Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Dendritic cell sarcoma: A pooled analysis including 462 cases with presentation of our case series

Dendritic cell tumors are extremely rare and current knowledge on these tumors is limited. The characteristics of three dendritic cell sarcoma subtypes and their optimal treatment approaches are not fully clarified. We aimed to make a systematic review of the literature and enrich the current data with five new cases. Pooled analysis of 462 reported cases revealed that the tumor had no age, gender or racial predilection. Our analysis suggests that the young age, advanced stage, intraabdominal involvement and unfavorable histological features (i.e. large tumor size, absence of lymphoplasmacytic infiltration, coagulative necrosis, high mitotic count) may predict poor prognosis. Subtypes of this tumor have different clinical behaviors with interdigitating dendritic cell sarcoma being the most aggressive form. In general, surgery is the most effective treatment modality and adjuvant radiotherapy has no significant effect on overall survival of patients. The role of chemotherapy for the management of advanced disease is controversial. (C) 2013 Elsevier Ireland Ltd. All rights reserved

Combining Landsat and ALOS Data for Land Cover Mapping

25th Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2017 -- Antalya, TURKEYWOS: 000413813100242In this study, L-band ALOS PALSAR radar satellite image and Landsat TM optical satellite image were used to investigate the contribution of radar satellite image to optical satellite image for land cover mapping. Dual-polarimetric data of ALOS satellite and also normalized difference vegetation index (NDVI) generated from Landsat image were used for the analysis. In addition, different classification techniques were taken into consideration and forest dominated land cover maps were produced and the results were compared. Random Forest (RF), k-Nearest Neighbors (k-NN) and Support Vector Machines (SVM) approaches were applied as image classification techniques. While the best result among the methods is DVM, the data set in which combined data arc used gives the best general accuracy result.Turk Telekom, Arcelik A S, Aselsan, ARGENIT, HAVELSAN, NETAS, Adresgezgini, IEEE Turkey Sect, AVCR Informat Technologies, Cisco, i2i Syst, Integrated Syst & Syst Design, ENOVAS, FiGES Engn, MS Spektral, Istanbul Teknik Uni

Incidental retroperitoneal oncocytoma (Ectopic oncocytic adrenocortical adenoma): Case report and review of the literature

Ectopic adrenocortical tissue may be present in many anatomical localizations. Hyperplasia, adenoma or carcinoma can occasionally develop from the ectopic adrenal tissue. Therefore, it should be surgically excised when it is detected. Adrenocortical tumors are the most common type of adrenal neoplasms. Ectopic adrenocortical adenomas are rarely seen. A total of 34 cases of ectopic adrenocortical adenoma (14 of which are oncocytomas) have been reported at different localizations in English literature. Most of them are non-functional. Differential diagnosis is required with other benign or malign oncocytic neoplasms. We report a 56-year-old male patient, who presented with a retroperitoneal mass. Our case is the seventh case of ectopic retroperitoneal adrenal adenoma with oncocytic cells

Evaluation of image fusion methods using PALSAR, RADARSAT-1 and SPOT images for land use/land cover classification

WOS: 000406359500003This research aimed to explore the fusion of multispectral optical SPOT data with microwave L-band ALOS PALSAR and C-band RADARSAT-1 data for a detailed land use/cover mapping to find out the individual contributions of different wavelengths. Many fusion approaches have been implemented and analyzed for various applications using different remote sensing images. However, the fusion methods have conflict in the context of land use/cover (LULC) mapping using optical and synthetic aperture radar (SAR) images together. In this research two SAR images ALOS PALSAR and RADARSAT-1 were fused with SPOT data. Although, both SAR data were gathered in same polarization, and had same ground resolution, they differ in wavelengths. As different data fusion methods, intensity hue saturation (IHS), principal component analysis, discrete wavelet transformation, high pass frequency (HPF), and Ehlers, were performed and compared. For the quality analyses, visual interpretation was applied as a qualitative analysis, and spectral quality metrics of the fused images, such as correlation coefficient (CC) and universal image quality index (UIQI) were applied as a quantitative analysis. Furthermore, multispectral SPOT image and SAR fused images were classified with Maximum Likelihood Classification (MLC) method for the evaluation of their efficiencies. Ehlers gave the best score in the quality analysis and for the accuracy of LULC on LULC mapping of PALSAR and RADARSAT images. The results showed that the HPF method is in the second place with an increased thematic mapping accuracy. IHS had the worse results in all analyses. Overall, it is indicated that Ehlers method is a powerful technique to improve the LULC classification

GEOSPATIAL ANALYSIS USING REMOTE SENSING IMAGES: CASE STUDIES OF ZONGULDAK TEST FIELD

23rd Congress of the International-Society-for-Photogrammetry-and-Remote-Sensing (ISPRS) -- JUL 12-19, 2016 -- Prague, CZECH REPUBLICWOS: 000392750100072Inclined topographies are one of the most challenging problems for geospatial analysis of air-borne and space-borne imageries. However, flat areas are mostly misleading to exhibit the real performance. For this reason, researchers generally require a study area which includes mountainous topography and various land cover and land use types. Zonguldak and its vicinity is a very suitable test site for performance investigation of remote sensing systems due to the fact that it contains different land use types such as dense forest, river, sea, urban area; different structures such as open pit mining operations, thermal power plant; and its mountainous structure. In this paper, we reviewed more than 120 proceeding papers and journal articles about geospatial analysis that are performed on the test field of Zonguldak and its surroundings. Geospatial analysis performed with imageries include elimination of systematic geometric errors, 2/3D georeferencing accuracy assessment, DEM and DSM generation and validation, ortho-image production, evaluation of information content, image classification, automatic feature extraction and object recognition, pan sharpening, land use and land cover change analysis and deformation monitoring. In these applications many optical satellite images are used i.e. ASTER, Bilsat-1, IKONOS, IRS-1C, KOMPSAT-1, KVR-1000, Landsat-3-5-7, Orbview-3, QuickBird, Pleiades, SPOT-5, TK-350, RADARSAT-1, WorldView-1-2; as well as radar data i.e. JERS-1, Envisat ASAR, TerraSAR-X, ALOS PALSAR and SRTM. These studies are performed by Departments of Geomatics Engineering at Bulent Ecevit University, at Istanbul Technical University, at Yildiz Technical University, and Institute of Photogrammetry and Geolnformation at Leibniz University Hannover. These studies are financially supported by TUBITAK (Turkey), the Universities, ESA, Airbus DS, ERSDAC (Japan) and Julich Research Centre (Germany).Int Soc Photogrammetry & Remote SensingTUBITAK (Turkey)Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK); Universities, ESA, Airbus DS, ERSDAC (Japan); Julich Research Centre (Germany)These studies are financially supported by TUBITAK (Turkey), the Universities, ESA, Airbus DS, ERSDAC (Japan) and Julich Research Centre (Germany)