Is Diffusion Tensor Imaging-Guided Radiotherapy the New State-of-the-Art? A Review of the Current Literature and Technical Insights

Despite the increasing precision of radiotherapy delivery, it is still frequently associated with neurological complications. This is in part due to damage to eloquent white matter (WM) tracts, which is made more likely by the fact they cannot be visualised on standard structural imaging. WM is additionally more vulnerable than grey matter to radiation damage. Primary brain malignancies also are known to spread along the WM. Diffusion tensor imaging (DTI) is the only in vivo method of delineating WM tracts. DTI is an imaging technique that models the direction of diffusion and therefore can infer the orientation of WM fibres. This review article evaluates the current evidence for using DTI to guide intracranial radiotherapy and whether it constitutes a new state-of-the-art technique. We provide a basic overview of DTI and its known applications in radiotherapy, which include using tractography to reduce the radiation dose to eloquent WM tracts and using DTI to detect or predict tumoural spread. We evaluate the evidence for DTI-guided radiotherapy in gliomas, metastatic disease, and benign conditions, finding that the strongest evidence is for its use in arteriovenous malformations. However, the evidence is weak in other conditions due to a lack of case-controlled trials.

Network Constraints on Longitudinal Grey Matter Changes in First Episode Psychosis

Background: Different regions of the brain's grey matter are connected by a complex structural network of white matter fibres which are responsible for the propagation of action potentials and the transport of trophic and other molecules. In neurodegenerative disease, these connections constrain the way in which grey matter volume loss progresses. Here, we investigated whether connectome architecture also shapes the spatial pattern of longitudinal grey matter volume changes attributable to illness and antipsychotic medication in first episode psychosis (FEP). Methods: We conducted a triple-blind randomised placebo-control MRI study where 62 young adults with first episode psychosis received either an atypical antipsychotic or placebo over 6-months. A healthy control group was also recruited. Anatomical MRI scans were acquired at baseline, 3-months and 12-months. Deformation-based morphometry was used to estimate illness-related and antipsychotic-related grey matter volume changes over time. Representative functional and structural brain connectivity patterns were derived from an independent healthy control group using resting-state functional MRI and diffusion-weighted imaging. We used neighbourhood deformation models to predict the extent of brain change in a given area by the changes observed in areas to which it is either structurally connected or functionally coupled. Results: At baseline, we found that empirical illness-related regional volume differences were strongly correlated with predicted differences using a model constrained by structural connectivity weights (ρ = .541; p < .001). At 3-months and 12-months, we also found a strong correlation between longitudinal regional illness-related (ρ > .516; p < .001) and antipsychotic-related volume change (ρ > .591; p < .001) with volumetric changes in structurally connected areas. These correlations were significantly greater than those observed across various null models accounting for lower-order spatial and network properties of the data. Associations between empirical and predicted volume change estimates were much lower for models that only considered binary structural connectivity (all ρ < .376), or which were constrained by inter-regional functional coupling (all ρ < .436). Finally, we found that potential epicentres of volume change emerged posteriorly early in the illness and shifted to the prefrontal cortex by later illness stages. Conclusion: Psychosis- and antipsychotic-related grey matter volume changes are strongly shaped by anatomical brain connectivity. This result is consistent with findings in other neurological disorders and implies that such connections may constrain pathological processes causing brain dysfunction in FEP.

Atlasing white matter and grey matter joint contributions to resting-state networks in the human brain

Over the past two decades, the study of resting-state functional magnetic resonance imaging (fMRI) has revealed the existence of multiple brain areas displaying synchronous functional blood oxygen level-dependent signals (BOLD) - resting-state networks (RSNs). The variation in functional connectivity between the different areas of a resting-state network or between multiple networks, have been extensively studied and linked to cognitive states and pathologies. However, the white matter connections supporting each network remain only partially described. In this work, we developed a data-driven method to systematically map the white and grey matter contributing to resting-state networks. Using the Human Connectome Project, we generated an atlas of 30 resting-state networks, each with two maps: white matter and grey matter. By integrating structural and functional neuroimaging data, this method builds an atlas that unlocks the joint anatomical exploration of white and grey matter to resting-state networks. The method also allows highlighting the overlap between networks, which revealed that most (89%) of the brain's white matter is shared amongst multiple networks, with 16% shared by at least 7 resting-state networks. These overlaps, especially the existence of regions shared by numerous networks, suggest that white matter lesions in these areas might strongly impact the correlations and the communication within resting-state networks. We provide an open-source software to explore the joint contribution of white and grey matter to RSNs and facilitate the study of the impact of white matter damage on RSNs.

