Matter Magnetic Resonance Imaging Research Articles

Apparent diffusion coefficient values of the white matter in magnetic resonance imaging of the neonatal brain may help predict outcome in congenital cytomegalovirus infection

BackgroundWhite matter change is a well-known abnormality in congenital cytomegalovirus (cCMV) infection, but grading remains challenging and clinical relevance unclear.ObjectiveTo investigate if quantitative measurement of white matter apparent diffusion coefficient (ADC) values in magnetic resonance imaging (MRI) of the neonatal brain can predict outcome in cCMV.Materials and methodsA retrospective, single-center observational study, including patients with cCMV who had a neonatal brain MRI with diffusion-weighted imaging, was performed between 2007 and 2020. Regions of interest were systematically placed in the white matter on the ADC maps. Two pediatric radiologists independently scored additional brain abnormalities. Outcome measures were neonatal hearing and cognitive and motor development. Statistical analysis included simple and penalized elastic net regression.ResultsNeonatal brain MRI was evaluated in 255 patients (median age 21 days, 25–75 percentiles: 14–28 days, 121 male). Gyral abnormalities were noted in nine patients (3.5%), ventriculomegaly in 24 (9.4%), and subependymal cysts in 58 (22.7%). General white matter ADC was significantly higher in patients with neonatal hearing loss and cognitive and motor impairment (P< 0.05). For neonatal hearing loss, simple logistic regression using only general white matter was the best prediction model, with a receiver operating characteristic area under the curve (AUC)=0.76. For cognitive impairment, interacting elastic net regression, including other brain abnormalities and frontoparietal white matter ADC, performed best, with AUC=0.89. For motor impairment, interacting elastic net regression, including other brain abnormalities and deep anterior frontal white matter performed best, with AUC=0.73.ConclusionNeonatal white matter ADC was significantly higher in patients with clinical impairments. Quantitative ADC measurement may be a useful tool for predicting clinical outcome in cCMV.Graphical

Chemotherapy-induced posterior reversible encephalopathy syndrome in an adolescent patient with acute lymphoblastic leukemia – A case report

Posterior reversible encephalopathy syndrome (PRES) is a clinicoradiological condition characterized by headaches, seizures, confusion, and visual impairment. It typically causes transient lesions in the posterior white matter in magnetic resonance imaging (MRI) of the brain. PRES induced by chemotherapy is uncommon in oncology but can be a significant neurological event. The exact cause of PRES remains unclear. This case report describes a 15-year-old female patient with acute lymphoblastic leukemia who developed PRES following chemotherapy with prednisolone (100 mg), vincristine (2 mg), and daunorubicin (40 mg) as per the modified Berlin-Frankfurt-Munster (95/2002) protocol. She developed headaches, partial seizures, and elevated blood pressure 1 day after starting chemotherapy. Brain MRI showed T2 and fluid-attenuated inversion recovery hyperintensities in the bilateral cerebral parenchyma, brainstem, and cerebellum. She was treated with levetiracetam (500 mg stat and then 1.5 g BD) for seizures, amlodipine (5 mg) for hypertension, and paracetamol (650 mg TDS) for headaches. Her symptoms improved and resolved within 2 days. The event was deemed possibly related to the chemotherapy drugs according to the World Health Organization-Uppsala Monitoring Centre causality assessment system.

Voxel-based correlation of 18F-THK5351 accumulation with gray matter structural networks in cognitively normal older adults.

ObjectiveThe aim of this study was to evaluate tau-related structural network metrics derived from gray matter magnetic resonance imaging (MRI) scans in cognitively normal (CN) older adults.MethodsWe recruited 47 amyloid-negative CN older adults (mean age ± standard deviation, 65.0 ± 7.9 years; 26 women). All participants underwent 3D T1-weighted MRI and 11C-Pittsburgh compound-B and 18F-THK5351 positron emission tomography scans. Four local network metrics (betweenness centrality, clustering coefficient, characteristic path length, and degree) were computed and rendered on individual brain images. We then evaluated the correlations between 18F-THK5351 positron emission tomography images and local network metric images at the voxel level.ResultsSignificant positive correlations of the four local network metrics with 18F-THK5351 were detected in the bilateral caudate.ConclusionOur findings suggest that tau and neuroinflammation in CN older adults may influence the gray matter structural network in the caudate.

Structural brain network differences in bipolar disorder using with similarity-based approach.

