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J J Gerbrands

Publications and source records attributed to J J Gerbrands.

8 recordsLinked to original sources

Derivation of optimal filters for the detection of coronary arteries.

In this paper optimal filters for the detection of coronary arteries with a diameter range of 0.5-6.0 mm in digital X-ray images are derived using a computational approach. This approach is based on the two requirements for optimal detection. First, the filter should maximize the number of detected true edges and minimize the number of detected false edges. Second, if an edge has been detected, its position should be as close as possible to the true edge position in the image. Since the grey value profile in a digital X-ray image associated with an arterial vessel is asymmetric, the theory on edge detection derived by Canny has been expanded with two additional boundary constraints to make it suitable for the derivation of filters for asymmetric edges. It is demonstrated that it is possible to derive optimal filters for coronary segments. The localization error, defined by the square root of the sum of the squared systematic and random errors in the assessment of the arterial diameter, depends on the size of the coronary artery and the amount of noise in the image. In this paper, an evaluation study is described to assess the relationship between localization error and the amount of noise upon the vessel profile. For that purpose, an analytical description of the vessel profile in an angiographic image was derived. For the larger arteries the relation between noise and localization error was found to be linear and no systematic over- or underestimations were observed, even if the noise level was very high. However, it can be shown that the smallest diameter that can be measured depends on the amount of noise present in the data. Even for images that contain only a low amount of noise, arterial diameters below 0.7 mm cannot be measured accurately. If the noise in the image increases, the lowest measurable arterial diameter value also increases. Also the random error increases rapidly for vessel diameters below 1.2 mm, but with a limited amount of noise and a diameter value above 0.7 mm the random error is still acceptable [0.15 mm (21%) for 0.7-mm vessels, 0.06 mm (6%) for 1-mm vessels].

Coronary Angiography↗

A model for the modulation transfer function of cardiovascular x-ray systems.

RATIONALE AND OBJECTIVES: To derive a theoretical model for the modulation transfer function (MTF) of the complete imaging chain of a cardiovascular x-ray system. A sufficiently accurate MTF model may be used in quantitative coronary arteriographic applications to decrease the systematic overestimation of small coronary vessels. The model could be used to restore blurred images in image restoration applications and also may be used for image quality assurance measurements. METHODS: Digital images of a step wedge phantom were acquired at different modes (5-, 7-, and 9-inch) of the image intensifier and at different kilovolt levels of the x-ray generator. From these images the MTFs that were used to estimate the parameters of the model were assessed. RESULTS: The total MTF of the cardiovascular x-ray imaging chain consisting of image intensifier, video camera, optical elements, and analog/digital converter can be modeled by the simple formula MTF = e-(w/f)R, where w is the frequency in linepairs per millimeter. The constants frequency f and the device index n are parameters that can be derived for an individual x-ray system using the phantom. In this formula, the contribution from the focus of the x-ray source has been excluded. The mean square error (MSE) between the measured values and those assessed from the theoretical model of the MTF for the horizontal direction was found to be equal to 0.00003 for the 5-inch mode of image intensifier, and for the vertical resolution at the 9-inch mode this MSE was equal to 0.00038. In addition, we have demonstrated that the contributions of the video camera and the image intensifier to the total MTF can be replaced by an imaginary electron-optical device. CONCLUSION: An accurate representation for the MTF of a cardiovascular x-ray system has been derived. This MTF model can be used in x-ray image quality assurance measurements and in quantitative image processing applications.

Cardiovascular System↗

Automated extraction, labelling and analysis of the coronary vasculature from arteriograms.

For clinical decision-making and documentation purposes we have developed techniques to extract, label and analyze the coronary vasculature from arteriograms in an automated, quantitative manner. Advanced image processing techniques were applied to extract and analyze the vasculatures from non-subtracted arteriograms while artificial intelligence techniques were employed to assign anatomical labels. Lumen diameters of 11 phantom vessels were assessed with an accuracy of 0.27 +/- 0.19 mm (dtrue = 0.45 + 0.92dmeasured; r > 0.99) and 0.21 +/- 0.15 mm (dtrue = 0.42 + 0.91dmeasured; r > 0.99), from cine and digital images, respectively. We collected a total of 15 routinely acquired cine-arteriograms showing 74 vessel segments with 18 stenoses (severity larger than 30% assessed quantitatively), and 53 digital arteriograms showing 236 vessel segments with 69 stenoses. From the cine arteriograms we extracted 64 (86%) of the vessel segments without manual correction and 196 (83%) from the digital arteriograms. Repeated analysis (3 times) of the arteriograms by the same operator resulted in a standard deviation of the mean segment diameters (precision) of 0.064 mm for the cine-images and 0.020 mm for the digital images, while the standard deviations in the measurement of the minimal luminal diameter of the observed stenoses were 0.020 mm and 0.019 mm, respectively. The LAD artery, the septal and diagonal branches were correctly identified automatically in 86% of the segments. From these evaluations we conclude that our automated approach provides reliable tools for the assessment of multi-vessel disease, both in an off- and on-line environment.

