Background: Differentiation between malignant and benign vertebral compression fracture is often problematic. This is precisely difficult in elderly who are predisposed to benign compression caused by osteoporosis .Establishing correct diagnosis is of great importance in determining the treatment andprognosis.A study was performed to determine which magnetic resonance imaging findings are useful in discrimination between metastatic and acute osteoporotic compression fractures of the spine. Recently MRI is being increasingly used for evaluation of these fractures.Objectives: The aim of this study is to establish the correct diagnosis of malignant and benign compression vertebral fracture by MRI to determine treatment and prognosis.Methods: MRI of (45 )patients with vertebral compression fracture who underwent MRI of spine during 2 years period ( 2004-2006) in Neuro surgical hospital were retrospectively reviewed by an expedient radiologist , A collapsed vertebra were considered to be acute if there was recent history of back pain of less than 3moths. All MRI sequences needed for spine examination was done( T1WI SE, T2WI GE STIR, and Mylography ) and Gadolinium contrast medium was given to all patients..Results: Of total 45 patients (31male, 14 female, their age range between 18-72years) , The criteria used to differentiate between benign andmalignant collapse spine on MRI was based on the signal intensity, morphology and contrast enhancement for the correct diagnosis. Homogenous and diffuse abnormal signal intensity, posterior convexity and involvement of pedicles are sign that are strongly suggestive of malignant collapse .Conversely, a band like area of low signal intensity adjacent to depressed end plateand preservation of signal intensity of vertebra suggest benign nature of the collapse.Conclusions: We found that MRI features is helpful in differentiation of malignant and benign compression fractures in majority of cases, and if initial MRI finding are equivocal correlation with other images technique, follow up and biopsy in selected cases helpful in arriving correct diagnosis
the sera levels of luteninizing hormone were investgaited prior tq surgery in 10 postmenopaisal women with benign and 10 postmenopausal women with maliganant healthy
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This work is aimed to design a system which is able to diagnose two types of tumors in a human brain (benign and malignant), using curvelet transform and probabilistic neural network. Our proposed method follows an approach in which the stages are preprocessing using Gaussian filter, segmentation using fuzzy c-means and feature extraction using curvelet transform. These features are trained and tested the probabilistic neural network. Curvelet transform is to extract the feature of MRI images. The proposed screening technique has successfully detected the brain cancer from MRI images of an almost 100% recognition rate accuracy.
kinetic studies were carried out the uterine homogenate time course of the association of with LH in benign and malignant uterine
Background: Parotid gland tumors account for 80% of all salivary gland neoplasms, 20% of these are malignant, but in daily clinical practice most parotid masses are operated on before obtaining the final histological diagnosis. This clinical setting further complicates the critical point of parotid surgery, which is the management of the facial nerve. Materials and methods: 45 patients underwent parotidectomy for benign and malignant neoplasms. A complete history is collected from the patients with the duration and the site of the tumor, the facial nerve examined and its associations, a medical consultation done for opinion and management. Clinical examination with facial nerve was mandatory to avoid any mistakes that may occur. The most si
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Test method was developed radioimmunotherapy to appoint in two groups of patients infected with a uterine tumor Great conditions in tumor tissue benign and malignant Ddh teacher radioactive iodine isotope
Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is use
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Background: Multiple sclerosis is a chronic heterogeneous demyelinating axonal and inflammatory disease involving the Central Nervous System [CNS] white matter with a possibility of gray matter involvement in which the insulating covers of nerve cells in the brain and spinal cord are damaged. This damage disrupts the ability of parts of the nervous system to communicate, resulting in a wide range of signs and symptoms. Cerebral venous insufficiency theory was raised as a possible etiology for the disease at 2008 by Zamboni an Italian cardiothoracic surgeon. This theory was defeated by Multiple Sclerosis[ MS] researchers and scientists who thought that the disease is an autoimmune rather than vascular.
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