Evaluation of the Statistical Detection of Change Algorithm for Screening Patients with MS with New Lesion Activity on Longitudinal Brain MRI.

BACKGROUND AND PURPOSE: Identification of new MS lesions on longitudinal MR imaging by human readers is time-consuming and prone to error. Our objective was to evaluate the improvement in the performance of subject-level detection by readers when assisted by the automated statistical detection of change algorithm. MATERIALS AND METHODS: A total of 200 patients with MS with a mean interscan interval of 13.2 (SD, 2.4) months were included. Statistical detection of change was applied to the baseline and follow-up FLAIR images to detect potential new lesions for confirmation by readers (Reader + statistical detection of change method). This method was compared with readers operating in the clinical workflow (Reader method) for a subject-level detection of new lesions. RESULTS: Reader + statistical detection of change found 30 subjects (15.0%) with at least 1 new lesion, while Reader detected 16 subjects (8.0%). As a subject-level screening tool, statistical detection of change achieved a perfect sensitivity of 1.00 (95% CI, 0.88-1.00) and a moderate specificity of 0.67 (95% CI, 0.59-0.74). The agreement on a subject level was 0.91 (95% CI, 0.87-0.95) between Reader + statistical detection of change and Reader, and 0.72 (95% CI, 0.66-0.78) between Reader + statistical detection of change and statistical detection of change. CONCLUSIONS: The statistical detection of change algorithm can serve as a time-saving screening tool to assist human readers in verifying 3D FLAIR images of patients with MS with suspected new lesions. Our promising results warrant further evaluation of statistical detection of change in prospective multireader clinical studies.

Quantitative Susceptibility Mapping of Time-Dependent Susceptibility Changes in Multiple Sclerosis Lesions.

BACKGROUND AND PURPOSE: MR imaging studies have demonstrated that magnetic susceptibility in multiple sclerosis lesions is dependent on lesion age. The objective of this study was to use quantitative susceptibility mapping to determine whether lesions with a hyperintense rim, indicative of iron-laden inflammatory cells (rim+), follow a unique time-dependent trajectory of susceptibility change compared with those without (rim-). MATERIALS AND METHODS: We studied patients with MS with at least 1 new gadolinium-enhancing lesion and at least 3 longitudinal quantitative susceptibility mapping scans obtained between 1.1 and 6.1 years. Lesions were classified as rim+ if a hyperintense rim appeared on quantitative susceptibility mapping at any time. A multilevel growth curve model compared longitudinal susceptibility among rim+ and rim- lesions. RESULTS: Thirty-two new gadolinium-enhancing lesions from 19 patients with MS were included, and 16 lesions (50%) were identified as rim+. Quantitative susceptibility mapping rim+ lesions were larger than rim- lesions with gadolinium enhancement (P < .001). Among all lesions, susceptibility increased sharply after enhancement to a peak between 1 and 2 years followed by a decrease. The overall susceptibility curve height for rim- lesions was 4.27 parts per billion lower than that for rim+ lesions (P = .01). Rim- lesions demonstrated a higher linear slope relative to rim+ lesions (P = .023) but faster cubic decay relative to rim+ lesions (P = .005). Rim- lesions started decaying approximately 2 years earlier compared with rim+ lesions. CONCLUSIONS: There was a marked difference in the susceptibility temporal trajectory between rim+ and rim- lesions during the first 6 years of lesion formation. Most rim+ lesions retain iron for years after the initial lesion appearance.

Baseline biomarkers of connectome disruption and atrophy predict future processing speed in early multiple sclerosis.

