First use of a new extended reality tool for preoperative planning in coronary artery bypass surgery: a case-report.

A 73-year-old male presented with angina symptoms and was diagnosed with three-vessel coronary artery disease by use of computed tomography angiography and coronary angiography. This diagnosis necessitated coronary artery bypass grafting (CABG) surgery. A custom made AI-driven algorithm was used to generate a patient-specific three-dimensional coronary artery model from computed tomography angiography imaging data. This framework enabled precise segmentation and reconstruction of the coronary vasculature, yielding an accurate anatomical and pathological representation. Subsequently, this generated model was integrated into a novel extended reality tool for preoperative planning and intraoperative guidance in CABG surgery. Both preoperatively and intraoperatively, the tool augmented spatial orientation and facilitated precise stenosis localization, thereby enhancing the surgeon's operative proficiency. This case report underscores the utility of advanced extended reality tools in cardiovascular surgery, emphasizing their pivotal role in refining surgical planning and execution.

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.

Semi-automatic standardized analysis method to objectively evaluate near-infrared fluorescent dyes in image-guided surgery.

Significance: Near-infrared fluorescence imaging still lacks a standardized, objective method to evaluate fluorescent dye efficacy in oncological surgical applications. This results in difficulties in translation between preclinical to clinical studies with fluorescent dyes and in the reproduction of results between studies, which in turn hampers further clinical translation of novel fluorescent dyes. Aim: Our aim is to develop and evaluate a semi-automatic standardized method to objectively assess fluorescent signals in resected tissue. Approach: A standardized imaging procedure was designed and quantitative analysis methods were developed to evaluate non-targeted and tumor-targeted fluorescent dyes. The developed analysis methods included manual selection of region of interest (ROI) on white light images, automated fluorescence signal ROI selection, and automatic quantitative image analysis. The proposed analysis method was then compared with a conventional analysis method, where fluorescence signal ROIs were manually selected on fluorescence images. Dice similarity coefficients and intraclass correlation coefficients were calculated to determine the inter- and intraobserver variabilities of the ROI selections and the determined signal- and tumor-to-background ratios. Results: The proposed non-targeted fluorescent dyes analysis method showed statistically significantly improved variabilities after application on indocyanine green specimens. For specimens with the targeted dye SGM-101, the variability of the background ROI selection was statistically significantly improved by implementing the proposed method. Conclusion: Semi-automatic methods for standardized quantitative analysis of fluorescence images were successfully developed and showed promising results to further improve the reproducibility and standardization of clinical studies evaluating fluorescent dyes.

Intraprocedural assessment of ablation margins using computed tomography co-registration in hepatocellular carcinoma treatment with percutaneous ablation: IAMCOMPLETE study.

PURPOSE: The primary objective of this study was to determine the feasibility of ablation margin quantification using a standardized scanning protocol during thermal ablation (TA) of hepatocellular carcinoma (HCC), and a rigid registration algorithm. Secondary objectives were to determine the inter- and intra-observer variability of tumor segmentation and quantification of the minimal ablation margin (MAM). MATERIALS AND METHODS: Twenty patients who underwent thermal ablation for HCC were included. There were thirteen men and seven women with a mean age of 67.1 ± 10.8 (standard deviation [SD]) years (age range: 49.1-81.1 years). All patients underwent contrast-enhanced computed tomography examination under general anesthesia directly before and after TA, with preoxygenated breath hold. Contrast-enhanced computed tomography examinations were analyzed by radiologists using rigid registration software. Registration was deemed feasible when accurate rigid co-registration could be obtained. Inter- and intra-observer rates of tumor segmentation and MAM quantification were calculated. MAM values were correlated with local tumor progression (LTP) after one year of follow-up. RESULTS: Co-registration of pre- and post-ablation images was feasible in 16 out of 20 patients (80%) and 26 out of 31 tumors (84%). Mean Dice similarity coefficient for inter- and intra-observer variability of tumor segmentation were 0.815 and 0.830, respectively. Mean MAM was 0.63 ± 3.589 (SD) mm (range: -6.26-6.65 mm). LTP occurred in four out of 20 patients (20%). The mean MAM value for patients who developed LTP was -4.00 mm, as compared to 0.727 mm for patients who did not develop LTP. CONCLUSION: Ablation margin quantification is feasible using a standardized contrast-enhanced computed tomography protocol. Interpretation of MAM was hampered by the occurrence of tissue shrinkage during TA. Further validation in a larger cohort should lead to meaningful cut-off values for technical success of TA.

