Ultra-high-field 7-Tesla MRI of the brain detected abnormalities in the substantia nigra among subjects with Parkinson’s disease.
Ultra-high-field 7-Tesla (7-T) MRI can provide detailed views of the brain implicated in Parkinson’s disease, which may lead to earlier detection, according to a study published in the journal Radiology.
Researchers from the University of Pisa in Italy undertook a study to use 7-T MRI to evaluate the anatomy of the substantia nigra (SN) in both healthy subjects and those with Parkinson’s disease.
After training on the appearance of the SN of eight healthy subjects (mean age 40.1 years), the researchers scanned 13 more subjects who did not have Parkinson’s disease (mean age 54.7 years) and 17 subjects who did have the disease (mean age 56.9 years). The images were evaluated twice by two blinded observers.
The researchers were able to distinguish a three-layered organization of the SN and detect abnormalities among the patients with Parkinson’s disease (PD) with a sensitivity of 100 percent and a specificity of 96.2 percent. "The main results of the our study are the demonstration of the capability of 7-T [MRI] to depict the borders of the SN and its inner organization, and to reveal simple radiologic signs that show the loss of the three-layer organization and the lateral spot of the SN in PD patients," the authors wrote. "Those signs allowed us to discriminate with near-perfect accuracy PD subjects from age-matched healthy subjects, which demonstrated a good diagnostic power of 7-T [MRI] in PD."
The authors concluded that more research must be done with larger study groups, but these findings were promising that 7-T MRI may eventually allow a radiological diagnosis to support a clinical diagnosis of Parkinson’s disease, in addition to other neurological diseases.
Emerging AI Algorithm Shows Promise for Abbreviated Breast MRI in Multicenter Study
April 25th 2025An artificial intelligence algorithm for dynamic contrast-enhanced breast MRI offered a 93.9 percent AUC for breast cancer detection, and a 92.3 percent sensitivity in BI-RADS 3 cases, according to new research presented at the Society for Breast Imaging (SBI) conference.
Could AI-Powered Abbreviated MRI Reinvent Detection for Structural Abnormalities of the Knee?
April 24th 2025Employing deep learning image reconstruction, parallel imaging and multi-slice acceleration in a sub-five-minute 3T knee MRI, researchers noted 100 percent sensitivity and 99 percent specificity for anterior cruciate ligament (ACL) tears.
New bpMRI Study Suggests AI Offers Comparable Results to Radiologists for PCa Detection
April 15th 2025Demonstrating no significant difference with radiologist detection of clinically significant prostate cancer (csPCa), a biparametric MRI-based AI model provided an 88.4 percent sensitivity rate in a recent study.