Age-related decline in cerebral oxygen consumption in multiple sclerosis.

Cerebral oxygen metabolism is altered in relapsing-remitting multiple sclerosis (RRMS), possibly a result of disease related cerebral atrophy with subsequent decreased oxygen demand. However, MS inflammation can also inhibit brain metabolism. Therefore, we measured cerebral blood flow (CBF) and cerebral metabolic rate of oxygen (CMRO2) using MRI phase contrast mapping and susceptibility-based oximetry in 44 patients with early RRMS and 36 healthy controls. Cerebral atrophy and white matter lesion load were assessed from high-resolution structural MRI. Expanded Disability Status Scale (EDSS) scores were collected from medical records. The CMRO2 was significantly lower in patients (-15%, p = 0.002) and decreased significantly with age in patients relative to the controls (-1.35 µmol/100 g/min/year, p = 0.036). The lower CMRO2 in RRMS was primarily driven by a higher venous oxygen saturation in the sagittal sinus (p = 0.007) and not a reduction in CBF (p = 0.69). There was no difference in cerebral atrophy between the groups, and no correlation between CMRO2 and MS lesion volume or EDSS score. Therefore, the progressive CMRO2 decline observed before the occurrence of significant cerebral atrophy and despite adequate CBF supports emerging evidence of dysfunctional cellular respiration as a potential pathogenic mechanism and therapeutic target in RRMS.

Scanner agnostic large-scale evaluation of MS lesion delineation tool for clinical MRI.

Introduction: Patients with MS are MRI scanned continuously throughout their disease course resulting in a large manual workload for radiologists which includes lesion detection and size estimation. Though many models for automatic lesion segmentation have been published, few are used broadly in clinic today, as there is a lack of testing on clinical datasets. By collecting a large, heterogeneous training dataset directly from our MS clinic we aim to present a model which is robust to different scanner protocols and artefacts and which only uses MRI modalities present in routine clinical examinations. Methods: We retrospectively included 746 patients from routine examinations at our MS clinic. The inclusion criteria included acquisition at one of seven different scanners and an MRI protocol including 2D or 3D T2-w FLAIR, T2-w and T1-w images. Reference lesion masks on the training (n = 571) and validation (n = 70) datasets were generated using a preliminary segmentation model and subsequent manual correction. The test dataset (n = 100) was manually delineated. Our segmentation model https://github.com/CAAI/AIMS/ was based on the popular nnU-Net, which has won several biomedical segmentation challenges. We tested our model against the published segmentation models HD-MS-Lesions, which is also based on nnU-Net, trained with a more homogenous patient cohort. We furthermore tested model robustness to data from unseen scanners by performing a leave-one-scanner-out experiment. Results: We found that our model was able to segment MS white matter lesions with a performance comparable to literature: DSC = 0.68, precision = 0.90, recall = 0.70, f1 = 0.78. Furthermore, the model outperformed HD-MS-Lesions in all metrics except precision = 0.96. In the leave-one-scanner-out experiment there was no significant change in performance (p < 0.05) between any of the models which were only trained on part of the dataset and the full segmentation model. Conclusion: In conclusion we have seen, that by including a large, heterogeneous dataset emulating clinical reality, we have trained a segmentation model which maintains a high segmentation performance while being robust to data from unseen scanners. This broadens the applicability of the model in clinic and paves the way for clinical implementation.

Delineation of Grade II and III Gliomas Investigated by 7T MRI: An Inter-Observer Pilot Study.

