Assessing the Brainstem Auditory Evoked Potentials in Subjects with Family History of Hypertension

Background

Hypertension (HTN) has a genetic predisposition and it also impairs microcirculation, thereby, affecting the well vascularized structures like the brainstem and causing changes in Brainstem Auditory Evoked Potentials (BAEPs).

Purpose

To find out the usefulness of BAEPs as a screening tool in apparently healthy individuals with a family history of HTN.

Methods

One hundred and ten volunteers, aged 17 to 23 years, were enrolled in the study as participants with proper consent. After excluding the subjects with existing diseases or co-morbidities (e.g. diabetes, HTN, schizophrenia, neuropathy, etc.), those on ototoxic or neurotoxic drugs, a preliminary physical examination was performed, following which BAEPs were recorded with a proper device. Statistical analysis is done with SPSS 2016 software using the chi-square test.

Results

A consistent distortion in the inter-peak latency of III-V waves is noted when a family history of HTN is present in either parent or maternal grandparents. Other statistically significant findings are present in V/I% (HTN in mother), wave I (HTN in paternal grandfather), wave III (HTN in maternal grandfather), and inter-peak latency I-V (HTN in maternal grandmother).

Conclusion

BAEP may be used as a screening tool in individuals with a family history of HTN with supportive evidence from further studies in the near future.

Scapholunate Ligament Rupture and Coincident Fracture Proximal Pole Scaphoid Presenting Late with Osteonecrosis: A Rare Case Report with Unique Management

CASE

A 29-year-old young active man with ununited necrosed proximal fifth of scaphoid with chronic scapholunate ligament disruption was managed by excision of proximal pole fragment and interosseous scapholunate reconstruction using modified Brunelli triple ligament tenodesis technique with satisfying outcome at 6 months and return to sports instructor job by the end of 1 year.

CONCLUSION

Meticulous understanding and algorithmic itemwise approach of injury components can lead to optimal management of complex unstable wrist injuries such as scapholunate dissociation. To the best of our knowledge, this is the first report on excision of proximal pole of scaphoid coupled with scapholunate ligament reconstruction.

Assessing the Effect of Augmented Reality on Procedural Outcomes During Ultrasound-Guided Vascular Access

OBJECTIVE

Augmented reality devices are increasingly accepted in health care, though most applications involve education and pre-operative planning. A novel augmented reality ultrasound application, HoloUS, was developed for the Microsoft HoloLens 2 to project real-time ultrasound images directly into the user's field of view. In this work, we assessed the effect of using HoloUS on vascular access procedural outcomes.

METHODS

A single-center user study was completed with participants with (N = 22) and without (N = 12) experience performing ultrasound-guided vascular access. Users completed a venipuncture and aspiration task a total of four times: three times on study day 1, and once on study day 2 between 2 and 4 weeks later. Users were randomized to use conventional ultrasound during either their first or second task and the HoloUS application at all other times. Task completion time, numbers of needle re-directions, head adjustments and needle visualization rates were recorded.

RESULTS

For expert users, task completion time was significantly faster using HoloUS (11.5 s, interquartile range [IQR] = 6.5-23.5 s vs. 18.5 s, IQR = 11.0-36.5 s; p = 0.04). The number of head adjustments was significantly lower using the HoloUS app (1.0, IQR = 0.0-1.0 vs. 3.0, IQR = 1.0-5.0; p < 0.0001). No significant differences were identified in other measured outcomes.

CONCLUSION

This is the first investigation of augmented reality-based ultrasound-guided vascular access using the second-generation HoloLens. It demonstrates equivalent procedural efficiency and accuracy, with favorable usability, ergonomics and user independence when compared with traditional ultrasound techniques.

StethAid: A Digital Auscultation Platform for Pediatrics

(1) Background: Mastery of auscultation can be challenging for many healthcare providers. Artificial intelligence (AI)-powered digital support is emerging as an aid to assist with the interpretation of auscultated sounds. A few AI-augmented digital stethoscopes exist but none are dedicated to pediatrics. Our goal was to develop a digital auscultation platform for pediatric medicine. (2) Methods: We developed StethAid-a digital platform for artificial intelligence-assisted auscultation and telehealth in pediatrics-that consists of a wireless digital stethoscope, mobile applications, customized patient-provider portals, and deep learning algorithms. To validate the StethAid platform, we characterized our stethoscope and used the platform in two clinical applications: (1) Still's murmur identification and (2) wheeze detection. The platform has been deployed in four children's medical centers to build the first and largest pediatric cardiopulmonary datasets, to our knowledge. We have trained and tested deep-learning models using these datasets. (3) Results: The frequency response of the StethAid stethoscope was comparable to those of the commercially available Eko Core, Thinklabs One, and Littman 3200 stethoscopes. The labels provided by our expert physician offline were in concordance with the labels of providers at the bedside using their acoustic stethoscopes for 79.3% of lungs cases and 98.3% of heart cases. Our deep learning algorithms achieved high sensitivity and specificity for both Still's murmur identification (sensitivity of 91.9% and specificity of 92.6%) and wheeze detection (sensitivity of 83.7% and specificity of 84.4%). (4) Conclusions: Our team has created a technically and clinically validated pediatric digital AI-enabled auscultation platform. Use of our platform could improve efficacy and efficiency of clinical care for pediatric patients, reduce parental anxiety, and result in cost savings.

