BOLD signal within and around white matter lesions distinguishes multiple sclerosis and non-specific white matter
Dinesh K Sivakolundu1,2, Kathryn L West1, Mark D Zuppichini1
1School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, USA.
Abstract:
Multiple sclerosis (MS) diagnostic criteria are based upon clinical presentation and presence of white matter hyperintensities on two-dimensional magnetic resonance imaging (MRI) views. Such criteria, however, are prone to false-positive interpretations due to the presence of similar MRI findings in non-specific white matter disease (NSWMD) states such as migraine and microvascular disease. The coexistence of age-related changes has also been recognized in MS patients, and this comorbidity further poses a diagnostic challenge. In this study, we investigated the physiologic profiles within and around MS and NSWMD lesions and their ability to distinguish the two disease states. MS and NSWMD lesions were identified using three-dimensional (3D) T2-FLAIR images and segmented using geodesic active contouring. A dual-echo functional MRI sequence permitted near-simultaneous measurement of blood-oxygen-level-dependent signal (BOLD) and cerebral blood flow (CBF). BOLD and CBF were calculated within lesions and in 3D concentric layers surrounding each lesion. BOLD slope, an indicator of lesion metabolic capacity, was calculated as the change in BOLD from a lesion through its surrounding perimeters. We observed sequential BOLD signal reductions from the lesion towards the perimeters for MS, while no such decreases were observed for NSWMD lesions. BOLD slope was significantly lower in MS compared to NSWM lesions, suggesting decreased metabolic activity in MS lesions. Furthermore, BOLD signal within and around lesions significantly distinguished MS and NSWMD lesions. These results suggest that this technique shows promise for clinical utility in distinguishing NSWMD or MS disease states and identifying NSWMD lesions occurring in MS patients.
Insights
Functional MRI can differentiate multiple sclerosis (MS) lesions from non-specific white matter disease (NSWMD) by analyzing metabolic activity. This technique shows promise for improving MS diagnosis and managing comorbidities.
Area of Science:
- Neuroimaging
- Neurology
- Biophysics
Background:
- Current multiple sclerosis (MS) diagnostic criteria rely on clinical presentation and 2D MRI, which can lead to misinterpretations due to non-specific white matter disease (NSWMD).
- Differentiating MS from NSWMD, such as microvascular disease or migraine, is challenging, especially with age-related changes complicating diagnoses in MS patients.
Purpose of the Study:
- To investigate the physiologic profiles within and around MS and NSWMD lesions using advanced MRI techniques.
- To assess the capability of these physiologic profiles to accurately distinguish between MS and NSWMD lesions.
Main Methods:
- Identified and segmented MS and NSWMD lesions using 3D T2-FLAIR MRI and geodesic active contouring.
- Employed a dual-echo functional MRI sequence to measure blood-oxygen-level-dependent (BOLD) signal and cerebral blood flow (CBF) within lesions and surrounding areas.
- Calculated the BOLD slope, representing lesion metabolic capacity, by analyzing BOLD signal changes from the lesion to its perimeters.
Main Results:
- Observed distinct patterns of BOLD signal reduction from lesion centers towards perimeters in MS, unlike in NSWMD lesions.
- Demonstrated a significantly lower BOLD slope in MS lesions compared to NSWMD lesions, indicating reduced metabolic activity in MS.
- Confirmed that BOLD signal patterns within and around lesions effectively distinguished between MS and NSWMD.
Conclusions:
- Functional MRI-based assessment of BOLD signal and CBF offers a promising method for differentiating MS from NSWMD.
- This technique may aid in clinical diagnosis, particularly in identifying NSWMD in patients with suspected or confirmed MS.
