Influence of Pathophysiological Patterns of Coronary Artery Disease on Immediate Percutaneous Coronary Intervention Outcomes.

BACKGROUND: Diffuse coronary artery disease (CAD) impacts the safety and efficacy of percutaneous coronary intervention (PCI). Pathophysiological CAD patterns can be quantified using fractional flow reserve (FFR) pullbacks incorporating the pullback pressure gradient (PPG) calculation. This study aimed to establish the capacity of PPG to predict optimal revascularisation and procedural outcomes. METHODS: This prospective, investigator-initiated, single-arm, multicentre study enrolled patients with at least one epicardial lesion with an FFR ≤ 0.80 scheduled for PCI. Manual FFR pullbacks were employed to calculate PPG. The primary outcome of optimal revascularisation was defined as a post-PCI FFR ≥ 0.88. RESULTS: 993 patients with 1044 vessels were included. The mean FFR was 0.68 ± 0.12, PPG 0.62 ± 0.17, and post-PCI FFR 0.87 ± 0.07. PPG was significantly correlated with the change in FFR after PCI (r=0.65, 95% CI 0.61-0.69, p<0.001) and demonstrated excellent predicted capacity for optimal revascularisation (AUC 0.82, 95% CI 0.79-0.84, p<0.001). Conversely, FFR alone did not predict revascularisation outcomes (AUC 0.54, 95% CI 0.50-0.57). PPG influenced treatment decisions in 14% of patients, redirecting them from PCI to alternative treatment modalities. Periprocedural myocardial infarction occurred more frequently in patients with low PPG (<0.62) compared to those with focal disease (OR 1.71, 95% CI: 1.00-2.97). CONCLUSIONS: Pathophysiological CAD patterns distinctly affect the safety and effectiveness of PCI. The PPG showed an excellent predictive capacity for optimal revascularisation and demonstrated added value compared to a FFR measurement.

Artificial Intelligence-Enabled Quantitative Coronary Plaque and Hemodynamic Analysis for Predicting Acute Coronary Syndrome.

BACKGROUND: A lesion-level risk prediction for acute coronary syndrome (ACS) needs better characterization. OBJECTIVES: This study sought to investigate the additive value of artificial intelligence-enabled quantitative coronary plaque and hemodynamic analysis (AI-QCPHA). METHODS: Among ACS patients who underwent coronary computed tomography angiography (CTA) from 1 month to 3 years before the ACS event, culprit and nonculprit lesions on coronary CTA were adjudicated based on invasive coronary angiography. The primary endpoint was the predictability of the risk models for ACS culprit lesions. The reference model included the Coronary Artery Disease Reporting and Data System, a standardized classification for stenosis severity, and high-risk plaque, defined as lesions with ≥2 adverse plaque characteristics. The new prediction model was the reference model plus AI-QCPHA features, selected by hierarchical clustering and information gain in the derivation cohort. The model performance was assessed in the validation cohort. RESULTS: Among 351 patients (age: 65.9 ± 11.7 years) with 2,088 nonculprit and 363 culprit lesions, the median interval from coronary CTA to ACS event was 375 days (Q1-Q3: 95-645 days), and 223 patients (63.5%) presented with myocardial infarction. In the derivation cohort (n = 243), the best AI-QCPHA features were fractional flow reserve across the lesion, plaque burden, total plaque volume, low-attenuation plaque volume, and averaged percent total myocardial blood flow. The addition of AI-QCPHA features showed higher predictability than the reference model in the validation cohort (n = 108) (AUC: 0.84 vs 0.78; P < 0.001). The additive value of AI-QCPHA features was consistent across different timepoints from coronary CTA. CONCLUSIONS: AI-enabled plaque and hemodynamic quantification enhanced the predictability for ACS culprit lesions over the conventional coronary CTA analysis. (Exploring the Mechanism of Plaque Rupture in Acute Coronary Syndrome Using Coronary Computed Tomography Angiography and Computational Fluid Dynamics II [EMERALD-II]; NCT03591328).

