Computational fluid dynamics modeling of symptomatic intracranial atherosclerosis may predict risk of stroke recurrence.

BackgroundPatients with symptomatic intracranial atherosclerosis (ICAS) of ≥ 70% luminal stenosis are at high risk of stroke recurrence. We aimed to evaluate the relationships between hemodynamics of ICAS revealed by computational fluid dynamics (CFD) models and risk of stroke recurrence in this patient subset.MethodsPatients with a symptomatic ICAS lesion of 70-99% luminal stenosis were screened and enrolled in this study. CFD models were reconstructed based on baseline computed tomographic angiography (CTA) source images, to reveal hemodynamics of the qualifying symptomatic ICAS lesions. Change of pressures across a lesion was represented by the ratio of post- and pre-stenotic pressures. Change of shear strain rates (SSR) across a lesion was represented by the ratio of SSRs at the stenotic throat and proximal normal vessel segment, similar for the change of flow velocities. Patients were followed up for 1 year.ResultsOverall, 32 patients (median age 65; 59.4% males) were recruited. The median pressure, SSR and velocity ratios for the ICAS lesions were 0.40 (-2.46-0.79), 4.5 (2.2-20.6), and 7.4 (5.2-12.5), respectively. SSR ratio (hazard ratio [HR] 1.027; 95% confidence interval [CI], 1.004-1.051; P = 0.023) and velocity ratio (HR 1.029; 95% CI, 1.002-1.056; P = 0.035) were significantly related to recurrent territorial ischemic stroke within 1 year by univariate Cox regression, respectively with the c-statistics of 0.776 (95% CI, 0.594-0.903; P = 0.014) and 0.776 (95% CI, 0.594-0.903; P = 0.002) in receiver operating characteristic analysis.ConclusionsHemodynamics of ICAS on CFD models reconstructed from routinely obtained CTA images may predict subsequent stroke recurrence in patients with a symptomatic ICAS lesion of 70-99% luminal stenosis

Vessel tractography using an intensity based tensor model with branch detection

In this paper, we present a tubular structure seg- mentation method that utilizes a second order tensor constructed from directional intensity measurements, which is inspired from diffusion tensor image (DTI) modeling. The constructed anisotropic tensor which is fit inside a vessel drives the segmen- tation analogously to a tractography approach in DTI. Our model is initialized at a single seed point and is capable of capturing whole vessel trees by an automatic branch detection algorithm developed in the same framework. The centerline of the vessel as well as its thickness is extracted. Performance results within the Rotterdam Coronary Artery Algorithm Evaluation framework are provided for comparison with existing techniques. 96.4% average overlap with ground truth delineated by experts is obtained in addition to other measures reported in the paper. Moreover, we demonstrate further quantitative results over synthetic vascular datasets, and we provide quantitative experiments for branch detection on patient Computed Tomography Angiography (CTA) volumes, as well as qualitative evaluations on the same CTA datasets, from visual scores by a cardiologist expert

Coronary Artery Segmentation and Motion Modelling

Conventional coronary artery bypass surgery requires invasive sternotomy and the use of a cardiopulmonary bypass, which leads to long recovery period and has high infectious potential. Totally endoscopic coronary artery bypass (TECAB) surgery based on image guided robotic surgical approaches have been developed to allow the clinicians to conduct the bypass surgery off-pump with only three pin holes incisions in the chest cavity, through which two robotic arms and one stereo endoscopic camera are inserted. However, the restricted field of view of the stereo endoscopic images leads to possible vessel misidentification and coronary artery mis-localization. This results in 20-30% conversion rates from TECAB surgery to the conventional approach. We have constructed patient-specific 3D + time coronary artery and left ventricle motion models from preoperative 4D Computed Tomography Angiography (CTA) scans. Through temporally and spatially aligning this model with the intraoperative endoscopic views of the patient's beating heart, this work assists the surgeon to identify and locate the correct coronaries during the TECAB precedures. Thus this work has the prospect of reducing the conversion rate from TECAB to conventional coronary bypass procedures. This thesis mainly focus on designing segmentation and motion tracking methods of the coronary arteries in order to build pre-operative patient-specific motion models. Various vessel centreline extraction and lumen segmentation algorithms are presented, including intensity based approaches, geometric model matching method and morphology-based method. A probabilistic atlas of the coronary arteries is formed from a group of subjects to facilitate the vascular segmentation and registration procedures. Non-rigid registration framework based on a free-form deformation model and multi-level multi-channel large deformation diffeomorphic metric mapping are proposed to track the coronary motion. The methods are applied to 4D CTA images acquired from various groups of patients and quantitatively evaluated

