Decomposition Technique for Bio-Transmittance Imaging Based on Attenuation Coefficient Matrix Inverse

Human body tissue disease diagnosis will become more accurate if transmittance images, such as X-ray images, are separated according to each constituent tissue. This research proposes a new image decomposition technique based on the matrix inverse method for biological tissue images. The fundamental idea of this research is based on the fact that when k different monochromatic lights penetrate a biological tissue, they will experience different attenuation coefficients. Furthermore, the same happens when monochromatic light penetrates k different biological tissues, as they will also experience different attenuation coefficients. The various attenuation coefficients are arranged into a unique k×k-dimensional square matrix. k-many images taken by k-many different monochromatic lights are then merged into an image vector entity; further, a matrix inverse operation is performed on the merged image, producing N-many tissue thickness images of the constituent tissues. This research demonstrates that the proposed method effectively decomposes images of biological objects into separate images, each showing the thickness distributions of different constituent tissues. In the future, this proposed new technique is expected to contribute to supporting medical imaging analysis.

Semi-Automatic Reconstruction of Patient-Specific Stented Coronaries based on Data Assimilation and Computer Aided Design

PURPOSE

The interplay between geometry and hemodynamics is a significant factor in the development of cardiovascular diseases. This is particularly true for stented coronary arteries. To elucidate this factor, an accurate patient-specific analysis requires the reconstruction of the geometry following the stent deployment for a computational fluid dynamics (CFD) investigation. The image-based reconstruction is troublesome for the different possible positions of the stent struts in the lumen and the coronary wall. However, the accurate inclusion of the stent footprint in the hemodynamic analysis is critical for detecting abnormal stress conditions and flow disturbances, particularly for thick struts like in bioresorbable scaffolds. Here, we present a novel reconstruction methodology that relies on Data Assimilation and Computer Aided Design.

METHODS

The combination of the geometrical model of the undeployed stent and image-based data assimilated by a variational approach allows the highly automated reconstruction of the skeleton of the stent. A novel approach based on computational mechanics defines the map between the intravascular frame of reference (called L-view) and the 3D geometry retrieved from angiographies. Finally, the volumetric expansion of the stent skeleton needs to be self-intersection free for the successive CFD studies; this is obtained by using implicit representations based on the definition of Nef-polyhedra.

RESULTS

We assessed our approach on a vessel phantom, with less than 10% difference (properly measured) vs. a customized manual (and longer) procedure previously published, yet with a significant higher level of automation and a shorter turnaround time. Computational hemodynamics results were even closer. We tested the approach on two patient-specific cases as well.

CONCLUSIONS

The method presented here has a high level of automation and excellent accuracy performances, so it can be used for larger studies involving patient-specific geometries.

Efficacy of Zotarolimus-Eluting Stents in Treating Diabetic Coronary Lesions: An Optical Coherence Tomography Study

BACKGROUND

Diabetes mellitus (DM) plays an important role in restenosis and late in-stent thrombosis (ST). The current study using optical coherence tomography (OCT) aims to compare target lesion neointima in patients with or without diabetes after zotarolimus-eluting stent (ZES) treatment.

METHODS

OCT images of 90,212 struts and quantitative coronary angiography (QCA) in 62 patients (32 with DM and 30 without DM) with 69 de novo coronary lesions (34 DM and 35 non-DM) both after ZES implantation and 12 ± 1 month angiographic follow-up were recorded. Patient characteristics, lesion characteristics, clinical outcomes, and OCT findings including neointimal thickness, coverage, malapposition, and intimal morphology were analyzed.

RESULTS

Baseline patient characteristics and lesion characteristics data were similar between the two groups. Higher neointimal thickness (0.14 ± 0.09 mm vs. 0.09 ± 0.04 mm, p = 0.021), more neovascularization (3.03 ± 6.24 vs. 0.52 ± 1.87, p = 0.017) and higher incidence of layered signal pattern (12.19 ± 19.91% vs. 4.28 ± 9.02%, p = 0.049) were observed in diabetic lesions comparing with non-diabetic lesions. No differences were found in malapposition, uncovered percentage, and thrombus between the two groups (all p > 0.05). Occurrence of clinical adverse events was also similar during the follow-up period (p > 0.05).

CONCLUSION

Although more neointimal proliferation and more neovascularization were found in diabetic coronary lesions when compared with non-diabetic lesions, treatment with ZES showed similar stent malapposition rate at 1-year follow-up. The data indicated that ZES treatment could possibly be effective in treating diabetic coronary lesions.

