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In diffusion tensor magnetic resonance imaging (DT-MRI), limitations concerning complex fiber architecture (when an image voxel contains fiber populations with more than one dominant orientation) are well-known. Fractional anisotropy (FA) values are lower in such areas because of a lower directionality of diffusion on the voxel-scale, which makes the interpretation of FA less straightforward. Moreover, the interpretation of the axial and radial diffusivities is far from trivial when there is more than one dominant fiber orientation within a voxel. In this work, using (i) theoretical considerations, (ii) simulations, and (iii) experimental data, it is demonstrated that the mean diffusivity (or the trace of the diffusion tensor) is lower in complex white matter configurations, compared with tissue where there is a single dominant fiber orientation within the voxel. We show that the magnitude of this reduction depends on various factors, including configurational and microstructural properties (e.g., the relative contributions of different fiber populations) and acquisition settings (e.g., the b-value). These results increase our understanding of the quantitative metrics obtained from DT-MRI and, in particular, the effect of the microstructural architecture on the mean diffusivity. More importantly, they reinforce the growing awareness that differences in DT-MRI metrics need to be interpreted cautiously. ► The mean diffusivity (MD) in diffusion tensor MRI is affected by crossing fibers. ► MD values are lower in complex fiber architecture than in single fiber voxels. ► This is shown using theoretical considerations, simulations and in vivo experiments. ► In vivo, mean diffusivity values decrease when fibers cross at larger angles.

Quantification of brain morphology has become an important cornerstone in understanding brain structure. Measures of cortical morphology such as thickness and surface area are frequently used to compare groups of subjects or characterise longitudinal changes. However, such measures are often treated as independent from each other. A recently described scaling law, derived from a statistical physics model of cortical folding, demonstrates that there is a tight covariance between three commonly used cortical morphology measures: cortical thickness, total surface area, and exposed surface area. We show that assuming the independence of cortical morphology measures can hide features and potentially lead to misinterpretations. Using the scaling law, we account for the covariance between cortical morphology measures and derive novel independent measures of cortical morphology. By applying these new measures, we show that new information can be gained; in our example we show that distinct morphological alterations underlie healthy ageing compared to temporal lobe epilepsy, even on the coarse level of a whole hemisphere. We thus provide a conceptual framework for characterising cortical morphology in a statistically valid and interpretable manner, based on theoretical reasoning about the shape of the cortex.

Background Tumour hypoxia resulting from inadequate perfusion is common in many solid tumours, including prostate cancer, and constitutes a major limiting factor in radiation therapy that contributes to treatment resistance. Emerging research in preclinical animal models indicates that exercise has the potential to enhance the efficacy of cancer treatment by modulating tumour perfusion and reducing hypoxia; however, evidence from randomised controlled trials is currently lacking. The ‘Exercise medicine as adjunct therapy during RADIation for CAncer of the prostaTE’ (ERADICATE) study is designed to investigate the impact of exercise on treatment response, tumour physiology, and adverse effects of treatment in prostate cancer patients undergoing external beam radiation therapy (EBRT). Methods The ERADICATE study is a two-arm, parallel group, phase II randomised controlled trial. Fifty patients diagnosed with prostate cancer will be randomised (1:1) to either an exercise intervention group (EBRT + exercise) or a usual care control group (EBRT only) for the duration of treatment (i.e., 2 to 8 weeks of EBRT). The exercise intervention will be clinic-based and supervised by exercise physiologists. Exercise sessions will include moderate- to vigorous-intensity aerobic and resistance exercise conducted two to three times per week for 60 min per session. Treatment response (primary outcome) will be assessed by change in tumour apparent diffusion coefficient derived from magnetic resonance imaging. Secondary outcomes will include acute and chronic changes in tumour perfusion and hypoxia, treatment-related toxicity, body composition, physical function, and quality of life. Survival outcomes will be assessed as exploratory endpoints. Study measurements will be conducted at baseline (i.e., prior to commencing EBRT), immediately after completion of EBRT, and during follow-up at 3 months as well as 2 years and 5 years post treatment. The study was approved by the Human Research Ethics Committee at Edith Cowan University. Discussion The ERADICATE study will investigate exercise as a novel therapeutic approach for sensitising prostate cancer to EBRT by targeting a known mechanism of treatment resistance. Improving treatment efficacy of EBRT with exercise may result in better patient outcomes clinically, while also addressing adverse effects of treatment and quality of life in prostate cancer patients. Trial registration The study was registered on the Australian New Zealand Clinical Trials Registry (ACTRN12624000786594) on 26/06/2024.

