Automated Segmentation of Bioresorbable Vascular Scaffold Struts in Intracoronary Optical Coherence Tomography Images

Bioresorbable vascular scaffolds (BVS), the next step in the continuum of minimally invasive vascular interventions present new opportunities for patients and clinicians but challenges as well. As they are comprised of polymeric materials standard imaging is challenging. This is especially problematic as modalities like optical coherence tomography (OCT) become more prevalent in cardiology. OCT, a light-based intracoronary imaging technique, provides cross-sectional images of plaque and luminal morphology. Until recently segmentation of OCT images for BVS struts was performed manually by experts. However, this process is time consuming and not tractable for large amounts of patient data. Several automated methods exist to segment metallic stents, which do not apply to the newer BVS. Given this current limitation coupled with the emerging popularity of the BVS technology, it is crucial to develop an automated methodology to segment BVS struts in OCT images. The objective of this paper is to develop a novel BVS strut detection method in intracoronary OCT images. First, we preprocess the image to remove imaging artifacts. Then, we use a K-means clustering algorithm to automatically segment the image. Finally, we isolate the stent struts from the rest of the image. The accuracy of the proposed method was evaluated using expert estimations on 658 annotated images acquired from 7 patients at the time of coronary arterial interventions. Our proposed methodology has a positive predictive value of 0.93, a Pearson Correlation coefficient of 0.94, and a F1 score of 0.92. The proposed methodology allows for rapid, accurate, and fully automated segmentation of BVS struts in OCT images.

Tissue characterization with depth-resolved attenuation coefficient and backscatter term in intravascular optical coherence tomography images

An important application of intravascular optical coherence tomography (IVOCT) for atherosclerotic tissue analysis is using it to estimate attenuation and backscatter coefficients. This work aims at exploring the potential of the attenuation coefficient, a proposed backscatter term, and image intensities in distinguishing different atherosclerotic tissue types with a robust implementation of depth-resolved (DR) approach. Therefore, the DR model is introduced to estimate the attenuation coefficient and further extended to estimate the backscatter-related term in IVOCT images, such that values can be estimated per pixel without predefining any delineation for the estimation. In order to exclude noisy regions with a weak signal, an automated algorithm is implemented to determine the cut-off border in IVOCT images. The attenuation coefficient, backscatter term, and the image intensity are further analyzed in regions of interest, which have been delineated referring to their pathology counterparts. Local statistical values were reported and their distributions were further compared with a two-sample t-test to evaluate the potential for distinguishing six types of tissues. Results show that the IVOCT intensity, DR attenuation coefficient, and backscatter term extracted with the reported implementation are complementary to each other on characterizing six tissue types: mixed, calcification, fibrous, lipid-rich, macrophages, and necrotic core.

Analysis and compensation for the effect of the catheter position on image intensities in intravascular optical coherence tomography

Intravascular optical coherence tomography (IVOCT) is an imaging technique that is used to analyze the underlying cause of cardiovascular disease. Because a catheter is used during imaging, the intensities can be affected by the catheter position. This work aims to analyze the effect of the catheter position on IVOCT image intensities and to propose a compensation method to minimize this effect in order to improve the visualization and the automatic analysis of IVOCT images. The effect of catheter position is modeled with respect to the distance between the catheter and the arterial wall (distance-dependent factor) and the incident angle onto the arterial wall (angle-dependent factor). A light transmission model incorporating both factors is introduced. On the basis of this model, the interaction effect of both factors is estimated with a hierarchical multivariant linear regression model. Statistical analysis shows that IVOCT intensities are significantly affected by both factors with p<0.001, as either aspect increases the intensity decreases. This effect differs for different pullbacks. The regression results were used to compensate for this effect. Experiments show that the proposed compensation method can improve the performance of the automatic bioresorbable vascular scaffold strut detection.

Edge Vascular Response After Resorption of the Everolimus-Eluting Bioresorbable Vascular Scaffold - A 5-Year Serial Optical Coherence Tomography Study

BACKGROUND

The edge vascular response (EVR) has been linked to important prognostic implications in patients treated with permanent metallic stents. We aimed to investigate the relationship of EVR with the geometric changes in the everolimus-eluting bioresorbable scaffold using serial optical coherence tomography (OCT) analysis.

METHODS AND RESULTS

In the first-in-man ABSORB trial, 28 patients (29 lesions) underwent serial OCT at 4 different time points (Cohort B1: post-procedure, 6, 24, and 60 months [n=13]; Cohort B2: post-procedure, 12, 36, and 60 months [n=15]) following implantation of the scaffold. In Cohort B1, there was no significant luminal change at the distal or proximal edge segment throughout the entire follow-up. In contrast, there was a significant reduction of the lumen flow area (LFA) of the scaffold between post-procedure and 6 months (-1.03±0.49 mm(2)[P<0.001]), whereas between 6 and 60 months the LFA remained stable (+0.31±1.00 mm(2)[P=0.293]). In Cohort B2, there was a significant luminal reduction of the proximal edge between post-procedure and 12 months (-0.57±0.74 mm(2)[P=0.017]), whereas the lumen area remained stable (-0.26±1.22 mm(2)[P=0.462]) between 12 and 60 months. The scaffold LFA showed a change similar to that observed in Cohort B1.

CONCLUSIONS

Our study demonstrated a reduction in the scaffold luminal area in the absence of major EVR, suggesting that the physiological continuity of the lumen contour is restored long term. (Circ J 2016; 80: 1131-1141).

Short- and Long-term Evaluation of Bioresorbable Scaffolds by Optical Coherence Tomography

The analysis of bioresorbable scaffolds (BRSs) by optical coherence tomography (OCT) requires a dedicated methodology, as the polymeric scaffold has a distinct appearance and undergoes dynamic structural changes with time. The high resolution of OCT allows for the detailed assessment of scaffold implantation, rupture, discontinuity, and strut integration. OCT does not provide reliable information on the extent of scaffold degradation, as it cannot differentiate between polylactide polymer and the provisional matrix of proteoglycan formed by connective tissue. Three-dimensional OCT reconstruction can aid in the evaluation of BRS in special scenarios such as overlapping scaffold segments and bifurcations.