Coded excitation using periodic and unipolar M-sequences for photoacoustic imaging and flow measurement.

Photoacoustic imaging is an emerging imaging technology combining optical imaging with ultrasound. Imaging of the optical absorption coefficient and flow measurement provides additional functional information compared to ultrasound. The issue with photoacoustic imaging is its low signal-to-noise ratio (SNR) due to scattering or attenuation; this is especially problematic when high pulse repetition frequency (PRF) lasers are used. In previous research, coded excitation utilizing several pseudorandom sequences has been considered as a solution for the problem. However, previously proposed temporal coding procedures using Golay codes or M-sequences are so complex that it was necessary to send a sequence twice to realize a bipolar sequence. Here, we propose a periodic and unipolar sequence (PUM), which is a periodic sequence derived from an m-sequence. The PUM can enhance signals without causing coding artifacts for single wavelength excitation. In addition, it is possible to increase the temporal resolution since the decoding start point can be set to any code in periodic irradiation, while only the first code of a sequence was available for conventional aperiodic irradiation. The SNR improvement and the increase in temporal resolution were experimentally validated through imaging evaluation and flow measurement.

Intraoperative Ablation Control Based on Real-Time Necrosis Monitoring Feedback: Numerical Evaluation.

Ablation therapy is a type of minimally invasive treatment, utilized for various organs including the brain, heart, and kidneys. The accuracy of the ablation process is critically important to avoid both insufficient and excessive ablation, which may result in compromised efficacy or complications. The thermal ablation is formulated by two theoretical models: the heat transfer (HT) and necrosis formation (NF) models. In modern medical practices, feed-forward (FF) and temperature feedback (TFB) controls are primarily used as ablation control methodologies. FF involves pre-therapy procedure planning based on previous experiences and theoretical knowledge without monitoring the intraoperative tissue response, hence, it can't compensate for discrepancies in the assumed HT or NF models. These discrepancies can arise due to individual patient's tissue characteristic differences and specific environmental conditions. Conversely, TFB control is based on the intraoperative temperature profile. It estimates the resulting heat damage based on the monitored temperature distribution and assumed NF model. Therefore, TFB can make necessary adjustments even if there is an error in the assumed HT model. TFB is thus seen as a more robust control method against modeling errors in the HT model. Still, TFB is limited as it assumes a fixed NF model, irrespective of the patient or the ablation technique used. An ideal solution to these limitations would be to actively monitor heat damage to the tissue during the operation and utilize this data to control ablation. This strategy is defined as necrosis feedback (NFB) in this study. Such real-time necrosis monitoring modalities making NFB possible are emerging, however, there is an absence of a generalized study that discusses the integration and quantifies the significance of the real-time necrosis monitor techniques for ablation therapy. Such an investigation is expected to clarify the universal principles of how these techniques would improve ablation therapy. In this study, we examine the potential of NFB in suppressing errors associated with the NF model as NFB is theoretically capable of monitoring and suppressing the errors associated with the NF models in its closed control loop. We simulate and compare the performances of TFB and NFB with artificially generated modeling errors using the finite element method (FEM). The results show that NFB provides more accurate ablation control than TFB when NF-oriented errors are applied, indicating NFB's potential to improve the ablation control accuracy and highlighting the value of the ongoing research to make real-time necrosis monitoring a clinically viable option.

Intraoperative Ablation Control Based on Real-time Necrosis Monitoring Feedback: Numerical Evaluation.

