Reliability of cortical lesion detection on double inversion recovery MRI applying the MAGNIMS-Criteria in multiple sclerosis patients within a 16-months period

Interrater reliability for the detection of cortical lesions on phase-sensitive inversion recovery magnetic resonance imaging in patients with multiple sclerosis

Objective

To assess the reliability of phase-sensitive inversion recovery (PSIR) magnetic resonance imaging (MRI) and its accuracy for determining the topography of demyelinating cortical lesions in patients with multiple sclerosis (MS).

Materials and Methods

This was a cross-sectional study conducted at a tertiary referral center for MS and other demyelinating disorders. We assessed the agreement among three raters for the detection and topographic classification of cortical lesions on fluid-attenuated inversion recovery (FLAIR) and PSIR sequences in patients with MS.

Results

We recruited 71 patients with MS. The PSIR sequences detected 50% more lesions than did the FLAIR sequences. For detecting cortical lesions, the level of interrater agreement was satisfactory, with a mean free-response kappa (κFR) coefficient of 0.60, whereas the mean κFR for the topographic reclassification of the lesions was 0.57. On PSIR sequences, the raters reclassified 366 lesions (20% of the lesions detected on FLAIR sequences), with excellent interrater agreement. There was a significant correlation between the total number of lesions detected on PSIR sequences and the Expanded Disability Status Scale score (ρ = 0.35; p < 0.001).

Conclusion

It seems that PSIR sequences perform better than do FLAIR sequences, with clinically satisfactory interrater agreement, for the detection and topographic classification of cortical lesions. In our sample of patients with MS, the PSIR MRI findings were significantly associated with the disability status, which could influence decisions regarding the treatment of such patients.

Cortical lesions, central vein sign, and paramagnetic rim lesions in multiple sclerosis: Emerging machine learning techniques and future avenues

The current diagnostic criteria for multiple sclerosis (MS) lack specificity, and this may lead to misdiagnosis, which remains an issue in present-day clinical practice. In addition, conventional biomarkers only moderately correlate with MS disease progression. Recently, some MS lesional imaging biomarkers such as cortical lesions (CL), the central vein sign (CVS), and paramagnetic rim lesions (PRL), visible in specialized magnetic resonance imaging (MRI) sequences, have shown higher specificity in differential diagnosis. Moreover, studies have shown that CL and PRL are potential prognostic biomarkers, the former correlating with cognitive impairments and the latter with early disability progression. As machine learning-based methods have achieved extraordinary performance in the assessment of conventional imaging biomarkers, such as white matter lesion segmentation, several automated or semi-automated methods have been proposed as well for CL, PRL, and CVS. In the present review, we first introduce these MS biomarkers and their imaging methods. Subsequently, we describe the corresponding machine learning-based methods that were proposed to tackle these clinical questions, putting them into context with respect to the challenges they are facing, including non-standardized MRI protocols, limited datasets, and moderate inter-rater variability. We conclude by presenting the current limitations that prevent their broader deployment and suggesting future research directions.

Reproducibility of Lesion Count in Various Subregions on MRI Scans in Multiple Sclerosis

Purpose

Lesion number and burden can predict the long-term outcome of multiple sclerosis, while the localization of the lesions is also a good predictive marker of disease progression. These biomarkers are used in studies and in clinical practice, but the reproducibility of lesion count is not well-known.

Methods

In total, five raters evaluated T2 hyperintense lesions in 140 patients with multiple sclerosis in six localizations: periventricular, juxtacortical, deep white matter, infratentorial, spinal cord, and optic nerve. Black holes on T1-weighted images and brain atrophy were subjectively measured on a binary scale. Reproducibility was measured using the intraclass correlation coefficient (ICC). ICCs were also calculated for the four most accurate raters to see how one outlier can influence the results.

