Accuracy of Unenhanced MRI in the Detection of New Brain Lesions in Multiple Sclerosis

Treatment Monitoring in Multiple Sclerosis - Efficacy and Safety

Magnetic resonance imaging is the most sensitive method for detecting inflammatory activity in multiple sclerosis, particularly in the brain where it reveals subclinical inflammation. Established MRI markers include contrast-enhancing lesions and active T2 lesions. Recent promising markers like slowly expanding lesions and phase rim lesions are being explored for monitoring chronic inflammation, but require further validation for clinical use. Volumetric and quantitative MRI techniques are currently limited to clinical trials and are not yet recommended for routine clinical use. Additionally, MRI is crucial for detecting complications from disease-modifying treatments and for implementing MRI-based pharmacovigilance strategies, such as in patients treated with natalizumab.

Real-World Validation of Coregistration and Structured Reporting for Magnetic Resonance Imaging Monitoring in Multiple Sclerosis

OBJECTIVE

The objectives of this research were to assess the effectiveness of computer-assisted detection reading (CADR) and structured reports in monitoring patients with multiple sclerosis (MS) and to evaluate the role of radiology technicians in this context.

METHODS

Eighty-seven patients with MS who underwent at least 2 sequential magnetic resonance imaging (MRI) follow-ups analyzed by 2 radiologists and a technician. Progression of disease (POD) was identified through the emergence of T2 fluid-attenuated inversion recovery white matter hyperintensities or contrast enhancements and evaluated both qualitatively (progression vs stability) and quantitatively (count of new white matter hyperintensities).

RESULTS

CADR increased the accuracy by 11%, enhancing interobserver consensus on qualitative progression and saving approximately 2 minutes per examination. Although structured reports did not improve these metrics, it may improve clinical communication and permit technicians to achieve approximately 80% accuracy in MRI readings.

CONCLUSIONS

The use of CADR improves the accuracy, agreement, and interpretation time in MRI follow-ups of MS. With the help of computer tools, radiology technicians could represent a significant aid in the follow-up of these patients.

Multiple Sclerosis: Clinical Update and Clinically-Oriented Radiologic Reporting

Multiple sclerosis (MS) is a chronic inflammatory disease of the nervous system. MR imaging findings play an integral part in establishing diagnostic hallmarks of the disease during initial diagnosis and evaluating disease status. Multiple iterations of diagnostic criteria and consensus guidelines are put forth by various expert groups incorporating imaging of the brain and spine, and efforts have been made to standardize imaging protocols for MS. Emerging ancillary imaging findings have also attracted increasing interests and should be sought for on radiologic examination. In this paper, the authors review the clinical guidelines and approach to imaging of MS and related disorders, focusing on clinically impactful image interpretation and MR imaging reporting.

Prospective study validating a multidimensional treatment decision score predicting the 24-month outcome in untreated patients with clinically isolated syndrome and early relapsing-remitting multiple sclerosis, the ProVal-MS study

INTRODUCTION

In Multiple Sclerosis (MS), patients´ characteristics and (bio)markers that reliably predict the individual disease prognosis at disease onset are lacking. Cohort studies allow a close follow-up of MS histories and a thorough phenotyping of patients. Therefore, a multicenter cohort study was initiated to implement a wide spectrum of data and (bio)markers in newly diagnosed patients.

METHODS

ProVal-MS (Prospective study to validate a multidimensional decision score that predicts treatment outcome at 24 months in untreated patients with clinically isolated syndrome or early Relapsing-Remitting-MS) is a prospective cohort study in patients with clinically isolated syndrome (CIS) or Relapsing-Remitting (RR)-MS (McDonald 2017 criteria), diagnosed within the last two years, conducted at five academic centers in Southern Germany. The collection of clinical, laboratory, imaging, and paraclinical data as well as biosamples is harmonized across centers. The primary goal is to validate (discrimination and calibration) the previously published DIFUTURE MS-Treatment Decision score (MS-TDS). The score supports clinical decision-making regarding the options of early (within 6 months after study baseline) platform medication (Interferon beta, glatiramer acetate, dimethyl/diroximel fumarate, teriflunomide), or no immediate treatment (> 6 months after baseline) of patients with early RR-MS and CIS by predicting the probability of new or enlarging lesions in cerebral magnetic resonance images (MRIs) between 6 and 24 months. Further objectives are refining the MS-TDS score and providing data to identify new markers reflecting disease course and severity. The project also provides a technical evaluation of the ProVal-MS cohort within the IT-infrastructure of the DIFUTURE consortium (Data Integration for Future Medicine) and assesses the efficacy of the data sharing techniques developed.

PERSPECTIVE

Clinical cohorts provide the infrastructure to discover and to validate relevant disease-specific findings. A successful validation of the MS-TDS will add a new clinical decision tool to the armamentarium of practicing MS neurologists from which newly diagnosed MS patients may take advantage. Trial registration ProVal-MS has been registered in the German Clinical Trials Register, `Deutsches Register Klinischer Studien` (DRKS)-ID: DRKS00014034, date of registration: 21 December 2018; https://drks.de/search/en/trial/DRKS00014034.

Evaluation of the quality and the productivity of neuroradiological reading of multiple sclerosis follow-up MRI scans using an intelligent automation software

PURPOSE

The assessment of multiple sclerosis (MS) lesions on follow-up magnetic resonance imaging (MRI) is tedious, time-consuming, and error-prone. Automation of low-level tasks could enhance the radiologist in this work. We evaluate the intelligent automation software Jazz in a blinded three centers study, for the assessment of new, slowly expanding, and contrast-enhancing MS lesions.

METHODS

In three separate centers, 117 MS follow-up MRIs were blindly analyzed on fluid attenuated inversion recovery (FLAIR), pre- and post-gadolinium T1-weighted images using Jazz by 2 neuroradiologists in each center. The reading time was recorded. The ground truth was defined in a second reading by side-by-side comparison of both reports from Jazz and the standard clinical report. The number of described new, slowly expanding, and contrast-enhancing lesions described with Jazz was compared to the lesions described in the standard clinical report.

