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Successful segmentation of the total intracranial vault (ICV) and ventricles is of critical importance when studying neurodegeneration through neuroimaging. We present iCVMapper and VentMapper, robust algorithms that use a convolutional neural network (CNN) to segment the ICV and ventricles from both single and multi-contrast MRI data. Our models were trained on a large dataset from two multi-site studies (N=528 subjects for ICV, N=501 for ventricular segmentation) consisting of older adults with varying degrees of cerebrovascular lesions and atrophy, which pose significant challenges for most segmentation approaches. The models were tested on 238 participants, including subjects with vascular cognitive impairment and high white matter hyperintensity burden. Two of the three test sets came from studies not used in the training dataset. We assessed our algorithms relative to four state-of-the-art ICV extraction methods (MONSTR, BET, Deep Extraction, FreeSurfer), as well as a ventricular segmentation tool (FreeSurfer). Our multi-contrast models outperformed other methods across all evaluation metrics, with average Dice coefficients of 0.98 and 0.94 for ICV and ventricular segmentation respectively. Both models were also the most time efficient, segmenting the structures in orders of magnitude faster than some of the other available methods. Our networks showed an increased accuracy with the use of a conditional random field (CRF) as a post-processing step. We further validated both segmentation models, highlighting their robustness to images with lower resolution and signal-to-noise ratio, compared to tested techniques. The pipeline and models are available at: https://icvmapp3r.readthedocs.io and https://ventmapp3r.readthedocs.io to enable further investigation of the roles of ICV and ventricles in relation to normal aging and neurodegeneration in large multi-site studies.

Background/Objective: Structural brain magnetic resonance imaging (MRI) is not mandatory in Alzheimer's disease (AD) research or clinical guidelines. We aimed to explore the use of structural brain MRI in AD/mild cognitive impairment (MCI) trials over the past 10 years and determine the frequency with which inclusion of standardized structural MRI acquisitions detects comorbid vascular and non-vascular pathologies. Methods: We systematically searched ClinicalTrials.gov for AD clinical trials to determine their neuroimaging criteria and then used data from an AD/MCI cohort who underwent standardized MRI protocols, to determine type and incidence of clinically relevant comorbid pathologies. Results: Of 210 AD clinical trials, 105 (50%) included structural brain imaging in their eligibility criteria. Only 58 (27.6%) required MRI. 16,479 of 53,755 (30.7%) AD participants were in trials requiring MRI. In the observational AD/MCI cohort, 141 patients met clinical criteria; 22 (15.6%) had relevant MRI findings, of which 15 (10.6%) were exclusionary for the study. Discussion: In AD clinical trials over the last 10 years, over two-thirds of participants could have been enrolled without brain MRI and half without even a brain CT. In a study sample, relevant comorbid pathology was found in 15% of participants, despite careful screening. Standardized structural MRI should be incorporated into NIA-AA diagnostic guidelines (when available) and research frameworks routinely to reduce diagnostic heterogeneity.

© 2019 International Society for Magnetic Resonance in Medicine Background: Characterization of left atrial (LA) hemodynamics in paroxysmal atrial fibrillation (PAF) may provide valuable insights for thromboembolic risk. Purpose: To evaluate LA vortex formation and velocity distributions by 4D flow MRI and identify associations with age, LA/LV (left ventricle) function, and established risk scores. Study Type: Prospective clinical. Population: Patients with PAF (n = 45, 46 ± 14 years) and healthy controls (n = 15, 54 ± 9 years) were enrolled. MRI Sequences: 3T standardized cardiac MRI protocol inclusive of 4D flow MRI. Assessment: Flow analysis planes were prescribed at each pulmonary vein. Velocity distribution analysis and vortex size quantification by the Lambda2 (λ2) method were performed in the LA. Statistics: Pearson or Spearman's correlation coefficients, r, were calculated to identify relationships between 4D flow-derived LA parameters and age, LA/LV function, and CHA2DS2-VASc stroke risk score. Univariate and multivariate determinants of stroke risk were assessed using linear regressions. To compare parameters within multiple groups, one-way analysis of variance or Kruskal–Wallis was used. Results: LA vortice sizes were observed in all subjects using λ2 showing inverse correlations with peak pulmonary vein inflow velocities (P < 0.05), and positive correlations with LA volume (P < 0.05). Vortex size was elevated in PAF at all phases of the cardiac cycle, being most prominent at end early diastole (3.98 ± 1.84 cm3 vs. 6.93 ± 3.11 cm3, P = 0.001). Velocity distribution analysis showed a greater incidence of flow stasis among patients with PAF (P < 0.05). In univariate regression, vortex size was associated with the CHA2DS2-VASc risk score at peak systole (0.457 ± 0.038, P ≤ 0.001). However, in multivariate regression age was the dominant determinant of stroke risk (0.348 ± 0.012, P = 0.006). Data Conclusion: This study demonstrated that LA vortex size is increased among low-risk patients with PAF and is associated with the CHA2DS2-VASc risk score. Age remained the dominant determinant of stroke risk. Level of Evidence: 2. Technical Efficacy: Stage 3. J. Magn. Reson. Imaging 2020;51:871–884.

BackgroundThe efficacy of acute ischemic stroke treatment is affected by thrombus composition and age, yet no diagnostic method capable of quantitative thrombus characterization currently exists. This in vitro study evaluates the use of R2*, quantitative susceptibility mapping (QSM), and proton density fat fraction (FF) maps derived from a single gradient echo (GRE) MRI acquisition for characterizing clot of various hematocrit, as well as added calcified and lipidic components, throughout aging.MethodsTwo thrombus phantoms containing porcine clots (10–60% hematocrit, one with added calcium or lard) were scanned serially throughout 6 days of aging. Three-dimensional multi-echo GRE imaging was used to generate R2*, QSM, and FF maps, from which mean values for all clots at every time point were obtained. Receiver operating characteristic analysis was used to derive thresholds differentiating acute from chronic clot, and measured R2* and QSM were tested for their ability to estimate clot hematocrit.ResultsR2* and QSM varied minimally over the first 6 hours of aging (acute), and QSM was found to linearly relate to clot hematocrit. Beyond 6 hours (chronic), R2* and QSM increased considerably over time and hematocrit could be estimated from the R2*/QSM ratio. R2* and QSM thresholds of 22 s-1 and 0.165 ppm differentiated acute from chronic clots with a sensitivity/specificity of 100%/100% and 85%/92%, respectively. QSM and FF maps definitively distinguished calcium and lipid, respectively, from clots of any hematocrit and age.ConclusionsR2*, QSM, and FF from a single multi-echo GRE scan discriminated hematocrit and age, and distinguished calcification and lipid withinin vitro clot.

Background and Purpose: Identification of changesin brain microstructure following mild traumatic brain injury (mTBI) could be instrumental in understanding the underlying pathophysiology. The purpose of this study was to apply neurite orientation dispersion and density imaging (NODDI) to a rodent model of mTBI to determine whether microstructural changes could be detected immediately following injury. Methods: Fifteen adult male Wistar rats were scanned on a Bruker 9.4 Tesla small animal MRI using a multi-shell acquisition (30 b = 1000 s/mm2 and 60 b = 2000 s/mm2). Nine animals experienced a single closed head controlled cortical impact followed by NODDI from 1 to 4 h post injury. Region of interest analysis focused on the corpus callosum and hippocampus. A mixed analysis of variance (ANOVA) was used to determine statistically significant interactions in neurite density index (NDI), orientation dispersion index (ODI), fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity. Follow up repeated-measures ANOVAs were used to determine individual changes over time. Results: NDI showed a significant increase in the hippocampus and corpus callosum following injury, while ODI showed increases in the corpus callosum. No significant changes were observed in the sham control animals. No changes were found in FA, MD, AD, or RD. Histological analysis revealed increased glial fibrillary acidic protein staining relative to controls in both the hippocampus and corpus callosum, with evidence of activated astrocytes in these regions. Conclusions: Changes in NODDI metrics were detected as early as 1 h following mTBI. No changes were detected with conventional diffusion tensor imaging (DTI) metrics, suggesting that NODDI provides greater sensitivity to microstructural changes than conventional DTI.

We have previously reported long-term changes in the brains of non-concussed varsity rugby players using magnetic resonance spectroscopy (MRS), diffusion tensor imaging (DTI) and functional magnetic imaging (fMRI). Others have reported cognitive deficits in contact sport athletes that have not met the diagnostic criteria for concussion. These results suggest that repetitive mild traumatic brain injuries (rmTBIs) that are not severe enough to meet the diagnostic threshold for concussion, produce long-term consequences. We sought to characterize the neuroimaging, cognitive, pathological and metabolomic changes in a mouse model of rmTBI. Using a closed-skull model of mTBI that when scaled to human leads to rotational and linear accelerations far below what has been reported for sports concussion athletes, we found that 5 daily mTBIs triggered two temporally distinct types of pathological changes. First, during the first days and weeks after injury, the rmTBI produced diffuse axonal injury, a transient inflammatory response and changes in diffusion tensor imaging (DTI) that resolved with time. Second, the rmTBI led to pathological changes that were evident months after the injury including: changes in magnetic resonance spectroscopy (MRS), altered levels of synaptic proteins, behavioural deficits in attention and spatial memory, accumulations of pathologically phosphorylated tau, altered blood metabolomic profiles and white matter ultrastructural abnormalities. These results indicate that exceedingly mild rmTBI, in mice, triggers processes with pathological consequences observable months after the initial injury. Supplementary Information The online version contains supplementary material available at 10.1186/s40478-021-01161-2.