Technical characterisation of digital stethoscopes: towards scalable artificial intelligence-based auscultation

Digital stethoscopes can enable the development of integrated artificial intelligence (AI) systems that can remove the subjectivity of manual auscultation, improve diagnostic accuracy, and compensate for diminishing auscultatory skills. Developing scalable AI systems can be challenging, especially when acquisition devices differ and thus introduce sensor bias. To address this issue, a precise knowledge of these differences, i.e., frequency responses of these devices, is needed, but the manufacturers often do not provide complete device specifications. In this study, we reported an effective methodology for determining the frequency response of a digital stethoscope and used it to characterise three common digital stethoscopes: Littmann 3200, Eko Core, and Thinklabs One. Our results show significant inter-device variability in that the frequency responses of the three studied stethoscopes were distinctly different. A moderate intra-device variability was seen when comparing two separate units of Littmann 3200. The study highlights the need for normalisation across devices for developing successful AI-assisted auscultation and provides a technical characterisation approach as a first step to accomplish it.

Automated identification of innocent Still's murmur using a convolutional neural network

Background

Still's murmur is the most prevalent innocent heart murmur of childhood. Auscultation is the primary clinical tool to identify this murmur as innocent. Whereas pediatric cardiologists routinely perform this task, primary care providers are less successful in distinguishing Still's murmur from the murmurs of true heart disease. This results in a large number of children with a Still's murmur being referred to pediatric cardiologists.

Objectives

To develop a computer algorithm that can aid primary care providers to identify the innocent Still's murmur at the point of care, to substantially decrease over-referral.

Methods

The study included Still's murmurs, pathological murmurs, other innocent murmurs, and normal (i.e., non-murmur) heart sounds of 1,473 pediatric patients recorded using a commercial electronic stethoscope. The recordings with accompanying clinical diagnoses provided by a pediatric cardiologist were used to train and test the convolutional neural network-based algorithm.

Results

A comparative analysis showed that the algorithm using only the murmur sounds recorded at the lower left sternal border achieved the highest accuracy. The developed algorithm identified Still's murmur with 90.0% sensitivity and 98.3% specificity for the default decision threshold. The area under the receiver operating characteristic curve was 0.943.

Conclusions

Still's murmur can be identified with high accuracy with the algorithm we developed. Using this approach, the algorithm could help to reduce the rate of unnecessary pediatric cardiologist referrals and use of echocardiography for a common benign finding.

Neuromorphic Architecture Accelerated Automated Seizure Detection in Multi-Channel Scalp EEG

Epileptic focal seizures can be localized in the brain using tracer injections during or immediately after the incidence of a seizure. A real-time automated seizure detection system with minimal latency can help time the injection properly to find the seizure origin accurately. Reliable real-time seizure detection systems have not been clinically reported yet. We developed an anomaly detection-based automated seizure detection system, using scalp-electroencephalogram (EEG) data, which can be trained using a few seizure sessions, and implemented it on commercially available hardware with parallel, neuromorphic architecture—the NeuroStack. We extracted nonlinear, statistical, and discrete wavelet decomposition features, and we developed a graphical user interface and traditional feature selection methods to select the most discriminative features. We investigated Reduced Coulomb Energy (RCE) networks and K-Nearest Neighbors (k-NN) for its several advantages, such as fast learning no local minima problem. We obtained a maximum sensitivity of 91.14%±1.77% and a specificity of 98.77%±0.57% with 5 s epoch duration. The system’s latency was 12 s, which is within most seizure event windows, which last for an average duration of 60 s. Our results showed that the CD feature consumes large computation resources and excluding it can reduce the latency to 3.6 s but at the cost of lower performance 80% sensitivity and 97% specificity. We demonstrated that the proposed methodology achieves a high specificity and an acceptable sensitivity within a short delay. Our results indicated also that individual-based RCE are superior to population-based RCE. The proposed RCE networks has been compared to SVM and ANN as a baseline for comparison as they are the most common machine learning seizure detection methods. SVM and ANN-based systems were trained on the same data as RCE and K-NN with features optimized specifically for them. RCE nets are superior to SVM and ANN. The proposed model also achieves comparable performance to the state-of-the-art deep learning techniques while not requiring a sizeable database, which is often expensive to build. These numbers indicate that the system is viable as a trigger mechanism for tracer injection.

Hyperacute stroke thrombolysis via telemedicine: a multicentre study of performance, safety and clinical efficacy

OBJECTIVES

Timely thrombolysis of ischaemic stroke improves functional recovery, yet its delivery nationally is challenging due to shortages in the stroke specialist workforce and large geographical areas. One solution is remote stroke specialist input to regional centres via telemedicine. This study evaluates the usage and key metrics of performance of the East of England Stroke Telemedicine Partnership-the largest telestroke service in the UK-in providing hyperacute stroke care.

DESIGN

Prospective observational study.

SETTING

The East of England Stroke Telemedicine Partnership provides a horizontal 'hubless' model of out-of-hours hyperacute stroke care to a population of 6.2 million across a 7500 square mile semirural region.

PARTICIPANTS

All (2709) telestroke consultations between 1 January 2014 and 31 December 2019.

MAIN OUTCOME MEASURES

Thrombolysis decision, pre-thrombolysis and post-thrombolysis stroke severity (National Institutes of Health Stroke Scale, NIHSS), haemorrhagic complications, and hyperacute pathway timings.

RESULTS

Over the period, 1149 (42.4%) individuals were thrombolysed. Thrombolysis rates increased from 147/379 (38.8%) in 2014 to 225/490 (45.9%) in 2019. Median (IQR) pre-thrombolysis NIHSS was 10 (6-17), reducing to 6 (2-14) 24-hour post-thrombolysis (p<0.001). Post-thrombolysis haemorrhage occurred in 27 cases (2.3%). Over the period, median (IQR) door-to-needle time reduced from 85 (65-108) min to 68 (55-97.5) min (p<0.01), driven by improved imaging-to-needle times from 52.5 (38-72.25) min to 42 (30.5-62.5) min (p<0.01). However, the same period saw an increase in median onset-to-hospital arrival time from 77.5 (60-109.25) min to 95 (70-135) min (p<0.001).

