Brain Diffusion Magnetic Resonance Imaging Research Articles

Brain diffusion MRI biomarkers after oncology treatments.

In addition to providing a measurement of the tumor's size and dimensions, magnetic resonance imaging (MRI) provides excellent noninvasive radiographic detection of tumor location. The MRI technique is an important modality that has been shown to be useful in the prognosis, diagnosis, treatment planning, and evaluation of response and recurrence in solid cancers. Diffusion-weighted imaging (DWI) is an imaging technique that quantifies water mobility. This imaging approach is good for identifying sub-voxel microstructure of tissues, correlates with tumor cellularity, and has been proven to be valuable in the early assessment of cytotoxic treatment for a variety of malignancies. Diffusion tensor imaging (DTI) is an MRI method that assesses the preferred amount of water transport inside tissues. This enables precise measurements of water diffusion, which changes according to the direction of white matter fibers, their density, and myelination. This measurement corresponds to some related variables: fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD), and others. DTI biomarkers can detect subtle changes in white matter microstructure and integrity following radiation therapy (RT) or chemoradiotherapy, which may have implications for cognitive function and quality of life. In our study, these indices were evaluated after brain chemoradiotherapy.

A Rare Case of Isolated Infarcts of the Pons with Sudden Vertigo: Clinical Features and Imaging Findings

Isolated infarcts of the pons (IIP) are a rare subtype of ischemic stroke, accounting for less than 1% of all strokes. It refers to a specific type of ischemic stroke that occurs within the pons region of the brain. IIP can be associated with vertebrobasilar insufficiency in certain cases. This case report describes a 64-year-old female patient who presented with acute vertigo and spontaneous nystagmus to the lesion side, ultimately diagnosed with IIP in the posterior right side of pons. Tegmental pontine infarcts typically manifest as oblique small (lacunar) infarctions that are localized in the mediolateral tegmental area of the middle to upper pons. The patient’s symptoms resolved spontaneously, but a 2-mm infarct was confirmed by brain diffusion magnetic resonance imaging. This case highlights the distinctive symptoms associated with IIP and emphasizes the importance of careful neurological examination and advanced neuroimaging techniques for accurate diagnosis.

The organization of frontostriatal brain wiring in non-affective early psychosis compared with healthy subjects using a novel diffusion imaging fiber cluster analysis.

Alterations in brain connectivity may underlie neuropsychiatric conditions such as schizophrenia. We here assessed the degree of convergence of frontostriatal fiber projections in 56 young adult healthy controls (HCs) and 108 matched Early Psychosis-Non-Affective patients (EP-NAs) using our novel fiber cluster analysis of whole brain diffusion magnetic resonance imaging tractography. Using whole brain tractography and our fiber clustering methodology on harmonized diffusion magnetic resonance imaging data from the Human Connectome Project for Early Psychosis we identified 17 white matter fiber clusters that connect frontal cortex (FCtx) and caudate (Cd) per hemisphere in each group. To quantify the degree of convergence and, hence, topographical relationship of these fiber clusters, we measured the inter-cluster mean distances between the endpoints of the fiber clusters at the level of the FCtx and of the Cd, respectively. We found (1) in both groups, bilaterally, a non-linear relationship, yielding convex curves, between FCtx and Cd distances for FCtx-Cd connecting fiber clusters, driven by a cluster projecting from inferior frontal gyrus; however, in the right hemisphere, the convex curve was more flattened in EP-NAs; (2) that cluster pairs in the right (p = 0.03), but not left (p = 0.13), hemisphere were significantly more convergent in HCs vs EP-NAs; (3) in both groups, bilaterally, similar clusters projected significantly convergently to the Cd; and, (4) a significant group by fiber cluster pair interaction for 2 right hemisphere fiber clusters (numbers 5, 11; p = .00023; p = .00023) originating in selective PFC subregions. In both groups, we found the FCtx-Cd wiring pattern deviated from a strictly topographic relationship and that similar clusters projected significantly more convergently to the Cd. Interestingly, we also found a significantly more convergent pattern of connectivity in HCs in the right hemisphere and that 2 clusters from PFC subregions in the right hemisphere significantly differed in their pattern of connectivity between groups.

Advancements in Gradient System Performance for Clinical and Research MRI.