With improvements to both scan quality and facial recognition software, there is an increased risk of participants being identified by a 3D render of their structural neuroimaging scans, even when all other personal information has been removed. To prevent this, facial features should be removed before data are shared or openly released, but while there are several publicly available software algorithms to do this, there has been no comprehensive review of their accuracy within the general population. To address this, we tested multiple algorithms on 300 scans from three neuroscience research projects, funded in part by the Ontario Brain Institute, to cover a wide range of ages (3–85 years) and multiple patient cohorts. While skull stripping is more thorough at removing identifiable features, we focused mainly on defacing software, as skull stripping also removes potentially useful information, which may be required for future analyses. We tested six publicly available algorithms (afni_refacer, deepdefacer, mri_deface, mridefacer, pydeface, quickshear), with one skull stripper (FreeSurfer) included for comparison. Accuracy was measured through a pass/fail system with two criteria; one, that all facial features had been removed and two, that no brain tissue was removed in the process. A subset of defaced scans were also run through several preprocessing pipelines to ensure that none of the algorithms would alter the resulting outputs. We found that the success rates varied strongly between defacers, with afni_refacer (89%) and pydeface (83%) having the highest rates, overall. In both cases, the primary source of failure came from a single dataset that the defacer appeared to struggle with - the youngest cohort (3–20 years) for afni_refacer and the oldest (44–85 years) for pydeface, demonstrating that defacer performance not only depends on the data provided, but that this effect varies between algorithms. While there were some very minor differences between the preprocessing results for defaced and original scans, none of these were significant and were within the range of variation between using different NIfTI converters, or using raw DICOM files.

BackgroundRegional changes to cortical thickness in individuals with neurodegenerative and cerebrovascular diseases (CVD) can be estimated using specialized neuroimaging software. However, the presence of cerebral small vessel disease, focal atrophy, and cortico-subcortical stroke lesions, pose significant challenges that increase the likelihood of misclassification errors and segmentation failures.PurposeThe main goal of this study was to examine a correction procedure developed for enhancing FreeSurfer’s (FS’s) cortical thickness estimation tool, particularly when applied to the most challenging MRI obtained from participants with chronic stroke and CVD, with varying degrees of neurovascular lesions and brain atrophy.MethodsIn 155 CVD participants enrolled in the Ontario Neurodegenerative Disease Research Initiative (ONDRI), FS outputs were compared between a fully automated, unmodified procedure and a corrected procedure that accounted for potential sources of error due to atrophy and neurovascular lesions. Quality control (QC) measures were obtained from both procedures. Association between cortical thickness and global cognitive status as assessed by the Montreal Cognitive Assessment (MoCA) score was also investigated from both procedures.ResultsCorrected procedures increased “Acceptable” QC ratings from 18 to 76% for the cortical ribbon and from 38 to 92% for tissue segmentation. Corrected procedures reduced “Fail” ratings from 11 to 0% for the cortical ribbon and 62 to 8% for tissue segmentation. FS-based segmentation of T1-weighted white matter hypointensities were significantly greater in the corrected procedure (5.8 mL vs. 15.9 mL, p < 0.001). The unmodified procedure yielded no significant associations with global cognitive status, whereas the corrected procedure yielded positive associations between MoCA total score and clusters of cortical thickness in the left superior parietal (p = 0.018) and left insula (p = 0.04) regions. Further analyses with the corrected cortical thickness results and MoCA subscores showed a positive association between left superior parietal cortical thickness and Attention (p < 0.001).ConclusionThese findings suggest that correction procedures which account for brain atrophy and neurovascular lesions can significantly improve FS’s segmentation results and reduce failure rates, thus maximizing power by preventing the loss of our important study participants. Future work will examine relationships between cortical thickness, cerebral small vessel disease, and cognitive dysfunction due to neurodegenerative disease in the ONDRI study.

ObjectiveTo determine whether intranasal oxytocin, alone or in combination with instructed mimicry of facial expressions, would augment neural activity in patients with frontotemporal dementia (FTD) in brain regions associated with empathy, emotion processing, and the simulation network, as indexed by blood oxygen–level dependent (BOLD) signal during fMRI.MethodsIn a placebo-controlled, randomized crossover design, 28 patients with FTD received 72 IU intranasal oxytocin or placebo and then completed an fMRI facial expression mimicry task.ResultsOxytocin alone and in combination with instructed mimicry increased activity in regions of the simulation network and in limbic regions associated with emotional expression processing.ConclusionsThe findings demonstrate latent capacity to augment neural activity in affected limbic and other frontal and temporal regions during social cognition in patients with FTD, and support the promise and need for further investigation of these interventions as therapeutics in FTD.ClinicalTrials.gov identifierNCT01937013.Classification of evidenceThis study provides Class III evidence that a single dose of 72 IU intranasal oxytocin augments BOLD signal in patients with FTD during viewing of emotional facial expressions.

The mathematization of nature is an age-old concept. The Greeks sought harmony in the celestial spheres. The Arab geometers constructed a spherical geometry of the heavens. Later, Galileo Galilei arithmetized kinematics. As the centuries advanced, polymaths like the Dutchman Christiaan Huygens applied more advanced mathematics in order to understand natural phenomena. It was not until the turn of the twentieth century that a more comprehensive mathematical approach to understanding biological phenomena was sought by D'Arcy Wentworth Thompson. This leads us to our current review of the biophysics of visual edge detection. This is an unfolding saga of stunning experimental revelations in unison with an underlying mathematical edifice. The concept of visual contrast is a fundamental idea in order to understand the phenomenon of visual edge detection. We begin with contrast visual testing and the development of frequency tuning curves, which provided an insight into the multi-channel processing of selective spatial frequencies by the visual cortex. The single-cell recordings from the simple cells of the cat visual cortex unfolded the gamma distribution curves of different neuronal firing frequencies for different spatial frequencies. The theoretical construction of the convolution of Gabor wavelets with stimulus intensity goes hand-in-hand with the experimental observation of the separation of simple visual cortical cells into even and odd functions, a spectacular finding. In this review, we march the reader through the mathematical basics and the pathophysiologic correlates. Beginning with a simple Fourier analysis of a square wave, Weber's biophysical law, and the gamma distribution of contrast tuning curves, we gradually introduce Fourier transforms, the uncertainty principle of waveform analysis, the basics of wavelet theory, Gabor elementary signals and transforms, the concepts of coherence, and Weyl group representation theory. Group theory provides the symmetry operations necessary to preserve the fidelity of an image as it travels from the retina and cascades up the visual cortex. Unitary operators that allow a retinal displacement of an image to be reflected by a similar displacement in the visual cortex is also a fundamental principle. Along the way, we encounter the Convolution Theorem of Fourier transforms, which is critical in constructing a visual percept. We intermittently interject relevant clinical data as we unpack the mathematical complexities. The advanced mathematics deployed in the biophysics of vision makes for difficult reading. There is a paucity of step-by-step reviews of this subject. Our approach is heuristic and at the end of this review, one should be able to follow superficially the algorithmic steps in understanding visual edge detection using Gabor filters. Therefore, we will adopt the Socratic method of asking questions and providing answers to help us through the complex web of mathematics. In a nutshell, we will show that a Gabor filter is the inner product of a Gaussian distribution and the wave function. The Fourier transform of the convolution of the Gabor filter and the stimulus intensity function is what is recorded from simple visual cortical cells. This is not a coincidental observation, as nature economizes and utilizes a function that minimizes the uncertainty principle of signal extraction.

A holistic multitask regression approach was implemented to tackle the limitations of clinical image analysis. Standard practice requires identifying multiple anatomic structures in multiple planes from multiple anatomic regions using multiple modalities. The proposed novel holistic multitask regression network (HMR-Net) formulates organ segmentation as a multitask learning problem. Multitask learning leverages the strength of joint task problem solving from capturing task correlations. HMR-Net performs multitask regression by estimating an organ’s class, regional location, and precise contour coordinates. The estimation of each coordinate point also corresponds to another regression task. HMR-Net leverages hierarchical multiscale and fused organ features to handle nonlinear relationships between image appearance and distinct organ properties. Simultaneously, holistic shape information is captured by encoding coordinate correlations. The multitask pipeline enables the capturing of holistic organ information (e.g. class, location, shape) to perform shape regression for medical image segmentation. HMR-Net was validated on eight representative datasets obtained from a total of 222 subjects. A mean average precision and dice score reaching up to 0.81 and 0.93, respectively, was achieved on the representative multiapplication database. The generalized model demonstrates comparable or superior performance compared to state-of-the-art algorithms. The high-performance accuracy demonstrates our model as an effective general framework to perform organ shape regression in multiple applications. This method was proven to provide high-contrast sensitivity to delineate even the smallest and oddly shaped organs. HMR-Net’s flexible framework holds great potential in providing a fully automatic preliminary analysis for multiple types of medical images.

