Jason W. Trobaugh

Non-invasive estimation of hyperthermia temperatures with ultrasound.

Ultrasound is an attractive modality for temperature monitoring because it is non-ionizing, convenient, inexpensive and has relatively simple signal processing requirements. This modality may be useful for temperature estimation if a temperature-dependent ultrasonic parameter can be identified, measured and calibrated. The most prominent methods for using ultrasound as a non-invasive thermometer exploit either (1) echo shifts due to changes in tissue thermal expansion and speed of sound (SOS), (2) variation in the attenuation coefficient or (3) change in backscattered energy from tissue inhomogeneities. The use of echo shifts has received the most attention in the last decade. By tracking scattering volumes and measuring the time shift of received echoes, investigators have been able to predict the temperature from a region of interest both theoretically and experimentally in phantoms, in isolated tissue regions in vitro and preliminary in vivo studies. A limitation of this method for general temperature monitoring is that prior knowledge of both SOS and thermal-expansion coefficients is necessary. Acoustic attenuation is dependent on temperature, but with significant changes occurring only at temperatures above 50°C, which may lead to its use in thermal ablation therapies. Minimal change in attenuation, however, below this temperature range reduces its attractiveness for use in clinical hyperthermia. Models and measurements of the change in backscattered energy suggest that, over the clinical hyperthermia temperature range, changes in backscattered energy are dependent on the properties of individual scatterers or scattering regions. Calibration of the backscattered energy from different tissue regions is an important goal of this approach. All methods must be able to cope with motion of the image features on which temperature estimates are based. A crucial step in identifying a viable ultrasonic approach to temperature estimation is its performance during in vivo tests.

The correction of stereotactic inaccuracy caused by brain shift using an intraoperative ultrasound device

Cranial stereotactic systems which utilize preoperative computed tomography (CT) or magnetic resonance imaging (MRI) data sets to guide surgery are subject to inaccuracy introduced by the intraoperative movement of the brain (brain shift). Although these systems allow precise navigation initially during a procedure, brain shift resulting from surgical intervention can lead to progressive degradation in accuracy, with the greatest inaccuracy occurring when deep structures are manipulated. One method of addressing this issue is with the use of an intraoperative scanning device such as CT or MRI; however, such scanners are costly and restrict surgical access. We have developed an alternative intraoperative imaging device consisting of an ultrasound unit coupled to a stereotactic system to quantify the degree of brain shift. This system determines the orientation of ultrasound images produced by the device and reformats the pre-operative CT or MRI images to match the ultrasound image. By comparing the position of specific structures on the two images, the amount of shift can be determined. Furthermore, this system is being expanded to include the aquisition of three-dimensional ultrasonic volumes.

Frameless stereotactic ultrasonography: Method and applications

In stereotactic neurosurgery, computed tomography (CT) and magnetic resonance (MR) images are registered in a coordinate system defined with respect to the skull. By intraoperatively tracking the coordinate position of a surgical instrument, various displays can be formed which show the position of the instrument in the MR and/or CT images. However, the accuracy of this display varies because intracranial structures may shift or warp from their position prior to surgery. Ultrasonic imaging systems provide real-time images of the brain, but structures in these images are difficult to interpret because the images are based on ultrasonic echoes. A method has been developed for the real-time registration of these images. With this registration, software continuously updates a corresponding image constructed from the set of MR and/or CT images used for guidance. By developing this second view of the structures in the ultrasound image, the surgeon can easily interpret the ultrasound image, and it becomes possible to determine the extent of the intra-operative structure shift between the two images.

In vivo change in ultrasonic backscattered energy with temperature in motion-compensated images.

Ultrasound is an attractive modality for non-invasive imaging to monitor temperature of tumorous regions undergoing hyperthermia therapy. Previously, we predicted monotonic changes in backscattered energy (CBE) of ultrasound with temperature for certain sub-wavelength scatterers. We also measured CBE values similar to our predictions in bovine liver, turkey breast muscle, and pork rib muscle in both 1D and 2D in in vitro studies. To corroborate those results in perfused, living tissue, we measured CBE in both normal tissue and in implanted human tumors (HT29 colon cancer line) in 7 nude mice. Images were formed by a phased-array imager with a 7.5 MHz linear probe during homogeneous heating from 37° to 45°C in 0.5°C steps and from body temperature to 43°C during heterogeneous heating. We used cross-correlation as a similarity measure in RF signals to automatically track feature displacement as a function of temperature. Feature displacement was non-uniform with a maximum value of 1 mm across all specimens during homogeneous heating, and 0.2 mm during heterogeneous heating. Envelopes of image regions, compensated for non-rigid motion, were found with the Hilbert transform then smoothed with a 3 × 3 running average filter before forming the backscattered energy at each pixel. Means of both the positive and negative changes in the BE images were evaluated. CBE was monotonic and accumulated to 4–5 dB during homogeneous heating to 45°C and 3–4 dB during heterogenous heating to 43°C. These results are consistent with our previous in vitro measurements and support the use of CBE for temperature estimation in vivo during hyperthermia.

