Disease progression in the first 5 years of treatment in multiple sclerosis: Predictive value of early brain and lesion volume changes.

BACKGROUND: Whether the degree of inflammation (and its resolution) and neurodegeneration after treatment initiation predicts disease progression in multiple sclerosis (MS) remains unclear. OBJECTIVES: To assess the predictive value of magnetic resonance imaging (MRI)-derived brain and lesion volume (LV) changes in years 1 and 2 of treatment for disease progression. METHODS: Patients receiving early interferon beta-1a treatment in REFLEX/REFLEXION (N = 262) were included. Predictive regression models included new/enlarging LV (positive activity), disappearing/shrinking LV (negative activity), and global/central atrophy during years 1 and 2. RESULTS: Faster global atrophy and/or pseudo-atrophy and positive lesion activity in years 1 and 2 related to an increased probability and faster conversion to clinically definite multiple sclerosis (CDMS). Negative lesion activity in year 1 and slower central atrophy in year 2 were predictive of confirmed disability progression (9-Hole Peg Test). Positive lesion activity in year 2 was predictive of faster global atrophy, while positive lesion activity in years 1 and 2 was predictive of faster central atrophy. CONCLUSIONS: A higher degree of global atrophy and/or pseudo-atrophy in year 1 was predictive of CDMS. Positive lesion activity in any year was related to CDMS and neurodegeneration. Disability was related to negative lesion activity in year 1 and slower central atrophy in year 2.

Clinical applicability of quantitative atrophy measures on MRI in patients suspected of Alzheimer's disease.

OBJECTIVES: Neurodegeneration in suspected Alzheimer's disease can be determined using visual rating or quantitative volumetric assessments. We examined the feasibility of volumetric measurements of gray matter (GMV) and hippocampal volume (HCV) and compared their diagnostic performance with visual rating scales in academic and non-academic memory clinics. MATERIALS AND METHODS: We included 231 patients attending local memory clinics (LMC) in the Netherlands and 501 of the academic Amsterdam Dementia Cohort (ADC). MRI scans were acquired using local protocols, including a T1-weighted sequence. Quantification of GMV and HCV was performed using FSL and FreeSurfer. Medial temporal atrophy and global atrophy were assessed with visual rating scales. ROC curves were derived to determine which measure discriminated best between cognitively normal (CN), mild cognitive impairment (MCI), and Alzheimer's dementia (AD). RESULTS: Patients attending LMC (age 70.9 ± 8.9 years; 47% females; 19% CN; 34% MCI; 47% AD) were older, had more cerebrovascular pathology, and had lower GMV and HCV compared to those of the ADC (age 64.9 ± 8.2 years; 42% females; 35% CN, 43% MCI, 22% AD). While visual ratings were feasible in > 95% of scans in both cohorts, quantification was achieved in 94-98% of ADC, but only 68-85% of LMC scans, depending on the software. Visual ratings and volumetric outcomes performed similarly in discriminating CN vs AD in both cohorts. CONCLUSION: In clinical settings, quantification of GM and hippocampal atrophy currently fails in up to one-third of scans, probably due to lack of standardized acquisition protocols. Diagnostic accuracy is similar for volumetric measures and visual rating scales, making the latter suited for clinical practice. In a real-life clinical setting, volumetric assessment of MRI scans in dementia patients may require acquisition protocol optimization and does not outperform visual rating scales. KEY POINTS: • In a real-life clinical setting, the diagnostic performance of visual rating scales is similar to that of automatic volumetric quantification and may be sufficient to distinguish Alzheimer's disease groups. • Volumetric assessment of gray matter and hippocampal volumes from MRI scans of patients attending non-academic memory clinics fails in up to 32% of cases. • Clinical MR acquisition protocols should be optimized to improve the output of quantitative software for segmentation of Alzheimer's disease-specific outcomes.

The value of subtraction MRI in detection of amyloid-related imaging abnormalities with oedema or effusion in Alzheimer's patients: An interobserver study.