The development of accurate prognoses in multiple sclerosis is difficult, as the disease is characterized by heterogeneous patterns of brain abnormalities that relate in an unclear way to future impairments. Here, we use a statistical modeling approach to determine if the baseline pattern of connectome disruption due to T2-FLAIR lesions could predict a patient's future processing speed, as measured using the Symbol Digits Modality Test scores. Imaging data, demographics and Symbol Digits Modality Test scores were collected from 61 early relapsing remitting multiple sclerosis patients. The Network Modification Tool was used to estimate damage to the connectome by quantifying white matter abnormalities' effects on 1) global network properties, 2) regional connectivity and 3) connectivity between pairs of regions. MS subjects showed significant improvement of processing speed between baseline and follow-up (t = -2.6, p = 0.0096); however, both baseline (t = -4.01, p = 0.00012) and follow-up (t = -2.10, p = 0.038) processing speed were significantly lower than age-matched healthy controls. Partial Least Squares Regression was used to create models that predict future processing speed from between baseline imaging metrics and demographics. The model based on region-pair disconnection and gray matter atrophy had the lowest AIC and highest prediction accuracy (R2 = 0.79) compared to models based on global (R2 = 0.41) or regional (R2 = 0.66) disconnection and gray matter atrophy, overlap with an ROI-based atlas and gray matter atrophy (R2 = 0.73) or gray matter atrophy alone (R2 = 0.71). We found that baseline measures of connectivity disruption in various parietal, temporal, occipital and subcortical regions and atrophy in the putamen were important predictors of future processing speed. We conclude that information about disruptions to pairwise brain connections is more informative of future processing speed than regional or global metrics or gray matter atrophy alone. The combination of quantitative disconnectome metrics, gray matter atrophy and statistical modeling approaches could enable clinicians in developing more accurate, individualized prognoses of future cognitive status in multiple sclerosis patients.

Quantitative Susceptibility Mapping of the Thalamus: Relationships with Thalamic Volume, Total Gray Matter Volume, and T2 Lesion Burden.

BACKGROUND AND PURPOSE: Both thalamic iron deposition and atrophy have been reported in patients with multiple sclerosis compared with healthy controls, but how they are related is unclear. The purpose of this study was to understand the pathophysiologic basis for this iron deposition. MATERIALS AND METHODS: Ninety-five patients with relapsing-remitting multiple sclerosis underwent 3T MR imaging with a standardized protocol that included quantitative susceptibility mapping to measure iron concentration and a 3D T1 echo-spoiled gradient-echo sequence to obtain thalamic volumes. Volumes of interest were manually delineated on the quantitative susceptibility map to encompass both thalami. Multivariate regression analyses were performed to identify the association between thalamic susceptibility and volume. Associations between thalamic susceptibility and total gray matter volume, cortical thickness, and T2 lesion volume were also assessed. RESULTS: The relative susceptibility of the thalamus was associated with T2 lesion volume (P = .015) and was higher in the presence of enhancing lesions (P = .013). The relative susceptibility of the thalami was not associated with thalamic volumes, total gray matter volumes, or cortical thickness (P > .05). CONCLUSIONS: Iron levels in the thalami are associated with T2 lesion burden and the presence of enhancing lesions, but not with thalamic or gray matter volumes, suggesting that iron accumulation is associated with white matter inflammation rather than gray matter neurodegeneration.

Fast and Robust Unsupervised Identification of MS Lesion Change Using the Statistical Detection of Changes Algorithm.

We developed a robust automated algorithm called statistical detection of changes for detecting morphologic changes of multiple sclerosis lesions between 2 T2-weighted FLAIR brain images. Results from 30 patients showed that statistical detection of changes achieved significantly higher sensitivity and specificity (0.964, 95% CI, 0.823-0.994; 0.691, 95% CI, 0.612-0.761) than with the lesion-prediction algorithm (0.614, 95% CI, 0.410-0.784; 0.281, 95% CI, 0.228-0.314), while resulting in a 49% reduction in human review time (P = .007).

Combining Quantitative Susceptibility Mapping with Automatic Zero Reference (QSM0) and Myelin Water Fraction Imaging to Quantify Iron-Related Myelin Damage in Chronic Active MS Lesions.