PURPOSE: Diffuse low-grade gliomas (DLGGs) are low-malignancy brain tumors originating from the glial cells of the brain growing continuously and infiltratively along the neural axons and infiltrating the surrounding brain tissue. DLGGs usually transform into higher malignancy, causing progressive disability and premature death. MRI scans are valuable when assessing soft tissue abnormalities, but, due to the infiltrative properties of DLGGs, delineating the tumor borders is a challenging task. Therefore, the aim of this study was to explore the difference in gross tumor volume (GTV) of DLGGs delineated from 7 Tesla and 3 Tesla MRI scans. METHOD: Patients were recruited at the department of neurosurgery and were scanned in both a 7T and a 3T MRI scanner prior to the operation. Two observers delineated the tumors using semi-automatic delineation software. The results from each observer were blinded to the other observer's delineation. RESULTS: Comparing GTVs from 7T and 3T, the percentage difference varied up to 40.4% on the T2-weighted images. The percentage difference in GTV varied up to 15.3% on the fluid-attenuated inversion recovery (FLAIR) images. On the T2-weighted images, most cases varied by approximately 15%; on the FLAIR sequence, half of the cases varied by approximately 5% and the other half by approximately 15%. The overall inter-observer agreement was near perfect, with an intraclass correlation of 0.969. The intraclass correlation was better on the FLAIR sequence than on the T2 sequence. CONCLUSION: Overall, the GTVs delineated from 7T images were smaller. The increase in field strength improved the inter-observer agreement only on the FLAIR sequence.

Reproducibility and Optimal Arterial Input Function Selection in Dynamic Contrast-Enhanced Perfusion MRI in the Healthy Brain.

BACKGROUND: Dynamic contrast-enhanced MRI (DCE-MRI) has seen increasing use for quantification of low level of blood-brain barrier (BBB) leakage in various pathological disease states and correlations with clinical outcomes. However, currently there exists limited studies on reproducibility in healthy controls, which is important for the establishment of a normality threshold for future research. PURPOSE: To investigate the reproducibility of DCE-MRI and to evaluate the effect of arterial input function (AIF) selection and manual region of interests (ROI) delineation vs. automated global segmentation. STUDY TYPE: Prospective. POPULATION: A total of 16 healthy controls; 11 females; mean age 28.7 years (SD 10.1). FIELD STRENGTH/SEQUENCE: A 3T; GE DCE; 3D TFE T1WI. 2D TSE T2. ASSESSMENT: The influx constant Ki , a measure of BBB permeability, and Vp , the blood plasma volume, was calculated using the Patlak model. Cerebral blood flow (CBF) was calculated using Tikhonov model free deconvolution. Manual tissue ROIs, drawn by H.J.S. (30+ years of experience), were compared to automatic tissue segmentation. STATISTICAL TESTS: Intraclass correlation coefficient (ICC) and repeatability coefficient (RC) was used to assess reproducibility. Bland-Altman plots were used to evaluate agreement between measurements day 1 vs. day 2, and manual vs. segmentation method. RESULTS: Ki showed excellent reproducibility in both white and gray matter with an ICC between 0.79 and 0.82 and excellent agreement between manual ROI and automatic segmentation, with an ICC of 0.89 for Ki in WM. Furthermore, Ki values in gray and white matter conforms with histological tissue characteristics, where gray matter generally has a 2-fold higher vessel density. The highest reproducibility measures of Ki (ICC = 0.83), CBF (ICC = 0.77) and Vd (ICC = 0.83) was obtained with the AIF sampled in the internal carotid artery (ICA). DATA CONCLUSION: DCE-MRI shows excellent reproducibility of pharmacokinetic variables derived from healthy controls. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Blood-brain barrier permeability changes in the first year after alemtuzumab treatment predict 2-year outcomes in relapsing-remitting multiple sclerosis.

