Hepatic steatosis modeling and MRI signal simulations for comparison of single- and dual-R2* models and estimation of fat fraction at 1.5T and 3T.

BACKGROUND AND OBJECTIVE: Magnetic resonance imaging (MRI) has emerged as a noninvasive clinical tool for assessment of hepatic steatosis. Multi-spectral fat-water MRI models, incorporating single or dual transverse relaxation decay rate(s) (R2*) have been proposed for accurate fat fraction (FF) estimation. However, it is still unclear whether single- or dual-R2* model accurately mimics in vivo signal decay for precise FF estimation and the impact of signal-to-noise ratio (SNR) on each model performance. Hence, this study aims to construct virtual steatosis models and synthesize MRI signals with different SNRs to systematically evaluate the accuracy of single- and dual-R2* models for FF and R2* estimations at 1.5T and 3.0T. METHODS: Realistic hepatic steatosis models encompassing clinical FF range (0-60 %) were created using morphological features of fat droplets (FDs) extracted from human liver biopsy samples. MRI signals were synthesized using Monte Carlo simulations for noise-free (SNRideal) and varying SNR conditions (5-100). Fat-water phantoms were scanned with different SNRs to validate simulation results. Fat water toolbox was used to calculate R2* and FF for both single- and dual-R2* models. The model accuracies in R2* and FF estimates were analyzed using linear regression, bias plot and heatmap analysis. RESULTS: The virtual steatosis model closely mimicked in vivo fat morphology and Monte Carlo simulation produced realistic MRI signals. For SNRideal and moderate-high SNRs, water R2* (R2*W) by dual-R2* and common R2* (R2*com) by single-R2* model showed an excellent agreement with slope close to unity (0.95-1.01) and R2 > 0.98 at both 1.5T and 3.0T. In simulations, the R2*com-FF and R2*W-FF relationships exhibited slopes similar to in vivo calibrations, confirming the accuracy of our virtual models. For SNRideal, fat R2* (R2*F) was similar to R2*W and dual-R2* model showed slightly higher accuracy in FF estimation. However, in the presence of noise, dual-R2* produced higher FF bias with decreasing SNR, while leading to only marginal improvement for high SNRs and in regions dominated by fat and water. In contrast, single-R2* model was robust and produced accurate FF estimations in simulations and phantom scans with clinical SNRs. CONCLUSION: Our study demonstrates the feasibility of creating virtual steatosis models and generating MRI signals that mimic in vivo morphology and signal behavior. The single-R2* model consistently produced lower FF bias for clinical SNRs across entire FF range compared to dual-R2* model, hence signifying that single-R2* model is optimal for assessing hepatic steatosis.

Assessment of whole-body and regional body fat using abdominal quantitative computed tomography in Chinese women and men.

BACKGROUND: Being overweight or obese has become a serious public health concern, and accurate assessment of body composition is particularly important. More precise indicators of body fat composition include visceral adipose tissue (VAT) mass and total body fat percentage (TBF%). Study objectives included examining the relationships between abdominal fat mass, measured by quantitative computed tomography (QCT), and the whole-body and regional fat masses, measured by dual energy X-ray absorptiometry (DXA), as well as to derive equations for the prediction of TBF% using data obtained from multiple QCT slices. METHODS: Whole-body and regional fat percentage were quantified using DXA in Chinese males (n = 68) and females (n = 71) between the ages of 24 and 88. All the participants also underwent abdominal QCT measurement, and their VAT mass and visceral fat volume (VFV) were assessed using QCT and DXA, respectively. RESULTS: DXA-derived TBF% closely correlated with QCT abdominal fat percentage (r = 0.89-0.93 in men and 0.76-0.88 in women). Stepwise regression showed that single-slice QCT data were the best predictors of DXA-derived TBF%, DXA android fat percentage and DXA gynoid fat percentage. Cross-validation analysis showed that TBF% and android fat percentage could be accurately predicted using QCT data in both sexes. There were close correlations between QCT-derived and DXA-derived VFV (r = 0.97 in men and 0.93 in women). CONCLUSION: Clinicians can assess the TBF% and android and gynoid fat percentages of Chinese women and men by analysing existing abdominal CT-derived data using the QCT technique.

