Posted on September 14th, 2021
Patients undergoing treatment for rare malignancies associated with occupational exposure to asbestos are now being evaluated using AI in a pilot study. Scientists have developed a prototype imaging system that has proved effective with mesothelioma and can accelerate much-needed breakthroughs in diagnosis and therapy.
Prolonged exposure to asbestos causes mesothelioma, a devastating form of cancer that most commonly affects the lungs and abdomen. Pleural mesothelioma is a rare kind of cancer that begins in the thin tissue lining that surrounds the lungs, called the pleura. The prognosis is extremely poor, and the overwhelming majority of individuals with malignant pleural mesothelioma are identified at an advanced stage.
At present, treatment options for mesothelioma, including chemotherapy, radiotherapy, and surgery, are limited, and clinical trials are essential for the development of new, more effective therapies. The prototype artificial intelligence system is capable of recognizing mesothelioma on CT scans, and it is anticipated that this technology would enable clinical trials of novel medicines to be conducted more quickly.
Because of its thermal stability and indestructibility, asbestos can resist deterioration for decades under virtually any circumstances. As a result of these desirable properties, asbestos became virtually miraculous in the eyes of manufacturers, who began utilizing it in hundreds of commercial applications, materials, equipment, and industrial materials. For instance, it was widely used as an insulator in the building of power plants, helping in the achievement of the high temperatures required to run the boilers and generate electricity.
Asbestos is now well recognized as a health threat, and its usage is strictly controlled by the Occupational Safety and Health Administration (OSHA) and the Environmental Protection Agency (EPA). Every time a worker cuts, drills, or handles materials that contain asbestos in any manner that produces dust, they are putting themselves at risk of serious illness. According to epidemiologic data, all asbestos fiber forms, including the most frequently used form of asbestos, chrysotile, induce mesothelioma in humans.
Between the 1930s and 1980s, asbestos became the most widely used mineral in all military branches. The hazardous mineral was widely employed on ships, tanks, trucks, aircraft, and vehicles, mainly for its durability, resilience to heat, and fireproofing properties. Besides asbestos-containing machinery and equipment in the military, the carcinogenic substance was utilized in barracks, mess halls, hospitals, and other structures where troops slept, worked, and ate. Other asbestos-containing items in the military were pipes, gaskets, valves, tubing, and grinders. The Navy has the greatest incidence of asbestos-related illnesses among its veterans due to the extensive usage of asbestos in shipbuilding.
On Navy ships, the highest concentrations of asbestos were found near boilers, engines, ammunition, and even sleeping rooms and mess halls. Despite the risk of exposure, companies such as Bethlehem Steel Shipyard, Long Beach Naval Shipyard, and Richmond Shipyard continued to utilize asbestos in all parts of ships, from stern to bow. Numerous shipyards with asbestos issues have been placed on the EPA's Superfund list, including Anniston Army Depot, Alabama Drydock and Shipping Company, Bender Shipbuilding and Repair Company, Gulf Shipbuilding Company, and Avondale Shipyards.
Occupational asbestos exposure through inhalation, and to lesser extent ingestion, can cause a range of asbestos-related conditions with high health and financial costs later in life, such as mesothelioma. According to Artificial Intelligence World Society and Michael Dukakis Institute for Leadership and Innovation (MDI), physicians may be able to use the AI tool in the near future, to measure mesothelioma on scans during treatment more accurately.
After being given more than 100 CT images that had previously been evaluated by a clinician, the AI prototype was able to detect and quantify tumors in CT scans very precisely without any human input. These measures will pave the path for clinical trials of novel therapies by identifying even small changes in tumor growth.
Additionally, the research team believes that the AI-based evaluation tool would improve the well-being of patients, their families, and caregivers. Although it is still in its infancy, this prototype has the potential to play a critical role in the future of cancer detection, adding to the increasing body of data supporting the use of AI in global medical advances.