3-D in vitro estimation of temperature using the change in backscattered ultrasonic energy

Temperature imaging with a non-invasive modality to monitor the heating of tumors during hyperthermia treatment is an attractive alternative to sparse invasive measurement. Previously, we predicted monotonic changes in backscattered energy (CBE) of ultrasound with temperature for certain sub-wavelength scatterers. We also measured CBE values similar to our predictions in bovine liver, turkey breast muscle, and pork rib muscle in 2-D in vitro studies and in nude mice during 2-D in vivo studies. To extend these studies to three dimensions, we compensated for motion and measured CBE in turkey breast muscle. 3-D data sets were assembled from images formed by a phased-array imager with a 7.5-MHz linear probe moved in 0.6-mm steps in elevation during uniform heating from 37 to 45°C in 0.5°C increments. We used cross-correlation as a similarity measure in RF signals to automatically track feature displacement as a function of temperature. Feature displacement was non-rigid. Envelopes of image regions, compensated for non-rigid motion, were found with the Hilbert transform then smoothed with a 3 × 3 running average filter before forming the backscattered energy at each pixel. CBE in 3-D motion-compensated images was nearly linear with an average sensitivity of 0.30 dB/°C. 3-D estimation of temperature in separate tissue regions had errors with a maximum standard deviation of about 0.5°C over 1-cm3 volumes. Success of CBE temperature estimation based on 3-D non-rigid tracking and compensation for real and apparent motion of image features could serve as the foundation for the eventual generation of 3-D temperature maps in soft tissue in a non-invasive, convenient, and low-cost way in clinical hyperthermia.

A physically based, probabilistic model for ultrasonic images incorporating shape, microstructure, and system characteristics

Describes a previous physical model for image formation that incorporates the imaging system characteristics, the surface shape, and the surface microstructure. That physical model was validated via a visual comparison of simulated and actual images of a cadaveric vertebra. In this work, a random phasor sum representation of the physical model provides the basis for a probabilistic form. In contrast to existing probabilistic models, we compute the amplitude mean and variance directly from the physical model. These statistics can be displayed as images to characterize the tissue, but, more importantly, they permit the subsequent assignment of a suitable density function to each pixel for the purposes of constructing a data likelihood. The order of these steps, i.e., first computing the statistics and then assigning a density function, permits the inclusion of the local surface shape, the surface microstructure, and the system characteristics at every image pixel without violating the physical model. Currently, the value of the SNR/sub 0/, the ratio of the mean to the standard deviation, is used to estimate whether a pixel is Rayleigh- or non-Rayleigh-distributed. This assessment forms the basis for a data likelihood constructed as a product of Rayleigh and Gaussian density functions describing the individual image pixels.

Ultrasound in image fusion: a framework and applications

The framework for image fusion used here was based on methods for computer-assisted surgery expanded to include ultrasound imaging and techniques for displaying fused images. In neurosurgery, ultrasound images fused with MR or CT data sets have provided (1) real-time imaging with the interpretive simplicity of MR or CT and (2) the means for assessing intra-operative changes in the anatomy. In the spine, ultrasound images have been used to achieve percutaneous registration of the spine with a CT data set, an enabling procedure for radiosurgery and minimally-invasive spinal surgery.

