Search

Pregnancy complications such as pre-eclampsia (PE) and intrauterine growth restriction (IUGR) are associated with structural and functional changes in the placenta. Different elastography techniques with an ability to assess the mechanical properties of tissue can identify and monitor the pathological state of the placenta. Currently available elastography techniques have been used with promising results to detect placenta abnormalities; however, limitations include inadequate measurement depth and safety concerns from high negative pressure pulses. Previously, we described a shear wave absolute vibro-elastography (SWAVE) method by applying external low-frequency mechanical vibrations to generate shear waves and studied 61 post-delivery clinically normal placentas to explore the feasibility of SWAVE for placental assessment and establish a measurement baseline. This next phase of the study, namely, SWAVE 2.0, improves the previous system and elasticity reconstruction by incorporating a multi-frequency acquisition system and using a 3-D local frequency estimation (LFE) method. Compared with its 2-D counterpart, the proposed system using 3-D LFE was found to reduce the bias and variance in elasticity measurements in tissue-mimicking phantoms. In the aim of investigating the potential of improved SWAVE 2.0 measurements to identify placental abnormalities, we studied 46 post-delivery placentas, including 26 diseased (16 IUGR and 10 PE) and 20 normal control placentas. By use of a 3.33-MHz motorized curved-array transducer, multi-frequency (80,100 and 120 Hz) elasticity measures were obtained with 3-D LFE, and both IUGR (15.30 ± 2.96 kPa, p = 3.35e

Purpose: In “human teleoperation” [1], augmented reality (AR) and haptics are used to tightly couple an expert leader to a human follower. To determine the feasibility of human teleoperation, we quantify the abil- ity of humans to track a position and/or force trajectory via AR cues. The human response time, precision, frequency response, and step response were characterized, and several rendering methods were compared. Methods: Volunteers (n=11) performed a series of tasks as the fol- lower in our human teleoperation system. The tasks involved tracking pre-recorded series of motions and forces, each time with a different rendering method. The order of tasks and rendering methods was ran- domized to avoid learning effects and bias. The volunteers then performed a series of frequency response tests and filled out a questionnaire. Results: Rendering the full ultrasound probe as a position target with an error bar displaying force led to the best position and force tracking. Following force and pose simultaneously was more difficult but did not lead to significant performance degradation versus following one at a time. On average, subjects tracked positions, orientations, and forces with rms tracking errors of 6.2 ± 1.9 mm, 5.9 ± 1.9˚, 1.0 ± 0.3 N, steady-state errors of 2.8 ± 2.1 mm, 0.26 ± 0.2 N, and lags of 345.5 ± 87.6 ms respectively. Performance decreased with input frequency, until the person could no longer follow, depending on the input amplitude. Conclusion: This paper characterizes human tracking ability in aug- mented reality human teleoperation, which shows the system’s feasi- bility and good performance, and is important for designing future human computer interfaces using augmented and virtual reality.

We previously introduced a novel mixed reality (MR) teleguidance system, human teleoperation [1,2], in which a human (expert) leader and a human (novice) follower are tightly coupled through MR and haptics for applications such as tele-ultrasound. In this paper, a communication system suitable for human teleoperation is presented and characterized in various network conditions, over Ethernet, Wi-Fi, 4G LTE, and 5G. To study all types of latency in the system, the human response time is additionally characterized through step response tests with 11 volunteers. The step responses were obtained by tracking the position and force of the human hand in response to a change in the MR target. The round-trip communication latency is 40+/-10 ms over 5G, and down to 1+/-0.6 ms over Ethernet for typical throughputs. The human response time to a step change in position depends on the step magnitude, but is 485-535 ms, while the reaction time for forces is 150-200 ms. Both lags are decreased when tracking smooth motions. Thus, we demonstrate that the system is network agnostic and can achieve good teleoperation performance and secure, fast communication in appropriate network conditions. The presented tools and concepts are applicable to any high-performance teleoperation system, for example for remote surgery.

We introduce two model-based iterative methods to obtain shear modulus images of tissue using magnetic resonance elastography. The first method jointly finds the displacement field that best fits tissue displacement data and the corresponding shear modulus. The displacement satisfies a viscoelastic wave equation constraint, discretized using the finite element method. Sparsifying regularization terms in both shear modulus and displacement are used in the cost function minimized for the best fit. The second method extends the first method for multifrequency tissue displacement data. The formulated problems are bi-convex. Their solution can be obtained iteratively by using the alternating direction method of multipliers. Sparsifying regularizations and the wave equation constraint filter out sensor noise and compressional waves. Our methods do not require bandpass filtering as a preprocessing step and converge fast irrespective of the initialization. We evaluate our new methods in multiple in silico and phantom experiments, with comparisons with existing methods, and we show improvements in contrast to noise and signal-to-noise ratios. Results from an in vivo liver imaging study show elastograms with mean elasticity comparable to other values reported in the literature.