CONCLUSIONS

The results from this large hyperacute telestroke cohort indicate two important points for clinical practice. First, telemedicine via a hubless horizontal model provides a clinically effective and safe method for delivering hyperacute stroke thrombolysis. Second, improved door-to-needle times were offset by a concerning rise in prehospital timings. These findings indicate that although telemedicine may benefit in-hospital hyperacute stroke care, improvements across the whole stroke pathway are essential.

Rapid Quality Assessment of Nonrigid Image Registration Based on Supervised Learning

When preprocedural images are overlaid on intraprocedural images, interventional procedures benefit in that more structures are revealed in intraprocedural imaging. However, image artifacts, respiratory motion, and challenging scenarios could limit the accuracy of multimodality image registration necessary before image overlay. Ensuring the accuracy of registration during interventional procedures is therefore critically important. The goal of this study was to develop a novel framework that has the ability to assess the quality (i.e., accuracy) of nonrigid multimodality image registration accurately in near real time. We constructed a solution using registration quality metrics that can be computed rapidly and combined to form a single binary assessment of image registration quality as either successful or poor. Based on expert-generated quality metrics as ground truth, we used a supervised learning method to train and test this system on existing clinical data. Using the trained quality classifier, the proposed framework identified successful image registration cases with an accuracy of 81.5%. The current implementation produced the classification result in 5.5 s, fast enough for typical interventional radiology procedures. Using supervised learning, we have shown that the described framework could enable a clinician to obtain confirmation or caution of registration results during clinical procedures.

Hybrid electromagnetic-ArUco tracking of laparoscopic ultrasound transducer in laparoscopic video

Purpose: The purpose of this work was to develop a new method of tracking a laparoscopic ultrasound (LUS) transducer in laparoscopic video by combining the hardware [e.g., electromagnetic (EM)] and the computer vision-based (e.g., ArUco) tracking methods. Approach: We developed a special tracking mount for the imaging tip of the LUS transducer. The mount incorporated an EM sensor and an ArUco pattern registered to it. The hybrid method used ArUco tracking for ArUco-success frames (i.e., frames where ArUco succeeds in detecting the pattern) and used corrected EM tracking for the ArUco-failure frames. The corrected EM tracking result was obtained by applying correction matrices to the original EM tracking result. The correction matrices were calculated in previous ArUco-success frames by comparing the ArUco result and the original EM tracking result. Results: We performed phantom and animal studies to evaluate the performance of our hybrid tracking method. The corrected EM tracking results showed significant improvements over the original EM tracking results. In the animal study, 59.2% frames were ArUco-success frames. For the ArUco-failure frames, mean reprojection errors for the original EM tracking method and for the corrected EM tracking method were 30.8 pixel and 10.3 pixel, respectively. Conclusions: The new hybrid method is more reliable than using ArUco tracking alone and more accurate and practical than using EM tracking alone for tracking the LUS transducer in the laparoscope camera image. The proposed method has the potential to significantly improve tracking performance for LUS-based augmented reality applications.

COVID-19 disparity among racial and ethnic minorities in the US: A cross sectional analysis

AIM

To analyze racial disparities in Coronavirus disease (COVID-19) cases in the United States of America and discuss possible reasons behind this inequality.

SUBJECT AND METHODS

We obtained estimated case counts of African-American, Caucasian, Native American, Asian and Hispanic individuals with coronavirus disease (COVID-19)infection through May 5, 2020, from publicly available data on state departments of health websites. We calculated race-specific fractions as the percentage of the total population and analyzed the reasons behind this disparity.

RESULTS

The incident rates of COVID-19 were higher among African Americans and among Latinos disproportionately higher than their representation in 14 states and 9 states, respectively. A similar observation was also reported for New York city. The percentage of deaths reported among African Americans was disproportionately higher than their represented share in the population in 23 out of 35 states. It was reported that 22.4% of COVID-19 deaths in the USA were African American, even though black people make up 13.4% of the USA population.

CONCLUSIONS

The analysis shows the disparity of coronavirus disease outcomes by ethnicity and race. Additional research is needed to determine the factors behind this inequality.

Preclinical evaluation of ultrasound-augmented needle navigation for laparoscopic liver ablation

PURPOSE

For laparoscopic ablation to be successful, accurate placement of the needle to the tumor is essential. Laparoscopic ultrasound is an essential tool to guide needle placement, but the ultrasound image is generally presented separately from the laparoscopic image. We aim to evaluate an augmented reality (AR) system which combines laparoscopic ultrasound image, laparoscope video, and the needle trajectory in a unified view.

METHODS

We created a tissue phantom made of gelatin. Artificial tumors represented by plastic spheres were secured in the gelatin at various depths. The top point of the sphere surface was our target, and its 3D coordinates were known. The participants were invited to perform needle placement with and without AR guidance. Once the participant reported that the needle tip had reached the target, the needle tip location was recorded and compared to the ground truth location of the target, and the difference was the target localization error (TLE). The time of the needle placement was also recorded. We further tested the technical feasibility of the AR system in vivo on a 40-kg swine.

RESULTS

The AR guidance system was evaluated by two experienced surgeons and two surgical fellows. The users performed needle placement on a total of 26 targets, 13 with AR and 13 without (i.e., the conventional approach). The average TLE for the conventional and the AR approaches was 14.9 mm and 11.1 mm, respectively. The average needle placement time needed for the conventional and AR approaches was 59.4 s and 22.9 s, respectively. For the animal study, ultrasound image and needle trajectory were successfully fused with the laparoscopic video in real time and presented on a single screen for the surgeons.

CONCLUSION

By providing projected needle trajectory, we believe our AR system can assist the surgeon with more efficient and precise needle placement.