Ablation therapy is a type of minimally invasive treatment, utilized for various organs including the brain, heart, and kidneys. The accuracy of the ablation process is critically important to avoid both insufficient and excessive ablation, which may result in compromised efficacy or complications. The thermal ablation is formulated by two theoretical models: the heat transfer (HT) and necrosis formation (NF) models. In modern medical practices, feed-forward (FF) and temperature feedback (TFB) controls are primarily used as ablation control methodologies. FF involves pre-therapy procedure planning based on previous experiences and theoretical knowledge without monitoring the intraoperative tissue response, hence, it can't compensate for discrepancies in the assumed HT or NF models. These discrepancies can arise due to individual patient's tissue characteristic differences and specific environmental conditions. Conversely, TFB control is based on the intraoperative temperature profile. It estimates the resulting heat damage based on the monitored temperature distribution and assumed NF model. Therefore, TFB can make necessary adjustments even if there is an error in the assumed HT model. TFB is thus seen as a more robust control method against modeling errors in the HT model. Still, TFB is limited as it assumes a fixed NF model, irrespective of the patient or the ablation technique used. An ideal solution to these limitations would be to actively monitor heat damage to the tissue during the operation and utilize this data to control ablation. This strategy is defined as necrosis feedback (NFB) in this study. Such real-time necrosis monitoring modalities making NFB possible are emerging, however, there is an absence of a generalized study that discusses the integration and quantifies the significance of the real-time necrosis monitor techniques for ablation therapy. Such an investigation is expected to clarify the universal principles of how these techniques would improve ablation therapy. In this study, we examine the potential of NFB in suppressing errors associated with the NF model as NFB is theoretically capable of monitoring and suppressing the errors associated with the NF models in its closed control loop. We simulate and compare the performances of TFB and NFB with artificially generated modeling errors using the finite element method (FEM). The results show that NFB provides more accurate ablation control than TFB when NF-oriented errors are applied, indicating NFB's potential to improve the ablation control accuracy and highlighting the value of the ongoing research to make real-time necrosis monitoring a clinically viable option.

Large area kidney imaging for pre-transplant evaluation using real-time robotic optical coherence tomography.

Optical coherence tomography (OCT) can be used to image microstructures of human kidneys. However, current OCT probes exhibit inadequate field-of-view, leading to potentially biased kidney assessment. Here we present a robotic OCT system where the probe is integrated to a robot manipulator, enabling wider area (covers an area of 106.39 mm by 37.70 mm) spatially-resolved imaging. Our system comprehensively scans the kidney surface at the optimal altitude with preoperative path planning and OCT image-based feedback control scheme. It further parameterizes and visualizes microstructures of large area. We verified the system positioning accuracy on a phantom as 0.0762 ± 0.0727 mm and showed the clinical feasibility by scanning ex vivo kidneys. The parameterization reveals vasculatures beneath the kidney surface. Quantification on the proximal convoluted tubule of a human kidney yields clinical-relevant information. The system promises to assess kidney viability for transplantation after collecting a vast amount of whole-organ parameterization and patient outcomes data.

Beyond synthetic aperture focusing: deconvolution-based elevation resolution enhancement using simulated point spread function for linear array-based three-dimensional photoacoustic imaging.

This paper introduces a deconvolution-based method to enhance the elevation resolution of a linear array-based three-dimensional (3D) photoacoustic (PA) imaging system. PA imaging combines the high contrast of optical imaging with the deep, multi-centimeter spatial resolution of ultrasound (US) imaging, providing structural and functional information about biological tissues. Linear array-based 3D PA imaging is easily accessible and applicable for ex vivo studies, small animal research, and clinical applications in humans. However, its elevation resolution is limited by the acoustic lens geometry, which establishes a single elevation focus. Previous work used synthetic aperture focusing (SAF) to enhance elevation resolution, but the resolution achievable by SAF is constrained by the size of the elevation focus. Here, we introduce the application of Richardson-Lucy deconvolution, grounded in simulated point-spread-functions, to surpass the elevation resolution attainable with SAF alone. We validated this approach using both simulation and experimental data, demonstrating that the full-width-at-half-maximum of point targets on the elevation plane was reduced compared to using SAF only, suggesting resolution improvement. This method shows promise for improving 3D image quality of existing linear array-based PA imaging systems, offering potential benefits for disease diagnosis and monitoring.

Cardiac-gated spectroscopic photoacoustic imaging for ablation-induced necrotic lesion visualization.