RESULTS

A total of 96 new lesions from 41 patients and 162 slowly expanding lesions (SELs) from 61 patients were described in the ground truth reading. A significantly larger number of new lesions were described using Jazz compared to the standard clinical report (63 versus 24). No SELs were reported in the standard clinical report, while 95 SELs were reported on average using Jazz. A total of 4 new contrast-enhancing lesions were found in all reports. The reading with Jazz was very time efficient, taking on average 2min33s ± 1min0s per case. Overall inter-reader agreement for new lesions between the readers using Jazz was moderate for new lesions (Cohen kappa = 0.5) and slight for SELs (0.08).

CONCLUSION

The quality and the productivity of neuroradiological reading of MS follow-up MRI scans can be significantly improved using the dedicated software Jazz.

Review of strategies to reduce the contamination of the water environment by gadolinium-based contrast agents

Gadolinium-based contrast agents (GBCA) are essential for diagnostic MRI examinations. GBCA are only used in small quantities on a per-patient basis; however, the acquisition of contrast-enhanced MRI examinations worldwide results in the use of many thousands of litres of GBCA per year. Data shows that these GBCA are present in sewage water, surface water, and drinking water in many regions of the world. Therefore, there is growing concern regarding the environmental impact of GBCA because of their ubiquitous presence in the aquatic environment. To address the problem of GBCA in the water system as a whole, collaboration is necessary between all stakeholders, including the producers of GBCA, medical professionals and importantly, the consumers of drinking water, i.e. the patients. This paper aims to make healthcare professionals aware of the opportunity to take the lead in making informed decisions about the use of GBCA and provides an overview of the different options for action.In this paper, we first provide a summary on the metabolism and clinical use of GBCA, then the environmental fate and observations of GBCA, followed by measures to reduce the use of GBCA. The environmental impact of GBCA can be reduced by (1) measures focusing on the application of GBCA by means of weight-based contrast volume reduction, GBCA with higher relaxivity per mmol of Gd, contrast-enhancing sequences, and post-processing; and (2) measures that reduce the waste of GBCA, including the use of bulk packaging and collecting residues of GBCA at the point of application.Critical relevance statement This review aims to make healthcare professionals aware of the environmental impact of GBCA and the opportunity for them to take the lead in making informed decisions about GBCA use and the different options to reduce its environmental burden.Key points• Gadolinium-based contrast agents are found in sources of drinking water and constitute an environmental risk.• Radiologists have a wide spectrum of options to reduce GBCA use without compromising diagnostic quality.• Radiology can become more sustainable by adopting such measures in clinical practice.

[Use of Gadolinium in Follow-Up MRI of Multiple Sclerosis Patients: Current Recommendations]

Multiple sclerosis is the most frequent demyelinating disease of the central nervous system and is characterized by early onset and progressive disability. Magnetic resonance imaging, due to its high sensitivity and specificity in the detection of demyelinating lesions, is the most useful diagnostic test for this disease, with the administration of gadolinium-based contrast agents being an important contribution to imaging interpretation. Although contrast is essential for diagnostic purposes, its routine use in monitoring disease activity, response to treatment, and related complications is controversial. This article aims to collate current recommendations regarding the use of gadolinium in the imaging follow-up of multiple sclerosis and establish effective and safe guidelines for clinical practice. The literature review was conducted in PubMed, using the terms 'multiple sclerosis', 'magnetic resonance imaging' and 'gadolinium', or 'contrast media'. Articles published between January 2013 and January 2023 concerning the safety of gadolinium and the use of these contrast agents in follow-up scans of adult patients diagnosed with multiple sclerosis were selected. Although no biological or clinical consequences have been unequivocally attributed to the retention of gadolinium in the brain, which were mostly reported with linear agents, health authorities have been recommending the restriction of contrast to essential clinical circumstances. In multiple sclerosis, the detection of subclinical contrast-enhancing lesions with no corresponding new/ enlarging T2-WI lesions is rare and has a questionable impact on therapeutic decisions. On the other hand, gadolinium has a higher sensitivity in the differential diagnosis of relapses, in the detection of recent disease activity, before and after treatment initiation, and in patients with a large lesion burden or diffuse/confluent T2-WI lesions. Contrary to progressive multifocal leukoencephalopathy screening, monitoring of immune restitution inflammatory syndrome also benefits from the administration of gadolinium. It is feasible and safe to exclude gadolinium-based contrast agents from routine follow-up scans of multiple sclerosis, despite their additional contribution in specific clinical circumstances that should be acknowledged by the neurologist and neuroradiologist.

Accuracy of Noncontrast T2 SPACE in Active MS Cord Lesion Detection

BACKGROUND AND PURPOSE

The diagnosis of active MS lesions is often based on postgadolinium T1-weighted MR imaging. Recent studies suggest a risk of IV gadolinium to patients, predominantly based on gadolinium deposition in tissue. Noncontrast sequences have shown promise in MS diagnosis, but none differentiate acute from chronic MS lesions. We hypothesized that 3D T2 sampling perfection with application-optimized contrasts by using different flip angle evolution (SPACE) MR imaging can help detect and differentiate active-versus-chronic MS lesions without the need for IV contrast.

MATERIALS AND METHODS

In this single-center retrospective study, 340 spinal MR imaging cases of MS were collected in a 24-month period. Two senior neuroradiologists blindly and independently reviewed postcontrast T1-weighted sagittal and T2-SPACE sagittal images for the presence of MS lesions, associated cord expansion/atrophy on T2-SPACE, and enhancement on postcontrast T1WI. Discrepancies were resolved by consensus between the readers. Sensitivity, specificity, and accuracy of T2-SPACE compared with postcontrast T1WI were computed, and interobserver agreement was calculated.

RESULTS

The sensitivity of lesion detection on T2-SPACE was 85.71%, 95% CI, 63.66%-96.95%; with a specificity of 93.52%, 95% CI, 90.06%-96.05%; and an accuracy of 92.99%, 95% CI, 89.58%-95.56. Additionally, 16/21 (84.2%) acute enhancing cord lesions showed cord expansion on T2-SPACE. The interobserver agreement was 92%.