Results

Overall, moderate reproducibility (ICC 0.5-0.75) was shown, which did not improve considerably when the most divergent rater was excluded. The areas that produced the worst results were the optic nerve region (ICC: 0.118) and atrophy judgment (ICC: 0.364). Comparing high- and low-lesion burdens in each region revealed that the ICC is higher when the lesion count is in the mid-range. In the periventricular and deep white matter area, where lesions are common, higher ICC was found in patients who had a lower lesion count. On the other hand, juxtacortical lesions and black holes that are less common showed higher ICC when the subjects had more lesions. This difference was significant in the juxtacortical region when the most accurate raters compared patients with low (ICC: 0.406 CI: 0.273-0.546) and high (0.702 CI: 0.603-0.785) lesion loads.

Conclusion

Lesion classification showed high variability by location and overall moderate reproducibility. The excellent range was not achieved, owing to the fact that some areas showed poor performance. Hence, putting effort toward the development of artificial intelligence for the evaluation of lesion burden should be considered.

Genetic diseases mimicking multiple sclerosis

Multiple sclerosis (MS) is an inflammatory neurodegenerative disorder manifesting as gradual or progressive loss of neurological functions. Most patients present with relapsing-remitting disease courses. Extensive research over recent decades has expounded our insights into the presentations and diagnostic features of MS. Groups of genetic diseases, CADASIL and leukodystrophies, for example, have been frequently misdiagnosed with MS due to some overlapping clinical and radiological features. The delayed identification of these diseases in late adulthood can lead to severe neurological complications. Herein we discuss genetic diseases that have the potential to mimic multiple sclerosis, with highlights on clinical identification and practicing pearls that may aid physicians in recognizing MS-mimics with genetic background in clinical settings.

Navigator-Guided Motion and B0 Correction of T2*-Weighted Magnetic Resonance Imaging Improves Multiple Sclerosis Cortical Lesion Detection

BACKGROUND

Cortical lesions are common in multiple sclerosis (MS). T2*-weighted (T2*w) imaging at 7 T is relatively sensitive for cortical lesions, but quality is often compromised by motion and main magnetic field (B0) fluctuations.

PURPOSE

The aim of this study was to determine whether motion and B0 correction with a navigator-guided gradient-recalled echo sequence can improve cortical lesion detection in T2*w magnetic resonance imaging.

MATERIALS AND METHODS

In this prospective study, a gradient-recalled echo sequence incorporating a navigator allowing for motion and B0 field correction was applied to collect T2*w images at 7 T from adults with MS between August 2019 and March 2020. T2*-weighted images were acquired in 1 to 3 partially overlapping scans per individual and were reconstructed using global average B0 correction ("uncorrected") or motion correction and spatially linear B0 correction ("corrected"). Image quality rating and manual segmentation of cortical lesions were performed on uncorrected and corrected images. Lesions seen on a single scan were retrospectively evaluated on the complementary scan. The association of cortical lesions with clinical disability was assessed. Mixed models were used to determine the effect of correction on lesion detection as well as on the relationship between disability and lesion count.

RESULTS

A total of 22 T2*w scans were performed on 11 adults with MS (mean [SD] age, 49 [11] years; 8 women). Quality improved for 20 of 22 scans (91%) after correction. A total of 69 cortical lesions were identified on uncorrected images (median per scan, 2; range, 0-11) versus 148 on corrected images (median per scan, 4.5; range, 0-25; rate ratio [RR], 2.1; P < 0.0001). For low-quality uncorrected scans with moderate to severe motion artifact (18/22, 82%), there was an improvement in cortical lesion detection with correction (RR, 2.5; P < 0.0001), whereas there was no significant change in cortical lesion detection for high-quality scans (RR, 1.3; P = 0.43).

CONCLUSIONS

Navigator-guided motion and B0 correction substantially improves the overall image quality of T2*w magnetic resonance imaging at 7 T and increases its sensitivity for cortical lesions.

Cognitive performance shows domain specific associations with regional cortical thickness in multiple sclerosis

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Cognitive impairment correlates with loss of cortical thickness in MS.

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Cognitive tests show distinctive regional associations with cortical thickness.

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Some regions, such as the left insula, correlate with multiple tests.

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Associations patterns seem reproducible in patients with very mild impairment.

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Better localization of cognitive functions may improve future MRI studies.

