Merchant SA, Shaikh MJS, Nadkarni P. Tuberculosis conundrum - current and future scenarios: A proposed comprehensive approach combining laboratory, imaging, and computing advances. World J Radiol 2022; 14(6): 114-136 [PMID: 35978978 DOI: 10.4329/wjr.v14.i6.114]
Corresponding Author of This Article
Suleman Adam Merchant, MBBS, MD, Former Dean, Professor & Head (Radiology), Lokmanya Tilak Municipal Medical College and General Hospital, Sion Hospital, Mumbai 400022, Maharashtra, India. suleman.a.merchant@gmail.com
Research Domain of This Article
Radiology, Nuclear Medicine & Medical Imaging
Article-Type of This Article
Review
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Radiol. Jun 28, 2022; 14(6): 114-136 Published online Jun 28, 2022. doi: 10.4329/wjr.v14.i6.114
Tuberculosis conundrum - current and future scenarios: A proposed comprehensive approach combining laboratory, imaging, and computing advances
Suleman Adam Merchant, Mohd Javed Saifullah Shaikh, Prakash Nadkarni
Suleman Adam Merchant, Lokmanya Tilak Municipal Medical College and General Hospital, Mumbai 400022, Maharashtra, India
Mohd Javed Saifullah Shaikh, Department of Radiology, North Bengal Neuro Centre, Jupiter magnetic resonance imaging, Diagnostic Centre, Siliguri 734003, West Bengal, India
Prakash Nadkarni, College of Nursing, University of Iowa, Iowa 52242, IA, United States
Author contributions: Merchant SA conceptualized the article; all authors wrote, read and approved the final manuscript.
Conflict-of-interest statement: All authors declare no conflict of interests for this article.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Suleman Adam Merchant, MBBS, MD, Former Dean, Professor & Head (Radiology), Lokmanya Tilak Municipal Medical College and General Hospital, Sion Hospital, Mumbai 400022, Maharashtra, India. suleman.a.merchant@gmail.com
Received: January 17, 2022 Peer-review started: January 17, 2022 First decision: March 16, 2022 Revised: April 17, 2022 Accepted: May 27, 2022 Article in press: May 27, 2022 Published online: June 28, 2022 Processing time: 162 Days and 7.5 Hours
Abstract
Tuberculosis (TB) remains a global threat, with the rise of multiple and extensively drug resistant TB posing additional challenges. The International health community has set various 5-yearly targets for TB elimination: mathematical modelling suggests that a 2050 target is feasible with a strategy combining better diagnostics, drugs, and vaccines to detect and treat both latent and active infection. The availability of rapid and highly sensitive diagnostic tools (Gene-Xpert, TB-Quick) will vastly facilitate population-level identification of TB (including rifampicin resistance and through it, multi-drug-resistant TB). Basic-research advances have illuminated molecular mechanisms in TB, including the protective role of Vitamin D. Also, Mycobacterium tuberculosis impairs the host immune response through epigenetic mechanisms (histone-binding modulation). Imaging will continue to be key, both for initial diagnosis and follow-up. We discuss advances in multiple imaging modalities to evaluate TB tissue changes, such as molecular imaging techniques (including pathogen-specific positron emission tomography imaging agents), non-invasive temporal monitoring, and computing enhancements to improve data acquisition and reduce scan times. Big data analysis and Artificial Intelligence (AI) algorithms, notably in the AI sub-field called “Deep Learning”, can potentially increase the speed and accuracy of diagnosis. Additionally, Federated learning makes multi-institutional/multi-city AI-based collaborations possible without sharing identifiable patient data. More powerful hardware designs - e.g., Edge and Quantum Computing- will facilitate the role of computing applications in TB. However, “Artificial Intelligence needs real Intelligence to guide it!” To have maximal impact, AI must use a holistic approach that incorporates time tested human wisdom gained over decades from the full gamut of TB, i.e., key imaging and clinical parameters, including prognostic indicators, plus bacterial and epidemiologic data. We propose a similar holistic approach at the level of national/international policy formulation and implementation, to enable effective culmination of TB’s endgame, summarizing it with the acronym “TB - REVISITED”.
Core Tip: A Holistic (comprehensive) approach is suggested to achieve tuberculosis (TB) elimination goals. Early diagnosis especially for Multi-Drug Resistant TB. Utility of Modern Rapid Diagnostic Tools. The role of Imaging in TB and key radiological signs. Comprehensive Artificial Intelligence(AI) algorithms incorporating key Imaging and clinical signs. The role of Vitamin D supplementation in complementing the TB drug regimen. Molecular Imaging. Quantum Computing and other perspectives in TB strategies to help achieve the various targets set for elimination of TB. A unified Global approach with edge computing/ dashboards and other technological innovations.