BACKGROUND: Immunotherapeutic treatments targeting amyloid-ß plaques in Alzheimer's disease (AD) are associated with the presence of amyloid-related imaging abnormalities with oedema or effusion (ARIA-E), whose detection and classification is crucial to evaluate subjects enrolled in clinical trials. PURPOSE: To investigate the applicability of subtraction MRI in the ARIA-E detection using an established ARIA-E-rating scale. METHODS: We included 75 AD patients receiving bapineuzumab treatment, including 29 ARIA-E cases. Five neuroradiologists rated their brain MRI-scans with and without subtraction images. The accuracy of evaluating the presence of ARIA-E, intraclass correlation coefficient (ICC) and specific agreement was calculated. RESULTS: Subtraction resulted in higher sensitivity (0.966) and lower specificity (0.970) than native images (0.959, 0.991, respectively). Individual rater detection was excellent. ICC scores ranged from excellent to good, except for gyral swelling (moderate). Excellent negative and good positive specific agreement among all ARIA-E imaging features was reported in both groups. Combining sulcal hyperintensity and gyral swelling significantly increased positive agreement for subtraction images. CONCLUSION: Subtraction MRI has potential as a visual aid increasing the sensitivity of ARIA-E assessment. However, in order to improve its usefulness isotropic acquisition and enhanced training are required. The ARIA-E rating scale may benefit from combining sulcal hyperintensity and swelling. KEY POINTS: • Subtraction technique can improve detection amyloid-related imaging-abnormalities with edema/effusion in Alzheimer's patients. • The value of ARIA-E detection, classification and monitoring using subtraction was assessed. • Validation of an established ARIA-E rating scale, recommendations for improvement are reported. • Complementary statistical methods were employed to measure accuracy, inter-rater-reliability and specific agreement.

Performance of five research-domain automated WM lesion segmentation methods in a multi-center MS study.

BACKGROUND AND PURPOSE: In vivoidentification of white matter lesions plays a key-role in evaluation of patients with multiple sclerosis (MS). Automated lesion segmentation methods have been developed to substitute manual outlining, but evidence of their performance in multi-center investigations is lacking. In this work, five research-domain automated segmentation methods were evaluated using a multi-center MS dataset. METHODS: 70 MS patients (median EDSS of 2.0 [range 0.0-6.5]) were included from a six-center dataset of the MAGNIMS Study Group (www.magnims.eu) which included 2D FLAIR and 3D T1 images with manual lesion segmentation as a reference. Automated lesion segmentations were produced using five algorithms: Cascade; Lesion Segmentation Toolbox (LST) with both the Lesion growth algorithm (LGA) and the Lesion prediction algorithm (LPA); Lesion-Topology preserving Anatomical Segmentation (Lesion-TOADS); and k-Nearest Neighbor with Tissue Type Priors (kNN-TTP). Main software parameters were optimized using a training set (N = 18), and formal testing was performed on the remaining patients (N = 52). To evaluate volumetric agreement with the reference segmentations, intraclass correlation coefficient (ICC) as well as mean difference in lesion volumes between the automated and reference segmentations were calculated. The Similarity Index (SI), False Positive (FP) volumes and False Negative (FN) volumes were used to examine spatial agreement. All analyses were repeated using a leave-one-center-out design to exclude the center of interest from the training phase to evaluate the performance of the method on 'unseen' center. RESULTS: Compared to the reference mean lesion volume (4.85 ± 7.29 mL), the methods displayed a mean difference of 1.60 ± 4.83 (Cascade), 2.31 ± 7.66 (LGA), 0.44 ± 4.68 (LPA), 1.76 ± 4.17 (Lesion-TOADS) and -1.39 ± 4.10 mL (kNN-TTP). The ICCs were 0.755, 0.713, 0.851, 0.806 and 0.723, respectively. Spatial agreement with reference segmentations was higher for LPA (SI = 0.37 ± 0.23), Lesion-TOADS (SI = 0.35 ± 0.18) and kNN-TTP (SI = 0.44 ± 0.14) than for Cascade (SI = 0.26 ± 0.17) or LGA (SI = 0.31 ± 0.23). All methods showed highly similar results when used on data from a center not used in software parameter optimization. CONCLUSION: The performance of the methods in this multi-center MS dataset was moderate, but appeared to be robust even with new datasets from centers not included in training the automated methods.

Hippocampal volume change measurement: quantitative assessment of the reproducibility of expert manual outlining and the automated methods FreeSurfer and FIRST.

