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Sex differences, tumor vascularity, and blood flow seen on multiecho dynamic contrast–based MRI scans enabled prediction of treatment response and overall survival in patients with rectal cancer. Background: MRI is the standard tool for rectal cancer staging. However, more precise diagnostic tests that can assess biologic tumor features decisive for treatment outcome are necessary. Tumor perfusion and hypoxia are two important features; however, no reference methods that measure these exist in clinical use. Purpose: To assess the potential predictive and prognostic value of MRI-assessed rectal cancer perfusion, as a surrogate measure of hypoxia, for local treatment response and survival. Materials and Methods: In this prospective observational cohort study, 94 study participants were enrolled from October 2013 to December 2017 (ClinicalTrials.gov: NCT01816607). Participants had histologically confirmed rectal cancer and underwent routine diagnostic MRI, an extended diffusion-weighted sequence, and a multiecho dynamic contrast agent–based sequence. Predictive and prognostic values of dynamic contrast-enhanced, dynamic susceptibility contrast (DSC), and intravoxel incoherent motion MRI were investigated with response to neoadjuvant treatment, progression-free survival, and overall survival as end points. Secondary objectives investigated potential sex differences in MRI parameters and relationship with lymph node stage. Statistical methods used were Cox regression, Student t test, and Mann-Whitney U test.Results: A total of 94 study participants (mean age, 64 years ± 11 [standard deviation]; 61 men) were evaluated. Baseline tumor blood flow from DSC MRI was lower in patients who had poor local tumor response to neoadjuvant treatment (96 mL/min/100 g ± 33 for ypT2–4, 120 mL/min/100 g ± 21 for ypT0–1; P = .01), shorter progression-free survival (hazard ratio = 0.97; 95% confidence interval: 0.96, 0.98; P < .001), and shorter overall survival (hazard ratio = 0.98; 95% confidence interval: 0.98, 0.99; P < .001). Women had higher blood flow (125 mL/min/100 g ± 27) than men (74 mL/min/100 g ± 26, P < .001) at stage 4. Volume transfer constant and plasma volume from dynamic contrast-enhanced MRI as well as ΔR2* peak and area under the curve for 30 and 60 seconds from DSC MRI were associated with local malignant lymph nodes (pN status). Median area under the curve for 30 seconds was 0.09 arbitrary units (au) ± 0.03 for pN1–2 and 0.19 au ± 0.12 for pN0 (P = .001). Conclusion:Low tumor blood flow from dynamic susceptibility contrast MRI was associated with poor treatment response in study participants with rectal cancer.

BACKGROUND AND PURPOSE: Although methylphenidate is frequently used to treat children with attention-deficit/hyperactivity disorder, it is currently unknown how methylphenidate affects brain development. In a randomized controlled trial, we investigated whether the cortical effects of methylphenidate are modulated by age. MATERIALS AND METHODS: Between June 1, 2011, and June 15, 2015, we conducted a randomized, double-blind, placebo-controlled trial (Effects of Psychotropic Drugs on Developing Brain-Methylphenidate) in 99 males with attention-deficit/hyperactivity disorder (according to Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, criteria) from referral centers in the greater Amsterdam area in the Netherlands. The trial was registered on March 24, 2011 (identifier NL34509.000.10) and subsequently at the Netherlands National Trial Register (identifier NTR3103). Participants (first enrolled October 13, 2011) were 10–12 years or 23–40 years of age and randomized to treatment with either methylphenidate or a placebo for 16 weeks. Our main outcome was a change in cortical thickness in predefined ROIs as measured by MR imaging pre- and posttreatment. RESULTS: We observed a time × medication × age interaction (F[1,88.825] = 4.316, P

Cortical microstructure is influenced by circadian rhythm and sleep deprivation, yet the precise underpinnings of these effects remain unclear. The ratio between T1-weighted and T2-weighted magnetic resonance images (T1w/T2w ratio) has been linked to myelin levels and dendrite density and may offer novel insight into the intracortical microstructure of the sleep deprived brain. Here, we examined intracortical T1w/T2w ratio in 41 healthy young adults (26 women) before and after 32 h of either sleep deprivation (n = 18) or a normal sleep-wake cycle (n = 23). Linear models revealed significant group differences in T1w/T2w ratio change after 32 h in four clusters, including bilateral effects in the insular, cingulate, and superior temporal cortices, comprising regions involved in attentional, auditory and pain processing. Across clusters, the sleep deprived group showed an increased T1w/T2w ratio, while the normal sleep-wake group exhibited a reduced ratio. These changes were not explained by in-scanner head movement, and 95% of the effects across clusters remained significant after adjusting for cortical thickness and hydration. Compared with a normal sleep-wake cycle, 32 h of sleep deprivation yields intracortical T1w/T2w ratio increases. While the intracortical changes detected by this study could reflect alterations in myelin or dendritic density, or both, histological analyses are needed to clarify the precise underlying cortical processes.

To test if adding permeability measurement to perfusion obtained from dynamic susceptibility contrast MRI (DSC-MRI) improves diagnostic performance in the differentiation of primary central nervous system lymphoma (PCNSL) from glioblastoma. DSC-MRI was acquired in 145 patients with pathologically proven glioblastoma (n = 89) or PCNSL (n = 56). The permeability metrics of contrast agent extraction fraction (Ex), apparent permeability (Ka), and leakage-corrected perfusion of normalized cerebral blood volume (nCBVres) and cerebral blood flow (nCBFres) were derived from a tissue residue function. For comparison purposes, the leakage-corrected normalized CBV (nCBV) and relative permeability constant (K2) were also obtained using the established Weisskoff-Boxerman leakage correction method. The area under the receiver operating characteristics curve (AUC) and cross-validation were used to compare the diagnostic performance of the single DSC-MRI parameters with the performance obtained with the addition of permeability metrics. PCNSL demonstrated significantly higher permeability (Ex, p

Elucidating the neurobiological effects of sleep and wake is an important goal of the neurosciences. Whether and how human cerebral blood flow (CBF) changes during the sleep-wake cycle remain to be clarified. Based on the synaptic homeostasis hypothesis of sleep and wake, we hypothesized that a day of wake and a night of sleep deprivation would be associated with gray matter resting CBF (rCBF) increases and that sleep would be associated with rCBF decreases. Thirty-eight healthy adult males (age 22.1 ± 2.5 years) underwent arterial spin labeling perfusion magnetic resonance imaging at three time points: in the morning after a regular night's sleep, the evening of the same day, and the next morning, either after total sleep deprivation (n = 19) or a night of sleep (n = 19). All analyses were adjusted for hematocrit and head motion. rCBF increased from morning to evening and decreased after a night of sleep. These effects were most prominent in bilateral hippocampus, amygdala, thalamus, and in the occipital and sensorimotor cortices. Group × time interaction analyses for evening versus next morning revealed significant interaction in bilateral lateral and medial occipital cortices and in bilateral insula, driven by rCBF increases in the sleep deprived individuals and decreases in the sleepers, respectively. Furthermore, group × time interaction analyses for first morning versus next morning showed significant effects in medial and lateral occipital cortices, in anterior cingulate gyrus, and in the insula, in both hemispheres. These effects were mainly driven by CBF increases from TP1 to TP3 in the sleep deprived individuals. There were no associations between the rCBF changes and sleep characteristics, vigilant attention, or subjective sleepiness that remained significant after adjustments for multiple analyses. Altogether, these results encourage future studies to clarify mechanisms underlying sleep-related rCBF changes.

To investigate the effects of a range of parameter settings on T1 measurement stability in the portal vein using the T1-mapping sequences Look-Locker (LL) and Modified Look-Locker inversion recovery (MOLLI). Ten different versions of LL and MOLLI sequences were tested and compared to a reference sequence provided by the MR manufacturer. Ten healthy volunteers were imaged multiple times on two separate scan days at 3T. The mean T1 values and coefficient of variation (CoV) were calculated for each of the ten sequences and compared to the reference sequence. Six of the tested sequences had T1 values close to the reference sequence; among those, three sequences achieved lower CoV than the reference sequence. Lowest CoV was achieved using a non-triggered LL sequence with 5 beat readout and a 45o flip angle (mean T1 1733 ms ± 89 ms, CoV 1.3% ± 0.58%). T1-measurements in the hepatic portal vein can be performed with high precision using either MOLLI or LL sequences provided that LL sampling duration is sufficiently long and flip angle sufficiently high. The advantage of constant timing outweighed the advantage of ECG-triggering.