In magnetic resonance imaging (MRI), spatial field gradients are applied along each axis to encode the location of the nuclear spin in the frequency domain. During recent years, the development of new gradient technologies has been focused on the generation of stronger and faster gradient fields for imaging with higher spatial and temporal resolution. This benefits imaging methods, such as brain diffusion and functional MRI, and enables human imaging at ultra-high field MRI. In addition to improving gradient performance, new technologies have been presented to minimize peripheral nerve stimulation and gradient-related acoustic noise, both generated by the rapid switching of strong gradient fields. This review will provide a general background on the gradient system and update on the state-of-the-art gradient technology. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 1.

Texture analysis in brain T2 and diffusion MRI differentiates histology-verified grey and white matter pathology types in multiple sclerosis

BackgroundMultiple sclerosis (MS) is a co mplex disease of the central nervous system involving several types of brain pathology that are difficult to characterize using conventional imaging methods. New methodWe originated novel texture analysis and machine learning approaches for classifying MS pathology subtypes as compared with 2 common advanced MRI measures: magnetization transfer ratio (MTR) and fractional anisotropy (FA). Texture analysis used an optimized grey level co-occurrence matrix method with histology-informed 7T T2-weighted magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) from 15 MS and 12 control brain specimens. DTI analysis took an innovative approach that assessed the texture across diffusion directions upsampled from 30 to 90. Tissue types included de- and re-myelinated lesions and normal-appearing areas in both grey and white matter, and diffusely abnormal white matter. Data analyses were stepwise, including: (1) group-wise classification using random forest algorithms based on all or individual imaging parameters; (2) parameter importance ranking; and (3) pairwise analysis using top-ranked features. ResultsTexture analysis performed better than MTR and FA, with T2 texture performed the best. T2 texture measures ranked the highest in classifying most grey and white matter tissue types, including de- versus re-myelinated lesions and among grey matter lesion subtypes (accuracy=0.86–0.59; kappa=0.60–0.41). Diffusion texture best differentiated normal appearing and control white matter. Comparison with existing methodsThere is no established method in imaging for differentiating MS pathology subtypes. In combined texture analysis and machine learning studies, there is also no direct evidence comparing conventional with advanced MRI measures for assessing MS pathology. Further, this study is unique in conducting innovative texture analysis with DTI following data-augmentation using robust methods. ConclusionsT2 and diffusion MRI texture analysis integrated with machine learning may be valuable approaches for characterizing MS pathology.

Diyabetik Retinopatili Hastalarda Vitreus Mizah Değişikliklerinin Difüzyon MRG ile Değerlendirilmesi

Aim: The objective of this study was to use diffusion-weighted imaging (DWI) to determine changes in the vitreous humor in diabetic retinopathy patients.Materials and Methods: All diabetic retinopathy patients over the age of 18 who had brain diffusion magnetic resonance imaging between May 1, 2019, and May 1, 2021, and whose images were available in the radiological information system were retrospectively scanned on our database. The study included 51 diabetic retinopathy patients and 51 non-diabetic control group patients. The t-test was used to compare the values of the vitreous humor apparent diffusion coefficient (ADC) in diabetic retinopathy patients with control group patients.Results: Patients with diabetic retinopathy had significantly higher minimum, median, and maximum ADC mean values in the right eye than the control group (p=0.011, p=0.007, p=0.026). Patients with diabetic retinopathy had significantly higher median and maximum ADC averages in the left eye than those in the control group (p=0.020, p=0.012). Although the mean minimum ADC of the left eye was higher in diabetic retinopathy patients than in the control group, the difference was not statistically significant (p=0.387).Conclusion: Because of the rise in ADC values in diabetic retinopathy patients compared to the normal control group, we detected that DWI could be used to assess if the vitreous humor is affected in this disease.

Noise Mapping and Removal in Complex-Valued Multi-Channel MRI via Optimal Shrinkage of Singular Values.

In magnetic resonance imaging (MRI), noise is a limiting factor for higher spatial resolution and a major cause of prolonged scan time, owing to the need for repeated scans. Improving the signal-to-noise ratio is therefore key to faster and higher-resolution MRI. Here we propose a method for mapping and reducing noise in MRI by leveraging the inherent redundancy in complex-valued multi-channel MRI data. Our method leverages a provably optimal strategy for shrinking the singular values of a data matrix, allowing it to outperform state-of-the-art methods such as Marchenko-Pastur PCA in noise reduction. Our method reduces the noise floor in brain diffusion MRI by 5-fold and remarkably improves the contrast of spiral lung 19F MRI. Our framework is fast and does not require training and hyper-parameter tuning, therefore providing a convenient means for improving SNR in MRI.