Magnetic Resonance Imaging-Based Assessment of Pancreatic Fat Strongly Correlates With Histology-Based Assessment of Pancreas Composition.

OBJECTIVE: The aim of the study is to assess the relationship between magnetic resonance imaging (MRI)-based estimation of pancreatic fat and histology-based measurement of pancreatic composition. MATERIALS AND METHODS: In this retrospective study, MRI was used to noninvasively estimate pancreatic fat content in preoperative images from high-risk individuals and disease controls having normal pancreata. A deep learning algorithm was used to label 11 tissue components at micron resolution in subsequent pancreatectomy histology. A linear model was used to determine correlation between histologic tissue composition and MRI fat estimation. RESULTS: Twenty-seven patients (mean age 64.0 ± 12.0 years [standard deviation], 15 women) were evaluated. The fat content measured by MRI ranged from 0% to 36.9%. Intrapancreatic histologic tissue fat content ranged from 0.8% to 38.3%. MRI pancreatic fat estimation positively correlated with microanatomical composition of fat (r = 0.90, 0.83 to 0.95], P < 0.001); as well as with pancreatic cancer precursor ( r = 0.65, P < 0.001); and collagen ( r = 0.46, P < 0.001) content, and negatively correlated with pancreatic acinar ( r = -0.85, P < 0.001) content. CONCLUSIONS: Pancreatic fat content, measurable by MRI, correlates to acinar content, stromal content (fibrosis), and presence of neoplastic precursors of cancer.

Longitudinal MR-based proton-density fat fraction (PDFF) and T2* for the assessment of associations between bone marrow changes and myelotoxic chemotherapy.

OBJECTIVES: MR imaging-based proton density fat fraction (PDFF) and T2* imaging has shown to be useful for the evaluation of degenerative changes in the spine. Therefore, the aim of this study was to investigate the influence of myelotoxic chemotherapy on the PDFF and T2* of the thoracolumbar spine in comparison to changes in bone mineral density (BMD). METHODS: In this study, 19 patients were included who had received myelotoxic chemotherapy (MC) and had received a MR imaging scan of the thoracolumbar vertebrates before and after the MC. Every patient was matched for age, sex, and time between the MRI scans to two controls without MC. All patients underwent 3-T MR imaging including the thoracolumbar spine comprising chemical shift encoding-based water-fat imaging to extract PDFF and T2* maps. Moreover, trabecular BMD values were determined before and after chemotherapy. Longitudinal changes in PDFF and T2* were evaluated and compared to changes in BMD. RESULTS: Absolute mean differences of PDFF values between scans before and after MC were at 8.7% (p = 0.01) and at -0.5% (p = 0.57) in the control group, resulting in significantly higher changes in PDFF in patients with MC (p = 0.008). BMD and T2* values neither showed significant changes in patients with nor in those without myelotoxic chemotherapy (p = 0.15 and p = 0.47). There was an inverse, yet non-significant correlation between changes in PDFF and BMD found in patients with myelotoxic chemotherapy (r = -0.41, p = 0.12). CONCLUSION: Therefore, PDFF could be a useful non-invasive biomarker in order to detect changes in the bone marrow in patients receiving myelotoxic therapy. CLINICAL RELEVANCE STATEMENT: Using PDFF as a non-invasive biomarker for early bone marrow changes in oncologic patients undergoing myelotoxic treatment may help enable more targeted countermeasures at commencing states of bone marrow degradation and reduce risks of possible fragility fractures. KEY POINTS: Quantifying changes in bone marrow fat fraction, as well as T2* caused by myelotoxic pharmaceuticals using proton density fat fraction, is feasible. Proton density fat fraction could potentially be established as a non-invasive biomarker for early bone marrow changes in oncologic patients undergoing myelotoxic treatment.

