The Impact of Bariatric Surgery on Coronary Microvascular Function Assessed Using Automated Quantitative Perfusion CMR.

BACKGROUND: Coronary microvascular function is impaired in patients with obesity, contributing to myocardial dysfunction and heart failure. Bariatric surgery decreases cardiovascular mortality and heart failure, but the mechanisms are unclear. OBJECTIVES: The authors studied the impact of bariatric surgery on coronary microvascular function in patients with obesity and its relationship with metabolic syndrome. METHODS: Fully automated quantitative perfusion cardiac magnetic resonance and metabolic markers were performed before and 6 months after bariatric surgery. RESULTS: Compared with age- and sex-matched healthy volunteers, 38 patients living with obesity had lower stress myocardial blood flow (MBF) (P = 0.001) and lower myocardial perfusion reserve (P < 0.001). A total of 27 participants underwent paired follow-up 6 months post-surgery. Metabolic abnormalities reduced significantly at follow-up including mean body mass index by 11 ± 3 kg/m2 (P < 0.001), glycated hemoglobin by 9 mmol/mol (Q1-Q3: 4-19 mmol/mol; P < 0.001), fasting insulin by 142 ± 131 pmol/L (P < 0.001), and hepatic fat fraction by 5.6% (2.6%-15.0%; P < 0.001). Stress MBF increased by 0.28 mL/g/min (-0.02 to 0.75 mL/g/min; P = 0.003) and myocardial perfusion reserve by 0.13 (-0.25 to 1.1; P = 0.036). The increase in stress MBF was lower in those with preoperative type 2 diabetes mellitus (0.1 mL/g/min [-0.09 to 0.46 mL/g/min] vs 0.75 mL/g/min [0.31-1.25 mL/g/min]; P = 0.002). Improvement in stress MBF was associated with reduction in fasting insulin (beta = -0.45 [95% CI: -0.05 to 0.90]; P = 0.03). CONCLUSIONS: Coronary microvascular function is impaired in patients with obesity, but can be improved significantly with bariatric surgery. Improvements in microvascular function are associated with improvements in insulin resistance but are attenuated in those with preoperative type 2 diabetes mellitus.

Diagnosis and prognosis of abnormal cardiac scintigraphy uptake suggestive of cardiac amyloidosis using artificial intelligence: a retrospective, international, multicentre, cross-tracer development and validation study.

BACKGROUND: The diagnosis of cardiac amyloidosis can be established non-invasively by scintigraphy using bone-avid tracers, but visual assessment is subjective and can lead to misdiagnosis. We aimed to develop and validate an artificial intelligence (AI) system for standardised and reliable screening of cardiac amyloidosis-suggestive uptake and assess its prognostic value, using a multinational database of 99mTc-scintigraphy data across multiple tracers and scanners. METHODS: In this retrospective, international, multicentre, cross-tracer development and validation study, 16 241 patients with 19 401 scans were included from nine centres: one hospital in Austria (consecutive recruitment Jan 4, 2010, to Aug 19, 2020), five hospital sites in London, UK (consecutive recruitment Oct 1, 2014, to Sept 29, 2022), two centres in China (selected scans from Jan 1, 2021, to Oct 31, 2022), and one centre in Italy (selected scans from Jan 1, 2011, to May 23, 2023). The dataset included all patients referred to whole-body 99mTc-scintigraphy with an anterior view and all 99mTc-labelled tracers currently used to identify cardiac amyloidosis-suggestive uptake. Exclusion criteria were image acquisition at less than 2 h (99mTc-3,3-diphosphono-1,2-propanodicarboxylic acid, 99mTc-hydroxymethylene diphosphonate, and 99mTc-methylene diphosphonate) or less than 1 h (99mTc-pyrophosphate) after tracer injection and if patients' imaging and clinical data could not be linked. Ground truth annotation was derived from centralised core-lab consensus reading of at least three independent experts (CN, TT-W, and JN). An AI system for detection of cardiac amyloidosis-associated high-grade cardiac tracer uptake was developed using data from one centre (Austria) and independently validated in the remaining centres. A multicase, multireader study and a medical algorithmic audit were conducted to assess clinician performance compared with AI and to evaluate and correct failure modes. The system's prognostic value in predicting mortality was tested in the consecutively recruited cohorts using cox proportional hazards models for each cohort individually and for the combined cohorts. FINDINGS: The prevalence of cases positive for cardiac amyloidosis-suggestive uptake was 142 (2%) of 9176 patients in the Austrian, 125 (2%) of 6763 patients in the UK, 63 (62%) of 102 patients in the Chinese, and 103 (52%) of 200 patients in the Italian cohorts. In the Austrian cohort, cross-validation performance showed an area under the curve (AUC) of 1·000 (95% CI 1·000-1·000). Independent validation yielded AUCs of 0·997 (0·993-0·999) for the UK, 0·925 (0·871-0·971) for the Chinese, and 1·000 (0·999-1·000) for the Italian cohorts. In the multicase multireader study, five physicians disagreed in 22 (11%) of 200 cases (Fleiss' kappa 0·89), with a mean AUC of 0·946 (95% CI 0·924-0·967), which was inferior to AI (AUC 0·997 [0·991-1·000], p=0·0040). The medical algorithmic audit demonstrated the system's robustness across demographic factors, tracers, scanners, and centres. The AI's predictions were independently prognostic for overall mortality (adjusted hazard ratio 1·44 [95% CI 1·19-1·74], p<0·0001). INTERPRETATION: AI-based screening of cardiac amyloidosis-suggestive uptake in patients undergoing scintigraphy was reliable, eliminated inter-rater variability, and portended prognostic value, with potential implications for identification, referral, and management pathways. FUNDING: Pfizer.