Intravascular Imaging Findings After PCI in Patients With Focal and Diffuse Coronary Artery Disease.

BACKGROUND: Following percutaneous coronary intervention (PCI), optical coherence tomography provides prognosis information. The pullback pressure gradient is a novel index that discriminates focal from diffuse coronary artery disease based on fractional flow reserve pullbacks. We sought to investigate the association between coronary artery disease patterns, defined by coronary physiology, and optical coherence tomography after stent implantation in stable patients undergoing PCI. METHODS AND RESULTS: This multicenter, prospective, single-arm study was conducted in 5 countries (NCT03782688). Subjects underwent motorized fractional flow reserve pullbacks evaluation followed by optical coherence tomography-guided PCI. Post-PCI optical coherence tomography minimum stent area, stent expansion, and the presence of suboptimal findings such as incomplete stent apposition, stent edge dissection, and irregular tissue protrusion were compared between patients with focal versus diffuse disease. Overall, 102 patients (105 vessels) were included. Fractional flow reserve before PCI was 0.65±0.14, pullback pressure gradient was 0.66±0.14, and post-PCI fractional flow reserve was 0.88±0.06. The mean minimum stent area was 5.69±1.99 mm2 and was significantly larger in vessels with focal disease (6.18±2.12 mm2 versus 5.19±1.72 mm2, P=0.01). After PCI, incomplete stent apposition, stent edge dissection, and irregular tissue protrusion were observed in 27.6%, 10.5%, and 51.4% of the cases, respectively. Vessels with focal disease at baseline had a lower prevalence of incomplete stent apposition (11.3% versus 44.2%, P=0.002) and more irregular tissue protrusion (69.8% versus 32.7%, P<0.001). CONCLUSIONS: Baseline coronary pathophysiological patterns are associated with suboptimal imaging findings after PCI. Patients with focal disease had larger minimum stent area and a higher incidence of tissue protrusion, whereas stent malapposition was more frequent in patients with diffuse disease.

Insertable Biosensors: Combining Implanted Sensing Materials with Wearable Monitors.

Insertable biosensor systems are medical diagnostic devices with two primary components: an implantable biosensor within the body and a wearable monitor that can remotely interrogate the biosensor from outside the body. Because the biosensor does not require a physical connection to the electronic monitor, insertable biosensor systems promise improved patient comfort, reduced inflammation and infection risk, and extended operational lifetimes relative to established percutaneous biosensor systems. However, the lack of physical connection also presents technical challenges that have necessitated new innovations in developing sensing chemistries, transduction methods, and communication modalities. In this review, we discuss the key developments that have made insertables a promising option for longitudinal biometric monitoring and highlight the essential needs and existing development challenges to realizing the next generation of insertables for extended-use diagnostic and prognostic devices. Expected final online publication date for the Annual Review of Biomedical Engineering, Volume 26 is May 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Blood-based multi-cancer detection: A state-of-the-art update.

The early detection of cancer is a key goal of the National Cancer Plan formally released by the National Institutes of Health's (NIH) National Cancer Institute (NCI) in April 2023. To support this effort, many laboratories and vendors are developing multi-cancer detection (MCD) assays that interrogate blood and other bodily fluids for cancer-related biomarkers, most commonly circulating tumor DNA (ctDNA). While this approach holds promise for non-invasively detecting early signals of multiple different cancers and potentially reducing cancer-related mortality, there is a dearth of prospective clinical data to inform the deployment of MCD assays for cancer screening in the general adult population. In this review we highlight differing technologies that underpin various MCD assays in clinical development, the importance of achieving adequate performance specifications for MCD assays, ongoing clinical studies investigating the utility of MCD assays in cancer screening and detection, and efforts by the NCI's Division of Cancer Prevention (DCP) to establish a network infrastructure that has the capacity to comprehensively address the scientific and logistical challenges of evaluating blood-based MCD approaches and other cancer screening tools.

Evaluating the efficacy of combination and single-agent immunotherapies in real-world patterns of disease progression and survival of metastatic melanoma patients.

