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.

In vitro PK/PD modeling of tyrosine kinase inhibitors in non-small cell lung cancer cell lines.

Tyrosine kinase inhibitors (TKIs) are routinely prescribed for the treatment of non-small cell lung cancer (NSCLC). As with all medications, patients can experience adverse events due to TKIs. Unfortunately, the relationship between many TKIs and the occurrence of certain adverse events remains unclear. There are limited in vivo studies which focus on TKIs and their effects on different regulation pathways. Many in vitro studies, however, that investigate the effects of TKIs observe additional changes, such as changes in gene activations or protein expressions. These studies could potentially help to gain greater understanding of the mechanisms for TKI induced adverse events. However, in order to utilize these pathways in a pharmacokinetic/pharmacodynamic (PK/PD) framework, an in vitro PK/PD model needs to be developed, in order to characterize the effects of TKIs in NSCLC cell lines. Through the use of ordinary differential equations, cell viability data and nonlinear mixed effects modeling, an in vitro TKI PK/PD model was developed with estimated PK and PD parameter values for the TKIs alectinib, crizotinib, erlotinib, and gefitinib. The relative standard errors for the population parameters are all less than 25%. The inclusion of random effects enabled the model to predict individual parameter values which provided a closer fit to the observed response. It is hoped that this model can be extended to include in vitro data of certain pathways that may potentially be linked with adverse events and provide a better understanding of TKI-induced adverse events.

Effects of the Fasting-Postprandial State on Arterial Spin Labeling MRI-Based Cerebral Perfusion Quantification in Alzheimer's Disease.

BACKGROUND: The fasting-postprandial state remains an underrecognized confounding factor for quantifying cerebral blood flow (CBF) in the cognitive assessment and differential diagnosis of Alzheimer's disease (AD). PURPOSE: To investigate the effects of fasting-postprandial state on arterial spin labeling (ASL)-based CBF in AD patients. STUDY TYPE: Prospective. SUBJECTS: Ninety-two subjects (mean age = 62.5 ± 6.4 years; females 29.3%), including 30 with AD, 32 with mild cognitive impairment (MCI), and 30 healthy controls (HCs). Differential diagnostic models were developed with a 4:1 training to testing set ratio. FIELD STRENGTH/SEQUENCE: 3-T, T1-weighted imaging using gradient echo and pseudocontinuous ASL imaging using turbo spin echo. ASSESSMENT: Two ASL scans were acquired to quantify fasting state and postprandial state regional CBFs based on an automated anatomical labeling atlas. Two-way ANOVA was used to assess the effects of fasting/postprandial state and disease state (AD, MCI, and HC) on regional CBF. Pearson's correlation analysis was conducted between regional CBF and cognitive scores (Mini-Mental State Examination [MMSE] and Montreal Cognitive Assessment [MoCA]). The diagnostic performances of the fasting state, postprandial state, and mixed state (random mixing of the fasting and postprandial state CBF) in differential diagnosis of AD were conducted using support vector machine and logistic regression models. STATISTICAL TESTS: Two-way ANOVA, Pearson's correlation, and area under the curve (AUC) of diagnostic model were performed. P values <0.05 indicated statistical significance. RESULTS: Fasting-state CBF was correlated with cognitive scores in more brain regions (17 vs. 4 [MMSE] and 15 vs. 9 [MoCA]) and had higher absolute correlation coefficients than postprandial-state CBF. In the differential diagnosis of AD patients from MCI patients and HCs, fasting-state CBF outperformed mixed-state CBF, which itself outperformed postprandial-state CBF. DATA CONCLUSION: Compared with postprandial CBF, fasting-state CBF performed better in terms of cognitive score correlations and in differentiating AD patients from MCI patients and HCs. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 3.

Parameter estimation of a model describing the human fingers.

The goal of this paper is twofold: firstly, to provide a novel mathematical model that describes the kinematic chain of motion of the human fingers based on Lagrangian mechanics with four degrees of freedom and secondly, to estimate the model parameters using data from able-bodied individuals. In the literature there are a variety of mathematical models that have been developed to describe the motion of the human finger. These models offer little to no information on the underlying mechanisms or corresponding equations of motion. Furthermore, these models do not provide information as to how they scale with different anthropometries. The data used here is generated using an experimental procedure that considers the free response motion of each finger segment with data captured via a motion capture system. The angular data collected are then filtered and fitted to a linear second-order differential approximation of the equations of motion. The results of the study show that the free response motion of the segments is underdamped across flexion/extension and ad/abduction.

