BRONCHIAL ARTERIOGRAPHY AND TRANSCATHETER EMBOLIZATION IN MANAGEMENT OF SEVERE HAEMOPTYSIS

The purpose of this study was to assess the effectiveness of bronchial arteriography and transcatheter embolization in treatment of severe haemoptysis. Forty five patients with severe haemoptysis were evaluated by means of bronchial arteriography and study of non bronchial systemic arteries and underwent transcatheter embolization. Specific causes of haemoptysis were Tuberculosis (n=37), Tuberculosis with Aspergilloma (n=4) and bronchiectasis (n=4). Gel foam pellets and polyvinyl alcohol (PVA) particles were used as embolic material in 36 patients and 9 patients respectively. The angiographic signs of haemorrhage encountered were extravasation of contrast in 2 patients (4.4%), hypervascularisation in 42 (93.3%), broncho-pulmonary shunt in 13 (28.8%) and bronchial artery aneurysm in 1 patient (2.2%). Immediate control of bleeding occurred in 44 (97.7%) of 45 patients after embolization. Recurrent haemoptysis occurred in 4 cases (11.9%) more than 1 month after embolization but bleeding was less severe, than before treatment. This study suggests that bronchial artery embolization is an effective method of managing patients with severe haemoptysis, minor bleeding recurrences appear to be relatively infrequent.KEYWORDS: Embolization, Haemoptysis, Lung haemorrhage     

How robust are our methods of detecting impaired glomerular filtration rate in the intensive care unit?

Background: Serum creatinine is not a sensitive marker to assess early loss of renal function in acute kidney injury. Timed creatinine clearance and several formula used to predict glomreular filtration rate have not been validated.     

Knowledge-based localization of hippocampus in human brain MRI

We present a novel and efficient method for localization of human brain structures such as hippocampus. Landmark localization is important for segmentation and registration. This method follows a statistical roadmap, consisting of anatomical landmarks, to reach the desired structures. Using a set of desired and undesired landmarks, identified on a training set, we estimate Gaussian models and determine optimal search areas for desired landmarks. The statistical models form a set of rules to evaluate the extracted landmarks during the search procedure. When applied on 900 MR images of 10 epileptic patients, this method demonstrated an overall success rate of 83%.