Cross-sectional angle prediction of lipid-rich and calcified tissue on computed tomography angiography images.

PURPOSE: The assessment of vulnerable plaque characteristics and distribution is important to stratify cardiovascular risk in a patient. Computed tomography angiography (CTA) offers a promising alternative to invasive imaging but is limited by the fact that the range of Hounsfield units (HU) in lipid-rich areas overlaps with the HU range in fibrotic tissue and that the HU range of calcified plaques overlaps with the contrast within the contrast-filled lumen. This paper is to investigate whether lipid-rich and calcified plaques can be detected more accurately on cross-sectional CTA images using deep learning methodology. METHODS: Two deep learning (DL) approaches are proposed, a 2.5D Dense U-Net and 2.5D Mask-RCNN, which separately perform the cross-sectional plaque detection in the Cartesian and polar domain. The spread-out view is used to evaluate and show the prediction result of the plaque regions. The accuracy and F1-score are calculated on a lesion level for the DL and conventional plaque detection methods. RESULTS: For the lipid-rich plaques, the median and mean values of the F1-score calculated by the two proposed DL methods on 91 lesions were approximately 6 and 3 times higher than those of the conventional method. For the calcified plaques, the F1-score of the proposed methods was comparable to those of the conventional method. The median F1-score of the Dense U-Net-based method was 3% higher than that of the conventional method. CONCLUSION: The two methods proposed in this paper contribute to finer cross-sectional predictions of lipid-rich and calcified plaques compared to studies focusing only on longitudinal prediction. The angular prediction performance of the proposed methods outperforms the convincing conventional method for lipid-rich plaque and is comparable for calcified plaque.

The effect of CTCA guided selective invasive graft assessment on coronary angiographic parameters and outcomes: Insights from the BYPASS-CTCA trial.

BACKGROUND: Computed tomography cardiac angiography (CTCA) is recommended for the evaluation of patients with prior coronary artery bypass graft (CABG) surgery. The BYPASS-CTCA study demonstrated that CTCA prior to invasive coronary angiography (ICA) in CABG patients leads to significant reductions in procedure time and contrast-induced nephropathy (CIN), alongside improved patient satisfaction. However, whether CTCA information was used to facilitate selective graft cannulation at ICA was not protocol mandated. In this post-hoc analysis we investigated the influence of CTCA facilitated selective graft assessment on angiographic parameters and study endpoints. METHODS: BYPASS-CTCA was a randomized controlled trial in which patients with previous CABG referred for ICA were randomized to undergo CTCA prior to ICA, or ICA alone. In this post-hoc analysis we assessed the impact of selective ICA (grafts not invasively cannulated based on the CTCA result) following CTCA versus non-selective ICA (imaging all grafts irrespective of CTCA findings). The primary endpoints were ICA procedural duration, incidence of CIN, and patient satisfaction post-ICA. Secondary endpoints included the incidence of procedural complications and 1-year major adverse cardiac events. RESULTS: In the CTCA cohort (n â€‹= â€‹343), 214 (62.4%) patients had selective coronary angiography performed, whereas 129 (37.6%) patients had non-selective ICA. Procedure times were significantly reduced in the selective CTCA â€‹+ â€‹ICA group compared to the non-selective CTCA â€‹+ â€‹ICA group (-5.82min, 95% CI -7.99 to -3.65, p â€‹< â€‹0.001) along with reduction of CIN (1.5% vs 5.8%, OR 0.26, 95% CI 0.10 to 0.98). No difference was seen in patient satisfaction with the ICA, however procedural complications (0.9% vs 4.7%, OR 0.21, 95% CI 0.09-0.87) and 1-year major adverse cardiac events (13.1% vs 20.9%, HR 0.55, 95% CI 0.32-0.96) were significantly lower in the selective group. CONCLUSIONS: In patients with prior CABG, CTCA guided selective angiographic assessment of bypass grafts is associated with improved procedural parameters, lower complication rates and better 12-month outcomes. Taken in addition to the main findings of the BYPASS-CTCA trial, these results suggest a synergistic approach between CTCA and ICA should be considered in this patient group. REGISTRATION: ClinicalTrials.gov, NCT03736018.

Comparison of endothelial shear stress between ultrathin strut bioresorbable polymer drug-eluting stent vs durable-polymer drug-eluting stent post-stent implantation: An optical coherence tomography substudy from BIOFLOW II.