Radiofrequency (RF) ablation is a minimally invasive therapy for atrial fibrillation. Conventional RF procedures lack intraoperative monitoring of ablation-induced necrosis, complicating assessment of completeness. While spectroscopic photoacoustic (sPA) imaging shows promise in distinguishing ablated tissue, multi-spectral imaging is challenging in vivo due to low imaging quality caused by motion. Here, we introduce a cardiac-gated sPA imaging (CG-sPA) framework to enhance image quality using a motion-gated averaging filter, relying on image similarity. Necrotic extent was calculated based on the ratio between spectral unmixed ablated tissue contrast and total tissue contrast, visualizing as a continuous color map to highlight necrotic area. The validation of the concept was conducted in both ex vivo and in vivo swine models. The ablation-induced necrotic lesion was successfully detected throughout the cardiac cycle through CG-sPA imaging. The results suggest the CG-sPA imaging framework has great potential to be incorporated into clinical workflow to guide ablation procedures intraoperatively.

Enhancing boundary detection of radiofrequency ablation lesions through photoacoustic mapping.

Atrial fibrillation (A-fib) is the most common type of heart arrhythmia, typically treated with radiofrequency catheter ablation to isolate the heart from abnormal electrical signals. Monitoring the formation of ablation-induced lesions is crucial for preventing recurrences and complications arising from excessive or insufficient ablation. Existing imaging modalities lack real-time feedback, and their intraoperative usage is in its early stages. A critical need exists for an imaging-based lesion indexing (LSI) method that directly reflects tissue necrosis formation. Previous studies have indicated that spectroscopic photoacoustic (sPA) imaging can differentiate ablated tissues from their non-ablated counterparts based on PA spectrum variation. In this paper, we introduce a method for detecting ablation lesion boundaries using sPA imaging. This approach utilizes ablation LSI, which quantifies the ratio between the signal from ablated tissue and the total tissue signal. We enhance boundary detection accuracy by adapting a regression model-based compensation. Additionally, the method was cross-validated with clinically used intraoperative monitoring parameters. The proposed method was validated with ex vivo porcine cardiac tissues with necrotic lesions created by different ablation durations. The PA-measured lesion size was compared with gross pathology. Statistical analysis demonstrates a strong correlation (R > 0.90) between the PA-detected lesion size and gross pathology. The PA-detected lesion size also exhibits a moderate to strong correlation (R > 0.75) with local impedance changes recorded during procedures. These results suggest that the introduced PA imaging-based LSI has great potential to be incorporated into the clinical workflow, guiding ablation procedures intraoperatively.

Large Area Kidney Imaging for Pre-transplant Evaluation using Real-Time Robotic Optical Coherence Tomography.

Optical coherence tomography (OCT) is a high-resolution imaging modality that can be used to image microstructures of human kidneys. These images can be analyzed to evaluate the viability of the organ for transplantation. However, current OCT devices suffer from insufficient field-of-view, leading to biased examination outcomes when only small portions of the kidney can be assessed. Here we present a robotic OCT system where an OCT probe is integrated with a robotic manipulator, enabling wider area spatially-resolved imaging. With the proposed system, it becomes possible to comprehensively scan the kidney surface and provide large area parameterization of the microstructures. We verified the probe tracking accuracy with a phantom as 0.0762±0.0727 mm and demonstrated its clinical feasibility by scanning ex vivo kidneys. The parametric map exhibits fine vasculatures beneath the kidney surface. Quantitative analysis on the proximal convoluted tubule from the ex vivo human kidney yields highly clinical-relevant information.

Needle Aligned Ultrasound Image-Guided Access Through Dual-Segment Array.

