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Abstract Because there is a lack of comparative studies assessing drug-coated balloon (DCB) and drug-eluting stent (DES) outcomes with respect to intraluminal (IL) and subintimal (SI) approaches in femoropopliteal (FP) total occlusive lesions, we compared the outcomes between DCB (including bailout stenting) and DES treatments for this lesion. A total of 487 limbs (434 patients) were divided into the IL (n = 344, DCB: n = 268, DES: n = 76) and SI (n = 143, DCB: n = 83, DES: n = 60) approach groups. The primary outcome was a major adverse limb event (MALE), defined as above-ankle amputation or repeat revascularization of the index limb. Secondary outcomes included clinically driven target lesion revascularization (TLR), loss of clinical patency, and all-cause death. After adjustment, in each IL and SI approach, the 2-year rates of MALE (p = 0.180 and p = 0.236, respectively), TLR, loss of clinical patency, and all-cause death were similar between the DCB and DES groups. In the DCB and DES groups, both primary and secondary outcomes were similar between the IL and SI approaches. DCB and DES strategies for patients presenting with FP total occlusive lesions demonstrated similar outcomes regardless of the IL or SI approach. Clinical Trial Registration: NCT02748226.

Background Coronary angiography is fundamental for the diagnosis and treatment of coronary artery disease. Manual quantitative coronary angiography (QCA) is accurate and reproducible; however, it is time-consuming and labor-intensive. However, recent advancements in artificial intelligence (AI) have enabled automated and rapid analysis of medical images, addressing the need for real-time quantitative coronary analysis. Aims This study aimed to evaluate the accuracy of AI-based QCA (AI-QCA) compared with that via manual QCA and clinician acceptance. Methods This retrospective, single-center study was conducted in two phases. Phase 1 was a pilot study comparing AI-QCA with manual QCA and visual estimation. It involved 15 patients who underwent coronary angiography at Seoul National University Bundang Hospital between September 2011 and July 2021. Phase 2 included a larger cohort of 762 patients, with 1002 coronary angiograms analyzed between May 2020 and April 2021. Results In phase 1, AI-QCA and manual QCA consistency varied among the observers, with AI-QCA showing superior consistency compared with visual estimation. However, a strong correlation between AI-QCA and manual-QCA was found in phase 2. AI-QCA accurately identified and quantitatively analyzed multiple lesions in the major vessels, providing results comparable with those of manual QCA. Conclusions AI-QCA demonstrated high concordance with manual QCA, offering real-time analysis and reduced workload. Therefore, AI-QCA has the potential to be a valuable tool for diagnosing and treating coronary artery disease, necessitating further studies for clinical validation.

Abstract Electrocardiogram (ECG) changes after primary percutaneous coronary intervention (PCI) in ST-segment elevation myocardial infarction (STEMI) patients are associated with prognosis. This study investigated the feasibility of predicting left ventricular (LV) dysfunction in STEMI patients using an artificial intelligence (AI)-enabled ECG algorithm developed to diagnose STEMI. Serial ECGs from 637 STEMI patients were analyzed with the AI algorithm, which quantified the probability of STEMI at various time points. The time points included pre-PCI, immediately post-PCI, 6 h post-PCI, 24 h post-PCI, at discharge, and one-month post-PCI. The prevalence of LV dysfunction was significantly associated with the AI-derived probability index. A high probability index was an independent predictor of LV dysfunction, with higher cardiac death and heart failure hospitalization rates observed in patients with higher indices. The study demonstrates that the AI-enabled ECG index effectively quantifies ECG changes post-PCI and serves as a digital biomarker capable of predicting post-STEMI LV dysfunction, heart failure, and mortality. These findings suggest that AI-enabled ECG analysis can be a valuable tool in the early identification of high-risk patients, enabling timely and targeted interventions to improve clinical outcomes in STEMI patients.