Automatic Quantification of Local Plaque Thickness Differences as Assessed by Serial Coronary Computed Tomography Angiography Using Scan-Quality-Based Vessel-Specific Thresholds.

INTRODUCTION: The use of serial coronary computed tomography angiography (CCTA) allows for the early assessment of coronary plaque progression, a crucial factor in averting major adverse cardiac events (MACEs). Traditionally, serial CCTA is assessed using anatomical landmarks to match baseline and follow-up scans. Recently, a tool has been developed that allows for the automatic quantification of local plaque thickness differences in serial CCTA utilizing plaque contour delineation. The aim of this study was to determine thresholds of plaque thickness differences that define whether there is plaque progression and/or regression. These thresholds depend on the contrast-to-noise ratio (CNR). METHODS: Plaque thickness differences between two scans acquired at the same moment in time should always be zero. The negative and positive differences in plaque contour delineation in these scans were used along with the CNR in order to create calibration graphs on which a linear regression analysis was performed. This analysis was conducted on a cohort of 50 patients referred for a CCTA due to chest complaints. A total of 300 coronary vessels were analyzed. First, plaque contours were semi-automatically determined for all major epicardial coronary vessels. Second, manual drawings of seven regions of interest (ROIs) per scan were used to quantify the scan quality based on the CNR for each vessel. RESULTS: A linear regression analysis was performed on the CNR and negative and positive plaque contour delineation differences. Accounting for the standard error of the estimate, the linear regression analysis revealed that above 1.009 - 0.002 × CNR there is an increase in plaque thickness (progression), and below - 1.638 + 0.012 × CNR there is a decrease in plaque thickness (regression). CONCLUSION: This study demonstrates the feasibility of developing vessel-specific, quality-based thresholds for visualizing local plaque thickness differences evaluated by serial CCTA. These thresholds have the potential to facilitate the early detection of atherosclerosis progression.

Computational Modeling of Thermal Ablation Zones in the Liver: A Systematic Review.

PURPOSE: This systematic review aims to identify, evaluate, and summarize the findings of the literature on existing computational models for radiofrequency and microwave thermal liver ablation planning and compare their accuracy. METHODS: A systematic literature search was performed in the MEDLINE and Web of Science databases. Characteristics of the computational model and validation method of the included articles were retrieved. RESULTS: The literature search identified 780 articles, of which 35 were included. A total of 19 articles focused on simulating radiofrequency ablation (RFA) zones, and 16 focused on microwave ablation (MWA) zones. Out of the 16 articles simulating MWA, only 2 used in vivo experiments to validate their simulations. Out of the 19 articles simulating RFA, 10 articles used in vivo validation. Dice similarity coefficients describing the overlap between in vivo experiments and simulated RFA zones varied between 0.418 and 0.728, with mean surface deviations varying between 1.1 mm and 8.67 mm. CONCLUSION: Computational models to simulate ablation zones of MWA and RFA show considerable heterogeneity in model type and validation methods. It is currently unknown which model is most accurate and best suitable for use in clinical practice.

A novel deep learning model for a computed tomography diagnosis of coronary plaque erosion.

