Search

Due to loss of tactile feedback the assessment of tumor margins during robotic surgery is based only on visual inspection, which is neither significantly sensitive nor specific. Here we demonstrate time-resolved fluorescence spectroscopy (TRFS) as a novel technique to complement the visual inspection of oral cancers during transoral robotic surgery (TORS) in real-time and without the need for exogenous contrast agents. TRFS enables identification of cancerous tissue by its distinct autofluorescence signature that is associated with the alteration of tissue structure and biochemical profile. A prototype TRFS instrument was integrated synergistically with the da Vinci Surgical robot and the combined system was validated in swine and human patients. Label-free and real-time assessment and visualization of tissue biochemical features during robotic surgery procedure, as demonstrated here, not only has the potential to improve the intraoperative decision making during TORS but also other robotic procedures without modification of conventional clinical protocols.

Patients undergoing gynecological procedures suffer from lasting side effects due to intraoperative nerve damage. Small, delicate nerves with complex and nonuniform branching patterns in the female pelvic neuroanatomy make nerve-sparing efforts during standard gynecological procedures such as hysterectomy, cystectomy, and colorectal cancer resection difficult, and thus many patients are left with incontinence and sexual dysfunction. Herein, a near-infrared (NIR) fluorescent nerve-specific contrast agent, LGW08-35, that is spectrally compatible with clinical fluorescence guided surgery (FGS) systems is formulated and characterized for rapid implementation for nerve-sparing gynecologic surgeries. The toxicology, pharmacokinetics (PK), and pharmacodynamics (PD) of micelle formulated LGW08-35 are examined, enabling the determination of the optimal imaging doses and time points, blood and tissue uptake parameters, and maximum tolerated dose (MTD). Application of the formulated fluorophore to imaging of female rat and swine pelvic neuroanatomy validates the continued clinical translation and use for real-time identification of important nerves such as the femoral, sciatic, lumbar, iliac, and hypogastric nerves. Further development of LGW08-35 for clinical use will unlock a valuable tool for surgeons in direct visualization of important nerves and contribute to the ongoing characterization of the female pelvic neuroanatomy to eliminate the debilitating side effects of nerve damage during gynecological procedures., (© 2023 Wiley‐VCH GmbH.)

Visual Parameter Space Analysis (VPSA) enables domain scientists to explore input-output relationships of computational models. Existing VPSA applications often feature multi-view visualizations designed by visualization experts for a specific scenario, making it hard for domain scientists to adapt them to their problems without professional help. We present RSVP, the Rapid Suggestive Visualization Prototyping system encoding VPSA knowledge to enable domain scientists to prototype custom visualization dashboards tailored to their specific needs. The system implements a task-oriented, multi-view visualization recommendation strategy over a visualization design space optimized for VPSA to guide users in meeting their analytical demands. We derived the VPSA knowledge implemented in the system by conducting an extensive meta design study over the body of work on VPSA. We show how this process can be used to perform a data and task abstraction, extract a common visualization design space, and derive a task-oriented VisRec strategy. User studies indicate that the system is user-friendly and can uncover novel insights.

We aim to comprehensively identify typical life-spanning trajectories and critical events that impact patients' hospital utilization and mortality. We use a unique dataset containing 44 million records of almost all inpatient stays from 2003 to 2014 in Austria to investigate disease trajectories. We develop a new, multilayer disease network approach to quantitatively analyze how cooccurrences of two or more diagnoses form and evolve over the life course of patients. Nodes represent diagnoses in age groups of ten years; each age group makes up a layer of the comorbidity multilayer network. Inter-layer links encode a significant correlation between diagnoses (p < 0.001, relative risk > 1.5), while intra-layers links encode correlations between diagnoses across different age groups. We use an unsupervised clustering algorithm for detecting typical disease trajectories as overlapping clusters in the multilayer comorbidity network. We identify critical events in a patient's career as points where initially overlapping trajectories start to diverge towards different states. We identified 1260 distinct disease trajectories (618 for females, 642 for males) that on average contain 9 (IQR 2-6) different diagnoses that cover over up to 70 years (mean 23 years). We found 70 pairs of diverging trajectories that share some diagnoses at younger ages but develop into markedly different groups of diagnoses at older ages. The disease trajectory framework can help us to identify critical events as specific combinations of risk factors that put patients at high risk for different diagnoses decades later. Our findings enable a data-driven integration of personalized life-course perspectives into clinical decision-making., (© 2024. The Author(s).)