The objective of this study is to describe survival outcomes in patients with metastatic melanoma in a real-world setting receiving combination and single-agent immunotherapy outside the clinical trial context. We conducted a retrospective single-institution study of patients with metastatic melanoma in a real-world setting. Survival was calculated using log-rank test. Contingency tables were analyzed using Fisher's Exact test. CD8 + T-cell densities were measured using quantitative immunofluorescence and analyzed using Mann-Whitney U test. The median overall survival (OS) for 132 patients was 45.3 months. Brain metastasis did not confer a higher risk of death relative to liver and/or bone disease (39.53 versus 30.00 months, respectively; P  = 0.687). Anti-PD-1 monotherapy was the most common first-line treatment, received by 49.2% of patients. There was no significant difference in OS between patients receiving single-agent anti-PD-1 and combination anti-PD-1 plus CTLA-4 (39.4 months versus undefined; P  = 0.643). Patients treated with combination therapy were more likely to be alive without progression at the last follow-up than those who received monotherapy (70.4% versus 49.2%; P  = 0.0408). Median OS was 21.8 months after initiation of second-line therapy after anti-PD-1 monotherapy. CD8+ T-cell densities were higher in patients who achieved disease control on first-line immunotherapy ( P  = 0.013). In a real-world setting, patients with metastatic melanoma have excellent survival rates, and treatment benefit can be achieved even after progression on first-line therapy. Combination immunotherapy may produce more favorable long-term outcomes in a real-world setting. High pretreatment CD8+ T-cell infiltration correlates with immunotherapy efficacy.

Impact of coronary CT image quality on the accuracy of the FFRCT Planner.

OBJECTIVE: To assess the accuracy of a virtual stenting tool based on coronary CT angiography (CCTA) and fractional flow reserve (FFR) derived from CCTA (FFRCT Planner) across different levels of image quality. MATERIALS AND METHODS: Prospective, multicenter, single-arm study of patients with chronic coronary syndromes and lesions with FFR ≤ 0.80. All patients underwent CCTA performed with recent-generation scanners. CCTA image quality was adjudicated using the four-point Likert scale at a per-vessel level by an independent committee blinded to the FFRCT Planner. Patient- and technical-related factors that could affect the FFRCT Planner accuracy were evaluated. The FFRCT Planner was applied mirroring percutaneous coronary intervention (PCI) to determine the agreement with invasively measured post-PCI FFR. RESULTS: Overall, 120 patients (123 vessels) were included. Invasive post-PCI FFR was 0.88 ± 0.06 and Planner FFRCT was 0.86 ± 0.06 (mean difference 0.02 FFR units, the lower limit of agreement (LLA) - 0.12, upper limit of agreement (ULA) 0.15). CCTA image quality was assessed as excellent (Likert score 4) in 48.3%, good (Likert score 3) in 45%, and sufficient (Likert score 2) in 6.7% of patients. The FFRCT Planner was accurate across different levels of image quality with a mean difference between FFRCT Planner and invasive post-PCI FFR of 0.02 ± 0.07 in Likert score 4, 0.02 ± 0.07 in Likert score 3 and 0.03 ± 0.08 in Likert score 2, p = 0.695. Nitrate dose ≥ 0.8mg was the only independent factor associated with the accuracy of the FFRCT Planner (95%CI - 0.06 to - 0.001, p = 0.040). CONCLUSION: The FFRCT Planner was accurate in predicting post-PCI FFR independent of CCTA image quality. CLINICAL RELEVANCE STATEMENT: Being accurate in predicting post-PCI FFR across a wide spectrum of CT image quality, the FFRCT Planner could potentially enhance and guide the invasive treatment. Adequate vasodilation during CT acquisition is relevant to improve the accuracy of the FFRCT Planner. KEY POINTS: • The fractional flow reserve derived from coronary CT angiography (FFRCT) Planner is a novel tool able to accurately predict fractional flow reserve after percutaneous coronary intervention. • The accuracy of the FFRCT Planner was confirmed across a wide spectrum of CT image quality. Nitrates dose at CT acquisition was the only independent predictor of its accuracy. • The FFRCT Planner could potentially enhance and guide the invasive treatment.

