Efficacy of 3D-multidetector computed tomography and fluoroscopy fusion for percutaneous left atrial appendage occlusion procedures.

INTRODUCTION: We studied the impact of the use of three-dimensional multidetector computed tomography (3D-MDCT) and fluoroscopy fusion on percutaneous left atrial appendage occlusion (LAAO) procedures in relation to procedure time, contrast volume, fluoroscopy time, and total radiation. METHODS: This was a single-center, prospective, single-blinded, randomized control trial. Patients meeting criteria for LAAO were randomized to undergo LAAO with the WATCHMAN FLXTM device with and without 3D-MDCT-fluoroscopy fusion guidance using a prespecified protocol using computed tomography angiography for WATCHMAN FLXTM sizing, moderate sedation, and intracardiac echocardiography for procedural guidance. RESULTS: Overall, 59 participants were randomly assigned to the fusion (n = 33) or no fusion (n = 26) groups. The median (interquartile range) age was 79 (75-83) years, 24 (41%) were female, and 55 (93%) were Caucasian. The median CHA2 DS2 VASc and HASBLED scores were 5 (4-6) and 3 (3-4), respectively. At the time of the study, 51 (53%) patients were on a direct acting oral anticoagulant. There were no significant differences between the fusion and no fusion groups in procedure time (52.4 ± 15.4 vs. 56.8 ± 19.5 min, p = .36), mean contrast volume used (33.8 ± 12.0 vs. 29.6 ± 11.5 mls, p = .19), mean fluoroscopy time (31.3 ± 9.9 vs. 28.9 ± 8.7 min, p = .32), mean radiation dose (1177 ± 969 vs. 1091 ± 692 mGy, p = .70), and radiation dose product curve (23.9 ± 20.5 vs. 35.0 ± 49.1 Gy cm2 , p = .29). There was no periprosthetic leak in the two groups in the immediate 1-month postprocedure follow-up periods. CONCLUSIONS: There was no significant difference with and without 3D-MDCT-fluoroscopy fusion in procedure time, contrast volume use, radiation dose, and radiation dose product.

Predictors of successful same-day discharge and 1-year outcomes after left atrial appendage closure.

BACKGROUND: Same-day discharge (SDD) following left atrial appendage closure (LAAC) is increasingly common but predictors of successful SDD and 1-year clinical outcomes have not been described. OBJECTIVE: The purpose of this study was to explore predictors of successful SDD and report 1-year outcomes in patients undergoing LAAC with SDD. METHODS: A prospective analysis was performed over a 20-month period of 225 consecutive patients that underwent LAAC in a large, academic hospital. All patients included in the study underwent a SDD protocol. Baseline characteristics and 1-year outcomes of patients discharged same day of the procedure versus those that required at least one overnight stay were compared. Adverse events, procedural success, and procedure times were evaluated. RESULTS: One hundred and sixty-one patients (72%) of patients were discharged the same day and 64 patients (28%) required at least an overnight stay (non-SDD: NSDD). NSDD patients were older and more often female. Procedure time was also longer in the NSDD group than in the SDD (63.4 vs. 55.1 min; p = 0.01). While overall procedural success rates were similar between the SDD and NSDD groups (99.4% vs. 98.4%; p = 0.39), NSDD patients had more complications (9.4% vs. 0%; p = 0.01) and higher number of devices per procedure (1.2 vs. 1.0; p = 0.01) as compared to SDD. At 1 year, there were no significant difference between the SDD and NSDD groups in stroke (1.1% vs. 0%; log-rank p = 0.44) and all-cause mortality (3.9% vs. 4.7%; log-rank p = 0.70). CONCLUSION: In this single-center LAAC experience, female sex, older age, and longer procedure duration were associated with higher likelihood for need of overnight stay. At 1-year follow-up, there were no significant differences in stroke events and death rates between SDD and NSDD groups.

A benchmark in the isolated tricuspid valve surgery is necessary.

Advances in surgical techniques, enabling correction of regurgitation, and preserving the tricuspid valve, are also factors that encourage early surgical indication and improve long-term outcomes.

Increased number of ventricular septal rupture cases after acute myocardial infarction in 2020.

