Disease correlates of rim lesions on quantitative susceptibility mapping in multiple sclerosis.

Quantitative susceptibility mapping (QSM), an imaging technique sensitive to brain iron, has been used to detect paramagnetic rims of iron-laden active microglia and macrophages in a subset of multiple sclerosis (MS) lesions, known as rim+ lesions, that are consistent with chronic active lesions. Because of the potential impact of rim+ lesions on disease progression and tissue damage, investigating their influence on disability and neurodegeneration is critical to establish the impact of these lesions on the disease course. This study aimed to explore the relationship between chronic active rim+ lesions, identified as having a hyperintense rim on QSM, and both clinical disability and imaging measures of neurodegeneration in patients with MS. The patient cohort was composed of 159 relapsing-remitting multiple sclerosis patients. The Expanded Disability Status Scale (EDSS) and Brief International Cognitive Assessment for Multiple Sclerosis, which includes both the Symbol Digit Modalities Test and California Verbal Learning Test-II, were used to assess clinical disability. Cortical thickness and thalamic volume were evaluated as imaging measures of neurodegeneration. A total of 4469 MS lesions were identified, of which 171 QSM rim+ (3.8%) lesions were identified among 57 patients (35.8%). In a multivariate regression model, as the overall total lesion burden increased, patients with at least one rim+ lesion on QSM performed worse on both physical disability and cognitive assessments, specifically the Symbol Digit Modalities Test (p = 0.010), California Verbal Learning Test-II (p = 0.030), and EDSS (p = 0.001). In a separate univariate regression model, controlling for age (p < 0.001) and having at least one rim+ lesion was related to more cortical thinning (p = 0.03) in younger patients (< 45 years). Lower thalamic volume was associated with older patients (p = 0.038) and larger total lesion burden (p < 0.001); however, the association did not remain significant with rim+ lesions (p = 0.10). Our findings demonstrate a novel observation that chronic active lesions, as identified on QSM, modify the impact of lesion burden on clinical disability in MS patients. These results support further exploration of rim+ lesions for therapeutic targeting in MS to reduce disability and subsequent neurodegeneration.

Lesion features on magnetic resonance imaging discriminate multiple sclerosis patients.

BACKGROUND: Magnetic resonance imaging (MRI) provides insight into various pathological processes in multiple sclerosis (MS) and may provide insight into patterns of damage among patients. OBJECTIVE: We sought to determine if MRI features have clinical discriminative power among a cohort of MS patients. METHODS: Ninety-six relapsing remitting and seven progressive MS patients underwent myelin water fraction (MWF) imaging and conventional MRI for cortical thickness and thalamic volume. Patients were clustered based on lesion level MRI features using an agglomerative hierarchical clustering algorithm based on principal component analysis (PCA). RESULTS: One hundred and three patients with 1689 MS lesions were analyzed. PCA on MRI features demonstrated that lesion MWF and volume distributions (characterized by 25th, 50th, and 75th percentiles) accounted for 87% of the total variability based on four principal components. The best hierarchical cluster confirmed two distinct patient clusters. The clustering features in order of importance were lesion median MWF, MWF 25th, MWF 75th, volume 75th percentiles, median individual lesion volume, total lesion volume, cortical thickness, and thalamic volume (all p values <0.01368). The clusters were associated with patient Expanded Disability Status Scale (EDSS) (n = 103, p = 0.0338) at baseline and at 5 years (n = 72, p = 0.0337). CONCLUSIONS: These results demonstrate that individual MRI features can identify two patient clusters driven by lesion-based values, and our unique approach is an analysis blinded to clinical variables. The two distinct clusters exhibit MWF differences, most likely representing individual remyelination capabilities among different patient groups. These findings support the concept of patient-specific pathophysiological processes and may guide future therapeutic approaches.

Impact of Lesion Location on Longitudinal Myelin Water Fraction Change in Chronic Multiple Sclerosis Lesions.

