BACKGROUND: Stress-transthoracic Doppler echocardiography (S-TDE) provides a noninvasive assessment of coronary flow parameters in the left anterior descending artery (LAD). However, the association between morphological characteristics and coronary flow changes after elective percutaneous coronary intervention (PCI) remains unclear. We aimed to evaluate the relationships between periprocedural coronary flow changes observed on S-TDE and lesion-specific plaque characteristics obtained by optical coherence tomography (OCT) in the interrogated vessels in patients with chronic coronary syndrome (CCS).
RESULTS: Patients with CCS who underwent pre- and post-PCI S-TDE and elective fractional flow reserve (FFR)-guided PCI under OCT guidance for de novo single LAD lesions were included. S-TDE-derived hyperemic diastolic peak flow velocity (hDPV) was used as a surrogate for coronary flow. Lesions were categorized into two groups based on the %hDPV increase or decrease. The baseline clinical, physiological, and OCT findings were compared between the groups. In total, 103 LAD lesions were studied in 103 patients. After PCI, hDPV significantly increased from 55.6 cm/s to 69.5 cm/s (P<0.01), with a median %hDPV increase of 27.2 (6.32-59.1) %, while %hDPV decreased in 20 (19.4%) patients. The FFR improved in all patients. On OCT, layered plaques were more frequently present in the culprit vessels in the %hDPV-decrease group than in the %hDPV-increase group (85.0% vs. 50.6%, P = 0.01). Multivariable logistic regression analysis showed that the presence of layered plaques and high pre-PCI hDPV were independent predictors of %hDPV decrease.
CONCLUSIONS: In patients who underwent successful uncomplicated elective PCI for de novo single LAD lesions, the presence of layered plaques was independently associated with hyperemic coronary flow decrease as assessed by S-TDE.

Purpose To clarify the predominant causative plaque constituent for periprocedural myocardial injury (PMI) following percutaneous coronary intervention: (a) erythrocyte-derived materials, indicated by a high plaque-to-myocardium signal intensity ratio (PMR) at coronary atherosclerosis T1-weighted characterization (CATCH) MRI, or (b) lipids, represented by a high maximum 4-mm lipid core burden index (maxLCBI4 mm) at near-infrared spectroscopy intravascular US (NIRS-IVUS). Materials and Methods This retrospective study included consecutive patients who underwent CATCH MRI before elective NIRS-IVUS-guided percutaneous coronary intervention at two facilities. PMI was defined as post-percutaneous coronary intervention troponin T values greater than five times the upper reference limit. Multivariable analysis was performed to identify predictors of PMI. Finally, the predictive capabilities of MRI, NIRS-IVUS, and their combination were compared. Results A total of 103 lesions from 103 patients (median age, 72 years [IQR, 64-78]; 78 male patients) were included. PMI occurred in 36 lesions. In multivariable analysis, PMR emerged as the strongest predictor (P = .001), whereas maxLCBI4 mm was not a significant predictor (P = .07). When PMR was excluded from the analysis, maxLCBI4 mm emerged as the sole independent predictor (P = .02). The combination of MRI and NIRS-IVUS yielded the largest area under the receiver operating curve (0.86 [95% CI: 0.64, 0.83]), surpassing that of NIRS-IVUS alone (0.75 [95% CI: 0.64, 0.83]; P = .02) or MRI alone (0.80 [95% CI: 0.68, 0.88]; P = .30). Conclusion Erythrocyte-derived materials in plaques, represented by a high PMR at CATCH MRI, were strongly associated with PMI independent of lipids. MRI may play a crucial role in predicting PMI by offering unique pathologic insights into plaques, distinct from those provided by NIRS. Keywords: Coronary Plaque, Periprocedural Myocardial Injury, MRI, Near-Infrared Spectroscopy Intravascular US Supplemental material is available for this article. © RSNA, 2024.

BACKGROUND: The Smoking paradox has generated inconsistent findings concerning the clinical prognosis of acute ST-segment elevation myocardial infarction (STEMI) patients, while providing limited insights into coronary anatomy and function which are crucial prognostic factors. Therefore, this study aimed to further investigate the existence of smoking paradox in coronary anatomy and function.
METHODS: This study divided STEMI patients into smokers and non-smokers. Quantitative coronary angiography, angiography‑derived microcirculatory resistance (AMR) and quantitative flow ratio (QFR) were utilized to analyze coronary anatomy and function. These parameters were compared using multivariable analysis and propensity score matching. The clinical outcomes were evaluated using Kaplan-Meier curve and Cox regression.
RESULTS: The study included 1258 patients, with 730 in non-smoker group and 528 in smoker group. Smokers were significantly younger, predominantly male, and had fewer comorbidities. Without adjusting for confounders, smokers exhibited larger lumen diameter [2.03(1.45-2.57) vs. 1.90(1.37-2.49), P = 0.033] and lower AMR [244(212-288) vs. 260(218-301), P = 0.006]. After matching and multivariate adjustment, smokers exhibited inversely smaller lumen diameter [1.97(1.38-2.50) vs. 2.15(1.63-2.60), P = 0.002] and higher incidence of coronary microvascular dysfunction [233(53.9%) vs. 190(43.6%), P = 0.002], but showed similar AMR and clinical outcomes compared to non-smokers. There was no difference in QFR between two groups.
CONCLUSIONS: Smoking among STEMI patients undergoing pPCI was associated with smaller lumen diameter and higher occurrence of coronary microvascular dysfunction, although it had no further impact on clinical prognosis. The smoking paradox observed in coronary anatomy or function may be explained by younger age, gender, and lower prevalence of comorbidities.

