Three-Dimensional Ultrasound Imaging
01 May 2001-Physics in Medicine and Biology (Annual Reviews 4139 El Camino Way, P.O. Box 10139, Palo Alto, CA 94303-0139, USA)-Vol. 46, Iss: 5, pp 463-510
TL;DR: A review article describes the developments of a number of 3D ultrasound imaging systems using mechanical, free-hand and 2D array scanning techniques and the sources of errors in the reconstruction techniques as well as formulae relating design specification to geometric errors.
Abstract: Ultrasound is an inexpensive and widely used imaging modality for the diagnosis and staging of a number of diseases. In the past two decades, it has benefited from major advances in technology and has become an indispensable imaging modality, due to its flexibility and non-invasive character. In the last decade, research investigators and commercial companies have further advanced ultrasound imaging with the development of 3D ultrasound. This new imaging approach is rapidly achieving widespread use with numerous applications. The major reason for the increase in the use of 3D ultrasound is related to the limitations of 2D viewing of 3D anatomy, using conventional ultrasound. This occurs because: (a) Conventional ultrasound images are 2D, yet the anatomy is 3D, hence the diagnostician must integrate multiple images in his mind. This practice is inefficient, and may lead to variability and incorrect diagnoses. (b) The 2D ultrasound image represents a thin plane at some arbitrary angle in the body. It is difficult to localize the image plane and reproduce it at a later time for follow-up studies. In this review article we describe how 3D ultrasound imaging overcomes these limitations. Specifically, we describe the developments of a number of 3D ultrasound imaging systems using mechanical, free-hand and 2D array scanning techniques. Reconstruction and viewing methods of the 3D images are described with specific examples. Since 3D ultrasound is used to quantify the volume of organs and pathology, the sources of errors in the reconstruction techniques as well as formulae relating design specification to geometric errors are provided. Finally, methods to measure organ volume from the 3D ultrasound images and sources of errors are described.
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University of Chicago1, University of Padua2, Mount Sinai Hospital3, Vita-Salute San Raffaele University4, University of Duisburg-Essen5, Harvard University6, VU University Medical Center7, Medical University of Łódź8, University of Liège9, Cleveland Clinic10, Houston Methodist Hospital11, University of Cambridge12, Imperial College London13, Tufts University14, Mayo Clinic15, Medical University of South Carolina16, Yale University17, Erasmus University Rotterdam18
TL;DR: The main goal of this document is to provide a practical guide on how to acquire, analyze, and display the various cardiac structures using 3D echocardiography, as well as limitations of the technique.
Abstract: CRT
: Cardiac resynchronization therapy
ECG
: Electrocardiographic
LV
: Left ventricular
RV
: Right ventricular
SDI
: Systolic dyssynchrony index
TEE
: Transesophageal echocardiographic
3D
: Three-dimensional
3DE
: Three-dimensional echocardiographic
TTE
: Transthoracic echocardiographic
TV
: Tricuspid valve
2D
: Two-dimensional
Three-dimensional (3D) echocardiographic (3DE) imaging represents a major innovation in cardiovascular ultrasound. Advancements in computer and transducer technologies permit real-time 3DE acquisition and presentation of cardiac structures from any spatial point of view. The usefulness of 3D echocardiography has been demonstrated in (1) the evaluation of cardiac chamber volumes and mass, which avoids geometric assumptions; (2) the assessment of regional left ventricular (LV) wall motion and quantification of systolic dyssynchrony; (3) presentation of realistic views of heart valves; (4) volumetric evaluation of regurgitant lesions and shunts with 3DE color Doppler imaging; and (5) 3DE stress imaging. However, for 3D echocardiography to be implemented in routine clinical practice, a full understanding of its technical principles and a systematic approach to image acquisition and analysis are required. The main goal of this document is to provide a practical guide on how to acquire, analyze, and display the various cardiac structures using 3D echocardiography, as well as limitations of the technique. In addition, this document describes the current and potential clinical applications of 3D echocardiography along with their strengths and weaknesses.
### a. Fully Sampled Matrix-Array Transducers
An important milestone in the history of real-time 3D echocardiography was reached shortly after the year 2000, with the development of fully sampled matrix-array transducers. These transducers provided excellent real-time imaging of the beating heart in three dimensions and required significant technological developments in both hardware and software, including transducer design, microelectronic techniques, and computing.
Currently, 3DE matrix-array transducers are composed of nearly 3,000 piezoelectric elements with operating frequencies ranging from 2 to 4 MHz and from 5 to 7 MHz for transthoracic echocardiographic (TTE) and transesophageal echocardiographic (TEE) imaging, respectively. These piezoelectric elements are arranged in a matrix configuration within the transducer and require a large number of digital channels for these fully sampled elements to be connected. To reduce both …
985 citations
TL;DR: Carotid plaque area and progression of plaque identified high-risk patients and may improve cost-effectiveness of secondary preventive treatment and may be useful for targeting preventive therapy.
