Transoral robotic surgery (TORS) is an effective minimally invasive alternative to traditional open surgery with improved surgical outcomes and reduced morbidity. However, TORS utilizes the natural orifice approach and does not provide haptic feedback, resulting in difficulty in assessing the extent of tumor or identifying critical structures. Intra-operative surgical navigation with image guidance has the potential to compensate for the sensory deficit in TORS. The authors previously enabled intra-operative image guidance for TORS and demonstrated the feasibility of electromagnetic tracking of da Vinci robotic instruments. In this paper, the authors described the development of a TORS navigation framework with real-time tracking and integration with the da Vinci surgeon’s console, assessed the system efficacy in a multi-user phantom localization study, and discussed study limitations. Five participants with various experience levels performed target localization tasks without and with navigation and all achieved significantly reduced target localization error (TLE) (p≤0.05; α=0.05), with the lowest TLE being 2.1mm. The authors successfully demonstrated the potential of the navigation system in facilitating precise target localization and enabling accurate image-guided TORS (igTORS).
KEYWORDS: Video, Video compression, Video processing, Digital video recorders, 3D video streaming, Robotic systems, Image processing, Image compression
Reconstruction of stereoendoscopic video has been explored for guiding minimally-invasive procedures across many surgical subspecialties, and may play an increasingly important role in navigation as stereo-equipped robotic systems become more widely available. Capturing stereo video for the purpose of offline reconstruction requires dedicated hardware, a mechanism for temporal synchronization, and video processing tools that perform accurate clip extraction, frame extraction, and lossless compression for archival. This work describes a minimal hardware setup comprising entirely off-the-shelf components for capturing video from the da Vinci and similar 3D-enabled surgical systems. Software utilities are also provided for synchronizing data collection and accurately handling captured video files. End-to-end testing demonstrates that all processing functions (clipping, frame cropping, compression, un-compression, and frame extraction) operate losslessly, and can be combined to generate reconstruction-ready stereo pairs from raw surgical video.
The transoral approach to resecting oral and oropharyngeal tumors is associated with lower morbidity than open surgery, but is associated with a high positive margin rate. When margins are positive, it is critical that resection specimens be accurately oriented in anatomical context for gross and microscopic evaluation, and also that surgeons, pathologists, and other care team members share an accurate spatial awareness of margin locations. With clinical interest in digital pathology on the rise, this work outlines a proposed framework for generating 3D specimen models intraoperatively via robot-integrated stereovision, and using these models to visualize involved margins in both ex vivo (flattened) and in situ (conformed) configurations. Preliminary pilot study results suggest that stereo specimen imaging can be easily integrated into the transoral robotic surgery workflow, and that the expected accuracy of raw reconstructions is around 1.60mm. Ongoing data collection and technical development will support a full system evaluation.
KEYWORDS: Surgery, Tissues, Animals, Animal model studies, Tumor growth modeling, Perfusion imaging, Optical properties, In vivo imaging, Diseases and disorders, Cancer
Guided surgery has demonstrated significant improvements in patient outcomes in some disease processes. Interest in this field has led to substantial growth in the technologies under investigation. Most likely no single technology will prove to be “best,” and combinations of macro- and microscale guidance— using radiological imaging navigation, probes (activatable, perfusion, and molecular-targeted; large- and small-molecule), autofluorescence, tissue intrinsic optical properties, bioimpedance, and other characteristics—will offer patients and surgeons the greatest opportunity for high-success/low-morbidity medical interventions. Problems are arising, however, from the lack of valid testing formats; surgical training simulators suffer the same problems. Small animal models do not accurately recreate human anatomy, especially in terms of tissue volume. Large animal models are expensive and have difficulty replicating many pathological states, particularly when molecular specificity for individual cancers is required. Furthermore, the sheer number of technologies and the potential for synergistic combination leads to exponential growth of testing requirements that is unrealistic for in vivo testing. Therefore, critical need exists to expand the ex vivo/in vitro testing platforms available to investigators and, once validated, a need to increase the acceptance of these methods for funding and regulatory endpoints. Herein is a review of the available ex vivo/in vitro testing formats for guided surgery, a review of their advantages/disadvantages, and consideration for how our field may safely and more swiftly move forward through stronger adoption of these testing and validation methods.
