A densely interconnected network for deep learning accelerated MRI.

OBJECTIVE: To improve accelerated MRI reconstruction through a densely connected cascading deep learning reconstruction framework. MATERIALS AND METHODS: A cascading deep learning reconstruction framework (reference model) was modified by applying three architectural modifications: input-level dense connections between cascade inputs and outputs, an improved deep learning sub-network, and long-range skip-connections between subsequent deep learning networks. An ablation study was performed, where five model configurations were trained on the NYU fastMRI neuro dataset with an end-to-end scheme conjunct on four- and eightfold acceleration. The trained models were evaluated by comparing their respective structural similarity index measure (SSIM), normalized mean square error (NMSE), and peak signal to noise ratio (PSNR). RESULTS: The proposed densely interconnected residual cascading network (DIRCN), utilizing all three suggested modifications achieved a SSIM improvement of 8% and 11%, a NMSE improvement of 14% and 23%, and a PSNR improvement of 2% and 3% for four- and eightfold acceleration, respectively. In an ablation study, the individual architectural modifications all contributed to this improvement for both acceleration factors, by improving the SSIM, NMSE, and PSNR with approximately 2-4%, 4-9%, and 0.5-1%, respectively. CONCLUSION: The proposed architectural modifications allow for simple adjustments on an already existing cascading framework to further improve the resulting reconstructions.

Operator dependency of arterial input function in dynamic contrast-enhanced MRI.

OBJECTIVE: To investigate the effect of inter-operator variability in arterial input function (AIF) definition on kinetic parameter estimates (KPEs) from dynamic contrast-enhanced (DCE) MRI in patients with high-grade gliomas. METHODS: The study included 118 DCE series from 23 patients. AIFs were measured by three domain experts (DEs), and a population AIF (pop-AIF) was constructed from the measured AIFs. The DE-AIFs, pop-AIF and AUC-normalized DE-AIFs were used for pharmacokinetic analysis with the extended Tofts model. AIF-dependence of KPEs was assessed by intraclass correlation coefficient (ICC) analysis, and the impact on relative longitudinal change in Ktrans was assessed by Fleiss' kappa (κ). RESULTS: There was a moderate to substantial agreement (ICC 0.51-0.76) between KPEs when using DE-AIFs, while AUC-normalized AIFs yielded ICC 0.77-0.95 for Ktrans, kep and ve and ICC 0.70 for vp. Inclusion of the pop-AIF did not reduce agreement. Agreement in relative longitudinal change in Ktrans was moderate (κ = 0.591) using DE-AIFs, while AUC-normalized AIFs gave substantial (κ = 0.809) agreement. DISCUSSION: AUC-normalized AIFs can reduce the variation in kinetic parameter results originating from operator input. The pop-AIF presented in this work may be applied in absence of a satisfactory measurement.

Automated segmentation of magnetic resonance bone marrow signal: a feasibility study.

BACKGROUND: Manual assessment of bone marrow signal is time-consuming and requires meticulous standardisation to secure adequate precision of findings. OBJECTIVE: We examined the feasibility of using deep learning for automated segmentation of bone marrow signal in children and adolescents. MATERIALS AND METHODS: We selected knee images from 95 whole-body MRI examinations of healthy individuals and of children with chronic non-bacterial osteomyelitis, ages 6-18 years, in a longitudinal prospective multi-centre study cohort. Bone marrow signal on T2-weighted Dixon water-only images was divided into three color-coded intensity-levels: 1 = slightly increased; 2 = mildly increased; 3 = moderately to highly increased, up to fluid-like signal. We trained a convolutional neural network on 85 examinations to perform bone marrow segmentation. Four readers manually segmented a test set of 10 examinations and calculated ground truth using simultaneous truth and performance level estimation (STAPLE). We evaluated model and rater performance through Dice similarity coefficient and in consensus. RESULTS: Consensus score of model performance showed acceptable results for all but one examination. Model performance and reader agreement had highest scores for level-1 signal (median Dice 0.68) and lowest scores for level-3 signal (median Dice 0.40), particularly in examinations where this signal was sparse. CONCLUSION: It is feasible to develop a deep-learning-based model for automated segmentation of bone marrow signal in children and adolescents. Our model performed poorest for the highest signal intensity in examinations where this signal was sparse. Further improvement requires training on larger and more balanced datasets and validation against ground truth, which should be established by radiologists from several institutions in consensus.