BACKGROUND: Recent clinical data indicate a different performance of biodegradable polymer (BP)-drug eluting stent (DES) compared to durable polymer (DP)-DES. Whether this can be explained by a beneficial impact of BP-DES stent design on the local hemodynamic forces distribution remains unclear. OBJECTIVES: To compare endothelial shear stress (ESS) distribution after implantation of ultrathin (us) BP-DES and DP-DES and examine the association between ESS and neointimal thickness (NIT) distribution in the two devices at 9 months follow up. METHODS AND RESULTS: We retrospectively identified patients from the BIOFLOW II trial that had undergone OCT imaging. OCT data were utilized to reconstruct the surface of the stented segment at baseline and 9 months follow-up, simulate blood flow, and measure ESS and NIT in the stented segment. The patients were divided into 3 groups depending on whether DP-DES (N = 8, n = 56,160 sectors), BP-DES with a stent diameter of >3 mm (strut thickness of 80 µm, N = 6, n = 36,504 sectors), or BP-DES with a stent diameter of ≤3 mm (strut thickness of 60 µm, N = 8, n = 50,040 sectors) were used for treatment. The ESS, and NIT distribution and the association of these two variables were estimated and compared among the 3 groups. RESULTS: In the DP-DES group mean NIT was 0.18 ± 0.17 mm and ESS 1.68 ± 1.66 Pa; for the BP-DES ≤3 mm group the NIT was 0.17 ± 0.11 mm and ESS 1.49 ± 1.24 Pa and for the BP-DES >3 mm group 0.20 ± 0.23 mm and 1.42 ± 1.24 Pa respectively (p < 0.001 for both NIT and ESS comparisons across groups). A negative correlation between NIT and baseline ESS was found, the correlation coefficient for all the stented segments was -0.33, p < 0.001. CONCLUSION: In this OCT sub-study of the BIOFLOW II trial, the NIT was statistically different between groups of patients treated with BP-DES and DP-DES. In addition, regions of low ESS were associated with increased NIT in all studied devices.

Efficacy of human experts and an automated segmentation algorithm in quantifying disease pathology in coronary computed tomography angiography: A head-to-head comparison with intravascular ultrasound imaging.

BACKGROUND: Coronary computed tomography angiography (CCTA) analysis is currently performed by experts and is a laborious process. Fully automated edge-detection methods have been developed to expedite CCTA segmentation however their use is limited as there are concerns about their accuracy. This study aims to compare the performance of an automated CCTA analysis software and the experts using near-infrared spectroscopy-intravascular ultrasound imaging (NIRS-IVUS) as a reference standard. METHODS: Fifty-one participants (150 vessels) with chronic coronary syndrome who underwent CCTA and 3-vessel NIRS-IVUS were included. CCTA analysis was performed by an expert and an automated edge detection method and their estimations were compared to NIRS-IVUS at a segment-, lesion-, and frame-level. RESULTS: Segment-level analysis demonstrated a similar performance of the two CCTA analyses (conventional and automatic) with large biases and limits of agreement compared to NIRS-IVUS estimations for the total atheroma (ICC: 0.55 vs 0.25, mean difference:192 (-102-487) vs 243 (-132-617) and percent atheroma volume (ICC: 0.30 vs 0.12, mean difference: 12.8 (-5.91-31.6) vs 20.0 (0.79-39.2). Lesion-level analysis showed that the experts were able to detect more accurately lesions than the automated method (68.2 â€‹% and 60.7 â€‹%) however both analyses had poor reliability in assessing the minimal lumen area (ICC 0.44 vs 0.36) and the maximum plaque burden (ICC 0.33 vs 0.33) when NIRS-IVUS was used as the reference standard. CONCLUSIONS: Conventional and automated CCTA analyses had similar performance in assessing coronary artery pathology using NIRS-IVUS as a reference standard. Therefore, automated segmentation can be used to expedite CCTA analysis and enhance its applications in clinical practice.

Novel near-infrared spectroscopy-intravascular ultrasound-based deep-learning methodology for accurate coronary computed tomography plaque quantification and characterization.