Background: There are no consensus guidelines regarding the use of percutaneous needle biopsy for the diagnosis of soft tissue and bone tumors. The aim of this study was to understand the efficacy of image-guided percutaneous biopsy for pediatric patients with soft tissue and bony masses, the role of intraoperative image guidance, and diagnostic accuracy., Patients and Methods: A retrospective institutional chart review was performed on patients who underwent percutaneous biopsy of soft tissue or bone tumors between 2007 and 2017. Data collected included preoperative imaging, type of biopsy, demographics, insurance status, number of samples taken, and pathologic results., Results: One hundred forty-one children and young adults underwent 169 biopsies. Female patients received 48.2% of biopsies. The mean age was 14.3 ± 7.0 years. Core needle biopsies made up 89.4% of procedures, while 10.6% were fine needle aspirate. The mean number of samples per patient was 3.6 ± 2.5. All patients had imaging guidance, with computed tomography used in 44.7% of patients, 9.9% using fluoroscopy, 7.1% using ultrasound for guidance, and 53 (37.6%) patients had more than one modality. Diagnostic specimens were obtained in 97.9% of biopsies. The most common overall pathology was osteoid osteoma. The most common malignant tumors were osteosarcoma and Ewing's sarcoma., Conclusion: Image-guided percutaneous biopsy is a safe and effective method of obtaining accurate tissue samples in children and young adults with soft tissue or bone masses., Level of Evidence: Level 4-Study of diagnostic test., (© 2023. Society of Surgical Oncology.)

Surgery is the preferred treatment option for most solid tumors. However, inaccurate detection of cancer borders leads to either incomplete removal of malignant cells or excess excision of healthy tissue. While fluorescent contrast agents and imaging systems improve tumor visualization, they can suffer from low signal-to-background and are prone to technical artifacts. Ratiometric imaging has the potential to eliminate many of these issues such as uneven probe distribution, tissue autofluorescence, and changes in positioning of the light source. Here, we describe a strategy to convert quenched fluorescent probes into ratiometric contrast agents. Conversion of the cathepsin-activated probe, 6QC-Cy5, into a two-fluorophore probe, 6QC-RATIO, significantly improved signal-to-background in vitro and in a mouse subcutaneous breast tumor model. Tumor detection sensitivity was further enhanced using a dual-substrate AND-gate ratiometric probe, Death-Cat-RATIO, that fluoresces only after orthogonal processing by multiple tumor-specific proteases. We also designed and built a modular camera system that was coupled to the FDA-approved da Vinci Xi robot, to enable real-time imaging of ratiometric signals at video frame rates compatible with surgical workflows. Our results demonstrate that ratiometric camera systems and imaging probes have the potential to be clinically implemented to improve surgical resection of many types of cancer., Competing Interests: The authors declare no competing financial interest., (© 2023 The Authors. Published by American Chemical Society.)

The prevalence of diseases often varies substantially from region to region. Besides basic demographic properties, the factors that drive the variability of each prevalence are to a large extent unknown. Here we show how regional prevalence variations in 115 different diseases relate to demographic, socio-economic, environmental factors and migratory background, as well as access to different types of health services such as primary, specialized and hospital healthcare. We have collected regional data for these risk factors at different levels of resolution; from large regions of care ( Versorgungsregion ) down to a 250 by 250 m square grid. Using multivariate regression analysis, we quantify the explanatory power of each independent variable in relation to the regional variation of the disease prevalence. We find that for certain diseases, such as acute heart conditions, diseases of the inner ear, mental and behavioral disorders due to substance abuse, up to 80% of the variance can be explained with these risk factors. For other diagnostic blocks, such as blood related diseases, injuries and poisoning however, the explanatory power is close to zero. We find that the time needed to travel from the inhabited center to the relevant hospital ward often contributes significantly to the disease risk, in particular for diabetes mellitus. Our results show that variations in disease burden across different regions can for many diseases be related to variations in demographic and socio-economic factors. Furthermore, our results highlight the relative importance of access to health care facilities in the treatment of chronic diseases like diabetes., (© 2023 Published by Elsevier Ltd.)

