Background

Magnetic resonance imaging (MRI) is applied to monitor multiple sclerosis (MS) evolution and to evaluate disease progression. Unfortunately, conventional MRI is non-specific for myelin. Therefore, the in vivo whole brain myelin imaging technique Multi-Component Driven Equilibrium Single Pulse Observation of T1 and T2 (mcDESPOT) [1], that allows the assessment of relative myelination by measuring the myelin water fraction (MWF) [2], is expected to quantify myelination of the entire brain and thus assesses intra- and interindividual differences.

Objectives

The aim of this study was to explore MWF as a biomarker to analyse myelination differences in relapsing remitting (RRMS) and secondary progressive (SPMS) MS patients. In this study MWF was retrieved in WM of healthy controls (HC), normal appearing WM (NAWM) and T2 lesions (T2L) to parse differences in global and focal myelin loss in RRMS and SPMS.

Methods

A 1.5T MR scanner (Siemens Sonata) and an 8-channel head RF coil was used to derive 3D-fluid attenuated inversion recovery (FLAIR) images of n=112 RRMS (EDSS_mean=2.7±1.2) and n=24 SPMS (EDSS_mean=5.4±1.4) patients. WM, NAWM and T2L were segmented into binary masks. Common data post processing involving brain extraction and co-registration of scans was used (FSL/ANTs)[3,4]. MWF maps were derived using the established mcDESPOT processing method [1]. A matched control group (n=63) was acquired. Differences in MWF of healthy controls, RRMS and SPMS were determined with a wilcoxon rank sum test (p < 0.05).

A 1.5T MR scanner (Siemens Magnetom Sonata equipped with a 8-channel radio-frequency coil was used and sets of 3DFluid-Attenuated Inversion Recovery (FLAIR), Spoiled Gradient Recalled (SPGR) and Balanced Steady- State Free-Precession (bSSFP) images were

obtained. According to the mcDESPOT protocol SPGR and bSSFP scans were acquired over a range of flip angles at constant echo time (TE) and repetition time (TR) using the following specifications: field of view (FOV) = 22 cm, slice thickness = 1.7 mm; SPGR: TE/TR = 2.0/ 5.7 ms, flip angle (α)= [5, 6, 7, 8, 9, 11, 13, 18]°; bSSFP: TE/ TR = 1.71/3.42 ms, α = [9, 14, 19, 24, 28, 34, 41, 51, 60]°; acquisition time ~13min.

Results

The MWF in WM of HC was (MWF_{mean, SD}=0.230 ± 0.007) versus MWF in NAWM of RRMS (MWF_{mean, SD}=0.224 ± 0.01) and SPMS (MWF_{mean, SD}=0.213 ± 0.012) patients. Significant MWF differences (p <0.05) were found for HC vs. MS patients. Mean T2L volume was significantly higher in SPMS patients (T2L volume_RRMS= 4,3ml±6,4ml vs. T2L volume_SPMS= 16.8ml±14.9ml). MWF in T2L of RRMS patients was MWF_{mean, SD} =0.117 ± 0.03 ranging from MWF_min=0.032 to MWF_max = 0.201 and for SPMS patients MWF_{mean, SD} =0.130 ± 0.02 ranging from MWF_min=0.088 to MWX_max = 0.177. Significant MWF differences were found for T2L of the RRMS vs. SPMS group.

Conclusions

Our findings demonstrate varying degrees of myelination within T2L in MS patients, indicating a heterogeneous MWF loss in RRMS and SPMS patients.

Background

Automated and reproducible measures of MS severity and subclinical inflammatory activity and neurodegeneration in routine practice could support therapeutic decisions and accelerate research. Toward this goal, we developed and validated a software prototype, MSPie (MS PATHS Image Evaluation). MSPie runs on syngo.via Frontier (Siemens Healthcare, Erlangen, Germany) and processes standardized T2 FLAIR and T1-weighted MRIs to quantify brain parenchymal fraction (BPF), T2 lesion volume, and #new/enlarging T2 lesions (NET2L). Results are reviewable by radiologists through an interface that displays current, prior, and subtraction images, as well as overlays of brain and lesion segmentations, and allows +/- corrections of NET2L.

Objectives

To assess an image analysis prototype integrated into radiological practice to generate quantitative brain volume and lesion measurements at the point of care.

Methods

MSPie was installed at 2 MS Partners Advancing Technology and Health Solutions (MS PATHS) institutions. 3 neuroradiologists per institution used MSPie to review 40 longitudinal pairs of routine MS PATHS MRIs. For each case, radiologists performed a visual assessment of the brain segmentation used for BPF, manually corrected NET2L if needed, approved or rejected the results, and completed a performance evaluation survey.

Results

MSPie performance was assessed in 240 cases. Radiologists accepted MSPie-generated BPF and lesion results for 230/240 cases (96%). 38.8% of cases required corrections of false positive (FP) or false negative (FN) NET2L, with a mean of 2.5 (FP+FN) NET2L per case. In 94% of cases, NET2L FP+FN was £3, a prespecified design target based on radiologists’ input. MSPie detected 221/229 true NET2L, yielding a sensitivity of 96.2%. In 18% of cases, radiologists reported MSPie-detected NET2L they would have missed. Mean performance ratings on a scale of 1(poor) to 5(excellent) were: 3.9 for overall performance; 3.9 for brain segmentation; 3.9 for T2 lesion segmentation.

