A Novel Tissue Identification Framework in Cataract Surgery Using an Integrated Bioimpedance-Based Probe and Machine Learning Algorithms.

OBJECTIVE: The objective of this work was to develop and experimentally validate a bioimpedance-based framework to identify tissues in contact with the surgical instrument during cataract surgery. METHODS: This work introduces an integrated hardware and software solution based on the unique bioimpedance of different intraocular tissues. The developed hardware can be readily integrated with commonly used surgical instruments. The proposed software framework, which encompasses data acquisition and a machine-learning classifier, is fast enough to be deployed in real-time surgical interventions. The experimental protocol included bioimpedance data collected from 31 ex vivo pig eyes targeting four intraocular tissues: Iris, Cornea, Lens, and Vitreous. RESULTS: A classifier based on a support vector machine exhibited an overall accuracy of 91% across all trials. The algorithm provided substantial performance in detecting the intraocular tissues with 100% reliability and 95% sensitivity for the lens, along with 88% reliability and 94% sensitivity for the vitreous. CONCLUSION: The developed impedance-based framework demonstrated successful intraocular tissue identification. SIGNIFICANCE: Clinical implications include the ability to ensure safe operations by detecting posterior capsule rapture with 94% probability and improving surgical efficacy through lens detection with 100% reliability.

Semi-Automated Extraction of Lens Fragments via a Surgical Robot Using Semantic Segmentation of OCT Images with Deep Learning - Experimental Results in ex vivo Animal Model.

The overarching goal of this work is to demonstrate the feasibility of using optical coherence tomography (OCT) to guide a robotic system to extract lens fragments from ex vivo pig eyes. A convolutional neural network (CNN) was developed to semantically segment four intraocular structures (lens material, capsule, cornea, and iris) from OCT images. The neural network was trained on images from ten pig eyes, validated on images from eight different eyes, and tested on images from another ten eyes. This segmentation algorithm was incorporated into the Intraocular Robotic Interventional Surgical System (IRISS) to realize semi-automated detection and extraction of lens material. To demonstrate the system, the semi-automated detection and extraction task was performed on seven separate ex vivo pig eyes. The developed neural network exhibited 78.20% for the validation set and 83.89% for the test set in mean intersection over union metrics. Successful implementation and efficacy of the developed method were confirmed by comparing the preoperative and postoperative OCT volume scans from the seven experiments.

Artificial intelligence and diabetes technology: A review.

Artificial intelligence (AI) is widely discussed in the popular literature and is portrayed as impacting many aspects of human life, both in and out of the workplace. The potential for revolutionizing healthcare is significant because of the availability of increasingly powerful computational platforms and methods, along with increasingly informative sources of patient data, both in and out of clinical settings. This review aims to provide a realistic assessment of the potential for AI in understanding and managing diabetes, accounting for the state of the art in the methodology and medical devices that collect data, process data, and act accordingly. Acknowledging that many conflicting definitions of AI have been put forth, this article attempts to characterize the main elements of the field as they relate to diabetes, identifying the main perspectives and methods that can (i) affect basic understanding of the disease, (ii) affect understanding of risk factors (genetic, clinical, and behavioral) of diabetes development, (iii) improve diagnosis, (iv) improve understanding of the arc of disease (progression and personal/societal impact), and finally (v) improve treatment.

Robotic posterior capsule polishing by optical coherence tomography image guidance.

BACKGROUND: In cataract surgery, polishing of the posterior capsule (PC) can lead to improved surgical outcomes but is currently avoided due to its high-risk nature. This work developed a robotic system capable of performing PC polishing on ex vivo pig eyes using optical coherence tomography (OCT) guidance. METHODS: The lenses of five ex vivo pig eyes were extracted and a thin layer of glue deposited onto the PC. Transpupillary OCT scans of the anterior segment were used to generate a PC-polishing trajectory. During polishing, OCT B-scans tracked the tool tip and were displayed to the operator. RESULTS: Complete removal of the glue was accomplished in all five trials with no PC rupture reported. CONCLUSIONS: The feasibility of using a robotic system guided by OCT to perform PC polishing on a biological model was demonstrated. Contributions include modelling of the PC anatomy, intraoperative OCT visualization, and automated tool-tip motion with scheduled aspiration pressures.

Automated Retinal Vein Cannulation on Silicone Phantoms Using Optical-Coherence-Tomography-Guided Robotic Manipulations.