An unusual occurrence of acute cerebellar infarct after self-cervical manipulation: a case report

İntroduction
 Spinal manipulation is a widely used method in the treatment of neck pain, but it has the potential for serious complications. Although controversial, stroke can occur especially after cervical manipulation. Stroke secondary to self-cervical manipulation is rare and only a few cases have been reported.
 Case Report
 We reported a 28-year-old male patient with complaints of dizziness, neck pain and right hemiparesthesia. Except the cerebellar gait and right hemiparesthesia, his neurological examination was normal. It was learnt that his complaints started an hour after the self-cervical manipulation. His brain computed tomography, brain and cervical computed tomography angiography were normal limits. The brain diffusion magnetic resonance imaging (MRI) revealed an acute infarction area. He was discharged without sequelae with antiaggregant treatment, after 8 days of follow-up in the hospital.
 Conclusion
 Although it is controversial whether the risk of stroke increases after cervical manipulation, we believe the risk of stroke may increase, especially when the manipulation is performed by non-professionals. Especially in younger patients with a history of cervical manipulation and neurological complaints, stroke should be suspected even if the neurological examination is normal.

Silent cerebral infarct in sickle cell anemia patients of southern Turkey

Background/aimSilent cerebral infarct (SCI) is an ischemic lesion seen before clinical signs of brain infarct and ischemic changes in brain tissue. This study aimed to detect SCI with noninvasive methods and to determine related risk factors in patients with sickle cell anemia (SCA).Materials and methodsFifty-four SCA patients who had no history of cerebral infarct and whose neurological examinations were normal were included in this study. Brain magnetic resonance imaging (MRI) and diffusion MRI were taken and the acquired data was compared statistically.ResultsSCI was detected in 11.1% (6/54) of the patients. No statistical differences in age, sex, physical examination findings, or treatments were detected between the 2 groups (with and without SCI). When examined in terms of HbS, the median (min–max) value in SCI-positive patients was 85.4 (80.5–92.1); the median value was 77.2 (49.0–96.7) in SCI-negative patients. The HbS values of the SCI group were statistically significantly higher than those of the group without SCI (P = 0.014). Patients with the HbSS or HbSβ0 genotypes had a significantly higher prevalence of SCI when compared with other sickle cell syndromes (P = 0.038).ConclusionSCI is not uncommon among SCA patients in Turkey. The presence of homozygote HbSS/Sβ0 genotype, high MCV, and HbS are risk factors for SCI.

Predicting motor outcome in preterm infants from very early brain diffusion MRI using a deep learning convolutional neural network (CNN) model

Background and aimsPreterm birth imposes a high risk for developing neuromotor delay. Earlier prediction of adverse outcome in preterm infants is crucial for referral to earlier intervention. This study aimed to predict abnormal motor outcome at 2 years from early brain diffusion magnetic resonance imaging (MRI) acquired between 29 and 35 weeks postmenstrual age (PMA) using a deep learning convolutional neural network (CNN) model. MethodsSeventy-seven very preterm infants (born <31 weeks gestational age (GA)) in a prospective longitudinal cohort underwent diffusion MR imaging (3T Siemens Trio; 64 directions, b ​= ​2000 ​s/mm2). Motor outcome at 2 years corrected age (CA) was measured by Neuro-Sensory Motor Developmental Assessment (NSMDA). Scores were dichotomised into normal (functional score: 0, normal; n ​= ​48) and abnormal scores (functional score: 1–5, mild-profound; n ​= ​29). MRIs were pre-processed to reduce artefacts, upsampled to 1.25 ​mm isotropic resolution and maps of fractional anisotropy (FA) were estimated. Patches extracted from each image were used as inputs to train a CNN, wherein each image patch predicted either normal or abnormal outcome. In a postprocessing step, an image was classified as predicting abnormal outcome if at least 27% (determined by a grid search to maximise the model performance) of its patches predicted abnormal outcome. Otherwise, it was considered as normal. Ten-fold cross-validation was used to estimate performance. Finally, heatmaps of model predictions for patches in abnormal scans were generated to explore the locations associated with abnormal outcome. ResultsFor the identification of infants with abnormal motor outcome based on the FA data from early MRI, we achieved mean sensitivity 70% (standard deviation SD 19%), mean specificity 74% (SD 39%), mean AUC (area under the receiver operating characteristic curve) 72% (SD 14%), mean F1 score of 68% (SD 13%) and mean accuracy 73% (SD 19%) on an unseen test data set. Patch-based prediction heatmaps showed that the patches around the motor cortex and somatosensory regions were most frequently identified by the model with high precision (74%) as a location associated with abnormal outcome. Part of the cerebellum, and occipital and frontal lobes were also highly associated with abnormal NSMDA/motor outcome. Discussion/conclusionThis study established the potential of an early brain MRI-based deep learning CNN model to identify preterm infants at risk of a later motor impairment and to identify brain regions predictive of adverse outcome. Results suggest that predictions can be made from FA maps of diffusion MRIs well before term equivalent age (TEA) without any prior knowledge of which MRI features to extract and associated feature extraction steps. This method, therefore, is suitable for any case of brain condition/abnormality. Future studies should be conducted on a larger cohort to re-validate the robustness and effectiveness of these models.