CONCLUSIONS

Our study shows that T2-SPACE facilitates noncontrast detection of acute MS lesions with high accuracy compared with postcontrast T1WI and with high interobserver agreement. The lack of gadolinium use provides an advantage, bypassing any potential adverse effects of repetitive contrast administration.

Longitudinal Assessment of Multiple Sclerosis Lesion Load With Synthetic Magnetic Resonance Imaging-A Multicenter Validation Study

INTRODUCTION

Double inversion recovery (DIR) has been validated as a sensitive magnetic resonance imaging (MRI) contrast in multiple sclerosis (MS). Deep learning techniques can use basic input data to generate synthetic DIR (synthDIR) images that are on par with their acquired counterparts. As assessment of longitudinal MRI data is paramount in MS diagnostics, our study's purpose is to evaluate the utility of synthDIR longitudinal subtraction imaging for detection of disease progression in a multicenter data set of MS patients.

METHODS

We implemented a previously established generative adversarial network to synthesize DIR from input T1-weighted and fluid-attenuated inversion recovery (FLAIR) sequences for 214 MRI data sets from 74 patients and 5 different centers. One hundred and forty longitudinal subtraction maps of consecutive scans (follow-up scan-preceding scan) were generated for both acquired FLAIR and synthDIR. Two readers, blinded to the image origin, independently quantified newly formed lesions on the FLAIR and synthDIR subtraction maps, grouped into specific locations as outlined in the McDonald criteria.

RESULTS

Both readers detected significantly more newly formed MS-specific lesions in the longitudinal subtractions of synthDIR compared with acquired FLAIR (R1: 3.27 ± 0.60 vs 2.50 ± 0.69 [ P = 0.0016]; R2: 3.31 ± 0.81 vs 2.53 ± 0.72 [ P < 0.0001]). Relative gains in detectability were most pronounced in juxtacortical lesions (36% relative gain in lesion counts-pooled for both readers). In 5% of the scans, synthDIR subtraction maps helped to identify a disease progression missed on FLAIR subtraction maps.

CONCLUSIONS

Generative adversarial networks can generate high-contrast DIR images that may improve the longitudinal follow-up assessment in MS patients compared with standard sequences. By detecting more newly formed MS lesions and increasing the rates of detected disease activity, our methodology promises to improve clinical decision-making.

Lesion location across diagnostic regions in multiple sclerosis

BACKGROUND

Lesions in the periventricular, (juxta)cortical, and infratentorial region, as visible on brain MRI, are part of the diagnostic criteria for Multiple sclerosis (MS) whereas lesions in the subcortical region are currently only a marker of disease activity. It is unknown whether MS lesions follow individual spatial patterns or whether they occur in a random manner across diagnostic regions.

AIM

First, to describe cross-sectionally the spatial lesion patterns in patients with MS. Second, to investigate the spatial association of new lesions and lesions at baseline across diagnostic regions.

METHODS

Experienced neuroradiologists analyzed brain MRI (3D, 3T) in a cohort of 330 early MS patients. Lesions at baseline and new solitary lesions after two years were segmented (manually and by consensus) and classified as periventricular, (juxta)cortical, or infratentorial (diagnostic regions) or subcortical-with or without Gadolinium-enhancement. Gadolinium enhancement of lesions in the different regions was compared by Chi square test. New lesions in the four regions served as dependent variable in four zero-inflated Poisson models each with the six independent variables of lesions in the four regions at baseline, age and gender.

RESULTS

At baseline, lesions were most often observed in the subcortical region (mean 13.0 lesions/patient), while lesion volume was highest in the periventricular region (mean 2287 µl/patient). Subcortical lesions were less likely to show gadolinium enhancement (3.1 %) than juxtacortical (4.3 %), periventricular (5.3 %) or infratentorial lesions (7.2 %). Age was inversely correlated with new periventricular, juxtacortical and subcortical lesions. New lesions in the periventricular, juxtacortical and infratentorial region showed a significant autocorrelative behavior being positively related to the number of lesions in the respective regions at baseline. New lesions in the subcortical region showed a different behavior with a positive association with baseline periventricular lesions and a negative association with baseline infratentorial lesions.

CONCLUSION

Across regions, new lesions do not occur randomly; instead, new lesions in the periventricular, juxtacortical and infratentorial diagnostic region are associated with that at baseline. Lesions in the subcortical regions are more closely related to periventricular lesions. Moreover, subcortical lesions substantially contribute to lesion burden in MS but are less likely to show gadolinium enhancement (than lesions in the diagnostic regions).

Retrospective cohort study to devise a treatment decision score predicting adverse 24-month radiological activity in early multiple sclerosis

Background

Multiple sclerosis (MS) is a chronic neuroinflammatory disease affecting about 2.8 million people worldwide. Disease course after the most common diagnoses of relapsing-remitting multiple sclerosis (RRMS) and clinically isolated syndrome (CIS) is highly variable and cannot be reliably predicted. This impairs early personalized treatment decisions.

Objectives

The main objective of this study was to algorithmically support clinical decision-making regarding the options of early platform medication or no immediate treatment of patients with early RRMS and CIS.

Design

Retrospective monocentric cohort study within the Data Integration for Future Medicine (DIFUTURE) Consortium.

Methods

Multiple data sources of routine clinical, imaging and laboratory data derived from a large and deeply characterized cohort of patients with MS were integrated to conduct a retrospective study to create and internally validate a treatment decision score [Multiple Sclerosis Treatment Decision Score (MS-TDS)] through model-based random forests (RFs). The MS-TDS predicts the probability of no new or enlarging lesions in cerebral magnetic resonance images (cMRIs) between 6 and 24 months after the first cMRI.

Results

Data from 65 predictors collected for 475 patients between 2008 and 2017 were included. No medication and platform medication were administered to 277 (58.3%) and 198 (41.7%) patients. The MS-TDS predicted individual outcomes with a cross-validated area under the receiver operating characteristics curve (AUROC) of 0.624. The respective RF prediction model provides patient-specific MS-TDS and probabilities of treatment success. The latter may increase by 5-20% for half of the patients if the treatment considered superior by the MS-TDS is used.