BACKGROUND AND PURPOSE: To examine the impact of lesion location on longitudinal myelin water fraction (MWF) changes in chronic multiple sclerosis (MS) lesions. Relative hypoxia, due to vascular watershed regions of the cerebrum, has been implicated in lesion development but impact on ongoing demyelination is unknown. METHODS: Forty-eight patients with relapsing-remitting and secondary progressive MS had two MWF scans with fast acquisition, spiral trajectory, and T2prep (FAST-T2) sequence, at an interval of 2.0 (±.3) years. Lesion location was identified based upon cerebral lobe and relation to the ventricles. Change in MWF was assessed using a mixed effects model, controlling for lesion location and patient covariates. RESULTS: Average age was 42.3 (±12) years, mean disease duration was 9.7 (±9.1) years, and median Expanded Disability Status Score (EDSS) was 2.5 (±2.3). The majority of 512 chronic lesions was located in the frontal and parietal lobes (75.6%) and more often periventricular (44.7%). All occipital lesions were periventricular. The average lesion MWF decreased from baseline (.07 ± .03) to 2 years (.06 ±.03) P < .01. Lesions within the occipital lobe showed a significant reduction in MWF as compared to other lobes. CONCLUSIONS: Chronic lesions in the occipital lobe showed the greatest reduction in MWF. Neuroanatomical localization of lesions to the occipital horns of the lateral ventricles, a watershed region, may contribute to ongoing demyelination in this lesion type.

A Bayesian piecewise survival cure rate model for spatially clustered data.

This paper proposes a Bayesian hierarchical cure rate survival model for spatially clustered time to event data. We consider a mixture cure rate model with covariates and a flexible (semi)parametric baseline survival distribution for uncured individuals. The spatial correlation structure is introduced in the form of frailties which follow a Multivariate Conditionally Autoregressive distribution on a pre-specified map. We obtain the usual posterior estimates, smoothed by regional level maps of spatial frailties and cure rates. A simulation study demonstrates that the parameters of the models with spatially correlated frailties have smaller relative biases and MSE than the ones obtained using simple frailty models. We apply our methodology to Hodgkin lymphoma cancer survival times for patients diagnosed in the state of Connecticut.

Quantitative susceptibility mapping identifies inflammation in a subset of chronic multiple sclerosis lesions.

Chronic active multiple sclerosis lesions, characterized by a hyperintense rim of iron-enriched, activated microglia and macrophages, have been linked to greater tissue damage. Post-mortem studies have determined that chronic active lesions are primarily related to the later stages of multiple sclerosis; however, the occurrence of these lesions, and their relationship to earlier disease stages may be greatly underestimated. Detection of chronic active lesions across the patient spectrum of multiple sclerosis requires a validated imaging tool to accurately identify lesions with persistent inflammation. Quantitative susceptibility mapping provides efficient in vivo quantification of susceptibility changes related to iron deposition and the potential to identify lesions harbouring iron-laden inflammatory cells. The PET tracer 11C-PK11195 targets the translocator protein expressed by activated microglia and infiltrating macrophages. Accordingly, this study aimed to validate that lesions with a hyperintense rim on quantitative susceptibility mapping from both relapsing and progressive patients demonstrate a higher level of innate immune activation as measured on 11C-PK11195 PET. Thirty patients were enrolled in this study, 24 patients had relapsing remitting multiple sclerosis, six had progressive multiple sclerosis, and all patients had concomitant MRI with a gradient echo sequence and PET with 11C-PK11195. A total of 406 chronic lesions were detected, and 43 chronic lesions with a hyperintense rim on quantitative susceptibility mapping were identified as rim+ lesions. Susceptibility (relative to CSF) was higher in rim+ (2.42 ± 17.45 ppb) compared to rim- lesions (-14.6 ± 19.3 ppb, P < 0.0001). Among rim+ lesions, susceptibility within the rim (20.04 ± 14.28 ppb) was significantly higher compared to the core (-5.49 ± 14.44 ppb, P < 0.0001), consistent with the presence of iron. In a mixed-effects model, 11C-PK11195 uptake, representing activated microglia/macrophages, was higher in rim+ lesions compared to rim- lesions (P = 0.015). Validating our in vivo imaging results, multiple sclerosis brain slabs were imaged with quantitative susceptibility mapping and processed for immunohistochemistry. These results showed a positive translocator protein signal throughout the expansive hyperintense border of rim+ lesions, which co-localized with iron containing CD68+ microglia and macrophages. In conclusion, this study provides evidence that suggests that a hyperintense rim on quantitative susceptibility measure within a chronic lesion is a correlate for persistent inflammatory activity and that these lesions can be identified in the relapsing patients. Utilizing quantitative susceptibility measure to differentiate chronic multiple sclerosis lesion subtypes, especially chronic active lesions, would provide a method to assess the impact of these lesions on disease progression.

MRI Analysis of White Matter Myelin Water Content in Multiple Sclerosis: A Novel Approach Applied to Finding Correlates of Cortical Thinning.

