End-diastolic segmentation of intravascular ultrasound images enables more reproducible volumetric analysis of atheroma burden.

BACKGROUND: Volumetric intravascular ultrasound (IVUS) analysis is currently performed at a fixed frame interval, neglecting the cyclic changes in vessel dimensions occurring during the cardiac cycle that can affect the reproducibility of the results. Analysis of end-diastolic (ED) IVUS frames has been proposed to overcome this limitation. However, at present, there is lack of data to support its superiority over conventional IVUS. OBJECTIVES: The present study aims to compare the reproducibility of IVUS volumetric analysis performed at a fixed frame interval and at the ED frames, identified retrospectively using a novel deep-learning methodology. METHODS: IVUS data acquired from 97 vessels were included in the present study; each vessel was segmented at 1 mm interval (conventional approach) and at ED frame twice by an expert analyst. Reproducibility was tested for the following metrics; normalized lumen, vessel and total atheroma volume (TAV), and percent atheroma volume (PAV). RESULTS: The mean length of the analyzed segments was 50.0 ± 24.1 mm. ED analysis was more reproducible than the conventional analysis for the normalized lumen (mean difference: 0.76 ± 4.03 mm3 vs. 1.72 ± 11.37 mm3 ; p for the variance of differences ratio < 0.001), vessel (0.30 ± 1.79 mm3 vs. -0.47 ± 10.26 mm3 ; p < 0.001), TAV (-0.46 ± 4.03 mm3 vs. -2.19 ± 14.39 mm3 ; p < 0.001) and PAV (-0.12 ± 0.59% vs. -0.34 ± 1.34%; p < 0.001). Results were similar when the analysis focused on the 10 mm most diseased segment. The superiority of the ED approach was due to a more reproducible detection of the segment of interest and to the fact that it was not susceptible to the longitudinal motion of the IVUS probe and the cyclic changes in vessel dimensions during the cardiac cycle. CONCLUSIONS: ED IVUS segmentation enables more reproducible volumetric analysis and quantification of TAV and PAV that are established end points in longitudinal studies assessing the efficacy of novel pharmacotherapies. Therefore, it should be preferred over conventional IVUS analysis as its higher reproducibility is expected to have an impact on the sample size calculation for the primary end point.

The Epidemiology of COVID-19 Vaccine-Induced Myocarditis.

Background: In December 2019, the emergence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) led to the COVID-19 pandemic, with millions of deaths worldwide. Vaccine breakthroughs in late 2020 resulted in the authorization of COVID-19 vaccines. While these vaccines have demonstrated efficacy, evidence from vaccine safety monitoring systems around the globe supported a causal association between COVID-19 vaccines, in particular those using mRNA technology, i.e., Moderna's mRNA-1273 and Pfizer-BioNTech's BNT162b2, and myocarditis. Objective: This paper aims to investigate the epidemiology of mRNA COVID-19 vaccine-induced myocarditis, including age, ethnicity, and gender associations with these vaccines. It also discusses the immunopathophysiological mechanisms of mRNA COVID-19 vaccine-associated myocarditis and outlines principles of diagnosis, clinical presentation, and management. Methods: A literature review was conducted using PubMed, Embase, and Queen Mary University of London Library Services databases. Search terms included "myocarditis," "coronavirus disease 2019," "SARS-CoV-2," "mRNA Covid-19 vaccines," "Covid vaccine-associated myocarditis," "epidemiology," "potential mechanisms," "myocarditis diagnosis," and "myocarditis management." Results: While the definite mechanism of mRNA COVID-19 vaccine-associated myocarditis remains ambiguous, potential mechanisms include molecular mimicry of spike proteins and activation of the adaptive immune response with dysregulated cytokine expression. Male predominance in COVID-19 vaccine-induced myocarditis may be attributed to sex hormones, variations in inflammatory reactions, coagulation states based on gender, and female-specific protective factors. Moreover, an analysis of diagnostic and management strategies reveals a lack of consensus on acute patient presentation management. Conclusion: In contrast to viral infections that stand as the predominant etiological factor for myocarditis with more severe consequences, the mRNA COVID-19 vaccination elicits a mild and self-limiting manifestation of the condition. There is currently insufficient evidence to confirm the definite underlying mechanism of COVID-19 vaccine-associated myocarditis. Further research is needed to develop preventive and therapeutic solutions in this context.

Systematic Review of Total Hip Arthroplasty Outcomes in Cerebral Palsy Patients and a Comparative Analysis with Rheumatoid Arthritis.

