Stage-Dependent Biomarker Changes in Spinocerebellar Ataxia Type 3.

Spinocerebellar ataxia type 3/Machado-Joseph disease is the most common autosomal dominant ataxia. In view of the development of targeted therapies, knowledge of early biomarker changes is needed. We analyzed cross-sectional data of 292 spinocerebellar ataxia type 3/Machado-Joseph disease mutation carriers. Blood concentrations of mutant ATXN3 were high before and after ataxia onset, whereas neurofilament light deviated from normal 13.3 years before onset. Pons and cerebellar white matter volumes decreased and deviated from normal 2.2 years and 0.6 years before ataxia onset. We propose a staging model of spinocerebellar ataxia type 3/Machado-Joseph disease that includes a biomarker stage characterized by objective indicators of neurodegeneration before ataxia onset. ANN NEUROL 2024;95:400-406.

Different inflammatory signatures based on CSF biomarkers relate to preserved or diminished brain structure and cognition.

Neuroinflammation is a hallmark of Alzheimer's disease (AD) and both positive and negative associations of individual inflammation-related markers with brain structure and cognitive function have been described. We aimed to identify inflammatory signatures of CSF immune-related markers that relate to changes of brain structure and cognition across the clinical spectrum ranging from normal aging to AD. A panel of 16 inflammatory markers, Aß42/40 and p-tau181 were measured in CSF at baseline in the DZNE DELCODE cohort (n = 295); a longitudinal observational study focusing on at-risk stages of AD. Volumetric maps of gray and white matter (GM/WM; n = 261) and white matter hyperintensities (WMHs, n = 249) were derived from baseline MRIs. Cognitive decline (n = 204) and the rate of change in GM volume was measured in subjects with at least 3 visits (n = 175). A principal component analysis on the CSF markers revealed four inflammatory components (PCs). Of these, the first component PC1 (highly loading on sTyro3, sAXL, sTREM2, YKL-40, and C1q) was associated with older age and higher p-tau levels, but with less pathological Aß when controlling for p-tau. PC2 (highly loading on CRP, IL-18, complement factor F/H and C4) was related to male gender, higher body mass index and greater vascular risk. PC1 levels, adjusted for AD markers, were related to higher GM and WM volumes, less WMHs, better baseline memory, and to slower atrophy rates in AD-related areas and less cognitive decline. In contrast, PC2 related to less GM and WM volumes and worse memory at baseline. Similar inflammatory signatures and associations were identified in the independent F.ACE cohort. Our data suggest that there are beneficial and detrimental signatures of inflammatory CSF biomarkers. While higher levels of TAM receptors (sTyro/sAXL) or sTREM2 might reflect a protective glia response to degeneration related to phagocytic clearance, other markers might rather reflect proinflammatory states that have detrimental impact on brain integrity.

Random forests for the analysis of matched case-control studies.

BACKGROUND: Conditional logistic regression trees have been proposed as a flexible alternative to the standard method of conditional logistic regression for the analysis of matched case-control studies. While they allow to avoid the strict assumption of linearity and automatically incorporate interactions, conditional logistic regression trees may suffer from a relatively high variability. Further machine learning methods for the analysis of matched case-control studies are missing because conventional machine learning methods cannot handle the matched structure of the data. RESULTS: A random forest method for the analysis of matched case-control studies based on conditional logistic regression trees is proposed, which overcomes the issue of high variability. It provides an accurate estimation of exposure effects while being more flexible in the functional form of covariate effects. The efficacy of the method is illustrated in a simulation study and within an application to real-world data from a matched case-control study on the effect of regular participation in cervical cancer screening on the development of cervical cancer. CONCLUSIONS: The proposed random forest method is a promising add-on to the toolbox for the analysis of matched case-control studies and addresses the need for machine-learning methods in this field. It provides a more flexible approach compared to the standard method of conditional logistic regression, but also compared to conditional logistic regression trees. It allows for non-linearity and the automatic inclusion of interaction effects and is suitable both for exploratory and explanatory analyses.

Random Survival Forests With Competing Events: A Subdistribution-Based Imputation Approach.