Positive surgical margins are a common complication of trans-oral tumor resection, and implementation of image guidance is typically hindered by significant tissue deformation introduced by oral retractors. Recent advances have produced multiple pathways for developing intraoperative trans-oral image guidance, which must ultimately be displayed to the surgeon in real time. This work presents a pipeline for automatically displaying CT-registered three-dimensional surface structures in the surgeon console of a da Vinci surgical system and assesses image-plane projection accuracy using Dice coefficient and intersection over union metrics. While coarse accuracy is acceptable (metric averages ⪆0.5), more accurate projections were obtained using registration methods based on optically tracking the endoscope shaft. Further improvement of registration, kinematic modeling, and endoscope calibration is necessary prior to use in preclinical evaluation of image guidance strategies for trans-oral robotic surgery.
Stereo reconstruction is an important tool for generating 3D surface observations of deformable tissues that can be used to non-rigidly update intraoperative image guidance. As compared to traditional image processing-based stereo matching techniques, emerging machine learning approaches aim to deliver shorter processing times, more accurate surface reconstructions, and greater robustness to the suboptimal qualities of intraoperative tissue imaging (e.g., occlusion, reflection, and minimally textured surfaces). This work evaluates the popular PSMNet convolutional neural network as tool for generating disparity maps from the video feed of the da Vinci Xi Surgical System. Reconstruction accuracy and speed were assessed for a series of 44 stereoendoscopic frame pairs showing key structures in a silicone renal phantom. Surface representation accuracy was found to be on the order of 1mm for reconstructions of the kidney and inferior vena cava, and disparity maps were produced in under 2s when inference was performed on a standard modern GPU. These preliminary results suggest that PSMNet and similar trained models may be useful tools for integrating intraoperative stereo reconstruction into advanced navigation platforms and warrant further development of the overall data pipeline and testing with biological tissues in representative surgical conditions.
Phantom evaluation of novel image guided surgery techniques enables low-cost, rapid design iteration prior to (or in place of) studies requiring biological specimens. This work introduces a novel, geometrically-accurate anatomical phantom model of surgical exposure of structures in the upper urinary tract. After segmenting the CT scan of a representative study subject, the kidneys, ureters, and associated vasculature were cast in silicone and loaded with barium to facilitate segmentation of phantom tomography. This deformable silicone model was secured to a rigid replication of the spine and retroperitoneal musculature. An acrylic housing was designed to mimic the abdominal cavity and was filled with wool batting to simulate occluding adipose tissue. Initial evaluation on CT showed good subjective correspondence with clinical tomography, as well as physiologically-relevant 25–30 mm kidney displacement between orientations, with the ability to produce larger displacements as would be expected due to intraoperative manipulation. Stereoendoscopic views of partially occluded structures during simulated dissection with the da Vinci S and Xi Surgical Systems show promise for use in developing and validating image guidance tools for surgical exposure in the abdomen.
Transoral robotic surgery (TORS) has demonstrated improved surgical outcomes with reduced morbidity when compared to traditional open surgical treatments. However, it is more difficult to assess the extent of tumor and localize critical structures due to lack of haptic feedback and the natural orifice approach. Enabling image-guided TORS (igTORS) to compensate for the sensory deficit requires a surgical navigation system that is compatible with both the TORS procedures and the da Vinci surgical system. Previously, the authors developed an imaging compatible oral retractor system for TORS to allow artifact-free intraoperative CT images for use in image guidance. In this work, we developed a surgical navigation system for TORS that utilizes intraoperative images and electromagnetic (EM) tracking. A cadaver experiment simulating a standard TORS procedure was performed to examine system feasibility and accuracy. A da Vinci Bovie instrument was tracked, and its real-time location was visualized in tri-planar CT images and displayed on the surgeon’s console and on the bedside vision cart using the TilePro feature. Target localization error (TLE) was computed to be 3.46±0.77 mm. This was the first time that surgical navigation in TORS was demonstrated with intraoperative image guidance and EM tracking of da Vinci instruments in a cadaver experiment.