TRIAL REGISTRATION

ClinicalTrials.gov identifier, NCT01747356.

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

Background / Objectives

Automatic 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.

Methods

The 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.

Results

When 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%).

Conclusions

This 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.

A Patient-Specific Study Investigating the Relation between Coronary Hemodynamics and Neo-Intimal Thickening after Bifurcation Stenting with a Polymeric Bioresorbable Scaffold

We present an application of a validated reconstruction methodology for the comparison between patient-specific hemodynamics and neo-intimal thickening at nine months from the intervention. (1) Background: Coronary bifurcation stenting alters the vessel geometry, influencing the local hemodynamics. The evaluation of wall shear stress (WSS) relies on the application of computational fluid dynamics to model its distribution along the coronary tree. The endothelium actively responds to WSS, which triggers eventual cell proliferation to cover the stent struts. (2) Methods: Baseline optical coherence tomography and angiographic data were combined to reconstruct a patient-specific coronary bifurcation with an implanted bioresorbable scaffold and to simulate the hemodynamics. Results were linked with the neo-intimal thickening after nine months from the intervention. (3) Results: Blood velocity patterns were disrupted at the bifurcation due to the presence of the stent. It was observed that 55.6% of the scaffolded lumen surface was exposed to values of time-averaged WSS lower than 0.4 Pa. Follow-up images showed a luminal narrowing of 19% in the main branch. There was also a complete coverage in 99% of struts. (4) Conclusions: This approach provided valuable complementary information that might improve the clinical outcomes in this subset of coronary diseases.

Patient-Specific Modeling of Stented Coronary Arteries Reconstructed from Optical Coherence Tomography: Towards a Widespread Clinical Use of Fluid Dynamics Analyses

The recent widespread application of optical coherence tomography (OCT) in interventional cardiology has improved patient-specific modeling of stented coronary arteries for the investigation of local hemodynamics. In this review, the workflow for the creation of fluid dynamics models of stented coronary arteries from OCT images is presented. The algorithms for lumen contours and stent strut detection from OCT as well as the reconstruction methods of stented geometries are discussed. Furthermore, the state of the art of studies that investigate the hemodynamics of OCT-based stented coronary artery geometries is reported. Although those studies analyzed few patient-specific cases, the application of the current reconstruction methods of stented geometries to large populations is possible. However, the improvement of these methods and the reduction of the time needed for the entire modeling process are crucial for a widespread clinical use of the OCT-based models and future in silico clinical trials.

A framework for computational fluid dynamic analyses of patient-specific stented coronary arteries from optical coherence tomography images

The clinical challenge of percutaneous coronary interventions (PCI) is highly dependent on the recognition of the coronary anatomy of each individual. The classic imaging modality used for PCI is angiography, but advanced imaging techniques that are routinely performed during PCI, like optical coherence tomography (OCT), may provide detailed knowledge of the pre-intervention vessel anatomy as well as the post-procedural assessment of the specific stent-to-vessel interactions. Computational fluid dynamics (CFD) is an emerging investigational tool in the setting of optimization of PCI results. In this study, an OCT-based reconstruction method was developed for the execution of CFD simulations of patient-specific coronary artery models which include the actual geometry of the implanted stent. The method was applied to a rigid phantom resembling a stented segment of the left anterior descending coronary artery. The segmentation algorithm was validated against manual segmentation. A strong correlation was found between automatic and manual segmentation of lumen in terms of area values. Similarity indices resulted >96% for the lumen segmentation and >77% for the stent strut segmentation. The 3D reconstruction achieved for the stented phantom was also assessed with the geometry provided by X-ray computed micro tomography scan, used as ground truth, and showed the incidence of distortion from catheter-based imaging techniques. The 3D reconstruction was successfully used to perform CFD analyses, demonstrating a great potential for patient-specific investigations. In conclusion, OCT may represent a reliable source for patient-specific CFD analyses which may be optimized using dedicated automatic segmentation algorithms.