Conclusion

Routine clinical data from multiple sources can be successfully integrated to build prediction models to support treatment decision-making. In this study, the resulting MS-TDS estimates individualized treatment success probabilities that can identify patients who benefit from early platform medication. External validation of the MS-TDS is required, and a prospective study is currently being conducted. In addition, the clinical relevance of the MS-TDS needs to be established.

The independent contribution of brain, spinal cord and gadolinium MRI in treatment decision in multiple sclerosis: A population-based retrospective study

BACKGROUND

Spinal cord and gadolinium (Gd)-enhanced magnetic resonance imaging (MRI) can provide additional information to brain MRI to determine prognosis of multiple sclerosis (MS). However, the real-world impact of routine use of brain MRI with spinal cord and/or Gd sequences is unknown. Our aim was to evaluate the effect of brain, spinal cord and Gd MRI on treatment decisions in MS.

METHODS

In this 2015-2020 population-based study, we performed a retrospective analysis on MS patients resident in the Campania Region (South Italy), with disease modifying treatment (DMT) prescription (n = 6,161). DMTs were classified as platform (dimethyl fumarate, glatiramer acetate, interferon-beta, peg-interferon-beta, teriflunomide), or high-efficacy (alemtuzumab, cladribine, fingolimod, natalizumab, ocrelizumab). We evaluated the association between binary MRI variables and switch from platform to high-efficacy DMT using multivariable logistic regression.

RESULTS

The likelihood of switch from platform to high-efficacy DMT was 47% higher when including post-Gd acquisitions to brain and/or spinal cord MRI, 59% higher when including spinal cord acquisitions to brain MRI, and 132% higher when including any MRI compared with no MRI (all p < 0.05). The likelihood of switch to high-efficacy DMT decreased over time from treatment start.

CONCLUSION

Our results show that spinal cord and Gd MRI acquisitions can provide relevant information to influence subsequent treatment decisions, especially in early treatment phases, compared with stand-alone brain MRI.

Impact of post-contrast MRI in the definition of active multiple sclerosis

BACKGROUND

For multiple sclerosis (MS) phenotypes classification, the presence of "disease activity" can be defined by clinical relapses and/or by magnetic resonance imaging (MRI) through gadolinium-enhancing (Gd+) lesions or new/enlarged T2 lesions. Recent MRI and pathology findings have demonstrated Gd deposition in the brain, suggesting to avoid Gd administration when dispensable. In this scenario, we aimed to evaluate the contribution of post-contrast MRIs to the definition of "active" MS phenotype.

METHODS

We retrospectively selected 84 "active" relapsing-remitting MS (RRMS) patients according to Lublin 2013, calculating both the number of Gd+ lesions not detectable as new/unequivocally enlarged on T2 images and the proportion of patients who would be still correctly classified as "active" without Gd administration.

RESULTS

13 out of 164 (7.9%) Gd+ lesions did not correspond to a new/enlarged T2 lesion. Gd administration did not modify the classification of MS as "active" in 83 out of 84 subjects (98.8%).

CONCLUSION

The contribution of Gd+ lesions to the correct classification of RRMS patients as "active" is marginal, thus limiting the need of routine Gd administration for this scope. Further studies are warranted to support these conclusions.

Sensitivity of portable low-field magnetic resonance imaging for multiple sclerosis lesions

Magnetic resonance imaging (MRI) is a fundamental tool in the diagnosis and management of neurological diseases such as multiple sclerosis (MS). New portable, low-field strength, MRI scanners could potentially lower financial and technical barriers to neuroimaging and reach underserved or disabled populations, but the sensitivity of these devices for MS lesions is unknown. We sought to determine if white matter lesions can be detected on a portable 64mT scanner, compare automated lesion segmentations and total lesion volume between paired 3T and 64mT scans, identify features that contribute to lesion detection accuracy, and explore super-resolution imaging at low-field. In this prospective, cross-sectional study, same-day brain MRI (FLAIR, T1w, and T2w) scans were collected from 36 adults (32 women; mean age, 50 ± 14 years) with known or suspected MS using Siemens 3T (FLAIR: 1 mm isotropic, T1w: 1 mm isotropic, and T2w: 0.34-0.5 × 0.34-0.5 × 3-5 mm) and Hyperfine 64mT (FLAIR: 1.6 × 1.6 × 5 mm, T1w: 1.5 × 1.5 × 5 mm, and T2w: 1.5 × 1.5 × 5 mm) scanners at two centers. Images were reviewed by neuroradiologists. MS lesions were measured manually and segmented using an automated algorithm. Statistical analyses assessed accuracy and variability of segmentations across scanners and systematic scanner biases in automated volumetric measurements. Lesions were identified on 64mT scans in 94% (31/33) of patients with confirmed MS. The average smallest lesions manually detected were 5.7 ± 1.3 mm in maximum diameter at 64mT vs 2.1 ± 0.6 mm at 3T, approaching the spatial resolution of the respective scanner sequences (3T: 1 mm, 64mT: 5 mm slice thickness). Automated lesion volume estimates were highly correlated between 3T and 64mT scans (r = 0.89, p < 0.001). Bland-Altman analysis identified bias in 64mT segmentations (mean = 1.6 ml, standard error = 5.2 ml, limits of agreement = -19.0-15.9 ml), which over-estimated low lesion volume and under-estimated high volume (r = 0.74, p < 0.001). Visual inspection revealed over-segmentation was driven venous hyperintensities on 64mT T2-FLAIR. Lesion size drove segmentation accuracy, with 93% of lesions > 1.0 ml and all lesions > 1.5 ml being detected. Using multi-acquisition volume averaging, we were able to generate 1.6 mm isotropic images on the 64mT device. Overall, our results demonstrate that in established MS, a portable 64mT MRI scanner can identify white matter lesions, and that automated estimates of total lesion volume correlate with measurements from 3T scans.

Economic impact of selective use of contrast for routine follow-up MRI of patients with multiple sclerosis

BACKGROUND AND PURPOSE

Imaging and autopsy studies show intracranial gadolinium deposition in patients who have undergone serial contrast-enhanced MRIs. This observation has raised concerns when using contrast administration in patients who receive frequent MRIs. To address this, we implemented a contrast-conditional protocol wherein gadolinium is administered only for multiple sclerosis (MS) patients with imaging evidence of new disease activity on precontrast imaging. In this study, we explore the economic impact of our new MRI protocol.

