Recommendations for quantitative cerebral perfusion MRI using multi-timepoint arterial spin labeling: Acquisition, quantification, and clinical applications.

Accurate assessment of cerebral perfusion is vital for understanding the hemodynamic processes involved in various neurological disorders and guiding clinical decision-making. This guidelines article provides a comprehensive overview of quantitative perfusion imaging of the brain using multi-timepoint arterial spin labeling (ASL), along with recommendations for its acquisition and quantification. A major benefit of acquiring ASL data with multiple label durations and/or post-labeling delays (PLDs) is being able to account for the effect of variable arterial transit time (ATT) on quantitative perfusion values and additionally visualize the spatial pattern of ATT itself, providing valuable clinical insights. Although multi-timepoint data can be acquired in the same scan time as single-PLD data with comparable perfusion measurement precision, its acquisition and postprocessing presents challenges beyond single-PLD ASL, impeding widespread adoption. Building upon the 2015 ASL consensus article, this work highlights the protocol distinctions specific to multi-timepoint ASL and provides robust recommendations for acquiring high-quality data. Additionally, we propose an extended quantification model based on the 2015 consensus model and discuss relevant postprocessing options to enhance the analysis of multi-timepoint ASL data. Furthermore, we review the potential clinical applications where multi-timepoint ASL is expected to offer significant benefits. This article is part of a series published by the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group, aiming to guide and inspire the advancement and utilization of ASL beyond the scope of the 2015 consensus article.

Evaluation of Virtual Grid processed clinical pelvic radiographs.

BACKGROUND: A physical scatter grid is not often used in pelvic bedside examinations. However, multiple studies regarding scatter correction software (SC SW) are available for mobile chest radiography but the results are unclear for pelvic radiography. PURPOSE: We evaluated SC SW of Fujifilm (Virtual Grid) on gridless pelvic radiographs obtained from a human Thiel-embalmed body to investigate the potential of Virtual Grid in pelvic bedside examinations. METHODS: Gridless, Virtual Grid, and physical grid pelvic radiographs of a female Thiel-embalmed body were collected with a broad range of tube loads. Different software (SW) grid ratios-6:1, 10:1, 13:1, 17:1, and 20:1-were applied on the gridless radiographs to investigate the image quality (IQ) improvement of 13 IQ criteria in a visual grading analysis (VGA) setup. RESULTS: Gridless radiograph scores are significantly lower (p < 0.001) than Virtual Grid and physical grid scores obtained with the same tube load. Virtual Grid radiographs score better than gridless radiographs obtained with a higher tube load which makes a dose reduction possible. The averaged ratings of the IQ criteria processed with different SW ratios increase with increasing SW grid ratios. However, no statistically significant differences were found between the SW grid ratios. The scores of the physical grid radiographs are higher than those of the Virtual Grid radiographs when they are obtained with the same tube load. CONCLUSION: We conclude that Virtual Grid with an SW ratio of 6:1 improves the IQ of gridless pelvic radiographs in such a manner that a dose reduction is possible. However, physical grid radiograph ratings are higher compared to those of Virtual Grid radiographs.

Current state and guidance on arterial spin labeling perfusion MRI in clinical neuroimaging.

This article focuses on clinical applications of arterial spin labeling (ASL) and is part of a wider effort from the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group to update and expand on the recommendations provided in the 2015 ASL consensus paper. Although the 2015 consensus paper provided general guidelines for clinical applications of ASL MRI, there was a lack of guidance on disease-specific parameters. Since that time, the clinical availability and clinical demand for ASL MRI has increased. This position paper provides guidance on using ASL in specific clinical scenarios, including acute ischemic stroke and steno-occlusive disease, arteriovenous malformations and fistulas, brain tumors, neurodegenerative disease, seizures/epilepsy, and pediatric neuroradiology applications, focusing on disease-specific considerations for sequence optimization and interpretation. We present several neuroradiological applications in which ASL provides unique information essential for making the diagnosis. This guidance is intended for anyone interested in using ASL in a routine clinical setting (i.e., on a single-subject basis rather than in cohort studies) building on the previous ASL consensus review.