Random survival forests (RSF) can be applied to many time-to-event research questions and are particularly useful in situations where the relationship between the independent variables and the event of interest is rather complex. However, in many clinical settings, the occurrence of the event of interest is affected by competing events, which means that a patient can experience an outcome other than the event of interest. Neglecting the competing event (i.e., regarding competing events as censoring) will typically result in biased estimates of the cumulative incidence function (CIF). A popular approach for competing events is Fine and Gray's subdistribution hazard model, which directly estimates the CIF by fitting a single-event model defined on a subdistribution timescale. Here, we integrate concepts from the subdistribution hazard modeling approach into the RSF. We develop several imputation strategies that use weights as in a discrete-time subdistribution hazard model to impute censoring times in cases where a competing event is observed. Our simulations show that the CIF is well estimated if the imputation already takes place outside the forest on the overall dataset. Especially in settings with a low rate of the event of interest or a high censoring rate, competing events must not be neglected, that is, treated as censoring. When applied to a real-world epidemiological dataset on chronic kidney disease, the imputation approach resulted in highly plausible predictor-response relationships and CIF estimates of renal events.

Pseudo-value regression trees.

This paper presents a semi-parametric modeling technique for estimating the survival function from a set of right-censored time-to-event data. Our method, named pseudo-value regression trees (PRT), is based on the pseudo-value regression framework, modeling individual-specific survival probabilities by computing pseudo-values and relating them to a set of covariates. The standard approach to pseudo-value regression is to fit a main-effects model using generalized estimating equations (GEE). PRT extend this approach by building a multivariate regression tree with pseudo-value outcome and by successively fitting a set of regularized additive models to the data in the nodes of the tree. Due to the combination of tree learning and additive modeling, PRT are able to perform variable selection and to identify relevant interactions between the covariates, thereby addressing several limitations of the standard GEE approach. In addition, PRT include time-dependent effects in the node-wise models. Interpretability of the PRT fits is ensured by controlling the tree depth. Based on the results of two simulation studies, we investigate the properties of the PRT method and compare it to several alternative modeling techniques. Furthermore, we illustrate PRT by analyzing survival in 3,652 patients enrolled for a randomized study on primary invasive breast cancer.

A tree-based modeling approach for matched case-control studies.

Conditional logistic regression (CLR) is the indisputable standard method for the analysis of matched case-control studies. However, CLR is strongly restricted with respect to the inclusion of non-linear effects and interactions of confounding variables. A novel tree-based modeling method is proposed which accounts for this issue and provides a flexible framework allowing for a more complex confounding structure. The proposed machine learning model is fitted within the framework of CLR and, therefore, allows to account for the matched strata in the data. A simulation study demonstrates the efficacy of the method. Furthermore, for illustration the method is applied to a matched case-control study on cervical cancer.

Early combination therapy of COVID-19 in high-risk patients.

PURPOSE: Prolonged shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been observed in immunocompromised hosts. Early monotherapy with direct-acting antivirals or monoclonal antibodies, as recommended by the international guidelines, does not prevent this with certainty. Dual therapies may therefore have a synergistic effect. METHODS: This retrospective, multicentre study compared treatment strategies for corona virus disease-19 (COVID-19) with combinations of nirmatrelvir/ritonavir, remdesivir, molnupiravir, and/ or mABs during the Omicron surge. Co-primary endpoints were prolonged viral shedding (≥ 106 copies/ml at day 21 after treatment initiation) and days with SARS-CoV-2 viral load ≥ 106 copies/ml. Therapeutic strategies and risk groups were compared using odds ratios and Fisher's tests or Kaplan-Meier analysis and long-rank tests. Multivariable regression analysis was performed. RESULTS: 144 patients were included with a median duration of SARS-CoV-2 viral load ≥ 106 copies/ml of 8.0 days (IQR 6.0-15.3). Underlying haematological malignancies (HM) (p = 0.03) and treatment initiation later than five days after diagnosis (p < 0.01) were significantly associated with longer viral shedding. Prolonged viral shedding was observed in 14.6% (n = 21/144), particularly in patients with underlying HM (OR 3.5; 95% CI 1.2-9.9; p = 0.02). Clinical courses of COVID-19 were mild to moderate with only few adverse effects potentially related to combination treatment. CONCLUSION: Early combination treatment of COVID-19 effectively prevented prolonged viral shedding in 85.6% of cases. Considering the rapid viral clearance rates and low toxicity, individualized dual therapy approaches may be beneficial in high-risk patients.