BACKGROUND AND PURPOSE: A hyperintense rim on susceptibility in chronic MS lesions is consistent with iron deposition, and the purpose of this study was to quantify iron-related myelin damage within these lesions as compared with those without rim. MATERIALS AND METHODS: Forty-six patients had 2 longitudinal quantitative susceptibility mapping with automatic zero reference scans with a mean interval of 28.9 ± 11.4 months. Myelin water fraction mapping by using fast acquisition with spiral trajectory and T2 prep was obtained at the second time point to measure myelin damage. Mixed-effects models were used to assess lesion quantitative susceptibility mapping and myelin water fraction values. RESULTS: Quantitative susceptibility mapping scans were on average 6.8 parts per billion higher in 116 rim-positive lesions compared with 441 rim-negative lesions (P < .001). All rim-positive lesions retained a hyperintense rim over time, with increasing quantitative susceptibility mapping values of both the rim and core regions (P < .001). Quantitative susceptibility mapping scans and myelin water fraction in rim-positive lesions decreased from rim to core, which is consistent with rim iron deposition. Whole lesion myelin water fractions for rim-positive and rim-negative lesions were 0.055 ± 0.07 and 0.066 ± 0.04, respectively. In the mixed-effects model, rim-positive lesions had on average 0.01 lower myelin water fraction compared with rim-negative lesions (P < .001). The volume of the rim at the initial quantitative susceptibility mapping scan was negatively associated with follow-up myelin water fraction (P < .01). CONCLUSIONS: Quantitative susceptibility mapping rim-positive lesions maintained a hyperintense rim, increased in susceptibility, and had more myelin damage compared with rim-negative lesions. Our results are consistent with the identification of chronic active MS lesions and may provide a target for therapeutic interventions to reduce myelin damage.

Quantitative Susceptibility Mapping and R2* Measured Changes during White Matter Lesion Development in Multiple Sclerosis: Myelin Breakdown, Myelin Debris Degradation and Removal, and Iron Accumulation.

BACKGROUND AND PURPOSE: Quantitative susceptibility mapping and R2* are sensitive to myelin and iron changes in multiple sclerosis lesions. This study was designed to characterize lesion changes on quantitative susceptibility mapping and R2* at various gadolinium-enhancement stages. MATERIALS AND METHODS: This study included 64 patients with MS with different enhancing patterns in white matter lesions: nodular, shell-like, nonenhancing < 1 year old, and nonenhancing 1-3 years old. These represent acute, late acute, early chronic, and late chronic lesions, respectively. Susceptibility values measured on quantitative susceptibility mapping and R2* values were compared among the 4 lesion types. Their differences were assessed with a generalized estimating equation, controlling for Expanded Disability Status Scale score, age, and disease duration. RESULTS: We analyzed 203 lesions: 80 were nodular-enhancing, of which 77 (96.2%) were isointense on quantitative susceptibility mapping; 33 were shell-enhancing, of which 30 (90.9%) were hyperintense on quantitative susceptibility mapping; and 49 were nonenhancing lesions < 1 year old and 41 were nonenhancing lesions 1-3 years old, all of which were hyperintense on quantitative susceptibility mapping. Their relative susceptibility/R2* values were 0.5 ± 4.4 parts per billion/-5.6 ± 2.9 Hz, 10.2 ± 5.4 parts per billion/-8.0 ± 2.6 Hz, 20.2 ± 7.8 parts per billion/-3.1 ± 2.3 Hz, and 33.2 ± 8.2 parts per billion/-2.0 ± 2.6 Hz, respectively, and were significantly different (P < .005). CONCLUSIONS: Early active MS lesions with nodular enhancement show R2* decrease but no quantitative susceptibility mapping change, reflecting myelin breakdown; late active lesions with peripheral enhancement show R2* decrease and quantitative susceptibility mapping increase in the lesion center, reflecting further degradation and removal of myelin debris; and early or late chronic nonenhancing lesions show both quantitative susceptibility mapping and R2* increase, reflecting iron accumulation.

Magnetic Susceptibility from Quantitative Susceptibility Mapping Can Differentiate New Enhancing from Nonenhancing Multiple Sclerosis Lesions without Gadolinium Injection.