Reliability, accuracy, and minimal detectable difference of a mixed concept marker set for finger kinematic evaluation.

The study of finger biomechanics requires special tools for accurately recording finger joint data. A marker set to evaluate finger postures during activities of daily living is needed to understand finger biomechanics in order to improve prosthesis design and clinical interventions. The purpose of this study was to evaluate the reliability of a proposed hand marker set (the Warwick marker set) to capture finger kinematics using motion capture. The marker set consisted of the application of two and three marker clusters to the fingers of twelve participants who participated in the tests across two sessions. Calibration markers were applied using a custom palpation technique. Each participant performed a series of range of motion movements and held a set of objects. Intra and inter-session reliability was calculated as well as Standard Error of Measurement (SEM) and Minimal Detectable Difference (MDD). The findings showed varying levels of intra- and inter-session reliability, ranging from poor to excellent. The SEM and MDD values were lower for the intra-session range of motion and grasp evaluation. The reduced reliability can potentially be attributed to skin artifacts, differences in marker placement, and the inherent kinematic variability of finger motion. The proposed marker set shows potential to assess finger postures and analyse activities of daily living, primarily within the context of single session tests.

Brain perfusion imaging by multi-delay arterial spin labeling: Impact of modeling dispersion and interaction with denoising strategies and pathology.

PURPOSE: Arterial spin labeling (ASL) acquisitions at multiple post-labeling delays may provide more accurate quantification of cerebral blood flow (CBF), by fitting appropriate kinetic models and simultaneously estimating relevant parameters such as the arterial transit time (ATT) and arterial cerebral blood volume (aCBV). We evaluate the effects of denoising strategies on model fitting and parameter estimation when accounting for the dispersion of the label bolus through the vasculature in cerebrovascular disease. METHODS: We analyzed multi-delay ASL data from 17 cerebral small vessel disease patients (50 ± 9 y) and 13 healthy controls (52 ± 8 y), by fitting an extended kinetic model with or without bolus dispersion. We considered two denoising strategies: removal of structured noise sources by independent component analysis (ICA) of the control-label image timeseries; and averaging the repetitions of the control-label images prior to model fitting. RESULTS: Modeling bolus dispersion improved estimation precision and impacted parameter values, but these effects strongly depended on whether repetitions were averaged before model fitting. In general, repetition averaging improved model fitting but adversely affected parameter values, particularly CBF and aCBV near arterial locations in patients. This suggests that using all repetitions allows better noise estimation at the earlier delays. In contrast, ICA denoising improved model fitting and estimation precision while leaving parameter values unaffected. CONCLUSION: Our results support the use of ICA denoising to improve model fitting to multi-delay ASL and suggest that using all control-label repetitions improves the estimation of macrovascular signal contributions and hence perfusion quantification near arterial locations. This is important when modeling flow dispersion in cerebrovascular pathology.

Moving Toward a Question-Centric Approach for Regulatory Decision Making in the Context of Drug Assessment.

The most intuitive question for market access for medicinal products is the benefit/risk (B/R) balance. The B/R assessment can conceptually be divided into subquestions related to establishing efficacy and safety. There are additional layers to the B/R ratio for medical products, including questions related to dose selection, clinical and nonclinical pharmacology, and drug quality. Explicitly stating the actual questions and how they contribute to the overall B/R provides a structure that fosters better informed cross-domain discussions. There is currently no systematic approach in the regulatory setting to assess and establish the acceptability of alternative methods and data sources. In most cases, the medicinal product sponsors tend to prioritize traditional data types and methods, which are well accepted by regulators for inclusion in regulatory submissions. This, in addition to the absence of rigor in the use and validation of new data types and methods, and the limited training of assessors in related fields can lead to increased regulatory skepticism toward new data types and methods. A data-knowledge backbone is needed to mitigate the uncertainty in efficacy and safety characterization. This white paper discusses the value of explicitly redefining and restructuring the regulatory scientific decision making around the scientific question to be addressed. The ecosystem proposed is based on three pillars: (i) a repository connecting questions, data, and methods; (ii) the development and validation of high-quality standards for data and methods; and (iii) credibility assessment. The ecosystem is applied to four use cases for illustration. The need for training and regulatory guidance is also discussed.

