AI Analysis of PET/CT Images can Predict Side Effects of Immunotherapy in Lung Cancer

Dr. Watanabe and his teams from Niigata University have revealed that PET/CT image analysis using artificial intelligence (AI) can predict the occurrence of interstitial lung disease, known as a serious side effect of immunotherapy in lung cancer.

Immunotherapy has dramatically improved the treatment outcomes of primary lung cancer; however, it sometimes causes a serious side effect called interstitial lung disease. Interstitial lung disease is characterized by scarring (fibrosis) of the lungs and may be life-threatening owing to respiratory failure. Unfortunately, it is difficult to predict the occurrence of interstitial lung disease induced by immunotherapy. Accordingly, effective methods for predicting the risk of developing interstitial lung disease after immunotherapy are required.

This retrospective study investigated 165 patients with primary lung cancer who received immunotherapy at Niigata University Medical and Dental Hospital. As it is suggested that interstitial lung disease arises when inflammatory cells activated through immunotherapy damage healthy lung as well as cancer cells, the researchers hypothesized that patients with severe inflammation in healthy lungs prior to immunotherapy are more likely to develop interstitial lung disease after the treatment. Dr. Watanabe and his teams focused on PET/CT scan, a nuclear imaging test that is able to detect inflammation in the whole body. The researchers quantified the degree of inflammation in noncancerous lungs, namely lung regions without cancer, using AI analysis of PET/CT images. The study demonstrated that the risk of developing interstitial lung disease after immunotherapy is approximately 6.5 times higher in patients with high inflammation in the noncancerous lung than in those with low inflammation.

Dr. Yamazaki says "PET/CT is generally performed to detect cancer metastasis, but it would potentially be useful for estimating the risks of side effects associated with cancer treatment. The results of our study may not only help to predict the occurrence of interstitial lung disease after immunotherapy, but also to elucidate the mechanism of this serious side effect. We should conduct a multicenter prospective study for further investigation."

Yamazaki M, Watanabe S, Tominaga M, Yagi T, Goto Y, Yanagimura N, Arita M, Ohtsubo A, Tanaka T, Nozaki K, Saida Y, Kondo R, Kikuchi T, Ishikawa H.
18F-FDG-PET/CT Uptake by Noncancerous Lung as a Predictor of Interstitial Lung Disease Induced by Immune Checkpoint Inhibitors.
Acad Radiol. 2024 Sep 2:S1076-6332(24)00606-8. doi: 10.1016/j.acra.2024.08.043

Most Popular Now

Unlocking the 10 Year Health Plan

The government's plan for the NHS is a huge document. Jane Stephenson, chief executive of SPARK TSL, argues the key to unlocking its digital ambitions is to consider what it...

Alcidion Grows Top Talent in the UK, wit…

Alcidion has today announced the addition of three new appointments to their UK-based team, with one internal promotion and two external recruits. Dr Paul Deffley has been announced as the...

AI can Find Cancer Pathologists Miss

Men assessed as healthy after a pathologist analyses their tissue sample may still have an early form of prostate cancer. Using AI, researchers at Uppsala University have been able to...

AI, Full Automation could Expand Artific…

Automated insulin delivery (AID) systems such as the UVA Health-developed artificial pancreas could help more type 1 diabetes patients if the devices become fully automated, according to a new review...

How AI could Speed the Development of RN…

Using artificial intelligence (AI), MIT researchers have come up with a new way to design nanoparticles that can more efficiently deliver RNA vaccines and other types of RNA therapies. After training...

MIT Researchers Use Generative AI to Des…

With help from artificial intelligence, MIT researchers have designed novel antibiotics that can combat two hard-to-treat infections: drug-resistant Neisseria gonorrhoeae and multi-drug-resistant Staphylococcus aureus (MRSA). Using generative AI algorithms, the research...

AI Hybrid Strategy Improves Mammogram In…

A hybrid reading strategy for screening mammography, developed by Dutch researchers and deployed retrospectively to more than 40,000 exams, reduced radiologist workload by 38% without changing recall or cancer detection...

Penn Developed AI Tools and Datasets Hel…

Doctors treating kidney disease have long depended on trial-and-error to find the best therapies for individual patients. Now, new artificial intelligence (AI) tools developed by researchers in the Perelman School...

New Training Year Starts at Siemens Heal…

In September, 197 school graduates will start their vocational training or dual studies in Germany at Siemens Healthineers. 117 apprentices and 80 dual students will begin their careers at Siemens...

Are You Eligible for a Clinical Trial? C…

A new study in the academic journal Machine Learning: Health discovers that ChatGPT can accelerate patient screening for clinical trials, showing promise in reducing delays and improving trial success rates. Researchers...

New AI Tool Addresses Accuracy and Fairn…

A team of researchers at the Icahn School of Medicine at Mount Sinai has developed a new method to identify and reduce biases in datasets used to train machine-learning algorithms...

Global Study Reveals How Patients View M…

How physicians feel about artificial intelligence (AI) in medicine has been studied many times. But what do patients think? A team led by researchers at the Technical University of Munich...