Evaluation of neurodegenerative disease progression may be assisted by quantification of the volume of structures in the human brain using magnetic resonance imaging (MRI). Automated segmentation software has improved the feasibility of this approach, but often the reliability of measurements is uncertain. We have established a unique dataset to assess the repeatability of brain segmentation and analysis methods. We acquired 120 T1-weighted volumes from 3 subjects (40 volumes/subject) in 20 sessions spanning 31 days, using the protocol recommended by the Alzheimer's Disease Neuroimaging Initiative (ADNI). Each subject was scanned twice within each session, with repositioning between the two scans, allowing determination of test-retest reliability both within a single session (intra-session) and from day to day (inter-session). To demonstrate the application of the dataset, all 3D volumes were processed using FreeSurfer v5.1. The coefficient of variation of volumetric measurements was between 1.6% (caudate) and 6.1% (thalamus). Inter-session variability exceeded intra-session variability for lateral ventricle volume ( P <0.0001), indicating that ventricle volume in the subjects varied between days. Design Type(s) observation design • reference design • replicate design • time series design Measurement Type(s) structural magnetic resonance imaging Technology Type(s) Magnetic Resonance Imaging Factor Type(s) Session Sample Characteristic(s) Homo sapiens • brain Machine-accessible metadata file describing the reported data (ISA-Tab format)

This paper presents a systematic review of diffusion MRI (dMRI) and tractography of cranial nerves within the posterior fossa. We assess the effectiveness of the diffusion imaging methods used and examine their clinical applications. The Pubmed, Web of Science and EMBASE databases were searched from January 1st 1997 to December 11th 2017 to identify relevant publications. Any study reporting the use of diffusion imaging and/or tractography in patients with confirmed cranial nerve pathology was eligible for selection. Study quality was assessed using the Methodological Index for Non-Randomized Studies (MINORS) tool. We included 41 studies comprising 16 studies of patients with trigeminal neuralgia (TN), 22 studies of patients with a posterior fossa tumor and three studies of patients with other pathologies. Most acquisition protocols used single-shot echo planar imaging (88%) with a single b-value of 1,000 s/mm (78%) but there was significant variation in the number of gradient directions, in-plane resolution, and slice thickness between studies. dMRI of the trigeminal nerve generated interpretable data in all cases. Analysis of diffusivity measurements found significantly lower fractional anisotropy (FA) values within the root entry zone of nerves affected by TN and FA values were significantly lower in patients with multiple sclerosis. Diffusivity values within the trigeminal nerve correlate with the effectiveness of surgical treatment and there is some evidence that pre-operative measurements may be predictive of treatment outcome. Fiber tractography was performed in 30 studies (73%). Most studies evaluating fiber tractography involved patients with a vestibular schwannoma (82%) and focused on generating tractography of the facial nerve to assist with surgical planning. Deterministic tractography using diffusion tensor imaging was performed in 93% of cases but the reported success rate and accuracy of generating fiber tracts from the acquired diffusion data varied considerably. dMRI has the potential to inform our understanding of the microstructural changes that occur within the cranial nerves in various pathologies. Cranial nerve tractography is a promising technique but new avenues of using dMRI should be explored to optimize and improve its reliability.

