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Vasospastic angina (VSA) was first described in 1959 by Myron Prinzmetal as "the variant form of angina pectoris" on the sole basis of medical history and ECG. This condition is currently categorized as an endotype of myocardial infarction without coronary obstruction (Myocardial Infarction with Non-Obstructive Coronary Arteries (MINOCA)). Diagnostic criteria have been suggested by expert consensus. Provocative testing during coronary angiography is the gold standard test but is rarely used. The clinical presentation is often neglected, and the diagnosis is missed. However, VSA may lead to life-threatening arrhythmias. There are simple and effective therapies that are markedly different from those for the atherosclerotic coronary artery disease.

Le vasospasme coronarien (VC) a été décrit pour la première fois en 1959 par Myron Prinzmetal comme « la forme variante de l'angine de poitrine ¼ sur la seule base de l'anamnèse et de l'ECG. Le VC est actuellement classé comme un endotype de l'infarctus du myocarde sans obstruction coronaire (Myocardial Infarction with Non-Obstructive Coronary Arteries (MINOCA)). Des critères diagnostiques ont été proposés par des consensus d'experts. Le test de provocation lors de la coronarographie est l'examen de choix mais est rarement employé. La symptomatologie est souvent méconnue et le diagnostic n'est pas suffisamment évoqué. Pourtant, le VC peut conduire à des arythmies potentiellement fatales. Nous disposons de moyens thérapeutiques simples et efficaces, qui diffèrent sensiblement de ceux de la maladie coronarienne athérosclérotique.

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Approximately half of all coronary angiograms performed for angina do not show obstructive coronary artery disease, and many of these patients have coronary microvascular dysfunction (CMD). Invasive testing for CMD has increased with the advent and wider availability of thermodilution systems. We review CMD pathophysiology and invasive diagnostic testing using the Doppler and thermodilution systems. We report the results of a PubMed search of invasive microvascular testing and discuss limitations of current diagnostic algorithms in the diagnosis of CMD, including controversies regarding the optimal cutoff value for abnormal coronary flow reserve, use of microvascular resistance indices, and options for increasing sensitivity of testing.

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BACKGROUND: Despite a large body of evidence supporting the use of intravascular imaging (IVI) to guide percutaneous coronary intervention (PCI), concerns exist about its universal recommendation. The selective use of IVI to guide PCI of complex lesions and patients is perceived as a rational approach. METHODS: We performed a systematic review and meta-analysis of randomized controlled trials (RCTs). Embase, PubMed, and Cochrane were systematically searched for RCTs that compared IVI-guided PCI with angiography-guided PCI in high-risk patients and complex coronary anatomies. The primary outcome was major adverse cardiac events (MACE). A random-effects model was used to calculate the risk ratios (RRs) with 95 % confidence intervals (CIs). RESULTS: A total of 15 RCTs with 14,109 patients were included and followed for a weighted mean duration of 15.8 months. IVI-guided PCI was associated with a decrease in the risk of MACE (RR: 0.65; 95 % CI: 0.56-0.77; p < 0.01), target vessel failure (TVF) (RR: 0.66; 95 % CI: 0.52-0.84; p < 0.01), all-cause mortality (RR: 0.71; 95 % CI: 0.55-0.91; p < 0.01), cardiovascular mortality (RR: 0.47; 95 % CI: 0.34-0.65; p < 0.01), stent thrombosis (RR: 0.55; 95 % CI: 0.38-0.79; p < 0.01), myocardial infarction (RR: 0.81; 95 % CI: 0.67-0.98; p = 0.03), and repeated revascularizations (RR: 0.70; 95 % CI: 0.58-0.85; p < 0.01) compared with angiography. There was no significant difference in procedure-related complications (RR: 1.03; 95 % CI: 0.75-1.42; p = 0.84) between groups. CONCLUSIONS: Compared with angiographic guidance alone, IVI-guided PCI of complex lesions and high-risk patients significantly reduced all-cause and cardiovascular mortality, MACE, TVF, stent thrombosis, myocardial infarction, and repeat revascularization.

