Long-Term Prognosis of Moderate to Severe Coronary Artery Calcification in Patients Undergoing Percutaneous Coronary Intervention

Calcium modification techniques in complex percutaneous coronary intervention: State-of-the-art review

As patients increase in age and medical complexity, coronary artery calcification is frequently encountered and its presence portends worse outcomes following percutaneous coronary intervention (PCI) - negatively impacting procedural success and long-term outcomes. This review paper explores available imaging techniques and calcium modification technique that can identify, characterize and modify these lesions to facilitate stent implantation. The data supporting these techniques are explored and an algorithm for decision-making during lesion modification is presented. Current barriers and future directions are additionally discussed.

Overview of Therapeutic Ultrasound Applications and Safety Considerations: 2024 Update

A 2012 review of therapeutic ultrasound was published to educate researchers and physicians on potential applications and concerns for unintended bioeffects (doi: 10.7863/jum.2012.31.4.623). This review serves as an update to the parent article, highlighting advances in therapeutic ultrasound over the past 12 years. In addition to general mechanisms for bioeffects produced by therapeutic ultrasound, current applications, and the pre-clinical and clinical stages are outlined. An overview is provided for image guidance methods to monitor and assess treatment progress. Finally, other topics relevant for the translation of therapeutic ultrasound are discussed, including computational modeling, tissue-mimicking phantoms, and quality assurance protocols.

Machine learning-based coronary artery calcium score predicted from clinical variables as a prognostic indicator in patients referred for invasive coronary angiography

OBJECTIVES

Utilising readily available clinical variables, we aimed to develop and validate a novel machine learning (ML) model to predict severe coronary calcification, and further assessed its prognostic significance.

METHODS

This retrospective study enrolled patients who underwent coronary CT angiography and subsequent invasive coronary angiography. Multiple ML algorithms were used to train the models for predicting severe coronary calcification (cardiac CT-measured coronary artery calcium [CT-CAC] score ≥ 400). The ML-based CAC (ML-CAC) score derived from the ML predictive probability was stratified into quartiles for prognostic analysis. The primary endpoint was a composite of all-cause death, nonfatal myocardial infarction, or nonfatal stroke.

RESULTS

Overall, 5785 patients were divided into training (80%) and test sets (20%). For clinical practicability, we selected the nine-feature support vector machine model with good and satisfactory performance regarding both discrimination and calibration based on five repetitions of the 10-fold cross-validation in the training set (mean AUC = 0.715, Brier score = 0.202), and based on the test in the test set (AUC = 0.753, Brier score = 0.191). In the test set cohort (n = 1137), the primary endpoint was observed in 50 (4.4%) patients during a median 2.8 years' follow-up. The ML-CAC system was significantly associated with an increased risk of the primary endpoint (adjusted hazard ratio for trend 2.26, 95% CI 1.35-3.79, p = 0.002). There was no significant difference in the prognostic value between the ML-CAC and CT-CAC systems (C-index, 0.67 vs. 0.69; p = 0.618).

CONCLUSION

ML-CAC score predicted from clinical variables can serve as a novel prognostic indicator in patients referred for invasive coronary angiography.

CLINICAL RELEVANCE STATEMENT

In patients referred for invasive coronary angiography who have not undergone preoperative CT-measured coronary artery calcium scoring, machine learning-based coronary artery calcium score assessment can serve as an alternative for predicting the prognosis.

KEY POINTS

• The coronary artery calcium (CAC) score, a solid prognostic indicator, can be predicted using non-CT methods. • We developed a machine learning (ML)-CAC model utilising nine clinical variables to predict severe coronary calcification. • The ML-CAC system offers significant prognostic value in patients referred for invasive coronary angiography.

Association of NPC1L1 and HMGCR gene polymorphisms with coronary artery calcification in patients with premature triple-vessel coronary disease

BACKGROUND

Coronary artery calcification (CAC) is a highly specific marker of atherosclerosis. Niemann-Pick C1-like 1 (NPC1L1) and 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) are the therapeutic targets of ezetimibe and statins, respectively, which are important for the progression of atherosclerosis. However, CAC's genetic susceptibility with above targets is still unknown. We aimed to investigate the association of NPC1L1 and HMGCR gene polymorphisms with CAC in patients with premature triple-vessel disease (PTVD).

METHODS

Four single nucleotide polymorphisms (SNPs) (rs11763759, rs4720470, rs2072183, rs2073547) of NPC1L1, and three SNPs (rs12916, rs2303151, rs4629571) of HMGCR were genotyped in 872 PTVD patients. According to the coronary angiography results, patients were divided into low-degree CAC group and high-degree CAC group.

RESULTS

A total of 872 PTVD patients (mean age, 47.71 ± 6.12; male, 72.8%) were finally included for analysis. Multivariate logistic regression analysis showed no significant association between the SNPs of NPC1L1 and HMGCR genes and high-degree CAC in the total population (P > 0.05). Subgroup analysis by gender revealed that the variant genotype (TT/CT) of rs4720470 on NPC1L1 gene was associated with increased risk for high-degree CAC in male patients only (OR = 1.505, 95% CI: 1.008-2.249, P = 0.046) in dominant model, but no significant association was found in female population, other SNPs of NPC1L1 and HMGCR genes (all P > 0.05).

