Intraoperative Neck Angles in Endoscopic and Microscopic Otologic Surgeries.

OBJECTIVE: To quantitatively compare the ergonomic risk of otologic surgeries performed with endoscopes and microscopes. STUDY DESIGN: Observational cross-sectional study. SETTING: Operating room of a tertiary academic medical center. METHODS: Intraoperative neck angles of otolaryngology attendings, fellows, and residents were assessed during 17 otologic surgeries using inertial measurement unit sensors. Sensors were attached midline between the shoulder blades and on the posterior scalp of participants and were calibrated just prior to beginning each case. Quaternion data were used to calculate neck angles during periods of active surgery. RESULTS: Endoscopic and microscopic cases included similar percentages of time in high-risk neck positions, 75% and 73%, respectively, according to a validated ergonomic risk assessment tool, the Rapid Upper Limb Assessment. However, microscopic cases included a higher percentage of time spent in extension (25%) compared to endoscopic cases (12%) (p < .001). When examining the magnitude of average flexion and extension angles, endoscopic and microscopic cases were not significantly different. CONCLUSION: Utilizing intraoperative sensor data, we found that both endoscopic and microscopic approaches in otologic surgery were associated with high-risk neck angles, which can result in sustained neck strain. These results suggest that optimal ergonomics may be better achieved by the consistent application of basic ergonomic principles than by changing the technology in the operating room.

Big Data Research Infrastructure Collaboration Toward the SKA (BRICSKA).

Astronomy is entering an era of mega-data that will render conventional research methods as well as data and visual analytics tools ineffective. The Square Kilometre Array (SKA) drives one of the most significant big data challenges of the next decades. South Africa, China and India are partners in the global SKA collaboration and host recently completed, next generation radio astronomy facilities. South Africa, Brazil, China and India are involved in the Large Synoptic Survey Telescope (LSST), which represents a complementary mega-data challenge, vastly increasing the current data volume of optical surveys, and providing critical multi-wavelength data set for SKA analytics. Russian researchers are also engaged in radio astronomy and multi-wavelength, multi-messenger projects driving increasing volumes of observational data. This project brings together teams leading programs in data innovation in each partner country to collaborate on the development of new technologies and systems to meet the big data challenge of SKA pathfinder facilities and the multi-wavelength projects that are critical to the advance of astronomy. In so doing we will prototype and demonstrate scalable big data technologies for the new big data era, and establish a BRICS multinational federated data intensive cloud network for collaborative programs in data intensive astronomy.

Using Big Data Analytics to Advance Precision Radiation Oncology.

Big clinical data analytics as a primary component of precision medicine is discussed, identifying where these emerging tools fit in the spectrum of genomics and radiomics research. A learning health system (LHS) is conceptualized that uses clinically acquired data with machine learning to advance the initiatives of precision medicine. The LHS is comprehensive and can be used for clinical decision support, discovery, and hypothesis derivation. These developing uses can positively impact the ultimate management and therapeutic course for patients. The conceptual model for each use of clinical data, however, is different, and an overview of the implications is discussed. With advancements in technologies and culture to improve the efficiency, accuracy, and breadth of measurements of the patient condition, the concept of an LHS may be realized in precision radiation therapy.

Metriculator: quality assessment for mass spectrometry-based proteomics.

SUMMARY: Quality control in mass spectrometry-based proteomics remains subjective, labor-intensive and inconsistent between laboratories. We introduce Metriculator, a software designed to facilitate long-term storage of extensive performance metrics as introduced by NIST in 2010. Metriculator features a web interface that generates interactive comparison plots for contextual understanding of metric values and an automated metric generation toolkit. The comparison plots are designed for at-a-glance determination of outliers and trends in the datasets, together with relevant statistical comparisons. Easy-to-use quantitative comparisons and a framework for integration plugins will encourage a culture of quality assurance within the proteomics community. AVAILABILITY AND IMPLEMENTATION: Available under the MIT license at http://github.com/princelab/metriculator.

Ultrasound elastography as a tool for imaging guidance during prostatectomy: initial experience.

BACKGROUND: During laparoscopic or robotic assisted laparoscopic prostatectomy, the surgeon lacks tactile feedback which can help him tailor the size of the excision. Ultrasound elastography (USE) is an emerging imaging technology which maps the stiffness of tissue. In the paper we are evaluating USE as a palpation equivalent tool for intraoperative image guided robotic assisted laparoscopic prostatectomy. MATERIAL/METHODS: Two studies were performed: 1) A laparoscopic ultrasound probe was used in a comparative study of manual palpation versus USE in detecting tumor surrogates in synthetic and ex-vivo tissue phantoms; N=25 participants (students) were asked to provide the presence, size and depth of these simulated lesions, and 2) A standard ultrasound probe was used for the evaluation of USE on ex-vivo human prostate specimens (N=10 lesions in N=6 specimens) to differentiate hard versus soft lesions with pathology correlation. Results were validated by pathology findings, and also by in-vivo and ex-vivo MR imaging correlation. RESULTS: In the comparative study, USE displayed higher accuracy and specificity in tumor detection (sensitivity=84%, specificity=74%). Tumor diameters and depths were better estimated using USE versus with manual palpation. USE also proved consistent in identification of lesions in ex-vivo prostate specimens; hard and soft, malignant and benign, central and peripheral. CONCLUSIONS: USE is a strong candidate for assisting surgeons by providing palpation equivalent evaluation of the tumor location, boundaries and extra-capsular extension. The results encourage us to pursue further testing in the robotic laparoscopic environment.