Retinal vein occlusion is one of the most common causes of vision loss, occurring when a blood clot or other obstruction occludes a retinal vein. A potential remedy for retinal vein occlusion is retinal vein cannulation, a surgical procedure that involves infusing the occluded vein with a fibrinolytic drug to restore blood flow through the vascular lumen. This work presents an image-guided robotic system capable of performing automated cannulation on silicone retinal vein phantoms. The system is integrated with an optical coherence tomography probe and camera to provide visual feedback to guide the robotic system. Through automation, the developed system targets a vein phantom to within 20 µm and automatically cannulates and infuses the vascular lumen with dyed water. The system was evaluated through 30 experimental trials and shown to be capable of performing automated cannulation of retinal vein phantoms with no reported cases of failure.

Spatial crime distribution and prediction for sporting events using social media.

Sporting events attract high volumes of people, which in turn leads to increased use of social media. In addition, research shows that sporting events may trigger violent behavior that can lead to crime. This study analyses the spatial relationships between crime occurrences, demographic, socio-economic and environmental variables, together with geo-located Twitter messages and their 'violent' subsets. The analysis compares basketball and hockey game days and non-game days. Moreover, this research aims to analyze crime prediction models using historical crime data as a basis and then introducing tweets and additional variables in their role as covariates of crime. First, this study investigates the spatial distribution of and correlation between crime and tweets during the same temporal periods. Feature selection models are applied in order to identify the best explanatory variables. Then, we apply localized kernel density estimation model for crime prediction during basketball and hockey games, and on non-game days. Findings from this study show that Twitter data, and a subset of violent tweets, are useful in building prediction models for the seven investigated crime types for home and away sporting events, and non-game days, with different levels of improvement.

Use of Mental Health Apps by Patients With Breast Cancer in the United States: Pilot Pre-Post Study.

BACKGROUND: Nearly half of the patients with breast cancer experience clinically significant mental distress within the first year of receiving their cancer diagnosis. There is an urgent need to identify scalable and cost-efficient ways of delivering empirically supported mental health interventions to patients with breast cancer. OBJECTIVE: The aim of this study was to evaluate the feasibility of in-clinic recruitment for a mobile phone app study and to evaluate the usability and preliminary impact of a suite of mental health apps (IntelliCare) with phone coaching on psychosocial distress symptoms in patients recently diagnosed with breast cancer. METHODS: This pilot study adopted a within-subject, 7-week pre-post study design. A total of 40 patients with breast cancer were recruited at a US National Cancer Institute-designated clinical cancer center. Self-reported distress (Patient Health Questionnaire-4) and mood symptoms (Patient-Reported Outcomes Measurement Information System depression and anxiety scales) were assessed at baseline and postintervention. App usability was assessed at postintervention. RESULTS: The minimum recruitment threshold was met. There was a significant decrease in general distress symptoms, as well as symptoms of depression and anxiety, from baseline to postintervention. Overall, participants reported high levels of ease of app use and learning. Scores for app usefulness and satisfaction were reinforced by some qualitative feedback suggesting that tailoring the apps more for patients with breast cancer could enhance engagement. CONCLUSIONS: There is a dire need for scalable, supportive interventions in cancer. The results from this study inform how scalable mobile phone-delivered programs with additional phone support can be used to support patients with breast cancer. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/11452.

Advanced robotic surgical systems in ophthalmology.

In this paper, an overview of advanced robotic surgical systems in ophthalmology is provided. The systems are introduced as representative examples of the degree of human vs. robotic control during surgical procedures. The details are presented on each system and the latest advancements of each are described. Future potential applications for surgical robotics in ophthalmology are discussed in detail, with representative examples provided alongside recent progress.

Large-Area Resistive Strain Sensing Sheet for Structural Health Monitoring.

Damage significantly influences response of a strain sensor only if it occurs in the proximity of the sensor. Thus, two-dimensional (2D) sensing sheets covering large areas offer reliable early-stage damage detection for structural health monitoring (SHM) applications. This paper presents a scalable sensing sheet design consisting of a dense array of thin-film resistive strain sensors. The sensing sheet is fabricated using flexible printed circuit board (Flex-PCB) manufacturing process which enables low-cost and high-volume sensors that can cover large areas. The lab tests on an aluminum beam showed the sheet has a gauge factor of 2.1 and has a low drift of 1.5 µ ϵ / d a y . The field test on a pedestrian bridge showed the sheet is sensitive enough to track strain induced by the bridge's temperature variations. The strain measured by the sheet had a root-mean-square (RMS) error of 7 µ ϵ r m s compared to a reference strain on the surface, extrapolated from fiber-optic sensors embedded within the bridge structure. The field tests on an existing crack showed that the sensing sheet can track the early-stage damage growth, where it sensed 600 µ ϵ peak strain, whereas the nearby sensors on a damage-free surface did not observe significant strain change.

