Dr. Hermant Parmar and colleagues at the National Neuroscience Institute in Singapore have documented acute hippocampal damage resulting from prolonged seizure activity, using diffusion-weighted MRI and MR spectroscopy. Theirs was one of the first studies to provide noninvasive evidence of such damage in humans.
Dr. Hermant Parmar and colleagues at the National Neuroscience Institute in Singapore have documented acute hippocampal damage resulting from prolonged seizure activity, using diffusion-weighted MRI and MR spectroscopy. Theirs was one of the first studies to provide noninvasive evidence of such damage in humans.
The team reviewed data in 10 temporal lobe epilepsy patients who underwent MR imaging within 48 hours of acute seizure. DWI showed hyperintensive signal involving the hippocampi in all 10 patients. MRS showed lactate within the abnormal hippocampus in three patients. On follow-up MR during a seizure-free period, five patients demonstrated T2 prolongation and atrophy.
The researchers hope to use these techniques to investigate the pathophysiology of temporal lobe epilepsy, as well as to predict future development of hippocampal sclerosis. They reported their findings at the 2004 RSNA meeting.
Leading Breast Radiologists Discuss the USPSTF Breast Cancer Screening Recommendations
May 17th 2024In recognition of National Women’s Health Month, Dana Bonaminio, MD, Amy Patel, MD, and Stacy Smith-Foley, MD, shared their thoughts and perspectives on the recently updated breast cancer screening recommendations from the United States Preventive Services Task Force (USPSTF).
Multicenter CT Study Shows Benefits of Emerging Diagnostic Model for Clear Cell Renal Cell Carcinoma
May 15th 2024Combining clinical and CT features, adjunctive use of a classification and regression tree (CART) diagnostic model demonstrated AUCs for detecting clear cell renal cell carcinoma (ccRCC) that were 15 to 22 percent higher than unassisted radiologist assessments.
CT Study: AI Algorithm Comparable to Radiologists in Differentiating Small Renal Masses
May 14th 2024An emerging deep learning algorithm had a lower AUC and sensitivity than urological radiologists for differentiating between small renal masses on computed tomography (CT) scans but had a 21 percent higher sensitivity rate than non-urological radiologists, according to new research.