Aims: Coronary computed tomography angiography (CCTA) is inferior to intravascular imaging in detecting plaque morphology and quantifying plaque burden. We aim to, for the first time, train a deep-learning (DL) methodology for accurate plaque quantification and characterization in CCTA using near-infrared spectroscopy-intravascular ultrasound (NIRS-IVUS). Methods and results: Seventy patients were prospectively recruited who underwent CCTA and NIRS-IVUS imaging. Corresponding cross sections were matched using an in-house developed software, and the estimations of NIRS-IVUS for the lumen, vessel wall borders, and plaque composition were used to train a convolutional neural network in 138 vessels. The performance was evaluated in 48 vessels and compared against the estimations of NIRS-IVUS and the conventional CCTA expert analysis. Sixty-four patients (186 vessels, 22 012 matched cross sections) were included. Deep-learning methodology provided estimations that were closer to NIRS-IVUS compared with the conventional approach for the total atheroma volume (ΔDL-NIRS-IVUS: -37.8 ± 89.0 vs. ΔConv-NIRS-IVUS: 243.3 ± 183.7 mm3, variance ratio: 4.262, P < 0.001) and percentage atheroma volume (-3.34 ± 5.77 vs. 17.20 ± 7.20%, variance ratio: 1.578, P < 0.001). The DL methodology detected lesions more accurately than the conventional approach (Area under the curve (AUC): 0.77 vs. 0.67, P < 0.001) and quantified minimum lumen area (ΔDL-NIRS-IVUS: -0.35 ± 1.81 vs. ΔConv-NIRS-IVUS: 1.37 ± 2.32 mm2, variance ratio: 1.634, P < 0.001), maximum plaque burden (4.33 ± 11.83% vs. 5.77 ± 16.58%, variance ratio: 2.071, P = 0.004), and calcific burden (-51.2 ± 115.1 vs. -54.3 ± 144.4, variance ratio: 2.308, P < 0.001) more accurately than conventional approach. The DL methodology was able to segment a vessel on CCTA in 0.3 s. Conclusions: The DL methodology developed for CCTA analysis from co-registered NIRS-IVUS and CCTA data enables rapid and accurate assessment of lesion morphology and is superior to expert analysts (Clinicaltrials.gov: NCT03556644).

CARDIAN: a novel computational approach for real-time end-diastolic frame detection in intravascular ultrasound using bidirectional attention networks.

Introduction: Changes in coronary artery luminal dimensions during the cardiac cycle can impact the accurate quantification of volumetric analyses in intravascular ultrasound (IVUS) image studies. Accurate ED-frame detection is pivotal for guiding interventional decisions, optimizing therapeutic interventions, and ensuring standardized volumetric analysis in research studies. Images acquired at different phases of the cardiac cycle may also lead to inaccurate quantification of atheroma volume due to the longitudinal motion of the catheter in relation to the vessel. As IVUS images are acquired throughout the cardiac cycle, end-diastolic frames are typically identified retrospectively by human analysts to minimize motion artefacts and enable more accurate and reproducible volumetric analysis. Methods: In this paper, a novel neural network-based approach for accurate end-diastolic frame detection in IVUS sequences is proposed, trained using electrocardiogram (ECG) signals acquired synchronously during IVUS acquisition. The framework integrates dedicated motion encoders and a bidirectional attention recurrent network (BARNet) with a temporal difference encoder to extract frame-by-frame motion features corresponding to the phases of the cardiac cycle. In addition, a spatiotemporal rotation encoder is included to capture the IVUS catheter's rotational movement with respect to the coronary artery. Results: With a prediction tolerance range of 66.7 ms, the proposed approach was able to find 71.9%, 67.8%, and 69.9% of end-diastolic frames in the left anterior descending, left circumflex and right coronary arteries, respectively, when tested against ECG estimations. When the result was compared with two expert analysts' estimation, the approach achieved a superior performance. Discussion: These findings indicate that the developed methodology is accurate and fully reproducible and therefore it should be preferred over experts for end-diastolic frame detection in IVUS sequences.

Computed Tomography Cardiac Angiography Before Invasive Coronary Angiography in Patients With Previous Bypass Surgery: The BYPASS-CTCA Trial.