Microbiology of Facial Skin Infections-Strains, Susceptibility, and Therapeutic Consequences.

BACKGROUND: Skin and soft tissue infections (SSTIs) are common conditions with severe and potentially life-threatening outcomes. However, the use of antibiotics to treat these infections is controversial. PURPOSE: This study was to identify the microorganisms responsible for facial SSTIs, their antibiotic sensitivities, and the therapeutic outcomes of treatment. STUDY DESIGN, SETTING, AND SAMPLE: This was a retrospective, observational cohort study conducted at a single oral and maxillofacial plastic surgery department. The study sample included 103 patients with facial SSTIs (61 men, 42 women) with a mean age of 41.8 years (standard deviation ± 20.4). PREDICTOR/EXPOSURE/INDEPENDENT VARIABLES: The predictor variables included patient characteristics, antibiotic use before the clinic visit, and the infection's site and origin. MAIN OUTCOME VARIABLE(S): The primary outcome variable was the presence of antibiotic resistance in the bacterial strains isolated from the infections. METHODS: The data were collected by reviewing the results of microbiological swabs and patient records obtained from patients with facial SSTIs. Categorical variables were described using absolute and relative frequencies, and continuous variables were described using mean and standard deviation. The association between antibiotic resistance and the predictor variables was analyzed using Pearson's χ2 test and student's t test. RESULTS: The most common cause of SSTI was an infected epidermal cyst (60.1%). Of all the microorganisms identified, 80.6% were Gram-positive, and 55.8% showed antibiotic resistance against one or more of the evaluated antibiotics, including several backup antibiotics. There were no identified risk factors that significantly influenced the probability of resistance, and there were no adverse events observed. CONCLUSION: The results of this study suggest that surgery should be the primary approach for treating SSTIs, as antibiotic administration may not be effective due to the unknown susceptibility of the causative strains. Antibiotics should be reserved for severe cases and high-risk patients, and if deemed necessary for SSTI management, a broad-spectrum antibiotic should be administered to cover resistant organisms.

Subjective cognitive decline and stage 2 of Alzheimer disease in patients from memory centers.

INTRODUCTION: It is uncertain whether subjective cognitive decline (SCD) in individuals who seek medical help serves the identification of the initial symptomatic stage 2 of the Alzheimer's disease (AD) continuum. METHODS: Cross-sectional and longitudinal data from the multicenter, memory clinic-based DELCODE study. RESULTS: The SCD group showed slightly worse cognition as well as more subtle functional and behavioral symptoms than the control group (CO). SCD-A+ cases (39.3% of all SCD) showed greater hippocampal atrophy, lower cognitive and functional performance, and more behavioral symptoms than CO-A+. Amyloid concentration in the CSF had a greater effect on longitudinal cognitive decline in SCD than in the CO group. DISCUSSION: Our data suggests that SCD serves the identification of stage 2 of the AD continuum and that stage 2, operationalized as SCD-A+, is associated with subtle, but extended impact of AD pathology in terms of neurodegeneration, symptoms and clinical progression.

Association between benzodiazepine premedication and 30-day mortality rate: A propensity-score weighted analysis of the Peri-interventional Outcome Study in the Elderly (POSE).

BACKGROUND: Recent guidelines suggest that benzodiazepine premedication should be avoided in elderly patients, though with limited supporting evidence. OBJECTIVE: We conducted a secondary analysis of the POSE data to explore the association of premedication in patients aged 80 years or older with 30-day mortality. DESIGN: We used propensity score methods to perform a confounder-adjusted time-to-event analysis of the association between benzodiazepine premedication and 30-day mortality of the POSE study. SETTING: POSE was conducted as a European multicentre prospective cohort study. PATIENTS: Adults aged 80 years or older scheduled for surgical or nonsurgical intervention under anaesthesia. RESULTS: A total of 9497 patients were analysed. One thousand five hundred and twenty-one patients received benzodiazepine premedication, 7936 patients received no benzodiazepine premedication, 30 received clonidine and 10 had missing premedication data. Inverse propensity-score-weighted log-rank analysis did not provide unambiguous evidence for an association between benzodiazepine premedication and 30-day mortality; median [range] P = 0.048 [0.044 to 0.078], estimated 30-day mortality rates 3.21% and 4.45% in benzodiazepine-premedicated and nonbenzodiazepine-premedicated patients, respectively. Inverse propensity-score-weighted Cox regression resulted in a hazard ratio of 0.71 (95% CI 0.49 to 1.04), pointing at a possible reduction of 30-day mortality in the benzodiazepine premedication group. Sensitivity analyses, which constituted subgroup, matched-pairs, and subclassification analyses, resulted in similar findings. CONCLUSION: This secondary analysis of the POSE data did not find evidence for an unambiguous association between benzodiazepine premedication and 30-day mortality. Point estimates indicated a reduction of 30-day mortality in benzodiazepine-premedicated patients. The results presented here might be affected by unmeasured confounding factors, which could be addressed in a randomised trial. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03152734.