Patients with acute coronary syndromes caused by plaque erosion might be managed conservatively without stenting. Currently, the diagnosis of plaque erosion requires an invasive imaging procedure. We sought to develop a deep learning (DL) model that enables an accurate diagnosis of plaque erosion using coronary computed tomography angiography (CTA). A total of 532 CTA scans from 395 patients were used to develop a DL model: 426 CTA scans from 316 patients for training and internal validation, and 106 separate scans from 79 patients for validation. Momentum Distillation-enhanced Composite Transformer Attention (MD-CTA), a novel DL model that can effectively process the entire set of CTA scans to diagnose plaque erosion, was developed. The novel DL model, compared to the convolution neural network, showed significantly improved AUC (0.899 [0.841-0.957] vs. 0.724 [0.622-0.826]), sensitivity (87.1 [70.2-96.4] vs. 71.0 [52.0-85.8]), and specificity (85.3 [75.3-92.4] vs. 68.0 [56.2-78.3]), respectively, for the patient-level prediction. Similar results were obtained at the slice-level prediction AUC (0.897 [0.890-0.904] vs. 0.757 [0.744-0.770]), sensitivity (82.2 [79.8-84.3] vs. 68.9 [66.2-71.6]), and specificity (80.1 [79.1-81.0] vs. 67.3 [66.3-68.4]), respectively. This newly developed DL model enables an accurate CT diagnosis of plaque erosion, which might enable cardiologists to provide tailored therapy without invasive procedures.Clinical Trial Registration: http://www.clinicaltrials.gov , NCT04523194.

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).

Ablation margin quantification after thermal ablation of malignant liver tumors: How to optimize the procedure? A systematic review of the available evidence.

Introduction: To minimize the risk of local tumor progression after thermal ablation of liver malignancies, complete tumor ablation with sufficient ablation margins is a prerequisite. This has resulted in ablation margin quantification to become a rapidly evolving field. The aim of this systematic review is to give an overview of the available literature with respect to clinical studies and technical aspects potentially influencing the interpretation and evaluation of ablation margins. Methods: The Medline database was reviewed for studies on radiofrequency and microwave ablation of liver cancer, ablation margins, image processing and tissue shrinkage. Studies included in this systematic review were analyzed for qualitative and quantitative assessment methods of ablation margins, segmentation and co-registration methods, and the potential influence of tissue shrinkage occurring during thermal ablation. Results: 75 articles were included of which 58 were clinical studies. In most clinical studies the aimed minimal ablation margin (MAM) was ≥ 5 mm. In 10/31 studies, MAM quantification was performed in 3D rather than in three orthogonal image planes. Segmentations were performed either semi-automatically or manually. Rigid and non-rigid co-registration algorithms were used about as often. Tissue shrinkage rates ranged from 7% to 74%. Conclusions: There is a high variability in ablation margin quantification methods. Prospectively obtained data and a validated robust workflow are needed to better understand the clinical value. Interpretation of quantified ablation margins may be influenced by tissue shrinkage, as this may cause underestimation.

Plaque volume, composition, and fraction versus ischemia and outcomes in patients with coronary artery disease.

BACKGROUND: The various plaque components have been associated with ischemia and outcomes in patients with coronary artery disease (CAD). The main goal of this analysis was to test the hypothesis that, at patient level, the fraction of non-calcified plaque volume (PV) of total PV is associated with ischemia and outcomes in patients with CAD. This ratio could be a simple and clinically useful parameter, if predicting outcomes. METHODS: Consecutive patients with suspected CAD undergoing coronary computed tomography angiography with selective positron emission tomography perfusion imaging were selected. Plaque components were quantitatively analyzed at patient level. The fraction of various plaque components were expressed as percentage of total PV and examined among patients with non-obstructive CAD, suspected stenosis with normal perfusion, and those with reduced myocardial perfusion. Clinical outcomes included all-cause mortality and myocardial infarction. RESULTS: In total, 494 patients (age 63 â€‹± â€‹9 years, 55% male) were included. Total PV and all plaque components were significantly larger in patients with reduced myocardial perfusion compared to patients with normal perfusion and those with non-obstructive CAD. During follow-up 35 events occurred. Patients with any plaque component â€‹≥ â€‹median showed worse outcomes (log-rank p â€‹< â€‹0.001 for all). In addition, low-attenuation plaque â€‹≥ â€‹median was associated with worse outcomes independent of total PV (adjusted HR: 2.754, 95% CI: 1.022-7.0419, p â€‹= â€‹0.045). The fractions of the various plaque components were not associated with outcomes. CONCLUSION: Larger total PV or any plaque component at patient level are associated with abnormal myocardial perfusion and adverse events. The various plaque components as fraction of total PV lack additional prognostic value.