INTRODUCTION: Ventricular septal rupture (VSR) is a serious mechanical complication after acute coronary syndrome and is related to high mortality. Even with advances in the management of acute myocardial infarction (AMI) such as reperfusion therapies, complication rates are still high. During quarantine, patients presenting mechanical complications after AMI have increased in our institution. METHODS: From a retrospective database analysis in our institution between the years 2004 and 2020, we identified 37 cases of VSR after AMI. Four chronic cases were excluded from our analysis. The primary endpoint was to identify baseline characteristics that increased 30-day mortality. RESULTS: Among 33 acute cases of VSR, 24 cases were submitted to surgery. The 30-day mortality of the operated patients was 45.8%. From 2004 to 2019 our average number of operations of VSR was 1.9 cases/year with an increase to 4 cases/year in 2020. Diabetes mellitus, age, cardiogenic shock, and use of intra-aortic balloon pump were associated with significantly increased mortality using logistic regression. CONCLUSION: We reported an increased number of mechanical complication cases from April to September 2020, compared to our historical records. Despite therapeutic advances, mortality rates remain high. Although the number of cases is small to conclude that the pandemic was responsible for this augmentation, we believe that it is related to the decreased number of patients seeking medical assistance.

The arrival of COVID-19 in Brazil and the impact on coronary artery bypass surgery.

BACKGROUND AND AIM OF THE STUDY: This study analyzed the arrival of coronavirus disease 2019 (COVID-19) in Brazil and its impact on coronary artery bypass grafting (CABG) surgery. METHODS: Patients undergoing isolated CABG in six hospitals in Brazil were divided into two periods: pre-COVID-19 (March-May 2019, N = 468) and COVID-19 era (March-May 2020, N = 182). Perioperative data were included on a dedicated REDCap platform. Patients with clinical and tomographic criteria and/or PCR (+) for severe acute respiratory syndrome coronavirus 2 infection were considered COVID-19 (+). Logistic regression analysis was performed to create a multiple predictive model for mortality after CABG in COVID-19 era. RESULTS: Compared to 2019, in 2020, CABG surgeries had a 2.8-fold increased mortality risk (95% confidence interval [CI]: 1-7.6, p = .041), patients who evolved with COVID-19 had a 11-fold increased mortality risk (95% CI: 2.2-54.9, p < .003), rates of morbidities and readmission to the intensive care unit. The surgical volume was decreased by 60%. The model to predict mortality after CABG in the COVID-19 era was validated with good calibration (Hosmer-Lemeshow = 1.43) and discrimination (receiver operating characteristic = 0.78). CONCLUSION: The COVID-19 pandemic had an adverse impact on mortality, morbidity and volume of patients undergoing CABG.

The impact of ligation of proximal side branches on blood flow and functional status of the internal thoracic artery in coronary anastomosis.

BACKGROUND: The effect of proximal side branches on the patency of the internal thoracic artery (ITA) is controversial. We used echocardiography and Doppler to verify the effect of ligation of branches on the flow and coronary flow reserve (CFR) of the grafted ITA in patients after coronary artery bypass grafting (CABG). METHODS: We prospectively investigated 53 patients with preserved left ventricular ejection fraction (LVEF >50%) who underwent CABG of the ITA. In Group I (25 patients), major branches were ligated during ITA anastomosis to the left anterior descending (LAD) coronary artery, whereas no ligation was performed in Group II (28 patients). Systolic flow (SF), diastolic flow (DF), and total flow (TF = SF + DF) were measured by Doppler echocardiography at the proximal level of the ITA preoperatively, at early postoperative stage, and 6 months after surgery. Dobutamine stress echocardiography (DSE) was performed at 6 months to determine CFR. RESULTS: The ITA flow was predominantly systolic before surgery and diastolic in the postoperative period. We found no differences between the groups in DF. On DSE, SF (19.5±9 mL/min vs 32.7±19 mL/min; P=.003) and TF (79±21 mL/min vs 101±47 mL/min; P=.037) were higher in Group II. There were no differences in CFR (1.9±0.46 vs 2.11±0.56; P=.143). CONCLUSION: In patients with preserved LVEF, ligation of major side branches during anastomosis to the LAD does not alter ITA flow or CFR.

Plaque Characteristics Derived from Intravascular Optical Coherence Tomography That Predict Cardiovascular Death.