Modelling the dynamics of a growing financial environment is a complex task that requires domain knowledge, expertise and access to heterogeneous information types. Such information can stem from several sources at different scales, complicating the task of forming a holistic impression of the financial landscape, especially in terms of the economical relationships between firms. Bringing this scattered information into a common context is, therefore, an essential step in the process of obtaining meaningful insights about the state of an economy. In this paper, we present Sabrina 2.0 , a Visual Analytics (VA) approach for exploring financial data across different scales, from individual firms up to nation-wide aggregate data. Our solution is coupled with a pipeline for the generation of firm-to-firm financial transaction networks, fusing information about individual firms with sector-to-sector transaction data and domain knowledge on macroscopic aspects of the economy. Each network can be created to have multiple instances to compare different scenarios. We collaborated with experts from finance and economy during the development of our VA solution, and evaluated our approach with seven domain experts across industry and academia through a qualitative insight-based evaluation. The analysis shows how Sabrina 2.0 enables the generation of insights, and how the incorporation of transaction models assists users in their exploration of a national economy., (© 2022 The Authors. Computer Graphics Forum published by Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd.)

Robotic surgery bedside assistants play an important role in robotic procedures by performing intra-corporeal tasks while accommodating the physical presence of the robot. We hypothesized that an augmented reality headset enabling 3D intra-corporeal vision while facing the surgical field could decrease time and improve accuracy of robotic bedside tasks. Bedside assistants (one physician assistant, one medical student, three surgical trainees, and two attending surgeons) performed validated tasks within a mock abdominal cavity with a surgical robot docked. Tasks were performed with a bedside monitor providing 2D or 3D vision, or an optical see-through head-mounted augmented reality device with 2D or 3D vision. The effect of augmented reality device resolution on performance was also evaluated. For the simplest task of touching a straw, performance was generally high, regardless of mode of visualization. With more complex tasks, including stapling and pulling a ring along a path, 3D augmented reality decreased time and number of errors per task. 3D augmented reality allowed the physician assistant to perform at the level of an attending surgeon using 3D augmented reality (p = 0.08). All participants had improved times for the ring path task with better resolution (lower resolution 23 ± 11 s vs higher resolution 14 ± 4 s, p = 0.002). 3D augmented reality vision with high resolution decreased time and improved accuracy of more complex tasks, enabling a less experienced robotic surgical bedside assistant to function similar to attending surgeons. These data warrant further study with additional complex tasks and bedside assistants at various levels of training., (© 2021. The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.)

Background: Identifying ground glass opacities (GGOs) is challenging during robot-assisted thoracic surgery (RATS). Intraoperative molecular imaging (IMI) using tumor-targeted fluorescent tracers may address this clinical problem, but has never been evaluated in RATS. In a pilot study, we sought to determine whether IMI during RATS (RIMI) can localize GGOs., Methods: Ten patients with a cT1 GGO were enrolled. Prior to resection, participants received a folate-receptor targeted fluorescent tracer (OTL38). During RATS, a white-light robotic scope was utilized to identify tumors. RIMI was then conducted using a RATS thoracoscope with a wavelength-specific camera. Finally, a video-assisted thoracic surgery (VATS) thoracoscope designed to detect OTL38 was used as a control to compare to RIMI. The lesions were then resected under RIMI guidance., Results: By white-light robotic scope, 7/10 (70%) GGOs were visually identifiable by pleuroparenchymal distortions. RIMI identified tumor-specific fluorescence in all (100%) subjects. RIMI clearly located the three nodules that could not be seen by robotic white-light imaging. The mean fluorescence intensity (MFI) of tumors was 99.48 arbitrary units (A.U.) (IQR, 75.72-130.49 A.U.), which was significantly higher than background tissue with mean MFI 20.61 A.U. (IQR, 13.49-29.93 A.U., P<0.0001). Mean signal-to-background ratio was 5.71 (range, 2.28-10.13). When compared to VATS-IMI as a control, there were no significant differences in MFI of tumors, background tissue, or signal-to-background ratios. In summary, RIMI compared favorably to VATS-IMI by all measured imaging characteristics., Conclusions: RIMI is feasible for identification of GGOs during robotic resection as compared to white light thoracoscopy and compares favorably to VATS-IMI., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-21-1004/coif). GTK reports grant funding from the American Philosophical Society and the National Institutes of Health (grant F32 CA254210-01). SS reports grant funding from the National Institutes of Health (grant R01 CA193556) and the State of Pennsylvania Health Research Formula Fund. NG and JS are paid employees of Intuitive Surgical, Inc. The other authors have no conflicts of interest to declare., (2022 Translational Lung Cancer Research. All rights reserved.)