METHODS

We compared scanner time and Medicare reimbursement using our contrast-conditional methodology versus that of prior protocols where all patients received gadolinium.

RESULTS

For 422 patients over 4 months, the contrast-conditional protocol amounted to 60% decrease in contrast injection and savings of approximately 20% of MRI scanner time. If the extra scanner time was used for performing MS follow-up MRIs in additional patients, the contrast-conditional protocol would amount to net revenue loss of $21,707 (∼3.7%).

CONCLUSIONS

Implementation of a new protocol to limit contrast in MS follow-up MRIs led to a minimal decrease in revenue when controlled for scanner time utilized and is outweighed by other benefits, including substantial decreased gadolinium administration, increased patient comfort, and increased availability of scanner time, which depending on type of studies performed could result in additional financial benefit.

Diagnostic value of gadolinium contrast administration for spinal cord magnetic resonance imaging in multiple sclerosis patients and correlative markers of lesion enhancement

Background

Magnetic resonance imaging is essential for monitoring people with multiple sclerosis, but the diagnostic value of gadolinium contrast administration in spine magnetic resonance imaging is unclear.

Objective

To assess the diagnostic value of gadolinium contrast administration in spine magnetic resonance imaging follow-up examinations and identify imaging markers correlating with lesion enhancement.

Methods

A total of 65 multiple sclerosis patients with at least 2 spinal magnetic resonance imaging follow-up examinations were included. Spine magnetic resonance imaging was performed at 3 Tesla with a standardized protocol (sagittal and axial T2-weighted turbo spin echo and T1-weighted post-contrast sequences). T2 lesion load and enhancing lesions were assessed by two independent neuroradiologists for lesion size, localization, and T2 signal ratio (T2 signal_lesion/T2 signal_{normal appearing spinal cord}).

Results

A total of 68 new spinal T2 lesions and 20 new contrast-enhancing lesions developed during follow-up. All enhancing lesions had a discernable correlate as a new T2 lesion. Lesion enhancement correlated with a higher T2 signal ratio compared to non-enhancing lesions (T2 signal ratio: 2.0 ± 0.4 vs. 1.4 ± 0.2, ****p < 0.001). Receiver operating characteristics analysis showed an optimal cutoff value of signal ratio 1.78 to predict lesion enhancement (82% sensitivity and 97% specificity).

Conclusion

Gadolinium contrast administration is dispensable in follow-up spine magnetic resonance imaging if no new T2 lesions are present. Probability of enhancement correlates with the T2 signal ratio.

The role of contrast-enhanced and non-contrast-enhanced MRI in the follow-up of multiple sclerosis

BACKGROUND

Magnetic resonance imaging (MRI) is widely used in patients with multiple sclerosis (MS) for different indications. However, frequent administration of gadolinium in these patients can have some potential complications. So, a more limited approach reducing the use of gadolinium should be considered.

PURPOSE

To evaluate the additional benefits of contrast-enhanced MRI over non-contrast-enhanced MRI in routine follow-up of patients with MS.

MATERIAL AND METHODS

This is a retrospective cohort study including patients with MS who underwent both contrast-enhanced and non-contrast-enhanced MRI for two time-points with an interval of at least six months. Non-contrast-enhanced images were compared for each patient and interpreted as non-progressive or progressive disease. Then, rate and type of enhancing lesions were analyzed and compared between the groups. All images were reviewed and compared visually by two radiologists.

RESULTS

A total of 462 patients (392 women; mean age = 36 years) were included. Of these patients, 352 were in the non-progressive group and 112 were in progressive group. Comparison of baseline and follow-up contrast-enhanced MRIs revealed that 13 (3.7%) patients in the non-progressive group and 58 (51.8%) patients in progressive group developed enhancing lesions (P < 0.001). All 58 patients in the progressive group developed new enhancing lesions, whereas all those in the non-progressive group revealed persistent or reactivated enhancing lesions without evidence of new lesions.

CONCLUSION

According to the very low incidence rate of new enhancing lesions in patients with non-progressive disease on follow-up non-contrast-enhanced MRI, routine administration of contrast in follow-up studies is not suggested.

2021 MAGNIMS-CMSC-NAIMS consensus recommendations on the use of MRI in patients with multiple sclerosis

The 2015 Magnetic Resonance Imaging in Multiple Sclerosis and 2016 Consortium of Multiple Sclerosis Centres guidelines on the use of MRI in diagnosis and monitoring of multiple sclerosis made an important step towards appropriate use of MRI in routine clinical practice. Since their promulgation, there have been substantial relevant advances in knowledge, including the 2017 revisions of the McDonald diagnostic criteria, renewed safety concerns regarding intravenous gadolinium-based contrast agents, and the value of spinal cord MRI for diagnostic, prognostic, and monitoring purposes. These developments suggest a changing role of MRI for the management of patients with multiple sclerosis. This 2021 revision of the previous guidelines on MRI use for patients with multiple sclerosis merges recommendations from the Magnetic Resonance Imaging in Multiple Sclerosis study group, Consortium of Multiple Sclerosis Centres, and North American Imaging in Multiple Sclerosis Cooperative, and translates research findings into clinical practice to improve the use of MRI for diagnosis, prognosis, and monitoring of individuals with multiple sclerosis. We recommend changes in MRI acquisition protocols, such as emphasising the value of three dimensional-fluid-attenuated inversion recovery as the core brain pulse sequence to improve diagnostic accuracy and ability to identify new lesions to monitor treatment effectiveness, and we provide recommendations for the judicious use of gadolinium-based contrast agents for specific clinical purposes. Additionally, we extend the recommendations to the use of MRI in patients with multiple sclerosis in childhood, during pregnancy, and in the post-partum period. Finally, we discuss promising MRI approaches that might deserve introduction into clinical practice in the near future.

Multiple sclerosis: prevalence of the 'central vein' sign in white matter lesions on gadolinium-enhanced susceptibility-weighted images

AIMS

To evaluate prospectively whether an intravenous gadolinium injection could improve the detection of the central vein sign on susceptibility-weighted imaging sequences obtained with a 1.5 T magnetic resonance scanner in patients with multiple sclerosis compared to unenhanced susceptibility-weighted images.

