Prior studies have determined that men are more likely to develop glioblastoma in comparison to women. These studies have also shown these tumors are usually more aggressive in males as compared to women.
Now scientists are using artificial intelligence (AI) to uncover risk factors that may help clinicians predict which tumors might grow more quickly and the differences between the sexes.
For their study, the researchers examined digital images of tumor samples, searching for patterns that could help predict how quickly a tumor could grow and, in turn, how long a patient could survive with the illness. The outcome dictates the treatments to be administered and the patient’s quality of life following diagnosis.
Normally, patients with glioblastoma don’t live long following their diagnosis. The current median survival for this very aggressive cancer form is 15 months post-diagnosis.
Professor Pallavi Tiwari, who specializes in biomedical engineering and is a radiology professor, and Ruchika Verma, a former graduate student, led the study. To determine the outcome, the researchers designed an artificial intelligence model that could pick out any pattern on thin slices of samples of tumors that may not be apparent to the naked human eye.
They then trained the model using data from more than 250 studies of patients with glioblastoma, making it easier for the model to recognize the unique characteristics of the tumors. These include the abundance of specific types of cells. In addition, they trained the model to pick out patterns between these characteristics and the survival time for patients, while taking their gender into account.
This allowed the model to determine that in males, the presence of pseudopalisading cells was linked to more aggressive tumors. In women, higher-risk characteristics included tumors invading healthy tissues. The model was also able to recognize characteristics that could translate into worse prognoses for both women and men. These findings could assist in the development of more individualized care for patients with glioblastoma.
Verma explained that with this discovery, they hoped to encourage additional research into the underlying biological differences observed in the tumors while inspiring new approaches for personalized therapy.
Tiwari and her colleagues are already using artificial intelligence to analyze breast and pancreatic cancers, focused on improving patient outcomes.
The researchers reported their findings in the “Science Advances” journal. Other researchers involved in the study included Tyler J. Alban, Prerana Parthasarathy, Mojgan Mokhtari, Paula Toro Castano, Mark L. Cohen, Justin D. Lathia and Manmeet Ahluwalia.
In addition to the use of AI in the healthcare sector, the technology is also finding utility in the business field. Enterprises such as Salesforce Inc. (NYSE: CRM) are innovating solutions that promise to revolutionize the way business operations are conducted.
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