Use of ultrasound and magnetic resonance image processing for evaluation of supraspinatus and biceps tendon pathology in dogs

Shoulder injuries, especially those caused by rotator cuff tears, are a pervasive problem in human and canine patients. The ability to quickly and accurately diagnose rotator cuff tears is important for early and targeted treatment. Prior clinical work has demonstrated that ultrasound and magnetic resonance imaging effectively diagnose these tears. However, there has been limited use of quantitative image processing to validate the imaging and clinical findings. The aim of our study was to evaluate the use of medical image processing to objectively assess tendon injuries in ultrasound and magnetic resonance images of biceps and supraspinatus tendons of dogs. Histogram peak intensity measurements were performed on regions of interest drawn on ultrasound and magnetic resonance images of the supraspinatus and biceps muscles and tendons in 5 dogs with known front limb lameness and pain localized to the shoulder joints. Peak intensity increased from untorn supraspinatus and biceps tendon to torn tendon at a greater magnitude in ultrasound imaging than in magnetic resonance imaging. The histogram analysis suggested that ultrasound imaging is a superior method for diagnosing torn supraspinatus and biceps tendons based on contrast. Furthermore, this conclusion is strengthened by practical considerations that favor ultrasound imaging as a primary form of diagnosis

Use of Software Tools to Implement Quality Control of Ultrasound Images in a Large Clinical Trial

Research Question This thesis aims to answer the question as to whether software tools might be developed for automating the analysis of images used to measure ovaries in transvaginal sonography (TVS) exams. Such tools would allow the routine collection of independent and objective metrics at low cost and might be used to drive a programme of continuous Quality Improvement (QI) in TVS scanning. The tools will be assessed by processing images from thousands of TVS exams performed by the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). Background This research is important because TVS is core to any ovarian cancer (OC) screening strategy yet independent and objective quality control (QC) metrics for this procedure are not routinely obtained due to the high cost of manual image inspection. Improving the quality of TVS in the National Health Service (NHS) would assist in the early diagnosis of the disease and result in improved outcome for some women. Therefore, the research has clear translational potential for the >1.2 million scans performed annually by the NHS. Research Findings A study performed to process images from 1,000 TVS exams has shown the tool produces accurate and reliable QC metrics. A further study revealed that over half of these exams should have been classified as unsatisfactory as an expert review of the images showed that that the sonographer had mistakenly measured a structure that was not an ovary. It also reported a correlation between such ovary visualisation and a novel metric (DCR) measured by the tools from the examination images. Conclusion The research results suggest both a need to improve the quality of TVS scanning and the viability of achieving this objective by introducing a QI programme driven by metrics gathered by software tools able to analyze the images used to measure ovaries