Utility of Osteoporosis Self-Assessment Tool as a Screening Tool for Predicting Osteoporosis in Indian Men.

The osteoporosis self-assessment tool (OSTA) predicts the risk of osteoporosis in an individual. It is a simple calculation-based tool [wt (kg) - age (yr)/5] and can be used for measuring bone mineral density (BMD). However, OSTA is influenced by ethnicity. We studied the performance of OSTA index as a screening tool for osteoporosis in 257 community-dwelling North Indian men above 50 yr age. Each subject underwent a detailed clinical, dietary, anthropometric, and biochemical assessment and bone density measurement using dual-energy X-ray absorptiometry. As per World Health Organization criteria, osteoporosis, osteopenia, and normal BMD were observed in 17.9%, 58.8%, and 23.3%, respectively. OSTA index ranged between -6.4 and 8.8. OST index ≤2 predicted osteoporosis with a sensitivity of 95.7% and a specificity of 33.6% and an area under the curve for a receiver operating characteristic curve of 0.702. The OSTA index is an effective screening tool for measuring BMD in elderly Indian men and can be used by primary care physicians.

The brain MR Image segmentation techniques and use of diagnostic packages.

RATIONALE AND OBJECTIVES: This article provides a survey of segmentation methods for medical images. Usually, classification of segmentation methods is done based on the approaches adopted and the domain of application. MATERIALS AND METHODS: This survey is conducted on the recent segmentation methods used in biomedical image processing and explores the methods useful for better segmentation. A critical appraisal of the current status of semiautomated and automated methods is made for the segmentation of anatomical medical images emphasizing the advantages and disadvantages. Computer-aided diagnosis (CAD) used by radiologists as a second opinion has become one of the major research areas in medical imaging and diagnostic radiology. A picture archiving communication system (PACS) is an integrated workflow system for managing images and related data that is designed to streamline operations throughout the whole patient care delivery process. RESULTS: By using PACS, the medical image interpretation may be changed from conventional hard-copy images to soft-copy studies viewed on the systems workstations. CONCLUSION: The automatic segmentations assist the doctors in making quick diagnosis. The CAD need not be comparable to that of physicians, but is surely complementary.