Influence of intracoronary hemodynamic forces on atherosclerotic plaque phenotypes.

BACKGROUND AND AIMS: Coronary hemodynamics impact coronary plaque progression and destabilization. The aim of the present study was to establish the association between focal vs. diffuse intracoronary pressure gradients and wall shear stress (WSS) patterns with atherosclerotic plaque composition. METHODS: Prospective, international, single-arm study of patients with chronic coronary syndromes and hemodynamic significant lesions (fractional flow reserve [FFR] ≤ 0.80). Motorized FFR pullback pressure gradient (PPG), optical coherence tomography (OCT), and time-average WSS (TAWSS) and topological shear variation index (TSVI) derived from three-dimensional angiography were obtained. RESULTS: One hundred five vessels (median FFR 0.70 [Interquartile range (IQR) 0.56-0.77]) had combined PPG and WSS analyses. TSVI was correlated with PPG (r = 0.47, [95% Confidence Interval (95% CI) 0.30-0.65], p < 0.001). Vessels with a focal CAD (PPG above the median value of 0.67) had significantly higher TAWSS (14.8 [IQR 8.6-24.3] vs. 7.03 [4.8-11.7] Pa, p < 0.001) and TSVI (163.9 [117.6-249.2] vs. 76.8 [23.1-140.9] m-1, p < 0.001). In the 51 vessels with baseline OCT, TSVI was associated with plaque rupture (OR 1.01 [1.00-1.02], p = 0.024), PPG with the extension of lipids (OR 7.78 [6.19-9.77], p = 0.003), with the presence of thin-cap fibroatheroma (OR 2.85 [1.11-7.83], p = 0.024) and plaque rupture (OR 4.94 [1.82 to 13.47], p = 0.002). CONCLUSIONS: Focal and diffuse coronary artery disease, defined using coronary physiology, are associated with differential WSS profiles. Pullback pressure gradients and WSS profiles are associated with atherosclerotic plaque phenotypes. Focal disease (as identified by high PPG) and high TSVI are associated with high-risk plaque features. CLINICAL TRIAL REGISTRATION: https://clinicaltrials,gov/ct2/show/NCT03782688.

Impact of Post-PCI FFR Stratified by Coronary Artery.

BACKGROUND: Low fractional flow reserve (FFR) after percutaneous coronary intervention (PCI) has been associated with adverse clinical outcomes. Hitherto, this assessment has been independent of the epicardial vessel interrogated. OBJECTIVES: This study sought to assess the predictive capacity of post-PCI FFR for target vessel failure (TVF) stratified by coronary artery. METHODS: We performed a systematic review and individual patient-level data meta-analysis of randomized clinical trials and observational studies with protocol-recommended post-PCI FFR assessment. The difference in post-PCI FFR between left anterior descending (LAD) and non-LAD arteries was assessed using a random-effect models meta-analysis of mean differences. TVF was defined as a composite of cardiac death, target vessel myocardial infarction, and clinically driven target vessel revascularization. RESULTS: Overall, 3,336 vessels (n = 2,760 patients) with post-PCI FFR measurements were included in 9 studies. The weighted mean post-PCI FFR was 0.89 (95% CI: 0.87-0.90) and differed significantly between coronary vessels (LAD = 0.86; 95% CI: 0.85 to 0.88 vs non-LAD = 0.93; 95% CI: 0.91-0.94; P < 0.001). Post-PCI FFR was an independent predictor of TVF, with its risk increasing by 52% for every reduction of 0.10 FFR units, and this was mainly driven by TVR. The predictive capacity for TVF was poor for LAD arteries (AUC: 0.52; 95% CI: 0.47-0.58) and moderate for non-LAD arteries (AUC: 0.66; 95% CI: 0.59-0.73; LAD vs non-LAD arteries, P = 0.005). CONCLUSIONS: The LAD is associated with a lower post-PCI FFR than non-LAD arteries, emphasizing the importance of interpreting post-PCI FFR on a vessel-specific basis. Although a higher post-PCI FFR was associated with improved prognosis, its predictive capacity for events differs between the LAD and non-LAD arteries, being poor in the LAD and moderate in the non-LAD vessels.

