ProstateZones - Segmentations of the prostatic zones and urethra for the PROSTATEx dataset.

Manual segmentations are considered the gold standard for ground truth in machine learning applications. Such tasks are tedious and time-consuming, albeit necessary to train reliable models. In this work, we present a dataset with expert segmentations of the prostatic zones and urethra for 200 randomly selected patients from the PROSTATEx dataset. Notably, independent duplicate segmentations were performed for 40 patients, providing inter-reader variability data. This results in a total of 240 segmentations. This dataset can be used to train machine learning models or serve as an external test set for evaluating models trained on private data, thereby addressing a current gap in the field. The delineated structures and terminology adhere to the latest Prostate Imaging Reporting and Data Systems v2.1 guidelines, ensuring consistency.

Artefacts on magnetic resonance imaging with Osia®2 bone conduction hearing aid: A cadaver study.

OBJECTIVES: Hearing implants often limit the assessment of magnetic resonance examinations due to susceptibility artefacts. Our aim was to evaluate the impact of artefacts attributed to the Osia®2 implant system in terms of utility in visualizing selected cranial structures. METHODS: A BI300 implant and an OSI200 actuator were implanted into a human cadaver head in the audiologically most favourable position according to the manufacturer's guidelines. Scanning was accomplished using the institutional head and inner ear protocol with a General Electric 1.5 Tesla scanner with retained and removed implant magnet, extended with T1 and T2 weighted sequences with metal-artefact reduction (MAVRIC SL). Image quality was evaluated by three radiologists. RESULTS: The Osia®2 produced significant artefacts in most of the series of standard imaging sequences predominantly on the ipsilateral side of the head. The majority of the artefacts were caused by the implant magnet. Even without removing the magnet, MAVRIC SL improved image quality to such an extent that it became comparable with that after magnet removal. CONCLUSIONS: The standard sequences suffer considerable quality loss due to the artefacts, attributed predominantly to the magnetic component. Metal-artefact reduction sequences are effective in obtaining sufficient-to-good quality images without surgical magnet removal.

Fatigue and depression influence the prevalence of anxiety in patients with multiple sclerosis.

BACKGROUND: There is scarce information in Middle-Eastern Europe regarding the prevalence of anxiety in patients with multiple sclerosis (pwMS) and its association with different clinical-demographic factors. OBJECTIVE: We aimed to determine the prevalence of anxiety in Hungarian MS patients and to analyze associated factors. MATERIALS AND METHODS: We evaluated 260 PwMS with the STAI-5 anxiety questionnaire. Fatigue (FIS), depression (BDI-II) and cognition (BICAMS) were also measured. Patients underwent standard neurological evaluations to evaluate Expanded Disability Status Scale (EDSS), and also measured the fine motor skills of the hand with the 9-hole peg test (9HPT), and the walking distance with the 25-foot walking test (T25FW). RESULTS: We identified 23.1% (N = 60) of the patients with anxiety (only state, trait or both forms concurrently). According to our two univariate, multivariable logistic regression analysis, fatigue and depression are strongly associated with both state and trait anxiety. In the absence of fatigue, the odds of trait anxiety are 82% lower (OR: 0.18; 95% CI: 0.06-0.53; p = 0.002), while in the case of pwMS without depression, the odds are reduced by 81% (OR: 0.19; CI95%= 0.07-0.51, p = 0.001). This association with fatigue (OR: 0.33; CI95%= 0.13-0.85, p = 0.021) and depression (OR: 0.14; CI95%=0.06-0.35; p < 0.001) can also be statistically verified on state anxiety. Importantly, a significant association with state anxiety was found in SPSM patients as well (OR: 34.94; CI95%=2.55-479.61; p = 0.008). CONCLUSIONS: Anxiety was strongly associated with fatigue, depression, and secondary progressive disease form. These results emphasize the burden of psychiatric morbidity in pwMS.

Imbalanced temporal states of cortical blood-oxygen-level-dependent signal variability during rest in episodic migraine.

