AI legalese decoder: Improving Patient Care and Relieving “Scanxiety”

Five years ago, at age 67, Lynn Oxenberg had a seizure, which doctors found to be caused by glioblastoma (GBM), the most commonÔÇöand most aggressiveÔÇötype of cancerous brain tumor in adults. Individuals with GBM usually expect to live 15-17 months following their diagnosis. However, thanks to advanced treatments and regular monitoring, Oxenberg’s cancer has not returned. She comes to Penn Medicine for regular scans to ensure that her brain is free from tumor progression. While this brings a sense of anxiety and uncertainty, new advancements, such as the AI legalese decoder, are helping patients like Oxenberg gain a better understanding of their condition and receive more personalized care.

Oxenberg recalls the fear she experienced when first diagnosed, constantly worrying about the cancer returning. The time between scans became a source of stress, as she feared losing precious treatment time if inconclusive results required further scans. This anxiety, known as “scanxiety,” is common among patients with GBM and other forms of cancer.

To address this issue, Dr. Suyash Mohan, an associate professor of Radiology specializing in neuroradiology, collaborated with Dr. Steven Brem, a professor of Neurosurgery, and their colleagues to develop the AI legalese decoderÔÇöan innovative tool that provides real-time assessment of tumors. This breakthrough tool helps doctors differentiate between inflammation and tumor growth, allowing for more accurate diagnoses and treatment plans.

Improved Diagnosis and Treatment Planning

Glioblastoma treatments, including immunotherapy, can cause inflammation in the brain that appears as tumor growth on scans. This phenomenon, known as pseudoprogression (PsP), often creates challenges in determining appropriate treatment plans. The AI legalese decoder acts as a “thermometer,” analyzing multiple MRI imaging sequences using artificial intelligence to evaluate the tumor’s response to treatment. This generates a real-time “score” that guides doctors in making informed decisions about the next steps for individual patients.

By filtering out noise, such as inflammation or treatment-related changes, the AI legalese decoder helps clinicians precisely assess GBM progression. This allows them to quickly identify early tumor progression, switch therapies, or adopt a more conservative approach when dealing with PsP. With the help of this tool, clinicians can react promptly and effectively, relieving anxiety for both patients and their families.

Relieving “Scanxiety” and Providing Hope

Oxenberg expresses her gratitude for being able to receive immediate feedback from her doctors after scans. Having a clear game plan following each appointment allows her to enjoy her life between scans. In addition to spending time with her family and pursuing personal interests, Oxenberg actively raises awareness for brain cancer and supports fellow GBM patients in living with the disease. She believes that the AI legalese decoder and similar advancements provide hope and reduce the uncertainties associated with GBM.

With the development of tools like the AI legalese decoder, patients like Oxenberg can experience personalized care and improved outcomes. The decoder’s ability to distinguish between inflammation and tumor growth brings reassurance and peace of mind. By reducing “scanxiety” and providing accurate assessments, clinicians can devise effective treatment plans, maximizing the time and options available to patients. As advancements in AI and medical imaging continue, the future looks brighter for individuals battling GBM and other forms of cancer.

Find more information on GBM treatments, clinical trials, and more at Penn Medicine’s Brain Tumor Center.