This study aimed to investigate whether plaque characteristics derived from intravascular optical coherence tomography (IVOCT) could predict a long-term cardiovascular (CV) death. This study was a single-center, retrospective study on 104 patients who had undergone IVOCT-guided percutaneous coronary intervention. Plaque characterization was performed using Optical Coherence TOmography PlaqUe and Stent (OCTOPUS) software developed by our group. A total of 31 plaque features, including lesion length, lumen, calcium, fibrous cap (FC), and vulnerable plaque features (e.g., microchannel), were computed from the baseline IVOCT images. The discriminatory power for predicting CV death was determined using univariate/multivariate logistic regressions. Of 104 patients, CV death was identified in 24 patients (23.1%). Univariate logistic regression revealed that lesion length, calcium angle, calcium thickness, FC angle, FC area, and FC surface area were significantly associated with CV death (p < 0.05). In the multivariate logistic analysis, only the FC surface area (OR 2.38, CI 0.98-5.83, p < 0.05) was identified as a significant determinant for CV death, highlighting the importance of the 3D lesion analysis. The AUC of FC surface area for predicting CV death was 0.851 (95% CI 0.800-0.927, p < 0.05). Patients with CV death had distinct plaque characteristics (i.e., large FC surface area) in IVOCT. Studies such as this one might someday lead to recommendations for pharmaceutical and interventional approaches.

Deep learning segmentation of fibrous cap in intravascular optical coherence tomography images.

Thin-cap fibroatheroma (TCFA) is a prominent risk factor for plaque rupture. Intravascular optical coherence tomography (IVOCT) enables identification of fibrous cap (FC), measurement of FC thicknesses, and assessment of plaque vulnerability. We developed a fully-automated deep learning method for FC segmentation. This study included 32,531 images across 227 pullbacks from two registries (TRANSFORM-OCT and UHCMC). Images were semi-automatically labeled using our OCTOPUS with expert editing using established guidelines. We employed preprocessing including guidewire shadow detection, lumen segmentation, pixel-shifting, and Gaussian filtering on raw IVOCT (r,θ) images. Data were augmented in a natural way by changing θ in spiral acquisitions and by changing intensity and noise values. We used a modified SegResNet and comparison networks to segment FCs. We employed transfer learning from our existing much larger, fully-labeled calcification IVOCT dataset to reduce deep-learning training. Postprocessing with a morphological operation enhanced segmentation performance. Overall, our method consistently delivered better FC segmentation results (Dice: 0.837 ± 0.012) than other deep-learning methods. Transfer learning reduced training time by 84% and reduced the need for more training samples. Our method showed a high level of generalizability, evidenced by highly-consistent segmentations across five-fold cross-validation (sensitivity: 85.0 ± 0.3%, Dice: 0.846 ± 0.011) and the held-out test (sensitivity: 84.9%, Dice: 0.816) sets. In addition, we found excellent agreement of FC thickness with ground truth (2.95 ± 20.73 µm), giving clinically insignificant bias. There was excellent reproducibility in pre- and post-stenting pullbacks (average FC angle: 200.9 ± 128.0°/202.0 ± 121.1°). Our fully automated, deep-learning FC segmentation method demonstrated excellent performance, generalizability, and reproducibility on multi-center datasets. It will be useful for multiple research purposes and potentially for planning stent deployments that avoid placing a stent edge over an FC.

OCTOPUS - Optical coherence tomography plaque and stent analysis software.