BACKGROUND: In relapsing-remitting multiple sclerosis (RRMS), early disease control reduces the risk of permanent disability. The blood-brain barrier (BBB) is compromised in MS, and its permeability is a potential biomarker. OBJECTIVE: To investigate BBB permeability measured by MRI as a marker of alemtuzumab efficacy. METHODS: Patients with RRMS initiating alemtuzumab treatment were recruited prospectively. BBB permeability was assessed as the Patlak-derived influx constant (Ki) by dynamic contrast-enhanced MRI before and 6, 12, and 18 months after the first course of alemtuzumab. No Evidence of Disease Activity-3 (NEDA-3) status was ascertained two years after treatment initiation. RESULTS: Patients who maintained NEDA-3 status at two years (n = 7) had a larger decrease in Ki between baseline and six months (-0.029 ml/100 g/min [CI -0.005 - -0.053]) and between baseline and 12 months in normal appearing white matter (0.043 [CI 0.022 - -0.065]), than those who experienced disease activity (n = 8). ROC curve analysis of the Ki change between baseline and 12 months in NAWM predicted a loss of NEDA status at 2 years with 86% sensitivity and 86% specificity (AUC 0.98, p = 0.002). CONCLUSION: BBB permeability predicted alemtuzumab efficacy at two years, indicating that BBB permeability is a biomarker of treatment response in RRMS.

Assessment of Artificial Intelligence Automatic Multiple Sclerosis Lesion Delineation Tool for Clinical Use.

PURPOSE: To implement and validate an existing algorithm for automatic delineation of white matter lesions on magnetic resonance imaging (MRI) in patients with multiple sclerosis (MS) on a local single-center dataset. METHODS: We implemented a white matter hyperintensity segmentation model, based on a 2D convolutional neural network, using the conventional T2-weighted fluid attenuated inversion recovery (FLAIR) MRI sequence as input. The model was adapted for delineation of MS lesions by further training on a local dataset of 93 MS patients with a total of 3040 lesions. A quantitative evaluation was performed on ten test patients, in which model-generated masks were compared to manually delineated masks from two expert delineators. A subsequent qualitative evaluation of the implemented model was performed by two expert delineators, in which generated delineation masks on a clinical dataset of 53 patients were rated acceptable (< 10% errors) or unacceptable (> 10% errors) based on the total number of true lesions. RESULTS: The quantitative evaluation resulted in an average accuracy score (F1) of 0.71, recall of 0.77 and dice similarity coefficient of 0.62. Our implemented model obtained the highest scores in all three metrics, when compared to three out of the box lesion segmentation models. In the clinical evaluation an average of 94% of our 53 model-generated masks were rated acceptable. CONCLUSION: After adaptation to our local dataset, the implemented segmentation model was able to delineate MS lesions with a high clinical value as rated by delineation experts while outperforming popular out of the box applications. This serves as a promising step towards implementation of automatic lesion delineation in our MS clinic.

Permeability of the blood-brain barrier predicts no evidence of disease activity at 2 years after natalizumab or fingolimod treatment in relapsing-remitting multiple sclerosis.

OBJECTIVE: To investigate whether blood-brain barrier (BBB) permeability, as measured by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), can provide early detection of suboptimal treatment response in relapsing-remitting multiple sclerosis (RRMS). METHODS: Thirty-five RRMS patients starting on fingolimod or natalizumab, drugs with a common effect of decreasing lymphocyte influx into the central nervous system, were scanned with DCE-MRI at 3T prior to treatment and at 3 and 6 months posttreatment. We calculated the influx constant Ki , a measure of BBB permeability, using the Patlak model. Suboptimal treatment response was defined as loss of no evidence of disease activity (NEDA) status after 2 years of treatment. RESULTS: Subjects with loss of NEDA status at 2 years had a 51% higher mean Ki in normal-appearing white matter (NAWM) measured after 6 months of treatment, compared to subjects with maintained NEDA status (mean difference = 0.06ml/100g/min, 95% confidence interval [CI] = 0.02-0.09, p = 0.002). Ki in NAWM at 6 months was a good predictor of loss of NEDA status at 2 years (area under the curve = 0.84, 95% CI = 0.70-0.99, p = 0.003), and a value above 0.136ml/100/g/min yielded an odds ratio of 12.4 for suboptimal treatment response at 2 years, with a sensitivity of 73% and a specificity of 82%. INTERPRETATION: Our results suggest that BBB permeability as measured by DCE-MRI reliably predicts suboptimal treatment response and is a surrogate marker of the state of health of the BBB. We find a predictive threshold for disease activity, which is remarkably identical in clinically isolated syndrome as previously reported and established RRMS as investigated here. Ann Neurol 2018;83:902-914.