BACKGROUND: Patients with previous coronary artery bypass grafting often require invasive coronary angiography (ICA). However, for these patients, the procedure is technically more challenging and has a higher risk of complications. Observational studies suggest that computed tomography cardiac angiography (CTCA) may facilitate ICA in this group, but this has not been tested in a randomized controlled trial. METHODS: This study was a single-center, open-label randomized controlled trial assessing the benefit of adjunctive CTCA in patients with previous coronary artery bypass grafting referred for ICA. Patients were randomized 1:1 to undergo CTCA before ICA or ICA alone. The co-primary end points were procedural duration of the ICA (defined as the interval between local anesthesia administration for obtaining vascular access and removal of the last catheter), patient satisfaction after ICA using a validated questionnaire, and the incidence of contrast-induced nephropathy. Linear regression was used for procedural duration and patient satisfaction score; contrast-induced nephropathy was analyzed using logistic regression. We applied the Bonferroni correction, with P<0.017 considered significant and 98.33% CIs presented. Secondary end points included incidence of procedural complications and 1-year major adverse cardiac events. RESULTS: Over 3 years, 688 patients were randomized with a median follow-up of 1.0 years. The mean age was 69.8±10.4 years, 108 (15.7%) were women, 402 (58.4%) were White, and there was a high burden of comorbidity (85.3% hypertension and 53.8% diabetes). The median time from coronary artery bypass grafting to angiography was 12.0 years, and there were a median of 3 (interquartile range, 2 to 3) grafts per participant. Procedure duration of the ICA was significantly shorter in the CTCA+ICA group (CTCA+ICA, 18.6±9.5 minutes versus ICA alone, 39.5±16.9 minutes [98.33% CI, -23.5 to -18.4]; P<0.001), alongside improved mean ICA satisfaction scores (1=very good to 5=very poor; -1.1 difference [98.33% CI, -1.2 to -0.9]; P<0.001), and reduced incidence of contrast-induced nephropathy (3.4% versus 27.9%; odds ratio, 0.09 [98.33% CI, 0.04-0.2]; P<0.001). Procedural complications (2.3% versus 10.8%; odds ratio, 0.2 [95% CI, 0.1-0.4]; P<0.001) and 1-year major adverse cardiac events (16.0% versus 29.4%; hazard ratio, 0.4 [95% CI, 0.3-0.6]; P<0.001) were also lower in the CTCA+ICA group. CONCLUSIONS: For patients with previous coronary artery bypass grafting, CTCA before ICA leads to reductions in procedure time and contrast-induced nephropathy, with improved patient satisfaction. CTCA before ICA should be considered in this group of patients. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT03736018.

Angiography and optical coherence tomography derived shear stress: are they equivalent in my opinion?

Advances in image reconstruction using either single or multimodality imaging data provide increasingly accurate three-dimensional (3D) patient's arterial models for shear stress evaluation using computational fluid dynamics (CFD). We aim to evaluate the impacts on endothelial shear stress (ESS) derived from a simple image reconstruction using 3D-quantitative coronary angiography (3D-QCA) versus a multimodality reconstruction method using optical coherence tomography (OCT) in patients' vessels treated with bioresorbable scaffolds. Seven vessels at baseline and five-year follow-up of seven patients from a previous CFD investigation were retrospectively selected for a head-to-head comparison of angiography-derived versus OCT-derived ESS. 3D-QCA significantly underestimated the minimum stent area [MSA] (-2.38mm2) and the stent length (-1.46 mm) compared to OCT-fusion method reconstructions. After carefully co-registering the region of interest for all cases with a sophisticated statistical method, the difference in MSA measurements as well as the inability of angiography to visualise the strut footprint in the lumen surface have translated to higher angiography-derived ESS than OCT-derived ESS (1.76 Pa or 1.52 times for the overlapping segment). The difference in ESS widened with a more restricted region of interest (1.97 Pa or 1.63 times within the scaffold segment). Angiography and OCT offer two distinctive methods of ESS calculation. Angiography-derived ESS tends to overestimate the ESS compared to OCT-derived ESS. Further investigations into ESS analysis resolution play a vital role in adopting OCT-derived ESS.

POST-IVUS: A perceptual organisation-aware selective transformer framework for intravascular ultrasound segmentation.