BACKGROUND: To measure hippocampal volume change in Alzheimer's disease (AD) or mild cognitive impairment (MCI), expert manual delineation is often used because of its supposed accuracy. It has been suggested that expert outlining yields poorer reproducibility as compared to automated methods, but this has not been investigated. AIM: To determine the reproducibilities of expert manual outlining and two common automated methods for measuring hippocampal atrophy rates in healthy aging, MCI and AD. METHODS: From the Alzheimer's Disease Neuroimaging Initiative (ADNI), 80 subjects were selected: 20 patients with AD, 40 patients with mild cognitive impairment (MCI) and 20 healthy controls (HCs). Left and right hippocampal volume change between baseline and month-12 visit was assessed by using expert manual delineation, and by the automated software packages FreeSurfer (longitudinal processing stream) and FIRST. To assess reproducibility of the measured hippocampal volume change, both back-to-back (BTB) MPRAGE scans available for each visit were analyzed. Hippocampal volume change was expressed in µL, and as a percentage of baseline volume. Reproducibility of the 1-year hippocampal volume change was estimated from the BTB measurements by using linear mixed model to calculate the limits of agreement (LoA) of each method, reflecting its measurement uncertainty. Using the delta method, approximate p-values were calculated for the pairwise comparisons between methods. Statistical analyses were performed both with inclusion and exclusion of visibly incorrect segmentations. RESULTS: Visibly incorrect automated segmentation in either one or both scans of a longitudinal scan pair occurred in 7.5% of the hippocampi for FreeSurfer and in 6.9% of the hippocampi for FIRST. After excluding these failed cases, reproducibility analysis for 1-year percentage volume change yielded LoA of ±7.2% for FreeSurfer, ±9.7% for expert manual delineation, and ±10.0% for FIRST. Methods ranked the same for reproducibility of 1-year µL volume change, with LoA of ±218 µL for FreeSurfer, ±319 µL for expert manual delineation, and ±333 µL for FIRST. Approximate p-values indicated that reproducibility was better for FreeSurfer than for manual or FIRST, and that manual and FIRST did not differ. Inclusion of failed automated segmentations led to worsening of reproducibility of both automated methods for 1-year raw and percentage volume change. CONCLUSION: Quantitative reproducibility values of 1-year microliter and percentage hippocampal volume change were roughly similar between expert manual outlining, FIRST and FreeSurfer, but FreeSurfer reproducibility was statistically significantly superior to both manual outlining and FIRST after exclusion of failed segmentations.

Mean upper cervical cord area (MUCCA) measurement in long-standing multiple sclerosis: relation to brain findings and clinical disability.

BACKGROUND: The majority of patients with multiple sclerosis (MS) present with spinal cord pathology. Spinal cord atrophy is thought to be a marker of disease severity, but in long-disease duration its relation to brain pathology and clinical disability is largely unknown. OBJECTIVE: Our aim was to investigate mean upper cervical cord area (MUCCA) in patients with long-standing MS and assess its relation to brain magnetic resonance imaging (MRI) measures and clinical disability. METHODS: MUCCA was measured in 196 MS patients and 55 healthy controls using 3DT1-weighted cervical images obtained at 3T MRI. Clinical disability was measured using the Expanded Disability Status Scale (EDSS), Nine-Hole-Peg test (9-HPT), and 25 feet Timed Walk Test (TWT). Stepwise linear regression was performed to assess the association between MUCCA and MRI measures, and between MUCCA and clinical disability. RESULTS: MUCCA was smaller (mean 11.7%) in MS patients compared with healthy controls (72.56±9.82 and 82.24±7.80 mm2 respectively; p<0.001), most prominently in male patients. MUCCA was associated with normalized brain volume, and number of cervical cord lesions. MUCCA was independently associated with EDSS, TWT, and 9-HPT. CONCLUSION: MUCCA was reduced in MS patients compared with healthy controls. It provides a relevant marker for clinical disability in long-standing disease, independent of other MRI measures.

The spatio-temporal relationship between concurrent lesion and brain atrophy changes in early multiple sclerosis: A post-hoc analysis of the REFLEXION study.

