Indications For Magnetic Resonance Imaging Research Articles

Association between Autism Spectrum Disorder, Trace Elements, and Intracranial Fluid Spaces.

(1) Autism spectrum disorder (ASD) belongs to the group of complex developmental disorders. Novel studies have suggested that genetic and environmental factors equally affect the risk of ASD. Identification of environmental factors involved in the development of ASD is therefore crucial for a better understanding of its etiology. Whether there is a causal link between trace elements, brain magnetic resonance imaging (MRI), and ASD remains a matter of debate and requires further studies. (2) In the prospective part of the study, we included 194 children, including an age-matched control group; in the retrospective study, 28 children with available MRI imaging were included. All children had urine analysis of trace elements performed. In those with available brain MRI, linear indexes for the ventricular volumes were measured and calculated. (3) We found the highest vanadium, rubidium, thallium, and silver levels in children with ASD. These elements also correlated with the estimated ventricular volume based on MRI indexes in children with ASD in the subanalysis. However, the severity of the deficits did not correlate with brain MRI indexes of our elements, except negatively with magnesium. (4) Trace elements have an impact on children with ASD, but further multi-centric studies are needed to explain the pathophysiological mechanisms.

Outcomes of myocarditis in systemic sclerosis: A 3-year follow-up.

The clinical course, the outcomes of myocarditis, and the imaging progression of cardiac magnetic resonance imaging (MRI) in systemic sclerosis (SSc) are still unknown. We aimed at defining changes in cardiac MRI findings, the clinical course, and the outcomes of SSc patients previously defined as having myocarditis by cardiac MRI. Methods: This prospective cohort study included SSc patients, who had previously been diagnosed with myocarditis through cardiac MRI at the Scleroderma Clinic of Khon Kaen University, between 2018 and 2020 and had had annual follow-ups of cardiac MRI for at least 3 years. Data on demographics, clinical characteristics, cardiac MRI findings, treatment regimens, and outcomes were collected. Serial cardiac MRI on a yearly basis was analyzed to assess changes in myocardial involvement over the 3-year period. Ten SSc patients diagnosed with myocarditis via cardiac MRI were included. Most belonged to the diffuse cutaneous subset with a mean age of 58.3±8.6 years and were mildly symptomatic. Initial cardiac MRI findings showed myocardial edema and hyperemia in all patients and eight patients had had pre-existing myocardial scars, suggesting disease chronicity. Treatment for concomitant interstitial lung disease involved steroids with either cyclophosphamide or mycophenolate mofetil in 6 patients. Outcomes of myocarditis were stable, improving, and worsening in 4, 4, and 2 patients, respectively. There was no complete resolution of the cardiac MRI indices for myocarditis, and none had had major cardiac events. Although SSc myocarditis on cardiac MRI may improve or show stability, the changes remained persistent. Among patients with SSc and mildly symptomatic myocarditis, the efficacy of steroids and immunosuppressive therapy is inconclusive. Over a 3-year follow-up, the prognosis had been acceptably good with no cardiac events.

Spatiotemporal Dynamics of Neuroinflammation Relate to Behavioral Recovery in Rats with Spinal Cord Injury.

The degree and dynamic progression of neuroinflammation after traumatic spinal cord injuries (SCI) are crucial determinants of the severity of injury and potential for recovery. We used Positron Emission Tomography (PET) to monitor neuroinflammation longitudinally, correlating it with Chemical Exchange Saturation Transfer (CEST) Magnetic Resonance Imaging (MRI) and behavior in contusion-injured rats. These studies help validate CEST metrics and confirm how imaging may be used to evaluate the efficacy of therapies and understand their mechanisms of action. 12 SCI and 4 sham surgery rats were subjected to CEST MRI and PET-Translocator Protein (TSPO) scans for 8weeks following injury. Z-spectra from the SCI were analyzed using a 5-Lorentzian pool model for fitting. Weekly motor and somatosensory behavior were correlated with imaging metrics, which were validated through post-mortem histological and immuo-staining using ionized calcium-binding adaptor protein-1 (iba-1, microglia) and glial fibrillary acidic protein (GFAP, astrocytes). PET-TSPO showed widespread inflammation and post-mortem histology confirmed the presence of activated microglia. Changes in CEST and nuclear Overhauser Effect (NOE) peaks at 3.5ppm and -1.6ppm respectively were largest within the first week after injury and more pronounced in rostral versus caudal segments. These temporal indices of neuroinflammation corresponded to the recovery of locomotor behaviors and somatic sensation in rats with moderate contusion injury. The results confirm that CEST MRI metrics are sensitive indices of states of neuroinflammation within injured spinal cords. The detection of dynamic spatiotemporal features of neuroinflammation progression underscores the importance of considering their timings and locations for neuroprotective and anti-inflammatory therapies. The availability of noninvasive MRI indices of neuroinflammation may facilitate clinical trials aimed at treatments that promote recovery after SCI.