Patients do not access physicians at random but rather via naturally emerging networks of patient flows between them. As mass quarantines, absences due to sickness, or other shocks thin out these networks, the system might be pushed to a tipping point where it loses its ability to deliver care. Here, we propose a data-driven framework to quantify regional resilience to such shocks via an agent-based model. For each region and medical specialty we construct patient-sharing networks and stress-test these by removing physicians. This allows us to measure regional resilience indicators describing how many physicians can be removed before patients will not be treated anymore. Our model could therefore enable health authorities to rapidly identify bottlenecks in access to care. Here, we show that regions and medical specialties differ substantially in their resilience and that these systemic differences can be related to indicators for individual physicians by quantifying their risk and benefit to the system., (© 2022. The Author(s).)

The zoonotic origin of SARS-CoV-2, the etiological agent of COVID-19, is not yet fully resolved. Although natural infections in animals are reported in a wide range of species, large knowledge and data gaps remain regarding SARS-CoV-2 in animal hosts. We used two major health databases to extract unstructured data and generated a global dataset of SARS-CoV-2 events in animals. The dataset presents harmonized host names, integrates relevant epidemiological and clinical data on each event, and is readily usable for analytical purposes. We also share the code for technical and visual validation of the data and created a user-friendly dashboard for data exploration. Data on SARS-CoV-2 occurrence in animals is critical to adapting monitoring strategies, preventing the formation of animal reservoirs, and tailoring future human and animal vaccination programs. The FAIRness and analytical flexibility of the data will support research efforts on SARS-CoV-2 at the human-animal-environment interface. We intend to update this dataset weekly for at least one year and, through collaborations, to develop it further and expand its use., (© 2022. The Author(s).)

Iatrogenic nerve injury significantly affects surgical outcomes. Although intraoperative neuromonitoring is utilized, nerve identification remains challenging and the success of nerve sparing is strongly correlated with surgeon experience levels. Fluorescence guided surgery (FGS) offers a potential solution for improved nerve sparing by providing direct visualization of nerve tissue intraoperatively. However, novel probes for FGS face a long regulatory pathway to achieve clinical translation. Herein, we report on the development of a clinically-viable, gel-based formulation that enables direct administration of nerve-specific probes for nerve sparing FGS applications, facilitating clinical translation via the exploratory investigational new drug (eIND) guidance. The developed formulation possesses unique gelling characteristics, allowing it to be easily spread as a liquid followed by rapid gelling for subsequent tissue hold. Optimization of the direct administration protocol with our gel-based formulation enabled a total staining time of 1-2 min for compatibility with surgical procedures and successful clinical translation., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

We aim to identify those measures that effectively control the spread of SARS-CoV-2 in Austrian schools. Using cluster tracing data we calibrate an agent-based epidemiological model and consider situations where the B1.617.2 (delta) virus strain is dominant and parts of the population are vaccinated to quantify the impact of non-pharmaceutical interventions (NPIs) such as room ventilation, reduction of class size, wearing of masks during lessons, vaccinations, and school entry testing by SARS-CoV2-antigen tests. In the data we find that 40% of all clusters involved no more than two cases, and 3% of the clusters only had more than 20 cases. The model shows that combinations of NPIs together with vaccinations are necessary to allow for a controlled opening of schools under sustained community transmission of the SARS-CoV-2 delta variant. For plausible vaccination rates, primary (secondary) schools require a combination of at least two (three) of the above NPIs., (© 2022. The Author(s).)

Due to its high lethality among older people, the safety of nursing homes has been of central importance during the COVID-19 pandemic. With test procedures and vaccines becoming available at scale, nursing homes might relax prohibitory measures while controlling the spread of infections. By control we mean that each index case infects less than one other person on average. Here, we develop an agent-based epidemiological model for the spread of SARS-CoV-2 calibrated to Austrian nursing homes to identify optimal prevention strategies. We find that the effectiveness of mitigation testing depends critically on test turnover time (time until test result), the detection threshold of tests and mitigation testing frequencies. Under realistic conditions and in absence of vaccinations, we find that mitigation testing of employees only might be sufficient to control outbreaks if tests have low turnover times and detection thresholds. If vaccines that are 60% effective against high viral load and transmission are available, control is achieved if 80% or more of the residents are vaccinated, even without mitigation testing and if residents are allowed to have visitors. Since these results strongly depend on vaccine efficacy against infection, retention of testing infrastructures, regular testing and sequencing of virus genomes is advised to enable early identification of new variants of concern.