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Persistent truncus arteriosus (PTA) is a rare congenital heart malformation. A 4-year-old girl was diagnosed with type I PTA through echocardiography and confirmed by cardiac CTA.

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The advent of large language models (LLMs) marks a transformative leap in natural language processing, offering unprecedented potential in radiology, particularly in enhancing the accuracy and efficiency of coronary artery disease (CAD) diagnosis. While previous studies have explored the capabilities of specific LLMs like ChatGPT in cardiac imaging, a comprehensive evaluation comparing multiple LLMs in the context of CAD-RADS 2.0 has been lacking. This study addresses this gap by assessing the performance of various LLMs, including ChatGPT 4, ChatGPT 4o, Claude 3 Opus, Gemini 1.5 Pro, Mistral Large, Meta Llama 3 70B, and Perplexity Pro, in answering 30 multiple-choice questions derived from the CAD-RADS 2.0 guidelines. Our findings reveal that ChatGPT 4o achieved the highest accuracy at 100 %, with ChatGPT 4 and Claude 3 Opus closely following at 96.6 %. Other models, including Mistral Large, Perplexity Pro, Meta Llama 3 70B, and Gemini 1.5 Pro, also demonstrated commendable performance, though with slightly lower accuracy ranging from 90 % to 93.3 %. This study underscores the proficiency of current LLMs in understanding and applying CAD-RADS 2.0, suggesting their potential to significantly enhance radiological reporting and patient care in coronary artery disease. The variations in model performance highlight the need for further research, particularly in evaluating the visual diagnostic capabilities of LLMs-a critical component of radiology practice. This study provides a foundational comparison of LLMs in CAD-RADS 2.0 and sets the stage for future investigations into their broader applications in radiology, emphasizing the importance of integrating both text-based and visual knowledge for optimal clinical outcomes.

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BACKGROUND: This study aimed to investigate the effects of meticulous nursing care (MNC) for patients with coronary heart disease undergoing coronary CT angiography (CCTA). METHODS: We conducted a comprehensive search of the Cochrane Library, PubMed, EMBASE, China National Knowledge Infrastructure, and Wangfang databases from inception to January 1, 2024. Randomized clinical trials (RCTs) evaluating the effects of MNC for CCTA were included. Outcomes assessed included self-rating anxiety scale (SAS), self-rating depression scale (SDS), overall satisfaction of nursing care (OSNC), examination time (ET, min), radiation dose received (RDR, mSv), breathing control time (BCT), and heart rate control time (HRCT).The methodological quality of all included RCTs was evaluated using the Cochrane risk-of-bias tool, while statistical analysis was conducted using RevMan 5.4 software. RESULTS: Six eligible trials involving 1064 patients were included. The results of the meta-analysis showed significant differences in SAS (MD = -2.84, 95% CI [-3.31, -2.37], I2 = 0%, P < .001), SDS (MD = -2.55, 95% CI [-3.51, -1.58], I2 = 0%, P < .001), OSNC (OR = 3.13, 95% CI [1.59, 6.17], I2 = 23%, P = .001), BCT (MD = -23.43, 95% CI [-25.07, -21.80], I2 = 45%, P < .001), HRCT (MD = -20.08, 95% CI [-21.70, -18.46], I2 = 29%, P < .001), ET (MD = -2.31, 95% CI [-2.56, -2.06], I2 = 5%, P < .001), and RDR (MD = -2.11, 95% CI [-2.45, -1.77], I2 = 0%, P < .001). CONCLUSION: MNC may benefit for patients with coronary heart disease undergoing CCTA. Future studies are still needed to warrant the current findings.

