A new model studied by researchers from China could help doctors to tell two different cancers apart. Mesothelioma scan results can often be confused with another cancer, called metastatic pleural disease (MPD).
Mesothelioma is a rare type of cancer that develops in the linings of internal organs. When the cancer grows in the lining of the lungs, it is called malignant pleural mesothelioma (MPM). This is because the lining the of the lungs and chest are called the pleura.
MPD also forms in the lining of the lungs. This cancer starts to grow in a different organ and spreads to the lung. Unlike mesothelioma, it is not caused by exposure to asbestos.
Difficulties in the Diagnosis of Mesothelioma
Mesothelioma is aggressive and treatment should start as soon as possible. Treatment is often delayed because mesothelioma can be difficult to diagnose. It can take decades after exposure to asbestos for symptoms to appear. And those symptoms often look like other, more common diseases.
The diagnosis of mesothelioma starts with an imaging scan. Computed tomography scans, or CT scans, are a type of X-ray. They take many X-ray scans from different angles. Doctors can use these scans to build a three-dimensional image of a patient’s body.
MPM and MPD look almost the same on a CT scan. This can make it hard for doctors to make the correct diagnosis. If that happens, the patient might need to undergo a more invasive biopsy procedure.
New Model That Can Help
An article published in Heliyon describes a model to help doctors tell the difference between malignant pleural mesothelioma and metastatic pleural disease using CT scans.
The study authors used data from 150 patients with MPM and 147 patients with MPD. The study authors compared the CT scans from these patients to look for important characteristics. They used this analysis to build a computer model that can tell the difference between MPM and MPD in a CT scan.
The model was successful at correctly identifying MPM and MPD from CT scans. The model will need more research with more patients to make a valuable diagnostic tool. It has the potential to make it easier for doctors to diagnose mesothelioma without invasive procedures.
Li Y, Cai B, Wang B, et al. Differentiating malignant pleural mesothelioma and metastatic pleural disease based on a machine learning model with primary CT signs: A multicentre study. Heliyon. 2022;8(11):e11383. Published 2022 Nov 4. doi:10.1016/j.heliyon.2022.e11383