Background Clopidogrel monotherapy improved clinical outcomes compared with aspirin monotherapy during a chronic maintenance period in patients who underwent coronary stenting in the HOST‐EXAM (Harmonizing Optimal Strategy for Treatment of Coronary Artery Stenosis–Extended Antiplatelet Monotherapy) trial. However, it is uncertain whether the beneficial effect of clopidogrel over aspirin is different according to the renal function. Methods and Results We conducted a post hoc analysis of the HOST‐EXAM trial. Chronic kidney disease (CKD) was defined as baseline estimated glomerular filtration rate

Abstract Hypertension is the leading cause of morbidity and mortality worldwide. Hypertension mostly accompanies no symptoms, and therefore blood pressure (BP) measurement is the only way for early recognition and timely treatment. Methods for BP measurement have a long history of development and improvement. Invasive method via arterial cannulation was first proven possible in the 1800’s. Subsequent scientific progress led to the development of the auscultatory method, also known as Korotkoff’ sound, and the oscillometric method, which enabled clinically available BP measurement. However, hypertension management status is still poor. Globally, less than half of adults are aware of their hypertension diagnosis, and only one-third of them being treated are under control. Novel methods are actively investigated thanks to technological advances such as sensors and machine learning in addition to the clinical needs for easier and more convenient BP measurement. Each method adopts different technologies with its own specific advantages and disadvantages. Promises of novel methods include comprehensive information on out-of-office BP capturing dynamic short-term and long-term fluctuations. However, there are still pitfalls such as the need for regular calibration since most novel methods capture relative BP changes rather than an absolute value. In addition, there is growing concern on their accuracy and precision as conventional validation protocols are inappropriate for cuffless continuous methods. In this article, we provide a comprehensive overview of the past and present of BP measurement methods. Novel and emerging technologies are also introduced with respect to their potential applications and limitations. Graphical Abstract

Abstract Mine operational safety is an important aspect of maintaining the operational continuity of a mining area. In this study, we used the InSAR time series to analyze land surface changes using the ICOPS (improved combined scatterers with optimized point scatters) method. This ICOPS method combines persistent scatterers (PS) with distributed scatterers (DS) to increase surface deformation analysis’s spatial coverage and quality. One of the improvements of this study is the use of machine learning in postprocessing, based on convolutional neural networks, to increase the reliability of results. This study used data from the Sentinel-1 SAR C-band satellite during the 2016–2022 observation period at the Musan mine, North Korea. In the InSAR surface deformation time analysis, the maximum average rate of land subsidence was approximately > 15.00 cm per year, with total surface deformation of 170 cm and 70 cm for the eastern dumping area and the western dumping area, respectively. Analyzing the mechanism of land surface changes also involved evaluating the geological conditions in the Musan mining area. Our research findings show that combining machine learning and statistical methods has great potential to enhance the understanding of mine surface deformation.

For change detection in synthetic aperture radar (SAR) imagery, amplitude change detection (ACD) and coherent change detection (CCD) are widely employed. However, time-series SAR data often contain noise and variability introduced by system and environmental factors, requiring mitigation. Additionally, the stability of SAR signals is preserved when calibration accounts for temporal and environmental variations. Although ACD and CCD techniques can detect changes, spatial variability outside the primary target area introduces complexity into the analysis. This study presents a robust change detection methodology designed to identify urban changes using KOMPSAT-5 time-series data. A comprehensive preprocessing framework—including coregistration, radiometric terrain correction, normalization, and speckle filtering—was implemented to ensure data consistency and accuracy. Statistical homogeneous pixels (SHPs) were extracted to identify stable targets, and coherence-based analysis was employed to quantify temporal decorrelation and detect changes. Adaptive thresholding and morphological operations refined the detected changes, while small-segment removal mitigated noise effects. Experimental results demonstrated high reliability, with an overall accuracy of 92%, validated using confusion matrix analysis. The methodology effectively identified urban changes, highlighting the potential of KOMPSAT-5 data for post-disaster monitoring and urban change detection. Future improvements are suggested, focusing on the stability of InSAR orbits to further enhance detection precision. The findings underscore the potential for broader applications of the developed SAR time-series change detection technology, promoting increased utilization of KOMPSAT SAR data for both domestic and international research and monitoring initiatives.

Abstract Background Previous studies have suggested that frequent toothbrushing is associated with a lower risk of future cardiovascular events. We sought to investigate further the relationship between toothbrushing, cardiovascular risk factors, and lifestyle behaviours. Methods We analysed a cross-sectional survey including 13,761 adults aged 30 years or older without a history of cardiovascular diseases from the Korean National Health and Nutritional Examination Survey. Conventional cardiovascular risk factors (blood pressure, lipid profiles, and fasting glucose), and inflammatory markers (high-sensitivity C-reactive protein [hsCRP], and white blood cell counts [WBC]) were investigated in relation to the frequency of toothbrushing. Results The estimated 10-year atherosclerotic cardiovascular disease (ASCVD) risk, calculated using the pooled cohort equations was 13.7%, 9.1%, and 7.3% for participants who reported toothbrushing 0–1, 2, and ≥ 3 times a day, respectively. Both conventional risk factors and inflammatory markers were significantly associated with frequent toothbrushing. However, after adjusting potential confounding factors such as age, sex, comorbidities, and lifestyle behaviours, only inflammatory markers were remained as significant factors. Conclusions Oral hygiene behaviours are closely linked to cardiovascular risk factors. This study suggests that reduced systemic inflammatory burden may explain the benefit of improved oral hygiene in terms of cardiovascular risk.