A novel lesion-mask free method based on a gamma mixture model was applied to myelin water fraction (MWF) maps to estimate the association between cortical thickness and myelin content, and how it differs between relapsing-remitting (RRMS) and secondary-progressive multiple sclerosis (SPMS) groups (135 and 23 patients, respectively). It was compared to an approach based on lesion masks. The gamma mixture distribution of whole brain, white matter (WM) MWF was characterized with three variables: the mode (most frequent value) m1 of the gamma component shown to relate to lesion, the mode m2 of the component shown to be associated with normal appearing (NA) WM, and the mixing ratio (λ) between the two distributions. The lesion-mask approach relied on the mean MWF within lesion and within NAWM. A multivariate regression analysis was carried out to find the best predictors of cortical thickness for each group and for each approach. The gamma-mixture method was shown to outperform the lesion-mask approach in terms of adjusted R2, both for the RRMS and SPMS groups. The predictors of the final gamma-mixture models were found to be m1 (ß = 1.56, p < 0.005), λ (ß = -0.30, p < 0.0005) and age (ß = -0.0031, p < 0.005) for the RRMS group (adjusted R2 = 0.16), and m2 (ß = 4.72, p < 0.0005) for the SPMS group (adjusted R2 = 0.45). Further, a DICE coefficient analysis demonstrated that the lesion mask had more overlap to an ROI associated with m1, than to an ROI associated with m2 (p < 0.00001), and vice versa for the NAWM mask (p < 0.00001). These results suggest that during the relapsing phase, focal WM damage is associated with cortical thinning, yet in SPMS patients, global WM deterioration has a much stronger influence on secondary degeneration. Through these findings, we demonstrate the potential contribution of myelin loss on neuronal degeneration at different disease stages and the usefulness of our statistical reduction technique which is not affected by the typical bias associated with approaches based on lesion masks.

A transformation class for spatio-temporal survival data with a cure fraction.

We propose a hierarchical Bayesian methodology to model spatially or spatio-temporal clustered survival data with possibility of cure. A flexible continuous transformation class of survival curves indexed by a single parameter is used. This transformation model is a larger class of models containing two special cases of the well-known existing models: the proportional hazard and the proportional odds models. The survival curve is modeled as a function of a baseline cumulative distribution function, cure rates, and spatio-temporal frailties. The cure rates are modeled through a covariate link specification and the spatial frailties are specified using a conditionally autoregressive model with time-varying parameters resulting in a spatio-temporal formulation. The likelihood function is formulated assuming that the single parameter controlling the transformation is unknown and full conditional distributions are derived. A model with a non-parametric baseline cumulative distribution function is implemented and a Markov chain Monte Carlo algorithm is specified to obtain the usual posterior estimates, smoothed by regional level maps of spatio-temporal frailties and cure rates. Finally, we apply our methodology to melanoma cancer survival times for patients diagnosed in the state of New Jersey between 2000 and 2007, and with follow-up time until 2007.

Measuring longitudinal myelin water fraction in new multiple sclerosis lesions.

OBJECTIVES: Investigating the potential of myelin repair strategies in multiple sclerosis (MS) requires an understanding of myelin dynamics during lesion evolution. The objective of this study is to longitudinally measure myelin water fraction (MWF), an MRI biomarker of myelin, in new MS lesions and to identify factors that influence their subsequent myelin content. METHODS: Twenty-three MS patients were scanned with whole-brain Fast Acquisition with Spiral Trajectory and T2prep (FAST-T2) MWF mapping at baseline and median follow-up of 6 months. Eleven healthy controls (HC) confirmed the reproducibility of FAST-T2 in white matter regions of interests (ROIs) similar to a lesion size. A random-effect-model was implemented to determine the association between baseline clinical and lesion variables and the subsequent MWF. RESULTS: ROI-based measurements in HCs were highly correlated between scans [mean r = 0.893 (.764-.967)]. In MS patients, 38 gadolinium enhancing (Gd+) and 25 new non-enhancing (Gd-) T2 hyperintense lesions (5.7 months, ±3.8) were identified. Significant improvement in MWF was seen in Gd+ lesions (0.035 ± 0.029, p < 0.001) as compared to Gd- lesions (0.006 ± 0.017, p = 0.065). In the model, a higher baseline MWF (p < 0.001) and the presence of Gd (p < 0.001) were associated with higher subsequent MWF. CONCLUSIONS: FAST T2 provides a clinically feasible method to quantify MWF in new MS lesions. The observed influence of baseline MWF, which represents a combined effect of both resolving edema and myelin change within acute lesions, suggests that the extent of initial inflammation impacts final myelin recovery.

