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A clinically feasible 7-Tesla protocol for the identification of cortical lesions in Multiple Sclerosis
- Publication Year :
- 2020
- Publisher :
- Springer, 2020.
-
Abstract
- The aim of this study was to evaluate the capability of sequences acquired on a 7-T MRI scanner, within times and anatomical coverage appropriate for clinical studies, to identify cortical lesions (CLs) in patients with Multiple Sclerosis (MS). Furthermore, we aimed to confirm the clinical significance of CL, testing the correlations between gray matter (GM) lesions and clinical scores. A 7-T MRI protocol included 3D-T1-weighted and T2*-weighted sequences. Images were evaluated independently by three readers of different experience, and the number of CLs was recorded. Between-rater concordance was assessed calculating the intraclass correlation coefficient (ICC). Lin’s concordance correlation coefficient was used to compare CL detection between sequences, while partial correlations and multivariable regression models were used to study the relationship between CL and clinical data. Forty MS patients (M/F, 17/23; 44.7 ± 12.6 years) were enrolled in this study, and CLs were identified in 35/40 subjects (87.5%). CL detection rate on 3D-T1-weighted images was significantly correlated with the detection rate on T2*-weighted images (r = 0.99; p
- Subjects :
- Adult
Male
medicine.medical_specialty
Intraclass correlation
Concordance
030218 nuclear medicine & medical imaging
Correlation
Multiple sclerosis
Young Adult
03 medical and health sciences
Imaging, Three-Dimensional
0302 clinical medicine
Magnetic resonance imaging
Clinical Protocols
medicine
Humans
Radiology, Nuclear Medicine and imaging
Clinical significance
Gray matter
Aged
Neuroradiology
Cerebral Cortex
medicine.diagnostic_test
business.industry
General Medicine
Middle Aged
medicine.disease
Concordance correlation coefficient
030220 oncology & carcinogenesis
Feasibility Studies
Female
Radiology
business
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....3a7ab42cedb868e7826c7f45d1d9a8b6