BACKGROUND: White matter (WM) lesions and brain atrophy are present early in multiple sclerosis (MS). However, their spatio-temporal relationship remains unclear. METHODS: Yearly magnetic resonance images were analysed in 387 patients with a first clinical demyelinating event (FCDE) from the 5-year REFLEXION study. Patients received early (from baseline; N = 258; ET) or delayed treatment (from month-24; N = 129; DT) with subcutaneous interferon beta-1a. FSL-SIENA/VIENA were used to provide yearly percentage volume change of brain (PBVC) and ventricles (PVVC). Yearly total lesion volume change (TLVC) was determined by a semi-automated method. Using linear mixed models and voxel-wise analyses, we firstly investigated the overall relationship between TLVC and PBVC and between TLVC and PVVC in the same follow-up period. Analyses were then separately performed for: the untreated period of DT patients (first two years), the first year of treatment (year 1 for ET and year 3 for DT), and a period where patients had received at least 1 year of treatment (stable treatment; ET: years 2, 3, 4, and 5; DT: years 4 and 5). RESULTS: Whole brain: across the whole study period, lower TLVC was related to faster atrophy (PBVC: B = 0.046, SE = 0.013, p < 0.001; PVVC: B = -0.466, SE = 0.118, p < 0.001). Within the untreated period of DT patients, lower TLVC was related to faster atrophy (PBVC: B = 0.072, SE = 0.029, p = 0.013; PVVC: B = -0.917, SE = 0.306, p = 0.003). A similar relationship was found within the first year of treatment of ET patients (PBVC: B = 0.081, SE = 0.027, p = 0.003; PVVC: B = -1.08, SE = 0.284, p < 0.001), consistent with resolving oedema and pseudo-atrophy. Voxel-wise: overall, higher TLVC was related to faster ventricular enlargement. Lower TLVC was related to faster widespread atrophy in year 1 in both ET (first year of treatment) and DT (untreated) patients. In the second untreated year of DT patients and within the stable treatment period of ET patients (year 4), faster periventricular and occipital lobe atrophy was associated with higher TLVC. CONCLUSIONS: WM lesion changes and atrophy occurred simultaneously in early MS. Spatio-temporal correspondence of these two processes involved mostly the periventricular area. Within the first year of the study, in both treatment groups, faster atrophy was linked to lower lesion volume changes, consistent with higher shrinking and disappearing lesion activity. This might reflect the pseudo-atrophy phenomenon that is probably related to the therapy driven (only in ET patients, as they received treatment from baseline) and "natural" (both ET and DT patients entered the study after a FCDE) resolution of oedema. In an untreated period and later on during stable treatment, (real) atrophy was related to higher lesion volume changes, consistent with increased new and enlarging lesion activity.

The spatio-temporal relationship between white matter lesion volume changes and brain atrophy in clinically isolated syndrome and early multiple sclerosis.

BACKGROUND: White matter lesions and brain atrophy are both present early in multiple sclerosis. However, the spatio-temporal relationship between atrophy and lesion processes remains unclear. METHODS: Yearly magnetic resonance images were analyzed in 392 patients with clinically isolated syndrome from the 5-year REFLEX/REFLEXION studies. Patients received early treatment (from baseline; N = 262) or delayed treatment (from month-24; N = 130) with subcutaneous interferon beta-1a. Global and central atrophy were assessed using FSL-SIENA to provide yearly percentage volume change of brain and ventricles, respectively. Yearly total lesion volume change was calculated by subtracting the sum of the negative lesion volume change (disappearing + shrinking) from the positive lesion volume change (new + enlarging) for each yearly interval, as determined by an in-house developed semi-automated method. Using linear mixed models, during the period where patients had received ≥1 year of treatment, we investigated whether total lesion volume change was associated with percentage brain volume change or percentage ventricular volume change in the next year, and vice versa. RESULTS: Higher total lesion volume change was related to significantly faster global atrophy (percentage brain volume change) in the next year (B = - 0.113, SE = 0.022, p < 0.001). In patients receiving early treatment only, total lesion volume change was also associated with percentage ventricular volume change in the next year (B = 1.348, SE = 0.181, p < 0.001). Voxel-wise analyses showed that in patients receiving early treatment, higher total lesion volume change in years 2, 3, and 4 was related to faster atrophy in the next year, and in year 4 this relationship was stronger in patients receiving delayed treatment. Interestingly, faster atrophy was related to higher total lesion volume change in the next year (percentage brain volume change: B = - 0.136, SE = 0.062, p = 0.028; percentage ventricular volume change: B = 0.028, SE = 0.008, p < 0.001). CONCLUSIONS: Higher lesion volume changes were associated with faster atrophy in the next year. Interestingly, there was also an association between faster atrophy and higher lesion volume changes in the next year.

Long-interval T2-weighted subtraction magnetic resonance imaging: a powerful new outcome measure in multiple sclerosis trials.

OBJECTIVE: To compare long-interval T2-weighted subtraction (T2w-Sub) imaging with monthly gadolinium-enhanced T1-weighted (Gd-T1w) imaging for (1) detection of active lesions, (2) assessment of treatment efficacy, and (3) statistical power, in a multiple sclerosis (MS), phase 2, clinical trial setting. METHODS: Magnetic resonance imaging (MRI) data over 9 months from 120 patients (61 treatment, 59 placebo) from the oral temsirolimus trial were used. T2w-Sub images were scored for active lesions, independent of the original reading of the monthly Gd-T1w images. Treatment efficacy was evaluated using the nonparametric Mann-Whitney U test, and parametric negative binomial (NB)-regression and power calculations were conducted. RESULTS: Datasets from 116 patients (58 treatment, 58 placebo) were evaluated. The mean number of T2w-Sub lesions in the treatment group was 3.0 (+/-4.6) versus 5.9 (+/-8.8) for placebo; the mean cumulative number of new Gd-T1w lesions in the treatment group was 5.5(+/-9.1) versus 9.1(+/-17.2) for placebo. T2w-Sub imaging showed increased power to assess treatment efficacy compared with Gd-T1w imaging, when evaluated by Mann-Whitney U test (p = 0.017 vs p = 0.177), or NB-regression without (p = 0.011 vs p = 0.092) or with baseline adjustment (p < 0.001 vs p = 0.002). Depending on the magnitude of the simulated treatment effect, sample size calculations showed reductions of 22 to 34% in the number of patients (translating into reductions of 81-83% in the number of MRI scans) needed to detect a significant treatment effect in favor of T2w-Sub imaging. INTERPRETATION: Compared with monthly Gd-T1w imaging, long-interval T2w-Sub MRI exhibited increased power to assess treatment efficacy, and could greatly increase the cost-effectiveness of phase 2 MS trials by limiting the number of patients, contrast injections, and MRI scans needed.