In recent years, several new diffusion MRI approaches have been proposed to explore microstructural properties of the white matter, such as Q-ball imaging and spherical deconvolution-based techniques to estimate the orientation distribution function. These methods can describe the estimated diffusion profile with a higher accuracy than the more conventional second-rank diffusion tensor imaging technique. Despite many important advances, there are still inconsistent findings between different models that investigate the \"crossing fibers\" issue. Due to the high information content and the complex nature of the data, it becomes virtually impossible to interpret and compare results in a consistent manner. In this work, we present novel fiber tractography visualization approaches that provide a more complete picture of the microstructural architecture of fiber pathways: multi-fiber hyperstreamlines and streamribbons. By visualizing, for instance, the estimated fiber orientation distribution along the reconstructed tract in a continuous way, information of the local fiber architecture is combined with the global anatomical information derived from tractography. Facilitating the interpretation of diffusion MRI data, this approach can be useful for comparing different diffusion reconstruction techniques and may improve our understanding of the intricate white matter network.

Purpose Gliomas are the commonest malignant brain tumours. Baseline characteristics on structural MRI, such as size, enhancement proportion and eloquent brain involvement inform grading and treatment planning. Currently, free-text imaging reports depend on the individual style and experience of the radiologist. Standardisation may increase consistency of feature reporting. Methods We compared 100 baseline free-text reports for glioma MRI scans with a structured feature list based on VASARI criteria and performed a full second read to document which VASARI features were in the baseline report. Results We found that quantitative features including tumour size and proportion of necrosis and oedema/infiltration were commonly not included in free-text reports. Thirty-three percent of reports gave a description of size only, and 38% of reports did not refer to tumour size at all. Detailed information about tumour location including involvement of eloquent areas and infiltration of deep white matter was also missing from the majority of free-text reports. Overall, we graded 6% of reports as having omitted some key VASARI features that would alter patient management. Conclusions Tumour size and anatomical information is often omitted by neuroradiologists. Comparison with a structured report identified key features that would benefit from standardisation and/or quantification. Structured reporting may improve glioma reporting consistency, clinical communication, and treatment decisions.

Background: In epilepsy, cognitive difficulties are common, partly a consequence of anti-seizure medications (ASM), and cognitive side-effects are often considered to be more disabling than seizures and significantly affect quality of life. Functional MRI during verbal fluency tasks demonstrated impaired frontal activation patterns and failed default mode network deactivation in people taking ASM with unfavourable cognitive profiles. The cognitive effect of ASMs given at different dosages in monotherapy, or in different combinations, remains to be determined. Methods: Here, we compared the effects of different drug loads on verbal fluency functional MRI (fMRI) in people (i) taking dual therapy of ASMs either considered to be associated with moderate (levetiracetam, lamotrigine, lacosamide, carbamazepine/oxcarbazepine, eslicarbazepine, valproic acid; n=119, 56 females) or severe (topiramate, zonisamide) side-effects; n=119, 56 females), (ii) taking moderate ASMs in either mono-, dual- or triple-therapy (60 subjects in each group), or (iii) taking different dosages of ASMs with moderate side-effect profiles (n=180). “Drug load” was defined as a composite value of numbers and dosages of medications, normalised to account for the highest and lowest dose of each specific prescribed medication. Results: In people taking \"moderate\" ASMs (n=119), we observed higher verbal-fluency related to left inferior frontal gyrus and right inferior parietal fMRI activations than in people taking \"severe\" ASMs (n=119). Irrespective of the specific ASM, people on monotherapy (n=60), showed greater frontal activations than people taking two (n=60), or three ASMs (n=60). People on two ASMs showed less default mode (precuneus) deactivation than those on monotherapy. In people treated with \"moderate\" ASMs (n=180), increased drug load correlated with reduced activation of language-related regions and the right piriform cortex. Conclusion: Our study delineates the effects of polytherapy and high doses of ASMs when given in monotherapy on the functional anatomy of langauge. Irrespective of the cognitive profile of individual ASMs, each additional ASM results in additional alterations of cognitive activation patterns. Selection of ASMs with moderate cognitive side effects, and low doses of ASMs when given in polytherapy, could reduce the cognitive effect.