Accurate and reliable non-invasive monitoring of early systemic disease—such as ongoing hemorrhage, sepsis, and acute respiratory disease like COVID-19—is one of the largest unmet needs in biomedicine. An early alert to progression with high sensitivity and an acceptable false-positive rate would allow medical staff to risk-stratify patients, saving resources, lives, and in the context of pandemic disease, minimize staff exposure. Noninvasive technologies have thus far failed to produce a reliable early detection system, reflecting the limitation of uniplex approaches to describe complex pathophysiology. Our team, in collaboration with an STTR start-up, have developed an optico-impedance system combining near-infrared spectroscopy and electrical impedance tomography measured at three locations (thorax, abdomen, limb) together with machine learning methods to provide exceptional diagnostic performance in systemic disease. The optical portion consists of 6 pairs of time-multiplexed red and IR LEDs embedded in custom 3D-printed probes, which are each connected to the leg of a trifurcated fiber bundle, allowing measurement of three-location, two-distance broadband 550-950 nm spectra using a single commercial spectrometer. Data is demultiplexed and analyzed using derivative spectroscopy to quantify oxy/deoxyhemoglobin. Additional diagnostic signal was obtained from: impedance tomography and spectroscopy, ECG and plethysmography. In one of the largest porcine hemorrhage studies to date (n = 60), we demonstrate an 85% accuracy to detect a 2-3% blood volume loss. Preliminary results from 11 healthy human subjects undergoing lower body negative pressure (LBNP) challenge show a 95% accuracy in detecting 15-mmHg changes in pressure—an excellent surrogate for occult hemorrhage. Our system fills a critical need, including in the current pandemic, where clinicians struggle to predict which patients will deteriorate.
Currently-available metallic retractors typically used in transoral robotic surgery (TORS) cause significant artifacts in CT imaging and cannot be safely used in MRI. The lack of imaging-compatible oral retractors poses a significant challenge to enabling intraoperative imaging in TORS. This work introduces a customizable compact 3D-printed polymer retractor system that enables multiple modes of adjustability, artifact-free CT and MR images, and adequate surgical exposure. The polymer retractor design was modeled after the traditional metal FK and Crowe-Davis retractors and can be used with an acrylic suspension system that rests over the patient’s chest. Finite element analysis was conducted to evaluate the mechanical performance in relevant clinical loading conditions. Cadaver experiments followed by endoscopic, CT, and MR imaging were performed to demonstrate functionality. Artifact-free CT and MR images were obtained. An interincisive distance of 42.50 mm and 200.09 cm3 working volume were achieved, which allow the introduction of robotic arms and necessary instruments in TORS. This polymer retractor system makes it possible to acquire intraoperative images and establishes a critical step to make image-guided TORS both feasible and effective.
Image guidance for abdominal procedures requires an anatomical model capable of representing significant displacement and deformation of relevant tissues in a computationally efficient manner. This work evaluates the suitability of statistical shape modeling to represent key structures in Robot Assisted Laparoscopic Partial Nephrectomy (RALPN) both individually, and also as a multi-body composite model. Tomography obtained from subjects in an ongoing RALPN study was used to produce surface model representations of the kidneys, abdominal aorta, and inferior vena cava. Each structure was resliced and remeshed in a standardized fashion to allow for extraction of the principal modes of variation. Reduced parameter representations of the example structures based on the strongest eigenmodes indicate that <5mm average RMSE modeling accuracy can be achieved with four parameters for the individual models and eight parameters for the four-body composite model. The magnitude of centroid displacements observed under the principal modes of variation is consistent with literature-reported values, suggesting that this approach may be suitable for image guidance in RALPN.