Weakly supervised segmentation for real-time surgical tool tracking

Surgical tool tracking has a variety of applications in different surgical scenarios. Electromagnetic (EM) tracking can be utilised for tool tracking, but the accuracy is often limited by magnetic interference. Vision-based methods have also been suggested; however, tracking robustness is limited by specular reflection, occlusions, and blurriness observed in the endoscopic image. Recently, deep learning-based methods have shown competitive performance on segmentation and tracking of surgical tools. The main bottleneck of these methods lies in acquiring a sufficient amount of pixel-wise, annotated training data, which demands substantial labour costs. To tackle this issue, the authors propose a weakly supervised method for surgical tool segmentation and tracking based on hybrid sensor systems. They first generate semantic labellings using EM tracking and laparoscopic image processing concurrently. They then train a light-weight deep segmentation network to obtain a binary segmentation mask that enables tool tracking. To the authors' knowledge, the proposed method is the first to integrate EM tracking and laparoscopic image processing for generation of training labels. They demonstrate that their framework achieves accurate, automatic tool segmentation (i.e. without any manual labelling of the surgical tool to be tracked) and robust tool tracking in laparoscopic image sequences.

Awareness, Knowledge and Practices of Contraceptive Methods among Married Males of Slums of Phulwarisharif block of Patna District, Bihar

Background: Even though India was the first country to launch family planning programme, population growth rate of India is still higher. Males are often the dominant decision makers of the family. Many studies regarding contraception has been done on females but the same is lacking on males. Aims & Objectives: The aim was to assess the level of awareness and practices about the contraceptive methods and factors associated with awareness and use among the married males in slums of Phulwarisharif block of Patna. Material & Methods: A cross-sectional study was conducted among 212 married males aged 18 to 60 years over a period of 3 months in slums of Phulwarisharif, Patna. Data were collected by interview of study subjects using predesigned and pretested questionnaire. Descriptive statistics and chi-square test were applied using SPSS software. Results: Among 212 married males 91.5 % have heard of at least one contraceptive method, while only 42.45% have ever used any contraceptive method. The major source of knowledge among 194 aware participants were friends and family members (78.9%). Age, duration of marriage, number of children and position in the family were associated with level of awareness. Conclusion: Despite of high awareness about contraceptives low utilization and limited knowledge was observed among the married male participants.

GPS Laparoscopic Ultrasound: Embedding an Electromagnetic Sensor in a Laparoscopic Ultrasound Transducer

Tracking the location and orientation of a laparoscopic ultrasound (LUS) transducer is a prerequisite in many surgical visualization and navigation applications. Electromagnetic (EM) tracking is a preferred method to track an LUS transducer with an articulating imaging tip. The conventional approach to integrating EM tracking with LUS is to attach an EM sensor on the outer surface of the imaging tip (external setup), which is not ideal for routine clinical use. In this work, we embedded an EM sensor inside a standard LUS transducer. We found that ultrasound image quality and the four-way articulation function of the transducer were not affected by this sensor integration. Furthermore, we found that the tracking accuracy of our integrated transducer was comparable to that of the external setup. An animal study conducted using the developed transducer suggests that an internally embedded EM sensor is a clinically more viable approach, and may be the future of tracking an articulating LUS transducer.

Laparoscopic Liver Resection with Augmented Reality: A Preclinical Experience

INTRODUCTION

Intraoperative imaging, such as ultrasound, provides subsurface anatomical information not seen by standard laparoscopy. Currently, information from the two modalities may only be integrated in the surgeon's mind, an often distracting and inefficient task. The desire to improve intraoperative efficiency has guided the development of a novel, augmented reality (AR) laparoscopic system that integrates, in real time, laparoscopic ultrasound (LUS) images with the laparoscopic video. This study shows the initial application of this system for laparoscopic hepatic wedge resection in a porcine model.

MATERIALS AND METHODS

The AR system consists of a standard laparoscopy setup, LUS scanner, electromagnetic tracking system, and a laptop computer for image fusion. Two liver lesions created in a 40-kg swine by radiofrequency ablation (RFA) were resected using the novel AR system and under standard laparoscopy.

RESULTS

Anatomical details from the LUS were successfully fused with the laparoscopic video in real time and presented on a single screen for the surgeons. The RFA lesions created were 2.5 and 1 cm in diameter. The 2.5 cm lesion was resected under AR guidance, taking about 7 minutes until completion, while the 1 cm lesion required 3 minutes using standard laparoscopy and ultrasound. Resection margins of both lesions grossly showed noncoagulated liver parenchyma, indicating a negative-margin resection.

CONCLUSIONS

The use of our AR system in laparoscopic hepatic wedge resection in a swine provided real-time integration of ultrasound image with standard laparoscopy. With more experience and testing, this system can be used for other laparoscopic procedures.

Fast calibration of electromagnetically tracked oblique-viewing rigid endoscopes

PURPOSE

The oblique-viewing (i.e., angled) rigid endoscope is a commonly used tool in conventional endoscopic surgeries. The relative rotation between its two moveable parts, the telescope and the camera head, creates a rotation offset between the actual and the projection of an object in the camera image. A calibration method tailored to compensate such offset is needed.

METHODS

We developed a fast calibration method for oblique-viewing rigid endoscopes suitable for clinical use. In contrast to prior approaches based on optical tracking, we used electromagnetic (EM) tracking as the external tracking hardware to improve compactness and practicality. Two EM sensors were mounted on the telescope and the camera head, respectively, with considerations to minimize EM tracking errors. Single-image calibration was incorporated into the method, and a sterilizable plate, laser-marked with the calibration pattern, was also developed. Furthermore, we proposed a general algorithm to estimate the rotation center in the camera image. Formulas for updating the camera matrix in terms of clockwise and counterclockwise rotations were also developed.