Sleep deprivation influences several critical functions, yet how it affects human brain white matter (WM) is not well understood. The aim of the present work was to investigate the effect of 32 hours of sleep deprivation on WM microstructure compared to changes observed in a normal sleep-wake cycle (SWC). To this end, we utilised diffusion weighted imaging (DWI) including the diffusion tensor model, diffusion kurtosis imaging and the spherical mean technique, a novel biophysical diffusion model. 46 healthy adults (23 sleep deprived vs 23 with normal SWC) underwent DWI across four time points (morning, evening, next day morning and next day afternoon, after a total of 32 hours). Linear mixed models revealed significant group × time interaction effects, indicating that sleep deprivation and normal SWC differentially affect WM microstructure. Voxel-wise comparisons showed that these effects spanned large, bilateral WM regions. These findings provide important insight into how sleep deprivation affects the human brain.

Accurate and reliable whole-brain segmentation is critical to longitudinal neuroimaging studies. We undertake a comparative analysis of two subcortical segmentation methods, Automatic Segmentation (ASEG) and Sequence Adaptive Multimodal Segmentation (SAMSEG), recently provided in the open-source neuroimaging package FreeSurfer 7.1, with regard to reliability, bias, sensitivity to detect longitudinal change, and diagnostic sensitivity to Alzheimer’s disease. First, we assess intra- and inter-scanner reliability for eight bilateral subcortical structures: amygdala, caudate, hippocampus, lateral ventricles, nucleus accumbens, pallidum, putamen and thalamus. For intra-scanner analysis we use a large sample of participants (n = 1629) distributed across the lifespan (age range = 4–93 years) and acquired on a 1.5T Siemens Avanto (n = 774) and a 3T Siemens Skyra (n = 855) scanners. For inter-scanner analysis we use a sample of 24 participants scanned on the day with three models of Siemens scanners: 1.5T Avanto, 3T Skyra and 3T Prisma. Second, we test how each method detects volumetric age change using longitudinal follow up scans (n = 491 for Avanto and n = 245 for Skyra; interscan interval = 1–10 years). Finally, we test sensitivity to clinically relevant change. We compare annual rate of hippocampal atrophy in cognitively normal older adults (n = 20), patients with mild cognitive impairment (n = 20) and Alzheimer’s disease (n = 20). We find that both ASEG and SAMSEG are reliable and lead to the detection of within-person longitudinal change, although with notable differences between age-trajectories for most structures, including hippocampus and amygdala. In summary, SAMSEG yields significantly lower differences between repeated measures for intra- and inter-scanner analysis without compromising sensitivity to changes and demonstrating ability to detect clinically relevant longitudinal changes.

Background The aim of this study was to investigate changes in structural magnetic resonance imaging (MRI) according to the RANO criteria and perfusion- and permeability related metrics derived from dynamic contrast-enhanced MRI (DCE) and dynamic susceptibility contrast MRI (DSC) during radiochemotherapy for prediction of progression and survival in glioblastoma. Methods Twenty-three glioblastoma patients underwent biweekly structural and perfusion MRI before, during, and two weeks after a six weeks course of radiochemotherapy. Temporal trends of tumor volume and the perfusion-derived parameters cerebral blood volume (CBV) and blood flow (CBF) from DSC and DCE, in addition to contrast agent capillary transfer constant (Ktrans) from DCE, were assessed. The patients were separated in two groups by median survival and differences between the two groups explored. Clinical- and MRI metrics were investigated using univariate and multivariate survival analysis and a predictive survival index was generated. Results Median survival was 19.2 months. A significant decrease in contrast-enhancing tumor size and CBV and CBF in both DCE- and DSC-derived parameters was seen during and two weeks past radiochemotherapy (p < 0.05). A 10%/30% increase in Ktrans/CBF two weeks after finishing radiochemotherapy resulted in significant shorter survival (13.9/16.8 vs. 31.5/33.1 months; p < 0.05). Multivariate analysis revealed an index using change in Ktrans and relative CBV from DSC significantly corresponding with survival time in months (r2 = 0.843; p < 0.001). Conclusions Significant temporal changes are evident during radiochemotherapy in tumor size (after two weeks) and perfusion-weighted MRI-derived parameters (after four weeks) in glioblastoma patients. While DCE-based metrics showed most promise for early survival prediction, a multiparametric combination of both DCE- and DSC-derived metrics gave additional information.

Dynamic susceptibility contrast (DSC) imaging is a widely used technique for assessment of cerebral blood volume (CBV). With combined gradient-echo and spin-echo DSC techniques, measures of the underlying vessel size and vessel architecture can be obtained from the vessel size index (VSI) and vortex area, respectively. However, how noise, and specifically the contrast-to-noise ratio (CNR), affect the estimations of these parameters has largely been overlooked. In order to address this issue, we have performed simulations to generate DSC signals with varying levels of CNR, defined by the peak of relaxation rate curve divided by the standard deviation of the baseline. Moreover, DSC data from 59 brain cancer patients were acquired at two different 3 T-scanners (N = 29 and N = 30, respectively), where CNR and relative parameter maps were obtained. Our simulations showed that the measured parameters were affected by CNR in different ways, where low CNR led to overestimations of CBV and underestimations of VSI and vortex area. In addition, a higher noise-sensitivity was found in vortex area than in CBV and VSI. Results from clinical data were consistent with simulations, and indicated that CNR < 4 gives highly unreliable measurements. Moreover, we have shown that the distribution of values in the tumour regions could change considerably when voxels with CNR below a given cut off are excluded when generating the relative parameter maps. The widespread use of CBV and attractive potential of VSI and vortex area, makes the noise-sensitivity of these parameters found in our study relevant for further use and development of the DSC imaging technique. Our results suggest that the CNR has considerable impact on the measured parameters, with the potential to affect the clinical interpretation of DSC-MRI, and should therefore be taken into account in the clinical decision-making process.

Recently, several magnetic resonance imaging (MRI) studies have reported time-of-day effects on brain structure and function. Due to the possibility that time-of-day effects reflect mechanisms of circadian regulation, the aim of this prospective study was to assess these effects while under strict experimental control of variables that might influence biological clocks, such as caffeine intake and exposure to blue-emitting light. In addition, the current study assessed whether time-of-day effects were driven by changes to extracellular space, by including estimations of non-Gaussian diffusion metrics obtained from diffusion kurtosis imaging, white matter tract integrity and the spherical mean technique, in addition to conventional diffusion tensor imaging -derived parameters. Participants were 47 healthy adults who underwent diffusion-weighted imaging in the morning and evening of the same day. Morning and evening scans were compared using voxel-wise tract based spatial statistics and permutation testing. A day of wakefulness was associated with widespread increases in fractional anisotropy, indices of kurtosis and indices of the axonal water fraction. In addition, wakefulness was associated with widespread decreases in radial diffusivity, both in the single compartment and in extra-axonal space. These results suggest that an increase in the intra-axonal space relative to the extra-axonal volume underlies time-of-day effects in human white matter, which is in line with activity-induced reductions to the extracellular volume. These findings provide important insight into possible mechanisms driving time-of-day effects in MRI.