Assessing the reproducibility of the SienaX and Siena brain atrophy measures using the ADNI back-to-back MP-RAGE MRI scans.

SienaX and Siena are widely used and fully automated algorithms for measuring whole brain volume and volume change in cross-sectional and longitudinal MRI studies and are particularly useful in studies of brain atrophy. The reproducibility of the algorithms was assessed using the 3D T1 weighted MP-RAGE scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. The back-to-back (BTB) MP-RAGE scans in the ADNI data set makes it a valuable benchmark against which to assess the performance of algorithms of measuring atrophy in the human brain with MRI scans. A total of 671 subjects were included for SienaX and 385 subjects for Siena. The annual percentage brain volume change (PBVC) rates were -0.65±0.82%/year for the healthy controls, -1.15±1.21%/year for mild cognitively impairment (MCI) and -1.84±1.33%/year for AD, in line with previous findings. The median of the absolute value of the reproducibility of SienaX's normalized brain volume (NBV) was 0.96% while the 90th percentile was 5.11%. The reproducibility of Siena's PBVC had a median of 0.35% and a 90th percentile of 1.37%. While the median reproducibility for SienaX's NBV was in line with the values previously reported in the literature, the median reproducibility of Siena's PBVC was about twice that reported. Also, the 90th percentiles for both SienaX and Siena were about twice the size that would be expected for a Gaussian distribution. Because of the natural variation of the disease among patients over a year, a perfectly reproducible whole brain atrophy algorithm would reduce the estimated group size needed to detect a specified treatment effect by only 30% to 40% as compared to Siena's.

Improved detection of active multiple sclerosis lesions: 3D subtraction imaging.

PURPOSE: To examine the benefits of using near-isotropic single-slab three-dimensional (3D) magnetic resonance (MR) imaging for the creation of subtraction images and to evaluate their performance in the detection of active multiple sclerosis (MS) brain lesions in comparison with two-dimensional (2D) subtraction images. MATERIALS AND METHODS: The study protocol was approved by the local ethics review board and all subjects gave written informed consent before investigation. Three-dimensional MR sequences, including double inversion-recovery, fluid-attenuated inversion recovery, T2-weighted, and T1-weighted magnetization-prepared rapid acquisition gradient-echo (MP-RAGE), and corresponding 2D sequences were performed twice in 14 patients (eight women, six men; mean age, 37.6 years) with MS and nine age-matched healthy control subjects (three women, six men; mean age, 31.7 years). Active lesions were scored by two independent raters, followed by a consensus reading. Lesion counts were evaluated by using negative binomial regression; interrater agreement was evaluated by using intraclass correlation coefficient. RESULTS: Three-dimensional subtraction images had less residual misregistration and flow artifacts and depicted higher numbers of active lesions with greater interobserver agreement compared with 2D subtraction images. Among the 3D sequences, MP-RAGE subtraction imaging enabled detection of a significantly higher mean number of positive active MS lesions compared with 2D subtraction imaging (2.8 versus 1.7, P = .012), particularly infratentorial lesions (0.6 vs 0.1, P < .05), and a substantially higher (nonsignificant) mean number of small (<3 mm) lesions (0.6 vs 0.1, P > .05). CONCLUSION: Three-dimensional subtraction imaging, after image registration, produced better image quality, leading to increased detection of active MS lesions with greater interobserver agreement in comparison with 2D subtraction imaging; 3D MP-RAGE subtraction imaging represents a promising technique to increase sensitivity in ascertaining lesion dissemination in time and increase the power of MR imaging metrics for the evaluation of treatment effects in clinical trials.

Subtraction MR images in a multiple sclerosis multicenter clinical trial setting.