Coronary computed tomography angiography-based endothelial wall shear stress in normal coronary arteries.

Endothelial wall shear stress (ESS) is a biomechanical force which plays a role in the formation and evolution of atherosclerotic lesions. The purpose of this study is to evaluate coronary computed tomography angiography (CCTA)-based ESS in coronary arteries without atherosclerosis, and to assess factors affecting ESS values. CCTA images from patients with suspected coronary artery disease were analyzed to identify coronary arteries without atherosclerosis. Minimal and maximal ESS values were calculated for 3-mm segments. Factors potentially affecting ESS values were examined, including sex, lumen diameter and distance from the ostium. Segments were categorized according to lumen diameter tertiles into small (< 2.6 mm), intermediate (2.6-3.2 mm) or large (≥ 3.2 mm) segments. A total of 349 normal vessels from 168 patients (mean age 59 ± 9 years, 39% men) were included. ESS was highest in the left anterior descending artery compared to the left circumflex artery and right coronary artery (minimal ESS 2.3 Pa vs. 1.9 Pa vs. 1.6 Pa, p < 0.001 and maximal ESS 3.7 Pa vs. 3.0 Pa vs. 2.5 Pa, p < 0.001). Men had lower ESS values than women, also after adjusting for lumen diameter (p < 0.001). ESS values were highest in small segments compared to intermediate or large segments (minimal ESS 3.8 Pa vs. 1.7 Pa vs. 1.2 Pa, p < 0.001 and maximal ESS 6.0 Pa vs. 2.6 Pa vs. 2.0 Pa, p < 0.001). A weak to strong correlation was found between ESS and distance from the ostium (ρ = 0.22-0.62, p < 0.001). CCTA-based ESS values increase rapidly and become widely scattered with decreasing lumen diameter. This needs to be taken into account when assessing the added value of ESS beyond lumen diameter in highly stenotic lesions.

Three-dimensional quantitative margin assessment in patients with colorectal liver metastases treated with percutaneous thermal ablation using semi-automatic rigid MRI/CECT-CECT co-registration.

PURPOSE: To assess the quantitative minimal ablation margin (MAM) in patients with colorectal liver metastases (CRLM) treated with percutaneous thermal ablation (TA) and correlate the quantitative MAM with local tumour recurrence (LTR). METHOD: Thirty-nine of 143 patients with solitary or multiple CRLM who underwent a first percutaneous TA procedure between January 2011 and May 2020 were considered eligible for study enrolment. Image fusion of pre- and post-ablation scans and 3D quantitative MAM assessment was performed using the in-house developed semi-automatic rigid MRI/CECT-CECT co-registration software deLIVERed. The quantitative MAM was analysed and correlated with LTR. RESULTS: Eighteen (46 %) patients were additionally excluded from further analyses due to suboptimal co-registration (quality co-registration score ≤ 3). The quality of co-registration was considered sufficient in 21 (54 %) patients with a total of 29 CRLM. LTR was found in 5 of 29 (17 %) TA-treated CRLM. In total, 12 (41 %) negative MAMs were measured (mean MAM -4.7 ± 2.7 mm). Negative MAMs were significantly more frequently seen in patients who developed LTR (100 %) compared to those without LTR (29 %; p = 0.003). The median MAM of patients who developed LTR (-6.6 mm (IQR -9.5 to -4.6)) was significantly smaller compared to the median MAM of patients without LTR (0.5 mm (IQR -1.8 to 3.0); p < 0.001). The ROC curve showed high accuracy in predicting LTR for the quantitative MAM (area under the curve of 0.975 ± 0.029). CONCLUSION: This study demonstrated the feasibility of 3D quantitative MAM assessment, using deLIVERed co-registration software, to assess technical success of TA in patients with CRLM and to predict LTR.