Purpose To test for measurable visual enhancement of the dentate nucleus (DN) on unenhanced T1-weighted magnetic resonance (MR) images in a cohort of patients with a primary brain tumor who had not received linear gadolinium-based contrast agents (GBCAs) but had received many injections of macrocyclic GBCAs. Materials and Methods Seventeen patients with high-grade gliomas who had received 10-44 administrations of the macrocyclic GBCA gadobutrol (0.1 mmol/kg of body weight) were retrospectively included in this regional ethics committee-approved study. Two neuroradiologists inspected T1-weighted MR images with optimized window settings to visualize small differences in contrast at the baseline and at the last examination for the presence of visual DN signal enhancement. Signal intensity (SI) in the DN was normalized to the SI of the pons, and a one-sample t test was used to test for differences between baseline normalized SI (nSI) in the DN (nSIDN) and the average change in nSIDN of all postbaseline MR imaging sessions (ΔnSIDNavg) or the change in nSIDN from baseline to the last MR imaging session (ΔnSIDN). Linear and quadratic correlation analyses were used to examine the association between the number of macrocyclic GBCA administrations and ΔnSIDN or ΔnSIDNavg. Results The mean ± standard deviation number of macrocyclic GBCA administrations was 22.2 ± 10.6 administered throughout 706 days ± 454. Visually appreciable signal enhancement was observed in two patients who had received 37 and 44 macrocyclic GBCA injections. Mean ΔnSIDN was greater than zero (0.03 ± 0.05; P = .016), and there was a significant linear association between the number of macrocyclic GBCA injections and ΔnSIDN (r = 0.69, P = .002) and ΔnSIDNavg (r = 0.77, P < .001). Conclusion A small but statistically significant dose-dependent T1-weighted signal enhancement was observed in the DN after multiple macrocyclic GBCA injections. Visually appreciable enhancement in the DN was observed on contrast-optimized images in two patients who had received 37 and 44 standard doses of macrocyclic GBCAs. © RSNA, 2017 Online supplemental material is available for this article.

Sleep is an evolutionarily conserved process required for human health and functioning. Insufficient sleep causes impairments across cognitive domains, and sleep deprivation can have rapid antidepressive effects in mood disorders. However, the neurobiological effects of waking and sleep are not well understood. Recently, animal studies indicated that waking and sleep are associated with substantial cortical structural plasticity. Here, we hypothesized that structural plasticity can be observed after a day of waking and sleep deprivation in the human cerebral cortex. To test this hypothesis, 61 healthy adult males underwent structural magnetic resonance imaging (MRI) at three time points: in the morning after a regular night's sleep, the evening of the same day, and the next morning, either after total sleep deprivation (N=41) or a night of sleep (N=20). We found significantly increased right prefrontal cortical thickness from morning to evening across all participants. In addition, pairwise comparisons in the deprived group between the two morning scans showed significant thinning of mainly bilateral medial parietal cortices after 23h of sleep deprivation, including the precuneus and posterior cingulate cortex. However, there were no significant group (sleep vs. sleep deprived group) by time interactions and we can therefore not rule out that other mechanisms than sleep deprivation per se underlie the bilateral medial parietal cortical thinning observed in the deprived group. Nonetheless, these cortices are thought to subserve wakefulness, are among the brain regions with highest metabolic rate during wake, and are considered some of the most sensitive cortical regions to a variety of insults. Furthermore, greater thinning within the left medial parietal cluster was associated with increased sleepiness after sleep deprivation. Together, these findings add to a growing body of data showing rapid structural plasticity within the human cerebral cortex detectable with MRI. Further studies are needed to clarify whether cortical thinning is one neural substrate of sleepiness after sleep deprivation.

In a blind, dual-center, multi-observer setting, we here identify the pre-treatment radiologic features by Magnetic Resonance Imaging (MRI) associated with subsequent treatment options in patients with glioma. Study included 220 previously untreated adult patients from two institutions (94 + 126 patients) with a histopathologically confirmed diagnosis of glioma after surgery. Using a blind, cross-institutional and randomized setup, four expert neuroradiologists recorded radiologic features, suggested glioma grade and corresponding confidence. The radiologic features were scored using the Visually AcceSAble Rembrandt Images (VASARI) standard. Results were retrospectively compared to patient treatment outcomes. Our findings show that patients receiving a biopsy or a subtotal resection were more likely to have a tumor with pathological MRI-signal (by T2-weighted Fluid-Attenuated Inversion Recovery) crossing the midline (Hazard Ratio; HR = 1.30 [1.21–1.87], P P P = 0.002) and correlated with the use of a more comprehensive adjuvant treatment protocol (Spearman = 0.48, P

Grant Support This project was funded by the Research Council of Norway. Background Oxygen uptake through the gastrointestinal tract after oral administration of oxygenated water in humans is not well studied and is debated in the literature. Due to the paramagnetic properties of oxygen and deoxyhemoglobin, MRI as a technique might be able to detect changes in relaxometry values caused by increased oxygen levels in the blood. Purpose To assess whether oxygen dissolved in water is absorbed from the gastrointestinal tract and transported into the bloodstream after oral administration. Study Type A randomized, double‐blinded, placebo‐controlled crossover trial. Population/Subjects Thirty healthy male volunteers age 20–35. Field Strength/Sequence 3T/Modified Look–Locker inversion recovery (MOLLI) T1‐mapping and multi fast field echo (mFFE) T2*‐mapping. Assessment Each volunteer was scanned in two separate sessions. T1 and T2* maps were acquired repeatedly covering the hepatic portal vein (HPV) and vena cava inferior (VCI, control vein) before and after intake of oxygenated or control water. Assessments were done by placing a region of interest in the HPV and VCI. Statistical Test A mixed linear model was performed to the compare control vs. oxygen group. Results Drinking caused a mean 1.6% 95% CI (1.1–2.0% P

Sleep is a universal phenomenon necessary for maintaining homeostasis and function across a range of organs. Lack of sleep has severe health-related consequences affecting whole-body functioning, yet no other organ is as severely affected as the brain. The neurophysiological mechanisms underlying these deficits are poorly understood. Here, we characterize the dynamic changes in brain connectivity profiles inflicted by sleep deprivation and how they deviate from regular daily variability. To this end, we obtained functional magnetic resonance imaging data from 60 young, adult male participants, scanned in the morning and evening of the same day and again the following morning. 41 participants underwent total sleep deprivation before the third scan, whereas the remainder had another night of regular sleep. Sleep deprivation strongly altered the connectivity of several resting-state networks, including dorsal attention, default mode, and hippocampal networks. Multivariate classification based on connectivity profiles predicted deprivation state with high accuracy, corroborating the robustness of the findings on an individual level. Finally, correlation analysis suggested that morning-to-evening connectivity changes were reverted by sleep (control group) – a pattern which did not occur after deprivation. We conclude that both, a day of waking and a night of sleep deprivation dynamically alter the brain functional connectome.

Seminal human brain histology work has demonstrated developmental waves of myelination. Here, using a micro-structural magnetic resonance imaging (MRI) marker sensitive to myelin, we studied fine-grained age differences to deduce waves of growth, stability, and decline of cortical myelination over the life-cycle. In 484 participants, aged 8-85 years, we fitted smooth growth curves to T1- to T2-weighted ratio in each of 360 regions from one of 7 cytoarchitectonic classes. From the first derivatives of these generally inverted-U trajectories, we defined three milestones: the age at peak growth; the age at onset of a stable plateau; and the age at the onset of decline. Age at peak growth had a bimodal distribution comprising an early (pre-pubertal) wave of primary sensory and motor cortices and a later (post-pubertal) wave of association, insular and limbic cortices. Most regions reached stability in the 30s but there was a second wave reaching stability in the 50s. Age at onset of decline was also bimodal: in some right hemisphere regions, the curve declined from the 60s, but in other left hemisphere regions, there was no significant decline from the stable plateau. Network analysis of the micro-structural connectome revealed that late developing (second wave) regions had significantly higher degree and other measures of centrality. These results are consistent with regionally heterogeneous waves of intracortical myelinogenesis and age-related demyelination, which may be relevant to the onset of neuropsychiatric disorders, and dementia, and the staged acquisition and decline of motor and cognitive skills over the course of the life-cycle.