PURPOSE: To explore the applicability of subtraction magnetic resonance (MR) images to (a) detect active multiple sclerosis (MS) lesions, (b) directly quantify lesion load change, and (c) detect treatment effects (distinguish treatment arms) in a placebo-controlled multicenter clinical trial by comparing the subtraction scheme with a conventional pair-wise comparison of nonregistered MR images. MATERIALS AND METHODS: Forty-six pairs of MR studies in 40 patients (31 women; mean age, 31.9 years) from a multicenter clinical trial were used. The clinical trial was approved by local ethics review boards, and all subjects gave written informed consent. Active MS lesions were scored by two independent raters, and lesion load measurements were conducted by using semiautomated software. Lesion counts were evaluated by using the Wilcoxon signed rank test, interrater agreement was evaluated by using the intraclass correlation coefficient (ICC), and treatment (interferon beta-1b) effect was evaluated by using the Mann-Whitney U test. RESULTS: When subtraction images were used, there was a 1.7-fold increase in the detection of positive active lesions, as compared with native image pairs, and significantly greater interobserver agreement (ICC = 0.98 vs 0.91, P < .001). Subtraction images also allowed direct quantification of positive disease activity, a measure that provided sufficient power to distinguish treatment arms (P = .012) compared with the standard measurement of total lesion load change on native images (P = .455). CONCLUSION: MR image subtraction enabled detection of higher numbers of active MS lesions with greater interobserver agreement and exhibited increased power to distinguish treatment arms, as compared with a conventional pair-wise comparison of nonregistered MR images.

Can measuring hippocampal atrophy with a fully automatic method be substantially less noisy than manual segmentation over both 1 and 3 years?

To quantify the "segmentation noise" of several widely used fully automatic methods for measuring longitudinal hippocampal atrophy in Alzheimer's disease and compare the results to the segmentation noise of manual segmentation over both 1 and 3 years. The segmentation noise of 5 longitudinal hippocampal atrophy measurement methods was quantified, including checking its Gaussianity, using 264 subjects from the ADNI1 back-to-back (BTB) data set over both 1 year and 3 year intervals. The segmentation methods were FreeSurfer 5.3.0 both cross sectional and longitudinal, FreeSurfer 6.0.0 longitudinal, MAPS-HBSI and FSL/FIRST 5.0.8. The BTB manual segmentation of 75 ADNI subjects from a previous study provided the manual distributions for comparison. All methods, including the manual segmentation, violated the Gaussianity assumption. Two methods, FreeSurfer 6.0.0 and MAPS-HBSI, had a segmentation noise substantially less than a surrogate for manual segmentation. FreeSurfer 5.3.0 longitudinal was confirmed as a surrogate for manual segmentation. The violation of the Gaussian assumption by the segmentation methods assessed, including manual, suggests results of previous studies that assumed Gaussian statistics without confirmation may need review. Fully automatic FreeSurfer 6.0.0 and MAPS-HBSI both have lower segmentation noise than manual requiring less than two thirds of the subjects to detect the same treatment effect.

Reproducibility of hippocampal atrophy rates measured with manual, FreeSurfer, AdaBoost, FSL/FIRST and the MAPS-HBSI methods in Alzheimer's disease.

The purpose of this study is to assess the reproducibility of hippocampal atrophy rate measurements of commonly used fully-automated algorithms in Alzheimer disease (AD). The reproducibility of hippocampal atrophy rate for FSL/FIRST, AdaBoost, FreeSurfer, MAPS independently and MAPS combined with the boundary shift integral (MAPS-HBSI) were calculated. Back-to-back (BTB) 3D T1-weighted MPRAGE MRI from the Alzheimer's Disease Neuroimaging Initiative (ADNI1) study at baseline and year one were used. Analysis on 3 groups of subjects was performed - 562 subjects at 1.5T, a 75 subject group that also had manual segmentation and 111 subjects at 3T. A simple and novel statistical test based on the binomial distribution was used that handled outlying data points robustly. Median hippocampal atrophy rates were -1.1%/year for healthy controls, -3.0%/year for mildly cognitively impaired and -5.1%/year for AD subjects. The best reproducibility was observed for MAPS-HBSI (1.3%), while the other methods tested had reproducibilities at least 50% higher at 1.5T and 3T which was statistically significant. For a clinical trial, MAPS-HBSI should require less than half the subjects of the other methods tested. All methods had good accuracy versus manual segmentation. The MAPS-HBSI method has substantially better reproducibility than the other methods considered.

Image registration and subtraction to detect active T(2) lesions in MS: an interobserver study.