Integration of Three-Dimensional Liver Models in a Multimodal Image-Guided Robotic Liver Surgery Cockpit.

Background: Robotic liver surgery represents the most recent evolution in the field of minimally-invasive liver surgery. For planning and guidance of liver resections, surgeons currently rely on preoperative 2-dimensional (2D) CT and/or MR imaging and intraoperative ultrasonography. Translating 2D images into digital 3-dimensional (3D) models may improve both preoperative planning and surgical guidance. The da Vinci® robotic surgical system is a platform suitable for the integration of multiple imaging modalities into one single view. In this study, we describe multimodal imaging options and introduce the Robotic Liver Surgery Cockpit; Methods: in-house developed software was used and validated for segmentation and registration to create a virtual reality 3D model of the liver based on preoperative imaging. The accuracy of the 3D models in the clinical setting was objectively assessed in 15 patients by measuring tumor diameters and subjectively with a postoperative conducted questionnaire; Results: Implementation and applicability of the 3D model in the surgical cockpit was feasible in all patients and the quality of the 3D reconstructions was high in 14 (93%) of cases. Tumor diameters measured on CT and/or MR imaging were comparable to automated measurements using the segmentation software and 3D models; Conclusions: the 3D model was successfully incorporated in the robotic surgery console as part of a multimodality imaging platform and aided the surgeon in planning and guidance of the resection. Future studies should focus on further automation of 3D rendering and progress into augmented reality.

Detailed behaviour of endothelial wall shear stress across coronary lesions from non-invasive imaging with coronary computed tomography angiography.

AIMS: Evolving evidence suggests that endothelial wall shear stress (ESS) plays a crucial role in the rupture and progression of coronary plaques by triggering biological signalling pathways. We aimed to investigate the patterns of ESS across coronary lesions from non-invasive imaging with coronary computed tomography angiography (CCTA), and to define plaque-associated ESS values in patients with coronary artery disease (CAD). METHODS AND RESULTS: Symptomatic patients with CAD who underwent a clinically indicated CCTA scan were identified. Separate core laboratories performed blinded analysis of CCTA for anatomical and ESS features of coronary atherosclerosis. ESS was assessed using dedicated software, providing minimal and maximal ESS values for each 3 mm segment. Each coronary lesion was divided into upstream, start, minimal luminal area (MLA), end and downstream segments. Also, ESS ratios were calculated using the upstream segment as a reference. From 122 patients (mean age 64 ± 7 years, 57% men), a total of 237 lesions were analyzed. Minimal and maximal ESS values varied across the lesions with the highest values at the MLA segment [minimal ESS 3.97 Pa (IQR 1.93-8.92 Pa) and maximal ESS 5.64 Pa (IQR 3.13-11.21 Pa), respectively]. Furthermore, minimal and maximal ESS values were positively associated with stenosis severity (P < 0.001), percent atheroma volume (P < 0.001), and lesion length (P ≤ 0.023) at the MLA segment. Using ESS ratios, similar associations were observed for stenosis severity and lesion length. CONCLUSIONS: Detailed behaviour of ESS across coronary lesions can be derived from routine non-invasive CCTA imaging. This may further improve risk stratification.

Study Protocol PROMETHEUS: Prospective Multicenter Study to Evaluate the Correlation Between Safety Margin and Local Recurrence After Thermal Ablation Using Image Co-registration in Patients with Hepatocellular Carcinoma.

