In ultrasound (US)-guided medical procedures, accurate tracking of interventional tools is crucial to patient safety and clinical outcome. This requires a calibration procedure to recover the relationship between the US image and the tracking coordinate system. In literature, calibration has been performed on passive phantoms, which depend on image quality and parameters, such as frequency, depth, and beam-thickness as well as in-plane assumptions. In this work, we introduce an active phantom for US calibration. This phantom actively detects and responds to the US beams transmitted from the imaging probe. This active echo (AE) approach allows identification of the US image midplane independent of image quality. Both target localization and segmentation can be done automatically, minimizing user dependency. The AE phantom is compared with a crosswire phantom in a robotic US setup. An out-of-plane estimation US calibration method is also demonstrated through simulation and experiments to compensate for remaining elevational uncertainty. The results indicate that the AE calibration phantom can have more consistent results across experiments with varying image configurations. Automatic segmentation is also shown to have similar performance to manual segmentation.
There has been increased interest in minimally invasive ablative treatments that typically require precise placement of the ablator tool to meet the predefined planning and lead to efficient tumor destruction. Standard ablative procedures involve free hand transcutaneous ultrasonography (TCUS) in conjunction with manual tool positioning. Unfortunately, existing TCUS systems suffer from many limitations and result in failure to identify nearly half of all treatable liver lesions. Freehand manipulation of the ultrasound (US) probe and ablator tool lacks the critical level of control, accuracy, stability, and guaranteed performance required for these procedures. Freehand US results in undefined gap distribution, anatomic deformation due to variable pressure from the sonographer's hand, and severe difficulty in maintaining optimal scanning position. In response to these limitations, we propose the use of a dual robotic arm system that manages both ultrasound manipulation and needle guidance. We report a prototype of the dual arm system and a comparative performance analysis between robotic vs. freehand systems, for both US scanning and needle placement in mechanical and animal tissue phantoms.
Abstract Despite current progress achieved in the surgical technique of radical prostatectomy, post-operative complications such as erectile dysfunction and urinary incontinence persist at high incidence rates. In this paper, we present a functional intra-operative guidance of the cavernous nerve (CN) network for nerve-sparing radical prostatectomy using near-infrared cyanine voltage-sensitive dye (VSD) imaging, which visualizes membrane potential variations in the CN and its branches (CNB) in real time. As a proof-of-concept experiment, we demonstrated a functioning complex nerve network in response to electrical stimulation of the CN, which was clearly differentiated from surrounding tissues in an in vivo rat prostate model. Stimulation of erection was confirmed by correlative intracavernosal pressure (ICP) monitoring. Within 10 min we performed trans-fascial staining of the CN by direct VSD administration. Our findings suggest the applicability of VSD imaging for nerve-sparing radical prostatectomy.
As thermal imaging attempts to estimate very small tissue motion (on the order of tens of microns), it can be negatively influenced by signal decorrelation. Patient's breathing and cardiac cycle generate shifts in the RF signal patterns. Other sources of movement could be found outside the patient's body, like transducer slippage or small vibrations due to environment factors like electronic noise. Here, we build upon a robust displacement estimation method for ultrasound elastography and we investigate an iterative motion compensation algorithm, which can detect and remove non-heat induced tissue motion at every step of the ablation procedure. The validation experiments are performed on laboratory induced ablation lesions in ex-vivo tissue. The ultrasound probe is either held by the operator's hand or supported by a robotic arm. We demonstrate the ability to detect and remove non-heat induced tissue motion in both settings. We show that removing extraneous motion helps unmask the effects of heating. Our strain estimation curves closely mirror the temperature changes within the tissue. While previous results in the area of motion compensation were reported for experiments lasting less than 10 seconds, our algorithm was tested on experiments that lasted close to 20 minutes.
Radiofrequency ablation (RFA) is the most widely used minimally invasive ablative therapy for liver cancer, but it is challenged by a lack of patient-specific monitoring. Inter-patient tissue variability and the presence of blood vessels make the prediction of the RFA difficult. A monitoring tool which can be personalized for a given patient during the intervention would be helpful to achieve a complete tumor ablation. However, the clinicians do not have access to such a tool, which results in incomplete treatment and a large number of recurrences. Computational models can simulate the phenomena and mechanisms governing this therapy. The temperature evolution as well as the resulted ablation can be modeled. When combined together with intraoperative measurements, computational modeling becomes an accurate and powerful tool to gain quantitative understanding and to enable improvements in the ongoing clinical settings. This paper shows how computational models of RFA can be evaluated using intra-operative measurements. First, simulations are used to demonstrate the feasibility of the method, which is then evaluated on two ex vivo datasets. RFA is simulated on a simplified geometry to generate realistic longitudinal temperature maps and the resulted necrosis. Computed temperatures are compared with the temperature evolution recorded using thermometers, and with temperatures monitored by ultrasound (US) in a 2D plane containing the ablation tip. Two ablations are performed on two cadaveric bovine livers, and we achieve error of 2.2 °C on average between the computed and the thermistors temperature and 1.4 °C and 2.7 °C on average between the temperature computed and monitored by US during the ablation at two different time points (t = 240 s and t = 900 s).
Photoacoustic imaging in surgical systems would be more prominent if the photoacoustic effect could be used for catheter tracking. A piezoelement in a catheter allows it to be localized with respect to tracked photoacoustic spots.
Quantification of brain function is a significant milestone towards understanding of the underlying workings of the brain. Photoacoustic (PA) imaging is the emerging brain sensing modality by which the molecular light absorptive contrast can be non-invasively quantified from deep-lying tissue (~several cm). In this BRAIN initiative effort, we propose high-speed transcranial PA imaging using a novel, compact pulsed LED illumination system (Prexion Inc., Japan) with 200-uJ pulse energy for 75-ns duration, and pulse repetition frequency (PRF) up to 4kHz at near-infrared (NIR) wavelengths of 690-nm and 850-nm switchable in real-time. To validate the efficacy of the proposed system, preliminary ex vivo experiments were conducted with mice skull and human temporal bone, which included vessel-mimicking tubes filled with 10% Indian Ink solution and light absorptive rubber material, respectively. The results indicated that significant PA contrast, 150% signal-to-noise ratio (SNR), can be achieved through the mice skull only with 64 subsequent frame averaging. The minimal number of frames for averaging required was only 16 to generate signal above background noise, leading to 250 Hz frame rate in the strictest temporal frame separation. Furthermore, distinguishable PA contrast was achieved with human temporal bone with 64-frame averaging. Overall, the preliminary results indicate that the LED illumination system can be a cost-effective solution for high-speed PA brain imaging in preclinical and clinical applications, compared to expansive and bulky Nd:YAG laser systems commonly used in PA imaging.
In this study, we are proposing a robot-assisted ultrasound tomography system that can offer soft tissue tomographic imaging and deeper or faster scan of the anatomy. This system consists of a robot-held ultrasound probe that tracks the position of another freehand probe, trying to align with it. One of the major challenges is achieving proper alignment of the two ultrasound probes. To enable proper alignment, two ultrasound calibrations and one hand-eye calibration are required. However, the system functionality and design is such that the ultrasound calibrations have become a challenge. In this paper, after providing an overview of the proposed robotic ultrasound tomography system, we focus on the calibrations problem. The results of the calibrations show a point reconstruction precision of a few millimeters for the current prototype, and the two images have at least 50% overlap visually; confirming the feasibility of such a system relying on accurate probe alignments.
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