A robotic system for telementoring and training in laparoscopic surgery.

A laparoscopic surgical training system, the LapaRobot, is introduced. The system is composed of an expert station and a trainee station connected through the Internet. Embedded actuators allow the trainee station to be driven by an expert surgeon so that a trainee learns proper technique through physical feedback. The surgical-tool trajectory and video feed can be recorded and later "played back" to a trainee to hone operative skills through guided repetition without the need for expert supervision. The system is designed to create a high-fidelity approximation of the intracorporeal workspace, incorporate commercially available surgical instruments, and provide a wealth of high-resolution data for quantitative analysis and feedback. Experimental evaluation demonstrated a 55% improvement in surgical performance with use of our system. In this paper, we introduce the details of the design and fabrication of the LapaRobot, illustrate the mechatronics and software-control schemes, and evaluate the system in a study.

Semiautomated optical coherence tomography-guided robotic surgery for porcine lens removal.

PURPOSE: To evaluate semiautomated surgical lens extraction procedures using the optical coherence tomography (OCT)-integrated Intraocular Robotic Interventional Surgical System. SETTING: Stein Eye Institute and Department of Mechanical and Aerospace Engineering, University of California, Los Angeles, USA. DESIGN: Experimental study. METHODS: Semiautomated lens extraction was performed on postmortem pig eyes using a robotic platform integrated with an OCT imaging system. Lens extraction was performed using a series of automated steps including robot-to-eye alignment, irrigation/aspiration (I/A) handpiece insertion, anatomic modeling, surgical path planning, and I/A handpiece navigation. Intraoperative surgical supervision and human intervention were enabled by real-time OCT image feedback to the surgeon via a graphical user interface. Manual preparation of the pig-eye models, including the corneal incision and capsulorhexis, was performed by a trained cataract surgeon before the semiautomated lens extraction procedures. A scoring system was used to assess surgical complications in a postoperative evaluation. RESULTS: Complete lens extraction was achieved in 25 of 30 eyes. In the remaining 5 eyes, small lens pieces (≤1.0 mm3) were detected near the lens equator, where transpupillary OCT could not image. No posterior capsule rupture or corneal leakage occurred. The mean surgical duration was 277 seconds ± 42 (SD). Based on a 3-point scale (0 = no damage), damage to the iris was 0.33 ± 0.20, damage to the cornea was 1.47 ± 0.20 (due to tissue dehydration), and stress at the incision was 0.97 ± 0.11. CONCLUSIONS: No posterior capsule rupture was reported. Complete lens removal was achieved in 25 trials without significant surgical complications. Refinements to the procedures are required before fully automated lens extraction can be realized.

The Performance of Patient-Worn Actigraphy Devices to Measure Recovery after Breast Reconstruction.

INTRODUCTION: Annually, over 250,000 women are diagnosed with breast cancer with over one-third undergoing mastectomy and contemplating reconstruction. Surgical breast reconstructive options vary in post-operative recovery, yet with a paucity of objective data to inform women of their expected recovery after flap or implant-based reconstruction. As a result, patient decision-making is based primarily on surgeon preference and subjective data regarding perceived invasiveness of surgical options. This study aims to identify recovery outcomes of interest to breast cancer patients and to determine the feasibility of objectively measuring patient recovery after mastectomy and reconstruction using patient-worn actigraphy devices. METHODS: Three survivorship focus groups for patients after mastectomy with and without reconstruction were used to identify recovery outcomes they considered relevant. Cloud storage systems and actigraphy devices were piloted to determine performance. Actigraphy devices were worn by patients peri-operatively to measure post-operative sleep quality and steps taken, normalized to individual patient pre-operative control data. RESULTS: Focus groups identified sleep quality, return to activity (measurable with actigraphy), and driving as variables impacting surgical decision-making. We prospectively measured outcomes for four women undergoing immediate pre-pectoral tissue expander placement and four women undergoing immediate free flap reconstruction. Actigraphy data demonstrated an initial decrease in activity, increase in sleep variability and increased heart rate that approached the patients' pre-operative normalized data as they recovered over time. CONCLUSIONS: These data demonstrate that actigraphy data would be of interest to patients making breast reconstruction decisions and that the data can be successfully collected to inform decision-making.