High-frequency Quantitative Ultrasound Imaging of Human Rotator Cuff Muscles: Assessment of Repeatability and Reproducibility.

This study evaluated the repeatability and reproducibility of using high-frequency quantitative ultrasound (QUS) measurement of backscatter coefficient (BSC), grayscale analysis, and gray-level co-occurrence matrix (GLCM) textural analysis, to characterize human rotator cuff muscles. The effects of varying scanner settings across two different operators and two US systems were investigated in a healthy volunteer with normal rotator cuff muscles and a patient with chronic massive rotator cuff injury and substantial muscle degeneration. The results suggest that BSC is a promising method for assessing rotator cuff muscles in both control and pathological subjects, even when operators were free to adjust system settings (depth, level of focus, and time-gain compensation). Measurements were repeatable and reproducible across the different operators and ultrasound imaging platforms. In contrast, grayscale and GLCM analyses were found to be less reliable in this setting, with significant measurement variability. Overall, the repeatability and reproducibility measurements of BSC indicate its potential as a diagnostic tool for rotator cuff muscle evaluation.

Similarities and discrepancies between commercially available bioelectrical impedance analysis system and dual-energy X-ray absorptiometry for body composition assessment in 10-14-year-old children.

A variety of easy-to-use commercial bioelectrical impedance appliances are available. The aim of this study was to examine the usefulness of a commercially available body composition meter using bioelectrical impedance analysis (BIA) by comparing its measurement results with those obtained from dual-energy X-ray absorptiometry (DXA). The participants were 443 children aged from 10 to 14 years (226 boys and 217 girls). Fat mass, fat-free mass, lean body mass, percentage of body fat, and bone mineral contents were evaluated for all participants using BIA and DXA. The agreement in the anthropometric data obtained from both devices was analyzed using correlation analysis, intraclass correlation coefficient (ICC), Lin's concordance correlation coefficient (CCC), Bland-Altman plots, and ordinary least products regression analysis. Equivalence between both devices was tested by two one-sided t-test. All measured indicators showed strong linear correlations between the two measurement systems (r, 0.853-1.000). Fat mass, fat-free mass, and lean body mass showed absolute concordance (ICC, 0.902-0.972; Lin's CCC, 0.902-0.972). BIA overestimated bone mineral content (62.7-66.5%) and underestimated percentage of body fat (- 8.9 to - 0.8%), lean body mass (- 3.5 to - 1.8%), and body mass (- 0.8 to - 0.5%). For fat mass and fat-free mass, the overestimate or underestimate varied according to the sex and statistical analysis test. Bland-Altman analysis and ordinary least products analysis showed fixed bias and proportional bias in all indicators. Results according to quartiles of body mass index showed poor agreement for fat mass and percentage of body fat in both boys and girls in the lowest body mass index quartile. The present results revealed strong linear correlations between BIA and DXA, which confirmed the validity of the present single-frequency BIA-derived parameters. Our results suggest that BIA cannot provide the exact same values as DXA for some body composition parameters, but that performance is sufficient for longitudinal use within an individual for daily health management and monitoring.

Sub-calcaneal plantar fat pad assessment using dual-energy computed tomography: First experience in the diabetic foot.

BACKGROUND: This study assessed the use of dual-energy computed tomography (CT) to evaluate sub-calcaneal plantar fat pad changes in people with diabetic neuropathy. METHODS: Dual-energy CT scans of people with diabetic neuropathy and non-diabetic controls were retrospectively included. Average CT values (in Hounsfield Units) and thickness (in centimeters) of the sub-calcaneal plantar fat pad were measured in mono-energetic images at two energy levels (40 keV and 70 keV). The CT values measured in patients with diabetic neuropathy were correlated to barefoot plantar pressure measurements performed during walking in a clinical setting. FINDINGS: Forty-five dual-energy CT scans of people with diabetic neuropathy and eleven DECT scans of non-diabetic controls were included. Mean sub-calcaneal plantar fat pad thickness did not significantly differ between groups (diabetes group 1.20 ± 0.34 cm vs. control group 1.21 ± 0.28 cm, P = 0.585). CT values at both 40 keV (-34.7 ± 48.7 HU vs. -76.0 ± 42.8 HU, P = 0.013) and 70 keV (-11.2 ± 30.8 HU vs. -36.3 ± 27.2 HU, P = 0.017) were significantly higher in the diabetes group compared to controls, thus contained less fatty tissue. This elevation was most apparent in patients with Type 1 diabetes. CT values positively correlated with the mean peak plantar pressure. INTERPRETATION: Dual-energy CT was able to detect changes in the plantar fat pad of people with diabetic neuropathy.

