IntroductionBreast cancer has a high prevalence in the community and places very high demands on resources. Digital mammography provides a good quality image with reduced radiation dose and can detect breast carcinoma in its earlier stages, resulting in good prognosis and improved patient survival.ObjectiveTo calculate the diagnostic accuracy of digital mammography in the detection of breast cancer, using histopathology as a gold standard in women aged over 30 years, who are undergoing mammography for screening and diagnostic purposes.Materials and methodsThis was a cross-sectional analytical study, conducted in the department of radiology, for a total duration of 10 months. A total of 122 patients of age above 30 years, referred for digital mammography for the evaluation of different symptoms related to breast diseases, followed by biopsy/surgery and histopathology, were included in the study.ResultOur data confirmed that digital mammography is a highly accurate tool for breast cancer detection having a sensitivity of 97%, a specificity of 64.5%, a positive predictive value of 89%, and a negative predictive value of 90.9%, with a diagnostic accuracy of 89.3%.ConclusionConsidering our results, we recommend that digital mammography should replace screen-film mammography as a basic tool to detect breast cancer for both screening and diagnostic purposes.

The Guyon's canal syndrome is a well known clinical entity and may have significant impact on patient's quality of life. We report a case of 43-year-old male who presented with complaints of pain and numbness in right hand and difficulty in writing for past one month. On imaging diagnosis of Guyon's canal syndrome because of tortuous ulnar artery was made with additional findings of DeQuervain's stenosing tenosynovitis and dorsal intercalated segmental instability syndrome with ligamentous injury and subsequently these were confirmed on surgery.Although it is a rare syndrome, early diagnosis and treatment prevents permanent neurological deficits and improve patient's quality of life.

Background Low back pain is a common condition and carries substantial socioeconomic implications. Magnetic resonance imaging (MRI) is the imaging modality of choice with lumbar neural foraminal stenosis being one of the most common causes of lower back pain syndromes. Studies have shown a lack of correlation between patients’ severity of disability and radiologically determined nerve root constriction. Therefore, the goal of this study will be to determine the frequency of severity of disability in patients with severe (i.e., grade III) lumbar neural foraminal stenosis on MRI to ascertain the impact of MRI diagnosis on clinical outcomes. Materials and methods Two hundred fifty patients of either gender with a history of backache referred for MRI were included by purposive sampling. Of these 250 patients, 27 patients had grade II lumbar neural foraminal stenosis, and 21 had grade I neural foraminal stenosis on MRI and were excluded. Thirty-two patients had a spinal infection (e.g., tuberculosis), and 24 patients had a history of trauma. Further, 31 patients were having follow-up scans for previously diagnosed lumbar neural foraminal stenosis. Hence, after excluding these cases, 115 patients were enrolled in this cross-sectional study with grade III lumbar neural foraminal stenosis on MRI. Results The mean age was 51 years (range: 20 to 82 years). Most of the patients (55.6%) were older than 50 years. The most common site of grade III lumbar neural foraminal stenosis was L4-L5 (56.5%). According to the Oswestry disability index, 47 patients (40.9%) had a severe disability, 32 (27.8%) had a moderate disability, 16 (13.9%) were diabled, 14 (12.2%) had a mild disability, and six (5.2%) were bedridden. Conclusions While MRI is the imaging modality of choice in degenerative lumbar spinal stenosis, clinical disabilities can be more extensive than what radiological findings may indicate in approximately 40% of the cases. Therefore, lumbar spinal stenosis should be a neuro-radiological diagnosis, and surgical decisions should be based on clinical scenarios in addition to MRI findings.