Application of frozen Thiel-embalmed specimens for radiotherapy delineation guideline development: a method to create accurate MRI-enhanced CT datasets.

PURPOSE: Thiel embalming followed by freezing in the desired position and acquiring CT + MRI scans is expected to be the ideal approach to obtain accurate, enhanced CT data for delineation guideline development. The effect of Thiel embalming and freezing on MRI image quality is not known. This study evaluates the above-described process to obtain enhanced CT datasets, focusing on the integration of MRI data obtained from frozen, Thiel-embalmed specimens. METHODS: Three Thiel-embalmed specimens were frozen in prone crawl position and MRI scanning protocols were evaluated based on contrast detail and structural conformity between 3D renderings from corresponding structures, segmented on corresponding MRI and CT scans. The measurement error of the dataset registration procedure was also assessed. RESULTS: Scanning protocol T1 VIBE FS enabled swift differentiation of soft tissues based on contrast detail, even allowing a fully detailed segmentation of the brachial plexus. Structural conformity between the reconstructed structures on CT and MRI was excellent, with nerves and blood vessels imported into the CT scan never intersecting with the bones. The mean measurement error for the image registration procedure was consistently in the submillimeter range (range 0.77-0.94 mm). CONCLUSION: Based on the excellent MRI image quality and the submillimeter error margin, the procedure of scanning frozen Thiel-embalmed specimens in the treatment position to obtain enhanced CT scans is recommended. The procedure can be used to support the postulation of delineation guidelines, or for training deep learning algorithms, considering automated segmentations.

Modeling brain dynamics after tumor resection using The Virtual Brain.

Brain tumor patients scheduled for tumor resection often face significant uncertainty, as the outcome of neurosurgery is difficult to predict at the individual patient level. Recently, simulation of the activity of neural populations connected according to the white matter fibers, producing personalized brain network models, has been introduced as a promising tool for this purpose. The Virtual Brain provides a robust open source framework to implement these models. However, brain network models first have to be validated, before they can be used to predict brain dynamics. In prior work, we optimized individual brain network model parameters to maximize the fit with empirical brain activity. In this study, we extend this line of research by examining the stability of fitted parameters before and after tumor resection, and compare it with baseline parameter variability using data from healthy control subjects. Based on these findings, we perform the first "virtual neurosurgery", mimicking patient's actual surgery by removing white matter fibers in the resection mask and simulating again neural activity on this new connectome. We find that brain network model parameters are relatively stable over time in brain tumor patients who underwent tumor resection, compared with baseline variability in healthy control subjects. Concerning the virtual neurosurgery analyses, use of the pre-surgery model implemented on the virtually resected structural connectome resulted in improved similarity with post-surgical empirical functional connectivity in some patients, but negligible improvement in others. These findings reveal interesting avenues for increasing interactions between computational neuroscience and neuro-oncology, as well as important limitations that warrant further investigation.

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.

Supporting measurements or more averages? How to quantify cerebral blood flow most reliably in 5 minutes by arterial spin labeling.

PURPOSE: To determine whether sacrificing part of the scan time of pseudo-continuous arterial spin labeling (PCASL) for measurement of the labeling efficiency and blood T1 is beneficial in terms of CBF quantification reliability. METHODS: In a simulation framework, 5-minute scan protocols with different scan time divisions between PCASL data acquisition and supporting measurements were evaluated in terms of CBF estimation variability across both noise and ground truth parameter realizations taken from the general population distribution. The entire simulation experiment was repeated for a single-post-labeling delay (PLD), multi-PLD, and free-lunch time-encoded (te-FL) PCASL acquisition strategy. Furthermore, a real data study was designed for preliminary validation. RESULTS: For the considered population statistics, measuring the labeling efficiency and the blood T1 proved beneficial in terms of CBF estimation variability for any distribution of the 5-minute scan time compared to only acquiring ASL data. Compared to single-PLD PCASL without support measurements as recommended in the consensus statement, a 26%, 33%, and 42% reduction in relative CBF estimation variability was found for optimal combinations of supporting measurements with single-PLD, free-lunch, and multi-PLD PCASL data acquisition, respectively. The benefit of taking the individual variation of blood T1 into account was also demonstrated in the real data experiment. CONCLUSIONS: Spending time to measure the labeling efficiency and the blood T1 instead of acquiring more averages of the PCASL data proves to be advisable for robust CBF quantification in the general population.