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AIM: To study the clinical status and data of laboratory and instrumental examination of patients with non-obstructive ischemic heart disease (IHD) and multifocal atherosclerosis (MFA) included in the KAMMA registry. MATERIAL AND METHODS: The subanalysis included 1,893 IHD patients who underwent coronary angiography (CAG) and ultrasonic examination of peripheral arteries. Based on the CAG data, patients were divided into two groups: group 1, patients with obstructive coronary atherosclerosis (CA) (maximum stenosis ≥50% and/or history of percutaneous coronary intervention/coronary artery bypass grafting, n=1728; 91.3%) and group 2, patients with non-obstructive CA (maximum stenosis <50%, n = 165; 8.7%). RESULTS: A comparative analysis based on the degree of coronary obstruction in patients with verified IHD who were included in the KAMMA registry showed that 8.7% of them had coronary artery stenosis of less than 50%. The overwhelming majority of patients with non-obstructive CA had MFA affecting the brachiocephalic arteries in 94.3% and the lower extremity arteries in 40.2%. Among patients with non-obstructive IHD, women predominated; risk factors such as smoking and type 2 diabetes mellitus were less frequent in this group than in the obstructive IHD group. Patients with non-obstructive CA more frequently had a history of dyslipidemia; they had higher total cholesterol and non-high-density lipoprotein cholesterol; and they more frequently received moderate-intensity statin therapy than patients with obstructive CA (55.8% vs. 34.5%). Characteristic features of patients with non-obstructive CA were less severe IHD and less frequent history of acute coronary syndrome. However, the incidence of stroke, peripheral arterial thrombosis, and chronic arterial insufficiency of the lower extremities did not differ in groups 1 and 2, whereas the incidence of paroxysmal atrial fibrillation was higher in the non-obstructive IHD group. CONCLUSION: IHD patients without coronary obstruction also require assessment of the peripheral arterial status, as they may have advanced MFA, which should be taken into account when choosing the "aggressiveness" of therapy.

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BACKGROUND: In recent years, as deep learning has received widespread attention in the field of heart disease, some studies have explored the potential of deep learning based on coronary angiography (CAG) or coronary CT angiography (CCTA) images in detecting the extent of coronary artery stenosis. However, there is still a lack of a systematic understanding of its diagnostic accuracy, impeding the advancement of intelligent diagnosis of coronary artery stenosis. Therefore, we conducted this study to review the accuracy of image-based deep learning in detecting coronary artery stenosis. METHODS: We retrieved PubMed, Cochrane, Embase, and Web of Science until April 11, 2023. The risk of bias in the included studies was appraised using the QUADAS-2 tool. We extracted the accuracy of deep learning in the test set and performed subgroup analyses by binary and multiclass classification scenarios. We performed a subgroup analysis based on different degrees of stenosis and applied a double arcsine transformation to process the data. The analysis was done by using R. RESULTS: Our systematic review finally included 18 studies, involving 3568 patients and 13,362 images. In the included studies, deep learning models were constructed based on CAG and CCTA. In binary classification tasks, the accuracy for detecting > 25%, > 50% and > 70% degrees of stenosis at the vessel level were 0.81 (95% CI: 0.71-0.85), 0.73 (95% CI: 0.58-0.88) and 0.61 (95% CI: 0.56-0.65), respectively. In multiclass classification tasks, the accuracy for detecting 0-25%, 25-50%, 50-70%, and 70-100% degrees of stenosis at the vessel level were 0.78 (95% CI: 0.73-0.84), 0.86 (95% CI: 0.78-0.93), 0.83 (95% CI: 0.70-0.97), and 0.70 (95% CI: 0.42-0.98), respectively. CONCLUSIONS: Our study shows that deep learning models based on CAG and CCTA appear to be relatively accurate in diagnosing different degrees of coronary artery stenosis. However, for various degrees of stenosis, their accuracy still needs to be further improved.