White matter tracts are known to be susceptible to injury following concussion. The objective of this study was to determine whether contact play in sport could alter white matter metabolite levels in female varsity athletes independent of changes induced by long-term exercise. Metabolite levels were measured by single voxel proton magnetic resonance spectroscopy (MRS) in the prefrontal white matter at the beginning (In-Season) and end (Off-Season) of season in contact (N = 54, rugby players) and non-contact (N = 23, swimmers and rowers) varsity athletes. Sedentary women (N = 23) were scanned once, at a time equivalent to the Off-Season time point. Metabolite levels in non-contact athletes did not change over a season of play, or differ from age matched sedentary women except that non-contact athletes had a slightly lower myo-inositol level. The contact athletes had lower levels of myo-inositol and glutamate, and higher levels of glutamine compared to both sedentary women and non-contact athletes. Lower levels of myo-inositol in non-contact athletes compared to sedentary women indicates long-term exercise may alter glial cell profiles in these athletes. The metabolite differences observed between contact and non-contact athletes suggest that non-contact athletes should not be used as controls in studies of concussion in high-impact sports because repetitive impacts from physical contact can alter white matter metabolite level profiles. It is imperative to use athletes engaged in the same contact sport as controls to ensure a matched metabolite profile at baseline.

The Ontario Neurodegenerative Research Initiative (ONDRI) is a 3 years multi-site prospective cohort study that has acquired comprehensive multiple assessment platform data, including 3T structural MRI, from neurodegenerative patients with Alzheimer's disease, mild cognitive impairment, Parkinson's disease, amyotrophic lateral sclerosis, frontotemporal dementia, and cerebrovascular disease. This heterogeneous cross-section of patients with complex neurodegenerative and neurovascular pathologies pose significant challenges for standard neuroimaging tools. To effectively quantify regional measures of normal and pathological brain tissue volumes, the ONDRI neuroimaging platform implemented a semi-automated MRI processing pipeline that was able to address many of the challenges resulting from this heterogeneity. The purpose of this paper is to serve as a reference and conceptual overview of the comprehensive neuroimaging pipeline used to generate regional brain tissue volumes and neurovascular marker data that will be made publicly available online.

ObjectiveTo longitudinally assess brain microstructure and function in female varsity athletes participating in contact and noncontact sports.MethodsConcussion-free female rugby players (n = 73) were compared to age-matched (ages 18–23) female swimmers and rowers (n = 31) during the in- and off-season. Diffusion and resting-state fMRI (rs-fMRI) measures were the primary outcomes. The Sports Concussion Assessment Tool and head impact accelerometers were used to monitor symptoms and impacts, respectively.ResultsWe found cross-sectional (contact vs noncontact) and longitudinal (in- vs off-season) changes in white matter diffusion measures and rs-fMRI network connectivity in concussion-free contact athletes relative to noncontact athletes. In particular, mean, axial, and radial diffusivities were increased with decreased fractional anisotropy in multiple white matter tracts of contact athletes accompanied with default mode and visual network hyperconnectivity (p < 0.001). Longitudinal diffusion changes in the brainstem between the in- and off-season were observed for concussion-free contact athletes only, with progressive changes observed in a subset of athletes over multiple seasons. Axial diffusivity was significantly lower in the genu and splenium of the corpus callosum in those contact athletes with a history of concussion.ConclusionsTogether, these findings demonstrate longitudinal changes in the microstructure and function of the brain in otherwise healthy, asymptomatic athletes participating in contact sport. Further research to understand the long-term brain health and biological implications of these changes is required, in particular to what extent these changes reflect compensatory, reparative, or degenerative processes.

© 2019 by the American Society of Neuroimaging BACKGROUND AND PURPOSE: The anterior cingulate cortex (ACC) is involved in several cognitive processes including executive function. Degenerative changes of ACC are consistently seen in Alzheimer's disease (AD). However, volumetric changes specific to the ACC in AD are not clear because of the difficulty in segmenting this region. The objectives of the current study were to develop a precise and high-throughput approach for measuring ACC volumes and to correlate the relationship between ACC volume and cognitive function in AD. METHODS: Structural T 1 -weighted magnetic resonance images of AD patients (n = 47) and age-matched controls (n = 47) at baseline and at 24 months were obtained from the Alzheimer's disease neuroimaging initiative (ADNI) database and studied using a custom-designed semiautomated segmentation protocol. RESULTS: ACC volumes obtained using the semiautomated protocol were highly correlated to values obtained from manual segmentation (r =.98) and the semiautomated protocol was considerably faster. When comparing AD and control subjects, no significant differences were observed in baseline ACC volumes or in change in ACC volumes over 24 months using the two segmentation methods. However, a change in ACC volume over 24 months did not correlate with a change in mini-mental state examination scores. CONCLUSIONS: Our results indicate that the proposed semiautomated segmentation protocol is reliable for determining ACC volume in neurodegenerative conditions including AD.

© 2020 SPIE. C-Arm positioning for interventional spine procedures can often be associated with a steep learning curve. The current training standards involve using real X-rays on cadavers or via apprenticeship-based programs. To help limit excess radiation exposure, several radiation-free training systems have been proposed in the literature but there lacks a hands-on, cost-effective simulator that does not require access to a physical C-Arm. In order to expand the accessibility of radiation-free C-Arm training, we have developed a 10:1 scaled down C-Arm simulator using 3D-printed parts and wireless accelerometers for tracking. We generated Digitally Reconstructed Radiographs (DRRs) in real-time using a 1-dimensional transfer function operating on a ray-traced projection of a patient CT scan. To evaluate the efficacy of the system as a training tool, we conducted a user study in which anesthesiology and orthopedic residents were evaluated on the accuracy of their C-Arm placement for three standard views used in spinal injection procedures. Both the experimental group and control group were given the same evaluation task with the experimental group receiving 5 minutes of training on the system using real-time DRRs and a standardized two page curriculum on proper image acquisition. The experimental group achieved an angular error of 4.76±1.66° which was lower than the control group at 6.88±3.67° and the overall feedback of the system was positive based on a Likert scale questionnaire filled out by each participant. The results indicate that our system has high potential for improving C-Arm placement in interventional spine procedures and we plan to conduct a follow-up study to evaluate the long-term training capabilities of the simulator.

Background and Purpose— Little is known about the association between covert vascular brain injury and cognitive impairment in middle-aged populations. We investigated if scores on a cognitive screen were lower in individuals with higher cardiovascular risk, and those with covert vascular brain injury. Methods— Seven thousand five hundred forty-seven adults, aged 35 to 69 years, free of cardiovascular disease underwent a cognitive assessment using the Digital Symbol Substitution test and Montreal Cognitive Assessment, and magnetic resonance imaging (MRI) to detect covert vascular brain injury (high white matter hyperintensities, lacunar, and nonlacunar brain infarctions). Cardiovascular risk factors were quantified using the INTERHEART (A Global Study of Risk Factors for Acute Myocardial Infarction) risk score. Multivariable mixed models tested for independent determinants of reduced cognitive scores. The population attributable risk of risk factors and MRI vascular brain injury on low cognitive scores was calculated. Results— The mean age of participants was 58 (SD, 9) years; 55% were women. Montreal Cognitive Assessment and Digital Symbol Substitution test scores decreased significantly with increasing age ( P P Conclusions— Among a middle-aged community-dwelling population, scores on a cognitive screen were lower in individuals with higher cardiovascular risk factors or MRI vascular brain injury. Much of the population attributable risk of low cognitive scores can be attributed to lower educational attainment, higher cardiovascular risk factors, and MRI vascular brain injury.

Background Pulmonary imaging of chronic obstructive pulmonary disease (COPD) has focused on CT or MRI measurements, but these have not been evaluated in combination. Purpose To generate multiparametric response map (mPRM) measurements in ex-smokers with or without COPD by using volume-matched CT and hyperpolarized helium 3 (3He) MRI. Materials and Methods In this prospective study (https://clinicaltrials.gov, NCT02279329), participants underwent MRI and CT and completed pulmonary function tests, questionnaires, and the 6-minute walk test between December 2010 and January 2019. Disease status was determined by using Global initiative for chronic Obstructive Lung Disease (GOLD) criteria. The mPRM voxel values were generated by using co-registered MRI and CT labels. Kruskal-Wallis and Bonferroni tests were used to determine differences across disease severity, and correlations were determined by using Spearman coefficients. Results A total of 175 ex-smokers (mean age, 69 years ± 9 [standard deviation], 108 men) with or without COPD were evaluated. Ex-smokers without COPD had a larger fraction of normal mPRM voxels (60% vs 37%, 20%, and 7% for GOLD I, II, and III/IV disease, respectively; all P ≤ .001) and a smaller fraction of abnormal voxels, including small airways disease (normal CT, not ventilated: 5% vs 6% [not significant], 11%, and 19% [P ≤ .001 for both] for GOLD I, II, and III/IV disease, respectively) and mild emphysema (normal CT, abnormal apparent diffusion coefficient [ADC]: 33% vs 54%, 56%, and 54% for GOLD I, II, and III/IV disease respectively; all P ≤ .001). Normal mPRM measurements were positively correlated with forced expiratory volume in 1 second (FEV1) (r = 0.65, P < .001), the FEV1-to-forced vital capacity ratio (r = 0.81, P < .001), and diffusing capacity (r = 0.75, P < .001) and were negatively correlated with worse quality of life (r = -0.48, P < .001). Abnormal mPRM measurements of small airways disease (normal CT, not ventilated) and mild emphysema (normal CT, abnormal ADC) were negatively correlated with FEV1 (r = -0.65 and -0.42, respectively; P < .001) and diffusing capacity (r = -0.53 and -0.60, respectively; P < .001) and were positively correlated with worse quality of life (r = 0.45 and r = 0.33, respectively; P < .001), both of which were present in ex-smokers without COPD. Conclusion Multiparametric response maps revealed two abnormal structure-function results related to emphysema and small airways disease, both of which were unexpectedly present in ex-smokers with normal spirometry and CT findings. © RSNA, 2020 Online supplemental material is available for this article.