The costs and benefits of estimating T1 of tissue alongside cerebral blood flow and arterial transit time in pseudo-continuous arterial spin labeling.

Multi-post-labeling-delay pseudo-continuous arterial spin labeling (multi-PLD PCASL) allows for absolute quantification of the cerebral blood flow (CBF) as well as the arterial transit time (ATT). Estimating these perfusion parameters from multi-PLD PCASL data is a non-linear inverse problem, which is commonly tackled by fitting the single-compartment model (SCM) for PCASL, with CBF and ATT as free parameters. The longitudinal relaxation time of tissue T1t is an important parameter in this model, as it governs the decay of the perfusion signal entirely upon entry in the imaging voxel. Conventionally, T1t is fixed to a population average. This approach can cause CBF quantification errors, as T1t can vary significantly inter- and intra-subject. This study compares the impact on CBF quantification, in terms of accuracy and precision, of either fixing T1t , the conventional approach, or estimating it alongside CBF and ATT. It is shown that the conventional approach can cause a significant bias in CBF. Indeed, simulation experiments reveal that if T1t is fixed to a value that is 10% off its true value, this may already result in a bias of 15% in CBF. On the other hand, as is shown by both simulation and real data experiments, estimating T1t along with CBF and ATT results in a loss of CBF precision of the same order, even if the experiment design is optimized for the latter estimation problem. Simulation experiments suggest that an optimal balance between accuracy and precision of CBF estimation from multi-PLD PCASL data can be expected when using the two-parameter estimator with a fixed T1t value between population averages of T1t and the longitudinal relaxation time of blood T1b .

Estimating the Patient-specific Dose to the Thyroid and Breasts and Overall Risk in Chest CT When Using Organ-based Tube Current Modulation.

Purpose To assess the potential dose reduction to the thyroid and breasts in chest computed tomography (CT) with organ-based tube current modulation (OBTCM). Materials and Methods In this retrospective study (from January 2015 to December 2016), the location of the breasts with respect to the reduced tube current zone was determined. With Monte Carlo simulations, patient-specific dose distributions of chest CT scans were calculated for 50 female patients (mean age, 53.7 years ± 17.5; range, 20-80 years). The potential dose reduction with OBTCM was assessed. In addition, simulations of clinical OBTCM scans were made for 17 of the 50 female patients (mean age, 43.8 years ± 17.1; range, 20-69 years). Posterior organs in the field of view were analyzed and lifetime attributable risk (LAR) of cancer incidence and mortality was estimated. Image quality between standard CT and OBTCM scans was compared. Results No women had all breast tissue within the reduced tube current zone. Dose reductions of 18% in the thyroid and 9% in the breasts were observed, whereas the doses in lung, liver, and kidney were 17%, 11%, and 26% higher. Overall, the LAR for cancer incidence was not significantly different between conventional and OBTCM scanning (P = .06). Image quality improved with OBTCM (P < .002). Conclusion The potential benefit of OBTCM to the female breast in chest CT is overestimated because of a limited reduced tube current zone; despite a 9% dose reduction to the female breast, posterior organs will absorb up to 26% more radiation, resulting in no reduction in radiation-induced malignancies. © RSNA, 2018.

Presence of the posterior pituitary bright spot sign on MRI in the general population: a comparison between 1.5 and 3T MRI and between 2D-T1 spin-echo- and 3D-T1 gradient-echo sequences.