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BACKGROUND: Despite the detailed imaging information provided by optical coherence tomography (OCT) during percutaneous coronary intervention (PCI), clinical benefits of this imaging technique in this setting remain uncertain. The aim of the OCCUPI trial was to compare the clinical benefits of OCT-guided versus angiography-guided PCI for complex lesions, assessed as the rate of major adverse cardiac events at 1 year. METHODS: This investigator-initiated, multicentre, randomised, open-label, superiority trial conducted at 20 hospitals in South Korea enrolled patients aged 19-85 years for whom PCI with drug-eluting stents was clinically indicated. After diagnostic angiography, clinical and angiographic findings were assessed to identify patients who met the criterion of having one or more complex lesions. Patients were randomly assigned 1:1 to receive PCI with OCT guidance (OCT-guidance group) or angiography guidance without OCT (angiography-guidance group). Web-response permuted-block randomisation (mixed blocks of four or six) was used at each participating site to allocate patients. The allocation sequence was computer-generated by an external programmer who was not involved in the rest of the trial. Outcome assessors were masked to group assignment. Patients, follow-up health-care providers, and data analysers were not masked. PCI was done according to conventional standard methods with everolimus-eluting stents. The primary endpoint was major adverse cardiac events (a composite of cardiac death, myocardial infarction, stent thrombosis, or ischaemia-driven target-vessel revascularisation), 1 year after PCI. The primary analysis was done in the intention-to-treat population. The margin used to establish superiority was 1·0 as a hazard ratio. This trial is registered with ClinicalTrials.gov (NCT03625908) and is completed. FINDINGS: Between Jan 9, 2019, and Sept 22, 2022, 1604 patients requiring PCI with drug-eluting stents for complex lesions were randomly assigned to receive either OCT-guided PCI (n=803) or angiography-guided PCI (n=801). 1290 (80%) of 1604 patients were male and 314 (20%) were female. The median age of patients at randomisation was 64 years (IQR 57-70). 1588 (99%) patients completed 1-year follow-up. The primary endpoint occurred in 37 (5%) of 803 patients in the OCT-guided PCI group and 59 (7%) of 801 patients in the angiography-guided PCI group (absolute difference -2·8% [95% CI -5·1 to -0·4]; hazard ratio 0·62 [95% CI 0·41 to 0·93]; p=0·023). Rates of stroke, bleeding events, and contrast-induced nephropathy were not significantly different across the two groups. INTERPRETATION: Among patients who required drug-eluting stent implantation for complex lesions, OCT guidance resulted in a lower incidence of major adverse cardiac events at 1 year compared with angiography guidance. These findings indicate the existence of a therapeutic benefit of OCT as an intravascular imaging technique for PCI guidance in patients with complex coronary lesions. FUNDING: Abbott Vascular and Cardiovascular Research Center. TRANSLATION: For the Korean translation of the abstract see Supplementary Materials section.

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Coronary artery segmentation is crucial for physicians to identify and locate plaques and stenosis using coronary computed tomography angiography (CCTA). However, the low contrast of CCTA images and the intricate structures of coronary arteries make this task challenging. To address these difficulties, we propose a novel model, the DFS-PDS network. This network comprises two subnetworks: a discriminative frequency segment subnetwork (DFS) and a position domain scales subnetwork (PDS). DFS introduced a gated mechanism within the feed-forward network, leveraging the Joint Photographic Experts Group (JPEG) compression algorithm, to discriminatively determine which low- and high-frequency information of the features should be preserved for latent image segmentation. The PDS aims to learn the shape prototype by predicting the radius. Additionally, our model has the consistent ability to guarantee region and boundary features through boundary consistency loss. During training, both subnetworks are optimized jointly, and in the testing stage, the coarse segmentation and radius prediction are produced. A coronary-geometric refinement method refines the segmentation masks by leveraging the shape prior to being reconstructed from the radius map, reducing the difficulty of segmenting coronary artery structures from complex surrounding structures. The DFS-PDS network is compared with state-of-the-art (SOTA) methods on two coronary artery datasets to evaluate its performance. The experimental results demonstrate that the DFS-PDS network performs better than the SOTA models, including Vnet, nnUnet, DDT, CS2-Net, Unetr, and CAS-Net, in terms of Dice or connectivity evaluation metrics.