Genetic background of grey matter brain networks related to attention-deficit/hyperactivity disorder

Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder and is associated with structural grey matter differences in the brain. We investigated the genetic background of some of these brain differences in a sample of 899 adults and adolescents consisting of individuals with ADHD and healthy controls. Previous work in an overlapping sample identified three ADHD-related grey matter brain networks located in areas of the superior, middle, and inferior frontal gyrus as well as the cerebellar tonsil and culmen. We associated these brain networks with protein coding genes using a statistical stability selection approach. We identified ten genes, the most promising of which were NR3C2, TRHDE, SCFD1, GNAO1, and UNC5D. These genes are expressed in brain and linked to neuropsychiatric disorders including ADHD. With our results we aid in the growing understanding of the aetiology of ADHD from genes to brain to behaviour.

Diagnostic accuracy of double inversion recovery (DIR) in detection of cortical gray matter lesions in patients with MS

Background Conventional imaging techniques have a low sensitivity for detection of cortical and deep grey matter lesions in MS which hinder accurate assessment of the total lesion burden. Aim of this work was to assess the diagnostic accuracy of double inversion recovery (DIR) sequence in the detection of cortical grey matter lesions in MS patients. Results Forty MS patients were prospectively included in this study. Imaging was performed using Philips Ingenia 1.5 T device. The sensitivity, specificity, PPV, NPV and accuracy of DIR sequence in detection of cortical grey matter lesions were 60%, 100%, 100%, 55.6% and 73.3%, respectively. The sensitivity, specificity, positive and negative predictive values as well as accuracy of Flair sequence were 50%, 100%, 100%, 50% and 66.7%, respectively. The sensitivity, specificity, positive and negative predictive values as well as accuracy of T2 sequence in the detection of cortical grey matter lesions were 22.5%, 100%, 100%, 39.2% and 48.3%, respectively. Conclusions Detection rate of cortical gray matter lesions was significantly higher on DIR sequence than on T2 and Flair sequences.

CT Scanning Findings in Clinically Diagnosed Cerebral Palsy

Background: Cerebral Palsy is a non-progressive disorder due to insult in the developing brain. This causes disorders in muscle tone, posture and movement. Cerebral palsy is usually diagnosed by clinical features. Though risk factors are identified in about 75% of cases, the etiology remains unclear. Magnetic resonance imaging is the standard method to detect central nervous system abnormalities; but in resource poor areas CT Scanning may be an alternative method to elucidate the underlying Central Nervous System abnormalities. Objectives: The objective was to detect CT Scanning findings in different types of Cerebral palsies. Methodology: This was a prospective and cross-sectional study conducted on 525 Children registered at Child Development Center attached to Rangpur Mother and Children Hospital. Cerebral palsy was diagnosed by using an Interview Schedule. During from 1.1.2016 to 31.12.2019 CT scanning of brain was performed purposefully to all children to detect the underlying Central Nervous System abnormalities. The purpose was explained to parents and consent was taken before performing the tests. The children were in sedation during the procedure. Result: A total of 1800 registered children, 525 (29.10%) children were suffering from Cerebral Palsy. The male and female ratio was 3:2 and age distribution was 2.6±1.5 years. Seventy nine percent (79.0%) of children came from poor families. Parental education up to class V was in 65% cases. Maximum number (63.0%) of cases was suffering from spastic type of Cerebral Palsy followed by athetoid type (18.3%) and 7.1% ataxic type. Among spastics, quadriplegia was present in 68.5% of cases followed by hemiplegia (18.5%). Perinatal asphyxia was the commonest (56.1%) risk factor of Cerebral Palsy. Among all the CTs 116 (22.0%) were with normal finding and 409 (78.0%) were with various types of abnormal findings. White Matter Injury was present in 79 (15.0%) of cases and among these volume loss in periventricular areas with ventricular dilatation and deep white matter damage was common. The next abnormalities were Focal Vascular Insults (9.0%), Malformations (5.0%) and Unclassified lesions (4.0%). Grey Matter Injury was common in spastic type of cerebral palsy but there was much overlapping of abnormal findings and most (66.3%) insults occurred in perinatal period. Conclusion: CT scanning of brain is a comparable test to detect the central nervous system abnormalities in resource poor areas. Grey matter injury is the common abnormality in Cerebral palsy but there is much overlapping between CT Scanning findings and clinical diagnosis. J Bangladesh Coll Phys Surg 2022; 40: 31-38

Non-modifiable factors as moderators of the relationship between physical activity and brain volume: A cross-sectional UK Biobank study