PURPOSE: To describe the prevalence of the posterior pituitary bright spot (PPBS) in the general population on 1.5 and 3T MRI examinations and on 2D-T1 spin-echo (SE) and 3D-T1 gradient-echo (GE) sequences. MATERIALS AND METHODS: 1017 subjects who received an MRI of the brain for aspecific neurological complaints were included. MRI was performed on 1.5T in 64.5% and on 3T in 35.5% of subjects. Presence of the PPBS was evaluated on sagittal 2D T1-SE echo images with slice thickness 3 mm in 67.5% and on sagittal 3D T1-GE with slice thickness 0.9 mm in 32.5% of subjects. RESULTS: The PPBS was detectable in 95.9% of subjects. After correction for sex and age, no statistically significant difference could be seen concerning PPBS detection between 1.5 and 3T MRI examinations (p = 0.533), nor between 2D T1-SE and 3D T1-GE sequences (p = 0.217). There was a statistically significant association between increasing age and the absence of the PPBS (p < 0.001). The PPBS could not be identified in 6.2% of male subjects, compared to 2.2% of female subjects (p = 0.01). DISCUSSION: Absence of the PPBS can be seen in 4.1% of patients undergoing MRI of the brain for non-endocrinological reasons. Neither field-strength nor the use of a thick-sliced 2D T1-SE versus a thin-sliced 3D T1-GE sequence influenced the detectability of the PPBS. There is a statistically significant association between increasing age and male sex and the absence of the PPBS.

Proximal aortic stiffening in Turner patients may be present before dilation can be detected: a segmental functional MRI study.

BACKGROUND: To study segmental structural and functional aortic properties in Turner syndrome (TS) patients. Aortic abnormalities contribute to increased morbidity and mortality of women with Turner syndrome. Cardiovascular magnetic resonance (CMR) allows segmental study of aortic elastic properties. METHOD: We performed Pulse Wave Velocity (PWV) and distensibility measurements using CMR of the thoracic and abdominal aorta in 55 TS-patients, aged 13-59y, and in a control population (n = 38;12-58y). We investigated the contribution of TS on aortic stiffness in our entire cohort, in bicuspid (BAV) versus tricuspid (TAV) aortic valve-morphology subgroups, and in the younger and older subgroups. RESULTS: Differences in aortic properties were only seen at the most proximal aortic level. BAV Turner patients had significantly higher PWV, compared to TAV Turner (p = 0.014), who in turn had significantly higher PWV compared to controls (p = 0.010). BAV Turner patients had significantly larger ascending aortic (AA) luminal area and lower AA distensibility compared to both controls (all p < 0.01) and TAV Turner patients. TAV Turner had similar AA luminal areas and AA distensibility compared to Controls. Functional changes are present in younger and older Turner subjects, whereas ascending aortic dilation is prominent in older Turner patients. Clinically relevant dilatation (TAV and BAV) was associated with reduced distensibility. CONCLUSION: Aortic stiffening and dilation in TS affects the proximal aorta, and is more pronounced, although not exclusively, in BAV TS patients. Functional abnormalities are present at an early age, suggesting an aortic wall disease inherent to the TS. Whether this increased stiffness at young age can predict later dilatation needs to be studied longitudinally.

Semi-automated brain tumor segmentation on multi-parametric MRI using regularized non-negative matrix factorization.