MRI assessment of cerebral perfusion in clinical trials.

Neurodegenerative mechanisms affect the brain through a variety of processes that are reflected as changes in brain structure and physiology. Although some biomarkers for these changes are well established, others are at different stages of development for use in clinical trials. One of the most challenging biomarkers to harmonize for clinical trials is cerebral blood flow (CBF). There are several magnetic resonance imaging (MRI) methods for quantifying CBF without the use of contrast agents, in particular arterial spin labeling (ASL) perfusion MRI, which has been increasingly applied in clinical trials. In this review, we present ASL MRI techniques, including strategies for implementation across multiple imaging centers, levels of confidence in assessing disease progression and treatment effects, and details of image analysis.

Amide proton transfer imaging in stroke.

Amide proton transfer (APT) imaging, a variant of chemical exchange saturation transfer MRI, has shown promise in detecting ischemic tissue acidosis following impaired aerobic metabolism in animal models and in human stroke patients due to the sensitivity of the amide proton exchange rate to changes in pH within the physiological range. Recent studies have demonstrated the possibility of using APT-MRI to detect acidosis of the ischemic penumbra, enabling the assessment of stroke severity and risk of progression, monitoring of treatment progress, and prognostication of clinical outcome. This paper reviews current APT imaging methods actively used in ischemic stroke research and explores the clinical aspects of ischemic stroke and future applications for these methods.

Time-encoded pseudo-continuous arterial spin labeling: Increasing SNR in ASL dynamic angiography.

PURPOSE: Dynamic angiography using arterial spin labeling (ASL) can provide detailed hemodynamic information. However, the long time-resolved readouts require small flip angles to preserve ASL signal for later timepoints, limiting SNR. By using time-encoded ASL to generate temporal information, the readout can be shortened. Here, the SNR improvements from using larger flip angles, made possible by the shorter readout, are quantitatively investigated. METHODS: The SNR of a conventional protocol with nine Look-Locker readouts and a 4 × $$ \times $$ 3 time-encoded protocol with three Look-Locker readouts (giving nine matched timepoints) were compared using simulations and in vivo data. Both protocols were compared using readouts with constant flip angles (CFAs) and variable flip angles (VFAs), where the VFA scheme was designed to produce a consistent ASL signal across readouts. Optimization of the background suppression to minimize physiological noise across readouts was also explored. RESULTS: The time-encoded protocol increased in vivo SNR by 103% and 96% when using CFAs or VFAs, respectively. Use of VFAs improved SNR compared with CFAs by 25% and 21% for the conventional and time-encoded protocols, respectively. The VFA scheme also removed signal discontinuities in the time-encoded data. Preliminary data suggest that optimizing the background suppression could improve in vivo SNR by a further 16%. CONCLUSIONS: Time encoding can be used to generate additional temporal information in ASL angiography. This enables the use of larger flip angles, which can double the SNR compared with a non-time-encoded protocol. The shortened time-encoded readout can also lead to improved background suppression, reducing physiological noise and further improving SNR.

ASL-BIDS, the brain imaging data structure extension for arterial spin labeling.

Arterial spin labeling (ASL) is a non-invasive MRI technique that allows for quantitative measurement of cerebral perfusion. Incomplete or inaccurate reporting of acquisition parameters complicates quantification, analysis, and sharing of ASL data, particularly for studies across multiple sites, platforms, and ASL methods. There is a strong need for standardization of ASL data storage, including acquisition metadata. Recently, ASL-BIDS, the BIDS extension for ASL, was developed and released in BIDS 1.5.0. This manuscript provides an overview of the development and design choices of this first ASL-BIDS extension, which is mainly aimed at clinical ASL applications. Discussed are the structure of the ASL data, focussing on storage order of the ASL time series and implementation of calibration approaches, unit scaling, ASL-related BIDS fields, and storage of the labeling plane information. Additionally, an overview of ASL-BIDS compatible conversion and ASL analysis software and ASL example datasets in BIDS format is provided. We anticipate that large-scale adoption of ASL-BIDS will improve the reproducibility of ASL research.

Potential Diagnostic Applications of Multi-Delay Arterial Spin Labeling in Early Alzheimer's Disease: The Chinese Imaging, Biomarkers, and Lifestyle Study.