Abstract: Background and Purpose—Carotid plaque area measured by ultrasound (cross-sectional area of longitudinal views of all plaques seen) was studied as a way of identifying patients at increased risk of stroke, myocardial infarction, and vascular death. Methods—Patients from an atherosclerosis prevention clinic were followed up annually for up to 5 years (mean, 2.51.3 years) with baseline and follow-up measurements recorded. Plaque area progression (or regression) was defined as an increase (or decrease) of 0.05 cm 2 from baseline. Results—Carotid plaque areas from 1686 patients were categorized into 4 quartile ranges: 0.00 to 0.11 cm 2 (n422), 0.12 to 0.45 cm 2 (n424), 0.46 to 1.18 cm 2 (n421), and 1.19 to 6.73 cm 2 (n419). The combined 5-year risk of stroke, myocardial infarction, and vascular death increased by quartile of plaque area: 5.6%, 10.7%, 13.9%, and 19.5%, respectively (P0.001) after adjustment for all baseline patient characteristics. A total of 1085 patients had 1 annual carotid plaque area measurements: 685 (63.1%) had carotid plaque progression, 306 (28.2%) had plaque regression, and 176 (16.2%) had no change in carotid plaque area over the period of follow-up. The 5-year adjusted risk of combined outcome was 9.4%, 7.6%, and 15.7% for patients with carotid plaque area regression, no change, and progression, respectively (P0.003). Conclusions—Carotid plaque area and progression of plaque identified high-risk patients. Plaque measurement may be useful for targeting preventive therapy and evaluating new treatments and response to therapy and may improve cost-effectiveness of secondary preventive treatment. (Stroke. 2002;33:2916-2922.)
555 citations
TL;DR: It is highly expected that micro/nanoparticle‐augmented SDT will be quickly developed as a new and efficient therapeutic modality which will find practical applications in cancer treatment and fundamental disciplines regarding materials science, chemistry, medicine and nanotechnology will be advanced.
Abstract: The fast development of photoactivation for cancer treatment provides an efficient photo-therapeutic strategy for cancer treatment, but traditional photodynamic or photothermal therapy suffers from the critical issue of low in vivo penetration depth of tissues. As a non-invasive therapeutic modality, sonodynamic therapy (SDT) can break the depth barrier of photoactivation because ultrasound has an intrinsically high tissue-penetration performance. Micro/nanoparticles can efficiently augment the SDT efficiency based on nanobiotechnology. The state-of-art of the representative achievements on micro/nanoparticle-enhanced SDT is summarized, and specific functions of micro/nanoparticles for SDT are discussed, from the different viewpoints of ultrasound medicine, material science and nanobiotechnology. Emphasis is put on the relationship of structure/composition-SDT performance of micro/nanoparticle-based sonosensitizers. Three types of micro/nanoparticle-augmented SDT are discussed, including organic and inorganic sonosensitizers and micro/nanoparticle-based but sonosensitizer-free strategies to enhance the SDT outcome. SDT-based synergistic cancer therapy augmented by micro/nanoparticles and their biosafety are also included. Some urgent critical issues and potential developments of micro/nanoparticle-augmented SDT for efficient cancer treatment are addressed. It is highly expected that micro/nanoparticle-augmented SDT will be quickly developed as a new and efficient therapeutic modality which will find practical applications in cancer treatment. At the same time, fundamental disciplines regarding materials science, chemistry, medicine and nanotechnology will be advanced.
497 citations
TL;DR: Several popular deep learning architectures are briefly introduced, and their applications in various specific tasks in US image analysis, such as classification, detection, and segmentation are discussed.
448 citations
TL;DR: In this article, the authors review progress made largely within the last five years towards the routine use of anatomically realistic CFD models, derived from in vivo medical imaging, to elucidate the role of local hemodynamics in the development and progression of atherosclerosis in large arteries.
Abstract: Local hemodynamics are an important factor in atherosclerosis, from the development of early lesions, to the assessment of stroke risk, to determining the ultimate fate of a mature plaque. Until recently, our understanding of arterial fluid dynamics and their relationship to atherosclerosis was limited by the use of idealized or averaged artery models. Recent advances in medical imaging, computerized image processing, and computational fluid dynamics (CFD) now make it possible to computationally reconstruct the time-varying, three-dimensional blood flow patterns in anatomically realistic models. In this paper we review progress, made largely within the last five years, towards the routine use of anatomically realistic CFD models, derived from in vivo medical imaging, to elucidate the role of local hemodynamics in the development and progression of atherosclerosis in large arteries. In addition to describing various image-based CFD studies carried out to date, we review the medical imaging and image processing techniques available to acquire the necessary geometric and functional boundary conditions. Issues related to accuracy, precision, and modeling assumptions are also discussed. © 2002 Biomedical Engineering Society.