129Xe MRI provides rapid, sensitive, non-invasive, high spatial resolution and simultaneous measurements of pulmonary ventilation, tissue microstructure and gas exchange, and is poised for routine clinical assessments in patients with chronic lung diseasehttp://bit.ly/2PKkFcU

PURPOSE To develop a rapid Fourier decomposition (FD) free-breathing pulmonary 1 H MRI (FDMRI) image processing and biomarker pipeline for research use. METHODS We acquired MRI in 20 asthmatic subjects using a balanced steady-state free precession (bSSFP) sequence optimized for ventilation imaging. 2D 1 H MRI series were segmented by enforcing the spatial similarity between adjacent images and the right-to-left lung volume-ratio. The segmented lung series were co-registered using a coarse-to-fine deformable registration framework that used dual optimization techniques. All pairwise registrations were implemented in parallel and FD was performed to generate 2D ventilation-weighted maps and ventilation-defect-percent (VDP). Lung segmentation and registration accuracy were evaluated by comparing algorithm and manual lung-masks, deformed manual lung-masks, and fiducials in the moving and fixed images using Dice-similarity-coefficient (DSC), mean-absolute-distance (MAD), and target-registration-error (TRE). The relationship of FD-VDP and 3 He-VDP was evaluated using the Pearson-correlation-coefficient (r) and Bland Altman analysis. Algorithm reproducibility was evaluated using the coefficient-of-variation (CoV) and intra-class-correlation-coefficient (ICC) for segmentation, registration, and FD-VDP components. RESULTS For lung segmentation, there was a DSC of 95 ± 1.5% and MAD of 2.3 ± 0.5 mm, and for registration there was a DSC of 97 ± 0.8%, MAD of 1.6 ± 0.4 mm and TRE of 3.6 ± 1.2 mm. Reproducibility for segmentation DSC (CoV/ICC = 0.5%/0.92), registration TRE (CoV/ICC = 0.4%/0.98), and FD-VDP (Cov/ICC = 3.9%/0.97) was high. The pipeline required 10 min/subject. FD-VDP was correlated with 3 He-VDP (r = 0.69, P < 0.001) although there was a bias toward lower FD-VDP (bias = -4.9%). CONCLUSIONS We developed and evaluated a pipeline that provides a rapid and precise method for FDMRI ventilation maps.

© 2018 International Society for Magnetic Resonance in Medicine Background: Harmonized protocols to collect imaging data must be devised, employed, and maintained in multicentric studies to reduce interscanner variability in subsequent analyses. Purpose: To present a standardized protocol for multicentric research on dementia linked to neurodegeneration in aging, harmonized on all three major vendor platforms. The protocol includes a common procedure for qualification, quality control, and quality assurance and feasibility in large-scale studies. Study Type: Prospective. Subjects: The study involved a geometric phantom, a single individual volunteer, and 143 cognitively healthy, mild cognitively impaired, and Alzheimer's disease participants in a large-scale, multicentric study. Field Strength/Sequences: MRI was perform with 3T scanners (GE, Philips, Siemens) and included 3D T 1 w, PD/T 2 w, T *2 , T 2 w-FLAIR, diffusion, and BOLD resting state acquisitions. Assessment: Measures included signal- and contrast-to-noise ratios (SNR and CNR, respectively), total brain volumes, and total scan time. Statistical Tests: SNR, CNR, and scan time were compared between scanner vendors using analysis of variance (ANOVA) and Tukey tests, while brain volumes were tested using linear mixed models. Results: Geometric phantom T 1 w SNR was significantly (P < 0.001) higher in Philips (mean: 71.4) than Siemens (29.5), while no significant difference was observed between vendors for T 2 w (32.0 and 37.2, respectively, P = 0.243). Single individual volunteer T 1 w CNR was higher in subcortical regions for Siemens (P < 0.001), while Philips had higher cortical CNR (P = 0.044). No significant difference in brain volumes was observed between vendors (P = 0.310/0.582/0.055). The average scan time was 41.0 minutes (SD: 2.8) and was not significantly different between sites (P = 0.071) and cognitive groups (P = 0.853). Data Conclusion: The harmonized Canadian Dementia Imaging Protocol suits the needs of studies that need to ensure quality MRI data acquisition for the measurement of brain changes across adulthood, due to aging, neurodegeneration, and other etiologies. A detailed description, exam cards, and operators' manual are freely available at the following site: www.cdip-pcid.ca. Level of Evidence: 2. Technical Efficacy: Stage 2. J. Magn. Reson. Imaging 2019;49:456–465.

RATIONALE: Inflammation and smooth muscle dysfunction are integral components of severe asthma that contribute to luminal obstruction causing airflow limitation, ventilation heterogeneity, and symptoms. This is important for guiding treatment decisions directed at the inflammatory (e.g., anti-T-helper cell type 2 monoclonal antibodies) and noninflammatory, smooth muscle-mediated (e.g., bronchial thermoplasty) components of severe asthma. OBJECTIVES: To investigate the contribution of eosinophilic bronchitis and smooth muscle dysfunction to magnetic resonance imaging (MRI) ventilation heterogeneity in patients with severe asthma. METHODS: We measured the inhaled hyperpolarized gas MRI response to salbutamol as a marker of smooth muscle dysfunction, and sputum eosinophils as a marker of airway inflammation, and their contributions to ventilation heterogeneity (quantified as the ventilation defect percent [VDP]) in 27 patients with severe asthma. Spirometry and forced oscillation airway resistance measurements were also acquired pre- and postsalbutamol. Patients were dichotomized on the basis of sputum eosinophilia, and pre- and postsalbutamol VDP and physiological measurements were evaluated. MEASUREMENTS AND MAIN RESULTS: MRI VDP improved with salbutamol inhalation in patients in whom sputum eosinophilia was uncontrolled (≥3%, n = 16) (P = 0.002) and in those in whom it was controlled ( CONCLUSIONS: In patients with severe asthma, MRI regionally identifies the inflammatory and noninflammatory components of airway disease. Ventilation heterogeneity persists postsalbutamol in patients with uncontrolled eosinophilic bronchitis, which may be the functional consequence of airway inflammation.

Rationale and Objectives In patients with severe emphysema and poor quality of life, bronchoscopic lung volume reduction (BLVR) may be considered and guided based on lobar emphysema severity. In particular, x-ray computed tomography (CT) emphysema measurements are used to identify the most diseased and the second–most diseased lobes as BLVR targets. Inhaled gas magnetic resonance imaging (MRI) also provides chronic obstructive pulmonary disease (COPD) biomarkers of lobar emphysema and ventilation abnormalities. Our objective was to retrospectively evaluate CT and MRI biomarkers of lobar emphysema and ventilation in patients with COPD eligible for BLVR. We hypothesized that MRI would provide complementary biomarkers of emphysema and ventilation that help determine the most appropriate lung lobar targets for BLVR in patients with COPD. Materials and Methods We retrospectively evaluated 22 BLVR-eligible patients from the Thoracic Imaging Network of Canada cohort (diffusing capacity of the lung for carbon monoxide = 37 ± 12%predicted, forced expiratory volume in 1 second = 34 ± 7%predicted, total lung capacity = 131 ± 17%predicted, and residual volume = 216 ± 36%predicted). Lobar CT emphysema, measured using a relative area of Results In 7 of 22 patients, there were different CT and MRI predictions of the most diseased lobe. In some patients, there were large ventilation defects in lobes not targeted by CT, indicative of a poorly ventilated lung. CT and MRI classification of the most diseased and the second–most diseased lobes showed a fair-to-moderate intermethod reliability (Cohen κ = 0.40–0.59). Conclusions In this proof-of-concept retrospective analysis, quantitative MRI ventilation and CT emphysema measurements provided different BLVR targets in over 30% of the patients. The presence of large MRI ventilation defects in lobes next to CT-targeted lobes might also change the decision to proceed or to guide BLVR to a different lobar target.

Background Chatbot is a timely topic applied in various fields, including medicine and health care, for human-like knowledge transfer and communication. Machine learning, a subset of artificial intelligence, has been proven particularly applicable in health care, with the ability for complex dialog management and conversational flexibility. Objective This review article aims to report on the recent advances and current trends in chatbot technology in medicine. A brief historical overview, along with the developmental progress and design characteristics, is first introduced. The focus will be on cancer therapy, with in-depth discussions and examples of diagnosis, treatment, monitoring, patient support, workflow efficiency, and health promotion. In addition, this paper will explore the limitations and areas of concern, highlighting ethical, moral, security, technical, and regulatory standards and evaluation issues to explain the hesitancy in implementation. Methods A search of the literature published in the past 20 years was conducted using the IEEE Xplore, PubMed, Web of Science, Scopus, and OVID databases. The screening of chatbots was guided by the open-access Botlist directory for health care components and further divided according to the following criteria: diagnosis, treatment, monitoring, support, workflow, and health promotion. Results Even after addressing these issues and establishing the safety or efficacy of chatbots, human elements in health care will not be replaceable. Therefore, chatbots have the potential to be integrated into clinical practice by working alongside health practitioners to reduce costs, refine workflow efficiencies, and improve patient outcomes. Other applications in pandemic support, global health, and education are yet to be fully explored. Conclusions Further research and interdisciplinary collaboration could advance this technology to dramatically improve the quality of care for patients, rebalance the workload for clinicians, and revolutionize the practice of medicine.