Background Dynamic contrast‐based MRI and intravoxel incoherent motion imaging (IVIM) MRI are both methods showing promise as diagnostic and prognostic tools in rectal cancer. Both methods aim at measuring perfusion‐related parameters, but the relationship between them is unclear. Purpose To investigate the relationship between perfusion‐ and permeability‐related parameters obtained by IVIM‐MRI, T1‐weighted dynamic contrast‐enhanced (DCE)‐MRI and T2*‐weighted dynamic susceptibility contrast (DSC)‐MRI. Study Type Prospective. Subjects In all, 94 patients with histologically confirmed rectal cancer. Field Strength/Sequence Subjects underwent pretreatment 1.5T clinical procedure MRI, and in addition a study‐specific diffusion‐weighted sequence (b = 0, 25, 50, 100, 500, 1000, 1300 s/mm2) and a multiecho dynamic contrast‐based echo‐planer imaging sequence. Assessment Median tumor values were obtained from IVIM (perfusion fraction [f], pseudodiffusion [D*], diffusion [D]), from the extended Tofts model applied to DCE data (Ktrans, kep, vp, ve) and from model free deconvolution of DSC (blood flow [BF] and area under curve). A subgroup of the excised tumors underwent immunohistochemistry with quantification of microvessel density and vessel size. Statistical Test Spearman's rank correlation test. Results D* was correlated with BF (rs = 0.47, P < 0.001), and f was negatively correlated with kep (rs = –0.31, P = 0.002). BF was correlated with Ktrans (rs = 0.29, P = 0.004), but this correlation varied extensively when separating tumors into groups of low (rs = 0.62, P < 0.001) and high (rs = –0.06, P = 0.68) BF. Ktrans was negatively correlated with vessel size (rs = –0.82, P = 0.004) in the subgroup of tumors with high BF. Data Conclusion We found an association between D* from IVIM and BF estimated from DSC‐MRI. The relationship between IVIM and DCE‐MRI was less clear. Comparing parameters from DSC‐MRI and DCE‐MRI highlights the importance of the underlying biology for the interpretation of these parameters. Level of Evidence: 2 Technical Efficacy: Stage 1 © 2019 The Authors. his is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Context: Insulin resistance and dysglycemia are associated with physical inactivity and adiposity, and may be improved by exercise. Objective: Investigate the effect of exercise on insulin sensitivity, body composition and adipose depots in sedentary men with (n = 11) or without (n = 11) overweight and dysglycemia. Material and methods: Euglycemic-hyperinsulinemic clamp, ankle-to-neck MRI, MRS, muscle and adipose tissue biopsies before and after 12 weeks combined strength and endurance exercise. Results: Insulin sensitivity, VO2max, strength, whole-body and muscle fat content, and abdominal adipose depots were improved without obvious differences between normo- and dysglycemic men. Hepatic fat, waist circumference and subcutaneous adipose tissue were reduced in the dysglycemic group. For both groups plasma adiponectin was reduced, whereas IL-6 was unchanged. Visceral fat was preferentially lost compared with other adipose depots. Discussion and conclusion: Body composition, fat distribution and in...

BACKGROUND AND PURPOSE: A small subset of primary central nervous system lymphomas exhibits high cerebral blood volume, which is indistinguishable from that in glioblastoma on dynamic susceptibility contrast MR imaging. Our study aimed to test whether estimates of combined perfusion and vascular permeability metrics derived from DSC-MR imaging can improve the diagnostic performance in differentiating hypervascular primary central nervous system lymphoma from glioblastoma. MATERIALS AND METHODS: A total of 119 patients (with 30 primary central nervous system lymphomas and 89 glioblastomas) exhibited hypervascular foci using the reference method of leakage-corrected CBV (reference-normalized CBV). An alternative postprocessing method used the tissue residue function to calculate vascular permeability (extraction fraction), leakage-corrected CBV, cerebral blood flow, and mean transit time. Parameters were compared using Mann-Whitney U tests, and the diagnostic performance to distinguish primary central nervous system lymphoma from glioblastoma was calculated using the area under the curve from the receiver operating characteristic curve and was cross-validated with bootstrapping. RESULTS: Hypervascular primary central nervous system lymphoma showed similar leakage-corrected normalized CBV and leakage-corrected CBV compared with glioblastoma (P > .05); however, primary central nervous system lymphoma exhibited a significantly higher extraction fraction (P < .001) and CBF (P = .01) and shorter MTT (P < .001) than glioblastoma. The extraction fraction showed the highest diagnostic performance (the area under the receiver operating characteristic curve [AUC], 0.78; 95% confidence interval, 0.69–0.85) for distinguishing hypervascular primary central nervous system lymphoma from glioblastoma, with a significantly higher performance than both CBV (AUC, 0.53–0.59, largest P = .02) and CBF (AUC, 0.72) and MTT (AUC, 0.71). CONCLUSIONS: Estimation of vascular permeability with DSC-MR imaging further characterizes hypervascular primary central nervous system lymphoma and improves diagnostic performance in glioblastoma differentiation.

Flutemetamol (18F-Flut) is an [18F]-labelled amyloid PET tracer with increasing availability. The main objectives of this study were to investigate 1) cerebrospinal fluid (CSF) Aβ 1-42 (Aβ42) concentrations associated with regional 18F-Flut uptake, 2) associations between cortical 18F-Flut and [18F]-fludeoxyglucose (18F-FDG)-PET, and 3) the potential use of 18F-Flut in WM pathology. Cognitively impaired, nondemented subjects were recruited (n = 44). CSF was drawn, and 18F-Flut-PET, 18F-FDG-PET, and MRI performed. Our main findings were: 1) Different Alzheimer’s disease predilection areas showed increased 18F-Flut retention at different CSF Aβ42 concentrations (posterior regions were involved at higher concentrations). 2) There were strong negative correlations between regional cortical 18F-Flut and 18F-FDG uptake. 3) Increased 18F-Flut uptake were observed in multiple subcortical regions in amyloid positive subjects, including investigated reference regions. However, WM hyperintensity 18F-Flut standardized uptake value ratios (SUVr) were not significantly different, thus we cannot definitely conclude that the higher uptake in 18F-Flut(+) is due to amyloid deposition. In conclusion, our findings support clinical use of CSF Aβ42, putatively relate decreasing CSF Aβ42 concentrations to a sequence of regional amyloid deposition, and associate amyloid pathology to cortical hypometabolism. However, we cannot conclude that 18F-Flut-PET is a suitable marker for WM pathology due to high aberrant WM uptake.

To investigate dynamic susceptibility contrast (DSC) perfusion weighted imaging (PWI) in white matter lesions (WML) in patients with multiple sclerosis (MS), using automatically generated binary masks of brain tissue.WML in MS have in some studies demonstrated perfusion abnormalities compared to normal appearing white matter (NAWM), however perfusion changes in WML in MS have in general not been well documented.DSC PWI was performed at 1.5 Tesla in 69 newly diagnosed MS patients. Parametric perfusion maps representing cerebral blood volume (CBV), cerebral blood flow (CBF) and mean transit time (MTT) were obtained. Binary masks of WML, white matter (WM) and grey matter (GM) were automatically generated and co-registered to the perfusion maps. The WML mask was manually edited and modified to correct for errors in the automatic lesion detection. Perfusion parameters were derived both from WML and NAWM using the manually modified WML mask, and using the original non-modified WML mask (with and without GM exclusion mask). Differences in perfusion measures between WML and NAWM were analyzed.CBF was significantly lower (p0.001) and MTT significantly higher (p0.001) in WML compared to NAWM. CBV did not show significant difference between WML and NAWM. The non-modified WML mask gave similar results as manually modified WML mask if the GM exclusion mask was used in the analysis.DSC PWI revealed lower CBF and higher MTT, consistent with reduced perfusion, in WML compared to NAWM in patients with early MS. Automatically generated binary masks are a promising tool in perfusion analysis of WML.

To investigate putative interacting or distinct pathways for hippocampal complex substructure (HCS) atrophy and cognitive affection in early-stage Alzheimer's disease (AD) and cerebrovascular disease (CVD), we recruited healthy controls, patients with mild cognitive impairment (MCI) and poststroke patients. HCSs were segmented, and quantitative white-matter hyperintensity (WMH) load and cerebrospinal fluid (CSF) amyloid-β concentrations were determined. The WMH load was higher poststroke. All examined HCSs were smaller in amyloid-positive MCI than in controls, and the subicular regions were smaller poststroke. Memory was reduced in amyloid-positive MCI, and psychomotor speed and executive function were reduced in poststroke and amyloid-positive MCI. Size of several HCS correlated with WMH load poststroke and with CSF amyloid-β concentrations in MCI. In poststroke and amyloid-positive MCI, neuropsychological function correlated with WMH load and hippocampal volume. There are similar patterns of HCS atrophy in CVD and early-stage AD, but different HCS associations with WMH and CSF biomarkers. WMHs add to hippocampal atrophy and the archetypal AD deficit delayed recall. In line with mounting evidence of a mechanistic link between primary AD pathology and CVD, these additive effects suggest interacting pathologic processes.