Use of Mental Health Apps by Breast Cancer Patients and Their Caregivers in the United States: Protocol for a Pilot Pre-Post Study.

BACKGROUND: Over one-third of cancer patients experience clinically significant mental distress, and distress in caregivers can exceed that of the cancer patients for whom they care. There is an urgent need to identify scalable and cost-efficient ways of delivering mental health interventions to cancer patients and their loved ones. OBJECTIVE: The aim of this study is to describe the protocol to pilot a mobile app-based mental health intervention in breast cancer patients and caregivers. METHODS: The IntelliCare mental health apps are grounded in evidence-based research in psychology. They have not been examined in cancer populations. This pilot study will adopt a within-subject, pre-post study design to inform a potential phase III randomized controlled trial. A target sample of 50 individuals (with roughly equal numbers of patients and caregivers) at least 18 years of age and fluent in English will be recruited at a US National Cancer Institute designated clinical cancer center. Consent will be obtained in writing and a mobile phone will be provided if needed. Self-report surveys assessing mental health outcomes will be administered at a baseline session and after a 7-week intervention. Before using the apps, participants will receive a 30-min coaching call to explain their purpose and function. A 10-min coaching call 3 weeks later will check on user progress and address questions or barriers to use. Self-report and semistructured interviews with participants at the end of the study period will focus on user experience and suggestions for improving the apps and coaching in future studies. RESULTS: This study is ongoing, and recruitment will be completed by the end of 2018. CONCLUSIONS: Results from this study will inform how scalable mobile phone-delivered programs can be used to support breast cancer patients and their loved ones. TRIAL REGISTRATION: ClinicalTrials.gov NCT03488745; https://clinicaltrials.gov/ct2/show/NCT03488745. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/11452.

Intraocular robotic interventional surgical system (IRISS): Semi-automated OCT-guided cataract removal.

BACKGROUND: With the development of laser-assisted platforms, the outcomes of cataract surgery have been improved by automating several procedures. The cataract-extraction step continues to be manually performed, but due to deficiencies in sensing capabilities, surgical complications such as posterior capsule rupture and incomplete cataract removal remain. METHODS: An optical coherence tomography (OCT) system is integrated into our intraocular robotic interventional surgical system (IRISS) robot. The OCT images are used for preoperative planning and intraoperative intervention in a series of automated procedures. Real-time intervention allows surgeons to evaluate the progress and override the operation. RESULTS: The developed system was validated by performing lens extraction on 30 postmortem pig eyes. Complete lens extraction was achieved on 25 eyes, and "almost complete" extraction was achieved on the remainder due to an inability to image small lens particles behind the iris. No capsule rupture was found. CONCLUSION: The IRISS successfully demonstrated semiautomated OCT-guided lens removal with real-time supervision and intervention.

Strain Transfer for Optimal Performance of Sensing Sheet.

Sensing sheets based on Large Area Electronics (LAE) and Integrated Circuits (ICs) are novel sensors designed to enable reliable early-stage detection of local unusual structural behaviors. Such a device consists of a dense array of strain sensors, patterned onto a flexible polyimide substrate along with associated electronics. Previous tests performed on steel specimens equipped with sensing sheet prototypes and subjected to fatigue cracking pointed to a potential issue: individual sensors that were on or near a crack would immediately be damaged by the crack, thereby rendering them useless in assessing the size of the crack opening or to monitor future crack growth. In these tests, a stiff adhesive was used to bond the sensing sheet prototype to the steel specimen. Such an adhesive provided excellent strain transfer, but it also caused premature failure of individual sensors within the sheet. Therefore, the aim of this paper is to identify an alternative adhesive that survives minor damage, yet provides strain transfer that is sufficient for reliable early-stage crack detection. A sensor sheet prototype is then calibrated for use with the selected adhesive.

Author Correction to: Dynamic Scheduling for Veterans Health Administration Patients Using Geospatial Dynamic Overbooking.