BACKGROUND: Segmentation of gliomas in multi-parametric (MP-)MR images is challenging due to their heterogeneous nature in terms of size, appearance and location. Manual tumor segmentation is a time-consuming task and clinical practice would benefit from (semi-) automated segmentation of the different tumor compartments. METHODS: We present a semi-automated framework for brain tumor segmentation based on non-negative matrix factorization (NMF) that does not require prior training of the method. L1-regularization is incorporated into the NMF objective function to promote spatial consistency and sparseness of the tissue abundance maps. The pathological sources are initialized through user-defined voxel selection. Knowledge about the spatial location of the selected voxels is combined with tissue adjacency constraints in a post-processing step to enhance segmentation quality. The method is applied to an MP-MRI dataset of 21 high-grade glioma patients, including conventional, perfusion-weighted and diffusion-weighted MRI. To assess the effect of using MP-MRI data and the L1-regularization term, analyses are also run using only conventional MRI and without L1-regularization. Robustness against user input variability is verified by considering the statistical distribution of the segmentation results when repeatedly analyzing each patient's dataset with a different set of random seeding points. RESULTS: Using L1-regularized semi-automated NMF segmentation, mean Dice-scores of 65%, 74 and 80% are found for active tumor, the tumor core and the whole tumor region. Mean Hausdorff distances of 6.1 mm, 7.4 mm and 8.2 mm are found for active tumor, the tumor core and the whole tumor region. Lower Dice-scores and higher Hausdorff distances are found without L1-regularization and when only considering conventional MRI data. CONCLUSIONS: Based on the mean Dice-scores and Hausdorff distances, segmentation results are competitive with state-of-the-art in literature. Robust results were found for most patients, although careful voxel selection is mandatory to avoid sub-optimal segmentation.

Spectral data de-noising using semi-classical signal analysis: application to localized MRS.

In this paper, we propose a new post-processing technique called semi-classical signal analysis (SCSA) for MRS data de-noising. Similar to Fourier transformation, SCSA decomposes the input real positive MR spectrum into a set of linear combinations of squared eigenfunctions equivalently represented by localized functions with shape derived from the potential function of the Schrödinger operator. In this manner, the MRS spectral peaks represented as a sum of these 'shaped like' functions are efficiently separated from noise and accurately analyzed. The performance of the method is tested by analyzing simulated and real MRS data. The results obtained demonstrate that the SCSA method is highly efficient in localized MRS data de-noising and allows for an accurate data quantification.

The role of Size-Specific Dose Estimate (SSDE) in patient-specific organ dose and cancer risk estimation in paediatric chest and abdominopelvic CT examinations.

OBJECTIVES: To develop a clinically applicable method to estimate patient-specific organ and blood doses and lifetime attributable risks (LAR) from paediatric torso CT examinations. METHODS: Individualized voxel models were created from full-body CT data of 10 paediatric patients (2-18 years). Patient-specific dose distributions of chest and abdominopelvic CT scans were simulated using Monte Carlo methods. Blood dose was calculated as a weighted sum of simulated organ doses. LAR of cancer incidence and mortality were estimated, according to BEIR-VII. A second simulation and blood dose calculation was performed using only the thoracic and abdominopelvic region of the original voxel models. For each simulation, the size-specific dose estimate (SSDE) was calculated. RESULTS: SSDE showed a significant strong linear correlation with organ dose (r > 0.8) and blood dose (r > 0.9) and LAR (r > 0.9). No significant differences were found between blood dose calculations with the full-body voxel models and the thoracic or abdominopelvic models. CONCLUSION: Even though clinical CT images mostly do not cover the whole body of the patient, they can be used as a voxel model for blood dose calculation. In addition, SSDE can estimate patient-specific organ and blood doses and LAR in paediatric torso CT examinations. KEY POINTS: • Blood dose can be simulated using the patient's clinical CT images. • SSDE estimates patient-specific organ/blood dose and LAR in paediatric CAP CT-examinations. • SSDE makes on-the-spot dose and LAR estimations possible in routine clinical practice.

Brachial plexus 3D reconstruction from MRI with dissection validation: a baseline study for clinical applications.