BACKGROUND: Migraine has been associated with functional brain changes including altered connectivity and activity both during and between headache attacks. Recent studies established that the variability of the blood-oxygen-level-dependent (BOLD) signal is an important attribute of brain activity, which has so far been understudied in migraine. In this study, we investigate how time-varying measures of BOLD variability change interictally in episodic migraine patients. METHODS: Two independent resting state functional MRI datasets acquired on 3T (discovery cohort) and 1.5T MRI scanners (replication cohort) including 99 episodic migraine patients (n3T = 42, n1.5T=57) and 78 healthy controls (n3T = 46, n1.5T=32) were analyzed in this cross-sectional study. A framework using time-varying measures of BOLD variability was applied to derive BOLD variability states. Descriptors of BOLD variability states such as dwell time and fractional occupancy were calculated, then compared between migraine patients and healthy controls using Mann-Whitney U-tests. Spearman's rank correlation was calculated to test associations with clinical parameters. RESULTS: Resting-state activity was characterized by states of high and low BOLD signal variability. Migraine patients in the discovery cohort spent more time in the low variability state (mean dwell time: p = 0.014, median dwell time: p = 0.022, maximum dwell time: p = 0.013, fractional occupancy: p = 0.013) and less time in the high variability state (mean dwell time: p = 0.021, median dwell time: p = 0.021, maximum dwell time: p = 0.025, fractional occupancy: p = 0.013). Higher uptime of the low variability state was associated with greater disability as measured by MIDAS scores (maximum dwell time: R = 0.45, p = 0.007; fractional occupancy: R = 0.36, p = 0.035). Similar results were observed in the replication cohort. CONCLUSION: Episodic migraine patients spend more time in a state of low BOLD variability during rest in headache-free periods, which is associated with greater disability. BOLD variability states show potential as a replicable functional imaging marker in episodic migraine.

Examining the Prevalence of Left Atrial Appendage Thrombus in a Cohort of Acute Stroke Patients with an Extended Computed Tomography Angiographic Protocol.

INTRODUCTION: Current guidelines recommend transthoracic echocardiography (TTE) for routine screening of cardiac emboli; however, the visualization of the left atrial appendage (LAA) where the thrombi are commonly found is poor. Transesophageal echocardiography (TEE) would provide better detectability of LAA thrombus, but it is a time-consuming and semi-invasive method. Extending non-gated carotid computed tomography angiography (CTA) examination to the LAA could reliably detect thrombi and could also aid treatment and secondary prevention of stroke. METHODS: We extended the CTA scan range of acute stroke patients 4 cm below the carina to include the left atrium and appendage. During the review, we evaluated LAA thrombi based on contrast relations. We then used gradient boosting to identify the most important predictors of LAA thrombi from a variety of different clinical parameters. RESULTS: We examined 240 acute stroke patients' extended CTA scans. We detected LAA thrombi in eleven cases (4.58%), eight of them had atrial fibrillation. 23.75% of all patients (57 cases) had recently discovered or previously known atrial fibrillation. Windsack morphology was the most commonly associated morphology with filling defects on CTA. According to the gradient-boosting analysis, LAA morphology showed the most predictive value for thrombi. CONCLUSION: Our extended CTA scans reliably detected LAA thrombi even in cases where TTE did not and showed that 2 patients' LAA thrombus would have been untreated based on electrocardiogram monitoring and TTE. We also showed that the benefits of CTA outweigh the disadvantages arising from the slight amount of excess radiation.

The 7-year follow-up of the Hungarian BICAMS validation cohort implies that cognitive performance may improve in multiple sclerosis patients.

BACKGROUND: Cognitive impairment (CI) is a frequent symptom of multiple sclerosis (MS) and has a great impact on the patients' quality of life, so screening is essential. The brief international cognitive assessment for multiple sclerosis (BICAMS) was developed for this purpose. However, longitudinal data is lacking with the use of the battery. OBJECTIVE: This study is to assess the performance of patients after 5 and 7 years of the original BICAMS validation study and to identify any influencing factors. METHODS: BICAMS was used to measure cognitive function of 52 relapsing-remitting MS patients (RRMS) from the original validation study after 5 years (n = 43) and again, after 7 years (n = 42). Patients filled out the fatigue impact scale (FIS) and multiple sclerosis quality of life-54 (MSQoL-54) questionnaire, and we evaluated expanded disability status scale (EDSS). RESULTS: There was an improvement in the BVMT-R and the CVLT-II assessments at both the 5-year (p<0.001 and p=0.025) and the 7-year retest (p<0.001 and p=0.002). The prevalence of CI significantly decreased at the 5-year mark (p=0.021) but remained stable after that. There was no deterioration in MSQoL scores during the study. The basic cognitive performance is the most important influencing factor, but the duration of the disease, the EDSS score, and the escalation of the therapy also affect the cognitive scores. CONCLUSION: This is the longest longitudinal study utilizing the BICAMS battery, reinforcing its feasibility as a clinical screening tool. It seems that cognitive performance may improve in the long term and early initiation of effective therapy may influence this outcome.