BACKGROUND Fetal fat is indicative of the energy balance within the fetus, which may be disrupted in pregnancy complications such as fetal growth restriction, macrosomia, and gestational diabetes. Water-fat separated MRI is a technique sensitive to tissue lipid content, measured as fat fraction (FF), and can be used to accurately measure fat volumes. Modified two-point Dixon and chemical shift encoded MRI (CSE-MRI) are water-fat separated MRI techniques that could be applied to imaging of fetal fat. Modified two-point Dixon has biases present that are corrected in CSE-MRI which may contribute to differences in the fat measurements. PURPOSE To compare the measurement of fetal fat volume and FF by modified two-point Dixon and CSE-MRI. STUDY TYPE Cross-sectional study for comparison of two MRI pulse sequences. POPULATION Twenty-one pregnant women with singleton pregnancies. FIELD STRENGTH/SEQUENCE 1.5T, modified two-point Dixon and CSE-MRI. ASSESSMENT Manual segmentation of total fetal fat volume and mean FF from modified 2-point Dixon and CSE-MRI FF images. STATISTICAL TESTS Reliability was assessed by calculating the intraclass correlation coefficient (ICC). Agreement was assessed using a one-sample t-test on the fat measurements difference values (modified two-point Dixon - CSE-MRI). The difference scores were tested against a value of 0, which would indicate that the measurements were identical. RESULTS The fat volume and FF measured by modified two-point Dixon and CSE-MRI had excellent reliability, demonstrated by ICCs of 0.93 (P < 0.001) and 0.90 (P < 0.001), respectively. They were not in agreement, with CSE-MRI giving mean fat volumes 180 mL greater and mean FF 3.0% smaller than modified two-point Dixon. DATA CONCLUSION The reliability between modified two-point Dixon and CSE-MRI indicates that either technique can be used to compare fetal fat measurements in different participants, but they are not in agreement possibly due to uncorrected biases in modified two-point Dixon. LEVEL OF EVIDENCE 4 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018.

Rationale and Objectives Thoracic x-ray computed tomography (CT) and hyperpolarized 3He magnetic resonance imaging (MRI) provide quantitative measurements of airspace enlargement in patients with emphysema. For patients with panlobular emphysema due to alpha-1 antitrypsin deficiency (AATD), sensitive biomarkers of disease progression and response to therapy have been difficult to develop and exploit, especially those biomarkers that correlate with outcomes like quality of life. Here, our objective was to generate and compare CT and diffusion-weighted inhaled-gas MRI measurements of emphysema including apparent diffusion coefficient (ADC) and MRI-derived mean linear intercept (Lm) in patients with AATD, chronic obstructive pulmonary disease (COPD) ex-smokers, and elderly never-smokers. Materials and Methods We enrolled patients with AATD (n = 8; 57 ± 7 years), ex-smokers with COPD (n = 8; 77 ± 6 years), and a control group of never-smokers (n = 5; 64 ± 2 years) who underwent thoracic CT, MRI, spirometry, plethysmography, the St. George's Respiratory Questionnaire, and the 6-minute walk test during a single 2-hour visit. MRI-derived ADC, Lm, surface-to-volume ratio, and ventilation defect percent were generated for the apical, basal, and whole lung as was CT lung area ≤−950 Hounsfield units (RA950), low attenuating clusters, and airway count. Results In patients with AATD, there was a significantly different MRI-derived ADC (P = .03), Lm (P .05) compared to COPD ex-smokers with a significantly different St. George's Respiratory Questionnaire. Conclusions In this proof-of-concept demonstration, we evaluated CT and MRI lung emphysema measurements and observed significantly worse MRI biomarkers of emphysema in patients with AATD compared to patients with COPD, although CT RA950 and diffusing capacity of carbon monoxide were not significantly different, underscoring the sensitivity of MRI measurements of AATD emphysema.

PURPOSE Recent pulmonary imaging research has revealed that in patients with chronic obstructive pulmonary disease (COPD) and asthma, structural and functional abnormalities are spatially heterogeneous. This novel information may help optimize treatment in individual patients, monitor interventional efficacy, and develop new treatments. Moreover, by automating the measurement of regional biomarkers for the 19 different anatomical lung segments, there is an opportunity to embed imaging biomarkers into clinically acceptable clinical workflows and improve lung disease clinical care. Therefore, to exploit the regional structure-function information provided by thoracic imaging, and as a first step toward this goal, our objective was to develop a fully automated registration pipeline for thoracic x-ray computed tomography (CT) and inhaled gas functional magnetic resonance imaging (MRI) whole lung and segmental structure-function biomarkers. METHODS Thirty-five patients including 15 severe, poorly controlled asthmatics and 20 COPD patients [classified according to the global initiative for chronic obstructive lung disease (GOLD) criteria)] provided written informed consent to a study protocol approved by Health Canada and underwent pulmonary function tests, MRI, and CT during a single 2-hour visit. Using this diverse patient dataset, we developed and evaluated a joint deformable registration approach to simultaneously coregister CT with both 1 H and 3 He MRI by enforcing the similarity of the deformation fields from the two individual registrations. We derived a simpler model that was equivalent to the original challenging optimization problem through variational analysis and the simpler model gave rise to an efficient numerical solver that was parallelized on a graphics processing unit. The coregistered CT-3 He MRI and whole lung/segmental lung masks were used to generate whole lung and segmental 3 He MRI ventilation defect percent (VDP). To estimate fiducial localization reproducibility, a single observer manually identified 109 pairs of CT and 3 He MRI fiducials for 35 patient images on five separate occasions and determined the fiducial localization error (FLE). CT-3 He MRI registration accuracy was evaluated using the target registration error (TRE). Whole lung VDP generated using the algorithm was compared with VDP generated using a previously validated semiautomated approach and computational efficiency was evaluated using run time. RESULTS In 35 patients including 15 with severe asthma and 20 with COPD, mean forced expiratory volume in 1 s (FEV1 ) was 63±24%pred and FEV1 /forced vital capacity (FVC) was 54 ± 17%. FLE was 0.16 mm and 0.34 mm for 3 He MRI and CT, respectively. TRE was 4.5 ± 2.0 mm, 4.0 ± 1.7 mm, 4.8 ± 2.3 mm for asthma, COPD GOLD II, and GOLD III groups, respectively, with a mean of 4.4 ± 2.0 mm for the entire dataset. TRE was significantly improved for joint CT-1 H/3 He MRI registration compared with CT-1 H MRI rigid registration (P

Recent years have seen various reviews on the lack of access to radiotherapy often based on geographic regions of the world such as Africa, Asia Pacific, Europe, Latin America and North America. Countries are often defined by their national income per capita levels based on World Bank definitions of high income, upper middle income, lower middle income and low income. Within the world regions, there are significant variations in gross national income (GNI) per capita among the different countries, and even within similar income levels, large variations exist. This report presents the actual status of radiotherapy and analyses the current needs and costs to provide full access in the different regions of the world. Actual coverage of the needs ranges from 34% in Africa to over 92% in Europe to about double the needs in North America. In line with this, proportional additional investments and operational costs are as high as more than 200% in Africa to almost none in North America. Two world regions face substantial challenges: Africa, based on the important demands to build new capacity and subsequently to maintain operational capability; and Asia Pacific, due to its high population density, translating into large absolute needs in radiotherapy treatments and resources, and hence in associated costs. With the data highlighting a large variability of GNI/capita even within similar income levels in the various world regions, it is expected that additional investment in resources and costs may be more dependent on income level of the country than on the GNI group or the geographic region of the world.

Rationale: In patients with asthma, x-ray computed tomography (CT) has provided evidence of thickened airway walls and airway occlusions, but the total number of CT-visible airways and its relationship with disease severity is unknown. Objectives: To measure CT total-airway-count (TAC) in asthma and evaluate relationships with asthma severity, airway morphology, pulmonary function and magnetic-resonance-imaging (MRI) ventilation. Methods: Participants underwent post-bronchodilator inspiratory CT, and pre- and post-bronchodilator spirometry and hyperpolarized 3He MRI. CT TAC was quantified as the sum of airways in the segmented airway-tree, and airway wall-area-percent (WA%) and lumen-area (LA) were measured. MRI ventilation abnormalities were quantified as the ventilation-defect-percent (VDP). Measurements and Main Results: We evaluated 70 participants including 15 Global-Initiative-for-Asthma (GINA) steps 1-3, 19 GINA4 and 36 GINA5 asthmatics. As compared with GINA1-3, TAC was significantly diminished in GINA4 (p=0.03) and GINA5 (p=0.045). Terminal airway intraluminal occlusion was present in five (two GINA4, three GINA5) of 70 participants. Sub-subsegmental airways were CT-invisible or missing in 69/70 participants; the most common number of missing sub-subsegments was 10. Participants with ≥10 missing subsegments had worse WA% (p Conclusions: TAC was significantly diminished in participants with greater asthma severity and was related to airway wall thickness and ventilation-defects. Fewer airways in severe as compared with mild asthma challenges our understanding of airways-disease in asthma.