Nerves are extremely difficult to identify and are often accidently damaged during surgery, leaving patients with lasting pain and numbness. Herein, a novel near-infrared (NIR) nerve-specific fluorophore, LGW01-08, was utilized for enhanced nerve identification using fluorescence guided surgery (FGS), formulated using clinical translatable strategies. Formulated LGW01-08 was examined for toxicology, pharmacokinetics (PK), and pharmacodynamics (PD) parameters in preparation for future clinical translation. Optimal LGW01-08 imaging doses were identified in each formulation resulting in a 10x difference between the toxicity to imaging dose window. Laparoscopic swine surgery completed using the da Vinci surgical robot (Intuitive Surgical) demonstrated the efficacy of formulated LGW01-08 for enhanced nerve identification. NIR fluorescence imaging enabled clear identification of nerves buried beneath ~3 mm of tissue that were unidentifiable by white light imaging. These studies provide a strong basis for future clinical translation of NIR nerve-specific fluorophores for utility during FGS to improve patient outcomes., Competing Interests: COMPETING INTERESTS Alexander Antaris, Alwin Klaassen and Jonathan Sorger are employees of Intuitive Surgical. Lei Wang, Connor Barth and Summer Gibbs are inventors on patent application PCT/US19/43739 held by Oregon Health and Science University that cover the composition and methods of use of the nerve-specific oxazine compound (LGW01–08) discussed in this manuscript. Lei Wang, Connor Barth, Vidhi Shah, Adam Alani and Summer Gibbs are inventors on patent application PCT/US19/45347 held jointly by Oregon Health and Science University and Oregon State University that covers the compositions and methods of use of the formulation strategies developed herein. Lei Wang, Connor Barth and Summer Gibbs are co-founders of Inherent Targeting, LLC.

Nerve damage is a major complication of surgery, causing pain and loss of function. We have identified novel near-infrared nerve-specific fluorophores that provide excellent nerve contrast with the ability to identify buried nerve tissue.

Surgical resection of tumours requires precisely locating and defining the margins between lesions and normal tissue. However, this is made difficult by irregular margin borders. Although molecularly targeted optical contrast agents can be used to define tumour margins during surgery in real time, the selectivity of the contrast agents is often limited by the target being expressed in both healthy and tumour tissues. Here, we show that AND-gate optical imaging probes that require the processing of two substrates by multiple tumour-specific enzymes produce a fluorescent signal with significantly improved specificity and sensitivity to tumour tissue. We evaluated the performance of the probes in mouse models of mammary tumours and of metastatic lung cancer, as well as during fluorescence-guided robotic surgery. Imaging probes that rely on multivariate activation to selectively target complex patterns of enzymatic activity should be useful in disease detection, treatment and monitoring.

Multimorbidity, the presence of two or more diseases in a patient, is maybe the greatest health challenge for the aging populations of many high-income countries. One of the main drivers of multimorbidity is diabetes mellitus (DM) due to its large number of risk factors and complications. Yet, we currently have very limited understanding of how to quantify multimorbidity beyond a simple counting of diseases and thereby inform prevention and intervention strategies tailored to the needs of elderly DM patients. Here, we conceptualize multimorbidity as typical temporal progression patterns of multiple diseases, so-called trajectories, and develop a framework to perform a matched and sex-specific comparison between DM and non-diabetic patients. We find that these disease trajectories can be organized into a multi-level hierarchy in which DM patients progress from relatively healthy states with low mortality to high-mortality states characterized by cardiovascular diseases, chronic lower respiratory diseases, renal failure, and different combinations thereof. The same disease trajectories can be observed in non-diabetic patients, however, we find that DM patients typically progress at much higher rates along their trajectories. Comparing male and female DM patients, we find a general tendency that females progress faster toward high multimorbidity states than males, in particular along trajectories that involve obesity. Males, on the other hand, appear to progress faster in trajectories that combine heart diseases with cerebrovascular diseases. Our results show that prevention and efficient management of DM are key to achieve a compression of morbidity into higher patient ages. Multidisciplinary efforts involving clinicians as well as experts in machine learning and data visualization are needed to better understand the identified disease trajectories and thereby contribute to solving the current multimorbidity crisis in healthcare., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Haug, Sorger, Gisinger, Gyimesi, Kautzky-Willer, Thurner and Klimek.)

Infantile myofibroma is the most common fibrous tumor of infancy. Despite the frequency of these tumors, the natural history is incompletely understood. We present two cases with a unique pattern of disease: solitary myofibromas with subsequent progression to diffuse myofibromatosis. Given the variable spectrum of disease and the corresponding difference in morbidity and potential mortality based on the extent of disease, we propose surveillance recommendations., (© 2020 Wiley Periodicals, Inc.)