Intravascular ultrasound (IVUS) is recommended in guiding coronary intervention. The segmentation of coronary lumen and external elastic membrane (EEM) borders in IVUS images is a key step, but the manual process is time-consuming and error-prone, and suffers from inter-observer variability. In this paper, we propose a novel perceptual organisation-aware selective transformer framework that can achieve accurate and robust segmentation of the vessel walls in IVUS images. In this framework, temporal context-based feature encoders extract efficient motion features of vessels. Then, a perceptual organisation-aware selective transformer module is proposed to extract accurate boundary information, supervised by a dedicated boundary loss. The obtained EEM and lumen segmentation results will be fused in a temporal constraining and fusion module, to determine the most likely correct boundaries with robustness to morphology. Our proposed methods are extensively evaluated in non-selected IVUS sequences, including normal, bifurcated, and calcified vessels with shadow artifacts. The results show that the proposed methods outperform the state-of-the-art, with a Jaccard measure of 0.92 for lumen and 0.94 for EEM on the IVUS 2011 open challenge dataset. This work has been integrated into a software QCU-CMS2 to automatically segment IVUS images in a user-friendly environment.

Retrograde percutaneous coronary intervention of chronic total occlusion via discontinuous septal channels.

OBJECTIVES: The study aims to investigate the safety and feasibility of retrograde CTO intervention via collateral connection grade 0 (CC-0) septal channel and to identify predictors of collateral tracking failure. BACKGROUND: Guidewire crossing a collateral channel is a critical step for successful retrograde percutaneous coronary intervention (PCI) of chronic total occlusion (CTO). METHODS: Retrograde PCI was attempted in 122 cases of CTO with CC-0 septal collaterals from December 2018 to May 2021. A hydrophilic polymer coating guidewire was used for crossing all intended CC-0 collaterals. A multivariable logistic regression analysis was performed to identify the predictors of guidewire tracking failure via the CC-0 collaterals. RESULTS: Successful guidewire tracking via CC-0 septal channel was achieved in 98 (80.3%) of 122 cases. The independent predictors of CC-0 septal channel guidewire tracking failure included well-developed non-septal collateral (OR: 5.297, 95% CI: 1.107-25.353, p = 0.037) and the ratio length of posterior descending artery (PDA) versus the distance of PDA ostium to cardiac apex ≤2/3 (OR: 3.970, 95% CI: 1.454-10.835, p = 0.007). Collateral perforation, target vessel perforation, and cardiac tamponade occurred in 5 (4.1%), 3 (2.5%), and 6 (4.9%) cases, respectively. There were no complications requiring emergency cardiac surgery or revascularization of nontarget vessel. CONCLUSIONS: Retrograde PCI via CC-0 septal channels with a hydrophilic polymer-coated guidewire is feasible and safe in patients with CTO. Well-developed nonseptal collaterals and short PDA length influence the procedure success and the risk of guidewire tracking failure via CC-0 septal channels.

Agreement of wall shear stress distribution between two core laboratories using three-dimensional quantitative coronary angiography.

Wall shear stress (WSS) estimated in models reconstructed from intravascular imaging and 3-dimensional-quantitative coronary angiography (3D-QCA) data provides important prognostic information and enables identification of high-risk lesions. However, these analyses are time-consuming and require expertise, limiting WSS adoption in clinical practice. Recently, a novel software has been developed for real-time computation of time-averaged WSS (TAWSS) and multidirectional WSS distribution. This study aims to examine its inter-corelab reproducibility. Sixty lesions (20 coronary bifurcations) with a borderline negative fractional flow reserve were processed using the CAAS Workstation WSS prototype to estimate WSS and multi-directional WSS values. Analysis was performed by two corelabs and their estimations for the WSS in 3 mm segments across each reconstructed vessel was extracted and compared. In total 700 segments (256 located in bifurcated vessels) were included in the analysis. A high intra-class correlation was noted for all the 3D-QCA and TAWSS metrics between the estimations of the two corelabs irrespective of the presence (range: 0.90-0.92) or absence (range: 0.89-0.90) of a coronary bifurcation, while the ICC was good-moderate for the multidirectional WSS (range: 0.72-0.86). Lesion level analysis demonstrated a high agreement of the two corelabls for detecting lesions exposed to an unfavourable haemodynamic environment (WSS > 8.24 Pa, κ = 0.77) that had a high-risk morphology (area stenosis > 61.3%, κ = 0.71) and were prone to progress and cause events. The CAAS Workstation WSS enables reproducible 3D-QCA reconstruction and computation of WSS metrics. Further research is needed to explore its value in detecting high-risk lesions.