Fine-Grained Parcellation of the Macaque Nucleus Accumbens by High-Resolution Diffusion Tensor Tractography

Limited in part by the spatial resolution of typical in vivo magnetic resonance imaging (MRI) data, recent neuroimaging studies have only identified a connectivity-based shell-core-like partitioning of the nucleus accumbens (Acb) in humans. This has hindered the process of making a more refined description of the Acb using non-invasive neuroimaging technologies and approaches. In this study, high-resolution ex vivo macaque brain diffusion MRI data were acquired to investigate the tractography-based parcellation of the Acb. Our results identified a shell-core-like partitioning in macaques that is similar to that in humans as well as an alternative solution that subdivided the Acb into four parcels, the medial shell, the lateral shell, the ventral core, and the dorsal core. Furthermore, we characterized the specific anatomical and functional connectivity profiles of these Acb subregions and generalized their specialized functions to establish a fine-grained macaque Acb brainnetome atlas. This atlas should be helpful in neuroimaging, stereotactic surgery, and comparative neuroimaging studies to reveal the neurophysiological substrates of various diseases and cognitive functions associated with the Acb.

Generalized Seizure Due To Acute Hyperosmolar Hyponatremıa Followıng Coronary Angıography: A Lesson Learned From A Case Report

Hyponatremia is a common electrolyte disorder, but symptomatic hyponatremia following coronary angiography is rare. Although patients with hyponatremia are generally asymptomatic, neurological manifestations may result in lethal complications. Here we presented a 69-year-old female, admitted for elective coronary angiography due to exertional chest pain. Seven hours later after coronary angiography, however, the patient had a headache, temporary mental confusion and her speech was slurring. A brain magnetic resonance imaging (MRI) test, arterial blood gas analysis, and the neurological examination were carried out. The neurological examination showed no focality and brain diffusion MRI was normal. Arterial blood gas analysis revealed sodium of 110 mmol/L and potassium of2.8 mmol/L. The patient was treated with hypertonic saline (3% NaCl) and vasopressin antagonist tolvaptan 15 mg at first and isotonic saline (0,09 NaCl) with a gradual normalization of electrolytes. Diagnosis of acute hyperosmolar hyponatremia should be considered in patients with developing mental or behavioral abnormalities following coronary angiography.

Sudden sensorineural hearing loss as the only symptom of multiple sclerosis

We present a 33-year-old male patient with sudden sensorineural hearing loss, the main and only symptom of the second attack, who had been diagnosed with multiple sclerosis (MS) 8 years ago. The patient came to our clinic with a sudden onset of hearing loss and tinnitus in his right ear 1 week ago. Four consecutive frequency sensorineural hearing losses were observed in the audiogram of the patient. Brain diffusion magnetic resonance imaging (MRI) has been reported to result in an increase in the number of plaques and a new plaque in the area of the left temporal lobe subcortical white matter compared to the plaques of many demyelinated, compared with MRI about 1 year ago. As in our patient, brain diffusion MRI, time and location of MS lesions, and evidence of dissemination can provide evidence for MS-related hearing loss in these patients. The auditory brainstem responses may also provide important supporting information in this case.

