CT Coronary Angiography with 100kV tube voltage and a low noise reconstruction filter in non-obese patients: evaluation of radiation dose and diagnostic quality of 2D and 3D image reconstructions using open source software (OsiriX)

INTRODUCTION AND PURPOSE. Computed tomography coronary angiography (CTCA) has seen a dramatic evolution in the last decade owing to the availability of multislice CT scanners with 64 detector rows and beyond. However, this evolution has been paralleled by an increase in radiation dose to patients, that can reach extremely high levels (>20mSv) when retrospective ECG-gating techniques are used. On CT angiography, reduction of tube voltage allows to cut radiation dose with improved contrast resolution due to the lower energy of the X-ray beam and increased photoelectric effect. Our purpose is twofold: 1) to evaluate the radiation dose of CTCA studies carried out using a tube voltage of 100kV and a low noise reconstruction filter, compared with a conventional tube voltage of 120kV and a standard reconstruction kernel; 2) to assess the impact of the 100kV acquisition technique on the diagnostic quality of 2D and 3D image reconstructions performed with open source software (OsiriX). MATERIALS AND METHODS. Fifty-one non-obese patients underwent CTCA on a 64-row CT scanner. Out of them, 28 were imaged using a tube voltage of 100kV and a low noise reconstruction filter, while in the remaining 23 patients a tube voltage of 120kV and a standard reconstruction kernel were selected. All CTCA datasets were exported via PACS to a Macintosh™ computer (iMac™) running OsiriX 4.0 (64-bit version), and Maximum Intensity Projection (MIP), Curved Planar Reformation (CPR), and Volume Rendering (VR) views of each coronary artery were generated using a dedicated plug-in (CMIV CTA; Linköping University, Sweden). Diagnostic quality of MIP, CPR, and VR reconstructions was assessed visually by two radiologists with experience in cardiac CT using a three-point score (1=poor, 2=good, 3=excellent). Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), intravascular CT density, and effective dose for each group were also calculated. RESULTS. Image quality of VR views was significantly better with the 100kV than with the 120kV protocol (2.77±0.43 vs 2.21±0.85, p=0.0332), while that of MIP and CPR reconstructions was comparable (2.59±0.50 vs 2.32±0.75, p=0.3271, and 2.68±0.48 vs 2.32±0.67, p=0.1118, respectively). SNR and CNR were comparable between the two protocols (16.42±4.64 vs 14.78±2.57, p=0.2502, and 13.43±3.77 vs 12.08±2.10, p=0.2486, respectively), but in the 100kV group aortic root density was higher (655.9±127.2 HU vs 517.2±69.7 HU, p=0.0016) and correlated with VR image quality (rs=0.5409, p=0.0025). Effective dose was significantly lower with the 100kV than with the 120kV protocol (7.43±2.69 mSv vs 18.83±3.60 mSv, p<0.0001). CONCLUSIONS. Compared with a standard tube voltage of 120kV, usage of 100kV and a low noise filter leads to a significant reduction of radiation dose with equivalent and higher diagnostic quality of 2D and 3D reconstructions, respectively in non-obese patients

3D reconstruction of cerebral blood flow and vessel morphology from x-ray rotational angiography

Three-dimensional (3D) information on blood flow and vessel morphology is important when assessing cerebrovascular disease and when monitoring interventions. Rotational angiography is nowadays routinely used to determine the geometry of the cerebral vasculature. To this end, contrast agent is injected into one of the supplying arteries and the x-ray system rotates around the head of the patient while it acquires a sequence of x-ray images. Besides information on the 3D geometry, this sequence also contains information on blood flow, as it is possible to observe how the contrast agent is transported by the blood. The main goal of this thesis is to exploit this information for the quantitative analysis of blood flow. I propose a model-based method, called flow map fitting, which determines the blood flow waveform and the mean volumetric flow rate in the large cerebral arteries. The method uses a model of contrast agent transport to determine the flow parameters from the spatio-temporal progression of the contrast agent concentration, represented by a flow map. Furthermore, it overcomes artefacts due to the rotation (overlapping vessels and foreshortened vessels at some projection angles) of the c-arm using a reliability map. For the flow quantification, small changes to the clinical protocol of rotational angiography are desirable. These, however, hamper the standard 3D reconstruction. Therefore, a new method for the 3D reconstruction of the vessel morphology which is tailored to this application is also presented. To the best of my knowledge, I have presented the first quantitative results for blood flow quantification from rotational angiography. Additionally, the model-based approach overcomes several problems which are known from flow quantification methods for planar angiography. The method was mainly validated on images from different phantom experiments. In most cases, the relative error was between 5% and 10% for the volumetric mean flow rate and between 10% and 15% for the blood flow waveform. Additionally, the applicability of the flow model was shown on clinical images from planar angiographic acquisitions. From this, I conclude that the method has the potential to give quantitative estimates of blood flow parameters during cerebrovascular interventions

Blood Vessel Segmentation and shape analysis for quantification of Coronary Artery Stenosis in CT Angiography

