Medicine and Health Sciences Commons^™

Emerging Applications Of Contrast-Enhanced Ultrasound In Trauma, Brenda Tester, Ji-Bin Liu, John R. Eisenbrey, George Koenig

Department of Radiology Faculty Papers

The use of contrast-enhanced ultrasound (CEUS) has expanded over the past decade to include a variety of diagnostic and therapeutic applications. These include urgent clinical situations that require timely diagnosis and subsequent treatment. With the introduction of microbubble ultrasound contrast agents (UCAs), CEUS provides increased sensitivity and specificity over conventional ultrasound. Within the trauma setting, CEUS benefits include point of care imaging and an ability to monitor perfusion in real-time. Additionally, UCAs are non-nephrotoxic, and can be used when contrast enhanced CT is contraindicated. In this review, we discuss recent advancements of CEUS within trauma settings.

The Use Of Computerized Tomography Scans In Elective Knee And Hip Arthroplasty-What Do They Tell Us And At What Risk?, Taylor D'Amore, Gregg R Klein, Jess H. Lonner

Rothman Institute Faculty Papers

The average background radiation exposure in the United States has nearly doubled over the previous quarter century, with almost all the increase derived from medical imaging. Nearly 2% of all cancers in the United States may be attributable to radiation from computerized tomography (CT) scans. Given the nondiagnostic nature of CT scans that are used in elective knee and hip arthroplasty today, special consideration should be given to the inherent risk of radiation exposure with routine use of this technology. Methods to decrease radiation exposure including modulating the settings of the CT machine and using alternative non-CT-based systems can decrease …

Machine Learning Based Medical Image Deepfake Detection: A Comparative Study, Siddharth Solaiyappan, Yuxin Wen

Engineering Faculty Articles and Research

Deep generative networks in recent years have reinforced the need for caution while consuming various modalities of digital information. One avenue of deepfake creation is aligned with injection and removal of tumors from medical scans. Failure to detect medical deepfakes can lead to large setbacks on hospital resources or even loss of life. This paper attempts to address the detection of such attacks with a structured case study. Specifically, we evaluate eight different machine learning algorithms, which include three conventional machine learning methods (Support Vector Machine, Random Forest, Decision Tree) and five deep learning models (DenseNet121, DenseNet201, ResNet50, ResNet101, VGG19) …

Single Center Retrospective Review Of Post-Laparotomy Ct Abdomen And Pelvis Findings And Trends, Dylan C. Steffey, Emad A. Chishti, Maximo J. Acevedo, Luis F. Acosta, James T. Lee

Radiology Faculty Publications

Purpose: To identify common findings visualized on CT following damage control laparotomy, including post-surgical changes and additional injuries, and to determine change in frequency of post-laparotomy CT at our institution over time.

Methods: Single institution, IRB-Exempt, retrospective review of the University of Kentucky trauma registry from 1/2006 to 2/2019 for all trauma patients undergoing exploratory laparotomy initially and subsequently undergoing CT of the abdomen and pelvis within 24 hours. Operative findings from surgical operation notes and findings reported on post-laparotomy CT were recorded, including vascular and solid organ injuries, operative changes, free intraperitoneal fluid/air, and retroperitoneal findings. Next steps in …

Virtual Simulated Implantation Of An Adult-Sized Left Ventricular Assist Device In A Pediatric Patient, Dilachew A Adebo, Santosh C Uppu, Avichal Aggarwal, Jorge D Salazar, Damien J Lapar

Student and Faculty Publications

There is very limited experience with simulated virtual implantation of left ventricular assist devices (LVADs) to assess device fitness in pediatric patients. In this clinical vignette, we report the case of a 9-year-old male patient with dilated cardiomyopathy who underwent successful placement of an LVAD after virtual simulated implantation was performed. (Level of Difficulty: Advanced.)