Insights into single-timepoint ASL hemodynamics: what visual assessment and spatial coefficient of variation can tell.

PURPOSE: Arterial spin labeling (ASL) represents a noninvasive perfusion biomarker, and, in the study of nonvascular disease, the use of the single-timepoint ASL technique is recommended. However, the obtained cerebral blood flow (CBF) maps may be highly influenced by delayed arterial transit time (ATT). Our aim was to assess the complexity of hemodynamic information of single-timepoint CBF maps using a new visual scale and comparing it with an ATT proxy, the "coefficient of spatial variation" (sCoV). MATERIAL AND METHODS: Individual CBF maps were estimated in a memory clinic population (mild cognitive impairment, dementia and cognitively unimpaired controls) and classified into four levels of delayed perfusion based on a visual rating scale. Calculated measures included global/regional sCoVs and common CBF statistics, as mean, median and standard deviation. One-way ANOVA was performed to compare these measures across the four groups of delayed perfusion. Spearman correlation was used to study the association of global sCoV with clinical data and CBF statistics. RESULTS: One hundred and forty-four participants (72 ± 7 years, 53% women) were included in the study. The proportion of maps with none, mild, moderate, and severe delayed perfusion was 15, 20, 37, and 28%, respectively. SCoV demonstrated a significant increase (p < 0.05) across the four groups, except when comparing none vs mild delayed perfusion groups (pBonf > 0.05). Global sCoV values, as an ATT proxy, ranged from 67 ± 4% (none) to 121 ± 24% (severe delayed) and were significantly associated with age and CBF statistics (p < 0.05). CONCLUSION: The impact of ATT delay in single-time CBF maps requires the use of a visual scale or sCoV in clinical or research settings.

Automated image quality assessment for selecting among multiple magnetic resonance image acquisitions in the German National Cohort study.

In magnetic resonance imaging (MRI), the perception of substandard image quality may prompt repetition of the respective image acquisition protocol. Subsequently selecting the preferred high-quality image data from a series of acquisitions can be challenging. An automated workflow may facilitate and improve this selection. We therefore aimed to investigate the applicability of an automated image quality assessment for the prediction of the subjectively preferred image acquisition. Our analysis included data from 11,347 participants with whole-body MRI examinations performed as part of the ongoing prospective multi-center German National Cohort (NAKO) study. Trained radiologic technologists repeated any of the twelve examination protocols due to induced setup errors and/or subjectively unsatisfactory image quality and chose a preferred acquisition from the resultant series. Up to 11 quantitative image quality parameters were automatically derived from all acquisitions. Regularized regression and standard estimates of diagnostic accuracy were calculated. Controlling for setup variations in 2342 series of two or more acquisitions, technologists preferred the repetition over the initial acquisition in 1116 of 1396 series in which the initial setup was retained (79.9%, range across protocols: 73-100%). Image quality parameters then commonly showed statistically significant differences between chosen and discarded acquisitions. In regularized regression across all protocols, 'structured noise maximum' was the strongest predictor for the technologists' choice, followed by 'N/2 ghosting average'. Combinations of the automatically derived parameters provided an area under the ROC curve between 0.51 and 0.74 for the prediction of the technologists' choice. It is concluded that automated image quality assessment can, despite considerable performance differences between protocols and anatomical regions, contribute substantially to identifying the subjective preference in a series of MRI acquisitions and thus provide effective decision support to readers.

Reliability of multi-site UK Biobank MRI brain phenotypes for the assessment of neuropsychiatric complications of SARS-CoV-2 infection: The COVID-CNS travelling heads study.

