The main function of the IVUS technique is to serve as a guide in the interventional procedures, allowing us to measure the cross section of the artery. The precision in the measurements of distance is subject to the following potential sources of error :
(a) Incorrect identification of the surface and the sections to be measured. Although the vessel and the interface defining the wall vessel have sufficiently good acoustics in most of the cases, in several cases the identification of the surface and differentiating tissues can be difficult. Improving the radial resolution could improve the detection of contours, which would reduce the errors. These errors can in some cases be systematic and lead to an overestimation of the dimensions. This could get considerably worse if the irregularities of the vessels are very pronounced.
(b) Assumption that the sound speed is constant in the arterial structure. The second kind of problem related to the assumption of constant speed of the sound of 1540 m/sec is systematic and small (of the order of 1-2%), which brings as a consequence the propagation of the error in the location of each one of the structures under study.
(c) Artifacts caused by inhomogeneities in the rotation of the catheter and pronounced reverberations generated by very acute irregularities of the vessel. The appearance of some artifacts such as the inhomogeneities in the rotation of the catheter influences the quality of the image. The absence of beams, when the catheter stops momentarily, brings as a consequence a propagation of errors in the tangential direction of the image.
(d) Presence of zones of acoustic shade, which prevents access to certain regions of interest (ROIs). The presence of zones of acoustic shade is intimately related to the presence of calcification or regions of high acoustic impedance. The shades prevent some structures from being evaluated from the distribution of the gray levels.
(e) The presence of the catheter, the reticule, and the guide proves disadvantageous to the processing of the images and to the evaluation of the data by some procedure of images processing.
(f) Impossibility of spatially locating the catheter. The impossibility of locating the catheter with respect to a specific axis of coordinates makes it impossible to make any attempt for three-dimensional representation of the vessel only with the IVUS technique. For example, spatial location of the effective section of the lumen and location of plaque and the reconstruction in the lengthwise direction of the vessel are still an open problem of investigation .
(g) Impossibility of evaluating dynamic parameters, different from the single static characterization using the gray levels. First achievements are related to IVUS elastography  the purpose of which is to propose a technique for tissue characterization.
The mentioned shortcomings are difficult to quantify and depend on the experience of the operator, that is he should have been trained in handling a large number of patient cases. Some of the limitations of the IVUS technique can be attenuated through algorithms of image processing; the limitations due to a suboptimal location of the borders of the arterial structure can be overcome with new algorithms of segmentation. The question is how to develop robust algorithms that can solve these problems, analyzing the artifacts with their multiple appearances in IVUS images. Having a complete set of patient data to present all variance of artifacts appearance in images would mean to dispose of a huge number of patient cases. A more efficient solution is to develop a simulation model for IVUS data construction so that synthetic data is available in order to "train" image processing techniques. In this way, different appearances of artifacts can be designed to assure robust performance of image processing techniques.
Differences in IVUS data are caused not only by different morphological structures of vessels but also by different parameters that influence the formation of IVUS images. The images depend on the IVUS apparatus calibration as well as on interventional devices; small differences in parameters can lead to a different gray-level appearance that can be interpreted in a different way by physicians. A simulation model for IVUS data can help train the medical staff as well as play an important role in designing and testing new interventional devices. At the end, being aware which parameters and in which grade influence to image formation is of unquestionable importance for all persons involved in comprehension of IVUS data and taking final decision for diagnosis and intervention of vessel lesions. In this chapter, we discuss a simple simulation model for the formation of 2D IVUS data that explains the complete process of data generation as a result of the interaction between ultrasound signals and vessel morphological structures.
Correct image processing needs an understanding of image formation, gray-level meaning, artifact causes, the averaging, and the motion of the dynamics structures effects in the image. The generation of simulated IVUS images investigates four important aspects: (a) The generation, processing, and visualization of the data in the format that doctors use, (b) the exploration of some of the artifacts generated by the averaging of the beams, (c) the smoothing and treatment of the images to generate sufficient data for the validation of image processing algorithms, and (d) comparison of data generated by the image formation model with the real data. IVUS images can be obtained in a simulated form, from a simple physical model based on the transmission and reception of high-frequency sound waves, when these radially penetrate a simulated arterial structure (Fig. 1.4). We assume that for this model the waves are emitted by a transducer located at the center of the artery and that these waves propagate radially through the blood and the arterial structures (intima, media, and adventitia), being reflected progressively by them. The reflected waves or echoes that return are received by the transducer, which now behaves as a receiver. The time interval between the emission and the reception of the waves is directly related to the distance between the source and the reflector (Fig. 1.5). The echo amplitude, which is a function of time, is transformed on gray scale and later to penetration depth, so the radial coordinate is determined. If we place a rotatory transducer, make a registry of the corresponding echoes for each angular position of the transducer, and combine all the lines obtained from different positions, we will be able to obtain a simulated 2D image of the structure under study. The 3D IVUS simulated images can be generated as a sequence of n-planes generated independently, taking into account the arterial deformation caused by the blood pulsatile pressure.
Was this article helpful?