CONCLUSIONS

We reported for the first time that the rs4720470 on NPC1L1 gene was associated with high-degree CAC in male patients with PTVD. In the future, whether therapies related to this target could reduce CAC and cardiovascular events deserves further investigation.

A study of balloon type on calcified coronary lesion predilation: A finite element analysis

Calcified coronary lesions have been one of the more difficult types of lesion for interventional treatment, and angioplasty is required to break the calcification before stent implantation so that the stent can expand smoothly, however, it remains unclear which type of angioplasty is optimal for different calcified lesions. In this study, a finite element approach was used to model normal balloons, cutting balloons, and AngioSculpt balloons. In addition, calcified lesions of different degrees, thicknesses, and lengths were modeled according to Intravascular ultrasound (IVUS) calcification grade. The above three balloons were used to pretreat calcified lesions, and the brittle fracture module for calcification was used to detect fracture success, to facilitate virtual stent implantation after predilation. The simulation results showed that with a thickness of less than 0.3 mm, balloons were unable to deal with calcified plaques in lesions of less than 120°, for 180° calcified lesions the cutting balloon fractured the calcified material at 1.2 MPa, the AngioSculpt balloon produced multiple fractures at 0.8 MPa for 270° calcified plaques, but was unable to fracture calcified lesions with a thickness of 0.4 mm. Based on these results, we conclude that the length of the lesion did not affect calcification fracture, while the thickness of the lesion did. In calcified lesions of approximately 180°, the cutting balloon showed the best predilation results, while the AngioSculpt balloon was optimal for 270°. In annular calcification, all three balloons were unable to fracture the lesion.

3-Year outcomes in patients with heavily calcified lesions undergoing percutaneous coronary intervention using cutting balloons

BACKGROUND

Percutaneous coronary intervention (PCI) of heavily calcified lesions (HCLs) is associated with higher complication rates and worse clinical outcomes. Cutting balloon (CB) has been widely used for HCLs, but patients' prognosis had not been fully clarified. The study aimed to compare 3-year clinical outcomes between patients with HCLs that are treated with CBs and those with non-HCLs.

METHOD

Patients who underwent PCI in Guizhou Provincial People's Hospital from June 2015 to September 2018 were retrospectively included. HCL was defined as radiopaque and high-pressure undilatable lesions. CBs were routinely used in combination with non-compliant balloons for the HCLs. Major adverse cardiac event (MACE) and target vessel failure (TVF) were assessed at 3-year follow-up.

RESULT

Among 2432 patients included in the study, 210(8.6%) had HCLs with a procedural success rate of 91.0%. The patients with HCLs had a higher incidence of MACE (23.3% vs. 10.8%, P < 0.001) than those with non-HCLs. By propensity score matching, 172 patients with HCLs were 1:1 paired to those with non-HCLs, and their PCI vessels were exactly matched. The MACE and TVF were significantly higher in the patients with HCLs than those with non-HCLs (MACE: 21.5% vs. 13.4%, P = 0.036; TVF: 19.8% vs. 9.9%, P = 0.008). In the Cox regression analysis, HCL is independently associated with higher risks of MACE [HR: 1.72(1.01-2.94), P = 0.047], TVF [HR: 2.10(1.15-3.81), P = 0.015] and repeat revascularization [HR: 2.20(1.07-4.52), P = 0.032].

CONCLUSION

Patients with HCLs undergoing PCI using CBs in combination with non-compliant balloons had higher risks of complications, procedural failure, and worse clinical outcomes at 3 years than those with non-HCLs.

Bibliometric and Visual Analysis of Vascular Calcification Research

Background: Extensive studies related to vascular calcification (VC) were conducted in recent years. However, no bibliometric analysis has systematically investigated this topic. Our study aimed to determine the hotspots and frontiers of VC research in the past decade and provide a reference for future scientific research directions and decision-making in the VC field.

Methods: VC studies were acquired from the Web of Science Core Collection. Bibliometric and visual analyses were performed using CiteSpace, VOSviewer, and Microsoft Excel software.

Results: A total of 8,238 English articles on VC research published in 2011–2020 were obtained. In the past decade, annual publications and citations showed a significant growth trend, especially in 2018–2020. The most productive country, institution, journal and author are the United States, the University of California System, PLOS ONE, and Budoff MJ, respectively. The most frequently cited country, journal, and author are the United States, Journal of the American College of Cardiology, and Floege J, respectively. “Vascular calcification,” “atherosclerosis,” “chronic kidney disease,” and “cardiovascular disease” are the primary keywords. The burst keywords “revascularization,” “calciprotein particle,” “microRNA,” and “microcalcification” are speculated to be the research frontiers.

Conclusion: The main research hotspots in the VC field are the molecular mechanisms and prognosis of VC in patients with chronic kidney disease or cardiovascular disease. In addition, endovascular therapy and the development of new drugs targeting signal pathways for VC will become the focus of future research. Moreover, non-coding RNAs related to the diagnosis and treatment of VC are great research prospects.