D-dimer levels to exclude pulmonary embolism and reduce the need for CT angiography in COVID-19 in an outpatient population.

OBJECTIVES: Emerging results indicate that, in COVID-19, thromboembolic complications contribute to the high mortality and morbidity. Previous research showed that the prevalence of pulmonary embolism (PE) is between 25-50% in COVID-19 patients, however, most of these reports are based on data from patients with severe pneumonia, treated in intensive care units. MATERIALS AND METHODS: We conducted a retrospective, single-center, observational study to estimate the prevalence of PE in COVID-19 patients who underwent CT angiography and to identify the most important predictors. Adult outpatients with COVID-19, who presented at our COVID Outpatient Clinic between 1st and 31st of March in 2021 and underwent CTA examination were included in this study. Multiple linear regression analysis was used to identify predictors of PE in COVID-19 patients. The predictors were: age, gender, disease duration, CT severity index and log-transformed quantitative D-dimer (logQDDIM) value. RESULTS: 843 COVID-19 patients were included into the study. 82.56% (693 patients) of the infected patients had a pulmonary CTA examination and D-dimer levels (mean age: 59.82 years ± 15.66). 7.61% (53 patients) of the patients had PE. 2.02% (14 patients) of the patients had main branch or lobar PE. The multiple regression analysis found that only logQDDIM was a significant predictor. A logQDDIM cut-off value of 0.0169 (1.0171 ug/ml serum D-dimer) predicted PE with 99% sensitivity (p<0.0001, degree-of-freedom = 570, AUC = 0.72). CONCLUSIONS: We demonstrated in a large cohort of COVID-19 patients that a cut-off value of QDDIM of 1ug/ml can exclude pulmonary embolism in an outpatient setting, implicating that QDDIM might potentially supersede CTA as a screening approach in COVID-19 outpatient clinics.

Evaluation of transorbital sonography measures of optic nerve diameter in the context of global and regional brain volume in multiple sclerosis.

Transorbital sonography (TOS) could be a swift and convenient method to detect the atrophy of the optic nerve, possibly providing a marker that might reflect other quantitative structural markers of multiple sclerosis (MS). Here we evaluate the utility of TOS as a complementary tool for assessing optic nerve atrophy, and investigate how TOS-derived measures correspond to volumetric brain markers in MS. We recruited 25 healthy controls (HC) and 45 patients with relapsing-remitting MS and performed B-mode ultrasonographic examination of the optic nerve. Patients additionally underwent MRI scans to obtain T1-weighted, FLAIR and STIR images. Optic nerve diameters (OND) were compared between HC, MS patients with and without history of optic neuritis (non-ON) using a mixed-effects ANOVA model. The relationship between within-subject-average OND and global and regional brain volumetric measures was investigated using FSL SIENAX, voxel-based morphometry and FSL FIRST. OND was significantly different between HC-MS (HC = 3.2 ± 0.4 mm, MS = 3 ± 0.4 mm; p < 0.019) and we found significant correlation between average OND and normalised whole brain (ß = 0.42, p < 0.005), grey matter (ß = 0.33, p < 0.035), white matter (ß = 0.38, p < 0.012) and ventricular cerebrospinal fluid volume (ß = - 0.36, p < 0.021) in the MS group. History of ON had no impact on the association between OND and volumetric data. In conclusion, OND is a promising surrogate marker in MS, that can be simply and reliably measured using TOS, and its derived measures correspond to brain volumetric measures. It should be further explored in larger and longitudinal studies.

Real-world operation of multiple sclerosis centres in Central-Eastern European countries covering 107 million inhabitants.