MATERIALS AND METHODS

This prospective, institution review board-approved study included 19 patients affected by multiple sclerosis (six men; 13 women; mean age 40.8 years, range 20-74 years). Patients had the relapsing-remitting clinical subtype in 95% of cases, and only one (5%) patient had the primary progressive clinical subtype of multiple sclerosis. T2-weighted images, fluid-attenuated inversion recovery images, unenhanced and contrast-enhanced susceptibility-weighted images were evaluated in consensus by two neuroradiologists for the presence of the central vein sign. The readers were blinded to magnetic resonance imaging reports, clinical information, the presence and the localisation of focal hyperintense white matter lesions. Any discordance between readers was resolved through a joint review of the recorded images with an additional neuroradiologist.

RESULTS

A total of 317 multiple sclerosis lesions were analysed. The central vein sign had a higher prevalence detection rate on gadolinium-enhanced susceptibility-weighted images (272 of 317 lesions, 86%) compared to unenhanced susceptibility-weighted images (172 of 317 lesions, 54%).

CONCLUSION

Gadolinium-enhanced susceptibility-weighted imaging improves the detection rate of the central vein sign in multiple sclerosis lesions.

Deep-Learning Generated Synthetic Double Inversion Recovery Images Improve Multiple Sclerosis Lesion Detection

OBJECTIVES

The aim of the study was to implement a deep-learning tool to produce synthetic double inversion recovery (synthDIR) images and compare their diagnostic performance to conventional sequences in patients with multiple sclerosis (MS).

MATERIALS AND METHODS

For this retrospective analysis, 100 MS patients (65 female, 37 [22-68] years) were randomly selected from a prospective observational cohort between 2014 and 2016. In a subset of 50 patients, an artificial neural network (DiamondGAN) was trained to generate a synthetic DIR (synthDIR) from standard acquisitions (T1, T2, and fluid-attenuated inversion recovery [FLAIR]). With the resulting network, synthDIR was generated for the remaining 50 subjects. These images as well as conventionally acquired DIR (trueDIR) and FLAIR images were assessed for MS lesions by 2 independent readers, blinded to the source of the DIR image. Lesion counts in the different modalities were compared using a Wilcoxon signed-rank test, and interrater analysis was performed. Contrast-to-noise ratios were compared for objective image quality.

RESULTS

Utilization of synthDIR allowed to detect significantly more lesions compared with the use of FLAIR images (31.4 ± 20.7 vs 22.8 ± 12.7, P < 0.001). This improvement was mainly attributable to an improved depiction of juxtacortical lesions (12.3 ± 10.8 vs 7.2 ± 5.6, P < 0.001). Interrater reliability was excellent in FLAIR 0.92 (95% confidence interval [CI], 0.85-0.95), synthDIR 0.93 (95% CI, 0.87-0.96), and trueDIR 0.95 (95% CI, 0.85-0.98).Contrast-to-noise ratio in synthDIR exceeded that of FLAIR (22.0 ± 6.4 vs 16.7 ± 3.6, P = 0.009); no significant difference was seen in comparison to trueDIR (22.0 ± 6.4 vs 22.4 ± 7.9, P = 0.87).

CONCLUSIONS

Computationally generated DIR images improve lesion depiction compared with the use of standard modalities. This method demonstrates how artificial intelligence can help improving imaging in specific pathologies.

Heterogeneity of multiple sclerosis lesions in fast diffusional kurtosis imaging

Background

Mean kurtosis (MK), one of the parameters derived from diffusion kurtosis imaging (DKI), has shown increased sensitivity to tissue microstructure damage in several neurological disorders.

Methods

Thirty-seven patients with relapsing-remitting MS and eleven healthy controls (HC) received brain imaging on a 3T MR scanner, including a fast DKI sequence. MK and mean diffusivity (MD) were measured in the white matter of HC, normal-appearing white matter (NAWM) of MS patients, contrast-enhancing lesions (CE-L), FLAIR lesions (FLAIR-L) and black holes (BH).

Results

Overall 1529 lesions were analyzed, including 30 CE-L, 832 FLAIR-L and 667 BH. Highest MK values were obtained in the white matter of HC (0.814 ± 0.129), followed by NAWM (0.724 ± 0.137), CE-L (0.619 ± 0.096), FLAIR-L (0.565 ± 0.123) and BH (0.549 ± 0.12). Lowest MD values were obtained in the white matter of HC (0.747 ± 0.068 10⁻³mm²/sec), followed by NAWM (0.808 ± 0.163 10⁻³mm²/sec), CE-L (0.853 ± 0.211 10⁻³mm²/sec), BH (0.957 ± 0.304 10⁻³mm²/sec) and FLAIR-L (0.976 ± 0.35 10⁻³mm²/sec). While MK differed significantly between CE-L and non-enhancing lesions, MD did not.

Conclusion

MK adds predictive value to differentiate between MS lesions and might provide further information about diffuse white matter injury and lesion microstructure.

Differentiating epidural fibrosis from disc herniation on contrast-enhanced and unenhanced MRI in the postoperative lumbar spine

OBJECTIVE

To determine diagnostic confidence and inter-observer/intra-observer agreement in differentiating epidural fibrosis from disc herniation and lumbar spinal stenosis parameters on magnetic resonance images (MRI) in postoperative lumbar spines with (Gad-MRI) and without (unenhanced MRI) intravenous gadolinium-based contrast agent.

SUBJECTS AND METHODS

N = 124 lumbar spine MRI examinations of four groups were included: 1-6 months, 7-18 months, 19-36 months, more than 37 months between lumbar spine surgery and imaging. Two radiologists evaluated Gad-MRI and unenhanced MRI: diagnostic confidence was determined as confident or unconfident. Inter-observer and intra-observer agreement were assessed in differentiating epidural fibrosis from disc herniation and for lumbar spinal stenosis parameters on MRI. Fisher's exact test and Cohen's kappa served for statistics.

