Glioblastomas (GBMs) are highly aggressive tumors. A common clinical challenge after standard of care treatment is differentiating tumor progression from treatment-related changes, also known as pseudoprogression (PsP). Usually, PsP resolves or stabilizes without further treatment or a course of steroids, whereas true progression (TP) requires more aggressive management. Differentiating PsP from TP will affect the patient's outcome. This study investigated using deep learning to distinguish PsP MRI features from progressive disease.

Cleveland Clinic is a non-profit academic medical center. Advertising on our site helps support our mission. For over a century, malignant brain tumors such as glioblastoma (GBM) have carried a dismal prognosis. The most recent substantial advance has been provided by surgical resection and chemoradiation followed by adjuvant temozolomide therapy. Yet a problem during the requisite post-treatment surveillance imaging is that the brain's reaction to heavy doses of radiation can mimic the appearance of true tumor progression on MRI (Figure 1).