Background and objective: Compared with other imaging modalities, intravascular optical coherence tomography (IVOCT) has significant advantages for guiding percutaneous coronary interventions, assessing their outcomes, and characterizing plaque components. To aid IVOCT research studies, we developed the Optical Coherence TOmography PlaqUe and Stent (OCTOPUS) analysis software, which provides highly automated, comprehensive analysis of coronary plaques and stents in IVOCT images. Methods: User specifications for OCTOPUS were obtained from detailed, iterative discussions with IVOCT analysts in the Cardiovascular Imaging Core Laboratory at University Hospitals Cleveland Medical Center, a leading laboratory for IVOCT image analysis. To automate image analysis results, the software includes several important algorithmic steps: pre-processing, deep learning plaque segmentation, machine learning identification of stent struts, and registration of pullbacks for sequential comparisons. Intuitive, interactive visualization and manual editing of segmentations were included in the software. Quantifications include stent deployment characteristics (e.g., stent area and stent strut malapposition), strut level analysis, calcium angle, and calcium thickness measurements. Interactive visualizations include (x,y) anatomical, en face, and longitudinal views with optional overlays (e.g., segmented calcifications). To compare images over time, linked visualizations were enabled to display up to four registered vessel segments at a time. Results: OCTOPUS has been deployed for nearly 1 year and is currently being used in multiple IVOCT studies. Underlying plaque segmentation algorithm yielded excellent pixel-wise results (86.2% sensitivity and 0.781 F1 score). Using OCTOPUS on 34 new pullbacks, we determined that following automated segmentation, only 13% and 23% of frames needed any manual touch up for detailed lumen and calcification labeling, respectively. Only up to 3.8% of plaque pixels were modified, leading to an average editing time of only 7.5 s/frame, an approximately 80% reduction compared to manual analysis. Regarding stent analysis, sensitivity and precision were both greater than 90%, and each strut was successfully classified as either covered or uncovered with high sensitivity (94%) and specificity (90%). We demonstrated use cases for sequential analysis. To analyze plaque progression, we loaded multiple pullbacks acquired at different points (e.g., pre-stent, 3-month follow-up, and 18-month follow-up) and evaluated frame-level development of in-stent neo-atherosclerosis. In ex vivo cadaver experiments, the OCTOPUS software enabled visualization and quantitative evaluation of irregular stent deployment in the presence of calcifications identified in pre-stent images. Conclusions: We introduced and evaluated the clinical application of a highly automated software package, OCTOPUS, for quantitative plaque and stent analysis in IVOCT images. The software is currently used as an offline tool for research purposes; however, the software's embedded algorithms may also be useful for real-time treatment planning.

Prediction of stent under-expansion in calcified coronary arteries using machine learning on intravascular optical coherence tomography images.

It can be difficult/impossible to fully expand a coronary artery stent in a heavily calcified coronary artery lesion. Under-expanded stents are linked to later complications. Here we used machine/deep learning to analyze calcifications in pre-stent intravascular optical coherence tomography (IVOCT) images and predicted the success of vessel expansion. Pre- and post-stent IVOCT image data were obtained from 110 coronary lesions. Lumen and calcifications in pre-stent images were segmented using deep learning, and lesion features were extracted. We analyzed stent expansion along the lesion, enabling frame, segmental, and whole-lesion analyses. We trained regression models to predict the post-stent lumen area and then computed the stent expansion index (SEI). Best performance (root-mean-square-error = 0.04 ± 0.02 mm2, r = 0.94 ± 0.04, p < 0.0001) was achieved when we used features from both lumen and calcification to train a Gaussian regression model for segmental analysis of 31 frames in length. Stents with minimum SEI > 80% were classified as "well-expanded;" others were "under-expanded." Under-expansion classification results (e.g., AUC = 0.85 ± 0.02) were significantly improved over a previous, simple calculation, as well as other machine learning solutions. Promising results suggest that such methods can identify lesions at risk of under-expansion that would be candidates for intervention lesion preparation (e.g., atherectomy).

First-in-Human Multicenter Experience of the Newest Generation Supra-Annular Self-Expanding Evolut FX TAVR System.