In response to the COVID-19 pandemic, governments have implemented a wide range of non-pharmaceutical interventions (NPIs). Monitoring and documenting government strategies during the COVID-19 crisis is crucial to understand the progression of the epidemic. Following a content analysis strategy of existing public information sources, we developed a specific hierarchical coding scheme for NPIs. We generated a comprehensive structured dataset of government interventions and their respective timelines of implementation. To improve transparency and motivate collaborative validation process, information sources are shared via an open library. We also provide codes that enable users to visualise the dataset. Standardization and structure of the dataset facilitate inter-country comparison and the assessment of the impacts of different NPI categories on the epidemic parameters, population health indicators, the economy, and human rights, among others. This dataset provides an in-depth insight of the government strategies and can be a valuable tool for developing relevant preparedness plans for pandemic. We intend to further develop and update this dataset until the end of December 2020.

There are practically no quantitative tools for understanding how much stress a health care system can absorb before it loses its ability to provide care. We propose to measure the resilience of health care systems with respect to changes in the density of primary care providers. We develop a computational model on a 1-to-1 scale for a countrywide primary care sector based on patient-sharing networks. Nodes represent all primary care providers in a country; links indicate patient flows between them. The removal of providers could cause a cascade of patient displacements, as patients have to find alternative providers. The model is calibrated with nationwide data from Austria that includes almost all primary care contacts over 2 y. We assign 2 properties to every provider: the "CareRank" measures the average number of displacements caused by a provider's removal (systemic risk) as well as the fraction of patients a provider can absorb when others default (systemic benefit). Below a critical number of providers, large-scale cascades of patient displacements occur, and no more providers can be found in a given region. We quantify regional resilience as the maximum fraction of providers that can be removed before cascading events prevent coverage for all patients within a district. We find considerable regional heterogeneity in the critical transition point from resilient to nonresilient behavior. We demonstrate that health care resilience cannot be quantified by physician density alone but must take into account how networked systems respond and restructure in response to shocks. The approach can identify systemically relevant providers., Competing Interests: The authors declare no competing interest., (Copyright © 2019 the Author(s). Published by PNAS.)

Molecularly targeted optical contrast agents have the potential to enable surgeons to visualize specific molecular markers that can help improve surgical precision and thus outcomes. Fluorescently quenched substrates can be used to highlight tumor lesions by targeting proteases that are highly abundant in the tumor microenvironment. However, the majority of these and other molecularly targeted optical contrast agents are labeled with reporter dyes that are not ideally matched to the properties of clinical camera systems, which are typically optimized for detection of indocyanine-green (ICG). While a wide range of near-infrared (NIR) dyes are suitable for use with highly sensitive and highly tunable research-focused small animal imaging systems, most have not been evaluated for use with commonly used clinical imaging systems. Here we report the optimization of a small molecule fluorescently quenched protease substrate probe 6QC-ICG, which uses the indocyanine green (ICG) dye as its optical reporter. We evaluated dosing and kinetic parameters of this molecule in tumor-bearing mice and observed optimal tumor over background signals in as little as 90 min with a dose of 2.3 mg/kg. Importantly, the fluorescence intensity of the probe signal in tumors did not linearly scale with dose, suggesting the importance of detailed dosing studies. Furthermore, when imaged using the FDA approved da Vinci Si surgical system with Firefly detection, signals were significantly higher for the ICG probe compared to a corresponding probe containing a dye with similar quantum yield but with a slightly shifted excitation and emission profile. The increased signal intensity generated by the optimal dye and dose of the ICG labeled probe enabled detection of small, flat lesions that were less than 5 mm in diameter. Therefore, 6QC-ICG is a highly sensitive probe that performs optimally with clinical imaging systems and has great potential for applications in optical surgical navigation.

We propose a system to facilitate biology communication by developing a pipeline to support the instructional visualization of heterogeneous biological data on heterogeneous user-devices. Discoveries and concepts in biology are typically summarized with illustrations assembled manually from the interpretation and application of heterogenous data. The creation of such illustrations is time consuming, which makes it incompatible with frequent updates to the measured data as new discoveries are made. Illustrations are typically non-interactive, and when an illustration is updated, it still has to reach the user. Our system is designed to overcome these three obstacles. It supports the integration of heterogeneous datasets, reflecting the knowledge that is gained from different data sources in biology. After pre-processing the datasets, the system transforms them into visual representations as inspired by scientific illustrations. As opposed to traditional scientific illustration these representations are generated in real-time - they are interactive. The code generating the visualizations can be embedded in various software environments. To demonstrate this, we implemented both a desktop application and a remote-rendering server in which the pipeline is embedded. The remote-rendering server supports multi-threaded rendering and it is able to handle multiple users simultaneously. This scalability to different hardware environments, including multi-GPU setups, makes our system useful for efficient public dissemination of biological discoveries.