Rationale and design of the pullback pressure gradient (PPG) global registry.

INTRODUCTION: Diffuse disease has been identified as one of the main reasons leading to low post-PCI fractional flow reserve (FFR) and residual angina after PCI. Coronary pressure pullbacks allow for the evaluation of hemodynamic coronary artery disease (CAD) patterns. The pullback pressure gradient (PPG) is a novel metric that quantifies the distribution and magnitude of pressure losses along the coronary artery in a focal-to-diffuse continuum. AIM: The primary objective is to determine the predictive capacity of the PPG for post-PCI FFR. METHODS: This prospective, large-scale, controlled, investigator-initiated, multicenter study is enrolling patients with at least 1 lesion in a major epicardial vessel with a distal FFR ≤ 0.80 intended to be treated by PCI. The study will include 982 subjects. A standardized physiological assessment will be performed pre-PCI, including the online calculation of PPG from FFR pullbacks performed manually. PPG quantifies the CAD pattern by combining several parameters from the FFR pullback curve. Post-PCI physiology will be recorded using a standardized protocol with FFR pullbacks. We hypothesize that PPG will predict optimal PCI results (post-PCI FFR ≥ 0.88) with an area under the ROC curve (AUC) ≥ 0.80. Secondary objectives include patient-reported and clinical outcomes in patients with focal vs. diffuse CAD defined by the PPG. Clinical follow-up will be collected for up to 36 months, and an independent clinical event committee will adjudicate events. RESULTS: Recruitment is ongoing and is expected to be completed in the second half of 2023. CONCLUSION: This international, large-scale, prospective study with pre-specified powered hypotheses will determine the ability of the preprocedural PPG index to predict optimal revascularization assessed by post-PCI FFR. In addition, it will evaluate the impact of PPG on treatment decisions and the predictive performance of PPG for angina relief and clinical outcomes.

Coronary Atherosclerosis Phenotypes in Focal and Diffuse Disease.

BACKGROUND: The interplay between coronary hemodynamics and plaque characteristics remains poorly understood. OBJECTIVES: The aim of this study was to compare atherosclerotic plaque phenotypes between focal and diffuse coronary artery disease (CAD) defined by coronary hemodynamics. METHODS: This multicenter, prospective, single-arm study was conducted in 5 countries. Patients with functionally significant lesions based on an invasive fractional flow reserve ≤0.80 were included. Plaque analysis was performed by using coronary computed tomography angiography and optical coherence tomography. CAD patterns were assessed using motorized fractional flow reserve pullbacks and quantified by pullback pressure gradient (PPG). Focal and diffuse CAD was defined according to the median PPG value. RESULTS: A total of 117 patients (120 vessels) were included. The median PPG was 0.66 (IQR: 0.54-0.75). According to coronary computed tomography angiography analysis, plaque burden was higher in patients with focal CAD (87% ± 8% focal vs 82% ± 10% diffuse; P = 0.003). Calcifications were significantly more prevalent in patients with diffuse CAD (Agatston score per vessel: 51 [IQR: 11-204] focal vs 158 [IQR: 52-341] diffuse; P = 0.024). According to optical coherence tomography analysis, patients with focal CAD had a significantly higher prevalence of circumferential lipid-rich plaque (37% focal vs 4% diffuse; P = 0.001) and thin-cap fibroatheroma (TCFA) (47% focal vs 10% diffuse; P = 0.002). Focal disease defined by PPG predicted the presence of TCFA with an area under the curve of 0.73 (95% CI: 0.58-0.87). CONCLUSIONS: Atherosclerotic plaque phenotypes associate with intracoronary hemodynamics. Focal CAD had a higher plaque burden and was predominantly lipid-rich with a high prevalence of TCFA, whereas calcifications were more prevalent in diffuse CAD. (Precise Percutaneous Coronary Intervention Plan [P3]; NCT03782688).