Reliability and sensitivity of two whole-brain segmentation approaches included in FreeSurfer - ASEG and SAMSEG.

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.

Sleep and sleep deprivation differentially alter white matter microstructure: A mixed model design utilising advanced diffusion modelling.

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.

Cognition in adult patients with newly diagnosed non-lesional temporal lobe epilepsy.

OBJECTIVE: To evaluate whether cognitive performance is affected in newly diagnosed temporal lobe epilepsy (TLE) and to determine the most vulnerable cognitive domains. METHODS: In this baseline longitudinal study, differences in memory and non-memory cognitive functions were assessed using comprehensive neuropsychological test batteries in 21 adult patients with newly diagnosed non-lesional TLE and individually matched controls. In addition, the analyses included ratings of self-perceived emotional status. RESULTS: The patients performed more poorly than the control group regarding delayed visual memory (p = 0.013) and executive function tasks related to switching (Trail Making Test and verbal fluency shifting; p = 0.025 and p = 0.03, respectively). We found no differences in verbal learning and memory, attention/working memory/processing speed, and other executive functions. SIGNIFICANCE: Our results show that patients with TLE often have specific cognitive deficits at time of diagnosis, even in the absence of structural brain abnormalities. This supports the hypothesis that memory dysfunction is linked to an underlying pathology rather than to the effect of recurrent seizures, long-term use of anti-seizure medication, or other epilepsy-related factors. As certain executive functions are affected at an early stage, the pathology may involve brain regions beyond the temporal lobe and may comprise larger brain networks. These results indicate the need for greater awareness of cognition at the time of diagnosis of TLE and before initiation of treatment, and integration of neuropsychological assessment into early routine clinical care.

Evidence for wakefulness-related changes to extracellular space in human brain white matter from diffusion-weighted MRI.

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.

ExploreASL: An image processing pipeline for multi-center ASL perfusion MRI studies.

Arterial spin labeling (ASL) has undergone significant development since its inception, with a focus on improving standardization and reproducibility of its acquisition and quantification. In a community-wide effort towards robust and reproducible clinical ASL image processing, we developed the software package ExploreASL, allowing standardized analyses across centers and scanners. The procedures used in ExploreASL capitalize on published image processing advancements and address the challenges of multi-center datasets with scanner-specific processing and artifact reduction to limit patient exclusion. ExploreASL is self-contained, written in MATLAB and based on Statistical Parameter Mapping (SPM) and runs on multiple operating systems. To facilitate collaboration and data-exchange, the toolbox follows several standards and recommendations for data structure, provenance, and best analysis practice. ExploreASL was iteratively refined and tested in the analysis of >10,000 ASL scans using different pulse-sequences in a variety of clinical populations, resulting in four processing modules: Import, Structural, ASL, and Population that perform tasks, respectively, for data curation, structural and ASL image processing and quality control, and finally preparing the results for statistical analyses on both single-subject and group level. We illustrate ExploreASL processing results from three cohorts: perinatally HIV-infected children, healthy adults, and elderly at risk for neurodegenerative disease. We show the reproducibility for each cohort when processed at different centers with different operating systems and MATLAB versions, and its effects on the quantification of gray matter cerebral blood flow. ExploreASL facilitates the standardization of image processing and quality control, allowing the pooling of cohorts which may increase statistical power and discover between-group perfusion differences. Ultimately, this workflow may advance ASL for wider adoption in clinical studies, trials, and practice.