Serial MRI studies are used to analyse change in multiple sclerosis (MS) lesion volume in clinical trials. As such an evaluation is very time consuming and subject to quantification errors, one might assess only the change in number or size of lesions using subtracted images. The advantage of subtracted images is that both new and/or enlarging and resolving and/or shrinking lesions can be evaluated, resulting in a more precise volume change than a net volume change. We studied the interobserver agreement in the detection of active MS lesions using paired dual-echo T(2)-weighted spin-echo studies (3-mm slices) of 30 MS patients with a range of MS disease activity on MRI from treatment trials. Using an automatic matching algorithm based on mutual information, the follow-up scan was registered to baseline, after which subtracted images were obtained. After a training session with formulation of guidelines, six observers identified new, enlarging, resolving and shrinking lesions on subtracted images. Weighted kappa (kappa) values were calculated to assess interobserver agreement. Good agreement was found for new lesions (kappa 0.69 +/- 0.08), while moderate agreement was found for enlarging lesions (kappa 0.52 +/- 0.06). When new and enlarging lesions were combined, good agreement was found for "positive" activity (kappa 0.71 +/-0.06). The interobserver agreement was poor for resolving lesions (kappa 0.31 +/- 0.07), and moderate for shrinking lesions (kappa 0.53 +/- 0.08). In conclusion, the use of subtracted images in the visual detection of new T(2) lesions resulted in a good level of interobserver agreement for "positive" disease activity. Subtraction of registered images is a reliable, time efficient method to assess disease progression in MS.

The SIENA/FSL whole brain atrophy algorithm is no more reproducible at 3T than 1.5 T for Alzheimer's disease.

The back-to-back (BTB) acquisition of MP-RAGE MRI scans of the Alzheimer׳s Disease Neuroimaging Initiative (ADNI1) provides an excellent data set with which to check the reproducibility of brain atrophy measures. As part of ADNI1, 131 subjects received BTB MP-RAGEs at multiple time points and two field strengths of 3T and 1.5 T. As a result, high quality data from 200 subject-visit-pairs was available to compare the reproducibility of brain atrophies measured with FSL/SIENA over 12 to 18 month intervals at both 3T and 1.5 T. Although several publications have reported on the differing performance of brain atrophy measures at 3T and 1.5 T, no formal comparison of reproducibility has been published to date. Another goal was to check whether tuning SIENA options, including -B, -S, -R and the fractional intensity threshold (f) had a significant impact on the reproducibility. The BTB reproducibility for SIENA was quantified by the 50th percentile of the absolute value of the difference in the percentage brain volume change (PBVC) for the BTB MP-RAGES. At both 3T and 1.5 T the SIENA option combination of "-B f=0.2", which is different from the default values of f=0.5, yielded the best reproducibility as measured by the 50th percentile yielding 0.28 (0.23-0.39)% and 0.26 (0.20-0.32)%. These results demonstrated that in general 3T had no advantage over 1.5 T for the whole brain atrophy measure - at least for SIENA. While 3T MRI is superior to 1.5 T for many types of measurements, and thus worth the additional cost, brain atrophy measurement does not seem to be one of them.

Long-term effects of amyloid, hypometabolism, and atrophy on neuropsychological functions.

OBJECTIVE: To assess how amyloid deposition, glucose hypometabolism, and cerebral atrophy affect neuropsychological performance in patients with Alzheimer disease (AD) dementia, patients with mild cognitive impairment (MCI), and controls over time. METHODS: A total of 41 patients with AD dementia, 28 patients with MCI, and 19 controls underwent [(11)C]-Pittsburgh compound B ((11)C-PiB) and [(18)F]-2-fluoro-2-deoxy-d-glucose ((18)F-FDG)-PET and MRI scans at baseline. We extracted global binding potential for (11)C-PiB, the number of abnormal voxels for (18)F-FDG, and gray matter volumes using SIENAX for MRI as measures of amyloid, hypometabolism, and atrophy. In addition, repeat neuropsychological testing was performed, including memory, attention, language, and executive tasks (mean follow-up 2.2 ± 0.7 years). Cross-sectional and longitudinal relationships between imaging markers and cognition were assessed using linear mixed models, including terms for the imaging markers, time, sex, age, diagnosis, and interactions for imaging marker × time and imaging marker × time × diagnosis. RESULTS: Linear mixed models showed that baseline hypometabolism and atrophy were associated with poorer baseline performance on attention and executive functions (p < 0.05), whereas amyloid was not related to baseline cognition. Hypometabolism and amyloid were strongly associated with longitudinal decline in essentially all cognitive domains (pinteraction < 0.05), whereas atrophy was related specifically to future decline in Mini-Mental State Examination and memory (pinteraction < 0.05). CONCLUSION: Glucose hypometabolism and brain atrophy were associated with concurrent cognitive function, whereas brain amyloid was not. Amyloid deposition and glucose hypometabolism were predictors for decline of a wide variety of cognitive functions, while brain atrophy specifically predicted memory deterioration.