BACKGROUND: The latest-generation Evolut FX TAVR system (Medtronic) offers several potential design improvements over its predecessors, but early reported experience has been limited. OBJECTIVES: This study sought to report our multicenter, limited market release, first-in-human experience of transcatheter aortic valve replacement (TAVR) with the Evolut FX system and compare it with a single-center PRO+ (Medtronic) experience. METHODS: From June 27 to September 16, 2022, 226 consecutive patients from 9 US centers underwent transfemoral TAVR with the Evolut FX system for native aortic stenosis (89.4%) or prosthetic valve degeneration (10.6%). Commissural alignment was defined as 0° to 30° between native and FX commissures. Patient, anatomical, and procedural characteristics were retrospectively reviewed, and 30-day clinical and echocardiographic outcomes per Valve Academic Research Consortium-3 definitions were reported. RESULTS: Of 226 patients, 34.1% were low risk, 4% had a bicuspid valve, and 11.5% had a horizontal root (≥60°). Direct Inline sheath (Medtronic) was used in 67.6% and Lunderquist stiff wire (Cook Medical) in 35.4% of cases. Optimal hat marker orientation during deployment was achieved in 98.4%, with commissural alignment in 96.5%. At 30 days, 14.3% mild, 0.9% moderate, and no severe paravalvular leak were observed. Compared with the Evolut PRO+ experience from 1 center, FX had a more symmetrical implantation with shallower depth at the left coronary cusp (P < 0.001), fewer device recaptures (26.1% vs 39.5%; P = 0.004), and improved commissural alignment (96.5% vs 80.2%; P < 0.001). CONCLUSIONS: The Evolut FX system demonstrated favorable 30-day outcomes with a significant improvement over PRO+ in achieving commissural alignment, fewer device recaptures, and more symmetrical implantation. These features may benefit younger patients undergoing TAVR with the supra-annular, self-expanding valve, where lifetime management would be important.

Hypotheses, rationale, design, and methods for prognostic evaluation of cardiac biomarker elevation after percutaneous and surgical revascularization in the absence of manifest myocardial infarction. A comparative analysis of biomarkers and cardiac magnetic resonance. The MASS-V Trial.

BACKGROUND: Although the release of cardiac biomarkers after percutaneous (PCI) or surgical revascularization (CABG) is common, its prognostic significance is not known. Questions remain about the mechanisms and degree of correlation between the release, the volume of myocardial tissue loss, and the long-term significance. Delayed-enhancement of cardiac magnetic resonance (CMR) consistently quantifies areas of irreversible myocardial injury. To investigate the quantitative relationship between irreversible injury and cardiac biomarkers, we will evaluate the extent of irreversible injury in patients undergoing PCI and CABG and relate it to postprocedural modifications in cardiac biomarkers and long-term prognosis. METHODS/DESIGN: The study will include 150 patients with multivessel coronary artery disease (CAD) with left ventricle ejection fraction (LVEF) and a formal indication for CABG; 50 patients will undergo CABG with cardiopulmonary bypass (CPB); 50 patients with the same arterial and ventricular condition indicated for myocardial revascularization will undergo CABG without CPB; and another 50 patients with CAD and preserved ventricular function will undergo PCI using stents. All patients will undergo CMR before and after surgery or PCI. We will also evaluate the release of cardiac markers of necrosis immediately before and after each procedure. Primary outcome considered is overall death in a 5-year follow-up. Secondary outcomes are levels of CK-MB isoenzyme and I-Troponin in association with presence of myocardial fibrosis and systolic left ventricle dysfunction assessed by CMR. DISCUSSION: The MASS-V Trial aims to establish reliable values for parameters of enzyme markers of myocardial necrosis in the absence of manifest myocardial infarction after mechanical interventions. The establishments of these indices have diagnostic value and clinical prognosis and therefore require relevant and different therapeutic measures. In daily practice, the inappropriate use of these necrosis markers has led to misdiagnosis and therefore wrong treatment. The appearance of a more sensitive tool such as CMR provides an unprecedented diagnostic accuracy of myocardial damage when correlated with necrosis enzyme markers. We aim to correlate laboratory data with imaging, thereby establishing more refined data on the presence or absence of irreversible myocardial injury after the procedure, either percutaneous or surgical, and this, with or without the use of cardiopulmonary bypass.

Automated analysis of fibrous cap in intravascular optical coherence tomography images of coronary arteries.