Ultrasound (US) guided access for percutaneous nephrolithotomy (PCNL) is gaining popularity in the urology community as it reduces radiation risk. The most popular technique involves manual image-needle alignment. A misaligned needle however needs to be retracted and reinserted, resulting in a lengthened operation time and complications such as bleeding. These limitations can be mitigated through the co-registration between the US array and needle. The through-hole array concept provides the primary solution, including a hole at the center of the array. Because of the central opening, the image-needle alignment is achieved inherently. Previous literature has described applications that are limited to superficial and intravascular procedures, suggesting that developing a through-hole array for deeper target applications would be a new breakthrough. OBJECTIVE: Here, we present a dual-segment array with a central opening. As the prototype development, two segments of 32-element arrays are combined with an open space of 10 mm in length in between them. METHOD: We conducted phantom and ex-vivo studies considering the target depth of the 80-100 mm range. The image quality and needle visibility are evaluated by comparing the signal-to-noise ratio (SNR), full width at half maximum (FWHM), and contrast-to-noise ratio (CNR) results measured with a no-hole linear array under equivalent conditions. An ex-vivo study is performed using porcine kidneys with ceramic balls embedded to evaluate the needle access accuracy. RESULTS AND CONCLUSION: The mean needle access error of 20 trials is found to be 2.94 ±1.09 mm, suggesting its potential impact on realizing a simple and intuitive deep US image-guided access.

In-bore MRI-compatible Transrectal Ultrasound and Photoacoustic Imaging.

Prostate cancer (PCa) is known as one of the most prevalent and fatal cancer types. This report describes an MRI-compatible photoacoustic/ultrasound (PA/US) imaging platform to improve the diagnosis of PCa. In the proposed solution, PA imaging, which offers real-time, non-ionizing imaging with high sensitivity and specificity, is combined with MRI, aiming to overcome PA's limited field of view (FOV) and make PA scalable for translation to clinical settings. Central to the design of the system is a reflector-based transrectal probing mechanism composed of MRI-compatible materials. The linear transducer with a center hole for optical fiber delivery can be mechanically actuated to form a multi-angled scan, allowing PA/US imaging from varied cross-sectional views. Performance assessment was carried out in phantom and ex-vivo settings. We confirmed the MRI compatibility of the system and demonstrated the feasibility of its tri-modal imaging capability by visualizing a tubing phantom containing contrast agents. The ex-vivo evaluation of targeted tumor imaging capability was performed with a mouse liver sample expressing PSMA-positive tumors, affirming the system's compatibility in spectroscopic PA (sPA) imaging with biological tissue. These results support the feasibility of the in-bore MRI-compatible transrectal PA and US and the potential clinical adaptability.

Intraoperative laparoscopic photoacoustic image guidance system in the da Vinci surgical system.

This paper describes a framework allowing intraoperative photoacoustic (PA) imaging integrated into minimally invasive surgical systems. PA is an emerging imaging modality that combines the high penetration of ultrasound (US) imaging with high optical contrast. With PA imaging, a surgical robot can provide intraoperative neurovascular guidance to the operating physician, alerting them of the presence of vital substrate anatomy invisible to the naked eye, preventing complications such as hemorrhage and paralysis. Our proposed framework is designed to work with the da Vinci surgical system: real-time PA images produced by the framework are superimposed on the endoscopic video feed with an augmented reality overlay, thus enabling intuitive three-dimensional localization of critical anatomy. To evaluate the accuracy of the proposed framework, we first conducted experimental studies in a phantom with known geometry, which revealed a volumetric reconstruction error of 1.20 ± 0.71 mm. We also conducted an ex vivo study by embedding blood-filled tubes into chicken breast, demonstrating the successful real-time PA-augmented vessel visualization onto the endoscopic view. These results suggest that the proposed framework could provide anatomical and functional feedback to surgeons and it has the potential to be incorporated into robot-assisted minimally invasive surgical procedures.

Laparoscopic Photoacoustic Imaging System Based on Side-Illumination Diffusing Fibers.