Rethinking Oncologic Treatment Strategies with Interleukin-2.

High-dose recombinant human IL-2 (rhIL-2, aldesleukin) emerged as an important treatment option for selected patients with metastatic melanoma and metastatic renal cell carcinoma, producing durable and long-lasting antitumor responses in a small fraction of patients and heralding the potential of cancer immunotherapy. However, the adoption of high-dose rhIL-2 has been restricted by its severe treatment-related adverse event (TRAE) profile, which necessitates highly experienced clinical providers familiar with rhIL-2 administration and readily accessible critical care medicine support. Given the comparatively wide-ranging successes of immune checkpoint inhibitors and chimeric antigen receptor T cell therapies, there have been concerted efforts to significantly improve the efficacy and toxicities of IL-2-based immunotherapeutic approaches. In this review, we highlight novel drug development strategies, including biochemical modifications and engineered IL-2 variants, to expand the narrow therapeutic window of IL-2 by leveraging downstream activation of the IL-2 receptor to selectively expand anti-tumor CD8-positive T cells and natural killer cells. These modified IL-2 cytokines improve single-agent activity in solid tumor malignancies beyond the established United States Food and Drug Administration (FDA) indications of metastatic melanoma and renal cell carcinoma, and may also be safer in rational combinations with established treatment modalities, including anti-PD-(L)1 and anti-CTLA-4 immunotherapy, chemotherapies, and targeted therapy approaches.

Relationship between coronary volume, myocardial mass, and post-PCI fractional flow reserve.

BACKGROUND: Fractional flow reserve (FFR) measured after percutaneous coronary intervention (PCI) carries prognostic information. Yet, myocardial mass subtended by a stenosis influences FFR. We hypothesized that a smaller coronary lumen volume and a large myocardial mass might be associated with lower post-PCI FFR. AIM: We sought to assess the relationship between vessel volume, myocardial mass, and post-PCI FFR. METHODS: This was a subanalysis with an international prospective study of patients with significant lesions (FFR ≤ 0.80) undergoing PCI. Territory-specific myocardial mass was calculated from coronary computed tomography angiography (CCTA) using the Voronoi's algorithm. Vessel volume was extracted from quantitative CCTA analysis. Resting full-cycle ratio (RFR) and FFR were measured before and after PCI. We assessed the association between coronary lumen volume (V) and its related myocardial mass (M), and the percent of total myocardial mass (%M) with post-PCI FFR. RESULTS: We studied 120 patients (123 vessels: 94 left anterior descending arteries, 13 left Circumflex arteries, 16 right coronary arteries). Mean vessel-specific mass was 61 ± 23.1 g (%M 39.6 ± 11.7%). The mean post-PCI FFR was 0.88 ± 0.06 FFR units. Post-PCI FFR values were lower in vessels subtending higher mass (0.87 ± 0.05 vs. 0.89 ± 0.07, p = 0.047), and with lower V/M ratio (0.87 ± 0.06 vs. 0.89 ± 0.07, p = 0.02). V/M ratio correlated significantly with post-PCI RFR and FFR (RFR r = 0.37, 95% CI: 0.21-0.52, p < 0.001 and FFR r = 0.41, 95% CI: 0.26-0.55, p < 0.001). CONCLUSION: Post-PCI RFR and FFR are associated with the subtended myocardial mass and the coronary volume to mass ratio. Vessels with higher mass and lower V/M ratio have lower post-PCI RFR and FFR.

Evaluation of an artificial intelligence coronary artery calcium scoring model from computed tomography.