Objective: Previous studies have shown differences in the regional brain structure and function between patients with bipolar disorder (BD) and healthy subjects, but little is known about the structural connectivity between BD patients and healthy subjects. In this study, we evaluated the disease-related changes in regional structural connectivity derived from gray matter magnetic resonance imaging (MRI) scans. Methods: The subjects were 73 patients with BD and 80 healthy volunteers who underwent 3-Tesla MRI. Network metrics, such as the small world properties, were computed. We also performed rendering of the network metric images such as the degree, betweenness centrality, and clustering coefficient, on individual brain image. Then, we estimated the differences between them, and evaluate the relationships between the clinical symptoms and the network metrics in the patients with BD. Results: BD patients showed a lower clustering coefficient in the right parietal region and left occipital region, compared with healthy subjects. A weak negative correlation between Young mania rating scale and clustering coefficient was found in left anterior cingulate cortex. Conclusions: We found differences in gray matter structural connectivity between BD patients and healthy subjects by a similarity-based approach. These points may provide objective biological information as an adjunct to the clinical diagnosis of BD.

Relationship between androgenic alopecia and white matter hyperintensities in apparently healthy subjects.

A healthy brain is essential for living a longer and fuller life. Detecting asymptomatic white matter hyperintensities (WMHs) may be clinically important in terms of treatment and prognostic evaluation. WMHs in brain may reflect brain aging. Androgenic alopecia (AGA) is associated with significant cardiovascular risk factors that also have a negative impact on brain aging. The main purpose of present study was to know whether alopecia might provide predictive information of WMHs that may be considered as a surrogate marker of cerebral small vessel disease which is related to arteriolosclerosis and vascular risk factors. From January 2017 to March 2018, 256 cases were enrolled consecutively. Patients under 18years old, older than 90years old, known to be affected by neurodegenerative diseases, demyelinating disorders or stroke and/or a brain tumor, were excluded from the study. A 4-point cerebral white matter Magnetic Resonance Imaging (MRI) hyperintensities scoring system, the Fazekas scale, was used to evaluate brain aging. Presence of AGA was evaluated with inspection according to Hamilton-Norwood classification system (grade I to VII). Two hundred eleven (82%) of individuals had mild alopecia (grade I, II, III), 28 (11%) had moderate alopecia (grade IV, V) and 17 (7%) had severe alopecia (grade VI, VII). Frequency of abnormal WMHs was significantly higher in patients with AGA compared to the without AGA. Hypertension (HT) (95% confidence interval [CI]: 1.873-9.487, p< 0.001) and the AGA (95% CI: 2.989-12.916, p< 0.0001) were independent determinants of abnormal WMHs. AGA may be regarded as a surrogate marker of asymptomatic WMHs which is related to arteriolosclerosis and vascular risk factors that has a significant impact on people's life.

Reduced Cerebral White Matter Integrity Assessed by DTI in Cognitively Normal H63D-HFE Polymorphism Carriers.

The H63D-HFE single nucleotide polymorphism (SNP) has been associated with brain iron dysregulation; however, the emergent role of this missense variant in brain structure and function has yet to be determined. Previous work has demonstrated that HFE SNP carriers have reduced white matter magnetic resonance imaging (MRI) proton relaxation rates. The mechanism by which white matter alterations perturb MRI relaxation is unknown as is how these metrics are related to myelin integrity. Fifteen subjects heterozygous for the HFE-H63D SNP and 25 controls with wild-type HFE had diffusion-weighted, anatomical MRIs taken, and underwent cognitive assessment. Fractional anisotropy (FA), mean diffusion (MD), and mode of anisotropy (MO) were calculated from the diffusion dataset to investigate the relationship between the H63D-HFE SNP and myelin integrity. A decrease in FA, an increase in MD, and an increase in MO are demonstrated in multiple H63D-HFE polymorphism carrier white matter tracts. Regions with altered diffusion metrics are notably located in heavily myelinated white matter association fibers, such as the anterior corona radiata and longitudinal fasciculi. The MRI data presented here demonstrate that H63D-HFE polymorphism carriers have diffusivity changes in white matter compared to wild-type subjects. The reduced integrity white matter tracts in H63D-HFE carriers are hypothesized to be related to increased susceptibility of these late-myelinating regions to cellular stress induced by oligodendrocyte iron dyshomeostasis.