PURPOSE: The present study aimed to establish a baseline for detailed 3D brachial plexus reconstruction from magnetic resonance imaging (MRI). Concretely, the goal was to determine the individual brachial plexus anatomy with maximum detail and accuracy achievable, as yet irrespective of whether the methods used could be economically and practically applied in the clinical setting. MATERIALS AND METHODS: Six embalmed cadavers were randomly taken for MRI imaging of the brachial plexus. Detailed two-dimensional (2D) segmentation for all brachial plexus parts was done. The 2D brachial plexus segmentations were 3D reconstructed using Mimics(®) software. Then, these 3D reconstructions were anatomically validated by dissection of the cadavers. After finalising the cadaver experiments, brachial plexus MRIs were obtained in three healthy male volunteers and the same reconstruction procedure as in vitro was followed. RESULTS: A procedure was developed for brachial plexus 3D reconstruction based on MRI without the use of any contrast agent. Anatomical validation of six cadaver brachial plexus reconstructions showed high correspondence with the dissected brachial plexuses. Anatomical variations of the main branches were equally present in the 3D reconstructions generated. However, there were also some differences that related to the difference between the surface anatomy of the nerve and the internal nerve structure. In vivo, it was possible to reconstruct the complete brachial plexus in such a manner that normal-appearing BPs were derived in a reproducible way. CONCLUSIONS: This study showed that the described procedure results in accurate and reproducible brachial plexus 3D reconstructions.

Organ Doses and Radiation Risk of Computed Tomographic Coronary Angiography in a Clinical Patient Population: How Do Low-Dose Acquisition Modes Compare?

OBJECTIVE: To compare the organ doses and lifetime-attributable risk of cancer for electrocardiogram-triggered sequential and high-pitch helical scanning in a clinical patient population. METHODS: Phantom thermoluminiscence dosimeter measurements were used as a model for the organ dose assessment of 314 individual patients who underwent coronary computed tomographic angiography. Patient-specific lifetime-attributable cancer risks were calculated. RESULTS: Phantom measurements showed that heart rate had a significant influence on the delivered radiation exposure in sequential mode, and calcium scoring and contrast bolus tracking scans make a nonnegligible contribution to patients' dose. Therefore, they should be taken into account for patients' organ dose estimations. Median cancer induction risks are low, with 0.008% (0.0016%) and 0.022% (0.056%) for high-pitch and sequential scanning for men (women), respectively. CONCLUSIONS: The use of high-pitch helical scanning leads to 65% and 72% lower lifetime-attributable risk values for men and women, respectively, compared with sequential scanning.

Correlation of clinical and physical-technical image quality in chest CT: a human cadaver study applied on iterative reconstruction.

BACKGROUND: The first aim of this study was to evaluate the correlation between clinical and physical-technical image quality applied to different strengths of iterative reconstruction in chest CT images using Thiel cadaver acquisitions and Catphan images. The second aim was to determine the potential dose reduction of iterative reconstruction compared to conventional filtered back projection based on different clinical and physical-technical image quality parameters. METHODS: Clinical image quality was assessed using three Thiel embalmed human cadavers. A Catphan phantom was used to assess physical-technical image quality parameters such as noise, contrast-detail and contrast-to-noise ratio (CNR). Both Catphan and chest Thiel CT images were acquired on a multislice CT scanner at 120 kVp and 0.9 pitch. Six different refmAs settings were applied (12, 30, 60, 90, 120 and 150refmAs) and each scan was reconstructed using filtered back projection (FBP) and iterative reconstruction (SAFIRE) algorithms (1,3 and 5 strengths) using a sharp kernel, resulting in 24 image series. Four radiologists assessed the clinical image quality, using a visual grading analysis (VGA) technique based on the European Quality Criteria for Chest CT. RESULTS: Correlation coefficients between clinical and physical-technical image quality varied from 0.88 to 0.92, depending on the selected physical-technical parameter. Depending on the strength of SAFIRE, the potential dose reduction based on noise, CNR and the inverse image quality figure (IQF(inv)) varied from 14.0 to 67.8%, 16.0 to 71.5% and 22.7 to 50.6% respectively. Potential dose reduction based on clinical image quality varied from 27 to 37.4%, depending on the strength of SAFIRE. CONCLUSION: Our results demonstrate that noise assessments in a uniform phantom overestimate the potential dose reduction for the SAFIRE IR algorithm. Since the IQF(inv) based dose reduction is quite consistent with the clinical based dose reduction, an optimised contrast-detail phantom could improve the use of contrast-detail analysis for image quality assessment in chest CT imaging. In conclusion, one should be cautious to evaluate the performance of CT equipment taking into account only physical-technical parameters as noise and CNR, as this might give an incomplete representation of the actual clinical image quality performance.