Background: Cerebral blood flow (CBF) alterations are involved in the onset and progression of Alzheimer's disease (AD) and can be a potential biomarker. However, CBF measured by single-delay arterial spin labeling (ASL) for discrimination of mild cognitive impairment (MCI, an early stage of AD) was lack of accuracy. Multi-delay ASL can not only provide CBF quantification but also provide arterial transit time (ATT). Unfortunately, the technique was scarcely applied to the diagnosis of AD. Here, we detected the utility of ASL with 1-delay and 7-delay in ten regions of interest (ROIs) to identify MCI and AD. Materials and Methods: Pseudocontinuous ASL (pCASL) MRI was acquired on a 3T GE scanner in adults from the Chinese Imaging, Biomarkers, and Lifestyle (CIBL) Study of AD cohort, including 26 normal cognition (NC), 37 MCI, and 39 AD. Receiver operating characteristic (ROC) analyses with 1-delay and 7-delay ASL were performed for the identification of MCI and AD. The DeLong test was used to compare ROC curves. Results: For CBF of 1-delay or 7-delay the AUCs showed moderate-high performance for the AD/NC and AD/MCI comparisons (AUC = 0.83∼0.96) (p < 0.001). CBF of 1-delay performed poorly in MCI/NC comparison (AUC = 0.69) (p < 0.001), but CBF of 7-delay fared well with an AUC of 0.79 (p < 0.001). The combination of CBF and ATT of 7-delay showed higher performance for AD/NC, AD/MCI, and MCI/NC comparisons with AUCs of 0.96, 0.89, and 0.89, respectively (p < 0.001). Furthermore, combination of CBF, ATT, sex, age, APOE ε4, and education improved further the accuracy (p < 0.001). In subgroups analyses, there were no significant differences in CBF of 7-delay ASL for identification of AD or MCI between age subgroups (p > 0.05). Conclusion: The combination of CBF and ATT with 7-delay ASL showed higher performance for identification of MCI than CBF of 1-delay, when adding to sex, age, APOE ε4 carrier status, and education years, the diagnostic performance was further increased, presenting a potential imaging biomarker in early AD.

The ingredients for an antimicrobial mathematical modelling broth.

Mathematical modelling has made significant contributions to the optimization of the use of antimicrobial treatments. This article discusses the key processes that such mathematical modelling should attempt to capture. In particular, this article highlights that the response of the host immune system requires quantification, and this is illustrated with a novel model structure.

Review and consensus recommendations on clinical APT-weighted imaging approaches at 3T: Application to brain tumors.

Amide proton transfer-weighted (APTw) MR imaging shows promise as a biomarker of brain tumor status. Currently used APTw MRI pulse sequences and protocols vary substantially among different institutes, and there are no agreed-on standards in the imaging community. Therefore, the results acquired from different research centers are difficult to compare, which hampers uniform clinical application and interpretation. This paper reviews current clinical APTw imaging approaches and provides a rationale for optimized APTw brain tumor imaging at 3 T, including specific recommendations for pulse sequences, acquisition protocols, and data processing methods. We expect that these consensus recommendations will become the first broadly accepted guidelines for APTw imaging of brain tumors on 3 T MRI systems from different vendors. This will allow more medical centers to use the same or comparable APTw MRI techniques for the detection, characterization, and monitoring of brain tumors, enabling multi-center trials in larger patient cohorts and, ultimately, routine clinical use.

Quantitative chemical exchange saturation transfer imaging of nuclear overhauser effects in acute ischemic stroke.

PURPOSE: In chemical exchange saturation transfer imaging, saturation effects between - 2 to - 5 ppm (nuclear Overhauser effects, NOEs) have been shown to exhibit contrast in preclinical stroke models. Our previous work on NOEs in human stroke used an analysis model that combined NOEs and semisolid MT; however their combination might feasibly have reduced sensitivity to changes in NOEs. The aim of this study was to explore the information a 4-pool Bloch-McConnell model provides about the NOE contribution in ischemic stroke, contrasting that with an intentionally approximate 3-pool model. METHODS: MRI data from 12 patients presenting with ischemic stroke were retrospectively analyzed, as well as from six animals induced with an ischemic lesion. Two Bloch-McConnell models (4 pools, and a 3-pool approximation) were compared for their ability to distinguish pathological tissue in acute stroke. The association of NOEs with pH was also explored, using pH phantoms that mimic the intracellular environment of naïve mouse brain. RESULTS: The 4-pool measure of NOEs exhibited a different association with tissue outcome compared to 3-pool approximation in the ischemic core and in tissue that underwent delayed infarction. In the ischemic core, the 4-pool measure was elevated in patient white matter ( 1.20±0.20 ) and in animals ( 1.27±0.20 ). In the naïve brain pH phantoms, significant positive correlation between the NOE and pH was observed. CONCLUSION: Associations of NOEs with tissue pathology were found using the 4-pool metric that were not observed using the 3-pool approximation. The 4-pool model more adequately captured in vivo changes in NOEs and revealed trends depending on tissue pathology in stroke.