Male spondyloarthritis patients and those with longer disease duration have less severe disc degeneration: propensity score-matched comparison.

Using whole spine sagittal T2 MRI, we aimed to compare the severity and prevalence of disc degeneration (DD) in axial SpA patients vs the general population and to determine any association between spinal inflammation, structural changes, mobility and DD among SpA patients. Two prospectively collected cohorts of SpA patients (n = 411) and the general population (n = 2007) were recruited. Eventually, 967 participants from the populational cohort and 304 participants from the SpA cohort were analysed. Two hundred and nineteen matched pairs were generated by propensity score matching. Imaging parameters, including Pfirrmann grading, disc herniation, high-intensity zone, Schmorl's node, Modic change and anterior marrow change were studied and compared from C2/3 to L5/S1. DD was defined as Pfirrmann grade 4 or 5. Demographic factors, including age, sex and BMI, were collected. Multivariable linear regression was used to determine the association between spinal inflammation [Spondyloarthritis Research Consortium of Canada (SPARCC) spine MRI index], structural changes [modified Stoke Ankylosing Spondylitis Spinal Score (mSASSS)] and mobility (BASMI) with lumbar Pfirrmann score. SpA patients had lower prevalence of DD (P < 0.001). The disease stage-stratified regression model showed that SPARCC spinal MRI index was associated with higher lumbar Pfirrmann scores in early disease (β = 0.196, P = 0.044), whereas mSASSS was associated with lower lumbar Pfirrmann scores in later disease (β = -0.138, P = 0.038). Males had higher mSASSS (P < 0.001) and lower odds of whole spine DD (odds ratio = 0.622, P = 0.028). SpA patients had lower DD severity than the general population. Males had higher mSASSSs, and increased mSASSS at later disease was associated with less severe DD.

The correlation of conventional and advanced MRI findings with cognitive function in multiple sclerosis: A systematic review and meta-analysis

There are limited data on the possible association between conventional and advanced magnetic resonance imaging (MRI) findings and cognitive function in patients with multiple sclerosis (MS). Therefore, this systematic review and meta-analysis aimed to explore the correlation between MRI-derived metrics and cognitive tests in patients with MS. An electronic literature search of the PubMed, Web of Sciences, Embase, and Scopus databases was performed to identify related studies. The correlation coefficients of the MRI indices and cognitive tests were pooled. Thirteen studies were selected for inclusion of 824 patients diagnosed with MS. Most evaluated patients (60.44%) had relapsing-remitting MS (RRMS). The Paced Auditory Serial Addition Test (PASAT-3), Brief Visuospatial Memory Test (BVMT), and Symbol Digit Modalities Test (SDMT) were inversely correlated with the mean diffusivity (MD) of the brain with pooled correlation coefficient of -0.225, -0.361, and -0.438, respectively (P&lt;0.0001). The SDMT test positively correlated with fractional anisotropy (FA) with a correlation coefficient of 0.351 (P&lt;0.0001) and inversely correlated with T2 lesion volume with a correlation coefficient of -0.367 (P&lt;0.0001). In the case of other tests, there was low number of studies with significant correlations being reported. We found significant correlations between some neuropsychological tests and MRI findings in patients with MS. Brain atrophy might disrupt the process of correct registration between anatomical and MRI diffusion scans. However, we did not have enough studies with exactly matched anatomical areas to evaluate correlations and we recommend that histological validation of diffusion tensor imaging (DTI) findings for brain atrophy is needed as a basis for picture processing procedures and correlation with cognition status.