Sex Differences and Tumor Blood Flow from Dynamic Susceptibility Contrast MRI Are Associated with Treatment Response after Chemoradiation and Long-term Survival in 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. © RSNA, 2020 Online supplemental material is available for this article.

Effect of Drinking Oxygenated Water Assessed by in vivo MRI Relaxometry.

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 < 0.001) increase in T1 of HPV blood and water oxygenation attributed another 0.70% 95% confidence interval (CI) (0.07-1.3% P = 0.028) increase. Oxygenation did not change T1 in VCI blood. Mean T2 * increased 9.6% 95% CI (1.7-17.5% P = 0.017) after ingestion of oxygenated water and 1.2% 95% CI (-4.3-6.8% P = 0.661) after ingestion of control water. The corresponding changes in VCI blood were not significant. DATA CONCLUSION: Ingestion of water caused changes in T1 and T2 * of HPV blood compatible with dilution due to water absorption. The effects were enhanced by oxygen. Assessment of oxygen enrichment of HPV blood was not possible due to the dilution effect. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:720-728.

Waves of Maturation and Senescence in Micro-structural MRI Markers of Human Cortical Myelination over the Lifespan.

Seminal human brain histology work has demonstrated developmental waves of myelination. Here, using a micro-structural magnetic resonance imaging (MRI) marker linked 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 seven 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 30-s but there was a second wave reaching stability in the 50-s. Age at onset of decline was also bimodal: in some right hemisphere regions, the curve declined from the 60-s, but in other left hemisphere regions, there was no significant decline from the stable plateau. These results are consistent with regionally heterogeneous waves of intracortical myelinogenesis and age-related demyelination.

Determination of oxygen r1 at 3 Tesla using samples with a concentration range of dissolved oxygen.

OBJECTIVE: To investigate the sensitivity of modified Look-Locker inversion recovery (MOLLI) to measure changes in dissolved oxygen (DO) concentrations in water samples and to calculate sequence-specific relaxivity (r1m) and limit of detection (LOD). MATERIALS AND METHODS: Ten water samples with a range of DO concentrations were scanned at 3 T using two variations of MOLLI schemes. Using linear regression the r1 of DO was estimated from the measured DO concentrations and T1 relaxation rates (R1). The results were combined with previously reported values on in vivo stability measures of the MOLLI sequences and used to estimate a LOD. RESULTS: DO concentrations ranged from 0.5 to 21.6 mg L-1. A linear correlation between DO and R1 was obtained with both MOLLI sequences, with an average correlation coefficient (R2) 0.9 and an average estimated r1 ([Formula: see text]) of 4.45 × 10-3 s-1 mg-1 L. Estimated LOD was ≈ 10 mg L-1. CONCLUSION: MOLLI T1-mapping sequences may be used for detecting dissolved oxygen in vivo at 3 T with an [Formula: see text] in the range 4.18-4.8 × 10-3 s-1 mg-1 L and a corresponding LOD for dissolved oxygen of approximately 10 mg L-1. MOLLI-based T1 mapping may be a useful non-invasive tool for quantification of in vivo changes of DO concentration during oxygen challenges.

Cerebral blood flow changes after a day of wake, sleep, and sleep deprivation.

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 ±â€¯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.

Comparison of Intravoxel incoherent motion imaging and multiecho dynamic contrast-based MRI in rectal cancer.

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 J. Magn. Reson. Imaging 2019;50:1114-1124.

Restriction spectrum imaging of white matter and its relation to neurological disability in multiple sclerosis.