Recently, aerial jammers (AJs) have been actively considered because of their swiftness and adaptability to maximize the impact of jammers. The previous studies mainly focused on the optimization of a single AJ (transmit power, location, etc.) consisting of intended users and eavesdroppers in single-cell environment. In this paper, macroscopic impact of multiple randomly deployed AJs to multiple radio access technologies (multi-RATs) is analyzed, which have been actively studied for future cellular systems. In particular, multi-radio heterogeneous networks consisting of WiFi-enabled small base stations (SBSs) and 5G-enabled macro/micro base stations (MBSs) are considered. An integrated framework is developed and evaluated for multi-RATs in the presence of both co-channel interference and AJ interference based on tools from stochastic geometry. The main challenge is to analyze the optimal control of portion of AJs to interfere two different RATs to maximize the outage probability. Both analytical and simulation results are presented to demonstrate the impacts of various network parameters to the overall outage probability.

(1) Background: Shift work can affect physical health and the immune system by altering the body’s circadian rhythms. This study investigated the factors associated with the hepatitis B virus (HBV) vaccination response in manufacturing workers, classified by whether they engaged in shift work or not. (2) Methods: This retrospective observational study was conducted among adults employed at two manufacturing companies. Those with negative initial hepatitis B surface antibody (HBsAb) levels before vaccination and who subsequently received a three-dose series of HBV vaccine were enrolled. Hepatitis B surface antibodies were examined for 3 years after the first dose. The endpoint of this study was the failure of a seroprotective anti-HB response after vaccination (HBsAb < 10 mIU/mL). Binary logistic regression models were used to analyze factors associated with response failures. (3) Results: Of the 1103 eligible subjects, 337 (30.6%) were shift workers. The failure rate was numerically higher in the shift workers (9.2%) than in the non-shift workers (7.9%), without statistical significance (p = 0.405). However, after adjustment with the binary logistic regression models, the shift workers had a statistically significantly higher rate of response failures than the non-shift workers (odds ratio 2.87; 95% confidence interval 1.64–5.05, p < 0.001), as did males, older workers, those with a low initial anti-HB titer, those with a vitamin D deficiency, and current smokers. (4) Conclusions: Our findings suggest a possible association between shift work and the serologic responses to HBV vaccination. Novel strategies for vaccination should be considered for shift workers.

Abstract Effluent from wastewater treatment plants is considered an important source of micropollutants (MPs) in aquatic environments. However, monitoring MPs in effluents is often inefficient owing to the variety in their types. Thus, this study derived marker constituents to estimate the behavior of MPs in each cluster using the self-organizing map (SOM), a machine learning-based clustering analysis method. In SOM analysis, the physicochemical properties, functional groups, and the initial biotransformation rules of 29 out 42 MPs were used to ultimately estimate the degradation rate constants of 13 MPs. Consequently, when the physicochemical properties and functional groups were considered, SOM analysis showed outstanding performance to label MPs with an accuracy value of 0.75 for each aerobic and anoxic condition. Based on the clustering results, 11 MPs were determined to be marker constituents under each aerobic and anoxic condition. Moreover, an estimation method for the rate constants of unlabeled MPs was successfully developed using the identified markers with the random forest classifier. The proposed algorithm could estimate both sorption and biotransformation of MPs regardless of dominant removal mechanisms, whether the MPs were removed by sorption or biotransformation. An accuracy of 0.77 was calculated for estimating rate constants under both aerobic and anoxic conditions, which is remarkably higher than those reported previously. The proposed procedure could be extended further to efficiently monitor MPs in effluents.