RESULTS

The proposed calibration method was validated using a conventional [Formula: see text], 5-mm laparoscope. Freehand calibrations were performed using the proposed method, and the calibration time averaged 2 min and 8 s. The calibration accuracy was evaluated in a simulated clinical setting with several surgical tools present in the magnetic field of EM tracking. The root-mean-square re-projection error averaged 4.9 pixel (range 2.4-8.5 pixel, with image resolution of [Formula: see text] for rotation angles ranged from [Formula: see text] to [Formula: see text].

CONCLUSIONS

We developed a method for fast and accurate calibration of oblique-viewing rigid endoscopes. The method was also designed to be performed in the operating room and will therefore support clinical translation of many emerging endoscopic computer-assisted surgical systems.

Deformable registration of CT and cone-beam CT with local intensity matching

Cone-beam CT (CBCT) is a widely used intra-operative imaging modality in image-guided radiotherapy and surgery. A short scan followed by a filtered-backprojection is typically used for CBCT reconstruction. While data on the mid-plane (plane of source-detector rotation) is complete, off-mid-planes undergo different information deficiency and the computed reconstructions are approximate. This causes different reconstruction artifacts at off-mid-planes depending on slice locations, and therefore impedes accurate registration between CT and CBCT. In this paper, we propose a method to accurately register CT and CBCT by iteratively matching local CT and CBCT intensities. We correct CBCT intensities by matching local intensity histograms slice by slice in conjunction with intensity-based deformable registration. The correction-registration steps are repeated in an alternating way until the result image converges. We integrate the intensity matching into three different deformable registration methods, B-spline, demons, and optical flow that are widely used for CT-CBCT registration. All three registration methods were implemented on a graphics processing unit for efficient parallel computation. We tested the proposed methods on twenty five head and neck cancer cases and compared the performance with state-of-the-art registration methods. Normalized cross correlation (NCC), structural similarity index (SSIM), and target registration error (TRE) were computed to evaluate the registration performance. Our method produced overall NCC of 0.96, SSIM of 0.94, and TRE of 2.26 → 2.27 mm, outperforming existing methods by 9%, 12%, and 27%, respectively. Experimental results also show that our method performs consistently and is more accurate than existing algorithms, and also computationally efficient.

Laparoscopic stereoscopic augmented reality: toward a clinically viable electromagnetic tracking solution

The purpose of this work was to develop a clinically viable laparoscopic augmented reality (AR) system employing stereoscopic (3-D) vision, laparoscopic ultrasound (LUS), and electromagnetic (EM) tracking to achieve image registration. We investigated clinically feasible solutions to mount the EM sensors on the 3-D laparoscope and the LUS probe. This led to a solution of integrating an externally attached EM sensor near the imaging tip of the LUS probe, only slightly increasing the overall diameter of the probe. Likewise, a solution for mounting an EM sensor on the handle of the 3-D laparoscope was proposed. The spatial image-to-video registration accuracy of the AR system was measured to be [Formula: see text] and [Formula: see text] for the left- and right-eye channels, respectively. The AR system contributed 58-ms latency to stereoscopic visualization. We further performed an animal experiment to demonstrate the use of the system as a visualization approach for laparoscopic procedures. In conclusion, we have developed an integrated, compact, and EM tracking-based stereoscopic AR visualization system, which has the potential for clinical use. The system has been demonstrated to achieve clinically acceptable accuracy and latency. This work is a critical step toward clinical translation of AR visualization for laparoscopic procedures.

Technical Note: scuda: A software platform for cumulative dose assessment

PURPOSE

Accurate tracking of anatomical changes and computation of actually delivered dose to the patient are critical for successful adaptive radiation therapy (ART). Additionally, efficient data management and fast processing are practically important for the adoption in clinic as ART involves a large amount of image and treatment data. The purpose of this study was to develop an accurate and efficient Software platform for CUmulative Dose Assessment (scuda) that can be seamlessly integrated into the clinical workflow.

METHODS

scuda consists of deformable image registration (DIR), segmentation, dose computation modules, and a graphical user interface. It is connected to our image PACS and radiotherapy informatics databases from which it automatically queries/retrieves patient images, radiotherapy plan, beam data, and daily treatment information, thus providing an efficient and unified workflow. For accurate registration of the planning CT and daily CBCTs, the authors iteratively correct CBCT intensities by matching local intensity histograms during the DIR process. Contours of the target tumor and critical structures are then propagated from the planning CT to daily CBCTs using the computed deformations. The actual delivered daily dose is computed using the registered CT and patient setup information by a superposition/convolution algorithm, and accumulated using the computed deformation fields. Both DIR and dose computation modules are accelerated by a graphics processing unit.

RESULTS

The cumulative dose computation process has been validated on 30 head and neck (HN) cancer cases, showing 3.5 ± 5.0 Gy (mean±STD) absolute mean dose differences between the planned and the actually delivered doses in the parotid glands. On average, DIR, dose computation, and segmentation take 20 s/fraction and 17 min for a 35-fraction treatment including additional computation for dose accumulation.

CONCLUSIONS

The authors developed a unified software platform that provides accurate and efficient monitoring of anatomical changes and computation of actually delivered dose to the patient, thus realizing an efficient cumulative dose computation workflow. Evaluation on HN cases demonstrated the utility of our platform for monitoring the treatment quality and detecting significant dosimetric variations that are keys to successful ART.