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PURPOSE: As a non-invasive coronary functional examination, coronary computed tomography angiography (CCTA)-derived fractional flow reserve (CT-FFR) showed predictive value in several non-cardiac surgeries. This study aimed to evaluate the predictive value of CT-FFR in lung cancer surgery. METHOD: We retrospectively collected 227 patients from January 2017 to June 2022 and used machine learning-based CT-FFR to evaluate the stable coronary artery disease (CAD) patients undergoing lung cancer surgery. The major adverse cardiac event (MACE) was defined as perioperative myocardial injury (PMI), myocardial infarction, heart failure, atrial and ventricular arrhythmia with hemodynamic disorder, cardiogenic shock and cardiac death. The multivariate logistic regression analysis was performed to identify risk factors for MACE and PMI. The discriminative capacity, goodness-of-fit, and reclassification improvement of prediction model were determined before and after the addition of CT-FFR≤0.8. RESULTS: The incidence of MACE was 20.7 % and PMI was 15.9 %. CT-FFR significantly outperformed CCTA in terms of accuracy for predicting MACE (0.737 vs 0.524). In the multivariate regression analysis, CT-FFR≤0.8 was an independent risk factor for both MACE [OR=10.77 (4.637, 25.016), P<0.001] and PMI [OR=8.255 (3.372, 20.207), P<0.001]. Additionally, we found that the performance of prediction model for both MACE and PMI improved after the addition of CT-FFR. CONCLUSIONS: CT-FFR can be used to assess the risk of perioperative MACE and PMI in patients with stable CAD undergoing lung cancer surgery. It adds prognostic information in the cardiac evaluation of patients undergoing lung cancer surgery.

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Background CT-derived fractional flow reserve (CT-FFR) and dynamic CT myocardial perfusion imaging enhance the specificity of coronary CT angiography (CCTA) for ruling out coronary artery disease (CAD). However, evidence on comparative diagnostic value remains scarce. Purpose To compare the diagnostic accuracy of CCTA plus CT-FFR, CCTA plus CT perfusion, and sequential CCTA plus CT-FFR and CT perfusion for detecting hemodynamically relevant CAD with that of invasive angiography. Materials and Methods This secondary analysis of a prospective study included patients with chest pain referred for invasive coronary angiography at nine centers from July 2016 to September 2019. CCTA and CT perfusion were performed with third-generation dual-source CT scanners. CT-FFR was assessed on-site. Independent core laboratories analyzed CCTA alone, CCTA plus CT perfusion, CCTA plus CT-FFR, and a sequential approach involving CCTA plus CT-FFR and CT perfusion for the presence of hemodynamically relevant stenosis. Invasive coronary angiography with invasive fractional flow reserve was the reference standard. Diagnostic accuracy metrics and the area under the receiver operating characteristic curve (AUC) were compared with the Sign test and DeLong test. Results Of the 105 participants (mean age, 64 years ± 8 [SD]; 68 male), 49 (47%) had hemodynamically relevant stenoses at invasive coronary angiography. CCTA plus CT-FFR and CCTA plus CT perfusion showed no evidence of a difference for participant-based sensitivities (90% vs 90%, P > .99), specificities (77% vs 79%, P > .99) and vessel-based AUCs (0.84 [95% CI: 0.77, 0.91] vs 0.83 [95% CI: 0.75, 0.91], P = .90). Both had higher participant-based specificity than CCTA alone (54%, both P < .001) without evidence of a difference in sensitivity between CCTA (94%) and CCTA plus CT perfusion (P = .50) or CCTA plus CT-FFR (P = .63). The sequential approach combining CCTA plus CT-FFR with CT perfusion achieved higher participant-based specificity than CCTA plus CT-FFR (88% vs 77%, P = .03) without evidence of a difference in participant-based sensitivity (88% vs 90%, P > .99) and vessel-based AUC (0.85 [95% CI: 0.77, 0.93], P = .78). Compared with CCTA plus CT perfusion, the sequential approach showed no evidence of a difference in participant-based sensitivity (P > .99), specificity (P = .06), or vessel-based AUC (P = .54). Conclusion There was no evidence of a difference in diagnostic accuracy between CCTA plus CT-FFR and CCTA plus CT perfusion for detecting hemodynamically relevant CAD. A sequential approach combining CCTA plus CT-FFR with CT perfusion led to improved participant-based specificity with no evidence of a difference in sensitivity compared with CCTA plus CT-FFR. ClinicalTrials.gov registration no.: NCT02810795 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Sinitsyn in this issue.

