Agile Ultrasound The Next Revolution in Ultrasound Imaging
Abstract Diagnostic use of ultrasound has greatly expanded over the past couple of decades because it offers many advantages as an imaging modality. Over that time, image quality has improved significantly, however, fundamental issues remain. The human body consists of a variety of tissue types, each of which affects the ultrasound beam differently. It is theoretically possible to compensate for the sound characteristics of different tissue types, but because ultrasound must provide real-time images, the time permitted for computation of those corrections is short. Because of this time constraint, conventional ultrasound systems must limit computational complexity, making many simplifying assumptions about the body in order to achieve real-time imaging. This leads to compromised image quality and requires that the user make many system adjustments to compensate for the resulting reductions in image quality. Advances in ultrasound system designs over the past ten years have made many improvements to the backend post-processing capabilities, but have not addressed the fundamental acquisition of data that drives image quality. To address these issues, GE has developed a new Agile Acoustic Architecture that uses advanced models of sound interaction with different tissue types and powerful distributed intelligence to bring image quality to new levels. Introduction Ultrasound is an indispensable diagnostic tool because of its non-invasive, non-ionizing, real-time, portable, and low-cost nature. However, when compared with other imaging modalities, ultrasound image quality is more variable, depending both on type of patient and the expertise of the operator. Reducing the patient and user dependencies would have a great impact on ultrasound acceptance. The root cause of these image quality dependencies is the complex interaction of the human body with the ultrasound signal. Compared with other modalities, ultrasound users have become accustomed to making many more system adjustments to improve the image quality to compensate for the distortions that come from these complex interactions. The complex interaction of sound in the human body The human body consists of many different tissue types and structures, the properties of which have been well studied and characterized for differences in attenuation and speed of sound. Tissue Attenuation @ 1 MHz Sound Speed (m/s) (db/cm) Water 0.002 1480 Blood 0.18 1560 Liver 0.94 1555 Muscle 1.2 1600 Kidney 1.0 1565 Fat 0.63 1460 Bone 20 4080 Table 1: Ultrasound attenuation and speed of sound for various tissue types 1 Page 2 of 10
Figure 1: Transverse section of upper Figure 2: Attenuation versus frequency for abdominal viscera 1 various tissue types 2 As ultrasound passes through multiple different tissues in the body, variations in the speed and attenuation along the ultrasound beam cause an aberration or distortion in the beam. As an example, sound passing through the body along the dashed white line in Figure 1 passes through skin, subcutaneous fat, muscle, and liver tissue before it reaches the kidney, and passes through the same mix of tissues on return. Figure 3 shows the effect on an ultrasound waveform after passing through such tissue types, which induces a depth dependent distortion. Near field Middle field Far field Ideal propagation Attenuation Attenuation + Phase aberration Attenuation + Phase aberration + Nonlinear propagation Figure 3: Distortion of ultrasound waveform over depth due to various causes As shown in figure 2, attenuation of ultrasound is not only tissue dependent but also frequency dependent, and thus different frequencies will experience different levels of distortion. Since Page 3 of 10
broadband ultrasound is widely used in modern ultrasound systems, distortion of the ultrasound beam is a rather complex function of both tissue type and depth. Uncompensated, this distortion introduced by each tissue type degrades the spatial and contrast resolution in the ultrasound image and leads to reduced image uniformity. Figure 4: Image quality degradation caused by distortion in the ultrasound beam The role of the beamformer in an ultrasound system Point Spherica l Transdu Beamform ing Coheren t Front-end Back-end Processing Figure 5 Beamforming of a point source Time-Gain Compensation Time-Frequency Compensation S ti l filt i Ultrasound systems form images by sequentially transmitting acoustic energy into the body, receiving the returned echoes, and processing the received signals to extract information about the location and strength of reflectors in the body. The part of the ultrasound system that does this image formation is the beamformer. Since signals returning from the body arrive at different points along ultrasound transducer face at different times, beamformers use a system of delays to realign the signals returning from the body. Both on transmission and on reception, the beamformer uses this system of delays to focus energy in specific regions of the body. The better the system can enhance signals from the desired region and eliminate unwanted signal from other regions, the better the image quality. In a dynamic receive focus system, the focusing delays are continuously updated for every point in space. To counteract the effects caused by the physics of sound waves in the body affecting signal propagation and attenuation, an ultrasound system must continuously adjust a multitude of internal system parameters in the beamformer to Page 4 of 10