An improved matrix separation method for characterization of ultrapure germanium (8N)

An improved matrix separation method has been described to characterize ultrapure germanium of 8N (99.999999%) purity. In this method, temperature of the reaction vessel in which in-situ generated chlorine gas reacts with germanium solid material directly is optimized to quantitatively remove Ge matrix from all its impurities. Optimized reaction temperature has been found to be 230±5°C. Recovery studies on more than 60 elements have been carried out at the optimized temperature. Recoveries of all the analytes except As, Se, Sn, Hg, Tl are found to be quantitative. The method has been examined for various amounts of Ge material and found to be suitable even for 10g of Ge sample and provides low parts per billion and trillion levels of process blanks. Determination of concentrations of impurities has been done by inductively coupled plasma quadrupole mass spectrometer (ICP-QMS) and high resolution continuum source graphite furnace atomic absorption spectrometer (HR-CS-GFAAS). In the absence of certified reference materials for ultrapure germanium, accuracy of the proposed method is established by spike recovery tests. Precision of this method is found to vary from 7% to 50% for concentrations between 4 and 0.004ngg(-1). Limits of detection (LOD) for the target analytes are found to be between 6 and 0.011ngmL(-1) or 1.8-0.003ngg(-1) for the proposed procedure. The method has been successfully applied for that characterization of ultrapure germanium material of 8N purity.

Automated Identification of Innocent Still's Murmur in Children

OBJECTIVE

Still's murmur is the most common innocent heart murmur in children. It is also the most commonly misdiagnosed murmur, resulting in a high number of unnecessary referrals to pediatric cardiologist. The purpose of this study was to develop a computer algorithm for automated identification of Still's murmur that may help reduce unnecessary referrals.

METHODS

We first developed an accurate segmentation algorithm to locate the first and the second heart sounds. Once these sounds were identified, we extracted signal features specific to Still's murmur. Subsequently, machine learning-based classifiers, artificial neural network and support vector machine, were used to identify Still's murmur.

RESULTS

We evaluated our classifiers using the jackknife method using 87 Still's murmurs and 170 non-Still's murmurs. Our algorithm identified Still's murmur accurately with 84-93% sensitivity and 91-99% specificity.

CONCLUSION

We have achieved accurate automated identification of Still's murmur while minimizing false positives. The performance of our algorithm is comparable to the rate of murmur identification by auscultation by pediatric cardiologists.

SIGNIFICANCE

To our knowledge, our solution is the first murmur classifier that focuses singularly on Still's murmur. Following further refinement and testing, the presented algorithm could reduce the number of children with Still's murmur referred unnecessarily to pediatric cardiologists.

The Utility of Cloud Computing in Analyzing GPU-Accelerated Deformable Image Registration of CT and CBCT Images in Head and Neck Cancer Radiation Therapy

The images generated during radiation oncology treatments provide a valuable resource to conduct analysis for personalized therapy, outcomes prediction, and treatment margin optimization. Deformable image registration (DIR) is an essential tool in analyzing these images. We are enhancing and examining DIR with the contributions of this paper: 1) implementing and investigating a cloud and graphic processing unit (GPU) accelerated DIR solution and 2) assessing the accuracy and flexibility of that solution on planning computed tomography (CT) with cone-beam CT (CBCT). Registering planning CTs and CBCTs aids in monitoring tumors, tracking body changes, and assuring that the treatment is executed as planned. This provides significant information not only on the level of a single patient, but also for an oncology department. However, traditional methods for DIR are usually time-consuming, and manual intervention is sometimes required even for a single registration. In this paper, we present a cloud-based solution in order to increase the data analysis throughput, so that treatment tracking results may be delivered at the time of care. We assess our solution in terms of accuracy and flexibility compared with a commercial tool registering CT with CBCT. The latency of a previously reported mutual information-based DIR algorithm was improved with GPUs for a single registration. This registration consists of rigid registration followed by volume subdivision-based nonrigid registration. In this paper, the throughput of the system was accelerated on the cloud for hundreds of data analysis pairs. Nine clinical cases of head and neck cancer patients were utilized to quantitatively evaluate the accuracy and throughput. Target registration error (TRE) and structural similarity index were utilized as evaluation metrics for registration accuracy. The total computation time consisting of preprocessing the data, running the registration, and analyzing the results was used to evaluate the system throughput. Evaluation showed that the average TRE for GPU-accelerated DIR for each of the nine patients was from 1.99 to 3.39 mm, which is lower than the voxel dimension. The total processing time for 282 pairs on an Amazon Web Services cloud consisting of 20 GPU enabled nodes took less than an hour. Beyond the original registration, the cloud resources also included automatic registration quality checks with minimal impact to timing. Clinical data were utilized in quantitative evaluations, and the results showed that the presented method holds great potential for many high-impact clinical applications in radiation oncology, including adaptive radio therapy, patient outcomes prediction, and treatment margin optimization.

The SOAR stroke score predicts hospital length of stay in acute stroke: an external validation study

AIMS

The objective of this study is to externally validate the SOAR stroke score (Stroke subtype, Oxfordshire Community Stroke Project Classification, Age and prestroke modified Rankin score) in predicting hospital length of stay (LOS) following an admission for acute stroke.

METHODS

We conducted a multi-centre observational study in eight National Health Service hospital trusts in the Anglia Stroke & Heart Clinical Network between September 2008 and April 2011. The usefulness of the SOAR stroke score in predicting hospital LOS in the acute settings was examined for all stroke and then stratified by discharge status (discharged alive or died during the admission).

RESULTS

A total of 3596 patients (mean age 77 years) with first-ever or recurrent stroke (92% ischaemic) were included. Increasing LOS was observed with increasing SOAR stroke score (p < 0.001 for both mean and median) and the SOAR stroke score of 0 had the shortest mean LOS (12 ± 20 days) while the SOAR stroke score of 6 had the longest mean LOS (26 ± 28 days). Among patients who were discharged alive, increasing SOAR stroke score had a significantly higher mean and median LOS (p < 0.001 for both mean and median) and the LOS peaked among patients with score value of 6 [mean (SD) 35 ± 31 days, median (IQR) 23 (14-48) days]. For patients who died as in-patient, there was no significant difference in mean or median LOS with increasing SOAR stroke score (p = 0.68 and p = 0.79, respectively).