Thin-cap fibroatheroma (TCFA) and plaque rupture have been recognized as the most frequent risk factor for thrombosis and acute coronary syndrome. Intravascular optical coherence tomography (IVOCT) can identify TCFA and assess cap thickness, which provides an opportunity to assess plaque vulnerability. We developed an automated method that can detect lipidous plaque and assess fibrous cap thickness in IVOCT images. This study analyzed a total of 4360 IVOCT image frames of 77 lesions among 41 patients. Expert cardiologists manually labeled lipidous plaque based on established criteria. To improve segmentation performance, preprocessing included lumen segmentation, pixel-shifting, and noise filtering on the raw polar (r, θ) IVOCT images. We used the DeepLab-v3 plus deep learning model to classify lipidous plaque pixels. After lipid detection, we automatically detected the outer border of the fibrous cap using a special dynamic programming algorithm and assessed the cap thickness. Our method provided excellent discriminability of lipid plaque with a sensitivity of 85.8% and A-line Dice coefficient of 0.837. By comparing lipid angle measurements between two analysts following editing of our automated software, we found good agreement by Bland-Altman analysis (difference 6.7° ± 17°; mean ~ 196°). Our method accurately detected the fibrous cap from the detected lipid plaque. Automated analysis required a significant modification for only 5.5% frames. Furthermore, our method showed a good agreement of fibrous cap thickness between two analysts with Bland-Altman analysis (4.2 ± 14.6 µm; mean ~ 175 µm), indicating little bias between users and good reproducibility of the measurement. We developed a fully automated method for fibrous cap quantification in IVOCT images, resulting in good agreement with determinations by analysts. The method has great potential to enable highly automated, repeatable, and comprehensive evaluations of TCFAs.

Automatic microchannel detection using deep learning in intravascular optical coherence tomography images.

Microchannel formation is known to be a significant marker of plaque vulnerability, plaque rupture, and intraplaque hemorrhage, which are responsible for plaque progression. We developed a fully-automated method for detecting microchannels in intravascular optical coherence tomography (IVOCT) images using deep learning. A total of 3,075 IVOCT image frames across 41 patients having 62 microchannel segments were analyzed. Microchannel was manually annotated by expert cardiologists, according to previously established criteria. In order to improve segmentation performance, pre-processing including guidewire detection/removal, lumen segmentation, pixel-shifting, and noise filtering was applied to the raw (r,θ) IVOCT image. We used the DeepLab-v3 plus deep learning model with the Xception backbone network for identifying microchannel candidates. After microchannel candidate detection, each candidate was classified as either microchannel or no-microchannel using a convolutional neural network (CNN) classification model. Our method provided excellent segmentation of microchannel with a Dice coefficient of 0.811, sensitivity of 92.4%, and specificity of 99.9%. We found that pre-processing and data augmentation were very important to improve results. In addition, a CNN classification step was also helpful to rule out false positives. Furthermore, automated analysis missed only 3% of frames having microchannels and showed no false positives. Our method has great potential to enable highly automated, objective, repeatable, and comprehensive evaluations of vulnerable plaques and treatments. We believe that this method is promising for both research and clinical applications.

Decision-Making During Percutaneous Coronary Intervention Guided by Optical Coherence Tomography: Insights From the LightLab Initiative.

BACKGROUND: Use of intracoronary imaging is associated with improved outcomes in patients undergoing percutaneous coronary intervention (PCI). Yet, the impact of intracoronary imaging on real-time physician decision-making during PCI is not fully known. METHODS: The LightLab Initiative is a multicenter, prospective, observational study designed to characterize the use of a standardized optical coherence tomography (OCT) workflow during PCI. Participating physicians performed pre-PCI and post-PCI OCT in accordance with this workflow and operator assessments of lesion characteristics and treatment plan were recorded for each lesion based on angiography alone and following OCT. Physicians were categorized as having low (n=15), intermediate (n=13), or high (n=14) OCT use in the year preceding participation. RESULTS: Among 925 patients with 1328 lesions undergoing PCI, the prescribed OCT workflow was followed in 773 (84%) of patients with 836 lesions. Operator lesion assessment and decision-making during PCI changed with OCT use in 86% (721/836) of lesions. Pre-PCI OCT use changed operator decision-making in 80% of lesions, including lesion assessment (45%), vessel preparation strategy (27%), stent diameter (37%), and stent length (36%). Post-PCI OCT changed stent optimization decision-making in 31% of lesions. These findings were consistent across strata of physician prior OCT experience. CONCLUSIONS: A standardized OCT workflow impacted PCI decision-making in 86% of lesions, with a predominant effect on pre-PCI lesion assessment and planning of treatment strategy. This finding was consistent regardless of operator experience level and provides insight into mechanisms by which intravascular imaging might improve PCI outcomes.

Automated Segmentation of Microvessels in Intravascular OCT Images Using Deep Learning.