BACKGROUND AND PURPOSE: Magnetic susceptibility values of multiple sclerosis lesions increase as they change from gadolinium-enhancing to nonenhancing. Can susceptibility values measured on quantitative susceptibility mapping without gadolinium injection be used to identify the status of lesion enhancement in surveillance MR imaging used to monitor patients with MS? MATERIALS AND METHODS: In patients who had prior MR imaging and quantitative susceptibility mapping in a current MR imaging, new T2-weighted lesions were evaluated for enhancement on conventional T1-weighted imaging with gadolinium, and their susceptibility values were measured on quantitative susceptibility mapping. Receiver operating characteristic analysis was used to assess the diagnostic accuracy of using quantitative susceptibility mapping in distinguishing new gadolinium-enhancing from new nonenhancing lesions. A generalized estimating equation was used to assess differences in susceptibility values among lesion types. RESULTS: In 54 patients, we identified 86 of 133 new lesions that were gadolinium-enhancing and had relative susceptibility values significantly lower than those of nonenhancing lesions (ß = -17.2; 95% CI, -20.2 to -14.2; P < .0001). Using susceptibility values to discriminate enhancing from nonenhancing lesions, we performed receiver operating characteristic analysis and found that the area under the curve was 0.95 (95% CI, 0.92-0.99). Sensitivity was measured at 88.4%, and specificity, at 91.5%, with a cutoff value of 11.2 parts per billion for quantitative susceptibility mapping-measured susceptibility. CONCLUSIONS: During routine MR imaging monitoring to detect new MS lesion activity, quantitative susceptibility mapping can be used without gadolinium injection for accurate identification of the BBB leakage status in new T2WI lesions.

Modeling the relationship among gray matter atrophy, abnormalities in connecting white matter, and cognitive performance in early multiple sclerosis.

BACKGROUND AND PURPOSE: Quantitative assessment of clinical and pathologic consequences of white matter abnormalities in multiple sclerosis is critical in understanding the pathways of disease. This study aimed to test whether gray matter atrophy was related to abnormalities in connecting white matter and to identify patterns of imaging biomarker abnormalities that were related to patient processing speed. MATERIALS AND METHODS: Image data and Symbol Digit Modalities Test scores were collected from a cohort of patients with early multiple sclerosis. The Network Modification Tool was used to estimate connectivity irregularities by projecting white matter abnormalities onto connecting gray matter regions. Partial least-squares regression quantified the relationship between imaging biomarkers and processing speed as measured by the Symbol Digit Modalities Test. RESULTS: Atrophy in deep gray matter structures of the thalami and putamen had moderate and significant correlations with abnormalities in connecting white matter (r = 0.39-0.41, P < .05 corrected). The 2 models of processing speed, 1 for each of the WM imaging biomarkers, had goodness-of-fit (R(2)) values of 0.42 and 0.30. A measure of the impact of white matter lesions on the connectivity of occipital and parietal areas had significant nonzero regression coefficients. CONCLUSIONS: We concluded that deep gray matter regions may be susceptible to inflammation and/or demyelination in white matter, possibly having a higher sensitivity to remote degeneration, and that lesions affecting visual processing pathways were related to processing speed. The Network Modification Tool may be used to quantify the impact of early white matter abnormalities on both connecting gray matter structures and processing speed.

Incidence and factors associated with treatment failure in the CLIMB multiple sclerosis cohort study.

OBJECTIVE: To determine the rate of treatment failure in patients outside of a controlled treatment trial and to ascertain the factors physicians used to make this decision. METHODS: One hundred and thirty four patients with the diagnosis of relapsing-remitting (RR) multiple sclerosis (MS) or clinically isolated symptom (CIS) enrolled in the CLIMB study (Comprehensive Longitudinal Investigation of Multiple Sclerosis at the Brigham and Women's Hospital) were treated with either interferon beta or glatiramer acetate as their initial treatment for MS. RESULTS: The probability of failing initial treatment within 3 years was 30%. Clinical activity, defined as relapses and/or progression in disability, determined treatment failure in 35.7% (n=10) of nonresponders. New T2 hyperintense or gadolinium-enhancing lesions on MRI was used to define treatment failure in 28.6% (n=8) and new MRI lesions were used in combination with clinical activity in 35.7% (n=10). Treatment failures had a higher T2 hyperintense lesion volume (p=0.015) and number of gadolinium-enhancing lesions (p=0.0001) on the enrollment MRI than responders. CONCLUSIONS: These observations demonstrate that treating physicians use both clinical and MRI parameters to define a response to treatment and initiation of a treatment change and that baseline MRI identified those with increased risk of treatment failure.