We present an approach to represent DNA nanostructures in varying forms of semantic abstraction, describe ways to smoothly transition between them, and thus create a continuous multiscale visualization and interaction space for applications in DNA nanotechnology. This new way of observing, interacting with, and creating DNA nanostructures enables domain experts to approach their work in any of the semantic abstraction levels, supporting both low-level manipulations and high-level visualization and modifications. Our approach allows them to deal with the increasingly complex DNA objects that they are designing, to improve their features, and to add novel functions in a way that no existing single-scale approach offers today. For this purpose we collaborated with DNA nanotechnology experts to design a set of ten semantic scales. These scales take the DNA's chemical and structural behavior into account and depict it from atoms to the targeted architecture with increasing levels of abstraction. To create coherence between the discrete scales, we seamlessly transition between them in a well-defined manner. We use special encodings to allow experts to estimate the nanoscale object's stability. We also add scale-adaptive interactions that facilitate the intuitive modification of complex structures at multiple scales. We demonstrate the applicability of our approach on an experimental use case. Moreover, feedback from our collaborating domain experts confirmed an increased time efficiency and certainty for analysis and modification tasks on complex DNA structures. Our method thus offers exciting new opportunities with promising applications in medicine and biotechnology.

Considerable advances in cancer-specific optical imaging have improved the precision of tumor resection. In comparison to traditional imaging modalities, this technology is unique in its ability to provide real-time feedback to the operating surgeon. Given the significant clinical implications of optical imaging, there is an urgent need to standardize surgical navigation tools and contrast agents to facilitate swift regulatory approval. Because fluorescence-enhanced surgery requires a combination of both device and drug, each may be developed in conjunction, or separately, which are important considerations in the approval process. This report is the result of a one-day meeting held on May 4, 2016 with officials from the National Cancer Institute, the FDA, members of the American Society of Image-Guided Surgery, and members of the World Molecular Imaging Society, which discussed consensus methods for FDA-directed human testing and approval of investigational optical imaging devices as well as contrast agents for surgical applications. The goal of this workshop was to discuss FDA approval requirements and the expectations for approval of these novel drugs and devices, packaged separately or in combination, within the context of optical surgical navigation. In addition, the workshop acted to provide clarity to the research community on data collection and trial design. Reported here are the specific discussion items and recommendations from this critical and timely meeting. Cancer Res; 77(9); 2197-206. ©2017 AACR ., (©2017 American Association for Cancer Research.)

3D visibility analysis plays a key role in urban planning for assessing the visual impact of proposed buildings on the cityscape. A call for proposals typically yields around 30 candidate buildings that need to be evaluated with respect to selected viewpoints. Current visibility analysis methods are very time-consuming and limited to a small number of viewpoints. Further, analysts neither have measures to evaluate candidates quantitatively, nor to compare them efficiently. The primary contribution of this work is the design study of Vis-A-Ware, a visualization system to qualitatively and quantitatively evaluate, rank, and compare visibility data of candidate buildings with respect to a large number of viewpoints. Vis-A-Ware features a 3D spatial view of an urban scene and non-spatial views of data derived from visibility evaluations, which are tightly integrated by linked interaction. To enable a quantitative evaluation we developed four metrics in accordance with experts from urban planning. We illustrate the applicability of Vis-A-Ware on the basis of a use case scenario and present results from informal feedback sessions with domain experts from urban planning and development. This feedback suggests that Vis-A-Ware is a valuable tool for visibility analysis allowing analysts to answer complex questions more efficiently and objectively.