Nutritional assessment by ultrasound of the rectus femoris and preperitoneal adipose tissue as predictors of hospitalized patient complications.

INTRODUCTION: Malnutrition and sarcopenia are associated with increased risk of adverse events and worse outcome in hospitalised patients. Ultrasonography is a useful tool in the assessment of body composition. PATIENTS AND METHODS: Twenty-three patients admitted to a hospital ward were recruited. Ultrasonographic variables of muscle tissue and adipose tissue were collected, as well as their variation during admission. These were correlated with anthropometric, clinical and analytical data. RESULTS: We observed a correlation of ultrasound measurements with length of hospitalisation (maximum preperitoneal fat -0.585, rectus femoris thickness - RF -0.539, RF area -0.540), frailty (RF -0.599) and dependency (RF 0.628). RF contractile capacity correlated with reported weekly exercise (0.642). CONCLUSION: RF and preperitoneal fat thickness correlate with the number of days of admission and functional capacity, emerging as prognostic variables.

Assessment of correlation between conventional anthropometric and imaging-derived measures of body fat composition: a systematic literature review and meta-analysis of observational studies.

BACKGROUND: In studies of the association of adiposity with disease risk, widely used anthropometric measures of adiposity (e.g. body-mass-index [BMI], waist circumference [WC], waist-hip ratio [WHR]) are simple and inexpensive to implement at scale. In contrast, imaging-based techniques (e.g. magnetic resonance imaging [MRI] and dual x-ray absorptiometry [DXA]) are expensive and labour intensive, but can provide more accurate quantification of body fat composition. There is, however, limited evidence about the relationship between conventional and imaging-derived measures of adiposity. METHODS: We searched Scopus and Web of Science for published reports in English of conventional versus imaging-derived measurements of adiposity. We identified 42 articles (MRI = 22; DXA = 20) that met selection criteria, involving 42,556 (MRI = 15,130; DXA = 27,426) individuals recruited from community or hospital settings. Study-specific correlation coefficients (r) were transformed using Fisher's Z transformation, and meta-analysed to yield weighted average correlations, both overall and by ancestry, sex and age, where feasible. Publication bias was investigated using funnel plots and Egger's test. RESULTS: Overall, 98% of participants were 18 + years old, 85% male and 95% White. BMI and WC were most strongly correlated with imaging-derived total abdominal (MRI-derived: r = 0.88-; DXA-derived: 0.50-0.86) and subcutaneous abdominal fat (MRI-derived: 0.83-0.85), but were less strongly correlated with visceral abdominal fat (MRI-derived: 0.76-0.79; DXA-derived: 0.80) and with DXA-derived %body fat (0.76). WHR was, at best, strongly correlated with imaging-derived total abdominal (MRI-derived: 0.60; DXA-derived: 0.13), and visceral abdominal fat (MRI-derived: 0.67; DXA-derived: 0.65), and moderately with subcutaneous abdominal (MRI-derived: 0.54), and with DXA-derived %body fat (0.58). All conventional adiposity measures were at best moderately correlated with hepatic fat (MRI-derived: 0.36-0.43). In general, correlations were stronger in women than in men, in Whites than in non-Whites, and in those aged 18 + years. CONCLUSIONS: In this meta-analysis, BMI and WC, but not WHR, were very strongly correlated with imaging-derived total and subcutaneous abdominal fat. By comparison, all three measures were moderately or strongly correlated with imaging-based visceral abdominal fat, with WC showing the greatest correlation. No anthropometric measure was substantially correlated with hepatic fat. Further larger studies are needed to compare these measures within the same study population, and to assess their relevance for disease risks in diverse populations.