Functional and structural MRI based obsessive-compulsive disorder diagnosis using machine learning methods

BackgroundThe success of neuroimaging in revealing neural correlates of obsessive-compulsive disorder (OCD) has raised hopes of using magnetic resonance imaging (MRI) indices to discriminate patients with OCD and the healthy. The aim of this study was to explore MRI based OCD diagnosis using machine learning methods.MethodsFifty patients with OCD and fifty healthy subjects were allocated into training and testing set by eight to two. Functional MRI (fMRI) indices, including amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo), degree of centrality (DC), and structural MRI (sMRI) indices, including volume of gray matter, cortical thickness and sulcal depth, were extracted in each brain region as features. The features were reduced using least absolute shrinkage and selection operator regression on training set. Diagnosis models based on single MRI index / combined MRI indices were established on training set using support vector machine (SVM), logistic regression and random forest, and validated on testing set.ResultsSVM model based on combined fMRI indices, including ALFF, fALFF, ReHo and DC, achieved the optimal performance, with a cross-validation accuracy of 94%; on testing set, the area under the receiver operating characteristic curve was 0.90 and the validation accuracy was 85%. The selected features were located both within and outside the cortico-striato-thalamo-cortical (CSTC) circuit of OCD. Models based on single MRI index / combined fMRI and sMRI indices underperformed on the classification, with a largest validation accuracy of 75% from SVM model of ALFF on testing set.ConclusionSVM model of combined fMRI indices has the greatest potential to discriminate patients with OCD and the healthy, suggesting a complementary effect of fMRI indices on the classification; the features were located within and outside the CSTC circuit, indicating an importance of including various brain regions in the model.

A cross-comparative analysis of in vivo versus ex vivo MRI indices in a mouse model of concussion

BackgroundWe present a cross-sectional, case-matched, and pair-wise comparison of structural magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), and neurite orientation dispersion and density imaging (NODDI) measures in vivo and ex vivo in a mouse model of concussion, thus aiming to establish the concordance of structural and diffusion imaging findings in living brain and after fixation. MethodsWe allocated 28 male mice aged 3–4 months to sham injury and concussion (CON) groups. CON mice had received a single concussive impact on day 0 and underwent MRI at day 2 (n = 9) or 7 (n = 10) post-impact, and sham control mice likewise underwent imaging at day 2 (n = 5) or 7 (n = 4). Immediately after the final scanning, we collected the perfusion-fixed brains, which were stored for imaging ex vivo 6–12 months later. We then compared the structural imaging, DTI, and NODDI results between different methods. ResultsIn vivo to ex vivo structural and DTI/NODDI findings were in notably poor agreement regarding the effects of concussion on structural integrity of the brain.Comparison with existing methods:ex vivo imaging was frequently done to study the effects of diseases and treatments, but our results showed that ex vivo and in vivo imaging can detect completely opposite and contradictory results. This is also the first study that compares in vivo and ex vivo NODDI. ConclusionOur findings call for caution in extrapolating translational capabilities obtained ex vivo to physiological measurements in vivo. The divergent findings may reflect fixation artefacts and the contribution of the glymphatic system changes.

Value of pelvic ultrasound combined with pituitary MRI in diagnosis of central precocious puberty in girls.

This study aimed to investigate the value of pelvic ultrasound combined with pituitary magnetic resonance imaging (MRI) based on an artificial intelligence algorithm in the diagnosis of girls with central precocious puberty (CPP), providing reference for the prevention and control of CPP in girls. 75 girls with CPP and 75 normal girls in Nantong First People's Hospital were studied. Pelvic ultrasound parameters were compared between the two groups based on an artificial intelligence algorithm. Pituitary MRI parameters were analyzed, and pituitary function parameters were explored. The results showed that the diagnostic sensitivity, specificity, and accuracy of the convolutional neural network (CNN) algorithm were 72.3%, 74.6%, and 78.3%, respectively. The sensitivity, specificity, and accuracy of CNN algorithm were significantly higher (p<0.05). The long diameter, anteroposterior diameter, and transverse diameter of the uterus in the precocious puberty (PP) group were significantly larger than those in the normal group (NG). The ovarian long diameter, ovarian anteroposterior diameter, and ovarian transverse diameter in PP group were significantly larger than those in NG. Uterine volume and ovarian volume in PP group were clearly higher than those in NG. The largest follicle diameter was clearly larger in PP patients than in NG patients. The coronal height, coronal width, sagittal height, and sagittal anteroposterior diameter of PP group were clearly higher than those of NG (p<0.05). The sagittal cross-sectional area of pituitary MRI morphology in PP group was significantly greater than that in NG. The pituitary MRI morphology pituitary volume was 272.68 mm in PP group and 191.37 mm in NG, and the pituitary volume was clearly larger in PP group than in NG. The pituitary function parameters estradiol (E2), luteinizing hormone (LH) peak, follicle-stimulating hormone (FSH) peak, and LH peak/FSH peak were greater in PP group than in NG. In summary, the uterine size and ovarian size of girls and the pituitary function index in PP group were larger. Pelvic ultrasound and pituitary MRI indexes can better diagnose CPP and can be widely used in clinical practice with positive diagnostic value.