Background: Total hip arthroplasty (THA) is considered a successful treatment option for patients with degenerative hip arthritis. However, in the setting of neuromuscular diseases, patients with cerebral palsy (CP) are considered high-risk due to instability, contractures, and altered muscle tone. The purpose of this systematic review is to analyse the data in the setting of THA in CP patients including indications, types of implants, revision rates, and patient-reported outcomes and compare these with those of a cohort requiring THA due to degenerative arthritis unrelated to neuromuscular disorders. Methods: PubMed, Embase, and Cochrane Library were searched from inception until June 10, 2023, to identify the relevant studies for THA on CP patients. The methodological quality of the studies was evaluated using the Newcastle-Ottawa Quality Assessment Scale (NOS). Results: The initial search generated 190 studies out of which 21 met the inclusion criteria. The most frequently reported indication was painful hip dislocation or subluxation due to failure of prior nonoperative treatment. The most frequently reported complication was dislocation affecting overall 7.5% (0-28%) of all patients, while other complications included periprosthetic fractures and heterotrophic ossification. The survival rates of primary THAs ranged from 85% to 100% at 5 years and from 73% to 86% at 10 years. Patients with CP who undergo total hip arthroplasty experience a greater overall rate of complications compared to patients with rheumatoid arthritis (RA) that undergo the same procedure. Conclusion: The current literature suggests that THA is a beneficial procedure for patients with CP through pain reduction and functional improvement. However, the increased rates of potential complications compared to the general population require careful consideration. We suggest that further investigations on the most appropriate time of procedure, implant type, and procedure are needed.

An automated software for real-time quantification of wall shear stress distribution in quantitative coronary angiography data.

BACKGROUND: Wall shear stress (WSS) estimated in 3D-quantitative coronary angiography (QCA) models appears to provide useful prognostic information and identifies high-risk patients and lesions. However, conventional computational fluid dynamics (CFD) analysis is cumbersome limiting its application in the clinical arena. This report introduces a user-friendly software that allows real-time WSS computation and examines its reproducibility and accuracy in assessing WSS distribution against conventional CFD analysis. METHODS: From a registry of 414 patients with borderline negative fractional flow reserve (0.81-0.85), 100 lesions were randomly selected. 3D-QCA and CFD analysis were performed using the conventional approach and the novel CAAS Workstation WSS software, and QCA as well as WSS estimations of the two approaches were compared. The reproducibility of the two methodologies was evaluated in a subgroup of 50 lesions. RESULTS: A good agreement was noted between the conventional approach and the novel software for 3D-QCA metrics (ICC range: 0.73-0-93) and maximum WSS at the lesion site (ICC: 0.88). Both methodologies had a high reproducibility in assessing lesion severity (ICC range: 0.83-0.97 for the conventional approach; 0.84-0.96 for the CAAS Workstation WSS software) and WSS distribution (ICC: 0.85-0.89 and 0.83-0.87, respectively). Simulation time was significantly shorter using the CAAS Workstation WSS software compared to the conventional approach (4.13 ± 0.59 min vs 23.14 ± 2.56 min, p < 0.001). CONCLUSION: CAAS Workstation WSS software is fast, reproducible, and accurate in assessing WSS distribution. Therefore, this software is expected to enable the broad use of WSS metrics in the clinical arena to identify high-risk lesions and vulnerable patients.

Machine learning for atherosclerotic tissue component classification in combined near-infrared spectroscopy intravascular ultrasound imaging: Validation against histology.

BACKGROUND AND AIMS: Accurate classification of plaque composition is essential for treatment planning. Intravascular ultrasound (IVUS) has limited efficacy in assessing tissue types, while near-infrared spectroscopy (NIRS) provides complementary information to IVUS but lacks depth information. The aim of this study is to train and assess the efficacy of a machine learning classifier for plaque component classification that relies on IVUS echogenicity and NIRS-signal, using histology as reference standard. METHODS: Matched NIRS-IVUS and histology images from 15 cadaveric human coronary arteries were analyzed (10 vessels were used for training and 5 for testing). Fibrous/pathological intimal thickening (F-PIT), early necrotic core (ENC), late necrotic core (LNC), and calcific tissue regions-of-interest were detected on histology and superimposed onto IVUS frames. The pixel intensities of these tissue types from the training set were used to train a J48 classifier for plaque characterization (ECHO-classification). To aid differentiation of F-PIT from necrotic cores, the NIRS-signal was used to classify non-calcific pixels outside yellow-spot regions as F-PIT (ECHO-NIRS classification). The performance of ECHO and ECHO-NIRS classifications were validated against histology. RESULTS: 262 matched frames were included in the analysis (162 constituted the training set and 100 the test set). The pixel intensities of F-PIT and ENC were similar and thus these two tissues could not be differentiated by echogenicity. With ENC and LNC as a single class, ECHO-classification showed good agreement with histology for detecting calcific and F-PIT tissues but had poor efficacy for necrotic cores (recall 0.59 and precision 0.29). Similar results were found when F-PIT and ENC were treated as a single class (recall and precision for LNC 0.78 and 0.33, respectively). ECHO-NIRS classification improved necrotic core and LNC detection, resulting in an increase of the overall accuracy of both models, from 81.4% to 91.8%, and from 87.9% to 94.7%, respectively. Comparable performance of the two models was seen in the test set where the overall accuracy of ECHO-NIRS classification was 95.0% and 95.5%, respectively. CONCLUSIONS: The combination of echogenicity with NIRS-signal appears capable of overcoming limitations of echogenicity, enabling more accurate characterization of plaque components.