INTRODUCTION: Magnetic resonance imaging (MRI) of the brain could be a key diagnostic and research tool for understanding the neuropsychiatric complications of COVID-19. For maximum impact, multi-modal MRI protocols will be needed to measure the effects of SARS-CoV-2 infection on the brain by diverse potentially pathogenic mechanisms, and with high reliability across multiple sites and scanner manufacturers. Here we describe the development of such a protocol, based upon the UK Biobank, and its validation with a travelling heads study. A multi-modal brain MRI protocol comprising sequences for T1-weighted MRI, T2-FLAIR, diffusion MRI (dMRI), resting-state functional MRI (fMRI), susceptibility-weighted imaging (swMRI), and arterial spin labelling (ASL), was defined in close approximation to prior UK Biobank (UKB) and C-MORE protocols for Siemens 3T systems. We iteratively defined a comparable set of sequences for General Electric (GE) 3T systems. To assess multi-site feasibility and between-site variability of this protocol, N = 8 healthy participants were each scanned at 4 UK sites: 3 using Siemens PRISMA scanners (Cambridge, Liverpool, Oxford) and 1 using a GE scanner (King's College London). Over 2,000 Imaging Derived Phenotypes (IDPs), measuring both data quality and regional image properties of interest, were automatically estimated by customised UKB image processing pipelines (S2 File). Components of variance and intra-class correlations (ICCs) were estimated for each IDP by linear mixed effects models and benchmarked by comparison to repeated measurements of the same IDPs from UKB participants. Intra-class correlations for many IDPs indicated good-to-excellent between-site reliability. Considering only data from the Siemens sites, between-site reliability generally matched the high levels of test-retest reliability of the same IDPs estimated in repeated, within-site, within-subject scans from UK Biobank. Inclusion of the GE site resulted in good-to-excellent reliability for many IDPs, although there were significant between-site differences in mean and scaling, and reduced ICCs, for some classes of IDP, especially T1 contrast and some dMRI-derived measures. We also identified high reliability of quantitative susceptibility mapping (QSM) IDPs derived from swMRI images, multi-network ICA-based IDPs from resting-state fMRI, and olfactory bulb structure IDPs from T1, T2-FLAIR and dMRI data. CONCLUSION: These results give confidence that large, multi-site MRI datasets can be collected reliably at different sites across the diverse range of MRI modalities and IDPs that could be mechanistically informative in COVID brain research. We discuss limitations of the study and strategies for further harmonisation of data collected from sites using scanners supplied by different manufacturers. These acquisition and analysis protocols are now in use for MRI assessments of post-COVID patients (N = 700) as part of the ongoing COVID-CNS study.

Whole-Body Magnetic Resonance Imaging in the Large Population-Based German National Cohort Study: Predictive Capability of Automated Image Quality Assessment for Protocol Repetitions.

BACKGROUND: Reproducible image quality is of high relevance for large cohort studies and can be challenging for magnetic resonance imaging (MRI). Automated image quality assessment may contribute to conducting radiologic studies effectively. PURPOSE: The aims of this study were to assess protocol repetition frequency in population-based whole-body MRI along with its effect on examination time and to examine the applicability of automated image quality assessment for predicting decision-making regarding repeated acquisitions. MATERIALS AND METHODS: All participants enrolled in the prospective, multicenter German National Cohort (NAKO) study who underwent whole-body MRI at 1 of 5 sites from 2014 to 2016 were included in this analysis (n = 11,347). A standardized examination program of 12 protocols was used. Acquisitions were carried out by certified radiologic technologists, who were authorized to repeat protocols based on their visual perception of image quality. Eleven image quality parameters were derived fully automatically from the acquired images, and their discrimination ability regarding baseline acquisitions and repetitions was tested. RESULTS: At least 1 protocol was repeated in 12% (n = 1359) of participants, and more than 1 protocol in 1.6% (n = 181). The repetition frequency differed across protocols (P < 0.001), imaging sites (P < 0.001), and over the study period (P < 0.001). The mean total scan time was 62.6 minutes in participants without and 67.4 minutes in participants with protocol repetitions (mean difference, 4.8 minutes; 95% confidence interval, 4.5-5.2 minutes). Ten of the automatically derived image quality parameters were individually retrospectively predictive for the repetition of particular protocols; for instance, "signal-to-noise ratio" alone provided an area under the curve of 0.65 (P < 0.001) for repetition of the Cardio Cine SSFP SAX protocol. Combinations generally improved prediction ability, as exemplified by "image sharpness" plus "foreground ratio" yielding an area under the curve of 0.89 (P < 0.001) for repetition of the Neuro T1w 3D MPRAGE protocol, versus 0.85 (P < 0.001) and 0.68 (P < 0.001) as individual parameters. CONCLUSIONS: Magnetic resonance imaging protocol repetitions were necessary in approximately 12% of scans even in the highly standardized setting of a large cohort study. Automated image quality assessment shows predictive value for the technologists' decision to perform protocol repetitions and has the potential to improve imaging efficiency.