Multiple Sclerosis (MS) patients often suffer from significant cognitive impairment. Earlier research has shown relationships between regional cortical atrophy and cognitive deterioration. However, due to a large number of neuropsychological assessments and a heterogenous pattern of cognitive deficits in MS patients, reported associations patterns are also heterogenous. Using an extensive neuropsychological battery of 23 different tasks, we explored domain (attention/information processing, memory, spatial processing, executive functioning) and task-specific associations with regional cortical thickness in a representative sample of MS patients (N = 97). Cortical regions associated with multiple cognitive tasks in the left hemisphere were predominantly located in the inferior insula (attention p < 0.001, memory p = 0.047, spatial processing p = 0.004, executive functioning p = 0.037), the gyrus frontalis superior (attention p = 0.015, memory p = 0.037, spatial processing p = 0.033, executive functioning p = 0.017) and temporal medial (attention p < 0.001, memory two clusters p = 0.016 and p < 0.001, executive functioning p = 0.016). In the right hemisphere, we detected the strongest association in the sulcus interparietalis with five cluster (attention SDMT p = 0.003 and TAP_DA p < 0.001; memory Rey recall p = 0.013 and VLMT verbal learning p = 0.016; spatial processing Rey copy p < 0.001). We replicated parts of our results in an independent sample of 30 mildly disabled MS patients. Moreover, comparisons to 29 healthy controls showed that the regional associations seemed to represent rather pathophysiological dependency than a physiological one. We believe that our results may prove useful in diagnosis and rehabilitation of cognitive impairments and may serve as guidance in future magnetic resonance imaging (MRI) studies.

Comparative study between double inversion recovery (DIR) and fluid-attenuated inversion recovery (FLAIR) MRI sequences for detection of cerebral lesions in multiple sclerosis

Background

Multiple sclerosis (MS) is a common chronic inflammatory demyelinating disorder more common in young adults. MS is characterized mainly with white matter (WM) affection; however, considerable gray matter (GM) involvement is also noted in many patients. MRI is used for diagnosis and follow up of the disease using different pulse sequences; FLAIR imaging provides the highest sensitivity in the detection of supratentorial, juxtacortical, and the periventricular lesions but is less sensitive in the posterior fossa. A double inversion recovery (DIR) pulse sequence was recently introduced to improve the visibility of GM lesions and especially cortical lesions. The aim of this study is to assess the role of DIR sequence in the detection of brain lesions in patients with MS compared to FLAIR sequence.

Results

DIR showed a significantly higher number of MS lesions in infratentorial region (2.9 ± 0.4 compared to 2.25 ± 0.3 in FLAIR) with a statistically significant difference (p = 0.002) and also in supratentorial periventricular regions (11.84 ± 8.07 in DIR and 11.31 ± 8.07 in FLAIR, p < 0.001). DIR imaging also demonstrated significantly more intracortical lesions (7.12 ± 1.2 compared to 1.4 ± 0.9 in FLAIR imaging) with a statistically significant difference (p < 0.001). On the other hand, corpus callosum lesions were significantly higher on FLAIR (0.84 ± 0.1) with respect to DIR imaging (0.68 ± 0.1) with a statistically significant difference in between (p = 0.025).

Conclusion

DIR is a powerful conventional MRI sequence for visualization of brain lesions in patients with MS and is superior to FLAIR sequence in detecting lesions in different locations, namely cortical, periventricular, and infratentorial regions; hence, DIR can be added to the MRI protocol of MS patients or even can replace FLAIR which would be of a good diagnostic value with only 80 s added to the scan time.

Development of Cortical Lesion Volumes on Double Inversion Recovery MRI in Patients With Relapse-Onset Multiple Sclerosis

Background and Objective: In multiple sclerosis (MS) patients, Double Inversion Recovery (DIR) magnetic resonance imaging (MRI) can be used to detect cortical lesions (CL). While the quantity and distribution of CLs seems to be associated with patients' disease course, literature lacks frequent assessments of CL volumes (CL-V) in this context. We investigated the reliability of DIR for the longitudinal assessment of CL-V development with frequent follow-up MRIs and examined the course of CL-V progressions in relation to white-matter lesions (WML), contrast enhancing lesions (CEL) and clinical parameters in patients with Relapsing-Remitting Multiple Sclerosis (RRMS).