OBJECTIVE: To develop a flexible miniaturized photoacoustic (PA) imaging probe for detecting anatomical structures during laparoscopic surgery. The proposed probe aimed to facilitate intraoperative detection of blood vessels and nerve bundles embedded in tissue not directly visible to the operating physician to preserve these delicate and vital structures. METHODS: We modified a commercially available ultrasound laparoscopic probe by incorporating custom-fabricated side-illumination diffusing fibers that illuminate the probe's field of view. The probe geometry, including the position and orientation of the fibers and the emission angle, was determined using computational models of light propagation in the simulation and subsequently validated through experimental studies. RESULTS: In wire phantom studies within an optical scattering medium, the probe achieved an imaging resolution of 0.43 ±0.09 mm and a signal-to-noise ratio of 31.2±1.84 dB. We also conducted an ex vivo study using a rat model, demonstrating the successful detection of blood vessels and nerves. CONCLUSION: Our results indicate the viability of a side-illumination diffusing fiber PA imaging system for guidance during laparoscopic surgery. SIGNIFICANCE: The potential clinical translation of this technology could enhance the preservation of critical vascular structures and nerves, thereby minimizing post-operative complications.

Concentric-ring arrays for forward-viewing ultrasound imaging.

Purpose: Current ultrasound (US)-image-guided needle insertions often require an expertized technique for clinicians because the performance of tasks in a three-dimensional space using two-dimensional images requires operators to cognitively maintain the spatial relationships between the US probe, the needle, and the lesion. This work presents forward-viewing US imaging with a ring array configuration to enable needle interventions without requiring the registration between tools and targets. Approach: The center-open ring array configuration allows the needle to be inserted from the center of the visualized US image, providing simple and intuitive guidance. To establish the feasibility of the ring array configuration, the design parameters causing the image quality, including the radius of the center hole and the number of ring layers and transducer elements, were investigated. Results: Experimental results showed successful visualization, even with a hole in the transducer elements, and the target visibility was improved by increasing the number of ring layers and the number of transducer elements in each ring layer. Reducing the hole radius improved the region's image quality at a shallow depth. Conclusions: Forward-viewing US imaging with a ring array configuration has the potential to be a viable alternative to conventional US image-guided needle insertion methods.

Actuated Reflector-Based 3-D Ultrasound Imaging With Synthetic Aperture Focusing.

The 3-D ultrasound (US) imaging addresses the limitation in field-of-view (FOV) in conventional 2-D US imaging by providing 3-D viewing of the anatomy. The 3-D US imaging has been extensively adapted for diagnosis and image-guided surgical intervention. However, conventional approaches to implement 3-D US imaging require either expensive and sophisticated 2-D array transducers or external actuation mechanisms to move a 1-D array mechanically. Here, we propose a 3-D US imaging mechanism using an actuated acoustic reflector instead of the sensor elements for volume acquisition with significantly extended 3-D FOV, which can be implemented with simple hardware and compact size. To improve image quality on the elevation plane, we implemented the synthetic aperture focusing (SAF) method according to the diagonal geometry of the virtual element array in the proposed imaging mechanism for elevation beamforming. We first evaluated the proposed imaging mechanism and SAF with simulated point targets and cyst targets. The results of point targets suggested improved image quality on the elevation plane, and the results of cysts targets demonstrated a potential to improve 3-D visualization of human anatomy. We built a prototype imaging system with a 3-D FOV of 38 mm (lateral) by 38 mm (elevation) by 50 mm (axial) and collected data in imaging experiments with phantoms. Experimental data showed consistency with simulation results. The SAF method enhanced quantifying the cyst volume size in the breast mimicking phantom compared with no elevation beamforming. These results suggested that the proposed 3-D US imaging mechanism could potentially be applied in clinical scenarios.

A-SEE: Active-Sensing End-effector Enabled Probe Self-Normal-Positioning for Robotic Ultrasound Imaging Applications.

Conventional manual ultrasound (US) imaging is a physically demanding procedure for sonographers. A robotic US system (RUSS) has the potential to overcome this limitation by automating and standardizing the imaging procedure. It also extends ultrasound accessibility in resource-limited environments with the shortage of human operators by enabling remote diagnosis. During imaging, keeping the US probe normal to the skin surface largely benefits the US image quality. However, an autonomous, real-time, low-cost method to align the probe towards the direction orthogonal to the skin surface without pre-operative information is absent in RUSS. We propose a novel end-effector design to achieve self-normal-positioning of the US probe. The end-effector embeds four laser distance sensors to estimate the desired rotation towards the normal direction. We then integrate the proposed end-effector with a RUSS system which allows the probe to be automatically and dynamically kept to normal direction during US imaging. We evaluated the normal positioning accuracy and the US image quality using a flat surface phantom, an upper torso mannequin, and a lung ultrasound phantom. Results show that the normal positioning accuracy is 4.17 ± 2.24 degrees on the flat surface and 14.67 ± 8.46 degrees on the mannequin. The quality of the RUSS collected US images from the lung ultrasound phantom was equivalent to that of the manually collected ones.