This thesis presents an automated framework for quantitative vascular shape analysis of the coronary arteries, which constitutes an important and fundamental component of an automated image-based diagnostic system. Firstly, an automated vessel segmentation algorithm is developed to extract the coronary arteries based on the framework of active contours. Both global and local intensity statistics are utilised in the energy functional calculation, which allows for dealing with non-uniform brightness conditions, while evolving the contour towards to the desired boundaries without being trapped in local minima. To suppress kissing vessel artifacts, a slice-by-slice correction scheme, based on multiple regions competition, is proposed to identify and track the kissing vessels throughout the transaxial images of the CTA data. Based on the resulting segmentation, we then present a dedicated algorithm to estimate the geometric parameters of the extracted arteries, with focus on vessel bifurcations. In particular, the centreline and associated reference surface of the coronary arteries, in the vicinity of arterial bifurcations, are determined by registering an elliptical cross sectional tube to the desired constituent branch. The registration problem is solved by a hybrid optimisation method, combining local greedy search and dynamic programming, which ensures the global optimality of the solution and permits the incorporation of any hard constraints posed to the tube model within a natural and direct framework. In contrast with conventional volume domain methods, this technique works directly on the mesh domain, thus alleviating the need for image upsampling. The performance of the proposed framework, in terms of efficiency and accuracy, is demonstrated on both synthetic and clinical image data. Experimental results have shown that our techniques are capable of extracting the major branches of the coronary arteries and estimating the related geometric parameters (i.e., the centreline and the reference surface) with a high degree of agreement to those obtained through manual delineation. Particularly, all of the major branches of coronary arteries are successfully detected by the proposed technique, with a voxel-wise error at 0.73 voxels to the manually delineated ground truth data. Through the application of the slice-by-slice correction scheme, the false positive metric, for those coronary segments affected by kissing vessel artifacts, reduces from 294% to 22.5%. In terms of the capability of the presented framework in defining the location of centrelines across vessel bifurcations, the mean square errors (MSE) of the resulting centreline, with respect to the ground truth data, is reduced by an average of 62.3%, when compared with initial estimation obtained using a topological thinning based algorithm

The computation of blood flow waveforms from digital X-ray angiographic data

This thesis investigates a novel technique for the quantitative measurement of pulsatile blood flow waveforms and mean blood flow rates using digital X-ray angiographic data. Blood flow waveforms were determined following an intra-arterial injection of contrast material. Instantaneous blood velocities were estimated by generating a 'parametric image' from dynamic X-ray angiographic images in which the image grey-level represented contrast material concentration as a function of time and true distance in three dimensions along a vessel segment. Adjacent concentration-distance profiles in the parametric image of iodine concentration versus distance and time were shifted along the vessel axis until a match occurred. A match was defined as the point where the mean sum of the squares of the differences between the two profiles was a minimum. The distance translated per frame interval gave the instantaneous contrast material bolus velocity. The technique initially was validated using synthetic data from a computer simulation of angiographic data which included the effect of pulsatile blood flow and X-ray quantum noise. The data were generated for a range of vessels from 2 mm to 6 mm in diameter. Different injection techniques and their effects on the accuracy of blood flow measurements were studied. Validation of the technique was performed using an experimental phantom of blood circulation, consisting of a pump, flexible plastic tubing, the tubular probe of an electromagnetic flowmeter and a solenoid to simulate a pulsatile flow waveform which included reverse flow. The technique was validated for both two- and three-dimensional representations of the blood vessel, for various flow rates and calibre sizes. The effects of various physical factors were studied, including the distance between injection and imaging sites and the length of artery analysed. Finally, this method was applied to clinical data from femoral arteries and arteries in the head and neck

Automatic Estimation of Coronary Blood Flow Velocity Step 1 for Developing a Tool to Diagnose Patients With Micro-Vascular Angina Pectoris

Aim: Our aim was to automatically estimate the blood velocity in coronary arteries using cine X-ray angiographic sequence. Estimating the coronary blood velocity is a key approach in investigating patients with angina pectoris and no significant coronary artery disease. Blood velocity estimation is central in assessing coronary flow reserve. Methods and Results: A multi-step automatic method for blood flow velocity estimation based on the information extracted solely from the cine X-ray coronary angiography sequence obtained by invasive selective coronary catheterization was developed. The method includes (1) an iterative process of segmenting coronary arteries modeling and removing the heart motion using a non-rigid registration, (2) measuring the area of the segmented arteries in each frame, (3) fitting the measured sequence of areas with a 7◦ polynomial to find start and stop time of dye propagation, and (4) estimating the blood flow velocity based on the time of the dye propagation and the length of the artery-tree. To evaluate the method, coronary angiography recordings from 21 patients with no obstructive coronary artery disease were used. In addition, coronary flow velocity was measured in the same patients using a modified transthoracic Doppler assessment of the left anterior descending artery. We found a moderate but statistically significant correlation between flow velocity assessed by trans thoracic Doppler and the proposed method applying both Spearman and Pearson tests. Conclusion: Measures of coronary flow velocity using a novel fully automatic method that utilizes the information from the X-ray coronary angiographic sequence were statistically significantly correlated to measurements obtained with transthoracic Doppler recordings.publishedVersio