Accuracy of 64-slice CT angiography for the detection of functionally relevant coronary stenoses as assessed with myocardial perfusion SPECT

Purpose: CT angiography (CTA) offers a valuable alternative for the diagnosis of CAD but its value in the detection of functionally relevant coronary stenoses remains uncertain. We prospectively compared the accuracy of 64-slice CTA with that of myocardial perfusion imaging (MPI) using 99mTc-tetrofosmin-SPECT as the gold standard for the detection of functionally relevant coronary artery disease (CAD). Methods: MPI and 64-slice CT were performed in 100 consecutive patients. CTA lesions were analysed quantitatively and area stenoses ≥50% and ≥75% were compared with the MPI findings. Results: In 23 patients, MPI perfusion defects were found (12 reversible, 13 fixed). A total of 399 coronary arteries and 1,386 segments was analysed. Eighty-four segments (6.1%) in 23 coronary arteries (5.8%) of nine patients (9.0%) were excluded owing to insufficient image quality. In the remaining 1,302 segments, quantitative CTA revealed stenoses ≥50% in 57 of 376 coronary arteries (15.2%) and stenoses ≥75% in 32 (8.5%) coronary arteries. Using a cut-off at ≥75% area stenosis, CTA yielded the following sensitivity, specificity, negative (NPV) and positive predictive value (PPV), and accuracy for the detection of any (fixed and reversible) MPI defect: by patient, 75%, 90%, 93%, 68% and 87%, respectively; by artery, 76%, 95%, 99%, 50% and 94%, respectively. Conclusion: Sixty-four-slice CTA is a reliable tool to rule out functionally relevant CAD in a non-selected population with an intermediate pretest likelihood of disease. However, an abnormal CTA is a poor predictor of ischaemi

Three-dimensional reconstruction of coronary arteries and plaque morphology using CT angiography - comparison and registration with IVUS

Background: The aim of this study is to present a new methodology for three-dimensional (3D) reconstruction of coronary arteries and plaque morphology using Computed Tomography Angiography (CTA). Methods: The methodology is summarized in six stages: 1) pre-processing of the initial raw images, 2) rough estimation of the lumen and outer vessel wall borders and approximation of the vessel's centerline, 3) manual adaptation of plaque parameters, 4) accurate extraction of the luminal centerline, 5) detection of the lumen - outer vessel wall borders and calcium plaque region, and 6) finally 3D surface construction. Results: The methodology was compared to the estimations of a recently presented Intravascular Ultrasound (IVUS) plaque characterization method. The correlation coefficients for calcium volume, surface area, length and angle vessel were 0.79, 0.86, 0.95 and 0.88, respectively. Additionally, when comparing the inner and outer vessel wall volumes of the reconstructed arteries produced by IVUS and CTA the observed correlation was 0.87 and 0.83, respectively. Conclusions: The results indicated that the proposed methodology is fast and accurate and thus it is likely in the future to have applications in research and clinical arena

Predictive factors of arterial calcification severity in computed tomography angiography (CTA) lower limbs