Minimally invasive approaches to treating tumors of the pharynx and larynx like trans-oral surgery have improved patient outcome, but challenges remain in localizing tumors for margin control. Introducing necessary retractors and scopes deforms the anatomy and the tumor, rendering preoperative imaging inaccurate and making tumor localization difficult. This paper describes a pipeline that uses preoperative imaging to generate a hybrid FEM-multibody model and then dynamically simulates tongue deformation due to insertion of an electromagnetically-tracked laryngoscope. We hypothesize that the simulation output will be a sufficient estimate of the final intraoperative state and thus provide the surgeon with more accurate guidance during surgical resection. This pipeline was trialed on a cadaver head. The skull, mandible, and laryngoscope were tracked, and fiducial clips were embedded in the tongue for calculating target localization error (TLE) between the simulated and real tongue deformation. Registration accuracies were 1.1, 1.3, and 0.8 mm, respectively, for the tracked skull, mandible, and laryngoscope, and tracking and segmentation validation between the last tracked frame and the ground-truth intraoperative CT was 0.8, 0.9, and 1.2 mm, respectively. TLE of 6.4±2.5 mm was achieved for the full pipeline, in contrast to the total tongue deformation of 37.2±11.4 mm (via tongue clips) between the preoperative and intraoperative CT. Use of tracking and deformation modeling is viable to estimate deformation of the tongue during laryngoscopy. Future work involves additional intraoperative data streams to help further refine model parameters and improve localization.
Although robotic instrumentation has revolutionized manipulation in oncologic laparoscopy, there remains a significant need for image guidance during the exposure portion of certain abdominal procedures. The high degree of mobility and potential for deformation associated with abdominal organs and related structures poses a significant challenge to implementing image-based navigation for the initial phase of robot-assisted laparoscopic partial nephrectomy (RALPN). This work introduces two key elements of a RALPN exposure simulation framework: a model for laparoscopic exposure and a compact representation of anatomical geometry suitable for integration into a statistical estimation framework. Data to drive the exposure simulation were collected during a clinical RALPN case in which the robotic endoscope was tracked in six dimensions. An initial rigid registration was performed between a preoperative CT scan and the frame of the optical tracker, allowing the endoscope trajectory to be replayed over tomography to simulate anatomical observations with realistic kinematics. CT data from five study subjects were combined with four publicly available datasets to produce a mean kidney shape. This template kidney was fit back to each of the input models by optimally tuning a set of eight parameters, achieving an average RMSE of 2.18mm. These developments represent important steps toward a full, clinically-relevant framework for simulating organ exposure and testing navigation algorithms. In future work, a particle filter estimation scheme will be integrated into the simulation to incrementally optimize correspondences between parametric anatomical models and simulated or reconstructed endoscopic observations.
Tumor phantoms (TP) have been described for the purposes of training surgical residents and further understanding tissue characteristics in malignancy. To date, there has not been a tumor phantom described for the purposes of research and training in oncologic surgery of the head and neck focusing on the larynx and pharynx. With the goal of providing radiographic, visual, and physical mimicry of head and neck squamous cell carcinoma (HNSCC), a phantom was developed as a proposed training and research tool for trans-oral surgical procedures such as transoral laser microsurgery (TLM) and transoral robotic surgery (TORS). TP’s were constructed with an agar-gelatin chicken stock base to approximate reported physical properties, then glutaraldehyde and Omnipaque-350 were used as a fixative and to enhance CT-visualization respectively. Further, to ensure heterogeneity in radiographic imaging, other materials like olive oil and condensed milk were explored. These ingredients were combined with the use of a novel, 3D printed, syringe adaptor designed to allow for the direct injection of the liquid tumor into model tissue. TP’s fixed quickly in vivo upon implantation and were imaged using CT and segmented. This injection-based model was piloted in bovine tissue and verified in porcine tissue with excess Omnipaque-350 for volumetric reliability then optimized utilizing 6 well plates. Following radiographic optimization, the viscoelastic properties of TP’s were measured through uniaxial compression. We observed a Young’s modulus similar to published literature values and consistent reproducibility. Most notably, our proposed TP can be used by multiple specialties by altering the color and concentration of agar in the base solution to approximate physical properties.