To develop a generic support vector machine (SVM) model by using magnetic resonance (MR) imaging-based blood volume distribution data for preoperative glioma survival associations and to prospectively evaluate the diagnostic effectiveness of this model in autonomous patient data.Institutional and regional medical ethics committees approved the study, and all patients signed a consent form. Two hundred thirty-five preoperative adult patients from two institutions with a subsequent histologically confirmed diagnosis of glioma after surgery were included retrospectively. An SVM learning technique was applied to MR imaging-based whole-tumor relative cerebral blood volume (rCBV) histograms. SVM models with the highest diagnostic accuracy for 6-month and 1-, 2-, and 3-year survival associations were trained on 101 patients from the first institution. With Cox survival analysis, the diagnostic effectiveness of the SVM models was tested on independent data from 134 patients at the second institution.were adjusted for known survival predictors, including patient age, tumor size, neurologic status, and postsurgery treatment, and were compared with survival associations from an expert reader.Compared with total qualitative assessment by an expert reader, the whole-tumor rCBV-based SVM model was the strongest parameter associated with 6-month and 1-, 2-, and 3-year survival in the independent patient data (area under the receiver operating characteristic curve, 0.794-0.851; hazard ratio, 5.4-21.2).Machine learning by means of SVM in combination with whole-tumor rCBV histogram analysis can be used to identify early patient survival in aggressive gliomas. The SVM model returned higher diagnostic accuracy values than an expert reader, and the model appears to be insensitive to patient, observer, and institutional variations.

Brain white matter hyperintensities (WMHs) are linked to increased risk of cerebrovascular and neurodegenerative diseases among the elderly. Consequently, detection and characterization of WMHs are of significant clinical importance. We propose a novel approach for WMH segmentation from multi-contrast MRI where both voxel-based and lesion-based information are used to improve overall performance in both volume-oriented and object-oriented metrics. Our segmentation method (AMOS-2D) consists of four stages following a “generate-and-test” approach: pre-processing, Gaussian white matter (WM) modelling, hierarchical multi-threshold WMH segmentation and object-based WMH filtering using support vector machines. Data from 28 subjects was used in this study covering a wide range of lesion loads. Volumetric T1-weighted images and 2D fluid attenuated inversion recovery (FLAIR) images were used as basis for the WM model and lesion masks defined manually in each subject by experts were used for training and evaluating the proposed method. The method obtained an average agreement (in terms of the Dice similarity coefficient, DSC) with experts equivalent to inter-expert agreement both in terms of WMH number (DSC = 0.637 vs. 0.651) and volume (DSC = 0.743 vs. 0.781). It allowed higher accuracy in detecting WMH compared to alternative methods tested and was further found to be insensitive to WMH lesion burden. Good agreement with expert annotations combined with stable performance largely independent of lesion burden suggests that AMOS-2D will be a valuable tool for fully automated WMH segmentation in patients with cerebrovascular and neurodegenerative pathologies.

Purpose The utility of perfusion weighted imaging in multiple sclerosis (MS) is not well investigated. The purpose of this study was to compare baseline normalized perfusion measures in subgroups of newly diagnosed MS patients. We wanted to test the hypothesis that this method can differentiate between groups defined according to disease severity and disease activity at one year follow-up. Methods Baseline magnetic resonance imaging (MRI) including a dynamic susceptibility contrast perfusion sequence was performed on a 1.5 Tesla scanner in 66 patients newly diagnosed with relapsing-remitting MS. From the baseline MRI, cerebral blood flow (CBF), cerebral blood volume (CBV) and mean transit time (MTT) maps were generated. Normalized (n) perfusion values were calculated by dividing each perfusion parameter obtained in white matter lesions by the same parameter obtained in normal appearing white matter. Neurological examination was performed at baseline and at follow-up approximately one year later to establish the multiple sclerosis severity score (MSSS) and evidence of disease activity (EDA). Results Baseline nMTT was lower in patients with MSSS>3.79 (p=0.016), in patients with EDA (p=0.041) and in patients with both MSSS>3.79 and EDA (p=0.032) at one-year follow-up. Baseline nCBF and nCBV did not differ between these groups. Conclusions Lower baseline nMTT was associated with higher disease severity and with presence of disease activity one year later in newly diagnosed MS patients. Further longitudinal studies are needed to confirm whether baseline normalized perfusion measures can differentiate between disease severity and disease activity subgroups over time. This is a post-peer-review, pre-copyedit version of an article published in Neuroradiology. The final authenticated version is available online at: http://dx.doi.org/10.1007/s00234-017-1849-4

Heart rate variability (HRV) has become an increasingly popular index of cardiac autonomic control in the biobehavioral sciences due to its relationship with mental illness and cognitive traits. However, the intraindividual stability of HRV in response to sleep and diurnal disturbances, which are commonly reported in mental illness, and its relationship with executive function are not well understood. Here, in 40 healthy adult males we calculated high frequency HRV—an index of parasympathetic nervous system (PNS) activity—using pulse oximetry during brain imaging, and assessed attentional and executive function performance in a subsequent behavioral test session at three time points: morning, evening, and the following morning. Twenty participants were randomly selected for total sleep deprivation whereas the other 20 participants slept as normal. Sleep deprivation and morning-to-night variation did not influence high frequency HRV at either a group or individual level; however, sleep deprivation abolished the relationship between orienting attention performance and HRV. We conclude that a day of wake and a night of laboratory-induced sleep deprivation do not alter supine high frequency HRV in young healthy male adults.

Objective To test the hypothesis that depressive symptoms correlate with Alzheimer's disease (AD) type changes in CSF and structural and functional imaging including hippocampus volume, cortical thickness, white matter lesions, Diffusion tensor imaging (DTI), and fluoro-deoxy-glucose positron emission tomography (FDG-PET) in patient with subjective (SCI) and mild (MCI) cognitive impairment. Method In 60 patients, depressive symptoms were assessed using the Geriatric Depression Scale. The subjects underwent MRI, 18F-FDG PET imaging, and lumbar CSF extraction. Results Subjects with depressive symptoms (n = 24) did not have more pathological AD biomarkers than non-depressed. Uncorrected there were trends towards larger hippocampal volumes (P = 0.06), less orbital WM damage measured by DTI (P = 0.10), and higher orbital glucose metabolism (P = 0.02) in the depressed group. The findings were similar when SCI and MCI were analyzed separately. Similarly, in patients with pathological CSF biomarkers (i.e., predementia AD, n = 24), we found that correlations between scores on GDS and CSF As42 and P-tau indicated less severe AD-specific CSF changes with increasing depression. Conclusion Depressive symptoms are common in SCI/MCI, but are not associated with pathological imaging or CSF biomarkers of AD. Depression can explain cognitive impairment in SCI/MCI or add to cognitive impairment leading to an earlier clinical investigation in predementia AD.

Background Volumetric magnetic resonance imaging (MRI) is now widely available and routinely used in the evaluation of high-grade gliomas (HGGs). Ideally, volumetric measurements should be included in this evaluation. However, manual tumor segmentation is time-consuming and suffers from inter-observer variability. Thus, tools for semi-automatic tumor segmentation are needed. Purpose To present a semi-automatic method (SAM) for segmentation of HGGs and to compare this method with manual segmentation performed by experts. The inter-observer variability among experts manually segmenting HGGs using volumetric MRIs was also examined. Material and Methods Twenty patients with HGGs were included. All patients underwent surgical resection prior to inclusion. Each patient underwent several MRI examinations during and after adjuvant chemoradiation therapy. Three experts performed manual segmentation. The results of tumor segmentation by the experts and by the SAM were compared using Dice coefficients and kappa statistics. Results A relatively close agreement was seen among two of the experts and the SAM, while the third expert disagreed considerably with the other experts and the SAM. An important reason for this disagreement was a different interpretation of contrast enhancement as either surgically-induced or glioma-induced. The time required for manual tumor segmentation was an average of 16 min per scan. Editing of the tumor masks produced by the SAM required an average of less than 2 min per sample. Conclusion Manual segmentation of HGG is very time-consuming and using the SAM could increase the efficiency of this process. However, the accuracy of the SAM ultimately depends on the expert doing the editing. Our study confirmed a considerable inter-observer variability among experts defining tumor volume from volumetric MRIs.