Phenotyping hypertrophic cardiomyopathy using cardiac diffusion magnetic resonance imaging: the relationship between microvascular dysfunction and microstructural changes.

AIMS: Microvascular dysfunction in hypertrophic cardiomyopathy (HCM) is predictive of clinical decline, however underlying mechanisms remain unclear. Cardiac diffusion tensor imaging (cDTI) allows in vivo characterization of myocardial microstructure by quantifying mean diffusivity (MD), fractional anisotropy (FA) of diffusion, and secondary eigenvector angle (E2A). In this cardiac magnetic resonance (CMR) study, we examine associations between perfusion and cDTI parameters to understand the sequence of pathophysiology and the interrelation between vascular function and underlying microstructure. METHODS AND RESULTS: Twenty HCM patients underwent 3.0T CMR which included: spin-echo cDTI, adenosine stress and rest perfusion mapping, cine-imaging, and late gadolinium enhancement (LGE). Ten controls underwent cDTI. Myocardial perfusion reserve (MPR), MD, FA, E2A, and wall thickness were calculated per segment and further divided into subendocardial (inner 50%) and subepicardial (outer 50%) regions. Segments with wall thickness ≤11 mm, MPR ≥2.2, and no visual LGE were classified as 'normal'. Compared to controls, 'normal' HCM segments had increased MD (1.61 ± 0.09 vs. 1.46 ± 0.07 × 10-3 mm2/s, P = 0.02), increased E2A (60 ± 9° vs. 38 ± 12°, P < 0.001), and decreased FA (0.29 ± 0.04 vs. 0.35 ± 0.02, P = 0.002). Across all HCM segments, subendocardial regions had higher MD and lower MPR than subepicardial (MDendo 1.61 ± 0.08 × 10-3 mm2/s vs. MDepi 1.56 ± 0.18 × 10-3 mm2/s, P = 0.003, MPRendo 1.85 ± 0.83, MPRepi 2.28 ± 0.87, P < 0.0001). CONCLUSION: In HCM patients, even in segments with normal wall thickness, normal perfusion, and no scar, diffusion is more isotropic than in controls, suggesting the presence of underlying cardiomyocyte disarray. Increased E2A suggests the myocardial sheetlets adopt hypercontracted angulation in systole. Increased MD, most notably in the subendocardium, is suggestive of regional remodelling which may explain the reduced subendocardial blood flow.

Automated Inline Analysis of Myocardial Perfusion MRI with Deep Learning.

PURPOSE: To develop a deep neural network-based computational workflow for inline myocardial perfusion analysis that automatically delineates the myocardium, which improves the clinical workflow and offers a "one-click" solution. MATERIALS AND METHODS: In this retrospective study, consecutive adenosine stress and rest perfusion scans were acquired from three hospitals between October 1, 2018 and February 27, 2019. The training and validation set included 1825 perfusion series from 1034 patients (mean age, 60.6 years ± 14.2 [standard deviation]). The independent test set included 200 scans from 105 patients (mean age, 59.1 years ± 12.5). A convolutional neural network (CNN) model was trained to segment the left ventricular cavity, myocardium, and right ventricle by processing an incoming time series of perfusion images. Model outputs were compared with manual ground truth for accuracy of segmentation and flow measures derived on a global and per-sector basis with t test performed for statistical significance. The trained models were integrated onto MR scanners for effective inference. RESULTS: The mean Dice ratio of automatic and manual segmentation was 0.93 ± 0.04. The CNN performed similarly to manual segmentation and flow measures for mean stress myocardial blood flow (MBF; 2.25 mL/min/g ± 0.59 vs 2.24 mL/min/g ± 0.59, P = .94) and mean rest MBF (1.08 mL/min/g ± 0.23 vs 1.07 mL/min/g ± 0.23, P = .83). The per-sector MBF values showed no difference between the CNN and manual assessment (P = .92). A central processing unit-based model inference on the MR scanner took less than 1 second for a typical perfusion scan of three slices. CONCLUSION: The described CNN was capable of cardiac perfusion mapping and integrated an automated inline implementation on the MR scanner, enabling one-click analysis and reporting in a manner comparable to manual assessment. Supplemental material is available for this article. © RSNA, 2020.

Suspended animation: the past, present and future of major cardiothoracic trauma.

About 50% of the trauma victims die at the scene mostly because of exsanguinating haemorrhage. Most trials of resuscitation fail in face of the ongoing bleeding. Ongoing research/studies to save these victims by inducing rapid hypothermia using cardiopulmonary bypass as an emergency initial measure along with delayed resuscitation show improved outcomes. A comprehensive review of this research and analysis of studies showed that rapid induction of hypothermia within 5 min of cardiac arrest is associated with better survival and improved neurological outcome. This led us to conclude that suspended animation is a lifesaving modality for the treatment of trauma victims, otherwise hurtling towards certain death. This should be integrated into regular clinical practice. The US Food and Drug Administration has given its approval for clinical trials on such an intervention.