BACKGROUND: In 2018 multiple sclerosis (MS) care unit (MSCU) recommendations were defined. Nevertheless, the information on MS care, and whether MS centres fulfil the international recommendation is limited. Thus our objectives were to assess whether centres meet the MSCU recommendations and gain a comprehensive overview of MS care in Central-Eastern European countries. METHODS: A self-report questionnaire assessing aspects of the MSCU recommendations, disease-modifying therapy (DMT) and registry use and the patient number was assembled and sent to nine Central-Eastern European countries. Furthermore, one Danish and one German centre were contacted as a reference. RESULTS: In 9/9 countries, MS care was pursued in centres by MS neurologists and MS nurses. In Austria and the Czech Republic, management of MS was conducted under strict regulations displaying a referral centre system, fundamentally similar to but independent of the MSCU criteria. Several centres fulfilled all aspects of the MSCU criteria, while others had similar insufficiencies consisting of a speech therapist, continence, pain and spasticity specialist, neuro-ophthalmologist, and oto-neurologist. In 9/9 countries, DMTs were reimbursed. However, some centres did not provide every available DMT. A national registry was available in 4/9 countries with mandatory registry use only in Austria and the Czech Republic. CONCLUSION: In countries where MSCU recommendations are not fulfilled, a strictly regulated centre system similar to the Austrian and Czech model with a registry-based quality control might ensure appropriate care for people with MS.

Multicenter Study on COVID-19 Lung Computed Tomography Segmentation with varying Glass Ground Opacities using Unseen Deep Learning Artificial Intelligence Paradigms: COVLIAS 1.0 Validation.

Variations in COVID-19 lesions such as glass ground opacities (GGO), consolidations, and crazy paving can compromise the ability of solo-deep learning (SDL) or hybrid-deep learning (HDL) artificial intelligence (AI) models in predicting automated COVID-19 lung segmentation in Computed Tomography (CT) from unseen data leading to poor clinical manifestations. As the first study of its kind, "COVLIAS 1.0-Unseen" proves two hypotheses, (i) contrast adjustment is vital for AI, and (ii) HDL is superior to SDL. In a multicenter study, 10,000 CT slices were collected from 72 Italian (ITA) patients with low-GGO, and 80 Croatian (CRO) patients with high-GGO. Hounsfield Units (HU) were automatically adjusted to train the AI models and predict from test data, leading to four combinations-two Unseen sets: (i) train-CRO:test-ITA, (ii) train-ITA:test-CRO, and two Seen sets: (iii) train-CRO:test-CRO, (iv) train-ITA:test-ITA. COVILAS used three SDL models: PSPNet, SegNet, UNet and six HDL models: VGG-PSPNet, VGG-SegNet, VGG-UNet, ResNet-PSPNet, ResNet-SegNet, and ResNet-UNet. Two trained, blinded senior radiologists conducted ground truth annotations. Five types of performance metrics were used to validate COVLIAS 1.0-Unseen which was further benchmarked against MedSeg, an open-source web-based system. After HU adjustment for DS and JI, HDL (Unseen AI) > SDL (Unseen AI) by 4% and 5%, respectively. For CC, HDL (Unseen AI) > SDL (Unseen AI) by 6%. The COVLIAS-MedSeg difference was < 5%, meeting regulatory guidelines.Unseen AI was successfully demonstrated using automated HU adjustment. HDL was found to be superior to SDL.

Modulation of cortical resting state functional connectivity during a visuospatial attention task in Parkinson's disease.

Visual dysfunction is a recognized early symptom of Parkinson's disease (PD) that partly scales motor symptoms, yet its background is heterogeneous. With additional deficits in visuospatial attention, the two systems are hard to disentangle and it is not known whether impaired functional connectivity in the visual cortex is translative in nature or disrupted attentional modulation also contributes. In this study, we investigate functional connectivity modulation during a visuospatial attention task in patients with PD. In total, 15 PD and 16 age-matched healthy controls performed a visuospatial attention task while undergoing fMRI, in addition to a resting-state fMRI scan. Tensorial independent component analysis was used to investigate task-related network activity patterns. Independently, an atlas-based connectivity modulation analysis was performed using the task potency method. Spearman's rank correlation was calculated between task-related network expression, connectivity modulation, and clinical characteristics. Task-related networks including mostly visual, parietal, and prefrontal cortices were expressed to a significantly lesser degree in patients with PD (p < 0.027). Resting-state functional connectivity did not differ between the healthy and diseased cohorts. Connectivity between the precuneus and ventromedial prefrontal cortex was modulated to a higher degree in patients with PD (p < 0.004), while connections between the posterior parietal cortex and primary visual cortex, and also the superior frontal gyrus and opercular cortex were modulated to a lesser degree (p < 0.001 and p < 0.011). Task-related network expression and superior frontal gyrus-opercular cortex connectivity modulation were significantly associated with UPDRSIII motor scores and the Hoehn-Yahr stages (R = -0.72, p < 0.006 and R = -0.90, p < 0.001; R = -0.68, p < 0.01 and R = -0.71, p < 0.007). Task-related networks function differently in patients with PD in association with motor symptoms, whereas impaired modulation of visual and default-mode network connectivity was not correlated with motor function.