Advances in human-computer interaction (HCI) technologies have granted sonographers and radiologists a much improved user experience when operating different ultrasound (US) machines. Continued HCI improvements in US would benefit from a systematic study of the HCI control logic used in this domain. Such a study has not been presented previously and is the subject of this paper. We surveyed sonographers to determine the most frequently used controls in US machines. We standardized the representation of the US machine HCI control logic by using the unified modelling language (UML). We used UML diagrams to analyze the HCI control logic of 10 different cart-based US machines from several major manufacturers, and we discovered that the control logic for the most frequently used functions are identical. While this control logic does not follow an established standard, it has been commonly adopted. Using the UML for the visualization and formulation of control logic, we can target logically optimal interactions (whose operation steps cannot be further reduced), e.g., adjustment of B-mode gain, frequency and depth, and can derive methods to simplify logically sub-optimal interactions, e.g., the pointing and selecting operation, as well as image measurements.Our study provides insights into existing HCI approaches used in US machines and establishes a rigorous UML-based framework for future US machine design to improve interoperability, efficiency and ease-of-use.

Robot-assisted laparoscopic radical prostatectomy (RALRP) using the da Vinci surgical robot is a common treatment for organ-confined prostate cancer. Augmented reality (AR) can help during RALRP by showing the surgeon the location of anatomical structures and tumors from preoperative imaging. Previously, we proposed hand-eye and camera intrinsic matrix estimation procedures that can be carried out with conventional instruments within the patient during surgery, take 3 min to perform, and fit seamlessly in the existing surgical workflow. In this paper, we describe and evaluate a complete AR guidance system for RALRP and quantify its accuracy.Our AR system requires three transformations: the transrectal ultrasound (TRUS) to da Vinci transformation, the camera intrinsic matrix, and the hand-eye transformation. For evaluation, a 3D-printed cross-wire was visualized in TRUS and stereo endoscope in a water bath. Manually triangulated cross-wire points from stereo images were used as ground truth to evaluate overall TRE between these points and points transformed from TRUS to camera.After transforming the ground-truth points from the TRUS to the camera coordinate frame, the mean target registration error (TRE) (SD) was [Formula: see text] mm. The mean TREs (SD) in the x-, y-, and z-directions are [Formula: see text] mm, [Formula: see text] mm, and [Formula: see text] mm, respectively.We describe and evaluate a complete AR guidance system for RALRP which can augment preoperative data to endoscope camera image, after a deformable magnetic resonance image to TRUS registration step. The streamlined procedures with current surgical workflow and low TRE demonstrate the compatibility and readiness of the system for clinical translation. A detailed sensitivity study remains part of future work.

In this article, we describe a system for detecting dominant prostate tumors, based on a combination of features extracted from a novel multi-parametric quantitative ultrasound elastography technique. The performance of the system was validated on a data-set acquired from n = 10 patients undergoing radical prostatectomy. Multi-frequency steady-state mechanical excitations were applied to each patient's prostate through the perineum and prostate tissue displacements were captured by a transrectal ultrasound system. 3D volumetric data including absolute value of tissue elasticity, strain and frequency-response were computed for each patient. Based on the combination of all extracted features, a random forest classification algorithm was used to separate cancerous regions from normal tissue, and to compute a measure of cancer probability. Registered whole mount histopathology images of the excised prostate gland were used as a ground truth of cancer distribution for classifier training. An area under receiver operating characteristic curve of 0.82 +/- 0.01 was achieved in a leave-one-patient-out cross validation. Our results show the potential of multi-parametric quantitative elastography for prostate cancer detection for the first time in a clinical setting, and justify further studies to establish whether the approach can have clinical use.

Our aim is to develop a clinically viable, fast-acquisition, prostate MR elastography (MRE) system with transperineal excitation. We developed a new actively shielded electromagnetic transducer, designed to enable quick deployment and positioning within the scanner. The shielding of the transducer was optimized using simulations. We also employed a new rapid pulse sequence that encodes the three-dimensional displacement field in the prostate gland using a fractionally encoded steady-state gradient echo sequence, thereby shortening the acquisition time to a clinically acceptable 8-10 min. The methods were tested in two phantoms and seven human subjects (six volunteers and one patient with prostate cancer). The MRE acquisition time for 24 slices, with an isotropic resolution of 2 mm and eight phase offsets, was 8 min, and the total scan, including positioning and set-up, was performed in 15-20 min. The phantom study demonstrated that the transducer does not interfere with the acquisition process and that it generates displacement amplitudes that exceed 100 µm even at frequencies as high as 300 Hz. In the in vivo human study, average wave amplitudes of 30 µm (46 µm at the apex) were routinely achieved within the prostate gland at 70 Hz. No pain or discomfort was reported. Results in a single patient suggest that MRE can identify cancer tumors, although this result is preliminary. The proposed methods allow the integration of prostate MRE with other multiparametric MRI methods. The results of this study clearly motivate the clinical evaluation of transperineal MRE in patients.