CONCLUSION

This external validation study confirms the usefulness of the SOAR stroke score in predicting LOS in patients with acute stroke especially in those who are likely to survive to discharge. This provides a simple prognostic score useful for clinicians, patients and service providers.

Fabrication and characterization of medical grade polyurethane composite catheters for near-infrared imaging

Peripherally inserted central catheters (PICCs) are hollow polymeric tubes that transport nutrients, blood and medications to neonates. To determine proper PICC placement, frequent X-ray imaging of neonates is performed. Because X-rays pose severe health risks to neonates, safer alternatives are needed. We hypothesize that near infrared (NIR) polymer composites can be fabricated into catheters by incorporating a fluorescent dye (IRDye 800CW) and visualized using NIR imaging. To fabricate catheters, polymer and dye are dry mixed and pressed, sectioned, and extruded to produce hollow tubes. We analyzed surface roughness, stiffness, dye retention, NIR contrast intensity, and biocompatibility. The extrusion process did not significantly alter the mechanical properties of the polymer composites. Over a period of 23 days, only 6.35 ± 5.08% dye leached out of catheters. The addition of 0.025 wt% dye resulted in a 14-fold contrast enhancement producing clear PICC images at 1 cm under a tissue equivalent. The addition of IRDye 800CW did not alter the biocompatibility of the polymer and did not increase adhesion of cells to the surface. We successfully demonstrated that catheters can be imaged without the use of harmful radiation and still maintain the same properties as the unaltered medical grade equivalent.

Application of single-image camera calibration for ultrasound augmented laparoscopic visualization

Accurate calibration of laparoscopic cameras is essential for enabling many surgical visualization and navigation technologies such as the ultrasound-augmented visualization system that we have developed for laparoscopic surgery. In addition to accuracy and robustness, there is a practical need for a fast and easy camera calibration method that can be performed on demand in the operating room (OR). Conventional camera calibration methods are not suitable for the OR use because they are lengthy and tedious. They require acquisition of multiple images of a target pattern in its entirety to produce satisfactory result. In this work, we evaluated the performance of a single-image camera calibration tool (rdCalib; Percieve3D, Coimbra, Portugal) featuring automatic detection of corner points in the image, whether partial or complete, of a custom target pattern. Intrinsic camera parameters of a 5-mm and a 10-mm standard Stryker^® laparoscopes obtained using rdCalib and the well-accepted OpenCV camera calibration method were compared. Target registration error (TRE) as a measure of camera calibration accuracy for our optical tracking-based AR system was also compared between the two calibration methods. Based on our experiments, the single-image camera calibration yields consistent and accurate results (mean TRE = 1.18 ± 0.35 mm for the 5-mm scope and mean TRE = 1.13 ± 0.32 mm for the 10-mm scope), which are comparable to the results obtained using the OpenCV method with 30 images. The new single-image camera calibration method is promising to be applied to our augmented reality visualization system for laparoscopic surgery.

Thrombolysis delivery by a regional telestroke network--experience from the U.K. National Health Service

Background

The majority of established telestroke services are based on “hub‐and‐spoke” models for providing acute clinical assessment and thrombolysis. We report results from the first year of the successful implementation of a locally based telemedicine network, without the need of 1 or more hub hospitals, across a largely rural landscape.

Methods and Results

Following a successful pilot phase that demonstrated safety and feasibility, the East of England telestroke project was rolled out across 7 regional hospitals, covering an area of 7500 square miles and a population of 5.6 million to enable out‐of‐hours access to thrombolysis. Between November 2010 and November 2011, 142 telemedicine consultations were recorded out‐of‐hours. Seventy‐four (52.11%) cases received thrombolysis. Median (IQR) onset‐to‐needle and door‐to‐needle times were 169 (141.5 to 201.5) minutes and 94 (72 to 113.5) minutes, respectively. Symptomatic hemorrhage rate was 7.3% and stroke mimic rate was 10.6%.

Conclusions

We demonstrate the safety and effectiveness of a horizontal networking approach for stroke telemedicine, which may be applicable to areas where traditional “hub‐and‐spoke” models may not be geographically feasible.

Stereoscopic augmented reality for laparoscopic surgery

BACKGROUND

Conventional laparoscopes provide a flat representation of the three-dimensional (3D) operating field and are incapable of visualizing internal structures located beneath visible organ surfaces. Computed tomography (CT) and magnetic resonance (MR) images are difficult to fuse in real time with laparoscopic views due to the deformable nature of soft-tissue organs. Utilizing emerging camera technology, we have developed a real-time stereoscopic augmented-reality (AR) system for laparoscopic surgery by merging live laparoscopic ultrasound (LUS) with stereoscopic video. The system creates two new visual cues: (1) perception of true depth with improved understanding of 3D spatial relationships among anatomical structures, and (2) visualization of critical internal structures along with a more comprehensive visualization of the operating field.

METHODS

The stereoscopic AR system has been designed for near-term clinical translation with seamless integration into the existing surgical workflow. It is composed of a stereoscopic vision system, a LUS system, and an optical tracker. Specialized software processes streams of imaging data from the tracked devices and registers those in real time. The resulting two ultrasound-augmented video streams (one for the left and one for the right eye) give a live stereoscopic AR view of the operating field. The team conducted a series of stereoscopic AR interrogations of the liver, gallbladder, biliary tree, and kidneys in two swine.

