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Background:Sickle cell disease (SCD) is an autosomal recessive hemolytic disorder; its cerebrovascular complications include silent cerebral ischemia, infarct, and brain atrophy. Conventional magnetic resonance imaging (MRI) often underestimates the extent of injury. Diffusion tensor imaging (DTI) can demonstrate and quantify microstructural brain changes in SCD cases having normal routine MRI.Objective:To identify various neurological abnormalities in asymptomatic sickle cell patients using routine MRI and to evaluate the microstructure of various regions of the brain using DTI.Materials and Methods:A prospective, randomized case–control study was conducted over a period of 2 years. A total of 58 cases of SCD and 56 age- and sex-matched controls were included. Routine MRI and DTI were performed in both the groups following a standard protocol. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) were calculated in certain pre-defined regions. Primary data were analyzed using MS excel version 17. Analysis of variance test was performed and statistical significance was set at P < 0.05.Results:Thirty regions of interest with 60 variables were included in the final analysis. Patients with SCD showed statistically significant reduced FA values, increased ADC values, or both, clustered in several brain areas, including pons, cerebral peduncle, corpus callosum, frontal, temporal, parietal white matter, centrum semiovale, periventricular areas, basal ganglia, and left thalamus (P < 0.05).Conclusion:DTI is a promising method for characterizing microstructural changes, when conventional MRI is normal.

Primary angiosarcoma (PAS) of the breast is a rare malignant tumor arising from endothelial cells lining the blood vessel and accounts for 0.04% of all breast tumors. It occurs predominantly in young patients usually presenting as nonspecific imaging features and is often overlooked and misdiagnosed at radiology and pathology. Angiosarcoma prognosis is generally poor; however, surgery followed by adjuvant chemotherapy and radiotherapy improves the prognosis. We report a rare case of PAS in a 65-year-old postmenopausal woman. She was diagnosed with PAS based on typical clinical, mammography, ultrasound, and magnetic resonance imaging (MRI) features followed by core biopsy of the lesion. Our case had the unique features of enlarged vessels within and surrounding the lesion in mammography, as well as in MRI, which could be very helpful for future diagnosis of this rare PAS in postmenopausal women.

Purpose: To assess the role of Dynamic contrast enhanced magnetic resonance imaging in characterization of breast lesions and to differentiate benign from malignant lesions on the basis of their morphology and enhancement kinetics. Material and Methods: Sixty patients referred to the department of Radiodiagnosis for breast MRI over a period of twenty months were included. Dynamic contrast enhanced (DCE) Magnetic Resonance Imaging (MRI) was performed to differentiate breast lesions on the basis of morphology and enhancement kinetics. The lesions were classified accordingly into type I (progressive enhancement) Type II (plateau) and Type III (washout) kinetics. Morphology and curves of benign and malignant lesions were compared. Result: fifty one benign lesions were detected in 32 patients and 29 malignant lesions were seen in 22 patients, whereas six patients showed normal MRI.It was found that benign lesion were round or oval in shape with well circumscribed margin and showed homogenous contrast enhancement whereas malignant lesions were irregular with spiculated margin and showed heterogenous contrast enhancement. The distribution curve types of benign lesion were Type I (81.25%-26cases), Type II (18.25%-6cases). For malignant lesions Type I (4.54%-1case), Type II (22.72%-5cases) and Type III (72.72%-16cases). Conclusion: The shape of the time-signal intensity curve were an important criteria in differentiating benign from malignant lesions in dynamic breast MR imaging. A type III time curve is a strong indicator of malignancy and is independent of other criteria.