© 2020 SPIE. Cardiac surgeons rely on diagnostic imaging for preoperative planning. Recently, developments have been made on improving 3D ultrasound (US) spatial compounding tailored for cardiac images. Compounded 3D ultrasound volumes are able to capture complex anatomical structures at a level similar to a CT scan, however these images are difficult to display and visualize due to an increased amount of surrounding tissue captured including excess noise at the volume boundaries. Traditional medical image visualization software does not easily allow for viewing 2D slices at arbitrary angles, and 3D rendering techniques do not adequately capture depth information without the use of advanced transfer functions or other depth-encoding techniques that must be tuned to each individual data set. Previous studies have shown that the effective use of virtual reality (VR) can improve image visualization, usability and reduce surgical errors in case planning. We demonstrate the novel use of a VR system for the application of measuring chordal lengths from compounded transesophageal and transgastric echocardiography (TEE, TTE) ultrasound images. Compounded images are constructed from TEE (en-face) views registered and spatially compounded with multiple TEE transgastric views in order to capture both the mitral valve leaflets and chordae tendineae with high levels of detail. Users performed the task of taking linear measurements of chordae visible in these images using both traditional software and a VR platform. Compared to traditional software, the VR platform offered a more intuitive experience with respect to orientation, however users felt there was a lack of precision when performing the measurement tasks.

Acetylcholine (ACh) has been suggested to facilitate plasticity and improve functional recovery after different types of brain lesions. Interestingly, numerous studies have shown that striatal cholinergic interneurons are relatively resistant to acute ischemic insults, but whether ACh released by these neurons enhances functional recovery after stroke is unknown. We investigated the role of endogenous striatal ACh in stroke lesion volume and functional outcomes following middle cerebral artery occlusion to induce focal ischemia in striatum-selective vesicular acetylcholine transporter-deficient mice (stVAChT-KO). As transporter expression is almost completely eliminated in the striatum of stVAChT-KO mice, ACh release is nearly abolished in this area. Conversely, in other brain areas, VAChT expression and ACh release are preserved. Our results demonstrate a larger infarct size after ischemic insult in stVAChT-KO mice, with more pronounced functional impairments and increased mortality than in littermate controls. These changes are associated with increased activation of GSK-3, decreased levels of β-catenin, and a higher permeability of the blood–brain barrier in mice with loss of VAChT in striatum neurons. These results support a framework in which endogenous ACh secretion originating from cholinergic interneurons in the striatum helps to protect brain tissue against ischemia-induced damage and facilitates brain recovery by supporting blood–brain barrier function.

© 2020 SPIE. Physical replicas of patient specific heart valve pathologies may improve clinicians' ability to plan the optimal treatment for patients with complex valvular heart disease. Our previous work has demonstrated the ability to replicate patient pathology of the adult mitral valve (MV) in a dynamic environment [13]. Infant congenital heart defects present possibly the most challenging form of valvular disease, given the range of pathologies, the relative size of these valves compared to adult anatomy, and the rarity of congenital heart disease. Patient specific valve models could be particularly valuable for pediatric cardiologists and surgeons, as a means to both plan for and practice interventions. Our current goal is to assess our ability to apply our workflow to the more challenging case of the tricuspid valve (TV) presented in cases of hypoplastic left heart syndrome (HLHS). We explore the feasibility of adapting our previous workflow for creating dynamic silicone MV models for pre-surgical planning and simulation training, to developing 3D echocardiogram derived, patient specific TV models for use in a physical heart simulator. These models are intended for characterization of the TV, and exploration of the relationship between specific anatomical features and tricuspid regurgitation (TR) severity. The simulations may be relevant to pre-surgical planning of repair of the particularly complex and unique anatomical pathologies presented in children with HLHS.

© 2019 Elsevier B.V. Motor imagery (MI) is a commonly used cognitive task in brain–computer interface (BCI) applications because it produces reliable activity in motor-planning regions. However, a number of functional near-infrared spectroscopy (fNIRS) studies have reported the unexpected finding of inverse oxygenation: increased deoxyhemoglobin and decreased oxyhemoglobin during task periods. This finding questions the reliability of fNIRS for BCI applications given that MI activation should result in a focal increase in blood oxygenation. In an attempt to elucidate this phenomenon, fMRI and fNIRS data were acquired on 15 healthy participants performing a MI task. The fMRI data provided global coverage of brain activity, thus allowing visualization of all potential brain regions activated and deactivated during task periods. Indeed, fMRI results from seven subjects included activation in the primary motor cortex and/or the pre-supplementary motor area during the rest periods in addition to the expected activation in the supplementary motor and premotor areas. Of these seven subjects, two showed inverse oxygenation with fNIRS. The proximity of the regions showing inverse oxygenation to the motor planning regions suggests that inverse activation detected by fNIRS may likely be a consequence of partial volume errors due to the sensitivity of the optodes to both primary motor and motor planning regions.

© 2019 Haddad et al. The processing of brain diffusion tensor imaging (DTI) data for large cohort studies requires fully automatic pipelines to perform quality control (QC) and artifact/outlier removal procedures on the raw DTI data prior to calculation of diffusion parameters. In this study, three automatic DTI processing pipelines, each complying with the general ENIGMA framework, were designed by uniquely combining multiple image processing software tools. Different QC procedures based on the RESTORE algorithm, the DTIPrep protocol, and a combination of both methods were compared using simulated ground truth and artifact containing DTI datasets modeling eddy current induced distortions, various levels of motion artifacts, and thermal noise. Variability was also examined in 20 DTI datasets acquired in subjects with vascular cognitive impairment (VCI) from the multi-site Ontario Neurodegenerative Disease Research Initiative (ONDRI). The mean fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were calculated in global brain grey matter (GM) and white matter (WM) regions. For the simulated DTI datasets, the measure used to evaluate the performance of the pipelines was the normalized difference between the mean DTI metrics measured in GM and WM regions and the corresponding ground truth DTI value. The performance of the proposed pipelines was very similar, particularly in FA measurements. However, the pipeline based on the RESTORE algorithm was the most accurate when analyzing the artifact containing DTI datasets. The pipeline that combined the DTIPrep protocol and the RESTORE algorithm produced the lowest standard deviation in FA measurements in normal appearing WM across subjects. We concluded that this pipeline was the most robust and is preferred for automated analysis of multisite brain DTI data.

PURPOSE Multi-b diffusion-weighted hyperpolarized inhaled-gas MRI provides imaging biomarkers of terminal airspace enlargement including ADC and mean linear intercept (Lm ), but clinical translation has been limited because image acquisition requires relatively long or multiple breath-holds that are not well-tolerated by patients. Therefore, we aimed to accelerate single breath-hold 3D multi-b diffusion-weighted 129 Xe MRI, using k-space undersampling in imaging direction using a different undersampling pattern for different b-values combined with the stretched exponential model to generate maps of ventilation, apparent transverse relaxation time constant ( T2∗ ), ADC, and Lm values in a single, short breath-hold; accelerated and non-accelerated measurements were directly compared. METHODS We evaluated multi-b (0, 12, 20, 30, and 45.5 s/cm2 ) diffusion-weighted 129 Xe T2∗ /ADC/morphometry estimates using acceleration factor (AF = 1 and 7) and multi-breath sampling in 3 volunteers (HV), and 6 participants with alpha-1 antitrypsin deficiency (AATD). RESULTS For the HV subgroup, mean differences of 5%, 2%, and 8% were observed between fully sampled and undersampled k-space for ADC, Lm , and T2∗ values, respectively. For the AATD subgroup, mean differences were 9%, 6%, and 12% between fully sampled and undersampled k-space for ADC, Lm and T2∗ values, respectively. Although mean differences of 1% and 4.5% were observed between accelerated and multi-breath sampled ADC and Lm values, respectively, mean ADC/Lm estimates were not significantly different from corresponding mean ADCM /LmM or mean ADCA /LmA estimates (all P > 0.60 , A = undersampled and M = multi-breath sampled). CONCLUSIONS Accelerated multi-b diffusion-weighted 129 Xe MRI is feasible at AF = 7 for generating pulmonary ADC and Lm in AATD and normal lung.

ObjectiveTo characterize the time course of ventricular volume expansion in genetic frontotemporal dementia (FTD) and identify the onset time and rates of ventricular expansion in presymptomatic FTD mutation carriers.MethodsParticipants included patients with a mutation in MAPT, PGRN, or C9orf72, or first-degree relatives of mutation carriers from the GENFI study with MRI scans at study baseline and at 1 year follow-up. Ventricular volumes were obtained from MRI scans using FreeSurfer, with manual editing of segmentation and comparison to fully automated segmentation to establish reliability. Linear mixed models were used to identify differences in ventricular volume and in expansion rates as a function of time to expected disease onset between presymptomatic carriers and noncarriers.ResultsA total of 123 participants met the inclusion criteria and were included in the analysis (18 symptomatic carriers, 46 presymptomatic mutation carriers, and 56 noncarriers). Ventricular volume differences were observed 4 years prior to symptom disease onset for presymptomatic carriers compared to noncarriers. Annualized rates of ventricular volume expansion were greater in presymptomatic carriers relative to noncarriers. Importantly, time-intensive manually edited and fully automated ventricular volume resulted in similar findings.ConclusionsVentricular volume differences are detectable in presymptomatic genetic FTD. Concordance of results from time-intensive manual editing and fully automatic segmentation approaches support its value as a measure of disease onset and progression in future studies in both presymptomatic and symptomatic genetic FTD.