Introduction: Traumatic brain injury (TBI) contributes to nearly a third of injury-related deaths, is the fourth leading cause of death in the U.S., and costs the U.S. ~$60 billion annually. There are two types of TBI, focal and diffuse, each requiring drastically different treatments. The current clinical standard for monitoring severe TBI is through intracranial pressure (ICP) sensing; however, significant limitations in the ICP response have motivated investigation into more multi-modal monitoring approaches. Electrical impedance has been shown to be sensitive to pathological changes within tissue including ischemia and stroke lesions. We hypothesize that by correlating electrical impedance to intracranial volume (ICV) changes we will be able to identify onset of a focal injury and localize it within the intracerebral space, overcoming many of the current limitations in TBI monitoring. Methods: A saline phantom and porcine animal model were used with controlled volume inflation steps of a Fogarty catheter. Impedance was collected across 8 electrode sectors and spatial localization capabilities compared to inclusion location. Autologous blood was then injected to simulate an intracerebral hemorrhage and the same protocol applied. Results: The phantom successfully detected inclusion presence, volume change and location. The animal model detected inclusion change with moderate success in accurately specifying location. Conclusion: Electrical impedance was successfully able to detect changes in intracranial volume in both a phantom and animal model. Additionally, initial results show potential spatial localization capabilities enabling differentiation of focal events from diffuse injury in monitoring of traumatic brain injury.
Magnetic Resonance Electrical Properties Tomography (MREPT) is an imaging modality that uses MR data to directly calculate the conductivity of the imaged object. This study evaluates if MREPT can be used to image differences between cancerous and benign prostate tissue. A total of 39 freshly excised prostates were imaged. MR data and four MREPT approaches were analyzed. Including a new MREPT approach that overlaps tiles (subdomains) resulting in an efficient approach that minimizes artifacts. No direct threshold value was found to differentiate the malignant from benign tissues. However, significance differences were found when comparing malignant and benign differences (differenced on a per slice basis), which reveals there are measurable differences between the two tissues. Ongoing work aims to develop a calibration technique that can exploit these differences so that malignant tissue can be robustly identified.
Despite a number of recent advances in robot-assisted surgery, achieving minimal access still requires that surgeons operate with reduced faculties for perception and manipulation as compared to open surgery. Image guidance shows promise for enhancing perception during local navigation (e.g. near occluded endophytic tumors), and we hypothesize that these methods can be extended to address the global navigation problem of efficiently locating and exposing a target organ and its associated anatomical structures. In this work we describe the high-level architecture of an augmented reality system for guiding access to abdominal organs in laparoscopic and robot-assisted procedures, and demonstrate the applicability of an array of assimilation algorithms through proof-of-concept simulation. Under the proposed framework, a coarse model of procedure-specific internal anatomy is initialized based on segmented pre-operative imaging. The model is rigidly registered to the patient at the time of trocar placement, then non-rigidly updated in an incremental manner during the access phase of surgery based on limited views of relevant anatomical structures as they are exposed. Observations are assumed to derive primarily from reconstruction of stereoscopic imaging; however, the assimilation framework provides a means of incorporating measurements made with other sensing modalities. Simulation results show that standard state estimation algorithms are suitable for accommodating large-scale displacement and deformation of the observed feature configuration relative to the initial model. Future work will include development of a suitable 3D model of anatomical structures involved in partial nephrectomy as well as provision for leveraging intraoperative dynamics in the assimilation framework.
In trans-oral surgeries, large intraoperative deformations limit the surgeons’ use of preoperative images to accurately resect tumors while traditional metal instruments render intraoperative images ineffective. A CT/MR compatible laryngoscopy system was developed previously to allow for the study of these deformations with intraoperative imaging. For this study, we compare the deformation analysis of two patient groups: those who had received prior radiation to the upper aerodigestive tract (irradiated) and those who have not (non-irradiated). We speculate that differences in tissue deformation exist between these two groups due to radiation-induced fibrosis (RIF) and that quantifying these distinct deformation patterns will lead to more patient-specific tissue modeling. Thirteen patients undergoing diagnostic laryngoscopy were recruited; five had been irradiated and eight had not. Artifact-free images were obtained and registered. Mandible, hyoid, and tongue region displacements were quantified. For the bony structures, significant differences were observed in certain displacement directions as well as magnitude, with the irradiated patient group experiencing less anatomical shift (non-irradiated vs irradiated: (Mandible) 12.6±3.6mm vs 7.9±2.8mm, p=0.029; (Hyoid) 13.3±3.1mm vs 9.0±1.8mm, p=0.019). For the tongue, average displacements of tongue fiducials were 26.2±11.1mm vs 22.9±8.4mm respectively (p=0.033). The data from this study can serve as ground truth to generate and evaluate upper aerodigestive tract deformation models to predict the intraoperative state and provide guidance to the surgeons.