The original version of this article unfortunately contained a mistake. The name of Matthew Gerber was incorrectly spelled as Mathew Gerber. The correct spelling is now presented correctly in this correction article.

Assessment of Circulating Tumor Cells as a Predictive Biomarker of Histology in Women With Suspected Ovarian Cancer.

BACKGROUND: The clinical assessment of circulating tumor cells (CTCs) as a blood-based biomarker is FDA-approved for use in breast, colorectal, and prostate cancers. The objective of this prospective clinical study was to determine whether pretreatment CTCs are a useful diagnostic biomarker in women with complex pelvic masses. METHODS: Whole blood was collected from 49 women with newly diagnosed pelvic masses. The presence of CTCs was compared between women with and without ovarian cancer histopathologic diagnosis after surgery using a Chi-squared test. RESULTS: CTCs were absent in those with benign disease (0/14), present in 17% (5/29) of patients with a histologic diagnosis of ovarian carcinoma, and present in 80% (4/5) of patients with ovarian metastases from other cancers (P = 0.001). All 5 women with ovarian cancer who had CTCs present presented stage III or IV of the disease (P = 0.13). CONCLUSIONS: CTCs were more prevalent in patients with metastases to the ovary than in primary ovarian carcinomas.

Intraocular robotic interventional surgical system (IRISS): Mechanical design, evaluation, and master-slave manipulation.

BACKGROUND: Since the advent of robotic-assisted surgery, the value of using robotic systems to assist in surgical procedures has been repeatedly demonstrated. However, existing technologies are unable to perform complete, multi-step procedures from start to finish. Many intraocular surgical steps continue to be manually performed. METHODS: An intraocular robotic interventional surgical system (IRISS) capable of performing various intraocular surgical procedures was designed, fabricated, and evaluated. Methods were developed to evaluate the performance of the remote centers of motion (RCMs) using a stereo-camera setup and to assess the accuracy and precision of positioning the tool tip using an optical coherence tomography (OCT) system. RESULTS: The IRISS can simultaneously manipulate multiple surgical instruments, change between mounted tools using an onboard tool-change mechanism, and visualize the otherwise invisible RCMs to facilitate alignment of the RCM to the surgical incision. The accuracy of positioning the tool tip was measured to be 0.205±0.003 mm. The IRISS was evaluated by trained surgeons in a remote surgical theatre using post-mortem pig eyes and shown to be effective in completing many key steps in a variety of intraocular surgical procedures as well as being capable of performing an entire cataract extraction from start to finish. CONCLUSIONS: The IRISS represents a necessary step towards fully automated intraocular surgery and demonstrated accurate and precise master-slave manipulation for cataract removal and-through visual feedback-retinal vein cannulation.

Tractional Abnormalities of the Central Foveal Bouquet in Epiretinal Membranes: Clinical Spectrum and Pathophysiological Perspectives.

PURPOSE: To investigate the tractional alterations of the central bouquet (CB) in idiopathic epiretinal membranes (ERMs). DESIGN: Retrospective, consecutive, observational case series. METHODS: ERMs were classified according to a 4-stage grading system. The CB was defined as a circular area of approximately 100 µm composed of densely packed cones (and Müller cells) in the central fovea. Tractional abnormalities of the CB were identified with spectral-domain optical coherence tomography. Ex vivo histopathologic analysis was performed. RESULTS: In this study 263 eyes with ERMs were included. Mean follow-up was 21.2 ± 16.7 months. At baseline, tractional abnormalities of the CB were diagnosed in 58 out of 263 eyes (22%) and divided into 3 categories: cotton ball sign (defined as a fuzzy hyperreflective area between the ellipsoid zone and the interdigitation zone in the central fovea), foveolar detachment, and acquired vitelliform lesion. The presence of ectopic inner foveal layers was negatively correlated with the presence of CB tractional abnormalities (P = .002). Visual acuity was highest in association with the cotton ball sign and lowest in the acquired vitelliform lesion group. Sequential morphologic progression was identified in 7 eyes. Ex vivo histopathologic analysis illustrated characteristic staining patterns supporting a potential mechanism of traction by Müller cells in the CB. CONCLUSIONS: The cotton ball sign, foveolar detachment, and acquired vitelliform lesion may comprise a continuum in the same clinical spectrum and may represent subsequent stages of CB abnormalities. Foveal Müller cells may play an integral role in the transmission of mechanical forces to the central foveal cones.