Screening for Myocardial Injury after Mild SARS-CoV-2 Infection with Advanced Transthoracic Echocardiography Modalities.

Although the clinical manifestations of SARS-CoV-2 viral infection affect mainly the respiratory system, cardiac complications are common and are associated with increased morbidity and mortality. While echocardiographic alterations indicating myocardial involvement are widely reported in patients hospitalized for acute COVID-19 infection, much fewer data available in non-hospitalized, mildly symptomatic COVID-19 patients. In our work, we aimed to investigate subclinical cardiac alterations characterized by parameters provided by advanced echocardiographic techniques following mild SARS-CoV-2 viral infection. A total of 86 patients (30 males, age: 39.5 ± 13.0 yrs) were assessed 59 ± 33 days after mild SARS-CoV-2 viral infection (requiring no hospital or <5 days in-hospital treatment) by advanced echocardiographic examination including 2-dimensional (2D) speckle tracking echocardiography and non-invasive myocardial work analysis, and were compared to an age-and sex-matched control group. Altogether, variables from eleven echocardiographic categories representing morphological or functional echocardiographic parameters showed statistical difference between the post-COVID patient group and the control group. The magnitude of change was subtle or mild in the case of these parameters, ranging from 1−11.7% of relative change. Among the parameters, global longitudinal strain [−20.3 (−21.1−−19.0) vs. −19.1 (−20.4−−17.6) %; p = 0.0007], global myocardial work index [1975 (1789−2105) vs. 1829 (1656−2057) Hgmm%; p = 0.007] and right ventricular free wall strain values (−26.6 ± 3.80 vs. −23.8 ± 4.0%; p = 0.0003) showed the most significant differences between the two groups. Subclinical cardiac alterations are present following even mild SARS-CoV-2 viral infection. These more subtle alterations are difficult to detect by routine echocardiography. Extended protocols, involving speckle-tracking echocardiography, non-invasive measurement of cardiac hemodynamics, and possibly myocardial work are necessary for detection and adequate follow-up.

Eight pruning deep learning models for low storage and high-speed COVID-19 computed tomography lung segmentation and heatmap-based lesion localization: A multicenter study using COVLIAS 2.0.

BACKGROUND: COVLIAS 1.0: an automated lung segmentation was designed for COVID-19 diagnosis. It has issues related to storage space and speed. This study shows that COVLIAS 2.0 uses pruned AI (PAI) networks for improving both storage and speed, wiliest high performance on lung segmentation and lesion localization. METHOD: ology: The proposed study uses multicenter ∼9,000 CT slices from two different nations, namely, CroMed from Croatia (80 patients, experimental data), and NovMed from Italy (72 patients, validation data). We hypothesize that by using pruning and evolutionary optimization algorithms, the size of the AI models can be reduced significantly, ensuring optimal performance. Eight different pruning techniques (i) differential evolution (DE), (ii) genetic algorithm (GA), (iii) particle swarm optimization algorithm (PSO), and (iv) whale optimization algorithm (WO) in two deep learning frameworks (i) Fully connected network (FCN) and (ii) SegNet were designed. COVLIAS 2.0 was validated using "Unseen NovMed" and benchmarked against MedSeg. Statistical tests for stability and reliability were also conducted. RESULTS: Pruning algorithms (i) FCN-DE, (ii) FCN-GA, (iii) FCN-PSO, and (iv) FCN-WO showed improvement in storage by 92.4%, 95.3%, 98.7%, and 99.8% respectively when compared against solo FCN, and (v) SegNet-DE, (vi) SegNet-GA, (vii) SegNet-PSO, and (viii) SegNet-WO showed improvement by 97.1%, 97.9%, 98.8%, and 99.2% respectively when compared against solo SegNet. AUC > 0.94 (p < 0.0001) on CroMed and > 0.86 (p < 0.0001) on NovMed data set for all eight EA model. PAI <0.25 s per image. DenseNet-121-based Grad-CAM heatmaps showed validation on glass ground opacity lesions. CONCLUSIONS: Eight PAI networks that were successfully validated are five times faster, storage efficient, and could be used in clinical settings.