Although robotic surgery has addressed many of the challenges presented by minimally invasive surgery, haptic feedback and the lack of knowledge of tissue stiffness is an unsolved problem. This paper presents a system for finding the absolute elastic properties of tissue using a freehand ultrasound scanning technique, which utilizes the da Vinci Surgical robot and a custom 2D ultrasound transducer for intraoperative use. An external exciter creates shear waves in the tissue, and a local frequency estimation method computes the shear modulus. Results are reported for both phantom and in vivo models. This system can be extended to any 6 degree-of-freedom tracking method and any 2D transducer to provide real-time absolute elastic properties of tissue.

In this article an ultrasound elastography technology is reported which provides quantitative images of tissue elasticity from deep soft tissue. The technique is analogous to Magnetic Resonance Elastography in the use of external mechanical vibrations which can penetrate deep tissue. Multifrequency steady-state mechanical vibrations are applied to the tissue at the skin and tissue displacements are measured by a conventional ultrasound system. Absolute values of tissue elasticity are computed in real-time for each frequency and displayed to the physician. The quantitative elasticity images produced by the technology are validated with magnetic resonance elastography images as the gold standard on standard elasticity phantoms. Preliminary in-vivo data from healthy volunteers are presented which show the potential of the technology for clinical use. The system is currently being used in different clinical studies to image kidney fibrosis, liver fibrosis, and prostate cancer.

In MR elastography (MRE), periodic tissue motion is phase encoded using motion-encoding gradients synchronized to an externally applied periodic mechanical excitation. Conventional methods result in extended scan time for quality phase images, thus limiting the broad application of MRE in the clinic. For practical scan times, researchers have been relying on one-dimensional or two-dimensional motion-encoding, low-phase sampling and a limited number of slices, and artifact-prone, single-shot, echo planar imaging (EPI) readout. Here, we introduce a rapid multislice pulse sequence capable of three-dimensional motion encoding that is also suitable for simultaneously encoding motion with multiple frequency components. This sequence is based on a gradient-recalled echo (GRE) sequence and exploits the principles of fractional encoding. This GRE MRE pulse sequence was validated as capable of acquiring full three-dimensional motion encoding of isotropic voxels in a large volume within less than a minute. This sequence is suitable for monofrequency and multifrequency MRE experiments. In homogeneous paraffin phantoms, the eXpresso sequence yielded similar storage modulus values as those obtained with conventional methods, although with markedly reduced variances (7.11 ± 0.26 kPa for GRE MRE versus 7.16 ± 1.33 kPa for the conventional spin-echo EPI sequence). The GRE MRE sequence obtained better phase-to-noise ratios than the equivalent spin-echo EPI sequence (matched for identical acquisition time) in both paraffin phantoms and in vivo data in the liver (59.62 ± 11.89 versus 27.86 ± 3.81, 61.49 ± 14.16 versus 24.78 ± 2.48 and 58.23 ± 10.39 versus 23.48 ± 2.91 in the X, Y and Z components, respectively, in the case of liver experiments). Phase-to-noise ratios were similar between GRE MRE used in monofrequency or multifrequency experiments (75.39 ± 14.93 versus 86.13 ± 18.25 at 28 Hz, 71.52 ± 24.74 versus 86.96 ± 30.53 at 56 Hz and 95.60 ± 36.96 versus 61.35 ± 26.25 at 84Hz, respectively).