Cineangiography↗

Accuracy and precision of quantitative digital coronary arteriography: observer-, short-, and medium-term variabilities.

Coronary arteriograms are increasingly acquired and stored in digital format, which allows instantaneous review of the pictorial data during the cardiac catheterization procedure. To support the angiographer in choosing the optimal sizes of the recanalization devices and studying the efficacy of the recanalization procedures, we have developed a new analytical software package (Automated Coronary Analysis = ACA) on the Philips DCI (-SX) digital cardiac imaging system. The ACA-package allows the objective and reproducible assessment of the morphologic and functional severity of coronary obstructions. Required user interaction is limited to the definition of the start and end points of the coronary segment to be analyzed. Automated contour detection is based on the use of first and second derivative functions along scanlines perpendicular to the automatically computed vessel pathline in the first iteration and perpendicular to the initial contours in the second iteration. These derivative functions have been modified based on the line spread function of the X-ray imaging chain, which is of particular importance for the accurate measurement of small vessel sizes. Phantom studies have indeed demonstrated that vessel sizes down to 0.66 mm can be measured accurately and reproducibly. Inter- and intraobserver variability studies have demonstrated a variability in the obstruction diameter of 0.11 mm and 0.10 mm, respectively, and in the percent diameter stenosis of 5.64% and 3.18%, respectively. These variability studies have been extended to short-term studies with repeated acquisition in the same angiographic views after 5 min and to medium-term studies with repeated acquisition in the initial angiographic views at the end of the catheterization procedures. With these standardized repeated acquisition and analysis procedures, the variabilities in the obstruction diameters increased to 0.19 and 0.18 mm, respectively, and remained below 6% in the percent diameter stenosis (5.61% and 5.28%, respectively). With an analysis time of approximately 15 sec on the DCI-SX, an efficient tool is now available in the catheterization laboratory for the objective and reproducible assessment of vessel dimensions and changes therein as a result of recanalization procedures.

Coronary Angiography↗

Developments towards the slice-wise three-dimensional reconstruction of the distribution of the contrast perfusion in the myocardial muscle from biplane angiographic views.

In theory, radiographic myocardial perfusion imaging allows a quantitative assessment of the functional significance of a coronary stenosis. However, in the conventional two-dimensional projection images there does not exist a one-two-one relationship between a selected myocardial region of interest (ROI) and one particular coronary segment perfusing that area due to over-projection of myocardial regions in front of and behind the selected ROI perfused by other arterial segments, which may result in measurements which are difficult to interpret or even unreliable. To overcome these problems, we have developed two algorithms to determine the spatial distribution of perfusion levels in slices of the heart, selected approximately perpendicular to the left ventricular long axis, from two orthogonal angiographic views: the Segmental Reconstruction Technique (SRT) and the Network Programming Reconstruction Technique (NPRT). Both techniques require a priori geometric information about the myocardium, which can be obtained from the epicardial coronary tree (epicardial boundaries) and the left ventricular lumen (endocardial boundaries). Using the SRT approach, pie-shaped segments are defined for each slice within the myocardial geometric constraints such that superimposition of these segments when projected in orthogonal biplane views is minimal. The reconstruction process uses a model with identical myocardial geometry and definition of segments. Each segment of the model is assigned a relative perfusion level with unit one if no other a priori information is available. In this case, the model contains geometric information only. In case a priori information about expected segmental perfusion levels is available, a level between zero and one is assigned to each segment. The a priori information on the myocardial perfusion levels can be extracted from either anatomic information about the location and severity of existing coronary arterial obstructions, or from a slice adjacent to the one under reconstruction. Using the NPRT approach perfusion levels are computed for each volume picture element of a slice within the reconstructed myocardial geometry, thus resulting in a much higher spatial resolution than the SRT approach. A priori information of perfusion levels must be included in this approach, again based upon anatomical information, or upon the slice adjacent to the one under reconstruction. The very first slice of a myocardial study will be reconstructed by the SRT approach. Extensive computer simulations for the SRT have proved that the mean difference between the actual and reconstructed segmental perfusion levels, on a scale from 0 to 1, is smaller than 0.45 (SEE = 0.0033, REE = 1.80) for various coronary artery disease states without the use of a priori information on expected perfusion levels. This error becomes smaller than 0.36 (SEE = 0.0026, REE = 1.42), if a priori information in the reconstruction technique is included. Similar computer simulations for the NPRT have proved that these mean differences in geometric segments equal to those defined for the SRT, are smaller than 2.94 (SEE = 0.0308, REE = 0.77) on a scale from 0 to 16, without the use of a priori information on expected perfusion levels, and smaller than 1.72 (SEE = 0.0304, REE = 1.10) on the same scale when a priori information is included. Therefore, it may be concluded that slice-wise three-dimensional reconstruction of perfusion levels is feasible from biplane computer-simulated data, and that a similarity exists for mean perfusion levels in corresponding regions in the simulated and reconstructed slices, for various states of single coronary artery disease.