Patterns of Regional Brain Atrophy and Brain Aging in Middle- and Older-Aged Adults With Type 1 Diabetes

Little is known about structural brain changes in type 1 diabetes (T1D) and whether there are early manifestations of a neurodegenerative condition like Alzheimer disease (AD) or evidence of premature brain aging. To evaluate neuroimaging markers of brain age and AD-like atrophy in participants with T1D in the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) study, identify which brain regions are associated with the greatest changes in patients with T1D, and assess the association between cognition and brain aging indices. This cohort study leveraged data collected during the combined DCCT (randomized clinical trial, 1983-1993) and EDIC (observational study, 1994 to present) studies at 27 clinical centers in the US and Canada. A total of 416 eligible EDIC participants and 99 demographically similar adults without diabetes were enrolled in the magnetic resonance imaging (MRI) ancillary study, which reports cross-sectional data collected in 2018 to 2019 and relates it to factors measured longitudinally in DCCT/EDIC. Data analyses were performed between July 2020 and April 2022. T1D diagnosis. Psychomotor and mental efficiency were evaluated using verbal fluency, digit symbol substitution test, trail making part B, and the grooved pegboard. Immediate memory scores were derived from the logical memory subtest of the Wechsler memory scale and the Wechsler digit symbol substitution test. MRI and machine learning indices were calculated to predict brain age and quantify AD-like atrophy. This study included 416 EDIC participants with a median (range) age of 60 (44-74) years (87 of 416 [21%] were older than 65 years) and a median (range) diabetes duration of 37 (30-51) years. EDIC participants had consistently higher brain age values compared with controls without diabetes, indicative of approximately 6 additional years of brain aging (EDIC participants: β, 6.16; SE, 0.71; control participants: β, 1.04; SE, 0.04; P < .001). In contrast, AD regional atrophy was comparable between the 2 groups. Regions with atrophy in EDIC participants vs controls were observed mainly in the bilateral thalamus and putamen. Greater brain age was associated with lower psychomotor and mental efficiency among EDIC participants (β, -0.04; SE, 0.01; P < .001), but not among controls. The findings of this study suggest an increase in brain aging among individuals with T1D without any early signs of AD-related neurodegeneration. These increases were associated with reduced cognitive performance, but overall, the abnormal patterns seen in this sample were modest, even after a mean of 38 years with T1D.

Topography of associations between cardiovascular risk factors and myelin loss in the ageing human brain

Our knowledge of the mechanisms underlying the vulnerability of the brain’s white matter microstructure to cardiovascular risk factors (CVRFs) is still limited. We used a quantitative magnetic resonance imaging (MRI) protocol in a single centre setting to investigate the cross-sectional association between CVRFs and brain tissue properties of white matter tracts in a large community-dwelling cohort (n = 1104, age range 46–87 years). Arterial hypertension was associated with lower myelin and axonal density MRI indices, paralleled by higher extracellular water content. Obesity showed similar associations, though with myelin difference only in male participants. Associations between CVRFs and white matter microstructure were observed predominantly in limbic and prefrontal tracts. Additional genetic, lifestyle and psychiatric factors did not modulate these results, but moderate-to-vigorous physical activity was linked to higher myelin content independently of CVRFs. Our findings complement previously described CVRF-related changes in brain water diffusion properties pointing towards myelin loss and neuroinflammation rather than neurodegeneration.

Reliability and validity of quantitative ultrasound for evaluating patellar alignment: A pilot study

BackgroundPatellar malalignment is a risk factor of patellofemoral pain. Evaluation of the patellar alignment have mostly used magnetic resonance imaging (MRI). Ultrasound (US) is a non-invasive instrument that can quickly evaluate patellar alignment. However, the method for evaluating patellar alignment via US has not been established. This study aimed to investigate the reliability and validity of evaluating patellar alignment via US. MethodsThe sixteen right knees were imaged via US and MRI. US images were obtained at two sites of the knee to measure US-tilt as the index of patellar tilt. Using a single US image, we measured US-lateral distance and US-angle as the index of patellar shift. All US images were obtained three times each by two observers to evaluate reliabilities. Lateral patellar angle (LPA), as the indicators of patellar tilt, and lateral patella distance (LPD) and bisect offset (BO), as the indicators of patellar shift, were measured via MRI. ResultsUS measurements provided high intra- (within-day and between days) and interobserver reliabilities with exception of interobserver reliability of US-lateral distance. Pearson correlation coefficient indicated that US-tilt is significantly positively correlated with LPA (r = 0.79), and US-angle is significantly positively correlated with LPD (r = 0.71) and BO (r = 0.63). ConclusionEvaluating patellar alignment via US showed high reliabilities. US-tilt and US-angle showed moderate to strong correlation with MRI indices of patellar tilt and shift via MRI, respectively. US methods are useful for evaluating accurate and objective indices of patellar alignment.