Background: The prognostic significance of having extraskeletal (EES) versus skeletal Ewing sarcoma (ES) in the setting of modern chemotherapy protocols is unknown. The purpose of this study was to compare the clinical characteristics, biologic features, and outcomes for patients with EES and skeletal ES., Methods: Patients had localized ES and were treated on two consecutive protocols using five-drug chemotherapy (INT-0154 and AEWS0031). Patients were analyzed based on having an extraskeletal (n = 213) or skeletal (n = 826) site of tumor origin. Event-free survival (EFS) was estimated using the Kaplan-Meier method, compared using the log-rank test, and modeled using Cox multivariate regression., Results: Patients with extraskeletal ES (EES) were more likely to have axial tumors (72% vs. 55%; P < 0.001), less likely to have tumors >8 cm (9% vs. 17%; P < 0.01), and less likely to be white (81% vs. 87%; P < 0.001) compared to patients with skeletal ES. There was no difference in key genomic features (type of EWSR1 translocation, TP53 mutation, CDKN2A mutation/loss) between groups. After controlling for age, race, and primary site, EES was associated with superior EFS (hazard ratio = 0.69; 95% confidence interval: 0.50-0.95; P = 0.02). Among patients with EES, age ≥18, nonwhite race, and elevated baseline erythrocyte sedimentation rate were independently associated with inferior EFS., Conclusion: Clinical characteristics, but not key tumor genomic features, differ between EES and skeletal ES. Extraskeletal origin is a favorable prognostic factor, independent of age, race, and primary site., Competing Interests: Statement None of the authors have any conflicts of interest related to this work or its publication. Author S.L.L. has a leadership role and stock/ownership interest in Salarius Pharmaceuticals, however, again, this is not a conflict for this study., (© 2016 Wiley Periodicals, Inc.)

State-of-the-art lighting design is based on physically accurate lighting simulations of scenes such as offices. The simulation results support lighting designers in the creation of lighting configurations, which must meet contradicting customer objectives regarding quality and price while conforming to industry standards. However, current tools for lighting design impede rapid feedback cycles. On the one side, they decouple analysis and simulation specification. On the other side, they lack capabilities for a detailed comparison of multiple configurations. The primary contribution of this paper is a design study of LiteVis, a system for efficient decision support in lighting design. LiteVis tightly integrates global illumination-based lighting simulation, a spatial representation of the scene, and non-spatial visualizations of parameters and result indicators. This enables an efficient iterative cycle of simulation parametrization and analysis. Specifically, a novel visualization supports decision making by ranking simulated lighting configurations with regard to a weight-based prioritization of objectives that considers both spatial and non-spatial characteristics. In the spatial domain, novel concepts support a detailed comparison of illumination scenarios. We demonstrate LiteVis using a real-world use case and report qualitative feedback of lighting designers. This feedback indicates that LiteVis successfully supports lighting designers to achieve key tasks more efficiently and with greater certainty.

The visual analysis of surface cracks plays an essential role in tunnel maintenance when assessing the condition of a tunnel. To identify patterns of cracks, which endanger the structural integrity of its concrete surface, analysts need an integrated solution for visual analysis of geometric and multivariate data to decide if issuing a repair project is necessary. The primary contribution of this work is a design study, supporting tunnel crack analysis by tightly integrating geometric and attribute views to allow users a holistic visual analysis of geometric representations and multivariate attributes. Our secondary contribution is Visual Analytics and Rendering, a methodological approach which addresses challenges and recurring design questions in integrated systems. We evaluated the tunnel crack analysis solution in informal feedback sessions with experts from tunnel maintenance and surveying. We substantiated the derived methodology by providing guidelines and linking it to examples from the literature.

There is a need for new molecular-guided contrast agents to enhance surgical procedures such as tumor resection that require a high degree of precision. Cysteine cathepsins are highly up-regulated in a wide variety of cancers, both in tumor cells and in the tumor-supporting cells of the surrounding stroma. Therefore, tools that can be used to dynamically monitor their activity in vivo could be used as imaging contrast agents for intraoperative fluorescence image guided surgery (FGS). Although multiple classes of cathepsin-targeted substrate probes have been reported, most suffer from overall fast clearance from sites of protease activation, leading to reduced signal intensity and duration in vivo. Here we describe the design and synthesis of a series of near-infrared fluorogenic probes that exploit a latent cationic lysosomotropic effect (LLE) to promote cellular retention upon protease activation. These probes show tumor-specific retention, fast activation kinetics, and rapid systemic distribution. We demonstrate that they are suitable for detection of diverse cancer types including breast, colon and lung tumors. Most importantly, the agents are compatible with the existing, FDA approved, da Vinci surgical system for fluorescence guided tumor resection. Therefore, our data suggest that the probes reported here can be used with existing clinical instrumentation to detect tumors and potentially other types of inflammatory lesions to guide surgical decision making in real time.