Abstract Background Diabetes mellitus (DM) is associated with thrombogenicity, clinically manifested with atherothrombotic events after percutaneous cutaneous intervention (PCI). This study aimed to investigate association between DM status and platelet reactivity, and their prognostic implication in PCI-treated patients. Methods The Platelet function and genoType-Related long-term Prognosis-Platelet Function Test (PTRG-PFT) cohort was established to determine the linkage of platelet function test (PFT) with long-term prognosis during dual antiplatelet therapy including clopidogrel in patients treated with drug-eluting stent (DES). We assessed platelet reactivity using VerifyNow and ‘high platelet reactivity (HPR)’ was defined as ≥ 252 P2Y12 reaction unit (PRU). Major adverse cardiac and cerebrovascular event (MACCE) was a composite of all-cause death, myocardial infarction, stent thrombosis or stroke. Results Between July 2003 and Aug 2018, DES-treated patients with available PFT were enrolled (n = 11,714). Diabetic patients demonstrated significant higher levels of platelet reactivity (DM vs. non-DM: 225.7 ± 77.5 vs. 213.6 ± 79.1 PRU, P

IntroductionThis study investigated the long-term prevalence of, and factors associated with, post-traumatic stress disorder (PTSD) among the bereaved families of the Sewol ferry disaster, in which 250 students lost their lives during a school excursion.MethodsEight years after the disaster, 181 family members were surveyed, and the prevalence of clinical PTSD symptoms was estimated. The Positive Resources Test (POREST), the Duke-UNC Functional Social Support Questionnaire, and the Brief COPE were evaluated using self-report measures. The multivariable binomial logistic regression was used to identify protective and risk factors for PTSD.ResultsPTSD symptoms were present in 49.7% of the family members 8 years after the incident. A one-point increase in the score on the optimism subscale of the POREST was associated with a 20.1% decreased likelihood of having clinical PTSD symptoms (OR = 0.799; p = 0.027; 95% CI = 0.655–0.975). Conversely, a one-point increase in the score on the avoidant subscale of Brief COPE was associated with a 13.2% increased likelihood of having clinical PTSD symptoms (OR = 1.132; p = 0.041; 95% CI = 1.005–1.274).DiscussionOur results provide evidence of the need for long-term mental health monitoring of bereaved families of disaster victims, along with valuable insights for the development of mental health intervention programs.

This paper studies physical layer security for Alamouti space–time block code (STBC) with joint maximum likelihood (JML) or zero forcing (ZF) detection techniques particularly over multi-input single-output (MISO) wiretap time-selective Rayleigh fading channels. Specifically, we derive the secrecy outage probabilities (SOPs) and their concise but effective approximations for various combinations of JML and ZF at the legitimate receiver and eavesdropper. We also investigate the secrecy diversity gain by applying the high signal-to-noise ratio (SNR) approximation of SOP and prove that the corresponding asymptotic diversity order of two, two, one, and one can be achieved for JML-JML, JML-ZF, ZF-JML, and ZF-ZF, respectively. Our asymptotic analytical results corroborate that the secrecy diversity order is dominantly affected by the detection strategy of the legitimate receiver rather than that of the eavesdropper.

Introduction. Hepatitis B virus (HBV) vaccination has decreased the overall incidence of HBV infection; however, approximately 5 to 10% of people are non-responders to the vaccination. This study investigated the factors associated with non-response to HBV vaccination, with an emphasis on vitamin D deficiency (VDD). Methods. This retrospective observational study focused on adult workers in a single heavy industry. Individuals with negative initial hepatitis B surface antibody (anti-HBs) levels prior to vaccination and who then received a two- or three-dose series of HBV vaccinations were enrolled. The study endpoint was failure to achieve a seroprotective antibody response, defined as an anti-HBs titer less than 10 mIU/mL. Propensity score matching (PSM) and binary logistic regression models were used to adjust the outcomes for other clinical characteristics. Results. Among 760 workers, 566 (74.5%) exhibited VDD. The non-response rates to HBV vaccination were 13.4% (76/566) and 5.7% (11/194) among workers with and without VDD, respectively (p = 0.005). Even after adjustment using PSM, VDD was still associated with a higher rate of response failure (adjusted odds ratio 2.74; 95% confidence interval 1.40–5.38, p = 0.003). The binary logistic regression model showed that VDD, older age, omission of the third vaccine dose, lower initial anti-HBs titer, and current smoking were associated with response failure. Conclusions. Our study suggests that VDD may impair the serologic response following HBV vaccination. Further research is needed to evaluate the effectiveness of vitamin D supplementation in increasing the response to HBV vaccination.