Muscle Health Patterns and Brain MRI Indices: A Cluster Analysis.

The interplay between muscle and brain lacks a holistic approach to assess the combined effect of multiple factors. This study utilizes clustering analysis to identify muscle health patterns and their relationships with various brain magnetic resonance imaging (MRI) indices. Two hundred and seventy-five cognitively intact participants who completed brain MRI from the Health, Aging, and Body Composition Study were enrolled. Muscle health-related markers that showed significant relationship with total gray matter volume entered the cluster analysis. Subsequently, macrostructural and microstructural MRI indices were examined with analysis of variance and multiple linear regression analysis to determine significant associations with muscle health clusters. The muscle health cluster included 6 variables: age, skeletal muscle mass index, gait speed, handgrip strength, change of total body fat, and serum leptin level. Clustering method produced 3 clusters which had characteristics of obese, leptin-resistant, and sarcopenia, respectively. Brain MRI indices that revealed significant associations with the clusters included gray matter volume (GMV) in cerebellum (p < .001), superior frontal gyrus (p = .019), inferior frontal gyrus (p = .003), posterior cingulum (p = .021), vermis (p = .045), and gray matter density (GMD) in gyrus rectus (p < .001) and temporal pole (p < .001). The leptin-resistant group had most degree of reduction in GMV, whereas the sarcopenia group had most degree of reduction in GMD. The leptin-resistant and sarcopenia populations had higher risk of neuroimaging alterations. Clinicians should raise awareness on the brain MRI findings in clinical settings. Because these patients mostly had central nervous system conditions or other critical illnesses, the risk of sarcopenia as a comorbidity will substantially affect the prognosis and medical care.

Optimizing multiparametric magnetic resonance imaging-targeted biopsy and detection of clinically significant prostate cancer: the role of perilesional sampling.

The added-value of systematic biopsy (SB) in patients undergoing magnetic resonance imaging(MRI)-targeted biopsy(TB) remains unclear and the spatial distribution of positive cores relative to the MRI lesion has been poorly studied. The aim of this study was to determine the utility of perilesional biopsy in detecting clinically significant prostate cancer(csPCa). We enrolled 505 consecutive patients that underwent SB and TB for suspicious MRI lesions (PI-RADS score 3-5) at Jules Bordet Institute between June 2016 and January 2022. Patient-specific tridimensional prostate maps were reviewed to determine the distance between systematic cores containing csPCa and the MRI index lesion. Primary outcomes were the cancer detection rate (CDR) per patient and the cumulative cancer distribution rate of positive cores for each 5 mm interval from the MRI index lesion. The secondary outcome was the identification of risk groups for the presence of csPCa beyond a 10 mm margin using the chi-square automated interaction detector (CHAID) machine learning algorithm. Overall, the CDR for csPCa of TB, SB, and combined method were 32%, 25%, and 37%, respectively. While combined method detected more csPCa compared to TB (37% vs. 32%, p < 0.001), no difference was found when TB was associated with perilesional sampling within 10 mm (37% vs. 35%, p = 0.2). The cumulative cancer distribution rate for csPCa reached 86% for the 10 mm margin. The CHAID algorithm identified three risk groups: (1) PI-RADS3 ("low-risk"), (2) PI-RADS4 or PI-RADS5 and PSA density<0.15 ng/ml ("intermediate-risk"), and (3) PI-RADS 5 and PSA density≥0.15 ng/ml ("high-risk"). The risk of missing csPCa was 2%, 8%, and 29% for low-, intermediate- and high-risk groups, respectively. Avoiding biopsies beyond a 10 mm margin prevented the detection of 19% of non-csPCa. Perilesional biopsy template using a 10 mm margin seems a reasonable alternative to the combined method with a comparable detection of csPCa. Our risk stratification may further enhance the selection of patients.