VCAM-1-targeted MRI Improves Detection of the Tumor-brain Interface.

PURPOSE: Despite optimal local therapy, tumor cell invasion into normal brain parenchyma frequently results in recurrence in patients with solid tumors. The aim of this study was to determine whether microvascular inflammation can be targeted to better delineate the tumor-brain interface through vascular cell adhesion molecule-1 (VCAM-1)-targeted MRI. EXPERIMENTAL DESIGN: Intracerebral xenograft rat models of MDA231Br-GFP (breast cancer) brain metastasis and U87MG (glioblastoma) were used to histologically examine the tumor-brain interface and to test the efficacy of VCAM-1-targeted MRI in detecting this region. Human biopsy samples of the brain metastasis and glioblastoma margins were examined for endothelial VCAM-1 expression. RESULTS: The interface between tumor and surrounding normal brain tissue exhibited elevated endothelial VCAM-1 expression and increased microvessel density. Tumor proliferation and stemness markers were also significantly upregulated at the tumor rim in the brain metastasis model. T2*-weighted MRI, following intravenous administration of VCAM-MPIO, highlighted the tumor-brain interface of both tumor models more extensively than gadolinium-DTPA-enhanced T1-weighted MRI. Sites of VCAM-MPIO binding, evident as hypointense signals on MR images, correlated spatially with endothelial VCAM-1 upregulation and bound VCAM-MPIO beads detected histologically. These findings were further validated in an orthotopic medulloblastoma model. Finally, the tumor-brain interface in human brain metastasis and glioblastoma samples was similarly characterized by microvascular inflammation, extending beyond the region detectable using conventional MRI. CONCLUSIONS: This work illustrates the potential of VCAM-1-targeted MRI for improved delineation of the tumor-brain interface in both primary and secondary brain tumors.

Validation of the estimation of the macrovascular contribution in multi-timepoint arterial spin labeling MRI using a 2-component kinetic model.

PURPOSE: In this paper, the ability to quantify cerebral blood flow by arterial spin labeling (ASL) was studied by investigating the separation of the macrovascular and tissue component using a 2-component model. Underlying assumptions of this model, especially the inclusion of dispersion in the analysis, were studied, as well as the temporal resolution of the ASL datasets. METHODS: Four different datasets were acquired: (1) 4D ASL angiography to characterize the macrovascular component and to study dispersion modeling within this component, (2) high temporal resolution ASL data to investigate the separation of the 2 components and the effect of dispersion modelling on this separation, (3) low temporal resolution ASL dataset to study the effect of the temporal resolution on the separation of the 2 components, and (4) low temporal resolution ASL data with vascular crushing. RESULTS: The model that included a gamma dispersion kernel had the best fit to the 4D ASL angiography. For the high temporal resolution ASL dataset, inclusion of the gamma dispersion kernel led to more signal included in the arterial blood volume map, which resulted in decreased cerebral blood flow values. The arterial blood volume and cerebral blood flow maps showed overall higher arterial blood volume values and lower cerebral blood flow values for the high temporal resolution dataset compared to the low temporal resolution dataset. CONCLUSION: Inclusion of a gamma dispersion kernel resulted in better fitting of the model to the data. The separation of the macrovascular and tissue component is affected by the inclusion of a gamma dispersion kernel and the temporal resolution of the ASL dataset.

Robust Multi-TE ASL-Based Blood-Brain Barrier Integrity Measurements.