Dynamic Changes in the Endocannabinoid System during the Aging Process: Focus on the Middle-Age Crisis.

Endocannabinoid (eCB) signaling is markedly decreased in the hippocampus (Hip) of aged mice, and the genetic deletion of the cannabinoid receptor type 1 (CB1) leads to an early onset of cognitive decline and age-related histological changes in the brain. Thus, it is hypothesized that cognitive aging is modulated by eCB signaling through CB1. In the present study, we detailed the changes in the eCB system during the aging process using different complementary techniques in mouse brains of five different age groups, ranging from adolescence to old age. Our findings indicate that the eCB system is most strongly affected in middle-aged mice (between 9 and 12 months of age) in a brain region-specific manner. We show that 2-arachidonoylglycerol (2-AG) was prominently decreased in the Hip and moderately in caudate putamen (CPu), whereas anandamide (AEA) was decreased in both CPu and medial prefrontal cortex along with cingulate cortex (mPFC+Cg), starting from 6 months until 12 months. Consistent with the changes in 2-AG, the 2-AG synthesizing enzyme diacylglycerol lipase α (DAGLα) was also prominently decreased across the sub-regions of the Hip. Interestingly, we found a transient increase in CB1 immunoreactivity across the sub-regions of the Hip at 9 months, a plausible compensation for reduced 2-AG, which ultimately decreased strongly at 12 months. Furthermore, quantitative autoradiography of CB1 revealed that [3H]CP55940 binding markedly increased in the Hip at 9 months. However, unlike the protein levels, CB1 binding density did not drop strongly at 12 months and at old age. Furthermore, [3H]CP55940 binding was significantly increased in the lateral entorhinal cortex (LEnt), starting from the middle age until the old age. Altogether, our findings clearly indicate a middle-age crisis in the eCB system, which could be a potential time window for therapeutic interventions to abrogate the course of cognitive aging.

Subdistribution hazard models for competing risks in discrete time.

A popular modeling approach for competing risks analysis in longitudinal studies is the proportional subdistribution hazards model by Fine and Gray (1999. A proportional hazards model for the subdistribution of a competing risk. Journal of the American Statistical Association94, 496-509). This model is widely used for the analysis of continuous event times in clinical and epidemiological studies. However, it does not apply when event times are measured on a discrete time scale, which is a likely scenario when events occur between pairs of consecutive points in time (e.g., between two follow-up visits of an epidemiological study) and when the exact lengths of the continuous time spans are not known. To adapt the Fine and Gray approach to this situation, we propose a technique for modeling subdistribution hazards in discrete time. Our method, which results in consistent and asymptotically normal estimators of the model parameters, is based on a weighted ML estimation scheme for binary regression. We illustrate the modeling approach by an analysis of nosocomial pneumonia in patients treated in hospitals.

Challenges, facilitators and barriers to screening study participants in early disease stages-experience from the MACUSTAR study.