Call for standardization in assessment and reporting of muscle and adipose change using computed tomography analysis in oncology: A scoping review.

Investigators are increasingly measuring skeletal muscle (SM) and adipose tissue (AT) change during cancer treatment to understand impact on patient outcomes. Recent meta-analyses have reported high heterogeneity in this literature, representing uncertainty in the resulting estimates. Using the setting of palliative-intent chemotherapy as an exemplar, we aimed to systematically summarize the sources of variability among studies evaluating SM and AT change during cancer treatment and propose standards for future studies to enable reliable meta-analysis. Studies that measured computed tomography-defined SM and/or AT change in adult patients during palliative-intent chemotherapy for solid tumours were included, with no date or geographical limiters. Of 2496 publications screened by abstract/title, 83 were reviewed in full text and 38 included for extraction, representing 34 unique cohorts across 8 tumour sites. The timing of baseline measurement was frequently defined as prior to treatment, while endpoint timing ranged from 6 weeks after treatment start to time of progression. Fewer than 50% specified the actual time interval between measurements. Measurement error was infrequently discussed (8/34). A single metric (cm2 /m2 , cm2 or %) was used to describe SM change in 18/34 cohorts, while multiple metrics were presented for 10/34 and no descriptive metrics for 6/34. AT change metrics and sex-specific reporting were available for 10/34 cohorts. Associations between SM loss and overall survival were evaluated in 24 publications, with classification of SM loss ranging from any loss to >14% loss over variable time intervals. Age and sex were the most common covariates, with disease response in 50% of models. Despite a wealth of data and effort, heterogeneity in study design, reporting and statistical analysis hinders evidence synthesis regarding the severity and outcomes of SM and AT change during cancer treatment. Proposed standards for study design include selection of homogenous cohorts, clear definition of baseline/endpoint timing and attention to measurement error. Standard reporting should include baseline SM and AT by sex, actual scan interval, SM and AT change using multiple metrics and visualization of the range of change observed. Reporting by sex would advance understanding of sexual dimorphism in SM and AT change. Evaluating the impact of tissue change on outcomes requires adjustment for relevant covariates and concurrent disease response. Adoption of these standards by researchers and publishers would alter the current paradigm to enable meta-analysis of future studies and move the field towards meaningful application of SM and AT change to clinical care.

Ultrasonographic Assessment of Body Fat Index for Prediction of Gestational Diabetes Mellitus and Neonatal Complications.

OBJECTIVES: To assess maternal pre-peritoneal fat and subcutaneous fat at 16-20 weeks gestation by ultrasound. Thus, calculate body fat index (BFI) and determine its cut-off value for prediction of gestational diabetes mellitus (GDM) and neonatal subcutaneous adiposity. METHODS: A cohort study was conducted in 200 pregnant women with singleton fetus during anomaly scan using BFI where they were screened for GDM at 24-28 weeks gestation by oral glucose tolerance test. Labour and neonatal outcomes were recorded. The receiver operating characteristic curve was used to determine the cut-offs for BFI, pre-peritoneal fat thickness, and subcutaneous fat thickness in order to predict GDM. RESULTS: The area under receiver operating characteristic curve for BFI was 0.967 (95% CI 0.932-0.987) with a sensitivity of 97.3%, specificity of 89.57%, negative predictive value of 99.3%, and diagnostic accuracy of 91% at a BFI cut-off of 0.88. The study analysis demonstrated BFI to be statistically superior to BMI > 22.9 kg/m2 for prediction of GDM. BFI > 0.88 was a risk factor for developing neonatal subcutaneous adiposity. CONCLUSIONS: BFI is a practical and convenient non-invasive screening tool to predict GDM and neonatal subcutaneous adiposity.

Medical imaging in the assessment of cardiovascular disease risk.