PURPOSE: The primary objective is to determine the minimal ablation margin required to achieve a local recurrence rate of < 10% in patients with hepatocellular carcinoma undergoing thermal ablation. Secondary objectives are to analyze the correlation between ablation margins and local recurrence and to assess efficacy. MATERIALS AND METHODS: This study is a prospective, multicenter, non-experimental, non-comparative, open-label study. Patients > 18 years with Barcelona Clinic Liver Cancer stage 0/A hepatocellular carcinoma (or B with a maximum of two lesions < 5 cm each) are eligible. Patients will undergo dual-phase contrast-enhanced computed tomography directly before and after ablation. Ablation margins will be quantitatively assessed using co-registration software, blinding assessors (i.e. two experienced radiologists) for outcome. Presence and location of recurrence are evaluated independently on follow-up scans by two other experienced radiologists, blinded for the quantitative margin analysis. A sample size of 189 tumors (~ 145 patients) is required to show with 80% power that the risk of local recurrence is confidently below 10%. A two-sided binomial z-test will be used to test the null hypothesis that the local recurrence rate is ≥ 10% for patients with a minimal ablation margin ≥ 2 mm. Logistic regression will be used to find the relationship between minimal ablation margins and local recurrence. Kaplan-Meier estimates are used to assess local and overall recurrence, disease-free and overall survival. DISCUSSION: It is expected that this study will result in a clear understanding of the correlation between ablation margins and local recurrence. Using co-registration software in future patients undergoing ablation for hepatocellular carcinoma may improve intraprocedural evaluation of technical success. Trial registration The Netherlands Trial Register (NL9713), https://www.trialregister.nl/trial/9713 .

Quantified coronary total plaque volume from computed tomography angiography provides superior 10-year risk stratification.

AIMS: Automated coronary total plaque volume (TPV) quantification derived from coronary computed tomographic angiography (CTA) datasets provide exact and reliable assessment of calcified and non-calcified coronary atherosclerosis burden. The aim of this analysis was to investigate the long-term predictive value of TPV. METHODS AND RESULTS: TPV was quantified in 1577 patients undergoing coronary CTA and cardiovascular events were collected during 10.5 years (interquartile range 6.0-11.4) of follow-up. The study endpoint comprised cardiac death and acute coronary syndrome and occurred in 59 (3.7%) patients. Coronary TPV provided additive prognostic value over clinical risk assessed with the Morise Score and coronary artery disease severity (rise in C-index from 0.744 to 0.769, P = 0.03). A category-based reclassification approach combining the Morise Score and TPV revealed superior risk stratification (categorical net reclassification improvement: 0.48 with 95% CI 0.13-0.68, P < 0.001) and resulted in reclassification of 800 (51%) patients compared with the Morise Score alone. The 10-year risk for the study endpoint was 0.6% (95% CI 0-1.3) for patients classified as low risk (n = 807), 4.8% (95% CI 2.4-7.2) for patients at intermediate risk (n = 400), and 10.3% (95% CI 6.6-13.9) for patients at high risk (n = 370) using the combined reclassification approach. CONCLUSION: Quantification of TPV from coronary CTA permits an improved 10-year cardiovascular risk stratification.

Automatic coronary artery plaque thickness comparison between baseline and follow-up CCTA images.

PURPOSE: Currently, coronary plaque changes are manually compared between a baseline and follow-up coronary computed tomography angiography (CCTA) images for long-term coronary plaque development investigation. We propose an automatic method to measure the plaque thickness change over time. METHODS: We model the lumen and vessel wall for both the baseline coronary artery tree (CAT-BL) and follow-up coronary artery tree (CAT-FU) as smooth three-dimensional (3D) surfaces using a subdivision fitting scheme with the same coarse meshes by which the correspondence among these surface points is generated. Specifically, a rigid point set registration is used to transform the coarse mesh from the CAT-FU to CAT-BL. The plaque thickness and the thickness difference is calculated as the distance between corresponding surface points. To evaluate the registration accuracy, the average distance between manually defined markers on clinical scans is calculated. Artificial CAT-BL and CAT-FU pairs were created to simulate the plaque decrease and increase over time. RESULTS: For 116 pairs of markers from nine clinical scans, the average marker distance after registration was 0.95 ± 0.98 mm (two times the voxel size). On the 10 artificial pairs of datasets, the proposed method successfully located the plaque changes. The average of the calculated plaque thickness difference is the same as the corresponding created value (standard deviation ± 0.1 mm). CONCLUSIONS: The proposed method automatically calculates local coronary plaque thickness differences over time and can be used for 3D visualization of plaque differences. The analysis and reporting of coronary plaque progression and regression will benefit from an automatic plaque thickness comparison.