Background: Cortical atrophy is common in early relapsing–remitting multiple sclerosis (RRMS). Whether this atrophy is caused by changes in cortical thickness or cortical surface area is not known, nor is their separate contributions to clinical symptoms. Objectives: To investigate the difference in cortical surface area, thickness and volume between early RRMS patients and healthy controls; and the relationship between these measures and neurological disability, cognitive decline, fatigue and depression. Methods: RRMS patients ( n = 61) underwent magnetic resonance imaging (MRI), neurological and neuropsychological examinations. We estimated cortical surface area, thickness and volume and compared them with matched healthy controls ( n = 61). We estimated the correlations between clinical symptoms and cortical measures within the patient group. Results: We found no differences in cortical surface area, but widespread differences in cortical thickness and volume between the groups. Neurological disability was related to regionally smaller cortical thickness and volume. Better verbal memory was related to regionally larger surface area; and better visuo-spatial memory, to regionally larger cortical volume. Higher depression scores and fatigue were associated with regionally smaller cortical surface area and volume. Conclusions: We found that cortical thickness, but not cortical surface area, is affected in early RRMS. We identified specific structural correlates to the main clinical symptoms in early RRMS.

OBJECTIVES Identification of eloquent brain areas in patients with intra-axial lesions is important to minimize the risk of neurological deficit. We performed a multicenter study comparing conventional 2-dimensional magnetic resonance imaging (MRI) for identification of the central sulcus to topographical MRI and blood-oxygenation-level-dependent functional MRI (BOLD-fMRI). METHODS Seventy-seven unoperated patients with brain lesions were imaged at 1.5 or 3 T. The central sulcus was identified by an experienced neuroradiologist on 2-dimensional MRI, by topographic analysis of 3-dimensional MRI in BrainVoyager, and by BOLD-fMRI analysis in BrainVoyager or SPM5. RESULTS The central sulcus in the affected hemisphere was readily identified in a significantly higher percentage of patients by 2-dimensional MRI and topographical analysis (77/77 patients) compared to BOLD-fMRI (57 patients; P < 0.001). The topographical analysis identified a significantly larger portion of the total central sulcus than 2-dimensional MRI (P < 0.05). No differences were found between institutions, histological versus radiological diagnoses, MRI sequence parameters, age, or sex. CONCLUSIONS Identification of the central sulcus is best performed using topographical analysis; however, 2-dimensional analysis may suffice for daily routine work.

To meet the need for Parkinson's disease biomarkers and evidence for amount and distribution of pathological changes, MRI diffusion tensor imaging (DTI) has been explored in a number of previous studies. However, conflicting results warrant further investigations. As tissue microstructure, particularly of the grey matter, is heterogeneous, a more precise diffusion model may benefit tissue characterization. The purpose of this study was to analyze the diffusion-based imaging technique restriction spectrum imaging (RSI) and DTI, and their ability to detect microstructural changes within brain regions associated with motor function in Parkinson's disease. Diffusion weighted (DW) MR images of a total of 100 individuals, (46 Parkinson's disease patients and 54 healthy controls) were collected using b-values of 0-4000s/mm2. Output diffusion-based maps were estimated based on the RSI-model combining the full set of DW-images (Cellular Index (CI), Neurite Density (ND)) and DTI-model combining b = 0 and b = 1000 s/mm2 (fractional anisotropy (FA), Axial-, Mean- and Radial diffusivity (AD, MD, RD)). All parametric maps were analyzed in a voxel-wise group analysis, with focus on typical brain regions associated with Parkinson's disease pathology. CI, ND and DTI diffusivity metrics (AD, MD, RD) demonstrated the ability to differentiate between groups, with strongest performance within the thalamus, prone to pathology in Parkinson's disease. Our results indicate that RSI may improve the predictive power of diffusion-based MRI, and provide additional information when combined with the standard diffusivity measurements. In the absence of major atrophy, diffusion techniques may reveal microstructural pathology. Our results suggest that protocols for MRI diffusion imaging may be adapted to more sensitive detection of pathology at different sites of the central nervous system.

Neuropathological correlates of Alzheimer's disease (AD) emerge years before dementia. Biomarkers preceding cognitive decline and reflecting the causative processes can potentially aid early intervention and diagnosis. Diffusion tensor imaging (DTI) indirectly reflects tissue microstructure. To answer whether DTI is an early biomarker for AD and to explore the relationship between DTI and the established biomarkers of medial temporal lobe atrophy and cerebrospinal fluid (CSF) Aβ(42), T-tau, and P-tau, we longitudinally studied normal controls and patients with subjective (SCI) or mild (MCI) cognitive impairment. 21 controls and 64 SCI or MCI cases recruited from a university-hospital based memory clinic were re-examined after two to three years. FreeSurfer was used for longitudinal processing of morphometric data, and DTI derived fractional anisotropy, radial diffusivity, and mean diffusivity were analyzed in Tract-Based Spatial Statistics. Using regression models, we explored and compared the predictive powers of DTI and CSF biomarkers in regard to cognitive change and atrophy of the medial temporal lobe. Both DTI and CSF biomarkers significantly predicted cognitive decline and atrophy in the medial temporal lobe. In this population, however, DTI was a better predictor of dementia and AD-specific medial temporal lobe atrophy than the CSF biomarkers. The case for DTI as an early biomarker for AD is strengthened, but further studies are needed to confirm these results.

Purpose: To evaluate the relationship between (a) pathologic levels of cerebrospinal fluid (CSF) total tau as an index of the in tensity of ongoing neuronal degeneration and (b) longitudinal changes in white matter (WM) integrity in patients with mild cognitive impairment (MCI). Materials and Methods: Participants gave written informed consent, and the Norwegian committee for medical research ethics approved the study. Thirty patients with MCI and nonpathologic CSF total tau levels, nine patients with MCI and pathologic CSF total tau levels, and 16 age-matched healthy control subjects underwent diffusion-tensor imaging at baseline and after a mean follow-up of 2.6 years 6 0.54 (standard deviation), with range of 1.58–3.98 years. The effect of diagnosis (MCI vs no MCI) at baseline and CSF tau levels at fractional anisotropy (FA), mean diffusivity, radial diffusivity (D R ), and axial diffusivity were tested with tract-based spatial statistics. Differences in WM integrity at baseline and follow-up and change over time were compared among patients with pathologic CSF total tau levels (MCI high tau), patients with normal CSF total tau levels (MCI low tau), and healthy control subjects. Linear mixed-model between-group within-subject analyses were conducted to examine differences in rate of change over time in FA and D R . Results: Longitudinal analysis of regional WM change revealed significant decrease in FA ( P = .038) and increase in D R (P = .018) in the MCI high-tau group relative to control subjects. For D R , the changes were regionally specific to the right cingulum and the right superior and inferior longitudinal fasciculi. Conclusion: Reduction in WM integrity was greater in patients with MCI who had the most intense neuronal degeneration as indexed by using CSF total tau, suggesting that these patients might represent a subgroup of MCI with more intense WM degeneration who are possibly at greater risk of developing Alzheimer disease. q

To implement a dynamic contrast-based multi-echo MRI sequence in assessment of rectal cancer and evaluate associations between histopathologic data and the acquired dynamic contrast-enhanced (DCE) and dynamic susceptibility contrast (DSC) -MRI parameters.This pilot study reports results from 17 patients with resectable rectal cancer. Dynamic contrast-based multi-echo MRI (1.5T) was acquired using a three-dimensional multi-shot EPI sequence, yielding both DCE- and DSC-data following a single injection of contrast agent. The Institutional Review Board approved the study and all patients provided written informed consent. Quantitative analysis was performed by pharmacokinetic modeling on DCE data and tracer kinetic modeling on DSC data. Mann-Whitney U-test and receiver operating characteristics curve statistics was used to evaluate associations between histopathologic data and the acquired DCE- and DSC-MRI parameters.For patients with histologically confirmed nodal metastasis, the primary tumor demonstrated a significantly lower KThis study shows the feasibility of acquiring DCE- and DSC-MRI in rectal cancer by dynamic multi-echo MRI. A significant association was found between both K4 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:194-206.