The choice of prior distribution for a covariance matrix in multivariate meta-analysis: a simulation study.

Bayesian meta-analysis is an increasingly important component of clinical research, with multivariate meta-analysis a promising tool for studies with multiple endpoints. Model assumptions, including the choice of priors, are crucial aspects of multivariate Bayesian meta-analysis (MBMA) models. In a given model, two different prior distributions can lead to different inferences about a particular parameter. A simulation study was performed in which the impact of families of prior distributions for the covariance matrix of a multivariate normal random effects MBMA model was analyzed. Inferences about effect sizes were not particularly sensitive to prior choice, but the related covariance estimates were. A few families of prior distributions with small relative biases, tight mean squared errors, and close to nominal coverage for the effect size estimates were identified. Our results demonstrate the need for sensitivity analysis and suggest some guidelines for choosing prior distributions in this class of problems. The MBMA models proposed here are illustrated in a small meta-analysis example from the periodontal field and a medium meta-analysis from the study of stroke. Copyright © 2015 John Wiley & Sons, Ltd.

CT angiography in the detection of carotid body enlargement in patients with hypertension and heart failure.

INTRODUCTION: The carotid body (CB) has previously been found to be enlarged and hyperactive in various disease states such as heart failure (HF), hypertension (HTN), and respiratory disease. Evaluation of CB size in these disease states using imaging has not been performed. The purpose of this case-control study was to compare CB sizes in patients with HF and HTN with those of controls using CT angiography. METHODS: A retrospective review was performed on 323 consecutive patients who had neck computed tomography angiography (CTA) exams in 2011. Following extensive review, 17 HF and HTN patients and 14 controls were identified. Two radiologists blinded to the patient disease status made consensus bilateral carotid body (CB) measurements on the CTA exams using a previously described standardized protocol. CB axial cross-sectional areas were compared between HF and HTN cases and controls using a paired t test. RESULTS: The right CB demonstrated a mean cross-sectional area of 2.79 mm(2) in HF and HTN patients vs. 1.40 mm(2) in controls (p = 0.02). The left CB demonstrated a mean cross-sectional area of 3.13 mm(2) in HF and HTN patients vs. 1.53 mm in controls (p = 0.03). CONCLUSION: Our results provide imaging evidence that the carotid bodies are enlarged in patients with HF and HTN. Our case-control series suggests that this enlargement can be detected on neck CTA.

Distinguishing benign and life-threatening pneumatosis intestinalis in patients with cancer by CT imaging features.

OBJECTIVE: The purpose of this study is to determine the overall proportion of clinically worrisome and benign pneumatosis intestinalis (PI) occurring in patients with cancer and to evaluate associated risk factors and CT features. MATERIALS AND METHODS: We retrospectively studied the CT examinations of 84 patients treated at our tertiary cancer center. Reviewers who were blinded to clinical data and classification analyzed PI in terms of location, pattern (linear, cystic, or both), and associated CT features, including pneumoperitoneum, portomesenteric venous air, bowel wall thickening, bowel dilatation, and ascites. On the basis of the review of clinical information and criteria derived from prior literature, the cases were classified as clinically worrisome PI (underlying bowel disease) or benign PI (diagnosis of exclusion that resolved on follow-up imaging without targeted therapy). Clinical factors reviewed included age, sex, cancer type, steroid use, and chemotherapy administration. RESULTS: Forty-seven patients were classified as having benign PI (56%) and the remainder as having clinically worrisome PI (44%). The following imaging features correlated significantly with clinically worrisome PI: bowel wall thickening (p < 0.001), mesenteric stranding (p < 0.001), ascites (p < 0.001), bowel dilatation (p = 0.004), location confined to small bowel (p = 0.012), and portomesenteric venous gas (p = 0.02). Benign PI was significantly associated with PI confined to the colon (p = 0.004). CONCLUSION: Benign PI was slightly more prevalent than clinically worrisome PI in our cohort of patients with cancer. The presence of certain CT features (mesenteric stranding, bowel wall thickening, and ascites) and the location of PI may be indicators of more significant bowel disease and, therefore, of clinically worrisome cases. There was no statistical significance achieved for nonimaging clinical factors.

Mitral apparatus assessment by delayed enhancement CMR: relative impact of infarct distribution on mitral regurgitation.