Microvessels in vascular plaque are associated with plaque progression and are found in plaque rupture and intra-plaque hemorrhage. To analyze this characteristic of vulnerability, we developed an automated deep learning method for detecting microvessels in intravascular optical coherence tomography (IVOCT) images. A total of 8403 IVOCT image frames from 85 lesions and 37 normal segments were analyzed. Manual annotation was performed using a dedicated software (OCTOPUS) previously developed by our group. Data augmentation in the polar (r,θ) domain was applied to raw IVOCT images to ensure that microvessels appear at all possible angles. Pre-processing methods included guidewire/shadow detection, lumen segmentation, pixel shifting, and noise reduction. DeepLab v3+ was used to segment microvessel candidates. A bounding box on each candidate was classified as either microvessel or non-microvessel using a shallow convolutional neural network. For better classification, we used data augmentation (i.e., angle rotation) on bounding boxes with a microvessel during network training. Data augmentation and pre-processing steps improved microvessel segmentation performance significantly, yielding a method with Dice of 0.71 ± 0.10 and pixel-wise sensitivity/specificity of 87.7 ± 6.6%/99.8 ± 0.1%. The network for classifying microvessels from candidates performed exceptionally well, with sensitivity of 99.5 ± 0.3%, specificity of 98.8 ± 1.0%, and accuracy of 99.1 ± 0.5%. The classification step eliminated the majority of residual false positives and the Dice coefficient increased from 0.71 to 0.73. In addition, our method produced 698 image frames with microvessels present, compared with 730 from manual analysis, representing a 4.4% difference. When compared with the manual method, the automated method improved microvessel continuity, implying improved segmentation performance. The method will be useful for research purposes as well as potential future treatment planning.

Neoatherosclerosis prediction using plaque markers in intravascular optical coherence tomography images.

Introduction: In-stent neoatherosclerosis has emerged as a crucial factor in post-stent complications including late in-stent restenosis and very late stent thrombosis. In this study, we investigated the ability of quantitative plaque characteristics from intravascular optical coherence tomography (IVOCT) images taken just prior to stent implantation to predict neoatherosclerosis after implantation. Methods: This was a sub-study of the TRiple Assessment of Neointima Stent FOrmation to Reabsorbable polyMer with Optical Coherence Tomography (TRANSFORM-OCT) trial. Images were obtained before and 18 months after stent implantation. Final analysis included images of 180 lesions from 90 patients; each patient had images of two lesions in different coronary arteries. A total of 17 IVOCT plaque features, including lesion length, lumen (e.g., area and diameter); calcium (e.g., angle and thickness); and fibrous cap (FC) features (e.g., thickness, surface area, and burden), were automatically extracted from the baseline IVOCT images before stenting using dedicated software developed by our group (OCTOPUS). The predictive value of baseline IVOCT plaque features for neoatherosclerosis development after stent implantation was assessed using univariate/multivariate logistic regression and receiver operating characteristic (ROC) analyses. Results: Follow-up IVOCT identified stents with (n = 19) and without (n = 161) neoatherosclerosis. Greater lesion length and maximum calcium angle and features related to FC were associated with a higher prevalence of neoatherosclerosis after stent implantation (p < 0.05). Hierarchical clustering identified six clusters with the best prediction p-values. In univariate logistic regression analysis, maximum calcium angle, minimum calcium thickness, maximum FC angle, maximum FC area, FC surface area, and FC burden were significant predictors of neoatherosclerosis. Lesion length and features related to the lumen were not significantly different between the two groups. In multivariate logistic regression analysis, only larger FC surface area was strongly associated with neoatherosclerosis (odds ratio 1.38, 95% confidence interval [CI] 1.05-1.80, p < 0.05). The area under the ROC curve was 0.901 (95% CI 0.859-0.946, p < 0.05) for FC surface area. Conclusion: Post-stent neoatherosclerosis can be predicted by quantitative IVOCT imaging of plaque characteristics prior to stent implantation. Our findings highlight the additional clinical benefits of utilizing IVOCT imaging in the catheterization laboratory to inform treatment decision-making and improve outcomes.

Assessment of Post-Dilatation Strategies for Optimal Stent Expansion in Calcified Coronary Lesions: Ex Vivo Analysis With Optical Coherence Tomography.