BACKGROUND: Recruiting asymptomatic participants with early disease stages into studies is challenging and only little is known about facilitators and barriers to screening and recruitment of study participants. Thus we assessed factors associated with screening rates in the MACUSTAR study, a multi-centre, low-interventional cohort study of early stages of age-related macular degeneration (AMD). METHODS: Screening rates per clinical site and per week were compiled and applicable recruitment factors were assigned to respective time periods. A generalized linear mixed-effects model including the most relevant recruitment factors identified via in-depth interviews with study personnel was fitted to the screening data. Only participants with intermediate AMD were considered. RESULTS: A total of 766 individual screenings within 87 weeks were available for analysis. The mean screening rate was 0.6 ± 0.9 screenings per week among all sites. The participation at investigator teleconferences (relative risk increase 1.466, 95% CI [1.018-2.112]), public holidays (relative risk decrease 0.466, 95% CI [0.367-0.591]) and reaching 80% of the site's recruitment target (relative risk decrease 0.699, 95% CI [0.367-0.591]) were associated with the number of screenings at an individual site level. CONCLUSIONS: Careful planning of screening activities is necessary when recruiting early disease stages in multi-centre observational or low-interventional studies. Conducting teleconferences with local investigators can increase screening rates. When planning recruitment, seasonal and saturation effects at clinical site level need to be taken into account. TRIAL REGISTRATION: ClinicalTrials.gov NCT03349801 . Registered on 22 November 2017.

Development of osteomyelitis following dental abscesses-influence of therapy and comorbidities.

OBJECTIVES: Bacterial osteomyelitis of the jaw is a severe disease potentially requiring extensive surgical treatment. We have evaluated the incidence rates of bacterial osteomyelitis following dental abscessation associated with primary or secondary tooth extraction. MATERIALS AND METHODS: A retrospective cohort study was designed and included patients with dental abscesses and surgical treatment including the extraction of focus teeth. Patients were either treated with primary removal during acute infection or secondary delayed extraction within an infection-free interval. The primary outcome variable was the occurrence of bacterial osteomyelitis following the abscess. Secondary outcomes were the influence of general disease, antibiotic therapy, and surgical technique. RESULTS: One hundred nine patients were enrolled in the study; 4 patients (3.7%) developed osteomyelitis. Primary tooth extraction was performed on all these patients (p = 0.017). Significant associations of diabetes (p = 0.001), the use of clindamycin (p = 0.025), and transcutaneous incision (p = 0.017) with the incidence of osteomyelitis were detected. CONCLUSIONS: More severe infections may be associated with a higher risk for the development of osteomyelitis following dental abscesses. A history of diabetes and clindamycin therapy might form further predisposing risk factors. Because of the low incidence and the small case number, our data need to be interpreted carefully. CLINICAL RELEVANCE: Osteomyelitis of the jaw is a rare but severe disease that may require extensive therapy and that impairs the quality of life of affected patients. The evaluation of risk factors to enable further reduction of incidence is therefore urgently required.

Diabetic Retinopathy Screening Using Smartphone-Based Fundus Imaging in India.

PURPOSE: Early detection and treatment can prevent irreversible blindness from diabetic retinopathy (DR), which is the leading cause of visual impairment among working-aged adults worldwide. Some 80% of affected persons live in low- and middle-income countries, yet lack of resources has largely prevented DR screening implementation in these world regions. Smartphone-based fundus imaging (SBFI) allows for low-cost mobile fundus examination using an adapter on a smartphone; however, key aspects such as image quality, diagnostic accuracy, and comparability of different approaches have not been systematically assessed to date. DESIGN: Evaluation of diagnostic technology. PARTICIPANTS: A total of 381 eyes of 193 patients with diabetes were recruited at outreach eye clinics in South India. METHODS: We compared 4 technically different approaches of SBFI (3 approaches based on direct and 1 approach based on indirect ophthalmoscopy) in terms of image quality and diagnostic accuracy for DR screening. MAIN OUTCOME MEASURES: Image quality (sharpness/focus, reflex artifacts, contrast, and illumination), field-of-view, examination time, and diagnostic accuracy for DR screening were analyzed against conventional fundus photography and clinical examination. RESULTS: Smartphone-based fundus imaging based on indirect ophthalmoscopy yielded the best image quality (P < 0.01), the largest field-of-view, and the longest examination time (111 vs. 68-86 seconds, P < 0.0001). Agreement with the reference standard (Cohen's kappa 0.868) and sensitivity/specificity to detect DR were highest for the indirect SBFI approach (0.79/0.99 for any DR and 1.0/1.0 for severe DR, 0.79/1.0 for diabetic maculopathy). CONCLUSIONS: Smartphone-based fundus imaging can meet DR screening requirements in an outreach setting; however, not all devices are suitable in terms of image quality and diagnostic accuracy. Smartphone-based fundus imaging might aid in alleviating the burden of DR screening in low- and middle-income countries, and these results will allow for a better selection of SBFI devices in field trials for DR screening.