OBJECTIVES: This study sought to assess patterns and functional consequences of mitral apparatus infarction after acute myocardial infarction (AMI). BACKGROUND: The mitral apparatus contains 2 myocardial components: papillary muscles and the adjacent left ventricular (LV) wall. Delayed-enhancement cardiac magnetic resonance (DE-CMR) enables in vivo study of inter-relationships and potential contributions of LV wall and papillary muscle infarction (PMI) to mitral regurgitation (MR). METHODS: Multimodality imaging was performed: CMR was used to assess mitral geometry and infarct pattern, including 3D DE-CMR for PMI. Echocardiography was used to measure MR. Imaging occurred 27 ± 8 days after AMI (CMR, echocardiography within 1 day). RESULTS: A total of 153 patients with first AMI were studied; PMI was present in 30% (n = 46 [72% posteromedial, 39% anterolateral]). When stratified by angiographic culprit vessel, PMI occurred in 65% of patients with left circumflex, 48% with right coronary, and only 14% of patients with left anterior descending infarctions (p <0.001). Patients with PMI had more advanced remodeling as measured by LV size and mitral annular diameter (p <0.05). Increased extent of PMI was accompanied by a stepwise increase in mean infarct transmurality within regional LV segments underlying each papillary muscle (p <0.001). Prevalence of lateral wall infarction was 3-fold higher among patients with PMI compared to patients without PMI (65% vs. 22%, p <0.001). Infarct distribution also impacted MR, with greater MR among patients with lateral wall infarction (p = 0.002). Conversely, MR severity did not differ on the basis of presence (p = 0.19) or extent (p = 0.12) of PMI, or by angiographic culprit vessel. In multivariable analysis, lateral wall infarct size (odds ratio 1.20/% LV myocardium [95% confidence interval: 1.05 to 1.39], p = 0.01) was independently associated with substantial (moderate or greater) MR even after controlling for mitral annular (odds ratio 1.22/mm [1.04 to 1.43], p = 0.01), and LV end-diastolic diameter (odds ratio 1.11/mm [0.99 to 1.23], p = 0.056). CONCLUSIONS: Papillary muscle infarction is common after AMI, affecting nearly one-third of patients. Extent of PMI parallels adjacent LV wall injury, with lateral infarction-rather than PMI-associated with increased severity of post-AMI MR.

Improved left ventricular mass quantification with partial voxel interpolation: in vivo and necropsy validation of a novel cardiac MRI segmentation algorithm.

BACKGROUND: Cardiac magnetic resonance (CMR) typically quantifies LV mass (LVM) by means of manual planimetry (MP), but this approach is time-consuming and does not account for partial voxel components--myocardium admixed with blood in a single voxel. Automated segmentation (AS) can account for partial voxels, but this has not been used for LVM quantification. This study used automated CMR segmentation to test the influence of partial voxels on quantification of LVM. METHODS AND RESULTS: LVM was quantified by AS and MP in 126 consecutive patients and 10 laboratory animals undergoing CMR. AS yielded both partial voxel (AS(PV)) and full voxel (AS(FV)) measurements. Methods were independently compared with LVM quantified on echocardiography (echo) and an ex vivo standard of LVM at necropsy. AS quantified LVM in all patients, yielding a 12-fold decrease in processing time versus MP (0:21±0:04 versus 4:18±1:02 minutes; P<0.001). AS(FV) mass (136±35 g) was slightly lower than MP (139±35; Δ=3±9 g, P<0.001). Both methods yielded similar proportions of patients with LV remodeling (P=0.73) and hypertrophy (P=1.00). Regarding partial voxel segmentation, AS(PV) yielded higher LVM (159±38 g) than MP (Δ=20±10 g) and AS(FV) (Δ=23±6 g, both P<0.001), corresponding to relative increases of 14% and 17%. In multivariable analysis, magnitude of difference between AS(PV) and AS(FV) correlated with larger voxel size (partial r=0.37, P<0.001) even after controlling for LV chamber volume (r=0.28, P=0.002) and total LVM (r=0.19, P=0.03). Among patients, AS(PV) yielded better agreement with echo (Δ=20±25 g) than did AS(FV) (Δ=43±24 g) or MP (Δ=40±22 g, both P<0.001). Among laboratory animals, AS(PV) and ex vivo results were similar (Δ=1±3 g, P=0.3), whereas AS(FV) (6±3 g, P<0.001) and MP (4±5 g, P=0.02) yielded small but significant differences with LVM at necropsy. CONCLUSIONS: Automated segmentation of myocardial partial voxels yields a 14-17% increase in LVM versus full voxel segmentation, with increased differences correlated with lower spatial resolution. Partial voxel segmentation yields improved CMR agreement with echo and necropsy-verified LVM.