Left Ventricle Wall Motion Analysis with Real-Time MRI Feature Tracking in Heart Failure Patients: A Pilot Study.

Volumetric measurements with cardiac magnetic resonance imaging (MRI) are effective for evaluating heart failure (HF) with systolic dysfunction that typically induces a lower ejection fraction (EF) than normal (&lt;50%) while they are not sensitive to diastolic dysfunction in HF patients with preserved EF (≥50%). This work is to investigate whether HF evaluation with cardiac MRI can be improved with real-time MRI feature tracking. In a cardiac MRI study, we recruited 16 healthy volunteers, 8 HF patients with EF &lt; 50% and 10 HF patients with preserved EF. Using real-time feature tracking, a cardiac MRI index, torsion correlation, was calculated which evaluated the correlation of torsional and radial wall motion in the left ventricle (LV) over a series of sequential cardiac cycles. The HF patients with preserved EF and the healthy volunteers presented significant difference in torsion correlation (one-way ANOVA, p &lt; 0.001). In the scatter plots of EF against torsion correlation, the HF patients with EF &lt; 50%, the HF patients with preserved EF and the healthy volunteers were well differentiated, indicating that real-time MRI feature tracking provided LV function assessment complementary to volumetric measurements. This study demonstrated the potential of cardiac MRI for evaluating both systolic and diastolic dysfunction in HF patients.

Association of impaired lung function with dementia, and brain magnetic resonance imaging indices: a large population-based longitudinal study.

to examine the association between different patterns of impaired lung function with the incident risk of dementia and magnetic resonance imaging (MRI)-based brain structural features. in UK Biobank, a total of 308,534 dementia-free participants with valid lung function measures (forced expiratory volume in 1 s [FEV1] and forced vital capacity [FVC]) were included. Association was assessed using Cox proportional hazards regression model. Furthermore, the association between impaired lung function and brain MRI biomarkers related to cognitive function was analysed among 30,159 participants. during a median follow-up of 12.6years, 3,607 incident all-cause dementia cases were recorded. Restrictive impairment (hazard ratio [HR], 1.42; 95% confidence interval [CI], 1.27-1.60) and obstructive impairment (HR, 1.28; 95% CI, 1.15-1.42) were associated with higher risk of all-cause dementia. The restricted cubic splines indicated FEV1% predicted and FVC % predicted had reversed J-shaped associations with dementia. Participants with impaired lung function have higher risks of all-cause dementia across all apolipoprotein E (APOE) risk categories, whereas associations were stronger among those of low APOE risk (P for interaction = 0.034). In addition, restrictive and obstructive impairment were linked to lower total (β: -0.075, SE: 0.021, Pfdr = 0.002; β: -0.033, SE: 0.017, Pfdr = 0.069) and frontoparietal grey matter volumes, higher white matter hyperintensity, poorer white matter integrity, lower hippocampus (β: -0.066, SE: 0.024, Pfdr = 0.017; β: -0.051, SE: 0.019, Pfdr = 0.019) and other subcortical volumes. participants with restrictive and obstructive impairments had a higher risk of dementia. Brain MRI indices further supported adverse effects and provided insight into potential pathophysiology biomarkers.

Association of Dilated Perivascular Spaces With Lipid Indices in Ischemic Stroke Patients.

BackgroundDilated perivascular spaces (dPVS) in the basal ganglia are associated with aging, vascular risk factors, and other magnetic resonance imaging (MRI) markers of cerebral small vessel disease (cSVD). While high blood lipids are a well-demonstrated risk factor for large artery atherosclerosis, their role in cSVD remains largely elusive.MethodsWe evaluated lipid profiles, cardiovascular risk factors, and brain MRI findings in patients with ischemic stroke or transient ischemic attack. We analyzed the extent of dPVS, cerebral microbleed (CMB), and cerebral white matter hyperintensities (WMHs) as MRI indices of cSVD and investigated associations of dPVS with lipid parameters and other cSVD indices.ResultsOur study enrolled 173 patients with ischemic stroke or transient ischemic attack. The mean age was 68.38±14.31 (range 35-99) years, and 57.8% (n=100) of patients were male. dPVSwere detected in 97% (n=168) of the patients. Among the whole population, half of the patients (n=87) had moderate to severe dPVS. According to the univariate analysis, age, hypertension, previous antiaggregant and/or anticoagulant use, and the high-density lipoprotein to low-density lipoprotein (HDL/LDL) ratio but not other lipid profiles, cerebral microbleed load, and cerebral white matter hyperintensities severity were found to be positively associated with dPVS number in the basal ganglia. After multivariate logistic regression analysis, only age and WMH severity remained statistically significant.ConclusionsdPVS are closely associated with other cSVD subtypes and aging. The studied lipid indices were not independently associated with moderate to severe dPVS in basal ganglia in ischemic stroke patients. The association of each lipid and HDL/LDL ratio needs to be further studied with a larger number of participants.

