Diffusion tensor imaging metrics as natural markers of multiple sclerosis-induced brain disorders with a low Expanded Disability Status Scale score

• Published in: NeuroImage (Orlando, Fla.) Vol. 290; p. 120567
• Main Authors: Krzyżak, Artur Tadeusz, Lasek, Julia, Schneider, Zofia, Wnuk, Marcin, Bryll, Amira, Popiela, Tadeusz, Słowik, Agnieszka
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15.04.2024; Elsevier Limited; Elsevier
• Subjects: B-matrix spatial distribution; Brain; Brain Diseases; Diffusion tensor imaging; Diffusion Tensor Imaging - methods; Diffusion tensor metrics; Expanded disability status scale; Healthy control; Humans; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Multiple sclerosis; Multiple Sclerosis - diagnostic imaging; Neuroimaging; Patients; Performance evaluation; Scanners; Spatial distribution; Spatial heterogeneity; Statistical analysis; Volunteers; Healthy control; Expanded disability status scale; Diffusion tensor metrics; B-matrix spatial distribution; Multiple sclerosis; Diffusion tensor imaging
• ISSN: 1053-8119; 1095-9572
• DOI: 10.1016/j.neuroimage.2024.120567

•DTI carried out over several months on phantom (100 measurements), 50 healthy control (HC) volunteers and 50 multiple sclerosis (MS) patients proved.•The existence of systematic errors with repetitive spatial characteristics and their statistically significant impact on diffusion tensor metrics (DTMs).•The effective elimination of their impact on DTMs by means of the BSD method.•DTMs statistically significantly differentiate the HC and MS groups in both the standard and BSD approaches,however, the latter provides more realistic values. Non-invasive and effective differentiation along with determining the degree of deviations compared to the healthy cohort is important in the case of various brain disorders, including multiple sclerosis (MS). Evaluation of the effectiveness of diffusion tensor metrics (DTM) in 3T DTI for recording MS-related deviations was performed using a time-acceptable MRI protocol with unique comprehensive detection of systematic errors related to spatial heterogeneity of magnetic field gradients. In a clinical study, DTMs were acquired in segmented regions of interest (ROIs) for 50 randomly selected healthy controls (HC) and 50 multiple sclerosis patients. Identical phantom imaging was performed for each clinical measurement to estimate and remove the influence of systematic errors using the b-matrix spatial distribution in the DTI (BSD-DTI) technique. In the absence of statistically significant differences due to age in healthy volunteers and patients with multiple sclerosis, the existence of significant differences between groups was proven using DTM. Moreover, a statistically significant impact of spatial systematic errors occurs for all ROIs and DTMs in the phantom and for approximately 90 % in the HC and MS groups. In the case of a single patient measurement, this appears for all the examined ROIs and DTMs. The obtained DTMs effectively discriminate healthy volunteers from multiple sclerosis patients with a low mean score on the Expanded Disability Status Scale. The magnitude of the group differences is typically significant, with an effect size of approximately 0.5, and similar in both the standard approach and after elimination of systematic errors. Differences were also observed between metrics obtained using these two approaches. Despite a small alterations in mean DTMs values for groups and ROIs (1–3 %), these differences were characterized by a huge effect (effect size ∼0.8 or more). These findings indicate the importance of determining the spatial distribution of systematic errors specific to each MR scanner and DTI acquisition protocol in order to assess their impact on DTM in the ROIs examined. This is crucial to establish accurate DTM values for both individual patients and mean values for a healthy population as a reference. This approach allows for an initial reliable diagnosis based on DTI metrics. [Display omitted]