Algorithms↗

Three-dimensional reconstruction of myocardial contrast perfusion from biplane cineangiograms by means of linear programming techniques.

The assessment of coronary flow reserve from the instantaneous distribution of the contrast agent within the coronary vessels and myocardial muscle at the control state and at maximal flow has been limited by the superimposition of myocardial regions of interest in the two-dimensional images. To overcome these limitations, we are in the process of developing a three-dimensional (3D) reconstruction technique to compute the contrast distribution in cross sections of the myocardial muscle from two orthogonal cineangiograms. To limit the number of feasible solutions in the 3D-reconstruction space, the 3D-geometry of the endo- and epicardial boundaries of the myocardium must be determined. For the geometric reconstruction of the epicardium, the centerlines of the left coronary arterial tree are manually or automatically traced in the biplane views. Next, the bifurcations are detected automatically and matched in these two views, allowing a 3D-representation of the coronary tree. Finally, the circumference of the left ventricular myocardium in a selected cross section can be computed from the intersection points of this cross section with the 3D coronary tree using B-splines. For the geometric reconstruction of the left ventricular cavity, we envision to apply the elliptical approximation technique using the LV boundaries defined in the two orthogonal views, or by applying more complex 3D-reconstruction techniques including densitometry. The actual 3D-reconstruction of the contrast distribution in the myocardium is based on a linear programming technique (Transportation model) using cost coefficient matrices. Such a cost coefficient matrix must contain a maximum amount of a priori information, provided by a computer generated model and updated with actual data from the angiographic views. We have only begun to solve this complex problem. However, based on our first experimental results we expect that the linear programming approach with advanced cost coefficient matrices and computed model will lead to acceptable solutions in the 3D-reconstruction of the myocardial contrast distribution from biplane cineangiograms.

Cineangiography↗

Assessment of short-, medium-, and long-term variations in arterial dimensions from computer-assisted quantitation of coronary cineangiograms.

A computer-assisted technique has been developed to assess absolute coronary arterial dimensions from 35 mm cineangiograms. The boundaries of optically magnified and video-digitized coronary segments and the intracardiac catheter are defined by automated edge-detection techniques. Contour positions are corrected for pincushion distortion. The accuracy and precision of the edge detection procedure as assessed from cinefilms of contrast-filled acrylate (Perspex) models were -30 and 90 micrometers, respectively. The variability of the analysis procedure itself in terms of absolute arterial dimensions was less than 0.12 mm, and in terms of percentage arterial narrowing for coronary obstructions less than 2.74%. Short-, medium-, and long-term variability measurements were assessed from repeated coronary angiographic examinations performed 5 min, 1 hr, and 90 days apart, respectively. For all studies the mean differences in absolute diameters were less than 0.13 mm. The variability in obstruction diameter ranged from 0.22 mm for the best-controlled study (medium-term) to 0.36 mm for the least-controlled study (long-term); variability in reference diameter ranged from 0.15 to 0.66 mm, respectively. It is concluded that the biological variations are a source of major concern and that further attempts toward standardization of the angiographic procedure are seriously needed.

Cineangiography↗

Clinical validation of fully automated computation of ejection fraction from gated equilibrium blood-pool scintigrams.

A fully automated procedure for the computation of left-ventricular ejection fraction (EF) from cardiac-gated Tc-99m blood-pool (GBP) scintigrams with fixed, dual, and variable ROI methods is described. By comparison with EF data from contrast ventriculography in 68 patients, the dual-ROI method (separate end-diastolic and end-systolic contours) was found to be the method of choice; processing time was 2 min. Success score of dual-ROI procedure was 92% as assessed from 100 GBP studies. Overall reproducibility of data acquisition and analysis was determined in 12 patients. Mean value and standard deviation of differences between repeat studies (average time interval 27 min) were 0.8% and 4.3% EF units, respectively, (r = 0.98). We conclude that left-ventricular EF can be computed automatically from GBP scintigrams with minimal operator-interaction and good reproducibility; EFs are similar to those from contrast ventriculography.

Adult↗