Ageing and brain white matter structure in 3,513 UK Biobank participants

Quantifying the microstructural properties of the human brain's connections is necessary for understanding normal ageing and disease. Here we examine brain white matter magnetic resonance imaging (MRI) data in 3,513 generally healthy people aged 44.64–77.12 years from the UK Biobank. Using conventional water diffusion measures and newer, rarely studied indices from neurite orientation dispersion and density imaging, we document large age associations with white matter microstructure. Mean diffusivity is the most age-sensitive measure, with negative age associations strongest in the thalamic radiation and association fibres. White matter microstructure across brain tracts becomes increasingly correlated in older age. This may reflect an age-related aggregation of systemic detrimental effects. We report several other novel results, including age associations with hemisphere and sex, and comparative volumetric MRI analyses. Results from this unusually large, single-scanner sample provide one of the most extensive characterizations of age associations with major white matter tracts in the human brain.

Histological Basis of Laminar MRI Patterns in High Resolution Images of Fixed Human Auditory Cortex.

Functional magnetic resonance imaging (fMRI) studies of the auditory region of the temporal lobe would benefit from the availability of image contrast that allowed direct identification of the primary auditory cortex, as this region cannot be accurately located using gyral landmarks alone. Previous work has suggested that the primary area can be identified in magnetic resonance (MR) images because of its relatively high myelin content. However, MR images are also affected by the iron content of the tissue and in this study we sought to confirm that different MR image contrasts did correlate with the myelin content in the gray matter and were not primarily affected by iron content as is the case in the primary visual and somatosensory areas. By imaging blocks of fixed post-mortem cortex in a 7 T scanner and then sectioning them for histological staining we sought to assess the relative contribution of myelin and iron to the gray matter contrast in the auditory region. Evaluating the image contrast in -weighted images and quantitative maps showed a reasonably high correlation between the myelin density of the gray matter and the intensity of the MR images. The correlation with T1-weighted phase sensitive inversion recovery (PSIR) images was better than with the previous two image types, and there were clearly differentiated borders between adjacent cortical areas in these images. A significant amount of iron was present in the auditory region, but did not seem to contribute to the laminar pattern of the cortical gray matter in MR images. Similar levels of iron were present in the gray and white matter and although iron was present in fibers within the gray matter, these fibers were fairly uniformly distributed across the cortex. Thus, we conclude that T1- and -weighted imaging sequences do demonstrate the relatively high myelin levels that are characteristic of the deep layers in primary auditory cortex and allow it and some of the surrounding areas to be reliably distinguished.

Parameterization of the distribution of white and grey matter in MRI using the [formula omitted]-stable distribution

This work presents a study of the distribution of the grey matter (GM) and white matter (WM) in brain magnetic resonance imaging (MRI). The distribution of GM and WM is characterized using a mixture of α-stable distributions. A Bayesian α-stable mixture model for histogram data is presented and unknown parameters are sampled using the Metropolis–Hastings algorithm. The proposed methodology is tested in 18 real images from the MRI brain segmentation repository. The GM and WM distributions are accurately estimated. The α-stable distribution mixture model presented in this paper can be used as previous step in more complex MRI segmentation procedures using spatial information. Furthermore, due to the fact that the α-stable distribution is a generalization of the Gaussian distribution, the proposed methodology can be applied instead of the Gaussian mixture model, which is widely used in segmentation of brain MRI in the literature.

Primary gliomatosis cerebri involving gray matter in pediatrics: a distinct entity? A multicenter study of 14 cases

Gliomatosis cerebri (GC) is a rare neoplasm including a variety of tumors, with extremely variable evolution and heterogeneity of prognosis. It may appear either de novo or after a focal glioma, involve predominantly the white or the gray matter, and concern either pediatric or adult patients. We focused on primary GC involving exclusively gray matter in a pediatric population in order better to define the presentation and outcome of this disease. We reviewed the databases of seven Departments of Pediatric Oncology to identify pediatric cases of GC between 1990 and 2007. Patients were included if they demonstrated a diffuse infiltrative process involving gray matter in magnetic resonance imaging (MRI) and histological tissue analyses, confirming a proliferative glial disorder. Fourteen patients with a median age of 8 years were identified. Epilepsy was the main presenting symptom. Brain MRI showed a lesion of the temporal and insular cerebral cortex associated with tumoral infiltration of the thalami and the basal ganglia. Histological examination confirmed the diagnosis of high-grade glioma. Prognosis was always very gloomy in the short term, with a median survival of less than a year. This rare entity, whose prognosis is appalling whatever the treatment proposed, should be clearly identified within the heterogeneous group of GC in the same way as diffuse intrinsic pontine gliomas have been identified among brain stem tumors. Systematic biopsies appear essential to permit the molecular studies which will assist in guiding the choice of future targeted treatments.