Introduction This study evaluated the efficacy and safety of a single-pill triple-combination of olmesartan/amlodipine/rosuvastatin (Olme/Amlo/Rosu) in comparison with a single-pill dual-combination of olmesartan/amlodipine (Olme/Amlo) in hypertensive patients with low-to-moderate cardiovascular risk. Methods This multicenter, active-control, randomized study included 106 hypertensive patients at low-to-moderate cardiovascular risk who were randomly assigned to receive either Olme/Amlo/Rosu 20/5/5 mg (Treatment 1), Olme/Amlo/Rosu 20/5/10 mg (Treatment 2), or Amlo/Olme 20/5 mg (Control) once daily for 8 weeks. The primary endpoint was the difference of the percent change in low-density lipoprotein cholesterol (LDL-C) level at 8 weeks from baseline in the 3 groups. Results The difference in the least square mean percent change (standard deviation) of LDL-C in the Treatment 1 and 2 groups compared with the Control group at 8 weeks was −32.6 (3.7) % and −45.9 (3.3) %, respectively ( P .05). Conclusion Single-pill triple-combination of olmesartan/amlodipine/rosuvastatin was superior to the single-pill dual-combination of amlodipine/olmesartan in LDLC-lowering effects, with excellent safety profiles and adherence rates, in hypertensive patients at low-to-moderate cardiovascular risk. Trial Registration: CLinicalTrials.gov identifier NCT04120753.

BackgroundWhile conventional electrocardiogram monitoring devices are useful for detecting atrial fibrillation, they have considerable drawbacks, including a short monitoring duration and invasive device implantation. The use of patch-type devices circumvents these drawbacks and has shown comparable diagnostic capability for the early detection of atrial fibrillation. ObjectiveWe aimed to determine whether a patch-type device (AT-Patch) applied to patients with a high risk of new-onset atrial fibrillation defined by the congestive heart failure, hypertension, age ≥75 years, diabetes mellitus, stroke, vascular disease, age 65-74 years, sex scale (CHA2DS2-VASc) score had increased detection rates. MethodsIn this nonrandomized multicenter prospective cohort study, we enrolled 320 adults aged ≥19 years who had never experienced atrial fibrillation and whose CHA2DS2-VASc score was ≥2. The AT-Patch was attached to each individual for 11 days, and the data were analyzed for arrhythmic events by 2 independent cardiologists. ResultsAtrial fibrillation was detected by the AT-Patch in 3.4% (11/320) of patients, as diagnosed by both cardiologists. Interestingly, when participants with or without atrial fibrillation were compared, a previous history of heart failure was significantly more common in the atrial fibrillation group (n=4/11, 36.4% vs n=16/309, 5.2%, respectively; P=.003). When a CHA2DS2-VASc score ≥4 was combined with previous heart failure, the detection rate was significantly increased to 24.4%. Comparison of the recorded electrocardiogram data revealed that supraventricular and ventricular ectopic rhythms were significantly more frequent in the new-onset atrial fibrillation group compared with nonatrial fibrillation group (3.4% vs 0.4%; P=.001 and 5.2% vs 1.2%; P

Background No large‐scale study has compared the clinical impact of triple antiplatelet therapy (TAPT: aspirin, clopidogrel, and cilostazol) and dual antiplatelet therapy (DAPT) on adverse limb events in patients with diabetes after endovascular therapy (EVT) for peripheral artery disease. Thus, we investigate the effect of cilostazol added to a DAPT on the clinical outcomes after EVT in patients with diabetes using a nationwide, multicenter, real‐world registry. Methods and Results A total of 990 patients with diabetes who underwent EVT were enrolled from the retrospective cohorts of a Korean multicenter EVT registry and were divided according to the antiplatelet regimen (TAPT [n=350; 35.4%] versus DAPT [n=640; 64.6%]). After propensity score matching based on clinical characteristics, a total of 350 pairs were compared for clinical outcomes. The primary end points were major adverse limb events, a composite of major amputation, minor amputation, and reintervention. For the matched study groups, the lesion length was 125.4±102.0 mm, and severe calcification was observed in 47.4%. The technical success rate (96.9% versus 94.0%; P=0.102) and the complication rate (6.9% versus 6.6%; P>0.999) were similar between the TAPT and DAPT groups. At 2‐year follow‐up, the incidence of major adverse limb events (16.6% versus 19.4%; P=0.260) did not differ between the 2 groups. However, the TAPT group showed less minor amputation than the DAPT group (2.0% versus 6.3%; P=0.004). In multivariate analysis, TAPT was an independent predictor of minor amputation (adjusted hazard ratio, 0.354 [95% CI, 0.158–0.794]; P=0.012). Conclusions In patients with diabetes undergoing EVT for peripheral artery disease, TAPT did not decrease the incidence of major adverse limb events but may be associated with a decreased risk of minor amputation.