Effect of High-Intensity Statin Therapy on Atherosclerosis (IBIS-4): Manual Versus Automated Methods of IVUS Analysis.

AIMS: Standard manual analysis of IVUS to study the impact of anti-atherosclerotic therapies on the coronary vessel wall is done by a core laboratory (CL), the ground truth (GT). Automatic segmentation of IVUS with a machine learning (ML) algorithm has the potential to replace manual readings with an unbiased and reproducible method. The aim is to determine if results from a CL can be replicated with ML methods. METHODS: This is a post-hoc, comparative analysis of the IBIS-4 (Integrated Biomarkers and Imaging Study-4) study (NCT00962416). The GT baseline and 13-month follow-up measurements of lumen and vessel area and percent atheroma volume (PAV) after statin induction were repeated by the ML algorithm. RESULTS: The primary endpoint was change in PAV. PAV as measured by GT was 43.95 % at baseline and 43.02 % at follow-up with a change of -0.90 % (p = 0.007) while the ML algorithm measured 43.69 % and 42.41 % for baseline and follow-up, respectively, with a change of -1.28 % (p < 0.001). Along the most diseased 10 mm segments, GT-PAV was 52.31 % at baseline and 49.42 % at follow-up, with a change of -2.94 % (p < 0.001). The same segments measured by the ML algorithm resulted in PAV of 51.55 % at baseline and 47.81 % at follow-up with a change of -3.74 % (p < 0.001). CONCLUSIONS: PAV, the most used endpoint in clinical trials, analyzed by the CL is closely replicated by the ML algorithm. ML automatic segmentation of lumen, vessel and plaque effectively reproduces GT and may be used in future clinical trials as the standard.

Early vascular healing after neXt-generation drug-eluting stent implantation in Patients with non-ST Elevation acute Coronary syndrome based on optical coherence Tomography guidance and evaluation (EXPECT): study protocol for a randomized controlled trial.

Background: There is limited evidence about vessel wall healing response following implantation of next-generation drug-eluting stents (DES) in patients admitted with a non-ST elevation acute coronary syndrome (NSTE-ACS). Cumulative data indicate that optical coherence tomography (OCT) imaging can optimize percutaneous coronary intervention results and expedite stent endothelialization in the general population but there is lack of data in NSTE-ACS patients. Methods: The EXPECT study is an investigator-initiated, prospective, randomized trial to assess early vascular healing response following next-generation DES implantation in patients admitted with NSTE-ACS based on OCT guidance and evaluation. Sixty patients are randomized at 1:1:1 ratio to OCT-guided percutaneous coronary intervention (PCI) with 3-month follow-up OCT imaging (O3 group, n = 20), to angiography-guided PCI with 3-month follow-up OCT imaging (A3 group, n = 20) and to angiography-guided PCI with 6-month follow-up OCT imaging (A6 group, n = 20). The primary endpoint of the study is stent strut coverage rate at 3- or 6- month follow-up in the studied groups. The secondary endpoints of the study include OCT imaging endpoints, clinical endpoints, and molecular biology endpoints at the different time points. The clinical endpoints comprised of major cardiovascular adverse events and individual components. The molecular biology endpoints comprised of lipid levels and the levels of inflammatory indicators. Discussion: The findings of the EXPECT study are anticipated to provide novel insights into vessel wall healing in NSTE-ACS population following implantation of next-generation DES, underscore the value of OCT imaging in expediting strut coverage in this setting, and explore the potential of an early discontinuation of dual antiplatelet therapy (DAPT) in this population. Clinical Trial Registration: ClinicalTrials.gov, NCT04375319.

Intravascular Ultrasound and Optical Coherent Tomography Combined Catheter.

Intravascular ultrasound (IVUS) and optical coherence tomography (OCT) are established intravascular imaging tools for evaluating plaque characteristics and volume, together with guiding percutaneous coronary interventions. The high tissue penetration of IVUS facilitates assessment of the entire vessel wall, whereas the higher resolution of OCT allows detailed assessment of endoluminal structures. A combined IVUS-OCT probe works synergistically, facilitating a greater understanding of de novo coronary artery disease and a better correlation with pathological specimens. In this review, we discuss the rationale and potential roles of the combined IVUS-OCT catheter system.