Introduction: Prostate cancer is the second leading cause of cancer death in men. Biopsy serves as the primary tool for cancer diagnoses in these men. However, false-negative diagnosis following biopsy can be as high as 30% and even when detected via biopsy it can be difficult to accurately grade the cancer. Electrical properties of prostate cancer have been reported to be significantly different than benign prostate. We hypothesize that a custom tetrapolar-based electrical impedance sensing biopsy (EIS-Bx) needle will be able to detect electrical properties of surrounding tissue and provide a "4 bit" image for guidance to potential cancer locations. Methods: A custom EIS-Bx device was designed using four goldplated electrode traces on a standard biopsy needle. A novel small form-factor impedance analyzer was designed to interface with the EIS-Bx needle. The EIS-Bx device was submerged in a saline bath while a high contrast inclusion was rotated in 45-degree increments around the needle. At each location, the impedance of 4 electrode configurations was recorded at 7 frequencies (ranging from 1kHz to 100kHz). The impedances of each quadrant were compared with the inclusion location to examine spatial differentiation. Results: Bipolar measurements clearly detected impedance changes correlated to inclusion presence across frequencies. These results validate the hypothesis of potential "4-bit" imaging for cancer detection and diagnostic guidance. Conclusion: Initial experiments successfully demonstrate spatial sensitivity to a moving inclusion using the EIS-Bx device. Future work will investigate the ability to differentiate cancer from benign tissue ex-vivo with quadrant specific resolution and to display this as a real-time map of prostate pathology.
A non-invasive and accurate modality that can continuously monitor stroke volume (SV) for extended periods of time is desired to allow for more proactive care of an increasing population of patients living with heart failure. Electrical impedance tomography (EIT) has been proposed as a method for accurate, non-invasive, continuous, and long-term SV monitoring. While cardiac EIT has been explored, clinical translation has yet to occur and a standardized method for evaluation and comparison of cardiac EIT images is desired. This work explores an automated process for segmenting and extracting features from the images that allow for evaluation and comparison. A simulation study was conducted using the 4D XCAT model to evaluate the proposed method’s ability to automatically segment and extract features from images reconstructed at various phases of the cardiac cycle. The same procedure was then applied to EIT reconstructions on data collected from five healthy volunteers. The automated segmentation is able to accurately capture the heart region-of-interest (ROI) in various images and extract features, which allows comparison of desired signals across reconstructions. ROI mean conductivity, ROI area, sum of conductivities within the ROI, and ROI maximum conductivity were chosen as promising features from the simulation study, with R2 values of 0.61, 0.73, 0.75, and 0.66 for a single heart-cycle, and minimum SV distinguishability of 25.54, 12.16, 12.16, and 17.22 ml. In experimental data, the area feature showed the least variation across individual reconstructions while the sum feature showed the highest variation.
Telemonitoring is becoming increasingly important as the proportion of the population living with cardiovascular disease (CVD) increases. Currently used health parameters in the suite of telemonitoring tools lack the sensitivity and specificity to accurately predict heart failure events, forcing physicians to play a reactive versus proactive role in patient care. A novel cardiac output (CO) monitoring device is proposed that leverages a custom smart phone application and a wearable electrical impedance tomography (EIT) system. The purpose of this work is to explore the potential of using respiratory-gated EIT to quantify stroke volume (SV) and assess its feasibility using real data. Simulations were carried out using the 4D XCAT model to create anatomically realistic meshes and electrical conductivity profiles representing the human thorax and the intrathoracic tissue. A single 5-second period respiration cycle with chest/lung expansion was modeled with end-diastole (ED) and end-systole (ES) heart volumes to evaluate how effective EIT-based conductivity changes represent clinically significant differences in SV. After establishing a correlation between conductivity changes and SV, the applicability of the respiratory-gated EIT was refined using data from the PhysioNet database to estimate the number of useful end-diastole (ED) and end-systole (ES) heart events attained over a 3.3 minute period. The area associated with conductivity changes was found to correlate to SV with a correlation coefficient of 0.92. A window of 12.5% around peak exhalation was found to be the optimal phase of the respiratory cycle from which to record EIT data. Within this window, ~47 useable ED and ES were found with a standard deviation of 28 using 3.3 minutes of data for 20 patients.