Multiple echo-time arterial spin labelling (multi-TE ASL) offers estimation of blood-tissue exchange dynamics by probing the T2 relaxation of the labelled spins. In this study, we provide a recipe for robust assessment of exchange time (Texch) as a proxy measure of blood-brain barrier (BBB) integrity based on a test-retest analysis. This includes a novel scan protocol and an extension of the two-compartment model with an "intra-voxel transit time" (ITT) to address tissue transit effects. With the extended model, we intend to separate the underlying two distinct mechanisms of tissue transit and exchange. The performance of the extended model in comparison with the two-compartment model was evaluated in simulations. Multi-TE ASL sequence with two different bolus durations was used to acquire in vivo data (n = 10). Cerebral blood flow (CBF), arterial transit time (ATT) and Texch were fitted with the two models, and mean grey matter values were compared. Additionally, the extended model also extracted ITT parameter. The test-retest reliability of Texch was assessed for intra-session, inter-session and inter-visit pairs of measurements. Intra-class correlation coefficient (ICC) and within-subject coefficient of variance (CoV) for grey matter were computed to assess the precision of the method. Mean grey matter Texch and ITT values were found to be 227.9 ± 37.9 ms and 310.3 ± 52.9 ms, respectively. Texch estimated by the extended model was 32.6 ± 5.9% lower than the two-compartment model. A significant ICC was observed for all three measures of Texch reliability (P < 0.05). Texch intra-session CoV, inter-session CoV and inter-visit CoV were found to be 6.6%, 7.9%, and 8.4%, respectively. With the described improvements addressing intra-voxel transit effects, multi-TE ASL shows good reproducibility as a non-invasive measure of BBB permeability. These findings offer an encouraging step forward to apply this potential BBB permeability biomarker in clinical research.

Imputing Biomarker Status from RWE Datasets-A Comparative Study.

Missing data is a universal problem in analysing Real-World Evidence (RWE) datasets. In RWE datasets, there is a need to understand which features best correlate with clinical outcomes. In this context, the missing status of several biomarkers may appear as gaps in the dataset that hide meaningful values for analysis. Imputation methods are general strategies that replace missing values with plausible values. Using the Flatiron NSCLC dataset, including more than 35,000 subjects, we compare the imputation performance of six such methods on missing data: predictive mean matching, expectation-maximisation, factorial analysis, random forest, generative adversarial networks and multivariate imputations with tabular networks. We also conduct extensive synthetic data experiments with structural causal models. Statistical learning from incomplete datasets should select an appropriate imputation algorithm accounting for the nature of missingness, the impact of missing data, and the distribution shift induced by the imputation algorithm. For our synthetic data experiments, tabular networks had the best overall performance. Methods using neural networks are promising for complex datasets with non-linearities. However, conventional methods such as predictive mean matching work well for the Flatiron NSCLC biomarker dataset.

Adapting the UK Biobank Brain Imaging Protocol and Analysis Pipeline for the C-MORE Multi-Organ Study of COVID-19 Survivors.

SARS-CoV-2 infection has been shown to damage multiple organs, including the brain. Multiorgan MRI can provide further insight on the repercussions of COVID-19 on organ health but requires a balance between richness and quality of data acquisition and total scan duration. We adapted the UK Biobank brain MRI protocol to produce high-quality images while being suitable as part of a post-COVID-19 multiorgan MRI exam. The analysis pipeline, also adapted from UK Biobank, includes new imaging-derived phenotypes (IDPs) designed to assess the possible effects of COVID-19. A first application of the protocol and pipeline was performed in 51 COVID-19 patients post-hospital discharge and 25 controls participating in the Oxford C-MORE study. The protocol acquires high resolution T1, T2-FLAIR, diffusion weighted images, susceptibility weighted images, and arterial spin labelling data in 17 min. The automated imaging pipeline derives 1,575 IDPs, assessing brain anatomy (including olfactory bulb volume and intensity) and tissue perfusion, hyperintensities, diffusivity, and susceptibility. In the C-MORE data, IDPs related to atrophy, small vessel disease and olfactory bulbs were consistent with clinical radiology reports. Our exploratory analysis tentatively revealed some group differences between recovered COVID-19 patients and controls, across severity groups, but not across anosmia groups. Follow-up imaging in the C-MORE study is currently ongoing, and this protocol is now being used in other large-scale studies. The protocol, pipeline code and data are openly available and will further contribute to the understanding of the medium to long-term effects of COVID-19.