Background Fixed airflow limitation and ventilation heterogeneity are common in chronic obstructive pulmonary disease (COPD). Conventional noncontrast CT provides airway and parenchymal measurements but cannot be used to directly determine lung function. Purpose To develop, train, and test a CT texture analysis and machine-learning algorithm to predict lung ventilation heterogeneity in participants with COPD. Materials and Methods In this prospective study (ClinicalTrials.gov: NCT02723474; conducted from January 2010 to February 2017), participants were randomized to optimization (n = 1), training (n = 67), and testing (n = 27) data sets. Hyperpolarized (HP) helium 3 (3He) MRI ventilation maps were co-registered with thoracic CT to provide ground truth labels, and 87 quantitative imaging features were extracted and normalized to lung averages to generate 174 features. The volume-of-interest dimension and the training data sampling method were optimized to maximize the area under the receiver operating characteristic curve (AUC). Forward feature selection was performed to reduce the number of features; logistic regression, linear support vector machine, and quadratic support vector machine classifiers were trained through fivefold cross validation. The highest-performing classification model was applied to the test data set. Pearson coefficients were used to determine the relationships between the model, MRI, and pulmonary function measurements. Results The quadratic support vector machine performed best in training and was applied to the test data set. Model-predicted ventilation maps had an accuracy of 88% (95% confidence interval [CI]: 88%, 88%) and an AUC of 0.82 (95% CI: 0.82, 0.83) when the HP 3He MRI ventilation maps were used as the reference standard. Model-predicted ventilation defect percentage (VDP) was correlated with VDP at HP 3He MRI (r = 0.90, P < .001). Both model-predicted and HP 3He MRI VDP were correlated with forced expiratory volume in 1 second (FEV1) (model: r = -0.65, P < .001; MRI: r = -0.70, P < .001), ratio of FEV1 to forced vital capacity (model: r = -0.73, P < .001; MRI: r = -0.75, P < .001), diffusing capacity (model: r = -0.69, P < .001; MRI: r = -0.65, P < .001), and quality-of-life score (model: r = 0.59, P = .001; MRI: r = 0.65, P < .001). Conclusion Model-predicted ventilation maps generated by using CT textures and machine learning were correlated with MRI ventilation maps (r = 0.90, P < .001). © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Fain in this issue.

When the earth transitioned to an oxygen-containing atmosphere, many bacterial species were killed by the free radicals that developed in their cytoplasm. New life forms took advantage of this change by evolving to use oxygen as the final resting place for electrons involved in the Krebs cycle. Animals today rely on getting oxygen into the blood stream and getting carbon dioxide out by ventilation through sequentially smaller and smaller tubes until diffusion takes over, finally reaching the terminal respiratory bronchiole and its associated alveoli for gas exchange. All animals are obligate aerobes. One group has estimated that there are 274 to 790 million alveoli in the healthy adult lung. In this issue of Radiology, Kim et al describe a visualization method to study the invisible small airways (seven to 30th generation) that move air from the trachea to the peripheral airways and back again for normal ventilation.

Aims Cardiovascular risk factors are used for risk stratification in primary prevention. We sought to determine if simple cardiac risk scores are associated with magnetic resonance imaging (MRI)-detected subclinical cerebrovascular disease including carotid wall volume (CWV), carotid intraplaque haemorrhage (IPH), and silent brain infarction (SBI). Methods and results A total of 7594 adults with no history of cardiovascular disease (CVD) underwent risk factor assessment and a non-contrast enhanced MRI of the carotid arteries and brain using a standardized protocol in a population-based cohort recruited between 2014 and 2018. The non-lab-based INTERHEART risk score (IHRS) was calculated in all participants; the Framingham Risk Score was calculated in a subset who provided blood samples (n = 3889). The association between these risk scores and MRI measures of CWV, carotid IPH, and SBI was determined. The mean age of the cohort was 58 (8.9) years, 55% were women. Each 5-point increase (∼1 SD) in the IHRS was associated with a 9 mm3 increase in CWV, adjusted for sex (P < 0.0001), a 23% increase in IPH [95% confidence interval (CI) 9–38%], and a 32% (95% CI 20–45%) increase in SBI. These associations were consistent for lacunar and non-lacunar brain infarction. The Framingham Risk Score was also significantly associated with CWV, IPH, and SBI. CWV was additive and independent to the risk scores in its association with IPH and SBI. Conclusion Simple cardiovascular risk scores are significantly associated with the presence of MRI-detected subclinical cerebrovascular disease, including CWV, IPH, and SBI in an adult population without known clinical CVD.

Background: Longitudinal progression to irreversible airflow limitation occurs in approximately 10% of patients with asthma, but it is difficult to identify patients who are at risk for this transition. Purpose: To investigate 6-year longitudinal changes in hyperpolarized helium 3 (3He) MRI ventilation defects in study participants with mild-to-moderate asthma and identify predictors of longitudinal changes in postbronchodilator forced expiratory volume in 1 second (FEV1) reversibility Materials and Methods: Spirometry and hyperpolarized 3He MRI were evaluated in participants with mild-to-moderate asthma in two prospectively planned visits approximately 6 years apart. Participants underwent methacholine challenge at baseline (January 2010 to April 2011) and pre- and postbronchodilator evaluations at follow-up (November 2016 to June 2017). FEV1 and MRI ventilation defects, quantified as ventilation defect volume (VDV), were compared between visits by using paired t tests. Participants were dichotomized by postbronchodilator change in FEV1 at follow-up, and differences between reversible and not-reversible groups were determined by using unpaired t tests. Multivariable models were generated to explain postbronchodilator FEV1 reversibility at follow-up. Results: Eleven participants with asthma (mean age, 42 years ± 9 [standard deviation]; seven men) were evaluated at baseline and after mean 78 months ± 7. Medications, exacerbations, FEV1 (76% predicted vs 76% predicted; P = .91), and VDV (240 mL vs 250 mL; P = .92) were not different between visits. In eight of 11 participants (73%), MRI ventilation defects at baseline were at the same location in the lung at follow-up MRI. In the remaining three participants (27%), MRI ventilation defects worsened at the same lung locations as depicted at baseline methacholine-induced ventilation. At follow-up, postbronchodilator FEV1 was not reversible in six of 11 participants; the concentration of methacholine to decrease FEV1 by 20% (PC20) was greater in FEV1-irreversible participants at follow-up (P = .01). In a multivariable model, baseline MRI VDV helped to predict postbronchodilator reversibility at follow-up (R 2 = 0.80; P < .01), but PC20, age, and FEV1 did not (R 2 = 0.63; P = .15). Conclusion: MRI-derived, spatially persistent ventilation defects predict postbronchodilator reversibility 78 months ± 7 later for participants with mild-to-moderate asthma in whom there were no changes in lung function, medication, or exacerbations.

Background Mild Cognitive Impairment (MCI) is an intermediate state between normal cognition and dementia that is associated with twice the risk of falls. It is unknown whether white matter integrity (WMI) is associated with increased risk of falls in MCI. The purpose of this study was to evaluate if early changes in WMI were associated with gait impairment and falls. Methods Forty-three participants with MCI from the Gait and Brain Study underwent standardized assessment of cognition, gait performance under single and dual-task conditions (walking while talking), and WMI using 3 Tesla diffusion tensor imaging (DTI). Macro-structural imaging characteristics (white and grey matter morphology) as well as microstructural WMI parameters were examined for associations with falls and gait performance. Significantly associated WM tracts were then used to test the interplay between WMI and history of falls, after adjusting for other important covariates. Results Multiple WM tracts (corpus callosum, forceps minor, and the left inferior fronto-occipital fasciculus) were significantly associated with history of falls and lower dual-task gait performance. A multivariable regression model showed that fall history was associated with the radial diffusivity in the forceps minor, even after adjusting for education, sex, BMI, MMSE scores, comorbidities, gait velocity and WMH volume as covariates. Conclusions Multiple WM tracts that are known to be involved in executive and visuospatial functions were preferentially affected in MCI individuals with history of falls. Our preliminary findings support the notion that WMI in key brain regions may increase risk of falls in older adults with MCI., Highlights • 43 older adults with MCI were assessed for falls, gait, and WMI using 3 T DTI. • Multiple WM tracts were associated with falls and lower dual-task gait performance. • Tracts affected are known to be involved in executive and visuospatial functions.

Ageing is associated with a decline in motor function that critically interferes with activities of daily living involving manual dexterity. Transcranial direct current stimulation (tDCS) is a form of non-invasive brain stimulation that has been shown to enhance manual dexterity in healthy aging adults. The supplementary motor area (SMA) is involved in motor preparation and bimanual control; therefore, bihemispheric tDCS incorporating the SMA may preferentially enhance bimanual motor movements in healthy older adults. The aim of the current study was to determine if tDCS incorporating SMA could improve manual dexterity in older adults. Twenty-four adults, aged 67–84 participated in this double-blind, randomized, cross over design, pilot study. One group of participants (n = 17) were randomized to receive stimulation or sham on their first visit and received the contrary on their second visit, seven days later. A second group of participants (n = 10) received three consecutive days of tDCS while performing a motor task. Participants performed unimanual and bimanual hand movements while receiving 2 mA of tDCS. The total time for participants to complete three trials of each task was recorded. No significant differences in performance times were observed between single or tri session tDCS and sham conditions. However, tDCS had opposing effects on the motor consolidation of anti-phase and in-phase bimanual tasks. During the tri session paradigm, older adults improved performance learning of antiphase bimanual movements more quickly than inphase bimanual movements, suggesting a different mechanism of action of these two movements.