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.

Periventricular magnetisation transfer abnormalities in early multiple sclerosis.

OBJECTIVE: Recent studies suggested that CSF-mediated factors contribute to periventricular (PV) T2-hyperintense lesion formation in multiple sclerosis (MS) and this in turn correlates with cortical damage. We thus investigated if such PV-changes are observable microstructurally in early-MS and if they correlate with cortical damage. METHODS: We assessed the magnetisation transfer ratio (MTR) in PV normal-appearing white matter (NAWM) and in MS lesions in 44 patients with a clinically isolated syndrome (CIS) suggestive of MS and 73 relapsing-remitting MS (RRMS) patients. Band-wise MTR values were related to cortical mean thickness (CMT) and compared with 49 healthy controls (HCs). For each band, MTR changes were assessed relative to the average MTR values of all HCs. RESULTS: Relative to HCs, PV-MTR was significantly reduced up to 2.63% in CIS and 5.37% in RRMS (p < 0.0001). The MTR decreased towards the lateral ventricles with 0.18%/mm in CIS and 0.31%/mm in RRMS patients, relative to HCs. In RRMS, MTR-values adjacent to the ventricle and in PV-lesions correlated positively with CMT and negatively with EDSS. CONCLUSION: PV-MTR gradients are present from the earliest stage of MS, consistent with more pronounced microstructural WM-damage closer to the ventricles. The positive association between reduced CMT and lower MTR in PV-NAWM suggests a common pathophysiologic mechanism. Together, these findings indicate the potential use of multimodal MRI as refined marker for MS-related tissue changes.

Do Hungarian multiple sclerosis care units fulfil international criteria?

A PATIENTS: Because of the past 3 decades' extensive research, several disease modifying therapies became available, thus a paradigm change is multiple sclerosis care was necessary. In 2018 a therapeutic guideline was created recommending that treatment of persons with multiple sclerosis should take place in specified care units where the entire spectrum of disease modifying therapies is available, patient monitoring is ensured, and therapy side effects are detected and treated promptly. In 2019 multiple sclerosis care unit criteria were developed, emphasizing personnel and instrumental requirements to provide most professional care. However, no survey was conducted assessing the real-world adaptation of these criteria. OBJECTIVE: To assess whether Hungarian care units fulfil international criteria. METHODS: A self-report questionnaire was assembled based on international guidelines and sent to Hungarian care units focusing on 3 main aspects: personnel and instrumental background, disease-modifying therapy use, number of people living with multiple sclerosis receiving care in care units. Data on number of persons with multiple sclerosis were compared to Hungarian prevalence estimates. Descriptive statistics were used to analyse data. RESULTS: Out of 27 respondent care units, 3 fulfilled minimum requirements and 7 fulfilled minimum and recommended requirements. The least prevalent neighbouring specialties were spasticity and pain specialist, and neuro-ophthalmologist and oto-neurologist. Only 15 centres used all available disease modifying therapies. A total number of 7213 people with multiple sclerosis received care in 27 respondent centres. Compared to prevalence estimates, 2500 persons with multiple sclerosis did not receive multiple sclerosis specific care in Hungary. CONCLUSION: Less than half of Hungarian care units provided sufficient care for people living with multiple sclerosis. Care units employing fewer neighbouring specialties, might have difficulties diagnosing and providing appropriate care for persons with multiple sclerosis, especially for people with progressive disease course, contributing to the reported low number of persons living with multiple sclerosis.

Connection between microstructural alterations detected by diffusion MRI and cognitive dysfunction in MS: A model-free analysis approach.