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In rats with unilateral nephrectomy and cardiac dysfunction, renal function deteriorates at an accelerated rate, as evidenced by increased proteinuria. Whether myocardial infarct-induced heart failure (HF) exacerbates renal injury in hypertensive rats with mild renal injury has not been reported. Rats underwent either coronary ligation or sham surgery. Thirty spontaneously hypertensive rats (SHRs) aged 8 weeks were randomly divided into two groups. Group 1 was the sham group, in which the rats underwent thoracotomy without ligation of the coronary artery. Group 2 underwent coronary artery ligation. The rats in group 2 underwent coronary artery ligation on week 0. The experiment lasted 12 weeks. Urine was collected in metabolic cages over a 24-h period. Urine was collected from the rats 2 days before the end of the experiment, and the ratio of urinary protein to urinary creatinine was measured in the clinical laboratory. All rats were examined by echocardiogram one day before the end of the experiment. On the last day of the experiment, blood was collected and sent to the laboratory for analysis. Hematoxylin-eosin (HE) and periodic acid-Schiff (PAS) staining were performed on heart and kidney sections. The ejection fraction in group 2 was lower than that in group 1 (P < 0.001). The urinary albumin to creatinine ratio in group 2 was greater than that in group 1 (P < 0.001). The urea and creatinine levels in group 1 were significantly lower than those in group 2 (P < 0.01). The levels of brain natriuretic peptide (BNP), neutrophil gelatinase-associated lipocalin (NGAL) and cystatin C were greater in the second group than in the first group (P < 0.05). The interleukin-1β (IL-1β) and interleukin-6 (IL-6) levels in group 2 were significantly greater than those in group 1 (P < 0.001). The malondialdehyde (MDA) levels in Group 2 were greater than those in Group 1 (P < 0.01). The glutathione peroxidase (GSH-Px) levels in Group 2 were lower than those in Group 1 (P < 0.05). The level of angiotensin II (AT-II) in group 1 was lower than that in group 2 (P < 0.001). Cardiac dysfunction secondary to myocardial infarction could induce cardiorenal interactions in SHRs. It could be interpreted by the activation of oxidative stress, changes in inflammation and alteration of renin-angiotensin-aldosterone system.

We illustrate the case of a 62-year-old man with a symptomatic anomalous right coronary artery from pulmonary artery (ARCAPA). Our patient had presented with dyspnea on exertion with electrocardiogram showing pronounced inferior Q waves and marked inferolateral ST-T wave changes. The patient had a nuclear stress test which showed inferior wall ischemia. Subsequently, the patient underwent coronary angiography which showed an ARCAPA. The patient underwent surgical repair with reimplantation of the right coronary artery to the ascending aorta which was tolerated well. Our case illustrates ARCAPA presenting late in adulthood with ischemic symptoms that was treated with corrective surgery.

The importance of 3D reconstruction of coronary arteries using multiple coronary angiography (CAG) images has been increasingly recognized in the field of cardiovascular disease management. This process relies on the camera matrix\'s optimization, needing correspondence info for identical point positions across two images. Therefore, an automatic method for determining correspondence between two CAG images is highly desirable. Despite this need, there is a paucity of research focusing on image matching in the CAG images. Additionally, standard deep learning image matching techniques often degrade due to unique features and noise in CAG images. This study aims to fill this gap by applying a deep learning-based image matching method specifically tailored for the CAG images. We have improved the structure of our point detector and redesigned loss function to better handle sparse labeling and indistinct local features specific to CAG images. Our method include changes to training loss and introduction of a multi-head descriptor structure leading to an approximate 6% improvement. We anticipate that our work will provide valuable insights into adapting techniques from general domains to more specialized ones like medical imaging and serve as an improved benchmark for future endeavors in X-ray image-based correspondence matching.

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BACKGROUND: Stent malapposition (SM) following percutaneous coronary intervention (PCI) for myocardial infarction continues to present significant clinical challenges. In recent years, machine learning (ML) models have demonstrated potential in disease risk stratification and predictive modeling.
OBJECTIVE: ML models based on optical coherence tomography (OCT) imaging, laboratory tests, and clinical characteristics can predict the occurrence of SM.
METHODS: We studied 337 patients from the Affiliated Hospital of Zunyi Medical University, China, who had PCI and coronary OCT from May to October 2023. We employed nested cross-validation to partition patients into training and test sets. We developed five ML models: XGBoost, LR, RF, SVM, and NB based on calcification features. Performance was assessed using ROC curves. Lasso regression selected features from 46 clinical and 21 OCT imaging features, which were optimized with the five ML algorithms.
RESULTS: In the prediction model based on calcification features, the XGBoost model and SVM model exhibited higher AUC values. Lasso regression identified five key features from clinical and imaging data. After incorporating selected features into the model for optimization, the AUC values of all algorithmic models showed significant improvements. The XGBoost model demonstrated the highest calibration accuracy. SHAP values revealed that the top five ranked features influencing the XGBoost model were calcification length, age, coronary dissection, lipid angle, and troponin.
CONCLUSIONS: ML models developed using plaque imaging features and clinical characteristics can predict the occurrence of SM. ML models based on clinical and imaging features exhibited better performance.