Current lung radiation therapy (RT) treatment planning algorithms used in most centers assume homogeneous lung function. However, co-existing pulmonary dysfunctions present in many non-small cell lung cancer (NSCLC) patients, particularly smokers, cause regional variations in both perfusion and ventilation, leading to inhomogeneous lung function. An adaptive RT treatment planning that deliberately avoids highly functional lung regions can potentially reduce pulmonary toxicity and morbidity. The ventilation component of lung function can be measured using a variety of techniques. Recently, 4DCT ventilation imaging has emerged as a cost-effective and accessible method. Current 4DCT ventilation calculation methods, including the intensity-based and Jacobian models, suffer from inaccurate estimations of air volume distribution and unreliability of intensity-based image registration algorithms. In this study, we propose a novel method that utilizes a biomechanical model-based registration along with an accurate air segmentation algorithm to calculate 4DCT ventilation maps. The results show a successful development of ventilation maps using the proposed method.

Radiation therapy (RT) is an important component of treatment for lung cancer. However, the accuracy of this method can be affected by the complex respiratory motion/deformation of the target tumor during treatment. To improve the accuracy of RT, patient-specific biomechanical models of the lung have been proposed for estimating the tumor’s respiratory motion/deformation. Chronic obstructive pulmonary disease (COPD) has a high incidence among lung cancer patients and is associated with heterogeneous destruction of lung parenchyma. This key heterogeneity element, however, has not been incorporated in lung biomechanical models developed in previous studies. In this work, we have developed a physiologically and patho-physiologically realistic lung biomechanical model that accounts for lung tissue heterogeneity. Four-dimensional computed tomography (4DCT) images were used to build a patient-specific finite element (FE) model of the lung. Image information was used to identify and incorporate inhomogeneities within the model. Mechanical properties of normal and diseased regions in the lung and the transpulmonary pressure driving the respiratory motion were estimated using an optimization algorithm that maximizes the similarity between the actual and simulated tumor and lung image data. Results from this proof of concept study on a lung cancer patient indicated improved accuracy of tumor motion estimation when COPD-induced lung tissue heterogeneities were incorporated in the model.

© 2019 Elsevier Inc. Background: In patients with neurological disorders, a divergence can exist between patients' perceptions regarding the outcomes and the objective neurological findings. Degenerative cervical myelopathy (DCM), a prevalent condition characterized by progressive compression of the cervical spinal cord, can produce debilitating symptoms and profound neurological findings. The purpose of the present study was to determine whether the physician-derived neurological examination findings, as recorded by American Spine Injury Association (ASIA) summary score, correlated with the patient-derived outcome measures for DCM. Methods: A total of 78 patients underwent surgical management of DCM with completion of preoperative and 6-month follow-up assessments. Surgical management consisted of either anterior or posterior cervical decompression. All patients underwent a neurological evaluation, including an ASIA assessment before surgery and 6 months after surgery, and completed the modified Japanese Orthopaedic Association (mJOA), neck disability index (NDI), and Short-Form 36-item (SF-36) scales pre- and postoperatively to measure both disease-specific and general perceived outcomes. Results: The objective physician-derived neurological testing (ASIA) did not correlate with the patient-derived scales (mJOA, NDI, and SF-36) pre- or postoperatively. Patients reported significant improvements (P < 0.001) at 6 months postoperatively in extremity functioning (mJOA), neck pain (NDI), overall physical health (SF-36), and objective strength and sensory functioning (ASIA). All patient-perceived outcome measures correlated with each other pre- and postoperatively (P < 0.01). Conclusions: Objective scoring of postoperative neurological function did not correlate with patient-perceived outcomes before and after surgery for DCM. Traditional testing of motor and sensory function as part of the neurological assessment may not be sensitive enough to assess the scope of neurological changes experienced by patients with DCM.

© 2019 Wiley Periodicals, Inc. Introduction: Catheter-tissue contact force is a determinant of radiofrequency (RF) ablation lesion effectiveness. However, ablation on a beating heart is subject to force variability, making it difficult to optimally deliver consistently durable and transmural lesions. This work evaluates improvements in contact force stability and lesion reproducibility by using a catheter contact-force controller (CFC) during lesion delivery in vitro and in vivo. Methods and Results: Using a sheath and force-sensing catheter, an experienced operator attempted to maintain a constant force of 20 g at targets within the atria and left ventricle of a pig manually and using the CFC; the average force and contact-force variation (CFV) achieved using each approach were compared. Ablation lesions (20 W, 30 seconds, 17 mL/min irrigation) were created in bovine tissue samples mounted on a platform programmed to reproduce clinically relevant motion. CFC-assisted lesions were delivered to stationary and moving tissue with forces of 5 to 35 g. Mimicking manual intervention, lesions were also delivered to moving tissue while the CFC was disabled. Resultant lesion volumes were compared using two-way analysis of variance. When using the CFC, the average force was within 1 g of the set level, with a CFV less than 5 g, during both in vitro and in vivo experiments. Reproducible and statistically identical (P =.82) lesion volumes proportional to the set force were achieved in both stationary and moving tissue when the CFC was used. Conclusions: CFC assistance maintains constant force in vivo and removes effect of motion on lesion volume during RF lesion delivery.

© 2019 The Author(s). Background: Currently there are no disease-modifying treatments for Parkinson's disease dementia (PDD), a condition linked to aggregation of the protein α-synuclein in subcortical and cortical brain areas. One of the leading genetic risk factors for Parkinson's disease is being a carrier in the gene for β-Glucocerebrosidase (GCase; gene name GBA1). Studies in cell culture and animal models have shown that raising the levels of GCase can decrease levels of α-synuclein. Ambroxol is a pharmacological chaperone for GCase and is able to raise the levels of GCase and could therefore be a disease-modifying treatment for PDD. The aims of this trial are to determine if Ambroxol is safe and well-tolerated by individuals with PDD and if Ambroxol affects cognitive, biochemical, and neuroimaging measures. Methods: This is a phase II, single-centre, double-blind, randomized placebo-controlled trial involving 75 individuals with mild to moderate PDD. Participants will be randomized into Ambroxol high-dose (1050 mg/day), low-dose (525 mg/day), or placebo treatment arms. Assessments will be undertaken at baseline, 6-months, and 12-months follow up times. Primary outcome measures will be the Alzheimer's disease Assessment Scale-cognitive subscale (ADAS-Cog) and the ADCS Clinician's Global Impression of Change (CGIC). Secondary measures will include the Parkinson's disease Cognitive Rating Scale, Clinical Dementia Rating, Trail Making Test, Stroop Test, Unified Parkinson's disease Rating Scale, Purdue Pegboard, Timed Up and Go, and gait kinematics. Markers of neurodegeneration will include MRI and CSF measures. Pharmacokinetics and pharmacodynamics of Ambroxol will be examined through plasma levels during dose titration phase and evaluation of GCase activity in lymphocytes. Discussion: If found effective and safe, Ambroxol will be one of the first disease-modifying treatments for PDD. Trial registration: ClinicalTrials.gov NCT02914366, 26 Sep 2016/retrospectively registered.

© 2019 Applications of ultrasound guidance for epidural injections are hindered by poor needle and epidural space visualization. This work presents an augmented reality (AR) ultrasound guidance system that addresses challenges in both needle visualization during navigation and epidural space identification for needle positioning. In this system, (i) B-mode ultrasound and the needle are visualized in a 3-D AR environment for improved navigation, and (ii) A-mode ultrasound, obtained from a custom-made single-element transducer housed at the needle tip, is used to identify the epidural space for improved needle positioning. Performance of the system was evaluated against ultrasound-only guidance in a phantom study with novice operators and an expert anesthesiologist. The procedure success rate was higher with the AR system (100%) than ultrasound-only guidance (57%). The AR system has the potential to improve procedure outcomes in terms of success rate, time, needle path-length and usability.

Introduction Neurodegeneration is a biproduct of aging that results in concomitant cognitive decline. Physical exercise is an emerging intervention to improve brain health. The underlying neural mechanisms linking exercise to neurodegeneration, however, are unclear. Functional brain network connectivity (FBNC) refers to neural regions that are anatomically separate but temporally synched in functional signalling. FBNC can be measured using functional Magnetic Resonance Imaging (fMRI) and is affected by neurodegeneration. Methods We conducted a systematic review using PubMed and EMBASE to assess the effect of physical exercise on FBNC in older adults with and without cognitive impairment. Results Our search yielded 1474 articles; after exclusion, 13 were included in the final review, 8 of which focused on cognitively healthy older adults. 10 studies demonstrated an increase in FBNC post-exercise intervention, while 11 studies showed improvements in secondary outcomes (cognitive and/or physical performance). One study showed significant correlations between FBNC and cognitive performance measures that significantly improved post-intervention. Discussion We found evidence that physical exercise increases FBNC. When assessing the association between FBNC with physical and cognitive functioning, careful consideration must be given to variability in exercise parameters, neural regions of interest and networks examined, and heterogeneity in methodological approaches.