Diagnostic accuracy of magnetic resonance imaging for nerve injury in obstetric brachial plexus injury: protocol for systematic review and meta-analysis

BackgroundEarly and accurate clinical diagnosis of the extent of obstetric brachial plexus injury (OBPI) is challenging. The current gold standard for delineating the nerve injury is surgical exploration, and synchronous reconstruction is performed if indicated. Magnetic resonance imaging (MRI) is a non-invasive method of assessing the anatomy and severity of nerve injury in OBPI but the diagnostic accuracy is unclear.The primary objective of this review is to determine the diagnostic accuracy of MRI in comparison to surgical brachial plexus exploration for detecting root avulsion in children under 5 with OBPI. The secondary objectives are to determine its’ diagnostic accuracy for detecting nerve abnormality and detecting pseudomeningocele(s) in this group.MethodsThis review will be conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA).We will include studies reporting the accuracy of MRI (index test) compared to surgical exploration (reference standard) in detecting any of the three target conditions (root avulsion, any nerve abnormality and pseudomeningocele) in children under five with OBPI. Case reports and studies where the number of true positives, false positives, true negatives and false negatives cannot be derived will be excluded. We plan to search PubMed, Embase and CENTRAL for relevant studies from database inception to 15 June 2022. We will also search grey literature (medRxiv, bioRxiv and Google Scholar) and perform forward and backward citation chasing. Screening and full-text assessment of eligibility will be conducted by two independent reviewers, who will then both extract the relevant data. The QUADAS-2 tool will be used to assess methodological quality and risk of bias of included studies by two reviewers independently. The following test characteristics for the target conditions will be extracted: true positives, false positives, true negatives and false negatives. Estimates of sensitivity and specificity with 95% confidence intervals will be shown in forest plots for each study. If appropriate, summary sensitivities and specificities for target conditions will be obtained via meta-analyses using a bivariate model.DiscussionThis study will aim to clarify the diagnostic accuracy of MRI for detecting nerve injury in OBPI and define its clinical role.Systematic review registrationPROSPERO CRD42021267629.

Multimodal MRI-Based Whole-Brain Assessment in Patients In Anoxoischemic Coma by Using 3D Convolutional Neural Networks

BackgroundThere is an unfulfilled need to find the best way to automatically capture, analyze, organize, and merge structural and functional brain magnetic resonance imaging (MRI) data to ultimately extract relevant signals that can assist the medical decision process at the bedside of patients in postanoxic coma. We aimed to develop and validate a deep learning model to leverage multimodal 3D MRI whole-brain times series for an early evaluation of brain damages related to anoxoischemic coma.MethodsThis proof-of-concept, prospective, cohort study was undertaken at the intensive care unit affiliated with the University Hospital (Toulouse, France), between March 2018 and May 2020. All patients were scanned in coma state at least 2 days (4 ± 2 days) after cardiac arrest. Over the same period, age-matched healthy volunteers were recruited and included. Brain MRI quantification encompassed both “functional data” from regions of interest (precuneus and posterior cingulate cortex) with whole-brain functional connectivity analysis and “structural data” (gray matter volume, T1-weighted, fractional anisotropy, and mean diffusivity). A specifically designed 3D convolutional neuronal network (CNN) was created to allow conscious state discrimination (coma vs. controls) by using raw MRI indices as the input. A voxel-wise visualization method based on the study of convolutional filters was applied to support CNN outcome. The Ethics Committee of the University Teaching Hospital of Toulouse, France (2018-A31) approved the study and informed consent was obtained from all participants.ResultsThe final cohort consisted of 29 patients in postanoxic coma and 34 healthy volunteers. Coma patients were successfully discerned from controls by using 3D CNN in combination with different MR indices. The best accuracy was achieved by functional MRI data, in particular with resting-state functional MRI of the posterior cingulate cortex, with an accuracy of 0.96 (range 0.94–0.98) on the test set from 10-time repeated tenfold cross-validation. Even more satisfactory performances were achieved through the majority voting strategy, which was able to compensate for mistakes from single MR indices. Visualization maps allowed us to identify the most relevant regions for each MRI index, notably regions previously described as possibly being involved in consciousness emergence. Interestingly, a posteriori analysis of misclassified patients indicated that they may present some common functional MRI traits with controls, which suggests further favorable outcomes.ConclusionsA fully automated identification of clinically relevant signals from complex multimodal neuroimaging data is a major research topic that may bring a radical paradigm shift in the neuroprognostication of patients with severe brain injury. We report for the first time a successful discrimination between patients in postanoxic coma patients from people serving as controls by using 3D CNN whole-brain structural and functional MRI data.Clinical Trial Numberhttp://ClinicalTrials.gov (No. NCT03482115).