Permeability of the blood-brain barrier predicts conversion from optic neuritis to multiple sclerosis.

Optic neuritis is an acute inflammatory condition that is highly associated with multiple sclerosis. Currently, the best predictor of future development of multiple sclerosis is the number of T2 lesions visualized by magnetic resonance imaging. Previous research has found abnormalities in the permeability of the blood-brain barrier in normal-appearing white matter of patients with multiple sclerosis and here, for the first time, we present a study on the capability of blood-brain barrier permeability in predicting conversion from optic neuritis to multiple sclerosis and a direct comparison with cerebrospinal fluid markers of inflammation, cellular trafficking and blood-brain barrier breakdown. To this end, we applied dynamic contrast-enhanced magnetic resonance imaging at 3 T to measure blood-brain barrier permeability in 39 patients with monosymptomatic optic neuritis, all referred for imaging as part of the diagnostic work-up at time of diagnosis. Eighteen healthy controls were included for comparison. Patients had magnetic resonance imaging and lumbar puncture performed within 4 weeks of onset of optic neuritis. Information on multiple sclerosis conversion was acquired from hospital records 2 years after optic neuritis onset. Logistic regression analysis showed that baseline permeability in normal-appearing white matter significantly improved prediction of multiple sclerosis conversion (according to the 2010 revised McDonald diagnostic criteria) within 2 years compared to T2 lesion count alone. There was no correlation between permeability and T2 lesion count. An increase in permeability in normal-appearing white matter of 0.1 ml/100 g/min increased the risk of multiple sclerosis 8.5 times whereas having more than nine T2 lesions increased the risk 52.6 times. Receiver operating characteristic curve analysis of permeability in normal-appearing white matter gave a cut-off of 0.13 ml/100 g/min, which predicted conversion to multiple sclerosis with a sensitivity of 88% and specificity of 72%. We found a significant correlation between permeability and the leucocyte count in cerebrospinal fluid as well as levels of CXCL10 and MMP9 in the cerebrospinal fluid. These findings suggest that blood-brain barrier permeability, as measured by magnetic resonance imaging, may provide novel pathological information as a marker of neuroinflammation related to multiple sclerosis, to some extent reflecting cellular permeability of the blood-brain barrier, whereas T2 lesion count may more reflect the length of the subclinical pre-relapse phase.See Naismith and Cross (doi:10.1093/brain/awv196) for a scientific commentary on this article.

Study of medication-free children with Tourette syndrome do not show imaging abnormalities.

BACKGROUND: Imaging studies of patients with Tourette's syndrome (TS) across different cohorts have shown alterations in gray and white matter in areas associated with the cortico-striato-thalamic-cortical (CSTC) pathways; however, no consistent findings have subsequently established a clear indication of the pathophysiology of TS. METHODS: This study was designed to investigate changes in gray and white matter in medication-free children with TS in the CSTC areas. With MRI, 24 children with TS and 18 healthy controls were analyzed using three complementary methods. RESULTS AND CONCLUSION: Analyses revealed no differences between controls and patients with TS in gray or white matter. Possible discrepancies between cohorts and methods may play a role in the different findings in other studies. Further studies investigating well-defined cohorts with TS analyzing both gray and white matter in the same cohort may add additional information to the pathophysiology of TS.

Evaluation of dynamic contrast-enhanced T1-weighted perfusion MRI in the differentiation of tumor recurrence from radiation necrosis.