PURPOSE OF REVIEW: The prevalence of obesity has exponentially increased during the past years. The assessment of human adipose tissue distribution enables the identification of diverse ectopic adipose tissue depots, and helps to explain its relationship with cardiovascular health status. In this review, we summarize the current methods used in the assessment of human adipose tissue distribution, and we discuss the relationship between ectopic adipose tissue distribution and the risk of developing cardiovascular diseases and metabolic complications. RECENT FINDINGS: The reference instruments to assess human adipose tissue distribution nowadays are the computed tomography and the magnetic resonance imaging (MRI). Today, MRI is the preferred imaging technique and enables the measurement of variations in the distribution of body adipose tissue among different phenotypes and individuals. This technique has helped to better understand the relationship between different ectopic adipose tissue depots and its relationship with cardiometabolic health among individuals. SUMMARY: Although body composition can be assessed by simple techniques, these calculations can provide erroneous results and conclusions, requiring complex interpretations when diverse metabolic situations are concomitantly engaged. Contrarily, medical imaging techniques (e.g. MRI) enables to objectively and unbiasedly measure changes that may occur during longitudinal studies (e.g. pharmacological drug interventions).

Imaging-based assessment of fatty acid composition in human bone marrow adipose tissue at 7 T: Method comparison and in vivo feasibility.

PURPOSE: To demonstrate the feasibility and accuracy of chemical shift-encoded imaging of the fatty acid composition (FAC) of human bone marrow adipose tissue at 7 T, and to determine suitable image-acquisition parameters using simulations. METHODS: The noise performance of FAC estimation was investigated using simulations with a range of inter-echo time, and accuracy was assessed using a phantom experiment. Furthermore, one knee of 8 knee-healthy subjects (ages 35-54 years) was imaged, and the fractions of saturated fatty acids (SFA) and polyunsaturated fatty acids (PUFA) were mapped. Values were compared between reconstruction methods, and between anatomical regions. RESULTS: Based on simulations, ΔTE = 0.6 ms was chosen. The phantom experiment demonstrated high accuracy of especially SFA using a constrained reconstruction model (slope = 1.1, average bias = -0.2%). The lowest accuracy was seen for PUFA using a free model (slope = 2.0, average bias = 9.0%). For in vivo images, the constrained model resulted in lower intersubject variation compared with the free model (e.g., in the femoral shaft, the SFA percent-point range was within 1.0% [vs. 3.0%]). Furthermore, significant regional FAC differences were detected. For example, using the constrained approach, the femoral SFA in the medial condyle was lower compared with the shaft (median [range]: 27.9% [27.1%, 28.4%] vs. 32.5% [31.8%, 32.8%]). CONCLUSION: Bone marrow adipose tissue FAC quantification using chemical-shift encoding is feasible at 7 T. Both the noise performance and accuracy of the technique are superior using a constrained signal model.

Deep-Learning for Epicardial Adipose Tissue Assessment With Computed Tomography: Implications for Cardiovascular Risk Prediction.