Anticipatory processes in brain state switching - evidence from a novel cued-switching task implicating default mode and salience networks.

The default mode network (DMN) is the core brain system supporting internally oriented cognition. The ability to attenuate the DMN when switching to externally oriented processing is a prerequisite for effective performance and adaptive self-regulation. Right anterior insula (rAI), a core hub of the salience network (SN), has been proposed to control the switching from DMN to task-relevant brain networks. Little is currently known about the extent of anticipatory processes subserved by DMN and SN during switching. We investigated anticipatory DMN and SN modulation using a novel cued-switching task of between-state (rest-to-task/task-to-rest) and within-state (task-to-task) transitions. Twenty healthy adults performed the task implemented in an event-related functional magnetic resonance imaging (fMRI) design. Increases in activity were observed in the DMN regions in response to cues signalling upcoming rest. DMN attenuation was observed for rest-to-task switch cues. Obversely, DMN was up-regulated by task-to-rest cues. The strongest rAI response was observed to rest-to-task switch cues. Task-to-task switch cues elicited smaller rAI activation, whereas no significant rAI activation occurred for task-to-rest switches. Our data provide the first evidence that DMN modulation occurs rapidly and can be elicited by short duration cues signalling rest- and task-related state switches. The role of rAI appears to be limited to certain switch types - those implicating transition from a resting state and to tasks involving active cognitive engagement.

Declutter the MRI protocol tree: Managing and comparing sequence parameters of multiple clinical Siemens MRI systems.

An MRI protocol tree on a clinical MRI system is a large database containing hundreds of protocols, each containing multiple sequences, and up to 900 parameters per sequence. Protocol variation between scan sessions or patients must be avoided as much as possible, as it may lead to financial loss and less than optimal outcomes for the patient. Without proper management, protocol variation and errors in MRI protocol trees are easily introduced and may remain undetected, leading to a cluttered protocol tree. This in turn reduces the efficiency of the radiological MRI workflow. We introduce a method and open-source software tools for managing MRI protocols on a sequence parameter level, which can detect deviations and variations in the protocol tree. It can be used offline, away from the scanner console, without disturbing the clinical workflow. These tools help to create a standardized protocol library across multiple MRI scanners, reducing variation and errors, enabling radiology departments to create optimal value for the patient and institution.

Developing blood-brain barrier arterial spin labelling as a non-invasive early biomarker of Alzheimer's disease (DEBBIE-AD): a prospective observational multicohort study protocol.

INTRODUCTION: Loss of blood-brain barrier (BBB) integrity is hypothesised to be one of the earliest microvascular signs of Alzheimer's disease (AD). Existing BBB integrity imaging methods involve contrast agents or ionising radiation, and pose limitations in terms of cost and logistics. Arterial spin labelling (ASL) perfusion MRI has been recently adapted to map the BBB permeability non-invasively. The DEveloping BBB-ASL as a non-Invasive Early biomarker (DEBBIE) consortium aims to develop this modified ASL-MRI technique for patient-specific and robust BBB permeability assessments. This article outlines the study design of the DEBBIE cohorts focused on investigating the potential of BBB-ASL as an early biomarker for AD (DEBBIE-AD). METHODS AND ANALYSIS: DEBBIE-AD consists of a multicohort study enrolling participants with subjective cognitive decline, mild cognitive impairment and AD, as well as age-matched healthy controls, from 13 cohorts. The precision and accuracy of BBB-ASL will be evaluated in healthy participants. The clinical value of BBB-ASL will be evaluated by comparing results with both established and novel AD biomarkers. The DEBBIE-AD study aims to provide evidence of the ability of BBB-ASL to measure BBB permeability and demonstrate its utility in AD and AD-related pathologies. ETHICS AND DISSEMINATION: Ethics approval was obtained for 10 cohorts, and is pending for 3 cohorts. The results of the main trial and each of the secondary endpoints will be submitted for publication in a peer-reviewed journal.