RESULTS

Diagnostic confidence in differentiating epidural fibrosis from disc herniation was significantly higher on Gad-MR images compared with unenhanced MRI at 1-18 months for observer 1 and at 1-6 months postoperatively for observer 2 (p values: 0.01-0.025). Inter-observer agreement at 1-6 months postoperatively for identification of epidural fibrosis was higher on Gad-MRI (kappa values: 0.53 versus 0.24). Inter-observer and intra-observer agreement for identification of disc herniation and for assessment of lumbar spinal stenosis parameters revealed inconsistent data, without a trend for higher inter-observer or intra-observer agreement on Gad-MRI compared with unenhanced MRI (kappa values: 0.17-0.75).

CONCLUSION

Gad-MR images compared with unenhanced MRI improved diagnostic confidence and agreement in differentiating epidural fibrosis from disc herniation for both observers in the first 6 months and for one observer in the first 18 months after lumbar spine surgery. After 18 months, Gad-MR images compared with unenhanced MRI did neither improve confidence nor agreement.

[Unexpected emergencies and emergency findings in outpatient radiology practice]

CLINICAL/METHODICAL ISSUE

Radiological emergencies or incidental findings that require rapid treatment are part of the daily routine of radiological units in clinics-but also in outpatient radiology. What is special about the care of these patients in the outpatient radiological area?

STANDARD RADIOLOGICAL METHODS

An acute or incidental diagnosis of an emergency situation generally occurs with CT or MRI. Outpatient radiology serves as a gatekeeper by preselecting critical cases and then, in close cooperation with all those involved, providing optimal therapy.

METHODOLOGICAL INNOVATIONS

Use of CT and MRI to assess the emergency situation allows optimal therapy for the patient to be initiated. In outpatient radiology, close cooperation in the team with the patient and the referring physicians means achieving an optimal result, which can be a great opportunity.

ACHIEVEMENTS

Close personal collaboration in the team with the referring physician and the patient is a decisive strength of outpatient radiology and can guarantee optimum care for the patient, especially in the case of acute emergencies or incidental findings which turn out to be clinical-radiological emergencies. The largest challenge in outpatient radiology is to select the critical cases of the many noncritical cases in the face of growing time and cost pressure in a time-economic manner.

PRACTICAL RECOMMENDATIONS

Outpatient radiology should be aware of the chance for close cooperation and communication with referring physician and patient, especially in emergency situations-for the well-being of the patient, but also to increase the acceptance and significance of the field of radiology.

AI in Radiology: Where are we today in Multiple Sclerosis Imaging?

Background MR imaging is an essential component in managing patients with Multiple sclerosis (MS). This holds true for the initial diagnosis as well as for assessing the clinical course of MS. In recent years, a growing number of computer tools were developed to analyze imaging data in MS. This review gives an overview of the most important applications with special emphasis on artificial intelligence (AI).

Methods Relevant studies were identified through a literature search in recognized databases, and through parsing the references in studies found this way. Literature published as of November 2019 was included with a special focus on recent studies from 2018 and 2019.

Results There are a number of studies which focus on optimizing lesion visualization and lesion segmentation. Some of these studies accomplished these tasks with high accuracy, enabling a reproducible quantitative analysis of lesion loads. Some studies took a radiomics approach and aimed at predicting clinical endpoints such as the conversion from a clinically isolated syndrome to definite MS. Moreover, recent studies investigated synthetic imaging, i. e. imaging data that is not measured during an MR scan but generated by a computer algorithm to optimize the contrast between MS lesions and brain parenchyma.

Conclusion Computer-based image analysis and AI are hot topics in imaging MS. Some applications are ready for use in clinical routine. A major challenge for the future is to improve prediction of expected disease courses and thereby helping to find optimal treatment decisions on an individual level. With technical improvements, more questions arise about the integration of new tools into the radiological workflow.

Key Points: 

Citation Format

Automated volumetric assessment with artificial neural networks might enable a more accurate assessment of disease burden in patients with multiple sclerosis

OBJECTIVES

Patients with multiple sclerosis (MS) regularly undergo MRI for assessment of disease burden. However, interpretation may be time consuming and prone to intra- and interobserver variability. Here, we evaluate the potential of artificial neural networks (ANN) for automated volumetric assessment of MS disease burden and activity on MRI.

METHODS

A single-institutional dataset with 334 MS patients (334 MRI exams) was used to develop and train an ANN for automated identification and volumetric segmentation of T2/FLAIR-hyperintense and contrast-enhancing (CE) lesions. Independent testing was performed in a single-institutional longitudinal dataset with 82 patients (266 MRI exams). We evaluated lesion detection performance (F1 scores), lesion segmentation agreement (DICE coefficients), and lesion volume agreement (concordance correlation coefficients [CCC]). Independent evaluation was performed on the public ISBI-2015 challenge dataset.

RESULTS

The F1 score was maximized in the training set at a detection threshold of 7 mm³ for T2/FLAIR lesions and 14 mm³ for CE lesions. In the training set, mean F1 scores were 0.867 for T2/FLAIR lesions and 0.636 for CE lesions, as compared to 0.878 for T2/FLAIR lesions and 0.715 for CE lesions in the test set. Using these thresholds, the ANN yielded mean DICE coefficients of 0.834 and 0.878 for segmentation of T2/FLAIR and CE lesions in the training set (fivefold cross-validation). Corresponding DICE coefficients in the test set were 0.846 for T2/FLAIR lesions and 0.908 for CE lesions, and the CCC was ≥ 0.960 in each dataset.

CONCLUSIONS

Our results highlight the capability of ANN for quantitative state-of-the-art assessment of volumetric lesion load on MRI and potentially enable a more accurate assessment of disease burden in patients with MS.

KEY POINTS

• Artificial neural networks (ANN) can accurately detect and segment both T2/FLAIR and contrast-enhancing MS lesions in MRI data. • Performance of the ANN was consistent in a clinically derived dataset, with patients presenting all possible disease stages in MRI scans acquired from standard clinical routine rather than with high-quality research sequences. • Computer-aided evaluation of MS with ANN could streamline both clinical and research procedures in the volumetric assessment of MS disease burden as well as in lesion detection.