Predicting short-term disability in multiple sclerosis.

OBJECTIVE: To develop covariate specific short-term disability curves to demonstrate the probability of progressing by Expanded Disability Status Scale (EDSS) at semiannual visits. METHODS: Semiannual EDSS scores were prospectively collected in 218 relapsing-remitting (RR) and clinically isolated syndrome (CIS) patients as part of the Comprehensive Longitudinal Investigation of Multiple Sclerosis at the Brigham and Women's Hospital (CLIMB) study. Baseline brain parenchymal fraction (BPF) and T2 lesion volume were available on 205 patients. A partial proportional odds model determined the influence of covariates on the change in EDSS score at subsequent visits. A discrete second order Markov transitional model was fit and generated a probability matrix for each subject; the 6-month probabilities of EDSS change were graphically represented. RESULTS: The univariate analysis demonstrated the lowest baseline BPF quartile (OR 1.99; p = 0.0203) and the highest T2 lesion volume quartile (OR 2.19; p = 0.0130) were associated with progression in EDSS. Covariate specific disability curves demonstrated the effect of BPF and T2 lesion volume on short-term progression. In subjects with a 6-month EDSS of 2, the probability of a sustained progression of an EDSS of 3 within 3 years was 0.277 for a subject with low BPF and a high T2 lesion volume vs 0.055 for a subject with high BPF and a low T2 lesion volume. CONCLUSIONS: Markov transitional models allow for the comparison of covariate specific short-term disability changes among groups of patients with multiple sclerosis.

Cognitive dysfunction in patients with clinically isolated syndromes or newly diagnosed multiple sclerosis.

Cognitive dysfunction is common in patients with multiple sclerosis (MS), and has been associated with MRI measures of lesion burden and atrophy. Little is known about the prevalence of cognitive impairment in patients with early MS. The associations between cognitive impairment and MRI measures of disease severity early in the disease course are also unclear. This study used a brief battery of cognitive tests to determine the prevalence and pattern of cognitive impairment in patients with clinically isolated syndromes or newly diagnosed MS. The associations between cognitive impairment and MRI measures of disease severity early in the disease course were also examined. Ninety-two patients with clinically isolated syndromes or the diagnosis of MS within the last 3 years participating in the CLIMB study underwent a neurologic examination, neuropsychological evaluation and MRI at 1.5 T. Forty-nine percent of patients were impaired on one or more cognitive measures. There were no significant correlations between cognitive scores and MRI measures of disease severity including total T2 lesion volume, normal appearing white matter volume, grey matter volume, and brain parenchymal fraction. These findings suggest that cognitive impairment may predate the appearance of gross structural abnormalities on MRI and serve as an early marker of disease activity in MS.

Cyclophosphamide therapy for MS.

Cyclophosphamide has been widely studied for the treatment of MS and the effective stabilization of selected patients on therapy has been suggested in several studies. This drug has selective effects on the immune response, such as suppression of helper Th1 activity and enhancement of helper Th2 responses; both of these processes are thought to be involved in the beneficial effect of cyclophosphamide in MS. Over the years, especially with the advent of magnetic resonance imaging (MRI), there has been an improved understanding of the profound anti-inflammatory effect of cyclophosphamide, evidenced by its effect on clinical relapses and contrast-enhancing lesions on MRI. Toxic effects on the bladder and the risk of malignancy prevent the widespread use of cyclophosphamide in early MS; however, it can be dosed safely and is usually well tolerated in actively progressing relapsing-remitting or early secondary progressive MS cases that are unresponsive to beta interferon and glatiramer acetate.