OBJECTIVES: Coronary artery calcium (CAC) scores derived from computed tomography (CT) scans are used for cardiovascular risk stratification. Artificial intelligence (AI) can assist in CAC quantification and potentially reduce the time required for human analysis. This study aimed to develop and evaluate a fully automated model that identifies and quantifies CAC. METHODS: Fully convolutional neural networks for automated CAC scoring were developed and trained on 2439 cardiac CT scans and validated using 771 scans. The model was tested on an independent set of 1849 cardiac CT scans. Agatston CAC scores were further categorised into five risk categories (0, 1-10, 11-100, 101-400, and > 400). Automated scores were compared to the manual reference standard (level 3 expert readers). RESULTS: Of 1849 scans used for model testing (mean age 55.7 ± 10.5 years, 49% males), the automated model detected the presence of CAC in 867 (47%) scans compared with 815 (44%) by human readers (p = 0.09). CAC scores from the model correlated very strongly with the manual score (Spearman's r = 0.90, 95% confidence interval [CI] 0.89-0.91, p < 0.001 and intraclass correlation coefficient = 0.98, 95% CI 0.98-0.99, p < 0.001). The model classified 1646 (89%) into the same risk category as human observers. The Bland-Altman analysis demonstrated little difference (1.69, 95% limits of agreement: -41.22, 44.60) and there was almost excellent agreement (Cohen's κ = 0.90, 95% CI 0.88-0.91, p < 0.001). Model analysis time was 13.1 ± 3.2 s/scan. CONCLUSIONS: This artificial intelligence-based fully automated CAC scoring model shows high accuracy and low analysis times. Its potential to optimise clinical workflow efficiency and patient outcomes requires evaluation. KEY POINTS: • Coronary artery calcium (CAC) scores are traditionally assessed using cardiac computed tomography and require manual input by human operators to identify calcified lesions. • A novel artificial intelligence (AI)-based model for fully automated CAC scoring was developed and tested on an independent dataset of computed tomography scans, showing very high levels of correlation and agreement with manual measurements as a reference standard. • AI has the potential to assist in the identification and quantification of CAC, thereby reducing the time required for human analysis.

Procedural Outcomes After Percutaneous Coronary Interventions in Focal and Diffuse Coronary Artery Disease.

Background Coronary artery disease (CAD) patterns play an essential role in the decision-making process about revascularization. The pullback pressure gradient (PPG) quantifies CAD patterns as either focal or diffuse based on fractional flow reserve (FFR) pullbacks. The objective of this study was to evaluate the impact of CAD patterns on acute percutaneous coronary intervention (PCI) results considered surrogates of clinical outcomes. Methods and Results This was a prospective, multicenter study of patients with hemodynamically significant CAD undergoing PCI. Motorized FFR pullbacks and optical coherence tomography (OCT) were performed before and after PCI. Post-PCI FFR >0.90 was considered an optimal result. Focal disease was defined as PPG >0.73 (highest PPG tertile). Overall, 113 patients (116 vessels) were included. Patients with focal disease were younger than those with diffuse CAD (61.4±9.9 versus 65.1±8.7 years, P=0.042). PCI in vessels with high PPG (focal CAD) resulted in higher post-PCI FFR (0.91±0.07 in the focal group versus 0.86±0.05 in the diffuse group, P<0.001) and larger minimal stent area (6.3±2.3 mm2 in focal versus 5.3±1.8 mm2 in diffuse CAD, P=0.015) compared withvessels with low PPG (diffuse CAD). The PPG was associated with the change in FFR after PCI (R2=0.51, P<0.001). The PPG significantly improved the capacity to predict optimal PCI results compared with an angiographic assessment of CAD patterns (area under the curvePPG 0.81 [95% CI, 0.73-0.88] versus area under the curveangio 0.51 [95% CI, 0.42-0.60]; P<0.001). Conclusions PCI in vessels with focal disease defined by the PPG resulted in greater improvement in epicardial conductance and larger minimal stent area compared with diffuse disease. PPG, but not angiographically defined CAD patterns, distinguished patients attaining superior procedural outcomes. Registration URL: https://clinicaltrials.gov/ct2/show/NCT03782688.