Automatic detection of lesion load change in Multiple Sclerosis using convolutional neural networks with segmentation confidence

The detection of new or enlarged white-matter lesions is a vital task in the monitoring of patients undergoing disease-modifying treatment for multiple sclerosis. However, the definition of 'new or enlarged' is not fixed, and it is known that lesion-counting is highly subjective, with high degree of inter- and intra-rater variability. Automated methods for lesion quantification, if accurate enough, hold the potential to make the detection of new and enlarged lesions consistent and repeatable. However, the majority of lesion segmentation algorithms are not evaluated for their ability to separate radiologically progressive from radiologically stable patients, despite this being a pressing clinical use-case. In this paper, we explore the ability of a deep learning segmentation classifier to separate stable from progressive patients by lesion volume and lesion count, and find that neither measure provides a good separation. Instead, we propose a method for identifying lesion changes of high certainty, and establish on an internal dataset of longitudinal multiple sclerosis cases that this method is able to separate progressive from stable time-points with a very high level of discrimination (AUC = 0.999), while changes in lesion volume are much less able to perform this separation (AUC = 0.71). Validation of the method on two external datasets confirms that the method is able to generalize beyond the setting in which it was trained, achieving an accuracies of 75 % and 85 % in separating stable and progressive time-points.

Comparison of Unenhanced and Gadolinium-Enhanced Imaging in Multiple Sclerosis: Is Contrast Needed for Routine Follow-Up MRI?

BACKGROUND AND PURPOSE

Gadolinium enhanced MRI is routinely used for follow-up of patients with multiple sclerosis. Our aim was to evaluate whether enhancing multiple sclerosis lesions on follow-up MR imaging can be detected by visual assessment of unenhanced double inversion recovery and FLAIR sequences.

MATERIALS AND METHODS

A total of 252 consecutive MRIs in 172 adult patients with a known diagnosis of multiple sclerosis were reviewed. The co-presence or absence of associated double inversion recovery and FLAIR signal abnormality within contrast-enhancing lesions was recorded by 3 neuroradiologists. In a subset of patients with prior comparisons, the number of progressive lesions on each of the 3 sequences was assessed.

RESULTS

A total of 34 of 252 MRIs (13%) demonstrated 55 enhancing lesions, of which 52 (95%) had corresponding hyperintensity on double inversion recovery and FLAIR. All lesions were concordant between double inversion recovery and FLAIR, and the 3 enhancing lesions not visible on either sequence were small (<2 mm) and cortical/subcortical (n = 2) or periventricular (n = 1). A total of 17 (22%) of the 76 MRIs with a prior comparison had imaging evidence of disease progression: Ten (59%) of these showed new lesions on double inversion recovery or FLAIR only, 6 (35%) showed progression on all sequences, and 1 (6%) was detectable only on postcontrast T1, being located in a region of confluent double inversion recovery and FLAIR abnormality.

CONCLUSIONS

There was a high concordance between enhancing lesions and hyperintensity on either double inversion recovery or FLAIR. Serial follow-up using double inversion recovery or FLAIR alone may capture most imaging progression, but isolated enhancing lesions in confluent areas of white matter abnormality could present a pitfall for this approach.

What is the Relevance of the Systematic Use of Gadolinium During the MRI Follow-Up of Multiple Sclerosis Patients Under Natalizumab?

BACKGROUND

Multiple sclerosis (MS) patients represent a population potentially affected by the intracerebral accumulation of gadolinium-based contrast agents (GBCA) due to repeated magnetic resonance imaging (MRI) performed during their lifetime; however, MRI is still the best tool to monitor MS inflammatory activity.

OBJECTIVE

This study aimed to evaluate the relevance of GBCA injections during the MRI follow-up of MS patients under natalizumab (Tysabri) treatment.

METHODS

The MRI data results were retrospectively reviewed in a monocentric study (University Hospital of Toulouse, France) from all consecutive patients treated with natalizumab from January 2014 to January 2017. For each examination during the whole MRI follow-up, new lesions (enhancing and non-enhancing) were analyzed.

RESULTS

A total of 129 patients were included in this study (65% female, mean age = 41 years, mean treatment duration 6.5 years, 50% positive for John Cunningham virus) and benefited from 735 MRIs with GBCA. Only 3 MRIs showed a new enhancing lesion, systematically encountered after treatment discontinuation.

CONCLUSION

According to this study based on the clinical and radiological practice, the systematic use of GBCA seems of limited relevance in the MRI follow-up of asymptomatic patients treated continuously with natalizumab.

An Initiative to Reduce Unnecessary Gadolinium-Based Contrast in Multiple Sclerosis Patients

OBJECTIVE

Patients with multiple sclerosis (MS) routinely undergo serial contrast-enhanced MRIs. Given concerns regarding tissue deposition of gadolinium-based contrast agents (GBCAs) and evidence that enhancement of lesions is only seen in patients with new disease activity on noncontrast imaging, we set out to implement a prospective quality improvement project whereby intravenous contrast would be reserved only for patients with evidence of new disease activity on noncontrast images.

METHODS

To prospectively implement such a protocol, we leveraged our in-house computer-assisted detection (CAD) software and 3-D laboratory radiology technologists to perform real-time preliminary assessments of the CAD-processed T2 fluid attenuated inversion recovery (FLAIR) noncontrast images as a basis for deciding whether to inject contrast. Before implementation, we held multidisciplinary meetings with neurology, neuroradiology, and MR technologists and distributed surveys to objectively assess opinions and obstacles to clinical implementation. We evaluated reduction in GBCA utilization and technologist performance relative to final neuroradiologist interpretations.

RESULTS

During a 2-month trial period, 153 patients were imaged under the new protocol. Technologists using the CAD software were able to identify patients with new or enlarging lesions on FLAIR images with 95% accuracy and 97% negative predictive value relative to final neuroradiologist interpretations, which allowed us to avoid the use of contrast and additional imaging sequences in 87% of patients.

DISCUSSION

A multidisciplinary effort to implement a quality improvement project to limit contrast in MS patients receiving follow-up MRIs allowed for improved safety and cost by targeting patients that would benefit from the use of intravenous contrast in real-time.