BACKGROUND: Cognitive decline is a prominent symptom of MS. Clear connection between cognitive status and white matter microstructural changes has not been unequivocally observed to date. OBJECTIVE: To characterise the relationship between white matter microstructure and cognitive performance a partial least squares (PLS) approach was used. METHODS: 53 RR MS patients' T1 and DTI images and BICAMS subtests were used in our analysis. Standard FSL pipeline was used to obtain diffusion parameters. A PLS approach was applied to reveal the diffusion parameter patterns responsible for the cognitive dysfunction. RESULTS: The first latent variable (LV) was mainly associated with demyelination, while the second and third explained axonal damage. While the first two LV represented mainly Brief Visuospatial Memory Test (BVMT) and Single Digit Modality Test (SDMT), the third LV depicted diffusion alterations mainly the verbal subtest. The first LVs spatial map showed demyelination in the corpus callosum. The second LVs spatial map showed the diffusion alterations in the thalamus. The third LV depicted diffusion alterations in the putative left superior longitudinal fascicle. CONCLUSION: Visual memory demanding tasks versus language functions depend on distinct patterns of diffusion parameters and the spatial organisation. Axial diffusivity alterations, a putative marker of irreversible axonal loss explained around 20% of variability in the cognitive functions.

Functional Connectivity Lateralisation Shift of Resting State Networks is Linked to Visuospatial Memory and White Matter Microstructure in Relapsing-Remitting Multiple Sclerosis.

Laterality patterns of resting state networks (RSN) change in various neuropsychiatric conditions. Multiple sclerosis (MS) causes neuro-cognitive symptoms involving dysfunctional large-scale brain networks. Yet, whether healthy laterality patterns of RSNs are maintained in MS and whether altered laterality patterns explain disease symptoms has not been explicitly investigated. We analysed functional MRI and diffusion tensor imaging data from 24 relapsing-remitting MS patients and 25 healthy participants. We performed group-level independent component analysis and used dual regression to estimate individual versions of well-established RSNs. Voxelwise laterality indices were calculated for each RSN. Group differences were assessed via a general linear model-based approach. The relationship between functional laterality and white matter microstructural asymmetry was assessed using Tract-Based Spatial Statistics. Spearman's correlation was calculated between laterality indices and Brief International Cognitive Assessment for Multiple Sclerosis scores. Functional laterality of the dorsal attention network showed a significant leftward shift in the MS group in the posterior intraparietal sulcus (p < 0.033). Default-mode network laterality showed a significant leftward shift in the MS group in the angular gyrus (p < 0.005). Diminished dorsal attention network laterality was associated with increased fractional anisotropy asymmetry in the superior longitudinal fasciculus (p < 0.02). In the default-mode network, leftward laterality of the angular gyrus was associated with higher BVMT-R scores (R = - 0.52, p < 0.023). Our results confirm previous descriptions of RSN dysfunction in relapsing-remitting MS and show that altered functional connectivity lateralisation patterns of RSNs might contibute to cognitive performance and structural remodellation even in patients with mild clinical symptoms.

Resting-state functional heterogeneity of the right insula contributes to pain sensitivity.

Previous studies have described the structure and function of the insular cortex in terms of spatially continuous gradients. Here we assess how spatial features of insular resting state functional organization correspond to individual pain sensitivity. From a previous multicenter study, we included 107 healthy participants, who underwent resting state functional MRI scans, T1-weighted scans and quantitative sensory testing on the left forearm. Thermal and mechanical pain thresholds were determined. Connectopic mapping, a technique using non-linear representations of functional organization was employed to describe functional connectivity gradients in both insulae. Partial coefficients of determination were calculated between trend surface model parameters summarizing spatial features of gradients, modal and modality-independent pain sensitivity. The dominant connectopy captured the previously reported posteroanterior shift in connectivity profiles. Spatial features of dominant connectopies in the right insula explained significant amounts of variance in thermal (R2 = 0.076; p < 0.001 and R2 = 0.031; p < 0.029) and composite pain sensitivity (R2 = 0.072; p < 0.002). The left insular gradient was not significantly associated with pain thresholds. Our results highlight the functional relevance of gradient-like insular organization in pain processing. Considering individual variations in insular connectopy might contribute to understanding neural mechanisms behind pain and improve objective brain-based characterization of individual pain sensitivity.