Prostate cancer (PCa) has a high 10-year recurrence rate, making PCa the second leading cause of cancer-specific mortality among men in the USA. PCa recurrences are often predicted by assessing the status of surgical margins (SM) with positive surgical margins (PSM) increasing the chances of biochemical recurrence by 2-4 times. To this end, an SM assessment system using Electrical Impedance Spectroscopy (EIS) was developed with a microendoscopic probe. This system measures the tissue bioimpedance over a range of frequencies (1 kHz to 1MHz), and computes a Composite Impedance Metric (CIM). CIM can be used to classify tissue as benign or cancerous. The system was used to collect the impedance spectra from excised prostates, which were obtained from men undergoing radical prostatectomy. The data revealed statistically significant (p<0.05) differences in the impedance properties of the benign and tumorous tissues, and between different tissue morphologies. To visualize the results of SM-assessment, a visualization tool using da Vinci stereo laparoscope is being developed. Together with the visualization tool, the EIS-based SM assessment system can be potentially used to intraoperatively classify tissues and display the results on the surgical console with a video feed of the surgical site, thereby augmenting a surgeon’s view of the site and providing a potential solution to the intraoperative SM assessment needs.
Positive surgical margins (PSMs) found following prostate cancer surgery are a significant risk factor for post-operative disease recurrence. Noxious adjuvant radiation and chemical-based therapies are typically offered to men with PSMs. Unfortunately, no real-time intraoperative technology is currently available to guide surgeons to regions of suspicion during the initial prostatectomy where immediate surgical excisions could be used to reduce the chance of PSMs. A microendoscopic electrical impedance sensing probe was developed with the intention of providing real-time feedback regarding margin status to surgeons during robot-assisted laparoscopic prostatectomy (RALP) procedures. A radially configured 17-electrode microendoscopic probe was designed, constructed, and initially evaluated through use of gelatin-based phantoms and an ex vivo human prostate specimen. Impedance measurements are recorded at 10 frequencies (10 kHz - 100 kHz) using a high-speed FPGA-based electrical impedance tomography (EIT) system. Tetrapolar impedances are recorded from a number of different electrode configurations strategically chosen to sense tissue in a pre-defined sector underlying the probe face. A circular electrical impedance map (EIM) with several color-coded pie-shaped sectors is created to represent the impedance values of the probed tissue. Gelatin phantom experiments show an obvious distinction in the impedance maps between high and low impedance regions. Similarly, the EIM generated from the ex vivo prostate case shows distinguishing features between cancerous and benign regions. Based on successful development of this probe and these promising initial results, EIMs of additional prostate specimens are being collected to further evaluate this approach for intraoperative surgical margin assessment during RALP procedures.
Robot-assisted laparoscopic partial nephrectomies (RALPN) are performed to treat patients with locally confined renal carcinoma. There are well-documented benefits to performing partial (opposed to radical) kidney resections and to using robot-assisted laparoscopic (opposed to open) approaches. However, there are challenges in identifying tumor margins and critical benign structures including blood vessels and collecting systems during current RALPN procedures. The primary objective of this effort is to couple multiple image and data streams together to augment visual information currently provided to surgeons performing RALPN and ultimately ensure complete tumor resection and minimal damage to functional structures (i.e. renal vasculature and collecting systems). To meet this challenge we have developed a framework and performed initial feasibility experiments to couple pre-operative high-resolution anatomic images with intraoperative MRI, ultrasound (US) and optical-based surface mapping and kidney tracking. With these registered images and data streams, we aim to overlay the high-resolution contrast-enhanced anatomic (CT or MR) images onto the surgeon’s view screen for enhanced guidance. To date we have integrated the following components of our framework: 1) a method for tracking an intraoperative US probe to extract the kidney surface and a set of embedded kidney markers, 2) a method for co-registering intraoperative US scans with pre-operative MR scans, and 3) a method for deforming pre-op scans to match intraoperative scans. These components have been evaluated through phantom studies to demonstrate protocol feasibility.