RESULTS

The preclinical studies demonstrated the feasibility of the stereoscopic AR system during in vivo procedures. Major internal structures could be easily identified. The system exhibited unobservable latency with acceptable image-to-video registration accuracy.

CONCLUSIONS

We presented the first in vivo use of a complete system with stereoscopic AR visualization capability. This new capability introduces new visual cues and enhances visualization of the surgical anatomy. The system shows promise to improve the precision and expand the capacity of minimally invasive laparoscopic surgeries.

The SOAR stroke score predicts inpatient and 7-day mortality in acute stroke

BACKGROUND AND PURPOSE

An accurate prognosis is useful for patients, family, and service providers after acute stroke.

METHODS

We validated the Stroke subtype, Oxfordshire Community Stroke Project Classification, Age, and prestroke Rankin stroke score in predicting inpatient and 7-day mortality using data from 8 National Health Service hospital trusts in the Anglia Stroke and Heart Clinical Network between September 2008 and April 2011.

RESULTS

A total of 3547 stroke patients (ischemic, 92%) were included. An incremental increase of inpatient and 7-day mortality was observed with increase in Stroke subtype, Oxfordshire Community Stroke Project Classification, Age, and prestroke Rankin stroke score. Using a cut-off of ≥3, the area under the receiver operator curves values for inpatient and 7-day mortality were 0.80 and 0.82, respectively.

CONCLUSIONS

A simple score based on 4 easily obtainable variables at the point of care may potentially help predict early stroke mortality.

Three-dimensional direct laryngoscopy and bronchoscopy: enhanced visualization of the airway

IMPORTANCE

This is the first description of 3-dimensional (3D) pediatric airway endoscopy in the otolaryngology literature detailing the superior visualization with this technology. Ultimately, enhanced optics may further improve the treatment of airway pathology.

OBJECTIVE

To report the first case series examining the use of 3D direct laryngoscopy and bronchoscopy (DLB) in the diagnosis and management of laryngotracheal pathology.

DESIGN

Case series.

SETTING

Tertiary care pediatric hospital.

PARTICIPANTS

Three patients underwent both telescopic 2-dimensional (2D) and 3D DLB for comparison purposes: a 12-year-old boy for visualization of complete tracheal rings, a 23-year-old man for dilation of tracheal stenosis, and a 4-month-old boy for resection of subglottic cysts.

MAIN OUTCOME MEASURES

Enhanced visualization of laryngotracheal pathology and facilitated endoscopic surgery.

RESULTS

To our knowledge, this is the first case series in the otolaryngology literature examining the use of 3D DLB for the resection of subglottic cysts, dilation of tracheal stenosis, and visualization of complete tracheal rings. We believe that the 3D view offers qualitatively improved depth perception, accuracy of balloon placement, and appraisal of subglottic cyst resection margins.

CONCLUSIONS AND RELEVANCE

This emerging technology has vast potential for improving endoscopy, surgical precision in airway interventions, tissue preservation, and methods of teaching. More research is needed in this area regarding the benefits and advantages of 3D compared with 2D endoscopy.

Modeling the polydomain-monodomain transition of liquid crystal elastomers

We study the mechanism of the polydomain-monodomain transition in liquid crystalline elastomers at the molecular scale. A coarse-grained model is proposed in which mesogens are described as ellipsoidal particles. Molecular dynamics simulations are used to examine the transition from a polydomain state to a monodomain state in the presence of uniaxial strain. Our model demonstrates soft elasticity, similar to that exhibited by side-chain elastomers in the literature. By analyzing the growth dynamics of nematic domains during uniaxial extension, we provide direct evidence that at a molecular level the polydomain-monodomain transition proceeds through cluster rotation and domain growth.

Isotropic-nematic phase transition in the Lebwohl-Lasher model from density of states simulations

Density of states Monte Carlo simulations have been performed to study the isotropic-nematic (IN) transition of the Lebwohl-Lasher model for liquid crystals. The IN transition temperature was calculated as a function of system size using expanded ensemble density of states simulations with histogram reweighting. The IN temperature for infinite system size was obtained by extrapolation of three independent measures. A subsequent analysis of the kinetics in the model showed that the transition occurs via spinodal decomposition through aggregation of clusters of liquid crystal molecules.

Precise measurement of the W-boson mass with the CDF II detector

We have measured the W-boson mass M(W) using data corresponding to 2.2  fb(-1) of integrated luminosity collected in pp collisions at sqrt[s] = 1.96  TeV with the CDF II detector at the Fermilab Tevatron collider. Samples consisting of 470,126 W → eν candidates and 624,708 W → μν candidates yield the measurement M(W) = 80,387 ± 12(stat.) ± 15(syst.) = 80,387 ± 19  MeV/c2. This is the most precise measurement of the W-boson mass to date and significantly exceeds the precision of all previous measurements combined.

Status of copper and magnesium levels in diabetic nephropathy cases: a case-control study from South India

Diabetic nephropathy is a complication of diabetes mellitus. This present study investigates the status of copper and magnesium in diabetic nephropathy cases to establish a possible relation. Forty patients of diabetic nephropathy participated in the study as cases. Forty age- and sex-matched healthy individuals served as controls. Blood samples were collected from both cases and controls for determination of FBS, PPBS, HbA1c, microalbumin, copper, and magnesium levels. The mean concentrations of FBS, PPBS, HbA1c, and microalbumin of cases were significantly higher than that of controls. The mean magnesium levels of cases (1.60 ± 0.32 meq/L) were significantly lower than controls 2.14 ± 0.16 meq/L (p < 0.05). But the mean copper levels of cases, 165.42 ± 5.71 μg/dl, shows no significant difference with controls, 166.6 ± 5.48 μg/dl, (p > 0.05).The findings in the present study suggest that hypomagnesemia may be linked with development of diabetic nephropathy.