Neurodevelopmental origins of functional variation in older age are increasingly being acknowledged, but identification of how early factors impact human brain and cognition throughout life has remained challenging. Much focus has been on age-specific mechanisms affecting neural foundations of cognition and their change. In contrast to this approach, we tested whether cerebral correlates of general cognitive ability (GCA) in development could be extended to the rest of the lifespan, and whether early factors traceable to prenatal stages, such as birth weight and parental education, may exert continuous influences. We measured the area of the cerebral cortex in a longitudinal sample of 974 individuals aged 4–88 y (1,633 observations). An extensive cortical region was identified wherein area related positively to GCA in development. By tracking area of the cortical region identified in the child sample throughout the lifespan, we showed that the cortical change trajectories of higher and lower GCA groups were parallel through life, suggesting continued influences of early life factors. Birth weight and parental education obtained from the Norwegian Mother–Child Cohort study were identified as such early factors of possible life-long influence. Support for a genetic component was obtained in a separate twin sample (Vietnam Era Twin Study of Aging), but birth weight in the child sample had an effect on cortical area also when controlling for possible genetic differences in terms of parental height. Our results provide novel evidence for stability in brain–cognition relationships throughout life, and indicate that early life factors impact brain and cognition for the entire life course. Non-commercial

Purpose: To investigate the effect of variations in temporal resolution and total measurement times on the estimations of kinetic parameters derived from dynamic contrast-enhanced (DCE) MRI in patients with high-grade gliomas (HGGs). Materials and Methods: DCE-MRI with high temporal resolution (dynamic sampling time (Ts) = 2.1 s and 3.4 s) and total sampling time (Tacq) of 5.2 min was acquired in 101 examinations from 15 patients. Using the modified Tofts model Ktrans, kep ve and vp were estimated. The effects of increasing Ts and reducing Tacq on the estimated kinetic parameters were estimated through down-sampling and data truncation, and the results were compared with numerical simulations. Results: There was an overall dependence of all four kinetic parameters on Ts and Tacq. Increasing Ts resulted in under-estimation of Ktrans and over-estimation of Vp, whereas kep and Ve varied in a less predictable manner. Reducing Tacq resulted in over-estimation of Ktrans and kep and under-estimation of vp and ve. Increasing Ts and reducing Tacq resulted in increased relative error for all four parameters. Conclusion: Estimated Ktrans, Kep, and Ve in HGGs were within 15% of the high sampling rate reference values for Ts

Purpose The purpose was to systematically evaluate the effect of diffusion gradient encoding scheme on estimated fractional anisotropy (FA), mean diffusivity (MD) and the voxel-wise probability of identifying crossing fibers in the brain. Materials and Methods Eight healthy volunteers (mean age 26.5±1.3 years, 5 males, 3 females) were imaged using a Spin-Echo Echo-Planar-Imaging sequence acquired with two signal averages [number of signals averaged (NSA)], 127 diffusion directions, and b -values of 750 s/mm 2 and 1500 s/mm 2 . The number of diffusion gradient directions ( N d ) was reduced from the original value whilst maintaining a homogeneous gradient distribution enabling direct comparison of subsampled data sets with N d =15, 28, 43, 84, 112 and 127. FA and MD maps were generated and analyzed using tract-based spatial statistics. Effect of N d on estimated FA and MD was tested with voxel-wise statistics in 13 regions of interest. The number of voxels supporting two fiber populations (NV 2 ) at different N d values was estimated using Bayesian estimation of diffusion parameters. Results Low FA values decreased significantly with increasing N d and with increasing NSA. MD was only marginally sensitive to N d and NSA. NV 2 increased significantly with N d but not with NSA. Thus, we conclude that accurate estimation of standard diffusion metrics FA and MD is mainly dependent on the signal-to-noise ratio (SNR), whereas the ability to differentiate multiple fiber populations requires a high diffusion sampling density.

Background A systematic comparison of magnetic resonance imaging (MRI) options for glioma diagnosis is lacking. Purpose To investigate multiple MR-derived image features with respect to diagnostic accuracy in tumor grading and survival prediction in glioma patients. Material and Methods T1 pre- and post-contrast, T2 and dynamic susceptibility contrast scans of 74 glioma patients with histologically confirmed grade were acquired. For each patient, a set of statistical features was obtained from the parametric maps derived from the original images, in a region-of-interest encompassing the tumor volume. A forward stepwise selection procedure was used to find the best combinations of features for grade prediction with a cross-validated logistic model and survival time prediction with a cox proportional-hazards regression. Results Presence/absence of enhancement paired with kurtosis of the FM (first moment of the first-pass curve) was the feature combination that best predicted tumor grade (grade II vs. grade III-IV; median AUC = 0.96), with the main contribution being due to the first of the features. A lower predictive value (median AUC = 0.82) was obtained when grade IV tumors were excluded. Presence/absence of enhancement alone was the best predictor for survival time, and the regression was significant ( P < 0.0001). Conclusion Presence/absence of enhancement, reflecting transendothelial leakage, was the feature with highest predictive value for grade and survival time in glioma patients.

Diffusion tensor imaging (DTI) and CSF biomarkers are useful diagnostic tools to differentiate patients with mild cognitive impairment (MCI) from normal controls, and may help predict conversion to dementia. Total Tau protein (T-tau) and DTI parameters are both markers for axonal damage, thus it is of interest to determine if DTI parameters are associated with elevated CSF T-tau levels in patients with cognitive impairment. For this purpose, patients with subjective cognitive impairment (SCI) and MCI were recruited from a university based memory clinic. Regions of interest were used to determine fractional anisotropy (FA), radial diffusivity (DR) and axial diffusivity (DA) in known white matter tracts in patients with MCI (n=39) and SCI (n=8) and 26 cognitively healthy controls. Significant lower FA and higher DR values were observed in patients with pathological vs. patients with normal CSF T-tau levels and vs. controls in left posterior cingulum fibers. T-tau values were negatively correlated with FA and positively correlated with DR values in the posterior cingulum fibers. Cingulum fiber diffusivity was related to T-tau pathology in SCI/MCI patients and altered DR may suggest that loss of myelin contributes to early white matter changes in patients at risk of developing Alzheimer's disease (AD).

Cortical thickness decreases from childhood throughout life, as estimated by magnetic resonance imaging (MRI). This monotone trajectory does not reflect the fundamentally different neurobiological processes underlying morphometric changes in development versus aging. We hypothesized that intracortical gray matter (GM) and subjacent white matter (WM) T1-weighted signal intensity would distinguish developmental and age-related changes in the cortex better than thickness. Intracortical GM and subjacent WM signal intensity and cortical thickness was measured across the brain surface in a healthy life span sample (n=429, 8-85 years). We also computed the relaxation rate of T2* (R2*) from multiecho sequences and mapped intracortical GM and subjacent WM values to the surface to delineate age-related variability in R2* and to adjust the T1 signal intensity for possible confounds of accumulated iron. While monotone age-related reductions in thickness were found, both intracortical GM and subcortical WM signal intensity showed inverted U patterns with peaks from eight to approximately 30 years of age. The spatial pattern of intracortical neurodevelopment followed a posterior-anterior gradient, with earliest maturation of occipital visual cortices and most protracted in superior frontal regions. From 50s and 60s, substantial signal reductions were observed in several regions, including the insula, cingulate, and inferior temporal gyrus. R2* showed similar patterns but peaked much later than the T1-weighted signal intensity measures. The results are presented as animations yielding detailed depictions of the dynamic regional variability in cortical neurodevelopment and aging and demonstrate that cortical thickness and T1-weighted signal intensity are sensitive to different cortical maturational and aging-related processes.

Working memory capacity is pivotal for a broad specter of cognitive tasks and develops throughout childhood. This must in part rely on development of neural connections and white matter microstructure maturation, but there is scarce knowledge of specific relations between this and different aspects of working memory. Diffusion tensor imaging (DTI) enables us to study development of brain white matter microstructure. In a longitudinal DTI study of 148 healthy children between 4 and 11 years scanned twice with an on average 1.6 years interval, we characterized change in fractional anisotropy (FA), mean (MD), radial (RD) and axial diffusivity (AD) in 10 major white matter tracts hypothesized to be of importance for working memory. The results showed relationships between change in several tracts and change in visuospatial working memory. Specifically, improvement in visuospatial working memory capacity was significantly associated with decreased MD, RD and AD in inferior longitudinal fasciculus (ILF), inferior fronto-occipital fasciculus (IFOF) and uncinate fasciculus (UF) in the right hemisphere, as well as forceps major (FMaj). No significant relationships were found between change in DTI metrics and change in verbal working memory capacity. These findings yield new knowledge about brain development and corresponding working memory improvements in childhood.

