Iffat Zafar, Tariq Gill, Michael Hogarth, Imran H. Khan
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An exploratory deep learning approach to investigate tuberculosis pathogenesis in nonhuman primate model: Combining automated radiological analysis with clinical and biomarkers data
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.
期刊介绍：
The Journal of Medical Primatology publishes research on non-human primates as models to study, prevent, and/or treat human diseases; subjects include veterinary medicine; morphology, physiology, reproductive biology, central nervous system, and cardiovascular diseases; husbandry, handling, experimental methodology, and management of non-human primate colonies and laboratories; non-human primate wildlife management; and behaviour and sociology as related to medical conditions and captive non-human primate needs.
Published material includes: Original Manuscripts - research results; Case Reports - scientific documentation of a single clinical study; Short Papers - case histories, methodologies, and techniques of particular interest; Letters to the Editor - opinions, controversies and sporadic scientific observations; Perspectives – opinion piece about existing research on a particular topic; Minireviews – a concise review of existing literature; Book Reviews by invitation; Special Issues containing selected papers from specialized meetings; and Editorials and memoriams authored by the Editor-in-Chief.
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