INTRODUCTION: Interventional cardiologists make adjustments in the presence of coronary calcifications known to limit stent expansion, but proper balloon sizing, plaque-modification approaches, and high-pressure regimens are not well established. Intravascular optical coherence tomography (IVOCT) provides high-resolution images of coronary tissues, including detailed imaging of calcifications, and accurate measurements of stent deployment, providing a means for detailed study of stent deployment. OBJECTIVE: Evaluate stent expansion in an ex vivo model of calcified coronary arteries as a function of balloon size and high-pressure, post-dilatation strategies. METHODS: We conducted experiments on cadaver hearts with calcified coronary lesions. We assessed stent expansion as a function of size and pressure of non-compliant (NC) balloons (i.e., nominal, 0.5, 1.0, and 1.5 mm balloons at 10, 20 and 30 atm). IVOCT images were acquired pre-stent, post-stent, and at all post-dilatations. Stent expansion was calculated using minimum expansion index (MEI). RESULTS: We analyzed 134 IVOCT pullbacks from ten ex-vivo experiments. The mean distal and proximal reference lumen diameters were 2.2 ± 0.5 mm and 2.5 ± 0.7 mm, respectively, 80% of times using a 3.0 mm diameter stent. Overall, based on stent sizing, a good expansion (MEI ≥ 80%) was reached using the 1:1 NC balloon at 20 atm, and expansion > 100% was reached using the 1:1 NC balloon at 30 atm. In the subgroup analysis, comparing low-calcified and high-calcified lesions, good expansion (MEI ≥ 80%) was reached using the 1:1 NC balloon at nominal pressure (10 atm) versus using 1:1 NC balloon at 30 atm, respectively. Significant vessel rupture was identified in all the vessels mainly upon post-dilatation with larger balloons, and 60% of the experiments (6 vessels, 3 in each calcium subgroup) presented rupture with the +1.0 mm NC balloon at 20 atm. CONCLUSION: When treating calcified lesions, good stent expansion was reached using smaller balloons at higher pressures without coronary injuries, whereas bigger balloons yielded unpredictable expansion even at lower pressures and demonstrated potential harmful damages to the vessels. As these findings could help physicians with appropriate planning of stent post-dilatation for calcified lesions, it will be important to clinically evaluate the recommended protocol.

Mechanical performances of balloon post-dilation for improving stent expansion in calcified coronary artery: Computational and experimental investigations.

Stent deployment in a calcified coronary artery is often associated with suboptimal outcomes such as stent underexpansion and malapposition. Post-dilation after stent deployment is commonly used for optimal stent implantation. There is no guideline for choosing the post-dilation balloon diameter and inflation pressure. In this work, ex-vivo/in-silico experiments were performed to investigate the efficacy of post-dilation balloon diameter and inflation pressure in improving the stent expansion in a calcified lesion. Post-dilations with three balloon diameters (3 mm, 3.5 mm, and 4 mm) were performed. For each balloon diameter, three inflation pressures (10 atm, 20 atm, and 30 atm) were sequentially applied. In ex-vivo experiments, optical coherence tomography images were acquired during the stenting procedure, i.e., pre- and post-deployment of 3 mm diameter stent, as well as after each post-dilation. The results from in-silico experiments were compared with ex-vivo experiments in terms of lumen area. In addition, stretch ratio analysis was developed to predict the stent-induced lumen area, along with the strain analysis and the in-silico experiments. Results have shown that target lumen area could be achieved with an oversized nominal balloon diameter of +0.5 mm (i.e., 0.5 mm greater than reference lumen diameter) at an inflation pressure of 20 atm. After each post-dilation, fibrotic tissue demonstrated a larger strain, contributing to improved lumen gain. However, minimal changes were observed in calcification. Moreover, a strong correlation (R2 = 0.95) between the stretch ratio of fibrotic tissue and lumen area after each post-dilation was observed. This indicated that the morphology of the fibrotic tissue could be a potential marker to predict the lumen gain. The detailed mechanistic quantifications of a single lesion cannot be generalized to all clinical cases. However, this work could be used to provide a fundamental understanding of the post-dilations, to develop experimental protocols for producing generalized guidelines, and to exploit their potential for optimal pre- and post-stent strategies.