BACKGROUND AND PURPOSE: Prenatal drug exposure may influence the developing brain. Our aim was to study WM characteristics with DTI in children with prenatal opiate and polysubstance exposure and in controls. We assessed whether group differences in FA, DA, and DR could be found and related to cognitive function. MATERIALS AND METHODS: The study was approved by a committee for medical research ethics. Parents signed an informed consent; children gave spoken consent. Our sample included 14 prenatally substance-exposed adopted children (5 girls; age range, 8.6–13.9 years; mean, 11.3 ± 1.7 years) and 14 control children (7 girls; age range, 9.0–10.2 years; mean, 9.8 ± 0.3 years). Tract-based spatial statistics were used to define a common WM skeleton for the sample, and FA was compared between groups throughout the skeleton, controlling for age and sex. Clusters of significant group differences ≥100 voxels ( P

Dynamic susceptibility contrast (DSC)-based perfusion analysis from MR images has become an established method for analysis of cerebral blood volume (CBV) in glioma patients. To date, little emphasis has, however, been placed on quantitative perfusion analysis of these patients, mainly due to the associated increased technical complexity and lack of sufficient stability in a clinical setting. The aim of our study was to develop a fully automated analysis framework for quantitative DSC-based perfusion analysis. The method presented here generates quantitative hemodynamic maps without user interaction, combined with automatic segmentation of normal-appearing cerebral tissue. Validation of 101 patients with confirmed glioma after surgery gave mean values for CBF, CBV, and MTT, extracted automatically from normal-appearing whole-brain white and gray matter, in good agreement with literature values. The measured age- and gender-related variations in the same parameters were also in agreement with those in the literature. Several established analysis methods were compared and the resulting perfusion metrics depended significantly on method and parameter choice. In conclusion, we present an accurate, fast, and automatic quantitative perfusion analysis method where all analysis steps are based on raw DSC data only.

Magnetic resonance imaging volumetry studies report inverted U-patterns with increasing white-matter (WM) volume into middle age suggesting protracted WM maturation compared with the cortical gray matter. Diffusion tensor imaging (DTI) is sensitive to degree and direction of water permeability in biological tissues, providing in vivo indices of WM microstructure. The aim of this cross-sectional study was to delineate age trajectories of WM volume and DTI indices in 430 healthy subjects ranging 8-85 years of age. We used automated regional brain volume segmentation and tract-based statistics of fractional anisotropy, mean, and radial diffusivity as markers of WM integrity. Nonparametric regressions were used to fit the age trajectories and to estimate the timing of maximum development and deterioration in aging. Although the volumetric data supported protracted growth into the sixth decade, DTI indices plateaued early in the fourth decade across all tested regions and then declined slowly into late adulthood followed by an accelerating decrease in senescence. Tractwise and voxel-based analyses yielded regional differences in development and aging but did not provide ample evidence in support of a simple last-in-first-out hypothesis of life-span changes.

To characterize gliomas from dynamic susceptibility contrast (DSC)–based cerebral blood volume (CBV) maps, a CBV value from a normal-appearing region of interest is typically identified manually and used to normalize the CBV maps. This method is user-dependent and time-consuming. We propose an alternative approach based on automatic identification of normal-appearing first-pass curves from brain tissue. Our results in 101 patients suggest similar or better diagnostic accuracy values than the manual approach.

This study compared sensitivity of FDG-PET, MR morphometry, and diffusion tensor imaging (DTI) derived fractional anisotropy (FA) measures to diagnosis and memory function in mild cognitive impairment (MCI). Patients ( n = 44) and normal controls (NC, n = 22) underwent FDG-PET and MRI scanning yielding measures of metabolism, morphometry and FA in nine temporal and parietal areas affected by Alzheimer's disease and involved in the episodic memory network. Patients also underwent memory testing (RAVLT). Logistic regression analysis yielded 100% diagnostic accuracy when all methods and ROIs were combined, but none of the variables then served as unique predictors. Within separate ROIs, diagnostic accuracy for the methods combined ranged from 65.6% (parahippocampal gyrus) to 73.4 (inferior parietal cortex). Morphometry predicted diagnostic group for most ROIs. PET and FA did not uniquely predict group, but a trend was seen for the precuneus metabolism. For the MCI group, stepwise regression analyses predicting memory scores were performed with the same methods and ROIs. Hippocampal volume and FA of the retrosplenial WM predicted learning, and hippocampal metabolism and parahippocampal cortical thickness predicted 5 minute recall. No variable predicted 30 minute recall independently of learning. In conclusion, higher diagnostic accuracy was achieved when multiple methods and ROIs were combined, but morphometry showed superior diagnostic sensitivity. Metabolism, morphometry and FA all uniquely explained memory performance, making a multi-modal approach superior. Memory variation in MCI is likely related to conversion risk, and the results indicate potential for improved predictive power by the use of multimodal imaging.

In this fMRI-study, 6-year-old children considered at risk for dyslexia were compared with an age-/gender-matched control group for differences in brain activation when presented with visual stimuli differing in demands for literacy processing. Stimuli were nameable pictures, brand logos familiar to children, and written words - these were either regularly spelled using early-acquired rules ("alphabetic") or more complex ("orthographic"). Brain responses distinguished between the presentation conditions, as a function of group, within many cortical areas. Activation in the alphabetic and orthographic conditions in the left angular gyrus correlated with individual at-risk index scores, and activation in inferior occipito-temporal regions further indicated differential activation for the two groups related to orthographic processing, especially. Since similar patterns are reported in adult dyslexics when processing written words, it appears that sensitivity to the cortical differentiation of reading networks is established prior to formal literacy training.

There is still limited knowledge about the relationship between different structural brain parameters, despite huge progress in analysis of neuroimaging data. The aim of the present study was to test the relationship between fractional anisotropy (FA) from diffusion tensor imaging (DTI) and regional white matter (WM) volume. As WM volume has been shown to develop until middle age, the focus was on changes in WM properties in the age range of 40 to 60 years. 100 participants were scanned with magnetic resonance imaging (MRI). Each hemisphere was parcellated into 35 WM regions, and volume, FA, axial, and radial diffusion in each region were calculated. The relationships between age and the regional measures of FA and WM volume were tested, and then FA and WM volume were correlated, corrected for intracranial volume, age, and sex. WM volume was weakly related to age, while FA correlated negatively with age in 26 of 70 regions, caused by a mix of reduced axial and increased radial diffusion with age. 23 relationships between FA and WM volume were found, with seven being positive and sixteen negative. The positive correlations were mainly caused by increased radial diffusion. It is concluded that FA is more sensitive than volume to changes in WM integrity during middle age, and that FA-age correlations probably are related to reduced amount of myelin with increasing age. Further, FA and WM volume are moderately to weakly related and to a large extent sensitive to different characteristics of WM integrity.

To retrospectively compare the diagnostic accuracy of an alternative method used to grade gliomas that is based on histogram analysis of normalized cerebral blood volume (CBV) values from the entire tumor volume (obtained with the histogram method) with that of the hot-spot method, with histologic analysis as the reference standard.The medical ethics committee approved this study, and all patients provided informed consent. Fifty-three patients (24 female, 29 male; mean age, 48 years; age range, 14-76 years) with histologically confirmed gliomas were examined with dynamic contrast material-enhanced 1.5-T magnetic resonance (MR) imaging. CBV maps were created and normalized to unaffected white matter (normalized CBV maps). Four neuroradiologists independently measured the distribution of whole-tumor normalized CBVs and analyzed this distribution by classifying the values into area-normalized bins. Glioma grading was performed by assessing the normalized peak height of the histogram distributions. Logistic regression analysis and interobserver agreement were used to compare the proposed method with a hot-spot method in which only the maximum normalized CBV was used.For the histogram method, diagnostic accuracy was independent of the observer. Interobserver agreement was almost perfect for the histogram method (kappa = 0.923) and moderate for the hot-spot method (kappa = 0.559). For all observers, sensitivity was higher with the histogram method (90%) than with the hot-spot method (55%-76%).Glioma grading based on histogram analysis of normalized CBV heterogeneity is an alternative to the established hot-spot method, as it offers increased diagnostic accuracy and interobserver agreement.