IntroductionTo evaluate contrast enhanced ultrasound (CEUS) as a modality to predict T stage of cancer of urinary bladder (CAUB) and to predict the grade of the tumor preoperatively.Material and methods110 patients with CAUB presenting to the Department of Urology at our institution between July 2014 and December 2015 underwent CEUS prior to endoscopic resection and the CEUS findings were compared with histopathology results.ResultsCEUS had a sensitivity of 75, 65 and 90% and specificity of 95, 85 and 92% in detecting Ta, T1 and muscle invasion respectively. CEUS had a sensitivity of 78% and specificity of 85% in detecting the grade of the lesion.ConclusionsCEUS is a good alternative for T staging and grading of CAUB preoperatively. It is uniquely advantageous in detecting clots or necrosis and in patients with low eGFR where other imaging modalities are contraindicated.
Abstract. The amount of data that is being generated in health care is enormous, especially with the widespread availability of multimedia devices. However, the data keeping in developing countries is still unstructured. Lots of this Big Data is therefore vulnerable to loss. In the current report we highlight the problem and suggest the need for cost effective solution.Keywords: Big data, data storage, data retrieval "In god we trust, all others (must) bring data".With these words, W. Deming, an American statistician, exhorted the global industry to move into the new age of "Big Data". Big data refers to data so large and voluminous that traditional data processing applications are inadequate to analyze them. This data when analyzed or mined can reveal insights and new knowledge which is especially relevant in the field of healthcare. This allows for better utilization of resources, increasing competitiveness and profitability along with betterment of care for the patients. Data in healthcare comes in many forms. The majority of healthcare data generated today is unstructured, e.g. We generate about approximately 10 Gigabyte (GB) of structured data per day. However there is a higher volume of data that is stored unstructured, collected at an individual level (data like laparoscopic/open surgical videos, radiological images, clinical photographs etc.). Partly this is due to the wide availability of multimedia devices and lack of facility for a central storage of the data-base. Even for this small structured data we are facing problems to store and ways to retrieve it as and when required. If we wish to store all the data (both structured and unstructured) the volume will be huge (approximately 20 terabytes a year) and problems of storage and retrieval will be compounded. This is an example of a medium sized (100-150 beds) healthcare facility in a resource constrained setting in a developing country like ours (1). As a solution to this problem, we have started to save data in optical disk drives and flash drives to store it individually. For larger data we rely on HDD and SSD on multiple individual computer terminals.
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