380 citations
References
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TL;DR: The rapidly expanding body of work on the development and application of deformable models to problems of fundamental importance in medical image analysis, including segmentation, shape representation, matching and motion tracking is reviewed.
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TL;DR: This paper presents a front-to-back image-order volume-rendering algorithm and discusses two techniques for improving its performance, which employs a pyramid of binary volumes to encode spatial coherence present in the data and uses an opacity threshold to adaptively terminate ray tracing.
Abstract: Volume rendering is a technique for visualizing sampled scalar or vector fields of three spatial dimensions without fitting geometric primitives to the data. A subset of these techniques generates images by computing 2-D projections of a colored semitransparent volume, where the color and opacity at each point are derived from the data using local operators. Since all voxels participate in the generation of each image, rendering time grows linearly with the size of the dataset. This paper presents a front-to-back image-order volume-rendering algorithm and discusses two techniques for improving its performance. The first technique employs a pyramid of binary volumes to encode spatial coherence present in the data, and the second technique uses an opacity threshold to adaptively terminate ray tracing. Although the actual time saved depends on the data, speedups of an order of magnitude have been observed for datasets of useful size and complexity. Examples from two applications are given: medical imaging and molecular graphics.
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TL;DR: This paper has reviewed, with somewhat variable coverage, the nine MR image segmentation techniques itemized in Table II; each has its merits and drawbacks.
Abstract: This paper has reviewed, with somewhat variable coverage, the nine MR image segmentation techniques itemized in Table II. A wide array of approaches have been discussed; each has its merits and drawbacks. We have also given pointers to other approaches not discussed in depth in this review. The methods reviewed fall roughly into four model groups: c-means, maximum likelihood, neural networks, and k-nearest neighbor rules. Both supervised and unsupervised schemes require human intervention to obtain clinically useful results in MR segmentation. Unsupervised techniques require somewhat less interaction on a per patient/image basis. Maximum likelihood techniques have had some success, but are very susceptible to the choice of training region, which may need to be chosen slice by slice for even one patient. Generally, techniques that must assume an underlying statistical distribution of the data (such as LML and UML) do not appear promising, since tissue regions of interest do not usually obey the distributional tendencies of probability density functions. The most promising supervised techniques reviewed seem to be FF/NN methods that allow hidden layers to be configured as examples are presented to the system. An example of a self-configuring network, FF/CC, was also discussed. The relatively simple k-nearest neighbor rule algorithms (hard and fuzzy) have also shown promise in the supervised category. Unsupervised techniques based upon fuzzy c-means clustering algorithms have also shown great promise in MR image segmentation. Several unsupervised connectionist techniques have recently been experimented with on MR images of the brain and have provided promising initial results. A pixel-intensity-based edge detection algorithm has recently been used to provide promising segmentations of the brain. This is also an unsupervised technique, older versions of which have been susceptible to oversegmenting the image because of the lack of clear boundaries between tissue types or finding uninteresting boundaries between slightly different types of the same tissue. To conclude, we offer some remarks about improving MR segmentation techniques. The better unsupervised techniques are too slow. Improving speed via parallelization and optimization will improve their competitiveness with, e.g., the k-nn rule, which is the fastest technique covered in this review. Another area for development is dynamic cluster validity. Unsupervised methods need better ways to specify and adjust c, the number of tissue classes found by the algorithm. Initialization is a third important area of research. Many of the schemes listed in Table II are sensitive to good initialization, both in terms of the parameters of the design, as well as operator selection of training data.(ABSTRACT TRUNCATED AT 400 WORDS)
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Abstract: Most direct volume renderings produced today employ 1D transfer functions which assign color and opacity to the volume based solely on the single scalar quantity which comprises the data set. Though they have not received widespread attention, multi-dimensional transfer functions are a very effective way to extract materials and their boundaries for both scalar and multivariate data. However, identifying good transfer functions is difficult enough in 1D, let alone 2D or 3D. This paper demonstrates an important class of 3D transfer functions for scalar data, and describes the application of multi-dimensional transfer functions to multivariate data. We present a set of direct manipulation widgets that make specifying such transfer functions intuitive and convenient. We also describe how to use modern graphics hardware to both interactively render with multidimensional transfer functions and to provide interactive shadows for volumes. The transfer functions, widgets and hardware combine to form a powerful system for interactive volume exploration.
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