INTRODUCTION: To investigate if perfusion measured with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can be used to differentiate radiation necrosis from tumor recurrence in patients with high-grade glioma. METHODS: The study was approved by the institutional review board and informed consent was obtained from all subjects. 19 patients were recruited following surgery and radiation therapy for glioma. Patients had contrast enhancing lesions, which during the standard MRI examination could not be exclusively determined as recurrence or radiation necrosis. DCE-MRI was used to measure cerebral blood volume (CBV), blood-brain barrier (BBB) permeability and cerebral blood flow (CBF). Subjects also underwent FDG-PET and lesions were classified as either metabolically active or inactive. Follow-up clinical MRI and lesion histology in case of additional tissue resection was used to determine whether lesions were regressing or progressing. RESULTS: Fourteen enhancing lesions could be classified as progressing (11) or regressing (three). An empirical threshold of 2.0 ml/100 g for CBV allowed detection of regressing lesions with a sensitivity of 100 % and specificity of 100 %. FDG-PET and DCE-MRI agreed in classification of tumor status in 13 out of the 16 cases where an FDG-PET classification was obtained. In two of the remaining three patients, MRI follow-up and histology was available and both indicated that the DCE-MRI answer was correct. CONCLUSION: CBV measurements using DCE-MRI may predict the status of contrast enhancing lesions and give results very similar to FDG-PET with regards to differentiation between tumor recurrence and radiation necrosis.

In vivo study of experimental pneumococcal meningitis using magnetic resonance imaging.

BACKGROUND: Magnetic Resonance Imaging (MRI) methods were evaluated as a tool for the study of experimental meningitis. The identification and characterisation of pathophysiological parameters that vary during the course of the disease could be used as markers for future studies of new treatment strategies. METHODS: Rats infected intracisternally with S. pneumoniae (n = 29) or saline (n = 13) were randomized for imaging at 6, 12, 24, 30, 36, 42 or 48 hours after infection. T1W, T2W, quantitative diffusion, and post contrast T1W images were acquired at 4.7 T. Dynamic MRI (dMRI) was used to evaluate blood-brain-barrier (BBB) permeability and to obtain a measure of cerebral and muscle perfusion. Clinical- and motor scores, bacterial counts in CSF and blood, and WBC counts in CSF were measured. RESULTS: MR images and dMRI revealed the development of a highly significant increase in BBB permeability (P < 0.002) and ventricle size (P < 0.0001) among infected rats. Clinical disease severity was closely related to ventricle expansion (P = 0.024). Changes in brain water distribution, assessed by ADC, and categorization of brain 'perfusion' by cortex DeltaSI(bolus) were subject to increased inter-rat variation as the disease progressed, but without overall differences compared to uninfected rats (P > 0.05). Areas of well-'perfused' muscle decreased with the progression of infection indicative of septicaemia (P = 0.05). CONCLUSION: The evolution of bacterial meningitis was successfully followed in-vivo with MRI. Increasing BBB-breakdown and ventricle size was observed in rats with meningitis whereas changes in brain water distribution were heterogeneous. MRI will be a valuable technique for future studies aiming at evaluating or optimizing adjunctive treatments.

Corticospinal tract degeneration and possible pathogenesis in ALS evaluated by MR diffusion tensor imaging.

BACKGROUND: MR diffusion tensor imaging (DTI) appears to be a powerful method to investigate the neuronal and axonal fibre distribution in the human brain. Changes in diffusion characteristics of water molecules in the white matter can be estimated as the apparent diffusion coefficient (ADC) and the fractional anisotropy index (FA). OBJECTIVES: To characterize DTI changes at three different levels in the corticospinal tract (CST) (corona radiata, internal capsule and pons) in order to elucidate if pathogenesis of ALS is due to an anterograde or retrograde axonal degeneration. METHODS: We studied eight ALS patients with clinical signs of upper motor neuron involvement. The patients were compared with 11 healthy age-matched controls. RESULTS: ADC was significantly increased in the CST in ALS patients at the level of the internal capsule and also increased in the pons, but without statistical significance. ADC was unchanged at the level of the corona radiata. FA was significantly reduced at the lowest level (pons), only tended to be reduced in the internal capsule, but was also unchanged in the corona radiata. CONCLUSIONS: Segmentation of the CST into three regions supports the hypothesis of a 'dying back' mechanism in ALS and suggests that ADC is a more sensitive measure than FA to detect pathological changes in ALS.