During the last decade, diffusion tensor imaging (DTI) has been used extensively to investigate microstructural properties of white matter fiber pathways. In many of these DTI-based studies, fiber tractography has been used to infer relationships between bundle-specific mean DTI metrics and measures-of-interest (e.g., when studying diffusion changes related to age, cognitive performance, etc.) or to assess potential differences between populations (e.g., comparing males vs. females, healthy vs. diseased subjects, etc.). As partial volume effects (PVEs) are known to affect tractography and, subsequently, the estimated DTI measures sampled along these reconstructed tracts in an adverse way, it is important to gain insight into potential confounding factors that may modulate this PVE. For instance, for thicker fiber bundles, the contribution of PVE-contaminated voxels to the mean metric for the entire fiber bundle will be smaller, and vice-versa — which means that the extent of PVE-contamination will vary from bundle to bundle. With the growing popularity of tractography-based methods in both fundamental research and clinical applications, it is of paramount importance to examine the presence of PVE-related covariates, such as thickness, orientation, curvature, and shape of a fiber bundle, and to investigate the extent to which these hidden confounds affect diffusion measures. To test the hypothesis that these PVE-related covariates modulate DTI metrics depending on the shape of a bundle, we performed simulations with synthetic diffusion phantoms and analyzed bundle-specific DTI measures of the cingulum and the corpus callosum in 55 healthy subjects. Our results indicate that the estimated bundle-specific mean values of diffusion metrics, including the frequently used fractional anisotropy and mean diffusivity, were indeed modulated by fiber bundle thickness, orientation, and curvature. Correlation analyses between gender and diffusion measures yield different results when volume is included as a covariate. This indicates that incorporating these PVE-related factors in DTI analyses is imperative to disentangle changes in “true microstructural” tissue properties from these hidden covariates. ► In fiber tract simulations, DTI measures (e.g., FA, MD) correlate with bundle volume. ► Confirming these simulations, FA was correlated with bundle volume in the cingulum. ► Correlations of FA with gender change when bundle volume is included as a covariate. ► We suggest to include tract volume as a covariate to improve DTI analysis specificity.

Objective To develop language functional MRI (fMRI) methods that accurately predict postsurgical naming decline in temporal lobe epilepsy (TLE). Methods Forty‐six patients with TLE (25 left) and 19 controls underwent two overt fMRI paradigms (auditory naming and picture naming, both with active baseline conditions) and one covert task (verbal fluency). Clinical naming performance was assessed preoperatively and 4 months following anterior temporal lobe resection. Preoperative fMRI activations were correlated with postoperative naming decline. Individual laterality indices (LI) were calculated for temporal (auditory and picture naming) and frontal regions (verbal fluency) and were considered as predictors of naming decline in multiple regression models, along with other clinical variables (age at onset of seizures, preoperative naming scores, hippocampal volume, age). Results In left TLE patients, activation of the left posterior inferior temporal gyrus during auditory naming and activation of left fusiform gyrus during picture naming were related to greater postoperative naming decline. Activation LI were the best individual predictors of naming decline in a multivariate regression model. For picture naming, an LI of higher than 0.34 gave 100% sensitivity and 92% specificity (positive predictive value (PPV) 91.6%). For auditory naming, a temporal lobe LI higher than 0.18 identified all patients with a clinically significant naming decline with 100% sensitivity and 58% specificity (PPV: 58.3%). No effect was seen for verbal fluency. Interpretation Auditory and picture naming fMRI are clinically applicable to predict postoperative naming decline after left temporal lobe resection in individual patients, with picture naming being more specific.