Apixaban versus warfarin in evaluation of progression of atherosclerotic and calcified plaques (prospective randomized trial).

Warfarin has been showed to increase vascular calcification. Apixaban, a direct factor Xa inhibitor, has no interaction with vitamin K and its effect on coronary plaques is unknown. We randomized and compared warfarin and apixaban on progression of coronary atherosclerotic plaques measured by coronary computed tomographic angiography in 66 subjects with non-valvular atrial fibrillation over the period of one-year follow up. There was significant higher total, calcified and low attenuation plaque volume in the group randomized to warfarin as compared to apixaban (all P < .05). Greater volume of total (ß2 = 28.54; P = .03), low attenuation plaque (ß2 = 3.58; P = .02) and calcified (ß2 = 14.10; P = .005) plaque progression was observed in the VKA_group.

A novel alignment procedure to assess calcified coronary plaques in histopathology, post-mortem computed tomography angiography and optical coherence tomography.

PURPOSE: Improve mapping and registration of longitudinal view on histopathology vessels in a three-dimensional alignment procedure for postmortem quantitative coronary plaque analyses. This new procedure is applied and results shown using calcified coronary plaque analyses within post-mortem computed tomography angiography (PMCTA), optical coherence tomography (OCT) and the gold standard of histopathology. RESULTS: In total, 338 annotated histopathology images were included, 166 PMCTA transversal images and 285 OCT images were aligned in the comparison. The results from the comparison using the alignment procedure showed overall that the calcified plaques seem to be overestimated by PMCTA and underestimated by OCT. CONCLUSIONS: The 3D fusion approach, aligning the images of PMCTA, OCT and histopathology as gold standard allowed for a slice-based comparison of the different modalities. The results showed that PMCTA overestimates the calcified plaques while OCT underestimates these, compared to histopathology.

Impact of diabetes on coronary artery plaque volume by coronary CT angiography and subsequent adverse cardiac events.

BACKGROUND: To investigate the impact of diabetes on coronary artery total plaque volume (TPV) and adverse events in long-term follow-up. METHODS: One-hundred-and-eight diabetic patients were matched to 324 non-diabetic patients, with respect to age, sex, body-mass index, hypertension, smoking habits, LDL and HDL cholesterol, family history for CAD as well as aspirin and statin medication. In all patients, TPV was quantified from coronary CT angiographies (CTA) using dedicated software. All-cause mortality, acute coronary syndrome and late revascularisation (>90 days) served as combined endpoint. RESULTS: Patients were followed for 5.6 years. The endpoint occurred in 18 (16.7%) diabetic and 26 (8.0%) non-diabetic patients (odds ratio 2.3, p = 0.03). Diabetic patients had significantly higher TPV than non-diabetic patients (55.1 mm³ [IQR: 6.2 and 220.4 mm³] vs. 24.9 mm³ [IQR: 0 and 166.7 mm³], p = 0.02). A TPV threshold of 110.5 mm³ provided good separation of diabetic and non-diabetic patients at higher and lower risk for adverse events. Noteworthy, diabetic and non-diabetic patients with a TPV<110.5 mm³ had comparable outcome (hazard ratio: 1.3, p = 0.59), while diabetic patients with TPV>110.5 mm³ had significantly higher incidence of adverse events (hazard ratio 2.3, p = 0.03) compared to non-diabetic patients with TPV>110.5 mm³. There was incremental prognostic value in diabetic and non-diabetic patients over the Framingham Risk Score (Integrated Discrimination Improvement: 0.052 and 0.012, p for both <0.05). CONCLUSION: Diabetes is associated with significantly higher TPV, which is independent of other CAD risk factors. Quantification of TPV improves the identification of diabetic patients at higher risk for future adverse events.