Enhancement of virtual colonoscopy system.

Colorectal cancer is the fourth most common cancer, and the fourth leading cause of cancer related death in the United States. It also happens to be one of the most preventable cancers provided an individual performs a regular screening. For years colonoscopy via colonoscope was the only method for colorectal cancer screening. In the past decade, colonography or virtual colonoscopy (VC) has become an alternative (or supplement) to the traditional colonoscopy. VC has become a much researched topic since its introduction in the mid-nineties. Various visualization methods have been introduced including: traditional flythrough, colon flattening, and unfolded-cube projection. In recent years, the CVIP Lab has introduced a patented visualization method for VC called flyover. This novel visualization method provides complete visualization of the large intestine without significant modification to the rendered three-dimensional model. In this thesis, a CVIP Lab VC interface was developed using Lab software to segment, extract the centerline, split (for flyover), and visualize the large intestine. This system includes adaptive level sets software to perform large intestine segmentation, and CVIP Lab patented curve skeletons software to extract the large intestine centerline. This software suite has not been combined in this manner before so the system stands as a unique contribution to the CVIP Lab colon project. The system is also a novel VC pipeline when compared to other academic and commercial VC methods. The complete system is capable of segmenting, finding the centerline, splitting, and visualizing a large intestine with a limited number of slices (~350 slices) for VC in approximately four and a half minutes. Complete CT scans were also validated with the centerline extraction external to the system (since the curve skeletons code used for centerline extraction cause memory exceptions because of high memory utilization)

Focal Spot, Fall/Winter 2003/2004

https://digitalcommons.wustl.edu/focal_spot_archives/1095/thumbnail.jp

Colonoscopy and Colorectal Cancer Screening

Colorectal cancer (CRC) represents a major public health problem worldwide. Fortunately most CRCs originate from a precursor lesion, the adenoma, which is accessible and removable. This is the rationale for CRC screening programs, which are aimed to diagnose CRC at an early stage or even better to detect and resect the advanced adenoma before CRC has developed. In this background colonoscopy emerges as the main tool to achieve these goals with recent evidence supporting its role in CRC prevention. This book deals with several topics to be faced when implementing a CRC screening program. The interested reader will learn about the rationale and challenges of implementing such a program, the management of the detected lesions, the prevention of complications of colonoscopy, and finally the use of other screening modalities that are emerging as valuable alternatives. The relevance of the topics covered in it and the updated evidence included by the authors turn this book into a very useful tool to introduce the reader in this amazing and evolving field

Focal Spot, Spring 2009

https://digitalcommons.wustl.edu/focal_spot_archives/1111/thumbnail.jp

Focal Spot, Summer 1999

https://digitalcommons.wustl.edu/focal_spot_archives/1082/thumbnail.jp

An evaluation of a checklist in Musculoskeletal (MSK) radiographic image interpretation when using Artificial Intelligence (AI)

Background: AI is being used increasingly in image interpretation tasks. There are challenges for its optimal use in reporting environments. Human reliance on technology and bias can cause decision errors. Trust issues exist amongst radiologists and radiographers in both over-reliance (automation bias) and reluctance in AI use for decision support. A checklist, used with the AI to mitigate against such biases, may optimise the use of AI technologies and promote good decision hygiene. Method: A checklist, to be used in image interpretation with AI assistance, was developed. Participants interpreted 20 examinations with AI assistance and then re- interpreted the 20 examinations with AI and a checklist. The MSK images were presented to radiographers as patient examinations to replicate the image interpretation task in clinical practice. Image diagnosis and confidence levels on the diagnosis provided were collected following each interpretation. The participant perception of the use of the checklist was investigated via a questionnaire.Results: Data collection and analysis are underway and will be completed at the European Congress of Radiology in Vienna, March 2023. The impact of the use of a checklist in image interpretation with AI will be evaluated. Changes in accuracy and confidence will be investigated and results will be presented. Participant feedback will be analysed to determine perceptions and impact of the checklist also. Conclusion: A novel checklist has been developed to aid the interpretation of images when using AI. The checklist has been tested for its use in assisting radiographers in MSK image interpretation when using AI.<br/

Cardiovascular computed tomography in cardiovascular disease: An overview of its applications from diagnosis to prediction

Cardiovascular computed tomography angiography (CTA) is a widely used imaging modality in the diagnosis of cardiovascular disease. Advancements in CT imaging technology have further advanced its applications from high diagnostic value to minimising radiation exposure to patients. In addition to the standard application of assessing vascular lumen changes, CTA-derived applications including 3D printed personalised models, 3D visualisations such as virtual endoscopy, virtual reality, augmented reality and mixed reality, as well as CT-derived hemodynamic flow analysis and fractional flow reserve (FFRCT) greatly enhance the diagnostic performance of CTA in cardiovascular disease. The widespread application of artificial intelligence in medicine also significantly contributes to the clinical value of CTA in cardiovascular disease. Clinical value of CTA has extended from the initial diagnosis to identification of vulnerable lesions, and prediction of disease extent, hence improving patient care and management. In this review article, as an active researcher in cardiovascular imaging for more than 20 years, I will provide an overview of cardiovascular CTA in cardiovascular disease. It is expected that this review will provide readers with an update of CTA applications, from the initial lumen assessment to recent developments utilising latest novel imaging and visualisation technologies. It will serve as a useful resource for researchers and clinicians to judiciously use the cardiovascular CT in clinical practice

Focal Spot, Winter 2006/2007

https://digitalcommons.wustl.edu/focal_spot_archives/1104/thumbnail.jp