Adaptation of lateral pterygoid and anterior digastric muscles after surgical mandibular advancement procedures in different vertical craniofacial types: a magnetic resonance imaging study.

OBJECTIVE: Surgical mandibular advancement procedures induce major adaptations of jaw-closing muscles. In this study, adaptation of antagonist muscles, the lateral pterygoid (LPM) and anterior digastric (DigA) muscles, was evaluated. STUDY DESIGN: Eighteen adult patients with mandibular retrognathia and individually varying vertical craniofacial dimensions were treated with bilateral sagittal split osteotomies (BSSO), in some cases combined with a Le Fort I osteotomy (LF Bimax). The sample was divided into 1 short-face (SF, n = 7) and 2 long-face groups (LF BSSO, n = 3; and LF Bimax, n = 8). Pre- and postoperative maximum cross-sectional areas (CSA) and volumes were compared in these groups. RESULTS: Postoperatively, CSA and volume of LPM increased in BSSO cases and decreased in bimaxillary cases. Inconsistent increases and decreases of CSA and volume of DigA were seen in all groups. CONCLUSIONS: The LPM became larger in SF and LF BSSO patients and smaller in LF Bimax patients. The DigA adapted unpredictably.

Multi-contrast, isotropic, single-slab 3D MR imaging in multiple sclerosis.

To describe signal and contrast properties of an isotropic, single-slab 3D dataset [double inversion-recovery (DIR), fluid-attenuated inversion recovery (FLAIR), T2, and T1-weighted magnetization prepared rapid acquisition gradient-echo (MPRAGE)] and to evaluate its performance in detecting multiple sclerosis (MS) brain lesions compared to 2D T2-weighted spin-echo (T2SE). All single-slab 3D sequences and 2D-T2SE were acquired in 16 MS patients and 9 age-matched healthy controls. Lesions were scored independently by two raters and characterized anatomically. Two-tailed Bonferroni-corrected Student's t-tests were used to detect differences in lesion detection between the various sequences per anatomical area after log-transformation. In general, signal and contrast properties of the 3D sequences enabled improved detection of MS brain lesions compared to 2D-T2SE. Specifically, 3D-DIR showed the highest detection of intracortical and mixed WM-GM lesions, whereas 3D-FLAIR showed the highest total number of WM lesions. Both 3D-DIR and 3D-FLAIR showed the highest number of infratentorial lesions. 3D-T2 and 3D-MPRAGE did not improve lesion detection compared to 2D-T2SE. Multi-contrast, isotropic, single-slab 3D MRI allowed an improved detection of both GM and WM lesions compared to 2D-T2SE. A selection of single-slab 3D contrasts, for example, 3D-FLAIR and 3D-DIR, could replace 2D sequences in the radiological practice.

Automated segmentation of multiple sclerosis lesion subtypes with multichannel MRI.

PURPOSE: To automatically segment multiple sclerosis (MS) lesions into three subtypes (i.e., enhancing lesions, T1 "black holes", T2 hyperintense lesions). MATERIALS AND METHODS: Proton density-, T2- and contrast-enhanced T1-weighted brain images of 12 MR scans were pre-processed through intracranial cavity (IC) extraction, inhomogeneity correction and intensity normalization. Intensity-based statistical k-nearest neighbor (k-NN) classification was combined with template-driven segmentation and partial volume artifact correction (TDS+) for segmentation of MS lesions subtypes and brain tissue compartments. Operator-supervised tissue sampling and parameter calibration were performed on 2 randomly selected scans and were applied automatically to the remaining 10 scans. Results from this three-channel TDS+ (3ch-TDS+) were compared to those from a previously validated two-channel TDS+ (2ch-TDS+) method. The results of both the 3ch-TDS+ and 2ch-TDS+ were also compared to manual segmentation performed by experts. RESULTS: Intra-class correlation coefficients (ICC) of 3ch-TDS+ for all three subtypes of lesions were higher (ICC between 0.95 and 0.96) than that of 2ch-TDS+ for T2 lesions (ICC = 0.82). The 3ch-TDS+ also identified the three lesion subtypes with high specificity (98.7-99.9%) and accuracy (98.5-99.9%). Sensitivity of 3ch-TDS+ for T2 lesions was 16% higher than with 2ch-TDS+. Enhancing lesions were segmented with the best sensitivity (81.9%). "Black holes" were segmented with the least sensitivity (62.3%). CONCLUSION: 3ch-TDS+ is a promising method for automated segmentation of MS lesion subtypes.