Acoustic-resolution photoacoustic microscope based on compact and low-cost delta configuration actuator.

The state-of-the-art configurations for acoustic-resolution photoacoustic (PA) microscope (AR-PAM) are large in size and expensive, hindering their democratization. While previous research on AR-PAMs introduced a low-cost light source to reduce the cost, few studies have investigated the possibility of optimizing the sensor actuation, particularly for the AR-PAM. Additionally, there is an unmet need to evaluate the image quality deterioration associated with the actuation inaccuracy. A low-cost actuation device is introduced to reduce the system size and cost of the AR-PAM while maintaining the image quality by implementing the advanced beamformers. This work proposes an AR-RAM incorporating the delta configuration actuator adaptable from a low-cost off-the-shelf 3D printer as the sensor actuation device. The image degradation due to the data acquisition positioning inaccuracy is evaluated in the simulation. We further assess the mitigation of potential actuation precision uncertainty through advanced 3D synthetic aperture focusing algorithms represented by the Delay-and-Sum (DAS) with Coherence Factor (DAS+CF) and Delay-Multiply-and-Sum (DMAS) algorithms. The simulation study demonstrated the tolerance of image quality on actuation inaccuracy and the effect of compensating the actuator motion precision error through advanced reconstruction algorithms. With those algorithms, the image quality degradation was suppressed to within 25% with the presence of 0.2 mm motion inaccuracy. The experimental evaluation using phantoms and an ex-vivo sample presented the applicability of low-cost delta configuration actuators for AR-PAMs. The measured full width at half maximum of the 0.2 mm diameter pencil-lead phantom were 0.45 ± 0.06 mm, 0.31 ± 0.04 mm, and 0.35 ± 0.07 mm, by applying the DAS, DAS+CF, and DMAS algorithms, respectively. AR-PAMs with a compact and low-cost delta configuration provide high-quality PA imaging with better accessibility for biomedical applications. The research evaluated the image degradation contributed by the actuation inaccuracy and suggested that the advanced beamformers are capable of suppressing the actuation inaccuracy.

System-level optimization in spectroscopic photoacoustic imaging of prostate cancer.

This study presents a system-level optimization of spectroscopic photoacoustic (PA) imaging for prostate cancer (PCa) detection in three folds. First, we present a spectral unmixing model to segregate spectral system error (SSE). We constructed two noise models (NMs) for the laser spectrotemporal fluctuation and the ultrasound system noise. We used these NMs in linear spectral unmixing to denoise and to achieve high temporal resolution. Second, we employed a simulation-aided wavelength optimization to select the most effective subset of wavelengths. NMs again were considered so that selected wavelengths were not only robust to the collinearity of optical absorbance, but also to noise. Third, we quantified the effect of frame averaging on improving spectral unmixing accuracy through theoretical analysis and numerical validation. To validate the whole framework, we performed comprehensive studies in simulation and an in vivo experiment which evaluated prostate-specific membrane antigen (PSMA) expression in PCa on a mice model. Both simulation analysis and in vivo studies confirmed that the proposed framework significantly enhances image signal-to-noise ratio (SNR) and spectral unmixing accuracy. It enabled more sensitive and faster PCa detection. Moreover, the proposed framework can be generalized to other spectroscopic PA imaging studies for noise reduction, wavelength optimization, and higher temporal resolution.

Autonomous Scanning Target Localization for Robotic Lung Ultrasound Imaging.