Reconstruction of stented coronary arteries from optical coherence tomography images: Feasibility, validation, and repeatability of a segmentation method

Optical coherence tomography (OCT) is an established catheter-based imaging modality for the assessment of coronary artery disease and the guidance of stent placement during percutaneous coronary intervention. Manual analysis of large OCT datasets for vessel contours or stent struts detection is time-consuming and unsuitable for real-time applications. In this study, a fully automatic method was developed for detection of both vessel contours and stent struts. The method was applied to in vitro OCT scans of eight stented silicone bifurcation phantoms for validation purposes. The proposed algorithm comprised four main steps, namely pre-processing, lumen border detection, stent strut detection, and three-dimensional point cloud creation. The algorithm was validated against manual segmentation performed by two independent image readers. Linear regression showed good agreement between automatic and manual segmentations in terms of lumen area (r>0.99). No statistically significant differences in the number of detected struts were found between the segmentations. Mean values of similarity indexes were >95% and >85% for the lumen and stent detection, respectively. Stent point clouds of two selected cases, obtained after OCT image processing, were compared to the centerline points of the corresponding stent reconstructions from micro computed tomography, used as ground-truth. Quantitative comparison between the corresponding stent points resulted in median values of ~150 μm and ~40 μm for the total and radial distances of both cases, respectively. The repeatability of the detection method was investigated by calculating the lumen volume and the mean number of detected struts per frame for seven repeated OCT scans of one selected case. Results showed low deviation of values from the median for both analyzed quantities. In conclusion, this study presents a robust automatic method for detection of lumen contours and stent struts from OCT as supported by focused validation against both manual segmentation and micro computed tomography and by good repeatability.

Optical Coherence Tomography Guided Percutaneous Coronary Intervention With Nobori Stent Implantation in Patients With Non-ST-Segment-Elevation Myocardial Infarction (OCTACS) Trial: Difference in Strut Coverage and Dynamic Malapposition Patterns at 6 Months

BACKGROUND

Incomplete strut coverage has been documented an important histopathologic morphometric predictor for later thrombotic events. This study sought to investigate whether optical coherence tomography (OCT)-guided percutaneous coronary intervention with Nobori biolimus-eluting stent implantation in patients with non-ST-segment-elevation myocardial infarction would provide improved strut coverage at 6 months in comparison with angiographic guidance only.

METHODS AND RESULTS

One hundred patients were randomized 1:1 to either OCT-guided or angio-guided Nobori biolimus-eluting stent implantation. Postprocedure OCT was performed in all patients. In the OCT-guided group, prespecified criteria indicating additional intervention were related to (1) stent underexpansion, (2) strut malapposition, (3) edge dissection(s), and (4) residual stenosis at the distal or proximal reference segment(s). A final OCT was performed in case of reintervention. Six-month OCT follow-up was available in 85 patients. Twenty-three (46%) OCT-guided patients had additional postdilation or stenting. The percentage of acutely malapposed struts was substantially lower in the OCT-guided group (3.4% [interquartile range, 0.3-7.6] versus 7.8% [interquartile range, 2.3-19.4]; P<0.01). At 6-month follow-up, the OCT-guided group had a significantly lower proportion of uncovered struts; 4.3% [interquartile range, 1.2-9.8] versus 9.0% [interquartile range, 5.5-14.5], P<0.01. Furthermore, OCT-guided patients had significantly more completely covered stents: 17.5% versus 2.2%, P=0.02. The percentages of malapposed struts and struts being both uncovered and malapposed at follow-up were comparable between groups.

CONCLUSIONS

OCT-guided optimization of Nobori biolimus-eluting stent implantation improves strut coverage at 6-month follow-up in comparison with angiographic guidance alone.

CLINICAL TRIAL REGISTRATION

URL: http://www.clinicaltrials.gov. Unique identifier: NCT02272283.

In situ Endothelialization: Bioengineering Considerations to Translation

Improving patency rates of current cardiovascular implants remains a major challenge. It is widely accepted that regeneration of a healthy endothelium layer on biomaterials could yield the perfect blood-contacting surface. Earlier efforts in pre-seeding endothelial cells in vitro demonstrated success in enhancing patency, but translation to the clinic is largely hampered due to its impracticality. In situ endothelialization, which aims to create biomaterial surfaces capable of self-endothelializing upon implantation, appears to be an extremely promising solution, particularly with the utilization of endothelial progenitor cells (EPCs). Nevertheless, controlling cell behavior in situ using immobilized biomolecules or physical patterning can be complex, thus warranting careful consideration. This review aims to provide valuable insight into the rationale and recent developments in biomaterial strategies to enhance in situ endothelialization. In particular, a discussion on the important bio-/nanoengineering considerations and lessons learnt from clinical trials are presented to aid the future translation of this exciting paradigm.