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This study introduces a novel self-supervised learning method for single-frame subtraction and vessel segmentation in coronary angiography, addressing the scarcity of annotated medical samples in AI applications. We pretrain a U-Net model on a large dataset of unannotated coronary angiograms using an image-to-image translation framework, then fine-tune it on a limited set of manually annotated samples. The pretrained model excels at comprehensive single-frame subtraction, outperforming existing DSA methods. Fine-tuning with just 40 samples yields a Dice coefficient of 0.828 for vessel segmentation. On the public XCAD dataset, our model sets a new state-of-the-art benchmark with a Dice coefficient of 0.755, surpassing both unsupervised and supervised learning approaches. This method achieves robust single-frame subtraction and demonstrates that combining pretraining with minimal fine-tuning enables accurate coronary vessel segmentation with limited manual annotations. We successfully apply this approach to assist physicians in visualizing potential vascular stenosis sites during coronary angiography. Code, dataset, and a live demo will be available available at: https://github.com/newfyu/DeepSA .

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BACKGROUND: As the burden and distribution of calcification within chronic total occlusion (CTO) lesions can be diverse, its effect on CTO recanalization using multiple devices and techniques is debatable. This study investigated the role of calcification in wiring-based intraplaque tracking techniques for CTO recanalization. METHODS: A modified J-CTO score without counting calcification was used to analyze the procedures of 458 consecutive patients who underwent CTO interventions. Failed guidewire crossing and intraplaque tracking were considered procedural failures. Recanalization time details were analyzed for successful procedures. RESULTS: In patients with calcified CTO, the rate of procedural success only significantly declined to be lower than that of noncalcified CTO when the modified J-CTO score was ≥3 (77% vs. 94%, p = 0.008). In 422 patients with successful procedures, the presence of calcification was irrelevant to guidewire crossing time, but was accompanied with longer time from guidewire cross to final angiogram when the modified J-CTO score was 1-2 (53 ± 35 vs. 35 ± 17 [noncalcified] min, p < 0.001). Multivariate analyses showed that calcification was independently associated with procedural failure (odds ratio [OR] = 5.1, 95% confidence interval [CI] = 1.4-18.3) in lesions with modified J-CTO ≥3, and prolonged angioplasty/stenting procedures >60 min (OR = 4.8, 95% CI = 2.2-10.2) in successfully recanalized lesions with modified J-CTO score 1-2. CONCLUSIONS: Using intraplaque guidewire tracking, calcification was unfavorable for very difficult CTO lesions, and caused prolongation of angioplasty time for lesions with moderate complexity. This suggested that the role of calcification in the J-CTO score could be altered when different recanalization techniques were applied for CTO interventions.

Since several commonly used scoring systems for grading the difficulty of CTO-PCI are derived from multiple recanalization techniques and devices, their application should be fundamental. However, most CTO interventionists usually have their own favored recanalization techniques in the real-world. As one of the parameters of J-CTO score, the findings of the study suggest that the interpretation of calcification during CTO-PCI could be altered and should be cautious if different recanalization technique was used.

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