Background: Grey matter atrophy occurs as a function of ageing and is accelerated in dementia. Previous research suggests physical activity attenuates grey matter loss; however, there appears to be individual variability in this effect. Understanding factors that can affect the relationship between physical activity and brain volume may enable prediction of individual response, and aid in identifying those that gain the greatest neural benefits from physical activity. The current study examined the relationship between objectively-measured physical activity and brain volume; and whether this relationship is moderated by age, sex, or a priori candidate genetic factors. Methods: Data from 10,083 men and women (50 years and over) of the UK Biobank were used to examine: 1) the relationship between objectively-measured physical activity and brain volume; and 2) whether the relationship between objectively-measured physical activity and brain volume is moderated by age, sex, brain-derived neurotrophic factor (BDNF) Val66Met, or apolipoprotein (APOE) e4 allele carriage. All participants underwent a magnetic resonance imaging scan to quantify grey matter volumes, physical activity monitoring via accelerometry, and genotyping. Results: Physical activity was associated with total grey matter volume (B = 0.14, p = 0.001, q = 0.005) and right hippocampal volume (B = 1.45, p = 0.008, q = 0.016). The physical activity*sex interaction predicted cortical grey matter (B = 0.22, p = 0.003, q = 0.004), total grey matter (B = 0.30, p < 0.001, q = 0.001), and right hippocampal volume (B = 3.60, p = 0.001, q = 0.002). Post-hoc analyses revealed males received benefit from higher physical activity levels, in terms of greater cortical grey matter volume (B = 0.13, p = 0.01), total grey matter volume (B=0.23, p < 0.001), and right hippocampal volume (B = 3.05, p = 0.008). No moderating effects of age, APOE e4 allele carriage, or BDNF Val66Met genotype were observed. Discussion: Our results indicate that in males, but not females, an association exists between objectively-measured physical activity and grey matter volume. Future research should evaluate longitudinal brain volumetrics to better understand the nature of sex-effects on the relationship between physical activity and brain volume.

Usefulness of two-dimensional measurements for the evaluation of brain volume and disability in multiple sclerosis

Background Two-dimensional (2D) measures have been proposed as potential proxies for whole-brain volume in multiple sclerosis (MS). Objective To verify whether 2D measurements by routine MRI are useful in predicting brain volume or disability in MS. Methods In this cross-sectional analysis, eighty-five consecutive Japanese MS patients—relapsing-remitting MS (81%) and progressive MS (19%)—underwent 1.5 Tesla T1-weighted 3D MRI examinations to measure whole-brain and grey matter volume. 2D measurements, namely, third ventricle width, lateral ventricle width (LVW), brain width, bicaudate ratio, and corpus callosum index (CCI), were obtained from each scan. Correlations between 2D measurements and 3D measurements, the Expanded Disability Status Scale (EDSS), or processing speed were analysed. Results The third and lateral ventricle widths were well-correlated with the whole-brain volume ( p < 0.0001), grey matter volume ( p < 0.0001), and EDSS scores ( p = 0.0001, p = .0004, respectively).The least squares regression model revealed that 78% of the variation in whole-brain volume could be explained using five explanatory variables, namely, LVW, CCI, age, sex, and disease duration. By contrast, the partial correlation coefficient excluding the effect of age showed that the CCI was significantly correlated with the EDSS and processing speed ( p < 0.0001). Conclusion Ventricle width correlated well with brain volumes, while the CCI correlated well with age-independent (i.e. disease-induced) disability.

Sex Differences in Brain Structure Account for the Sexual Distinction on Balanced Time Perspective

Sex differences in behaviour and cognition have been widely observed, however, little is known about such differences in maintaining a balanced time perspective or their potential underlying neural substrates. To answer the above questions, two studies were conducted. In Study 1, time perspective was assessed in 1,913 college students, including 771 males and 1,092 females, and demonstrated that females had a significantly more balanced time perspective than males. In Study 2, 58 males and 47 females underwent assessment of time perspective and structural brain imaging. Voxel-based morphometry analysis and cortical thickness analysis were used to analyse the structural imaging data. Results showed that compared with males, females demonstrated a more balanced time perspective, which primarily related to lower grey matter volume in left precuneus, right cerebellum, right putamen and left supplementary motor area. Analysis of cortical thickness failed to reveal any significant sex differences. Furthermore, the sex difference in grey matter volume of left precuneus, right cerebellum, right putamen and left supplementary motor area could account for the difference in balanced time perspective between males and females. The findings deepen our understanding of sex differences in human cognition and their potential neural signature, and may inform tailored interventions to support a balanced time perspective in daily life.