create the best image quality for every point in the image. (These three-dimensional points are called voxels.) This process must be done in real-time to provide reasonable imaging frame rates. The more parameters that can be adjusted, and the closer they match what is happening in the body, the better the image quality, and the higher the computational complexity. Moreover, as the spatial resolution of ultrasound systems increases, the reduction of the size of each image voxel requires a corresponding increase the number of voxels required to cover a given region of space, and thus dramatically increases the number of imaging computations required. Transmit voltage, waveform, transmit time delay, receive time delay, f-number, dynamic range, TGC, compression,,temporal averaging,, are just a few of the multitude of internal system parameters that must be adjusted to form an image. Figure 6: Computational complexity in forming an ultrasound image Given the number of parameters that must be adjusted for every image voxel in every frame, and the increasing number of image voxels in today s high-resolution ultrasound systems, the computational challenge is extraordinary. Conventional ultrasound system design In a conventional ultrasound system, the user selects a probe type and an imaging preset or collection of stored user control settings for the image formation. To be able to keep up with real-time imaging, the ultrasound operating system must calculate in advance what each channel must do for every image voxel. Prior to the start of imaging, the appropriate calculations for the given probe type and preset are loaded into each of the beamformer channels so that each beamformer channel simply executes the preprogrammed instructions as the image is produced. When the user selects a new probe or system preset, the system recalculates a new set of instructions for each channel and reloads each beamforming channel before scanning resumes. Page 5 of 10
Figure 7: Diagram of a Conventional Ultrasound System Design Every time the user changes a system operating parameter such as depth, focal zone position, or imaging frequency, the operating system must re-compute a portion of the beamforming information and again reprogram every channel. If perfect image quality were the goal, even today s fastest computers could not keep up with this process of channel-by-channel computation, loading, and resuming imaging. As a result, ultrasound engineers reduce the computational complexity by simplifying the assumptions about how sound interacts with the body so that they can reduce the number of parameters that must be calculated and downloaded to each channel. As an example, conventional ultrasound systems employ a rigid model of the human body using a single value for the speed and attenuation of sound in the body. These simplifications in a conventional ultrasound system lead to compromised image quality, and thus require the user to compensate by making many adjustments to system controls as they attempt to further improve image quality for each patient and organ. GE introduces a new Agile Acoustic Architecture with Agile Beamformer To address the fundamental limitations of a conventional system design, GE has developed a new system architecture and beamformer design based on the concept of agility. This new architecture and beamformer employ a series of powerful distributed processors, which when combined provide an order of magnitude increase in processing power and extremely high data rates, allowing the use of dynamic clinical models that more accurately represent the interaction of sound in the body. The result is dramatically improved image quality and reduced need for user optimization. Page 6 of 10
Patented Agile Acoustic Architecture The Agile Acoustic Architecture starts with the development of complex acoustic models based on clinical data. These models take into account more realistic and dynamic physics profiles for different tissue types, more precisely modeling differences in parameters like attenuation and speed of sound. Prior to scanning, the user selects the appropriate clinical model for the anatomy of interest. Unlike presets, which provide a starting point for the keyboard controls available to the user, the agile model adjusts internal system parameters not available to the user, and continuously adjusts those parameters based on any changes the user makes to keyboard controls. These models give the agile ultrasound system significant flexibility to compensate for the complexity of sound/body interaction and can be more dynamic and realistic than the rigid assumptions required in conventional systems. Figure 8: Agile Acoustic Architecture Design Due to their complexity, these acoustic models require significantly more processing power. Rather than relying on the central operating system to pre-calculate system parameters for each beamforming channel, the Agile Acoustic Architecture is built around powerful distributed processors on each beamforming channel. Each channel has been made intelligent and can calculate on its own what it needs to do for every voxel in the image. The models run in real-time on each distributed processor. When the user chooses a new model or changes an operating parameter only a minimal amount of information is loaded to each beamforming channel, and the channels do the rest to provide optimal image quality. Page 7 of 10
