It is commonly believed that the size of a pneumothorax is an important determinant of treatment decision, in particular regarding whether chest tube drainage (CTD) is required. However, the volumetric quantification of pneumothoraces has not routinely been performed in clinics. In this paper, we introduced an automated computer-aided volumetry (CAV) scheme for quantification of volume of pneumothoraces in chest multi-detect CT (MDCT) images. Moreover, we investigated the impact of accurate volume of pneumothoraces in the improvement of the performance in decision-making regarding CTD in the management of traumatic pneumothoraces. For this purpose, an occurrence frequency map was calculated for quantitative analysis of the importance of each clinical parameter in the decision-making regarding CTD by a computer simulation of decision-making using a genetic algorithm (GA) and a support vector machine (SVM). A total of 14 clinical parameters, including volume of pneumothorax calculated by our CAV scheme, was collected as parameters available for decision-making. The results showed that volume was the dominant parameter in decision-making regarding CTD, with an occurrence frequency value of 1.00. The results also indicated that the inclusion of volume provided the best performance that was statistically significant compared to the other tests in which volume was excluded from the clinical parameters. This study provides the scientific evidence for the application of CAV scheme in MDCT volumetric quantification of pneumothoraces in the management of clinically stable chest trauma patients with traumatic pneumothorax.
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http://dx.doi.org/10.1016/j.compmedimag.2012.03.005 | DOI Listing |
J Am Heart Assoc
January 2025
Department of Cardiology Beijing Anzhen Hospital, Capital Medical University Beijing China.
Background: Data on the predictive value of coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) for long-term outcomes are limited.
Methods And Results: A retrospective pooled analysis of individual patient data was performed. Deep-learning-based CT-FFR was calculated.
Ann Thorac Surg Short Rep
September 2024
Division of Cardiothoracic Surgery, Barnes-Jewish Hospital, Washington University-St Louis Medical School, St Louis, Missouri.
Background: Tricuspid valve surgical procedures (TVS) concomitant with mitral valve (MV) surgical procedures for less than severe tricuspid regurgitation (TR) remains controversial. This study examined the long-term outcomes of patients with moderate or mild to moderate TR undergoing MV surgical procedures with or without TVS.
Methods: Patients with moderate or mild to moderate TR undergoing MV replacement or repair between January 2002 and June 2021 were included.
Cardiovasc Diagn Ther
December 2024
Operational Research Center in Healthcare, Near East University, Nicosia, Turkey.
Background: Cardiovascular diseases (CVDs) continue to be the world's greatest cause of death. To evaluate heart function and diagnose coronary artery disease (CAD), myocardial perfusion imaging (MPI) has become essential. Artificial intelligence (AI) methods have been incorporated into diagnostic methods such as MPI to improve patient outcomes in recent years.
View Article and Find Full Text PDFChest
January 2025
Department of Medicine, University of British Columbia. Electronic address:
Topic Importance: Accurate assessment of a patient's volume status is crucial in many conditions, informing decisions on fluid prescribing, vasoactive agents, and decongestive therapies. Determining a patient's volume status is challenging, due to limitations in examination and investigations and the complexities of fluid homeostasis in disease states. Point-of-care ultrasound (POCUS) is useful in assessing hemodynamic parameters related to volume status, fluid responsiveness, and fluid tolerance.
View Article and Find Full Text PDFClin Chem Lab Med
January 2025
Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada.
Objectives: Careful consideration of the pre-analytical process for urine examination is essential to avoid errors and support accurate results and decision-making. Our objective was to assess the impact of various pre-analytical factors on urine test strip and quantitative chemistry results, including stability, tube type, fill volume, and centrifugation.
Methods: Residual random urine specimens were identified.
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