Methods: In this post-hoc analysis, image- and clinical data of a subset of 24 subjects that were part of a phase IIa clinical trial on the “Safety, Tolerability and Mechanisms of Action of Boswellic Acids in Multiple Sclerosis (SABA)” (ClinicalTrials.gov, NCT01450124) were included. The study was divided in three phases (screening, treatment, study-end). All patients received 12 MRI follow-up-examinations (including DIR) during a 16-months period. CL-Vs were assessed for each patient on each follow-up MRI separately by two experienced neuroradiologists. Results of neurological screening tests, as well as other MRI parameters (WML number and volume and CELs) were included from the SABA investigation data.

Results: Inter-rater agreement regarding CL-V assessment over time was good-to-excellent (κ = 0.89). Mean intraobserver variability was 1.1%. In all patients, a total number of 218 CLs was found. Total CL-Vs of all patients increased during the 4 months of baseline screening followed by a continuous and significant decrease from month 5 until study-end (p < 0.001, Kendall'W = 0.413). A positive association between WML volumes and CL-Vs was observed during baseline screening. Decreased CL-V were associated with lower EDSS and also with improvements of SDMT- and SCRIPPS scores.

Conclusion: DIR MRI seems to be a reliable tool for the frequent assessment of CL-Vs. Overall CL-Vs decreased during the follow-up period and were associated with improvements of cognitive and disability status scores. Our results suggest the presence of short-term CL-V dynamics in RRMS patients and we presume that the laborious evaluation of lesion volumes may be worthwhile for future investigations.

Clinical Trial Numbers:www.ClinicalTrials.gov, “The SABA trial”; number: NCT01450124

3D double inversion recovery MR imaging: Clinical applications and usefulness in a wide spectrum of central nervous system diseases

Double inversion recovery (DIR) imaging provides two inversion pulses that attenuate signals from cerebrospinal fluid and normal white matter. This review was undertaken to describe the principle of the DIR sequence, the clinical applications of 3D DIR in various central nervous system diseases and the clinical benefits of the 3D DIR compared with those of other MR sequences. 3D DIR imaging provides better lesion conspicuity and topography than other MR techniques. It is particularly useful for diagnosing the following disease entities: cortical and subcortical abnormalities such as multiple sclerosis, cortical microinfarcts and cortical development anomalies; sulcal abnormalities such as meningitis and subacute/chronic subarachnoid hemorrhage; and optic neuritis caused by multiple sclerosis or neuromyelitis optica.

Neuroimaging Techniques to Assess Inflammation in Multiple Sclerosis

Multiple Sclerosis (MS) is a chronic neurological disease that represents a leading cause of disability in young adults and is characterized by inflammation and degeneration of both white matter (WM) and gray matter (GM). Defining the presence or absence of inflammation on individual basis is a key point in choosing the therapy and monitoring the treatment response. Magnetic resonance imaging (MRI) represents the most sensitive non-invasive tool to monitor inflammation in the clinical practice. Indeed, in the early phase of inflammation MRI detects new lesions as extrusion of gadolinium contrast agents across the altered blood-brain-barrier (BBB). The occurrence of MRI lesions is used to confirm diagnosis and has been validated as surrogate marker of relapse to monitor response to treatments. However, focal gadolinium-enhancing lesions represent only an aspect of neuroinflammation. Recent studies have suggested the presence of a widespread inflammation of the central nervous system (CNS), which is mainly related to microglial cells activation occurring both at the edge of chronic focal lesions and throughout the normal-appearing brain tissue. New imaging techniques have been developed to study diffuse inflammation taking place outside the focal plaques. The scope of this review is to examine the various neuroimaging techniques and those biophysical quantities that can be non-invasively detected to enlighten the different aspects of neuroinflammation. Some techniques are commonly used in the clinical practice, while others are used in the research field to better understand the pathophysiological mechanisms of the disease and the role of inflammation.