BACKGROUND: Epicardial adipose tissue (EAT) volume is a marker of visceral obesity that can be measured in coronary computed tomography angiograms (CCTA). The clinical value of integrating this measurement in routine CCTA interpretation has not been documented. OBJECTIVES: This study sought to develop a deep-learning network for automated quantification of EAT volume from CCTA, test it in patients who are technically challenging, and validate its prognostic value in routine clinical care. METHODS: The deep-learning network was trained and validated to autosegment EAT volume in 3,720 CCTA scans from the ORFAN (Oxford Risk Factors and Noninvasive Imaging Study) cohort. The model was tested in patients with challenging anatomy and scan artifacts and applied to a longitudinal cohort of 253 patients post-cardiac surgery and 1,558 patients from the SCOT-HEART (Scottish Computed Tomography of the Heart) Trial, to investigate its prognostic value. RESULTS: External validation of the deep-learning network yielded a concordance correlation coefficient of 0.970 for machine vs human. EAT volume was associated with coronary artery disease (odds ratio [OR] per SD increase in EAT volume: 1.13 [95% CI: 1.04-1.30]; P = 0.01), and atrial fibrillation (OR: 1.25 [95% CI: 1.08-1.40]; P = 0.03), after correction for risk factors (including body mass index). EAT volume predicted all-cause mortality (HR per SD: 1.28 [95% CI: 1.10-1.37]; P = 0.02), myocardial infarction (HR: 1.26 [95% CI:1.09-1.38]; P = 0.001), and stroke (HR: 1.20 [95% CI: 1.09-1.38]; P = 0.02) independently of risk factors in SCOT-HEART (5-year follow-up). It also predicted in-hospital (HR: 2.67 [95% CI: 1.26-3.73]; P ≤ 0.01) and long-term post-cardiac surgery atrial fibrillation (7-year follow-up; HR: 2.14 [95% CI: 1.19-2.97]; P ≤ 0.01). CONCLUSIONS: Automated assessment of EAT volume is possible in CCTA, including in patients who are technically challenging; it forms a powerful marker of metabolically unhealthy visceral obesity, which could be used for cardiovascular risk stratification.

Perivascular fat attenuation index measured by coronary computed tomography angiography as a tool for assessment of ischaemia-causing lesions: a case report.

BACKGROUND: It can be difficult to diagnose coronary artery disease in patients with acute coronary syndrome if coronary angiography does not identify stenosis. Coronary inflammation, which can contribute to the pathogenesis of coronary artery disease and acute coronary syndrome, can be quantified using the perivascular fat attenuation index. Furthermore, the perivascular fat attenuation index is a marker for all-cause mortality, cardiac-related mortality and impaired global coronary flow reserve. CASE PRESENTATION: Here we report a case of a patient presenting with symptoms of acute coronary syndrome. The patient had hypokinesis of the lateral-posterior wall of the left ventricle, decreased myocardial perfusion in the posterior wall myocardium and elevated myocardial troponin-T and creatine phosphokinase levels. However, coronary computed tomography angiography did not identify arterial stenosis. The patient did have an increased perivascular fat attenuation index, indicating coronary inflammation. Moreover, the fat attenuation index was higher around the left circumflex artery than around the right coronary artery or left anterior descending artery. Intravascular ultrasonography identified an intramural haematoma, leading to a diagnosis of type 3 spontaneous coronary artery dissection in the left circumflex artery. CONCLUSIONS: Perivascular fat attenuation index may be a useful tool to help identify and localise disease-causing lesions, and to direct further testing to confirm a diagnosis of spontaneous coronary artery dissection in acute coronary syndrome patients without significant arterial stenosis.

The Modified Assessment Tool Based on Scapular Y-View for Global Fatty Infiltration in the Supraspinatus Muscle: Correlation, Predictive Performance, and Reliability Analyses.