Under the ceaseless global COVID-19 pandemic, lung ultrasound (LUS) is the emerging way for effective diagnosis and severeness evaluation of respiratory diseases. However, close physical contact is unavoidable in conventional clinical ultrasound, increasing the infection risk for health-care workers. Hence, a scanning approach involving minimal physical contact between an operator and a patient is vital to maximize the safety of clinical ultrasound procedures. A robotic ultrasound platform can satisfy this need by remotely manipulating the ultrasound probe with a robotic arm. This paper proposes a robotic LUS system that incorporates the automatic identification and execution of the ultrasound probe placement pose without manual input. An RGB-D camera is utilized to recognize the scanning targets on the patient through a learning-based human pose estimation algorithm and solve for the landing pose to attach the probe vertically to the tissue surface; A position/force controller is designed to handle intraoperative probe pose adjustment for maintaining the contact force. We evaluated the scanning area localization accuracy, motion execution accuracy, and ultrasound image acquisition capability using an upper torso mannequin and a realistic lung ultrasound phantom with healthy and COVID-19-infected lung anatomy. Results demonstrated the overall scanning target localization accuracy of 19.67 ± 4.92 mm and the probe landing pose estimation accuracy of 6.92 ± 2.75 mm in translation, 10.35 ± 2.97 deg in rotation. The contact force-controlled robotic scanning allowed the successful ultrasound image collection, capturing pathological landmarks.

Anatomical Feature-Based Lung Ultrasound Image Quality Assessment Using Deep Convolutional Neural Network.

Lung ultrasound (LUS) has been used for point-of-care diagnosis of respiratory diseases including COVID-19, with advantages such as low cost, safety, absence of radiation, and portability. The scanning procedure and assessment of LUS are highly operator-dependent, and the appearance of LUS images varies with the probe's position, orientation, and contact force. Karamalis et al. introduced the concept of ultrasound confidence maps based on random walks to assess the ultrasound image quality algorithmically by estimating the per-pixel confidence in the image data. However, these confidence maps do not consider the clinical context of an image, such as anatomical feature visibility and diagnosability. This work proposes a deep convolutional network that detects important anatomical features in an LUS image to quantify its clinical context. This work introduces an Anatomical Feature-based Confidence (AFC) Map, quantifying an LUS image's clinical context based on the visible anatomical features. We developed two U-net models, each segmenting one of the two classes crucial for analyzing an LUS image, namely 1) Bright Features: Pleural and Rib Lines and 2) Dark Features: Rib Shadows. Each model takes the LUS image as input and outputs the segmented regions with confidence values for the corresponding class. The evaluation dataset consists of ultrasound images extracted from videos of two sub-regions of the chest above the anterior axial line from three human subjects. The feature segmentation models achieved an average Dice score of 0.72 on the model's output for the testing data. The average of non-zero confidence values in all the pixels was calculated and compared against the image quality scores. The confidence values were different between different image quality scores. The results demonstrated the relevance of using an AFC Map to quantify the clinical context of an LUS image.

Tele-Operative Low-Cost Robotic Lung Ultrasound Scanning Platform for Triage of COVID-19 Patients.

Novel severe acute respiratory syndrome coronavirus 2 (COVID-19) has become a pandemic of epic proportions, and global response to prepare health systems worldwide is of utmost importance. 2-dimensional (2D) lung ultrasound (LUS) has emerged as a rapid, noninvasive imaging tool for diagnosing COVID-19 infected patients. Concerns surrounding LUS include the disparity of infected patients and healthcare providers, and importantly, the requirement for substantial physical contact between the patient and operator, increasing the risk of transmission. New variants of COVID-19 will continue to emerge; therefore, mitigation of the virus's spread is of paramount importance. A tele-operative robotic ultrasound platform capable of performing LUS in COVID-19 infected patients may be of significant benefit, especially in low- and middle-income countries. The authors address the issues mentioned above surrounding the use of LUS in COVID-19 infected patients and the potential for extension of this technology in a resource-limited environment. Additionally, first-time application, feasibility, and safety were validated in healthy subjects. Preliminary results demonstrate that our platform allows for the successful acquisition and application of robotic LUS in humans.