A discrete-scatterer model for ultrasonic images of rough surfaces

Automated analysis of ultrasonic images could be greatly improved with model-based Bayesian methods for image analysis. Such an approach would require an accurate probabilistic image model representing ultrasonic images in terms of the gross shape of underlying anatomical structure. Existing probabilistic models for ultrasonic image data do not adequately incorporate structure shape or system characteristics; thus, a substantially new approach is warranted. Toward that goal, we have developed models for the imaging system and rough surface with the following objectives: (1) accuracy in representation of basic image characteristics such as the texture and intensity, (2) a minimum of computational requirements, and (3) a form that is naturally extendable to an appropriate probabilistic image model. The imaging system was modeled as a linear system with a separable three-dimensional point-spread function with an envelope of Gaussian curves in each dimension. The rough surface was modeled as a collection of discrete scatterers placed on the continuum and parametrized by a surface roughness and scatterer concentration. Models were evaluated by a visual comparison of actual and simulated images of a cadaveric lumbar vertebra. The gross shape of the vertebral surface was estimated from computed tomography images of the vertebra, and simulated images were generated using the models and the gross surface shape. Actual images were registered with the surface and simulated images to within 2 mm. The similarity of the actual and simulated images was quite remarkable considering the simplicity of the models. Differences between the images were less than those between two simulated images separated by 0.4 mm or one-fifth the registration error. Further assessment of the models would require a statistical approach not yet available. The models do, however, provide the basis for the development of a computationally tractable probabilistic image model for image analysis. Such a model will provide the means for a statistical evaluation of the system and surface models.

Detection of the Fingerprint of the Electrophysiological Abnormalities that Increase Vulnerability to Life-Threatening Ventricular Arrhythmias

Reduction of sudden death requires accurate identification of patients at risk for ventricular tachycardia (VT) and effective therapies. The Multicenter Unsustained Tachycardia Trial and Multicenter Automatic Defibrillator Implantation Trials demonstrate that the implantable cardioverter defibrillator impacts favorably on the incidence of VT in patients with myocardial infarction, underscoring the need to detect the electrophysiologic abnormalities required for the development of VT. Methods used for this purpose include: Holter monitoring, ejection fraction, signal-averaged ECG, heart rate variability, T-wave alternans, baroreflex sensitivity, and programmed stimulation. Performance of each method alone has demonstrated high-negative but low-positive predictive values. Recent studies confirm that their use in combination augments performance.A second approach for improving performance has been to reexamine how well each method detects the electrophysiological derangements that lead to VT. Our recent work has focused on the signal-averaged ECG. Judging from transmural maps of ventricular activation during VT and sinus rhythm obtained from patients, late potentials fail to detect completely signals from myocardium responsible for VT. To obviate this limitation we developed an approach based on inferred epicardial potentials in the frequency domain from 190-surface ECGs using individualized heart-torso models. Torso geometry and electrode positions are measured with a 3-armed digitizer. The location of cardiac structures is determined using echocardiography. The pericardial surface is approximated by a sphere that encloses the heart. Epicardial potentials are inferred using the boundary element method with zero-order Tikhonov regularization and the Composite Residual Smoothing Operator over the QRS complex. Studies are underway to determine if analysis of bioelectrical signals enveloping arrhythmogenic tissue improves identification of patients vulnerable to VT.

Temperature dependence of ultrasonic backscattered energy in images compensated for tissue motion

Noninvasive temperature imaging would enhance the ability to uniformly heat tumors at therapeutic levels. Ultrasound is an attractive modality for this purpose. Previously, we predicted monotonic changes in ultrasonic backscattered energy (CBE) for certain sub wavelength scatterers. We measured CBE values similar to our predictions in bovine liver, turkey breast, and pork rib in 1D. Those measurements were corrected manually for changes in the axial position of scatterers with temperature. To investigate the effect of temperature on CBE in 2D, we imaged 1-cm thick samples of bovine liver during heating in a water bath from 37 to 50/spl deg/C. Images were formed by a Terason 2000 imager with a 7 MHz linear probe. Employing RF signals from the Terason 2000 (courtesy Teratech Corp.) permitted the use of cross-correlation as a similarity measure for automatic tracking of feature displacement as a function of temperature. Tissue motion across the specimen was non-uniform with typical total displacements of 0.5 to 1 mm in both axial and lateral directions. Tissue motion in 8 image regions was tracked from 37 to 50/spl deg/C in 0.5/spl deg/C steps. Motion compensated image regions were demodulated with the Hilbert transform and smoothed with a 3/spl times/3 running average filter before forming the backscattered energy at each pixel. Our measure of CBE compared means of both the positive and negative changes in the BE images. CBE changed monotonically by about 4 dB at 50/spl deg/C from its value at 37/spl deg/C. Relatively noise-free CBE curves from tissue volumes of less than 1 cm/sup 3/ supports the use of CBE for temperature estimation. Motion in 3D will affect CBE values, but because beam width in elevation is larger than the lateral width, effects of motion in elevation on CBE may be less. Thus, we expect CBE to support temperature estimation in 3D. Furthermore, because CBE exploits inherent tissue inhomogeneities, extension to in vivo applications is a genuine prospect.