[The baseline assessment of the German National Cohort (NAKO Gesundheitsstudie): participation in the examination modules, quality assurance, and the use of secondary data]. / Die Basiserhebung der NAKO Gesundheitsstudie: Teilnahme an den Untersuchungsmodulen, Qualitätssicherung und Nutzung von Sekundärdaten.

BACKGROUND: The German National Cohort (NAKO) is an interdisciplinary health study aimed at elucidating causes for common chronic diseases and detecting their preclinical stages. This article provides an overview of design, methods, participation in the examinations, and their quality assurance based on the midterm baseline dataset (MBD) of the recruitment. METHODS: More than 200,000 women and men aged 20-69 years derived from random samples of the German general population were recruited in 18 study centers (2014-2019). The data collection comprised physical examinations, standardized interviews and questionnaires, and the collection of biomedical samples for all participants (level 1). At least 20% of all participants received additional in-depth examinations (level 2), and 30,000 received whole-body magnet resonance imaging (MRI). Additional information will be collected through secondary data sources such as medical registries, health insurances, and pension funds. This overview is based on the MBD, which included 101,839 participants, of whom 11,371 received an MRI. RESULTS: The mean response proportion was 18%. The participation in the examinations was high with most of the modules performed by over 95%. Among MRI participants, 96% completed all 12 MRI sequences. More than 90% of the participants agreed to the use of complementary secondary and registry data. DISCUSSION: Individuals selected for the NAKO were willing to participate in all examinations despite the time-consuming program. The NAKO provides a central resource for population-based epidemiologic research and will contribute to developing innovative strategies for prevention, screening and prediction of chronic diseases.

Automated quality assessment in three-dimensional breast ultrasound images.

Automated three-dimensional breast ultrasound (ABUS) is a valuable adjunct to x-ray mammography for breast cancer screening of women with dense breasts. High image quality is essential for proper diagnostics and computer-aided detection. We propose an automated image quality assessment system for ABUS images that detects artifacts at the time of acquisition. Therefore, we study three aspects that can corrupt ABUS images: the nipple position relative to the rest of the breast, the shadow caused by the nipple, and the shape of the breast contour on the image. Image processing and machine learning algorithms are combined to detect these artifacts based on 368 clinical ABUS images that have been rated manually by two experienced clinicians. At a specificity of 0.99, 55% of the images that were rated as low quality are detected by the proposed algorithms. The areas under the ROC curves of the single classifiers are 0.99 for the nipple position, 0.84 for the nipple shadow, and 0.89 for the breast contour shape. The proposed algorithms work fast and reliably, which makes them adequate for online evaluation of image quality during acquisition. The presented concept may be extended to further image modalities and quality aspects.

Assessment of intracranial collateral flow by using dynamic arterial spin labeling MRA and transcranial color-coded duplex ultrasound.

