Automatic segmentation of optical coherence tomography pullbacks of coronary arteries treated with bioresorbable vascular scaffolds: Application to hemodynamics modeling

Abstract

Background / ObjectivesAutomatic algorithms for stent struts segmentation in optical coherence tomography (OCT) images of coronary arteries have been developed over the years, particularly with application on metallic stents. The aim of this study is three-fold: (1) to develop and to validate a segmentation algorithm for the detection of both lumen contours and polymeric bioresorbable scaffold struts from 8-bit OCT images, (2) to develop a method for automatic OCT pullback quality assessment, and (3) to demonstrate the applicability of the segmentation algorithm for the creation of patient-specific stented coronary artery for local hemodynamics analysis.MethodsThe proposed OCT segmentation algorithm comprises four steps: (1) image pre-processing, (2) lumen segmentation, (3) stent struts segmentation, (4) strut-based lumen correction. This segmentation process is then followed by an automatic OCT pullback image quality assessment. This method classifies the OCT pullback image quality as ‘good’ or ‘poor’ based on the number of regions detected by the stent segmentation. The segmentation algorithm was validated against manual segmentation of 1150 images obtained from 23 in vivo OCT pullbacks.ResultsWhen considering the entire set of OCT pullbacks, lumen segmentation showed results comparable with manual segmentation and with previous studies (sensitivity ~97%, specificity ~99%), while stent segmentation showed poorer results compared to manual segmentation (sensitivity ~63%, precision ~83%). The OCT pullback quality assessment algorithm classified 7 pullbacks as ‘poor’ quality cases. When considering only the ‘good’ classified cases, the performance indexes of the scaffold segmentation were higher (sensitivity >76%, precision >86%).ConclusionsThis study proposes a segmentation algorithm for the detection of lumen contours and stent struts in low quality OCT images of patients treated with polymeric bioresorbable scaffolds. The segmentation results were successfully used for the reconstruction of one coronary artery model that included a bioresorbable scaffold geometry for computational fluid dynamics analysis.

Three dimensional reconstruction of coronary artery stents from optical coherence tomography: experimental validation and clinical feasibility

“…Since μCT was an integral part of the reconstruction method, these techniques cannot be used in the clinical setting, and their applicability is limited to experimental research. However, a variation of the technique by Migliori et al 12 has been applied in clinical cases 9 . In contrast to these two studies, we used μCT solely for the purpose of validation in our method.…”

“…A platform for precise three-dimensional (3D) reconstruction of coronary stents, combined with 3D reconstruction of the arterial lumen, may unlock a wide spectrum of information and lay the ground for optimization of stenting procedures, patient-specific computational stenting simulations, and research and development of new stent scaffolds and stenting techniques. To the best of our knowledge, there have been very few attempts for OCT-based 3D reconstruction of coronary stents 9 – 13 . These studies had several limitations due to insufficient validation, lack of clinical feasibility, and use of older generation stent designs deployed in straight lumen vascular geometries.…”

Automated Coronary Optical Coherence Tomography Feature Extraction with Application to Three-Dimensional Reconstruction

“…Segmentation of the coronary artery lumen contour is perhaps the simplest task for automated techniques when there is no atherosclerotic disease and there has been appropriate clearance of blood from the OCT images. Here, globally used binarization methods [ 59 ], such as Otsu filtering [ 60 , 61 , 62 , 63 ], morphological operations, edge detection [ 64 , 65 , 66 ] and curve fitting [ 67 ] were often sufficient to automatically delineate the lumen. However, these methods are challenged when facing bifurcation regions and catheter artefacts, as well as improper blood clearance, which are not uncommon occurrences in clinical scenarios.…”

“…Tested on two stents (Integrity bare metal stent and Xience Alpine drug eluting stent) in four in vitro models and compared to manual segmentation and reconstruction, results showed good agreement, with an average distance between the strut centroids of 97.5 ± 54.4 µm. In in vivo cases, by improving lumen segmentation around struts with a novel correction step to account for blood artefacts, Bologna et al, automatically generated a stented artery model for simulation of WSS from the OCT based 3D point cloud and biplane angiography centerline ( Figure 13 ) [ 64 ]. However, these approaches suffered in the case of struts that did not have visible, continuous, or square outlines.…”

3D Reconstruction of Coronary Artery Stents From Optical Coherence Tomography: Experimental Validation and Clinical Feasibility

“…To the best of our knowledge, there have been very few attempts for OCT-based 3D reconstruction of coronary stents. [9][10][11][12][13] These studies had several limitations related to insufficient validation, lack of clinical feasibility, and use of older generation stent designs deployed in straight lumen geometries.…”