Conclusions

Incorporation of brain volume and T2 lesion quantification into MS imaging practice is feasible. MSPie demonstrated a high sensitivity for disease activity, detecting some NET2L that might have been missed by radiologists. MSPie achieved the prespecified target rate of acceptable false positive NET2L. MSPie might allow neuroradiologists to provide quantitative brain atrophy and T2 lesion metrics in clinical practice and to increase their diagnostic precision.

Disclosures: MS PATHS is sponsored by Biogen.

Background

Mean rates of brain atrophy in healthy controls range from 0.05-0.5%, depending on age and technical factors, including scanner, acquisition sequences, and image analysis techniques. In MS PATHS (MS Partners Advancing Technology for Health Solutions), standardized MRIs are analyzed using a software prototype (MSPie, MS PATHS Image Evaluation) that incorporates a novel approach to calculate BPF. Normative ranges measured using MSPie are needed to distinguish age- and disease-related changes.

Objectives

To establish a normative reference for interpretation of brain parenchymal fraction (BPF) in individual MS patients relative to age-matched healthy volunteers (HV).

Methods

HV aged 21-60 were recruited at 6 MS PATHS sites to be age-, race-, and gender-matched to the MS PATHS cohort. HVs were imaged at baseline and once/year using 3T scanners (Siemens Healthcare, Erlangen, Germany) and standardized acquisitions (3DFLAIR and 3DT1), as in routine MRIs in MS PATHS. MRIs from UK Biobank supplemented the normative dataset past the age of 60. All MRIs were analyzed with MSPie to calculate BPF. BPF normative percentile were calculated for each age using quantile regression. Mean annualized rate of brain atrophy was estimated from HVs with follow-up MRIs. BPF percentiles were applied to the MS PATHS cohort. Mean Processing Speed Test (PST) z-scores were compared in MS patients stratified based on BPF percentiles.

Results

209 HVs were enrolled, 590 UKBiobank HVs were selected, and 9479 MS patients had at least one MRI. HV BPF values ranged from 0.855-0.895 in the 21-30 age group to 0.796-0.882 in the 61-73 age group, demonstrating accelerating and more variable atrophy with increasing age. For MS patients age 21-73 years (n=6791), mean age-adjusted BPF percentile was 27.8%, where BPF values fell above the 50^th%-ile in 23.4% (“mild MS”) and below the 25^th%-ile in 57.6% (“severe MS”). Mean PST z-scores differed in BPF-based mild MS vs. severe MS groups (-0.15 and -0.83; p<0.001). Mean annualized BPF change in HV was -0.08% (range: -0.71% to +0.57%) based on 71 subjects (mean age: 41.1 years) with >2 MRIs.

Conclusions

Incorporating normative reference data into MSPie will aid clinicians with interpretation of individual patients’ BPF in clinical practice and may enable patient stratification based on BPF and other predictors. Additional longitudinal normative data are being collected to contextualize disease progression as measured by BPF change over time.

Disclosures: MS PATHS is sponsored by Biogen.

Background

Automated and reproducible measures of MS severity and subclinical inflammatory activity and neurodegeneration in routine practice could support therapeutic decisions and accelerate research. Toward this goal, we developed and validated a software prototype, MSPie (MS PATHS Image Evaluation). MSPie runs on syngo.via Frontier (Siemens Healthcare, Erlangen, Germany) and processes standardized T2 FLAIR and T1-weighted MRIs to quantify brain parenchymal fraction (BPF), T2 lesion volume, and #new/enlarging T2 lesions (NET2L). Results are reviewable by radiologists through an interface that displays current, prior, and subtraction images, as well as overlays of brain and lesion segmentations, and allows +/- corrections of NET2L.

Objectives

To assess an image analysis prototype integrated into radiological practice to generate quantitative brain volume and lesion measurements at the point of care.

Methods

MSPie was installed at 2 MS Partners Advancing Technology and Health Solutions (MS PATHS) institutions. 3 neuroradiologists per institution used MSPie to review 40 longitudinal pairs of routine MS PATHS MRIs. For each case, radiologists performed a visual assessment of the brain segmentation used for BPF, manually corrected NET2L if needed, approved or rejected the results, and completed a performance evaluation survey.

Results

MSPie performance was assessed in 240 cases. Radiologists accepted MSPie-generated BPF and lesion results for 230/240 cases (96%). 38.8% of cases required corrections of false positive (FP) or false negative (FN) NET2L, with a mean of 2.5 (FP+FN) NET2L per case. In 94% of cases, NET2L FP+FN was £3, a prespecified design target based on radiologists’ input. MSPie detected 221/229 true NET2L, yielding a sensitivity of 96.2%. In 18% of cases, radiologists reported MSPie-detected NET2L they would have missed. Mean performance ratings on a scale of 1(poor) to 5(excellent) were: 3.9 for overall performance; 3.9 for brain segmentation; 3.9 for T2 lesion segmentation.

Conclusions

Incorporation of brain volume and T2 lesion quantification into MS imaging practice is feasible. MSPie demonstrated a high sensitivity for disease activity, detecting some NET2L that might have been missed by radiologists. MSPie achieved the prespecified target rate of acceptable false positive NET2L. MSPie might allow neuroradiologists to provide quantitative brain atrophy and T2 lesion metrics in clinical practice and to increase their diagnostic precision.

Disclosures: MS PATHS is sponsored by Biogen.