Aflibercept for choroidal neovascularizations secondary to pseudoxanthoma elasticum: a prospective study.

PURPOSE: To evaluate the use of 2 mg intravitreal aflibercept for treatment of choroidal neovascularization (CNV) secondary to angioid streaks in patients with pseudoxanthoma elasticum (PXE). METHODS: In this 12-month prospective, open-label, uncontrolled, non-randomized interventional clinical trial, 15 PXE patients with CNV (mean age: 53 years, range 22-65) received one initial intravitreal injection of 2 mg aflibercept. Further injections were based on CNV activity at monthly examinations. The primary endpoint was change of best corrected visual acuity (BCVA) after 12 months. Secondary outcomes were change of central retinal thickness (CRT), leakage from CNV, retinal sensitivity, and vision-related quality of life. RESULTS: BCVA improved from 75.0 ± 10.8 (± SD, Snellen equivalent 20/32) to 79.3 ± 7.3 ETDRS letters (20/32) at final visit (p = 0.083). CRT decreased from 317 ± 81 to 279 ± 51 µm (p = 0.004). Retinal sensitivity on microperimetry changed from 17.8 ± 4.5 to 18.5 ± 4.3 dB (p = 0.103) and vision-related quality of life from a VQF-25 score of 80.7 ± 10.4 to 83.5 ± 14.5 (p = 0.554). The mean number of injections was 6.7 ± 2.6, and 5 participants had persistent or reactivated CNV activity at final visit. The observed adverse events were comparable with studies on aflibercept for other indications. CONCLUSION: The results of this study indicate that intravitreal aflibercept is a treatment option for CNV secondary to PXE.

Tree-based modeling of time-varying coefficients in discrete time-to-event models.

Hazard models are popular tools for the modeling of discrete time-to-event data. In particular two approaches for modeling time dependent effects are in common use. The more traditional one assumes a linear predictor with effects of explanatory variables being constant over time. The more flexible approach uses the class of semiparametric models that allow the effects of the explanatory variables to vary smoothly over time. The approach considered here is in between these modeling strategies. It assumes that the effects of the explanatory variables are piecewise constant. It allows, in particular, to evaluate at which time points the effect strength changes and is able to approximate quite complex variations of the change of effects in a simple way. A tree-based method is proposed for modeling the piecewise constant time-varying coefficients, which is embedded into the framework of varying-coefficient models. One important feature of the approach is that it automatically selects the relevant explanatory variables and no separate variable selection procedure is needed. The properties of the method are investigated in several simulation studies and its usefulness is demonstrated by considering two real-world applications.

In vivo assessment of cold stimulation effects on the fat fraction of brown adipose tissue using DIXON MRI.

PURPOSE: To evaluate the volume and changes of human brown adipose tissue (BAT) in vivo following exposure to cold using magnetic resonance imaging (MRI). MATERIALS AND METHODS: The clavicular region of 10 healthy volunteers was examined with a 3T MRI system. One volunteer participated twice. A cooling vest that was circulated with temperature-controlled water was used to expose each volunteer to a cold environment. Three different water temperature phases were employed: baseline (23°C, 20 min), cooling (12°C, 90 min), and a final warming phase (37°C, 30 min). Temperatures of the water in the circuit, of the body, and at the back skin of the volunteers were monitored with fiberoptic temperature probes. Applying the 2-point DIXON pulse sequence every 5 minutes, fat fraction (FF) maps were determined and evaluated over time to distinguish between brown and white adipose tissue. RESULTS: Temperature measurements showed a decrease of 3.8 ± 1.0°C of the back skin temperature, while the body temperature stayed constant at 37.2 ± 0.9°C. Focusing on the two interscapular BAT depots, a mean FF decrease of -2.9 ± 2.0%/h (P < 0.001) was detected during cold stimulation in a mean absolute volume of 1.31 ± 1.43 ml. Also, a correlation of FF decrease to back skin temperature decrease was observed in all volunteers (correlation coefficients: |r| = [0.51; 0.99]). CONCLUSION: We found that FF decreases in BAT begin immediately with mild cooling of the body and continue during long-time cooling. LEVEL OF EVIDENCE: 2 J. Magn. Reson. Imaging 2017;45:369-380.