Background: The use of multi-detector row technology has resulted in shorter acquisition time, increased volume coverage, lower dose of contrast medium, and improved spatial resolution for assessing small arterial branches. However the accuracy of the computed tomography angiography (CTA) examination may be degraded by the presence of calcified plaque. The objective of this study is to evaluate the factors that contribute to the severity of arterial calcification in CT lower limbs. Methodology: A cross sectional study that conducted in Hospital Universiti Sains Malaysia. CT lower limbs with calcifications from January 2010 to May 2017 were selected for this study. Patients who were amputated, CT images with metallic stent, and those with inadequate clinical information were excluded from the study. The calcium score was analyzed using the standardized calcium score software that was used for coronary arteries. Calcium score was divided into low and high using normal distribution curve. Possible clinical factors that affect arterial calcification were studied such as peripheral arterial disease symptoms, history of acute coronary symptoms, cardiovascular disease, end stage renal disease, blood cholesterol level, smoker/non-smoker, treated for diabetes/hypertension and latest systolic blood pressure. Framingham Risk Score was calculated using General cardiovascular disease Risk Prediction calculator, from official website Framingham Heart Study. Results: A total of 51 patients was included in the study (n=51) with the mean age was 67. Majority of the participants were Malay (88.2%). The numbers of male and female participants were almost equal. Multivariate analysis showed that interrelated factors that affect log arterial calcium score included age, diabetes, peripheral arterial disease and low density lipoprotein (R2 =0.589, p<0.001 to 0.015). There weresignificant moderate correlation between Framingham Score and Agatston Score. (r=0.555, p=0.001). Conclusion: Age, diabetes mellitus, peripheral arterial disease and low density lipoprotein are the potential associated factors that can be used to screen for possibility of severe lower limb arterial calcifications. High Agatston score is associated with high Framingham risk score

High-resolution ex vivo magnetic resonance angiography: a feasibility study on biological and medical tissues

<p>Abstract</p> <p>Background</p> <p>In biomedical sciences, ex vivo angiography is a practical mean to elucidate vascular structures three-dimensionally with simultaneous estimation of intravascular volume. The objectives of this study were to develop a magnetic resonance (MR) method for ex vivo angiography and to compare the findings with computed tomography (CT). To demonstrate the usefulness of this method, examples are provided from four different tissues and species: the human placenta, a rice field eel, a porcine heart and a turtle.</p> <p>Results</p> <p>The optimal solution for ex vivo MR angiography (MRA) was a compound containing gelatine (0.05 g/mL), the CT contrast agent barium sulphate (0.43 mol/L) and the MR contrast agent gadoteric acid (2.5 mmol/L). It was possible to perform angiography on all specimens. We found that ex vivo MRA could only be performed on fresh tissue because formalin fixation makes the blood vessels permeable to the MR contrast agent.</p> <p>Conclusions</p> <p>Ex vivo MRA provides high-resolution images of fresh tissue and delineates fine structures that we were unable to visualise by CT. We found that MRA provided detailed information similar to or better than conventional CTA in its ability to visualize vessel configuration while avoiding interfering signals from adjacent bones. Interestingly, we found that vascular tissue becomes leaky when formalin-fixed, leading to increased permeability and extravascular leakage of MR contrast agent.</p

Deep learning for cardiac image segmentation: A review

Deep learning has become the most widely used approach for cardiac image segmentation in recent years. In this paper, we provide a review of over 100 cardiac image segmentation papers using deep learning, which covers common imaging modalities including magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound (US) and major anatomical structures of interest (ventricles, atria and vessels). In addition, a summary of publicly available cardiac image datasets and code repositories are included to provide a base for encouraging reproducible research. Finally, we discuss the challenges and limitations with current deep learning-based approaches (scarcity of labels, model generalizability across different domains, interpretability) and suggest potential directions for future research

Three-dimensional reconstruction of coronary arteries and plaque morphology using CT angiography - comparison and registration with IVUS

BACKGROUND: The aim of this study is to present a new methodology for three-dimensional (3D) reconstruction of coronary arteries and plaque morphology using Computed Tomography Angiography (CTA). METHODS: The methodology is summarized in six stages: 1) pre-processing of the initial raw images, 2) rough estimation of the lumen and outer vessel wall borders and approximation of the vessel’s centerline, 3) manual adaptation of plaque parameters, 4) accurate extraction of the luminal centerline, 5) detection of the lumen - outer vessel wall borders and calcium plaque region, and 6) finally 3D surface construction. RESULTS: The methodology was compared to the estimations of a recently presented Intravascular Ultrasound (IVUS) plaque characterization method. The correlation coefficients for calcium volume, surface area, length and angle vessel were 0.79, 0.86, 0.95 and 0.88, respectively. Additionally, when comparing the inner and outer vessel wall volumes of the reconstructed arteries produced by IVUS and CTA the observed correlation was 0.87 and 0.83, respectively. CONCLUSIONS: The results indicated that the proposed methodology is fast and accurate and thus it is likely in the future to have applications in research and clinical arena