BACKGROUND AND PURPOSE: To evaluate the potential of a new dynamic MRA sequence (DynAngio) based on arterial spin labeling for the assessment of intracranial collateral flow. METHODS: Twelve patients with unilateral internal carotid artery obstruction were investigated. Different patterns of collateral flow were compared between DynAngio, transcranial color-coded duplex ultrasound, and time-of-flight MRA. RESULTS: There was a good agreement between the methods, with sensitivities between 80% and 90%. Small collateral vessels were detected more frequently with DynAngio compared to time-of-flight MRA. CONCLUSIONS: DynAngio provides anatomic and similar to transcranial color-coded duplex ultrasound functional information on collateral flow for the assessment of intracranial hemodynamics.

Risk and spectrum of diseases in travelers to popular tourist destinations.

BACKGROUND: Traveling to tropical regions is related to increased health risks. Travelers' diarrhea is the most frequent health problem, but the range of travel-related diseases also includes potential life-threatening diseases such as malaria. The actual risk of European travelers acquiring specific infectious diseases and other hazards in the tropics is to a large extent unknown and is therefore often adopted from that of the indigenous population. The objective of this study was to elucidate the risk for travel-related diseases, symptoms, and accidents in a population of Europeans who travel to popular tourist destinations. METHODS: From July 2003 to June 2004, 794 travelers consulting the travel clinic of the Berlin Institute of Tropical Medicine were recruited for a questionnaire-based observational study before traveling to Kenya, Tanzania, Senegal, the Gambia, India, Nepal, Thailand, or Brazil. RESULTS: Overall, illness was reported by 42.9% of travelers, with 10.2% reporting more than one adverse health event. Most frequently gastrointestinal symptoms were noted (34.6%), followed by respiratory symptoms (13.7%). More than 5% experienced an accident. Travel to the Indian subcontinent nearly doubled the risk of becoming ill; travel to Thailand significantly decreased the risk. Additional risk factors were a long duration of staying abroad, young age, and traveling under basic conditions. Of all travelers, 80% did not follow the traditionally recommended dietary restrictions. Among travelers visiting malaria-endemic areas, 20% did not carry any antimalarial drugs with them, not continuous chemoprophylaxis or standby medication. CONCLUSIONS: Because of the rising travel activity, especially to tropical countries, the importance of qualified pretravel advice consultation is increasing. To improve the travelers' health, attention needs to be paid to individual risk factors, the prevention and therapy of travelers' diarrhea, malaria prophylaxis, management of respiratory illness, and personal safety.

Assessment of irradiated brain metastases by means of arterial spin-labeling and dynamic susceptibility-weighted contrast-enhanced perfusion MRI: initial results.

RATIONALE AND OBJECTIVES: To assess if preradiation and early follow-up measurements of relative regional cerebral blood flow (rrCBF) can predict treatment outcome in patients with cerebral metastases and to evaluate rrCBF changes in tumor and normal tissue after stereotactic radiosurgery using arterial spin-labeling (ASL) and first-pass dynamic susceptibility-weighted contrast-enhanced (DSC) perfusion MRI. METHODS: In 25 patients with a total of 28 brain metastases, DSC MRI and ASL perfusion MRI using the Q2TIPS sequence were performed with a 1.5-T unit. Measurements were performed prior to and at 6 weeks, 12 weeks, and 24 weeks after stereotactic radiosurgery. Follow-up examinations were completely available in 25 patients for Q2TIPS and 17 patients with 18 metastases for DSC MRI. The rrCBF of the metastases and the normal brain tissue was determined by a region-of-interest analysis. rrCBF values were correlated with the treatment outcome that was classified according to tumor volume changes at 6 months. RESULTS: The alteration of the rrCBF at the 6-week follow-up was highly predictive for treatment outcome. A decrease of the rrCBF value predicted tumor response correctly in all metastases for Q2TIPS and in 13 of 16 metastases for DSC MRI. The pretherapeutic rrCBF was not able to predict treatment outcome. The rrCBF values in normal brain tissue affected by radiation doses less than 0.5 Gy remained unchanged after therapy. CONCLUSION: These preliminary results suggest that ASL and DSC MRI techniques determining rrCBF changes in brain metastases after stereotactic radiosurgery allow the prediction of treatment outcome.