The distributed processing in the Agile Acoustic Architecture provides significantly more computational capacity. As a result, more internal parameters are brought to bear on the problem of compensating for the complex ultrasound/body interactions. Less image quality is lost because of the difference between reality and simplifying assumptions. Since the image formation is better to start with, fewer user adjustments are required to obtain an optimal image. An analogy: The Agile Acoustic Architecture is like a well-trained sports team. In practice the coach teaches all the plays to the players. But once the game starts, the coach simply relays the play and each player makes optimal decisions independently based on the game situation and the actions of the opposing players at the time. Enabling Technology Miniaturization - Packs an order of magnitude more processing power in same volume - Harness the same technology allowing laptop sized ultrasound Ultra-high speed data links - Allows transfer of over 3 Gigabytes of data per second (30 x conventional systems) - Equivalent to downloading the entire Lord of the Rings movie trilogy in under 4 seconds Scalable architecture - Expandable for higher performance levels - Platform for new innovations Enabling technologies Having developed seven laptop-sized ultrasound systems, GE has made significant investments in miniaturization in order to put the processing power of a high-end ultrasound system in a hand-carried package. This miniaturization expertise, also allowed GE to pack an order of magnitude greater processing power into the space of a full-sized ultrasound system. This gives Agile ultrasound systems the power needed to run the new clinical models. Because Agile ultrasound is so data-intense, new intra-system communication methods are needed to transfer the data within the beamformer. Ultra high-speed data links have been developed to transmit both data and imaging parameters efficiently. These links allow transfer rates of 3 gigabytes of data every second, thirty times the data rate of a conventional ultrasound system. The implementation of more sophisticated sound/body models is just the beginning of Agile ultrasound. These more sophisticated models open up a new branch of ultrasound science that will drive other innovations in the coming years. Agile ultrasound s distributed processing makes it more scalable than other designs. This scalability should enable the practical implementation of the future scientific discoveries based these ideas. Benefits of the Agile Acoustic Architecture One benefit of the agile acoustic architecture is the excellent image uniformity with very few user adjustments. For example, when the user changes a control like focal zone position, a conventional ultrasound system will re-compute the focusing delay for each channel and download that data into all channels. Since this process can take much time, the conventional system will limit the number of internal parameters to simplify the calculation. Also to reduce the calculation burden, most systems Page 8 of 10
will compute large tables in advance for a limited number of potential focal zone locations and simply load these tables into each channel. Since the data is pre-computed without knowing what most of the other operating parameters will be, the number of parameters will also be limited. With limited internal parameters adjusted by the system, and simplified calculations, the likelihood that the imaging parameters used match the ideal imaging parameters needed is low and the resulting image quality is degraded. To compensate, the user will adjust a number of keyboard controls, such as gain, TCG, as they attempt to optimize the image. With the agile acoustic architecture, every channel has sufficient distributed intelligence to know what to do on its own. When the user changes a focal zone position, only the new location needs to be relayed to each channel where the distributed processor will make all new calculations for that channel. Since the imaging parameters do not have to be pre-calculated, focal zone positions are not limited to preset locations, and can be placed flexibly based on the clinical need. The intelligence in the dynamic model results in a more accurate calculation using tissue specific acoustic profiles. The result is more optimal image quality, improved near-field, and better uniformity, with fewer user adjustments. Clinical benefits The results of Agile Acoustic Architecture can be seen in the exquisite imaging performance of the system. Agile ultrasound can provide deep penetration in even the most difficult to image patients. The image quality is uniformly excellent, maintaining tight spatial resolution throughout the image. The more sophisticated Agile models allow the use of higher-than-normal imaging frequencies, even deep in the body, resulting in a pleasing high-resolution look from top to bottom. Since images are optimized automatically by the dynamic mathematical model, optimal imaging is provided with minimal user interaction. Figure 9: (Left) Normal liver image showing excellent spatial and contrast resolution and image uniformity. (Right) Hyperemic flow at 2mm around veins following laser venous ablation showing high-frequency imaging and great B-mode image quality behind the color flow. Page 9 of 10
Conclusion A new Agile Acoustic Architecture with advanced clinical models and powerful distributed intelligence provides dramatic improvements in image quality on a greater variety of patients with fewer user adjustments required. Despite these advances, Agile ultrasound is still in its infancy. The models employed today are a significant improvement over the conventional approach, but do not come close to reaching their potential. With the basic architecture in place, the opportunities to further refine sound-tissue models hold great promise for clinician and engineer alike. References 1 Color Atlas of Human Anatomy, McMinn & Hutchings, Mosby Year Book, 1998 pg 211. 2 Zagzebski, Essentials of Ultrasound Physics Page 10 of 10