Silicone-containing thermoresponsive membranes to form an optical glucose biosensor.

Glucose biosensors that could be subcutaneously injected and interrogated without a physically connected electrode and transmitter affixed to skin would represent a major advancement in reducing the user burden of continuous glucose monitors (CGMs). Towards this goal, an optical glucose biosensor was formed by strategically tailoring a thermoresponsive double network (DN) membrane to house a phosphorescence lifetime-based glucose sensing assay. This membrane was selected based on its potential to exhibit reduced biofouling via 'self-cleaning' due to cyclical deswelling/reswelling in vivo. The membrane was strategically tailored to incorporate oxygen-sensitive metalloporphyrin phosphor, Pd meso-tetra(sulfophenyl)-tetrabenzoporphyrin ([PdPh4(SO3Na)4TBP]3) (HULK) and glucose oxidase (GOx). Specifically, electrostatic interactions and colvalent bonds were used to stabilize HULK and GOx within the membrane, respectively. Enhancing the oxygen permeability of the membrane was necessary to achieve sensitivity of HULK/GOx to physiological glucose levels. Thus, silicone microparticles were incorporated at two concentrations. Key properties of SiHy-0.25 and SiHy-0.5 microparticle-containing compositions were compared to a control having no microparticles (SiHy-0). The discrete nature of the silicone microparticles maintained the desired thermosensitivity profile and did not impact water content. While the modulus decreased with silicone microparticle content, membranes were more mechanically robust versus a conventional hydrogel. SiHy-0.25, owing to apparent phase separation, displayed greater glucose diffusion and oxygen permeability versus SiHy-0.5. Furthermore, SiHy-0.25 biosensors exhibited the greatest glucose sensitivity range of 100 to 300 mg dL-1versus only 100 to 150 mg dL-1 for both SiHy-0 and SiHy-0.5 biosensors.

Clinical Validation of a Virtual Planner for Coronary Interventions Based on Coronary CT Angiography.

BACKGROUND: Low fractional flow reserve (FFR) values after percutaneous coronary intervention (PCI) carry a worse prognosis than high post-PCI FFR values. Therefore, the ability to predict post-PCI FFR might play an important role in procedural planning. Post-PCI FFR values can now be computed from pre-PCI coronary computed tomography angiography (CTA) using the fractional flow reserve derived from coronary computed tomography angiography revascularization planner (FFRCT Planner). OBJECTIVES: The aim of this study was to validate the accuracy of the FFRCT Planner. METHODS: In this multicenter, investigator-initiated, prospective study, patients with chronic coronary syndromes and significant lesions based on invasive FFR ≤0.80 were recruited. The FFRCT Planner was applied to the fractional flow reserve derived from coronary computed tomography angiography (FFRCT) model, simulating PCI. The primary objective was the agreement between the predicted post-PCI FFR by the FFRCT Planner and measured post-PCI FFR. Accuracy of the FFRCT Planner's luminal dimensions was assessed by using post-PCI optical coherence tomography as the reference. RESULTS: Overall, 259 patients were screened, with 120 patients (123 vessels) included in the final analysis. The mean patient age was 64 ± 9 years, and 24% had diabetes. Measured FFR post-PCI was 0.88 ± 0.06, and the FFRCT Planner FFR was 0.86 ± 0.06 (mean difference: 0.02 ± 0.07 FFR unit; limits of agreement: -0.12 to 0.15). Optical coherence tomography minimal stent area was 5.60 ± 2.01 mm2, and FFRCT Planner minimal stent area was 5.0 ± 2.2 mm2 (mean difference: 0.66 ± 1.21 mm2; limits of agreement: -1.7 to 3.0). The accuracy and precision of the FFRCT Planner remained high in cases with focal and diffuse disease and with low and high calcium burden. CONCLUSIONS: The FFRCT-based technology was accurate and precise for predicting FFR after PCI. (Precise Percutaneous Coronary Intervention Plan Study [P3]; NCT03782688).