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

Quantitative MRI measures are proposed as biomarkers of disease course and therapeutic response. Understanding the evolution of these metrics is key for interpretation of change in clinical practice.

Objectives

To describe longitudinal changes in T2 lesion volume (T2LV), whole brain (WBF) and gray matter (GMF) fraction, and thalamic volume (TV) over the disease course in a large multiple sclerosis (MS) cohort.

Methods

Demographics, disease history, and MRI were collected from MS patients at a single site. Patients with ≥2 MRI assessments were included. T2LV, WBF, GMF, and TV annualized rate of change and raw values compared to the first available scan were analyzed. Multivariate mixed-effects models were used to evaluate longitudinal MRI changes, adjusting for age at disease onset, sex, and patient-determined disease steps category (PDDS) with a random intercept for patient and an autoregressive covariance structure. For each outcome, three models were generated: a linear model, a second-order B-spline model, and a third-order B-spline model were tested for nonlinearity in the relationship between MRI outcome and disease duration and were compared based on Akaike Information Criterion.

Results

1012 patients were included (69.2% female, 72.9% relapsing-remitting MS, mean ± SD age at disease onset 34.4±10.3, age at baseline MRI 43.8±11.1, disease duration 9.4±5.8 years, mean number of MRIs 3.1±1.2, median [IQR] PDDS 1.0 [0.0-3.0]). Male sex (B=4.9) and PDDS>3 (B=7.0) were associated with greater T2LV accumulation over the disease course (best fit: linear model). T2LV annualized rate of change peaked at 5-6 years of disease duration (rate 9%/year) (best fit: third-order B spline). Male sex, older age, and PDDS>3 were associated with lower WBF, TV (best fit: linear model), and GMF (best fit: second-order B spline), all p<0.05. No non-linear effect of disease duration on WBF, TV, and GMF were observed. There was no statistically significant change in the annualized rate of change of WBF, TV, and GMF over the disease course.

Conclusions

The dynamics of T2LV accumulation are variable throughout the disease course, whereas the rate of change of WBF, TV, and GMF were more stable. These results suggest T2LV accumulation reflecting focal lesion activity predominates early in the disease while WBF, TV, and GMF loss reflecting underlying neurodegeneration is present at disease onset and continues throughout the course.

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.