Neurological Complications Following Pediatric Liver Transplant

We studied neurological complications (NCs) after liver transplantation (LT) in children. We performed an institutional review board-approved retrospective review of patients with LT ≤21 years during a period of 30 years (1980-2010). NCs were classified as early (within 3 months post-LT) and delayed (beyond 3 months post-LT). Of 65 children with LT, 20 (30.7%) had NCs; 16 were girls. Mean age was 11.8±5.9 years. Early NCs were found in 13.8% (9/65) of the patients: seizures in 7 and encephalopathy in 2. Abnormal neuroimaging findings were posterior reversible leukoencephalopathy syndrome (1), intracranial hemorrhage (1), mild cerebral edema (1), and bilateral basal ganglia T1W hyperintensities in magnetic resonance imaging (1). On follow-up, there were 3 deaths (unrelated to NCs). One with intracranial hemorrhage had residual hemiparesis and was taking a long-term antiepileptic drug. Late NCs are found in 16.9% (11/65) of the patients: seizures in 4, headache in 4, encephalopathy in 3 (1 had seizures in addition), and paresthesias caused by possible small-fiber neuropathy in 1. Abnormal neuroimaging findings were hypoxic-ischemic encephalopathy (1), encephalomalacia caused by old hemorrhage (1), and hyperintensity of the posterior periventricular white matter in magnetic resonance imaging (1). On follow-up, all of the patients survived; 1 had papilledema with secondary optic atrophy requiring optic nerve sheath fenestration and 1 needed long-term antiepileptic drug. NCs are common in children after LT, seizures being the most common. In contrary to the previous studies, we found delayed complications more often than early complications. Early detection and appropriate management of NCs is important.

Atlas-Free Surface Reconstruction of the Cortical Grey-White Interface in Infants

BackgroundThe segmentation of the cortical interface between grey and white matter in magnetic resonance images (MRI) is highly challenging during the first post-natal year. First, the heterogeneous brain maturation creates important intensity fluctuations across regions. Second, the cortical ribbon is highly folded creating complex shapes. Finally, the low tissue contrast and partial volume effects hamper cortex edge detection in parts of the brain.Methods and FindingsWe present an atlas-free method for segmenting the grey-white matter interface of infant brains in T2-weighted (T2w) images. We used a broad characterization of tissue using features based not only on local contrast but also on geometric properties. Furthermore, inaccuracies in localization were reduced by the convergence of two evolving surfaces located on each side of the inner cortical surface. Our method has been applied to eleven brains of one- to four-month-old infants. Both quantitative validations against manual segmentations and sulcal landmarks demonstrated good performance for infants younger than two months old. Inaccuracies in surface reconstruction increased with age in specific brain regions where the tissue contrast decreased with maturation, such as in the central region.ConclusionsWe presented a new segmentation method which achieved good to very good performance at the grey-white matter interface depending on the infant age. This method should reduce manual intervention and could be applied to pathological brains since it does not require any brain atlas.

Morphological contrast measure and contrast enhancement: One application to the segmentation of brain MRI

In this paper a morphological contrast measure is introduced. The quantification of the contrast is based on the analysis of the edges, which are associated with substantial changes in luminance. Due to this, the contrast measure is used to detect the image that presents a high visual contrast when a set of output images is analyzed. The set of output images is obtained by application of morphological contrast mappings with size criteria. These contrast transformations are defined under the notion of partitions generated by the set of flat zones of the image; therefore, they are connected transformations. In addition, an application to the segmentation of white and grey matter in brain magnetic resonance images (MRI) is provided. The detection of white matter is carried out by means of a contrast mapping with specific control parameters; subsequently, white and grey matter are separated and their ratio is calculated and compared with manual segmentations. Also, an example of segmentation of white and grey matter in MRI corrupted by 5% noise is presented in order to observe the performance of the morphological transformations proposed in this work.

MR image reconstruction from partial k-space using singularity function representation

Image reconstruction from partial k-space is an important matter in magnetic resonance imaging (MRI). The previously proposed methods are unable to cope with truncation artifacts without degrading image quality. We present a method that is particularly suitable for reconstructing magnetic resonance (MR) images from partial k-space by reducing substantially truncation artifacts while maintaining the spatial resolution of the image. The proposed method is based on the use of a so-called singularity function representation determined by singular points and singularity degrees. With this model, our strategy consists in restricting the singularity degrees within some dynamic range, beyond which the corresponding singular points are set to zero. The proposed method was evaluated on both simulated and human brain MR data. The results showed that this new strategy has significantly improved the reconstruction quality of partial k-space data.