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Background: Carcinoma of the breast is the most common malignancy in females. At present carcinoma breast is the leading cancer in Bangladesh and is competing cancer cervix in incidence. Epidemiological studies at regional and global levels suggest the occurrence of carcinoma breast at a younger, premenopausal age in Indian and Asian women as compared with western women. Knowledge of this factor emphasizes the need to modify the timing of modalities of detection of early carcinoma and its management. According to literature, majority of carcinoma breast cases in the western countries present in Stages I and II of the disease whereas in Bangladesh majority cases present in Stage III of the disease. The objective of this study is to observe age of occurrence of breast cancer and stage of cancer in SSMC and MH.Methods: A cross sectional observational study was conducted in 34 patients of histopathologically confirmed breast cancer.Results: Mean age of subjects was 46.24±7.4 years. Age distribution showed peaks at 41-50 years with 18 patients. This study shows that 82.35% of the total patients were having advanced carcinoma breast (Stage III, IV) and 77% of these patients were below 50 years of age.Conclusions: Breast cancer is increasingly occurring in younger age groups in Bangladesh when compared with western countries and a more aggressive nature of the disease strikes in their reproductive period suggesting the need for change in modalities of early cancer detection and adjusting preventive and therapeutic efforts. This small study may provocate thought for larger scale population study to evaluate the scenario in Bangladesh.

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Genitourinary complications following orthopaedic intervention are uncommon but well-described occurrences and exist on a spectrum of severity. These complications vary depending on the anatomic location and surgical approach, with surgery of the spine, hip, and pelvis of particular concern. Injuries to the urinary tract may present acutely with urinary retention or hematuria. However, they often have a delayed presentation with severe complications such as urinary fistula and recurrent infection. Delayed presentations may place the onus of timely and proper diagnosis on the orthopaedic provider, who may serve as the patient's primary source of long-term follow-up. Detailed knowledge of anatomy and at-risk structures is key to both preventing and identifying injury. Although iatrogenic injury is not always avoidable, early identification can help to facilitate timely evaluation and management to prevent long-term complications such as bladder dysfunction, obstructive renal injury, sexual dysfunction, and chronic pain.

INTRODUCTION AND OBJECTIVES: Currently, transrectal ultrasound (TRUS) guided biopsies is the only method for definitive diagnosis of prostate cancer. Studies by our group suggest that quantitative ultrasound (QUS) using machine learning-based lesion detection via high resolution micro-ultrasound could provide a more-sensitive, automated mechanism of identifying and targeting biopsies at cancersuspicious regions in the prostate.METHODS: Our previous studies utilized ultrasound signals at typical clinical frequencies, i.e., in the 6-MHz range. In our current study, a novel, 29-MHz, fine-resolution, micro-ultrasound instrument (ExactVu TM micro-ultrasound, Exact Imaging, Markham, Canada) was used to acquire RF data from 163 patients directly before 12-core biopsy (1,956 cores total). These retrospective data are a subset of data acquired in a multisite, 1,676-patient, randomized, clinical trial (clinicaltrials.gov NCT02079025). Machine learning-based lesion detection incorporated the following spectral-QUS features: effective scatter diameter (ESD), effective acoustic concentration (EAC), midband (M), intercept (I) and slope (S) as well as envelope statistics using a Nakagami distribution. The values of these features were calculated and used to train linear discriminant classifiers (LDCs) and support-vector machines (SVMs). Classifier performance was assessed using area-under-the-curve (AUC) values obtained from receiver operating characteristic (ROC) analyses with 10-fold cross validation.RESULTS: A combination of ESD and EAC parameters resulted in an AUC value of 0.75 using an LDC. When the PSA value was added as a feature, the AUC increased to 0.79. The best classification performance was obtained using an LDC by combining envelope statistics, PSA, ESD and EAC, which resulted in an AUC of 0.81. Using an SVM did not improve the classification significantly (i.e., best classifier AUC~0.75). In a separate study of the imaging capabilities of the ExactVu TM instrument, B-mode-based scoring and evaluation of lesions achieved an AUC of 0.74 for higher GS values (Gleason Sum > 7) for images interpreted by an expert.CONCLUSIONS: The AUC value of 0.81 achieved in the current study provides an encouraging basis for developing a new, entirely objective, automated method of assessing prostate-cancer risk and depicting suspicious regions in fine-resolution, real-time, micro-ultrasound images. The study results demonstrate that QUS-based imaging methods have great promise for reliably targeting prostate biopsies, planning and delivering focal treatment of prostate cancers, and monitoring treated or watched prostate cancers.