BACKGROUND: Restriction spectrum imaging (RSI) is a recently introduced magnetic resonance imaging diffusion technique. The utility of RSI in multiple sclerosis (MS) is unknown. OBJECTIVE: To investigate the association between RSI-derived parameters and neurological disability in MS. METHODS: Seventy-seven relapsing-remitting MS patients were scanned with RSI on a 3-T scanner. RSI-derived parameters: fast and slow apparent diffusion coefficient (sADC), fractional anisotropy, restricted fractional anisotropy, neurite density (ND), cellularity, extracellular water fraction, and free water fraction, were obtained in white matter lesions (WML) and normal appearing white matter (NAWM). Patients were divided into three groups according to their expanded disability status scale (EDSS): with minimal, low, and substantial disability (<2.5, 2.5-3, and >3, respectively). Group comparisons and correlation analyses were performed. RESULTS: All tested RSI-derived parameters differed between WML and NAWM ( p < 0.001 for all pairwise comparisons). The sADC in WML showed largest difference across disability subgroups (analysis of variance (ANOVA): F = 5.1, η2 = 0.12, p = 0.008). ND in NAWM showed strongest correlation with disability (ϱ = -0.39, p < 0.001). CONCLUSION: The strongest correlation with EDSS of ND obtained in NAWM indicates that processes outside lesions are important for disability in MS. Our study suggests that RSI-derived parameters may help understand the "clinico-radiological paradox" and improve disease monitoring in MS.

Permeability measurement using dynamic susceptibility contrast magnetic resonance imaging enhances differential diagnosis of primary central nervous system lymphoma from glioblastoma.

OBJECTIVES: 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. MATERIALS AND METHODS: 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. RESULTS: PCNSL demonstrated significantly higher permeability (Ex, p < .001) and lower perfusion (nCBVres, nCBFres, and nCBV, all p < .001) than glioblastoma. The combination of Ex and nCBVres showed the highest performance (AUC, 0.96; 95% confidence interval, 0.92-0.99) for differentiating PCNSL from glioblastoma, which was a significant improvement over the single perfusion (nCBV: AUC, 0.84; nCBVres: AUC, 0.84; nCBFres: AUC, 0.82; all p < .001) or Ex (AUC, 0.80; p < .001) parameters. CONCLUSIONS: Analysis of the combined permeability and perfusion metrics obtained from a single DSC-MRI acquisition improves the diagnostic value for differentiating PCNSL from glioblastoma in comparison with single-parameter nCBV analysis. KEY POINTS: • Permeability measurement can be calculated from DSC-MRI with a tissue residue function-based leakage correction. • Adding Exto CBV aids in the differentiation of PCNSL from glioblastoma. • CBV and Exmeasurements from DSC-MRI were highly reproducible.

Precision of T1-relaxation time measurements in the hepatic portal vein: influence of measurement technique and sequence parameters.

OBJECTIVE: 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). MATERIALS AND METHODS: 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. RESULTS: 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%). CONCLUSION: 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.

Neurodevelopmental origins of lifespan changes in brain and cognition.

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.

Preoperative quantitative dynamic contrast-enhanced MRI and diffusion-weighted imaging predict aggressive disease in endometrial cancer.

Background Quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) may yield preoperative tumor biomarkers relevant for prognosis and therapy in cancer. Purpose To explore the value of preoperative DCE-MRI and DWI for the prediction of aggressive disease in endometrial cancer patients. Material and Methods Preoperative MRI (1.5-T) from 177 patients were analyzed and imaging parameters reflecting tumor microvasculature (from DCE-MRI) and tumor microstructure (from DWI) were estimated. The derived imaging parameters were explored in relation to clinico-pathological stage, histological subtype and grade, molecular markers, and patient outcome. Results Low tumor blood flow (Fb) and low rate constant for contrast agent intravasation (kep) were associated with high-risk histological subtype ( P ≤ 0.04 for both) and tended to be associated with poor prognosis ( P ≤ 0.09). Low tumor apparent diffusion coefficient (ADC) value and large tumor volume were both significantly associated with deep myometrial invasion ( P < 0.001 for both) and were also unfavorable prognostic factors ( P = 0.05 and P < 0.001, respectively). Conclusion DCE-MRI and DWI represent valuable supplements to conventional MRI by providing preoperative imaging biomarkers that predict aggressive disease in endometrial cancer patients.