In postimplant dosimetry for prostate brachytherapy, dose is commonly calculated using the TG-43 1D formalism, because seed orientations are difficult to determine from CT images, the current standard for the procedure. However, the orientation of stranded seeds soon after implantation is predictable, as these seeds tend to maintain their relative spacing, and orient themselves along the implant trajectory. The aim of this study was to develop a method for determining seed orientations from reconstructed strand trajectories, and to use this information to investigate the dosimetric impact of applying the TG-43 2D formalism to clinical postimplant analysis.Using in-house software, the preplan to postimplant seed correspondence was determined for a cohort of 30 patients during routine day-0 CT-based postimplant dosimetry. All patients were implanted with stranded-seed trains. Spline curves were fit to each set of seeds composing a strand, with the requirement that the distance along the spline between seeds be equal to the seed spacing within the strand. The orientations of the seeds were estimated by the tangents to the spline at each seed centroid. Dose distributions were then determined using the 1D and 2D TG-43 formalisms. These were compared using the TG-137 recommended dose metrics for the prostate, prostatic urethra, and rectum.Seven hundred and sixty one strands were analyzed in total. Defining the z-axis to be cranial-positive and the x-axis to be left-lateral positive in the CT coordinate system, the average seed had an inclination of 21° ± 10° and an azimuth of -81° ± 57°. These values correspond to the average strand rising anteriorly from apex to base, approximately parallel to the midsagittal plane. Clinically minor but statistically significant differences in dose metrics were noted. Compared to the 2D calculation, the 1D calculation underestimated prostate V100 by 1.1% and D90 by 2.3 Gy, while overestimating V150 and V200 by 1.6% and 1.3%, respectively. Urethral and rectal dose quantifiers tended to be underestimated by the 1D calculation. The most pronounced differences were in the urethral D30 and rectal D2cc, which rose by 3.8 and 1.9 Gy, respectively, using the 2D calculation. The total volume of the 100% isodose region as a percentage of the prostate volume was found to increase by 0.4%.Stranded seeds in the supine patient are not oriented in a uniformly random manner, nor are they aligned along the axis of the CT scanner. Instead, this study identified a consistent anterior pitch that is likely attributable to differences in patient pose between implant and CT imaging. The angle of the ultrasound probe with respect to the patient during implant may have also been a contributing factor. The dose metrics derived using the 1D formalism were found to be within 2%, on average, of those derived using the 2D formalism. For greater accuracy, 2D dosimetry can be pursued using the strand-fitting method described in this work. If a 1D representation is used, integrating over the empirically determined seed orientation density reported here may be more appropriate than assuming that seed inclinations are distributed uniformly.

There is a need to provide real-time dosimetric feedback during prostate brachytherapy based on the location of the implanted seeds. The objective of our approach is to develop a system to accurately locate seeds with minimal impact on the current protocol for prostate brachytherapy and without additional imaging equipment.A new approach for intraoperatively computing dosimetry for prostate brachytherapy is presented. The approach uses transrectal ultrasound (TRUS) and fluoroscopic images. A fluoroscopic image of the TRUS probe is required to register the fluoroscopic and ultrasound images. The C-arm is not moved during the procedure and all images are acquired from the same C-arm angles. A needle path is interpolated for each needle based on the location of the needle tip in TRUS images and the known entry point of the needle. Throughout the procedure, fluoroscopic images are acquired to determine the coronal plane coordinates of the seeds and the remaining coordinate of each seed is computed from the needle path. For accurate results, intraoperative seed motion tracking is advised and a method to achieve such tracking is also presented.Experimentally, the TRUS and fluoroscopic images are registered with a mean and maximum error of 1.3 mm and 5.8 mm, respectively. In a phantom, 12 seeds are located using our approach and compared with the known locations, with a mean error in the x, y, and z direction of 0.96 mm, 0.33, and 0.68 mm, respectively, and a corresponding maximum error of 1.85 mm, 0.56 mm, and 1.63 mm. Experimental results show motion tracking in the y-direction with submillimeter accuracy. The feasibility of our approach is tested on five cases of clinical data using a semiautomated version of our system and the resulting dosimetry is compared with that found using postoperative computed tomography images. The D90 and V100 metrics computed using our approach and the computed tomography images differ by a maximum of 16.6% and 1.7%, respectively.TRUS can be combined with single pose fluoroscopic images to compute delivered dose intraoperatively for prostate brachytherapy. Phantom results demonstrate the accuracy of the method and preliminary clinical results show its potential.

This paper presents a fast image synthesis procedure for elastic volumes under deformation. Given the node displacements of a mesh and the 3D image voxel data of an undeformed volume, the method maps the image plane pixels to be synthesized from the deformed configuration back to the nominal pre-deformed configuration, where the pixel intensities are obtained easily through interpolation in the regular-grid structure of the voxel volume. For smooth interpolation, this mapping requires the identification of the mesh element enclosing each image pixel. To accelerate this point location procedure, a fast method of marking the image pixels is employed by finding the intersection of the mesh and the image, and marking this intersection on the image pixels using Bresenham's line drawing algorithm. A deformable tissue phantom was constructed, it was modeled using the finite element method, and its 3D ultrasound volume was acquired in its undeformed state. Actual B-mode images of the phantom under deformation by the ultrasound probe were then compared with the corresponding synthesized images simulated for the same deformations. Results show that realistic images can be synthesized in real-time using the proposed technique.

A new global isotropy index (GII) is proposed to quantify the configuration independent isotropy of a robot’s Jacobian or mass matrix. The matrix is scaled to homogenize the physical units, to tailor it to the demands of the application and to choose optimum actuator parameters. A new discrete global optimization algorithm is also proposed to optimize the GII without placing any conditions on the objective function. The algorithm is used to establish design guidelines and a globally optimum architecture for a planar haptic interface from both a kinematic and dynamic perspective and to compare three robots for use as a 5-DOF haptic pen. The algorithm demonstrates consistent effort reductions of up to six orders of magnitude over global searching with low sensitivity to initial conditions.