Prostate cancer diagnosis is based solely on biopsy-based findings. Unfortunately, routine biopsy protocols only sample
~0.95% of the entire gland limiting the technique's sensitivity to cancer detection. Previous studies have demonstrated
significant electrical property differences between malignant and benign prostate tissues due to their dissimilar
morphological architectures. We have taken the important step of translating these findings to the clinic by integrating
an electrical property sensor into the tip of a standard biopsy needle. This novel device allows clinicians to
simultaneously extract a tissue core and assess the electrical properties around the needle tip in real-time. The expected
volume of tissue sensed with this device was estimated using finite-element method (FEM) based simulations to model
the potential fields and current distributions. Prototype devices have been constructed and evaluated in a series of saline
baths in order to validate the FEM-based findings. Simulations suggest that the electrical property sensor is able to
interrogate a tissue volume of ~62.1 mm3 and experimental results demonstrated a volume of sensitivity of ~68.7 mm3.
This coupled device is being used to assess the increased sensitivity and specificity to cancer detection when electrical
properties are sensed in concert with tissue core extraction in a series of 50 ex vivo prostates. Typical 12-core prostate
biopsy protocols extract a total tissue volume of 228 mm3 for histological assessment. Employing this electrical
property sensor to gauge electrical properties at both the beginning and end of the needle trajectory will provide
pathological assessment of an additional 1648 mm3 of tissue.
The cracking and failure in ceramic substrates during the laser drilling process has been acknowledged as a major problem by designers and manufacturers in the electronic component industries. The cracking and failure is due to large localized thermal stresses within the narrow heat-affected zone on the ceramics. Although the knowledge of the stress distribution in the ceramic substrate is important in understanding and solving the cracking/failure problem, it is impossible to measure the stress directly. The physical parameters of the laser drilling process such as temperatures or displacements, which can be directly related to stresses, can however be measured. That is why, in this research, an electronic speckle pattern interferometer (ESPI) system was designed and used to take speckle pattern images of the ceramic surface during the laser drilling process. Using commercial software, the speckle fringe images were image processed to quantify whole-field transient out-of-plane displacement measurements. A deformation history of the ceramic surface during the laser shaping process with millisecond temporal resolution was obtained, restricted only by the camera frame rate, camera resolution and laser power available. A finite difference model was developed to compare the deformation measurements with the predicted strain calculations.
The experimental study and the analysis show that the designed in-situ electronic speckle pattern interferometer system provides an excellent experimental basis for whole- field, transient deformation measurements of ceramic substrates during the laser drilling process.
There is a need to analyze locomotive wheels for flank cracks in a non-destructive manner in order to prevent catastrophic failures. Flaw, shape, and size are desired parameters in establishing the quality of commercial tires. A variety of defects such as voids, inclusions, surface and internal cracks, or the like, must be discerned in order to prevent failure.
This paper exhibits and compares the benefits of a number of different techniques used for flaw detection. Non-destructive evaluation techniques used consist of a magnetic particle, dye penetrant, eddy current, electro-magnetic acoustic transducer (EMAT), and longitudinal and shear wave ultrasonic inspection. The techniques vary in their ability to ascertain the flaw characteristics. Surface, sub-surface, and internal defects were visualized using the various methodologies. Magnetic particle, dye penetrant, and eddy current inspection techniques are viable methods for looking at surface flaws. Depending on the penetration depth, sub- surface flaws were also detectable via these methods. EMAT and ultrasonic transducer methods can be used to find surface, subsurface, and internal flaws based on the configuration utilized.
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