With only 56 months left to end TB globally by 2030, the
progress is way off the mark. To end TB, we have to protect people from getting
infected with TB bacteria in the first place - and - we have to find all those
with TB disease (correct and timely diagnosis), link them to effective and
right treatment, care and support.
The Land of Smiles - Thailand - has done commendably well
in responding to TB over the years. For example, World Health Organization
(WHO) no longer lists it among high-burden countries for drug-resistant forms
of TB, but it continues to be in the list for high burden TB and TB-HIV
nations.
Thailand misses 1 in every 5 people with TB
disease
Out of the estimated 104,000 persons with TB disease in
Thailand in 2024, the country could diagnose and treat 81,700 of them. It
missed reaching out to over 22,000 people with TB – deadliest of all infectious
disease today. Annual TB decline (2023-2024) in Thailand as per the latest WHO
Global TB Report 2025 is 2% which is good but not good enough to end TB by
2030.
Ray of hope to find more TB in Thai hospitals
Health systems miss TB due to at least 2 major reasons:
1) access barriers faced by those most in need, 2) bad
diagnostic tools like microscopy that grossly underperforms in finding
TB (misses half or more of those with TB among those who take a TB test).
Diagnostic (and hence treatment) delays and catastrophic costs go in tandem.
That is why all the UN countries, including Thailand,
agreed at the 2023 United Nations General Assembly High Level Meeting on TB
that they would completely replace microscopy with WHO recommended molecular
tests for upfront TB testing by 2027.
As per latest WHO report, upfront molecular testing in
Thailand shot up to 69% in 2024 whereas globally it was 54% (and even lower in
South-East Asian region at 41%). The world has 20 more months to completely
replace poor performing TB microscopy test with upfront molecular testing (by
2027).
AI means Artificial intelligence as
well as “All Inclusive” approach
Evidence shows that not just diagnosing TB correctly is
enough but early and timely diagnosis is critical too. AI helps us find
people with TB even when they have no symptoms.
Thailand is deploying many more proven strategies to
improve infection prevention and control, find more TB early enough and link
those diagnosed with TB to right treatment, care and support. One such proven
tool is artificial intelligence (AI) which is helping Thai healthcare
professionals to not-miss those with TB (and few other diseases which
are screened by AI).
In 2022, Thailand FDA had approved Genki AI,
which is an AI powered lung health screening software (developed by DeepTek) to
automate the interpretation of chest X-rays for 27 different pathologies
including TB. Genki is also approved by US FDA and by regulators of several
other countries/ regions, such as European Union, Singapore, India, Malaysia,
Kenya, Indonesia, among others.
Thailand’s FDA approved Genki AI for screening for
a range of pathologies including TB, general opacity, pneumonia, nodules,
atelectasis, fibrosis, lung mass, opaque hemithorax, oedema, calcification,
pleural effusion, pleural thickening, pneumothorax, cardiomegaly among
others.
AI turning point of 2021
In July 2021, WHO had integrated AI
powered computer-aided detection software into its official guidelines for
TB screening and diagnosis to help bridge the "missing
millions" gap in TB detection. AI powered software can be used to
interpret digital chest X-rays for TB screening.
This was historically the first time ever when
AI powered computer-aided detection software was recommended for use in
interpreting chest X-Rays for TB. Several studies have shown that AI-enabled
computer-aided detection software can achieve highly sensitive TB detection in
population-based screening and its accuracy is at-par with human readers.
Moreover, AI enabled TB screening tools - like Genki - are highly cost
effective in resource limited high burden settings.
CNS Managing Editor Shobha Shukla visited one of Thailand’s
hospitals which is almost half a century old in Chonburi province - Aikchol
Hospital where noted radiologist Dr Grisit Prueksaritanond has been using Genki
AI for over a year now. Chonburi province is among those Thai provinces like
Bangkok notable for higher TB rates.
Dr Grisit shared insights on how Genki AI is helping him
not-miss TB and other lung abnormalities. Aikchol Hospital has X-Rays including
mobile X-Ray (of Shimadzu, Japan) powered with Genki AI.
Among over 1000 chest X-Rays scanned in a year with Genki
AI (as well as by Dr Grisit), it helps Dr Grisit reconfirm his X-Ray
interpretation and diagnosis, and has helped him stop missing 3 cases with
lesions - which otherwise (without Genki AI) would have been missed.
“Genki AI is crucial. I think it is very helpful,” said Dr
Grisit.
Multi-disease AI screening is a boon too
Dr Grisit points out that when Genki AI helps detect an
abnormality in the lung, “It is already very helpful.” This needs to be
followed up with medical expert’s further investigations (like confirmatory
tests and expert medical assessment and advise), be it general opacity, TB,
nodule, fibrosis, or lung mass, among others.
Dr Grisit reflected that “as long as it (Genki AI) can
detect something in the lung, I can evaluate further. Sometimes, I just might
have missed it wholly if I was not using any programme (AI).”
Dr Grisit underpinned importance of Genki AI screening of
chest X-rays in finding not just more TB, but also those with fibrosis,
pneumonia, pneumothorax, or nodules.
It is noteworthy that WHO is also shifting towards
multi-disease elimination approach in recent years.
Do not misdiagnose but diagnose early,
correctly
Dr Grisit highlighted the importance of not missing any
patient with lung abnormality. In the last one year, AI helped him diagnose at
least 3 cases correctly (which otherwise would have been missed). “So, I think
that is worth more. It is very sensitive – it is more sensitive than my eyes.
So that's better!”
Dr Grisit says that in settings where availability of
radiologists is scarce, AI can be a bigger boon.
Thailand is a higher middle-income country. But
availability of human experts is often scarce in low- and middle-income
countries. So it saves the time of experts where AI can be of help. And who
gets benefitted the most? The underserved people.
Generally speaking, AI became a substitute for a human
expert reader in places where experts (like a radiologist or trained medical
officer) were not available to detect abnormalities consistent with TB and
avoid delays in the care pathway – especially in low- and middle-income
countries. For example, Indian government has deployed AI-enabled handheld
X-Rays for screening high risk populations for TB.
While referring to AI computer aided detection of TB, Dr
Grisit said that "I think it is quite useful for the country that has few
radiologists. And it is also quite helpful if even where you have a radiologist
because AI can double check that he/she/they are not missing any finding in the
chest X-Ray."
Triaging those who do not have a disease
Especially in high burden and low resource settings, it is
important to triage those who are likely to not have the disease. AI is a great
help in this context, said Dr Grisit. “Ruling out people who do not have any
problem is important – and it is much quicker this way (so that those with some
health problems can access care earlier). Otherwise, it would be a very tedious
process for those people who do not have any disease or any lesions to get
ruled out.” Dr Grisit underpins the importance of medical experts (which is
often a legal mandate too) while we expand the use of AI in health systems.
With 56 months to end TB, Thailand - and the world - has to
keep the #endTB and #SDGs promise. We have to prevent people from getting
infected with TB disease as a human rights imperative - and those with TB
bacteria must access standard care in person-centred, rights-based and gender
transformative manner, where no one is left behind.