A novel MRI index for paraspinal muscle fatty infiltration: reliability and relation to pain and disability in lumbar spinal stenosis: results from a multicentre study

BackgroundFatty infiltration of the paraspinal muscles may play a role in pain and disability in lumbar spinal stenosis. We assessed the reliability and association with clinical symptoms of a method for assessing fatty infiltration, a simplified muscle fat index (MFI).MethodsPreoperative axial T2-weighted magnetic resonance imaging (MRI) scans of 243 patients aged 66.6 ± 8.5 years (mean ± standard deviation), 119 females (49%), with symptomatic lumbar spinal stenosis were assessed. Fatty infiltration was assessed using both the MFI and the Goutallier classification system (GCS). The MFI was calculated as the signal intensity of the psoas muscle divided by that of the multifidus and erector spinae. Observer reliability was assessed in 102 consecutive patients for three independent investigators by intraclass correlation coefficient (ICC) and 95% limits of agreement (LoA) for continuous variables and Gwet’s agreement coefficient (AC1) for categorical variables. Associations with patient-reported pain and disability were assessed using univariate and multivariate regression analyses.ResultsInterobserver reliability was good for the MFI (ICC 0.79) and fair for the GCS (AC1 0.33). Intraobserver reliability was good or excellent for the MFI (ICC range 0.86–0.91) and moderate to almost perfect for the GCS (AC1 range 0.55–0.92). Mean interobserver differences of MFI measurements ranged from -0.09 to -0.04 (LoA -0.32 to 0.18). Adjusted for potential confounders, none of the disability or pain parameters was significantly associated with MFI or GCS.ConclusionThe proposed MFI demonstrated high observer reliability but was not associated with preoperative pain or disability.

Microwave focal therapy of prostate cancer: a non-clinical study and exploratory clinical trial.

To examine the safety and efficacy of microwave tissue coagulation (MTC) for prostate cancer and assess its use in lesion-targeted focal therapy in a non-clinical study and a clinical phase II trial. In the non-clinical study using Microtaze® -AFM-712 (Alfresa Pharma Corporation, Osaka, Japan) with an MTC needle, MTC was performed using a transperineal approach to targeted canine prostatic tissue under real-time ultrasonography guidance. Using various MTC output and irradiation time combinations, the targeted and surrounding tissues (rectum, bladder and fat) were examined to confirm the extent of coagulative necrosis or potential cell death, and to compare intra-operative ultrasonography and pathology findings. The exploratory clinical trial was conducted to examine the safety and efficacy of MTC. Five selected patients underwent transperineal MTC to clinically single lesion magnetic resonance imaging (MRI)-visible lesions with Gleason score 3 + 4 or 4 + 4. Prostate-specific antigen (PSA), MRI and Expanded Prostate Cancer Index Composite questionnaire findings were compared before and 6 months after surgery. The region of coagulative necrosis was predictable by monitoring of ultrasonically visible vaporization; thus, by placing the MTC needle at a certain distance, we were able to perform a safe procedure without adverse events affecting the surrounding organs. Based on the non-clinical study, which used various combinations of output and irradiation time, MTC with 30-W output for 60-s irradiation was selected for the prostate. Based on the predictable necrosis, the therapeutic plan (where to place the MTC needle to achieve complete ablation of the target and how many sessions) was strictly determined per patient. There were no serious adverse events in any patient and only temporary urinary symptoms related to MTC therapy were observed. Furthermore, post-treatment satisfaction was very high. All preoperative MRI-visible lesions disappeared, and PSA decreased by 55% 6 months after surgery. Microwave tissue coagulation may be an option for lesion-targeted focal therapy for prostate cancer.