BACKGROUND: The accurate evaluation of rotator cuff (RC) fatty degeneration after tears is critical for appropriate surgical decision making and prognosis. However, there is currently no reliable and practical tool to reflect the global fatty infiltration (Global-FI) throughout the 3-dimensional (3D) volumetric RC muscles. PURPOSE: (1) To determine the correlations between 2 modified assessment tools and the Global-FI and their predictive performances and reliabilities for Global-FI prediction, and (2) to compare these predictive parameters with those of the conventional tool using a single scapular Y-view slice. STUDY DESIGN: Cohort study (diagnosis); Level of evidence, 3. METHODS: A total of 49 patients with full-thickness RC tears scheduled to undergo arthroscopic repairs were included, and their surgical shoulders underwent 6-point Dixon magnetic resonance imaging preoperatively. The Global-FI was measured by calculating the 3D-volumetric fat fraction (FF) of the whole supraspinatus muscle through all acquired oblique sagittal slices. As a commonly used radiological landmark, the scapular Y-view was used to evaluate single-plane fatty infiltration (Y-FI) by calculating the FF in 1 slice, defined as the conventional assessment tool. Two modified assessment tools expand the analytic imaging by integrating the FFs from the scapular Y-view slice and its neighboring slices, which were calculated by averaging the FFs of these 3 slices (meanY3-FI) and accumulating local 3D-volumetric FFs from 3 slices (volY3-FI), respectively. The correlations between 3 assessment tools and the Global-FI were analyzed, and the predictive performance for Global-FI prediction using these tools was determined by goodness of fit and agreement. Moreover, the inter- and intraobserver reliabilities of these assessment tools were evaluated. Similar analyses were performed in the small-medium, large, or massive tear subgroups. RESULTS: The Y-FI was significantly higher than the Global-FI in all cases and tear size subgroups, while the 2 modified assessment tools (meanY3-FI and volY3-FI) did not significantly differ from the Global-FI. All assessment tools were significantly correlated with the Global-FI, but the meanY3-FI and volY3-FI showed stronger correlations than the Y-FI, which was also determined in different tear sizes. Moreover, the regression models of the meanY3-FI and volY3-FI showed superior goodness of fit to Y-FI in Global-FI prediction in all cases and subgroups, with larger coefficients of determination (R2) and smaller root mean square errors. The predicted Global-FI using the regression model of volY3-FI had the best agreement with the measured Global-FI, followed by the meanY3-FI, both showing smaller biases and standard deviation of the percentage difference between predicted- and measured Global-FI than the conventional Y-FI. In addition, the 2 modified assessment tools achieved better interobserver and intraobserver reliabilities than the conventional tool in all cases and subgroups. CONCLUSION: Two modified assessment tools (meanY3-FI and volY3-FI) were comparable with the Global-FI of the whole supraspinatus muscle, showing stronger correlations with the Global-FI and better predictive performances and reliabilities than the conventional tool (Y-FI). Moreover, the volY3-FI was slightly superior to meanY3-FI in the predictive performance and reliability.

Assessment of myocardial bridging and the pericoronary fat attenuation index on coronary computed tomography angiography: predicting coronary artery disease risk.

BACKGROUND: The fat attenuation index (FAI) is a radiological parameter that represents pericoronary adipose tissue (PCAT) inflammation, along with myocardial bridging (MB), which leads to pathological shear stress in the coronary vessels; both are associated with coronary atherosclerosis. In the present study, we assessed the predictive value of FAI values and MB parameters through coronary computed tomography angiography (CCTA) for predicting the risk of coronary atherosclerosis and vulnerable plaque in patients with MB. METHODS: We included 428 patients who underwent CCTA and were diagnosed with MB. FAI values, MB parameters, and high-risk coronary plaque (HRP) characteristics were recorded. The subjects were classified into two groups (A and B) according to the absence or presence of coronary plaque in the segment proximal to the MB. Group B was further divided into Groups B1 (HRP-positive) and B2 (HRP-negative) according to the HRP characteristic classification method. The differences among the groups were analysed. Multiple logistic regression analysis was performed to determine the independent correlation between FAI values and MB parameters and coronary atherosclerosis and vulnerable plaque risk. RESULTS: Compared to the subjects in Group A, those in Group B presented greater MB lengths, MB depths and muscle index values, more severe MB systolic stenosis and higher FAIlesion values (all P < 0.05). In multivariate logistic analysis, age (OR 1.076, P < 0.001), MB systolic stenosis (OR 1.102, P < 0.001) and FAIlesion values (OR 1.502, P < 0.001) were independent risk factors for the occurrence of coronary atherosclerosis. Compared to subjects in Group B2, those in Group B1 presented greater MB lengths and higher FAI values (both P < 0.05). However, only the FAIlesion value was an independent factor for predicting HRP (OR 1.641, P < 0.001). CONCLUSION: In patients with MB, MB systolic stenosis was associated with coronary plaque occurrence in the segment proximal to the MB. The FAI value was not only closely related to coronary atherosclerosis occurrence but also associated with plaque vulnerability. FAI values may provide more significant value in the prediction of coronary atherosclerosis than MB parameters in CCTA.