Because nuclear power plants (NPPs) are safety-critical infrastructure, it is essential to increase their safety and minimize risk. To reduce human error and support decision-making by operators, several artificial-intelligence-based diagnosis methods have been proposed. However, because of the nature of data-driven methods, conventional artificial intelligence requires large amount of measurement values to train and achieve enough diagnosis resolution.We propose a graph neural network (GNN) based accident diagnosis algorithm to achieve high diagnosis resolution with limited measurements. The proposed algorithm is trained with both the knowledge about physical correlation between components and measurement values. To validate the proposed methodology has a sufficiently high diagnostic resolution with limited measurement values, the diagnosis of multiple accidents was performed with limited measurement values and also, the performance was compared with convolution neural network (CNN). In case of the experiment that requires low diagnostic resolution, both CNN and GNN showed good results. However, for the tests that requires high diagnostic resolution, GNN greatly outperformed the CNN.

In this study, a compact, low-power 2D phase comparison direction finder was designed and fabricated. For the design of the direction-finding (DF) receiver, a 2D phase comparison DF equation was derived from the structure of four uniformly arranged antennas, and the main design parameters were derived from the receiver’s system parameters. Based on the derived DF equations and design parameters, a DF receiver was designed, and a direction finder was fabricated. A comparison of the fabricated direction finder to a simulation model showed that its performance was comparable to the simulated performance and satisfied the system parameters. Moreover, a comparison of the theoretical, simulated, and actual injection and radiation DF precision showed that the fabricated direction finder had performance consistent with that indicated by the theoretical and simulation results and DF precision within 0.5°.

Background: The ultrathin-strut drug-eluting stent (DES) has shown better clinical results than thin- or thick-strut DES. We investigated if re-endothelialization was different among three types of DES: ultrathin-strut abluminal polymer-coated sirolimus-eluting stent (SES), thin-strut circumferential polymer-coated everolimus-eluting stent (EES), and thick-strut polymer-free biolimus-eluting stent (BES) to gain insight into the effect of stent design on promoting vascular healing.Methods: After implanting three types of DES in the coronary arteries of minipigs, we performed optical coherence tomography (OCT) at weeks 2, 4, and 12 (n = 4, each). Afterward, we harvested the coronary arteries and performed immunofluorescence for endothelial cells (ECs), smooth muscle cells (SMCs), and nuclei. We obtained 3D stack images of the vessel wall and reconstructed the en face view of the inner lumen. We compared re-endothelialization and associated factors among the different types of stents at different time points.Results: SES showed significantly faster and denser re-endothelialization than EES and BES at weeks 2 and 12. Especially in week 2, SES elicited the fastest SMC coverage and greater neointimal cross-sectional area (CSA) compared to EES and BES. A strong correlation between re-endothelialization and SMC coverage was observed in week 2. However, the three stents did not show any difference at weeks 4 and 12 in SMC coverage and neointimal CSA. At weeks 2 and 4, SMC layer morphology showed a significant difference between stents. A sparse SMC layer was associated with denser re-endothelialization and was significantly higher in SES. Unlike the sparse SMC layer, the dense SMC layer did not promote re-endothelialization during the study period.Conclusion: Re-endothelialization after stent implantation was related to SMC coverage and SMC layer differentiation, which were faster in SES. Further investigation is needed to characterize the differences among the SMCs and explore methods for increasing the sparse SMC layer in order to improve stent design and enhance safety and efficacy.

BackgroundAn accurate quantitative analysis of coronary artery stenotic lesions is essential to make optimal clinical decisions. Recent advances in computer vision and machine learning technology have enabled the automated analysis of coronary angiography. ObjectiveThe aim of this paper is to validate the performance of artificial intelligence–based quantitative coronary angiography (AI-QCA) in comparison with that of intravascular ultrasound (IVUS). MethodsThis retrospective study included patients who underwent IVUS-guided coronary intervention at a single tertiary center in Korea. Proximal and distal reference areas, minimal luminal area, percent plaque burden, and lesion length were measured by AI-QCA and human experts using IVUS. First, fully automated QCA analysis was compared with IVUS analysis. Next, we adjusted the proximal and distal margins of AI-QCA to avoid geographic mismatch. Scatter plots, Pearson correlation coefficients, and Bland-Altman were used to analyze the data. ResultsA total of 54 significant lesions were analyzed in 47 patients. The proximal and distal reference areas, as well as the minimal luminal area, showed moderate to strong correlation between the 2 modalities (correlation coefficients of 0.57, 0.80, and 0.52, respectively; P