Understanding microstructure of the brain by comparison of neurite orientation dispersion and density imaging (NODDI) with transparent mouse brain

BackgroundNeurite orientation dispersion and density imaging (NODDI) is a diffusion magnetic resonance imaging (MRI) technique with the potential to visualize the microstructure of the brain. Revolutionary histological methods to render the mouse brain transparent have recently been developed, but verification of NODDI by these methods has not been reported.PurposeTo confirm the concordance of NODDI with histology in terms of density and orientation dispersion of neurites of the brain.Material and MethodsWhole brain diffusion MRI of a thy-1 yellow fluorescent protein mouse was acquired with a 7-T MRI scanner, after which transparent brain sections were created from the same mouse. NODDI parameters calculated from the MR images, including the intracellular volume fraction (Vic) and the orientation dispersion index (ODI), were compared with histological findings. Neurite density, Vic, and ODI were compared between areas of the anterior commissure and the hippocampus containing crossing fibers (crossing areas) and parallel fibers (parallel areas), and the correlation between fiber density and Vic was assessed.ResultsThe ODI was significantly higher in the crossing area compared to the parallel area in both the anterior commissure and the hippocampus (P = 0.0247, P = 0.00022, respectively). Neurite density showed a similar tendency, but was significantly different only in the hippocampus (P = 7.91E−07). There was no significant correlation between neurite density and Vic.ConclusionNODDI was verified by histology for quantification of the orientation dispersion of neurites. These results indicate that the ODI is a suitable index for understanding the microstructure of the brain in vivo.

Neuroticism, depressive symptoms and white-matter integrity in the Lothian Birth Cohort 1936

Clinical depression is associated with reductions in white-matter integrity in several long tracts of the brain. The extent to which these findings are localized or related to depressive symptoms or personality traits linked to disease risk remains unclear. Method Members of the Lothian Birth Cohort 1936 (LBC936) were assessed in two waves at mean ages of 70 and 73 years. At wave 1, they underwent assessments of depressive symptoms and the personality traits of neuroticism and extraversion. Brain diffusion magnetic resonance imaging (MRI) data were obtained at the second wave and mood assessments were repeated. We tested whether depressive symptoms were related to reduced white-matter tract fractional anisotropy (FA), a measure of integrity, and then examined whether high neuroticism or low extraversion mediated this relationship. Six hundred and sixty-eight participants provided useable data. Bilateral uncinate fasciculus FA was significantly negatively associated with depressive symptoms at both waves (standardized β=0.12-0.16). Higher neuroticism and lower extraversion were also significantly associated with lower uncinate FA bilaterally (standardized β=0.09-0.15) and significantly mediated the relationship between FA and depressive symptoms. Trait liability to depression and depressive symptoms are associated with reduced structural connectivity in tracts connecting the prefrontal cortex with the amygdala and anterior temporal cortex. These effects suggest that frontotemporal disconnection is linked to the etiology of depression, in part through personality trait differences.

Neonatal Neurobehavior and Diffusion MRI Changes in Brain Reorganization Due to Intrauterine Growth Restriction in a Rabbit Model

BackgroundIntrauterine growth restriction (IUGR) affects 5–10% of all newborns and is associated with a high risk of abnormal neurodevelopment. The timing and patterns of brain reorganization underlying IUGR are poorly documented. We developed a rabbit model of IUGR allowing neonatal neurobehavioral assessment and high resolution brain diffusion magnetic resonance imaging (MRI). The aim of the study was to describe the pattern and functional correlates of fetal brain reorganization induced by IUGR.Methodology/Principal FindingsIUGR was induced in 10 New Zealand fetal rabbits by ligation of 40–50% of uteroplacental vessels in one horn at 25 days of gestation. Ten contralateral horn fetuses were used as controls. Cesarean section was performed at 30 days (term 31 days). At postnatal day +1, neonates were assessed by validated neurobehavioral tests including evaluation of tone, spontaneous locomotion, reflex motor activity, motor responses to olfactory stimuli, and coordination of suck and swallow. Subsequently, brains were collected and fixed and MRI was performed using a high resolution acquisition scheme. Global and regional (manual delineation and voxel based analysis) diffusion tensor imaging parameters were analyzed. IUGR was associated with significantly poorer neurobehavioral performance in most domains. Voxel based analysis revealed fractional anisotropy (FA) differences in multiple brain regions of gray and white matter, including frontal, insular, occipital and temporal cortex, hippocampus, putamen, thalamus, claustrum, medial septal nucleus, anterior commissure, internal capsule, fimbria of hippocampus, medial lemniscus and olfactory tract. Regional FA changes were correlated with poorer outcome in neurobehavioral tests.ConclusionsIUGR is associated with a complex pattern of brain reorganization already at birth, which may open opportunities for early intervention. Diffusion MRI can offer suitable imaging biomarkers to characterize and monitor brain reorganization due to fetal diseases.