Automated detection and localization of pericardial effusion from point-of-care cardiac ultrasound examination.
Ilkay Yildiz PotterMegan M LeoAshkan VaziriJames A FeldmanPublished in: Medical & biological engineering & computing (2023)
Focused Assessment with Sonography in Trauma (FAST) exam is the standard of care for pericardial and abdominal free fluid detection in emergency medicine. Despite its life saving potential, FAST is underutilized due to requiring clinicians with appropriate training and practice. To aid ultrasound interpretation, the role of artificial intelligence has been studied, while leaving room for improvement in localization information and computation time. The purpose of this study was to develop and test a deep learning approach to rapidly and accurately identify both the presence and location of pericardial effusion on point-of-care ultrasound (POCUS) exams. Each cardiac POCUS exam is analyzed image-by-image via the state-of-the-art YoloV3 algorithm and pericardial effusion presence is determined from the most confident detection. We evaluate our approach over a dataset of POCUS exams (cardiac component of FAST and ultrasound), comprising 37 cases with pericardial effusion and 39 negative controls. Our algorithm attains 92% specificity and 89% sensitivity in pericardial effusion identification, outperforming existing deep learning approaches, and localizes pericardial effusion by 51% Intersection Over Union with ground-truth annotations. Moreover, image processing demonstrates only 57 ms latency. Experimental results demonstrate the feasibility of rapid and accurate pericardial effusion detection from POCUS exams for physician overread.
Keyphrases
- deep learning
- artificial intelligence
- loop mediated isothermal amplification
- machine learning
- convolutional neural network
- magnetic resonance imaging
- healthcare
- big data
- primary care
- left ventricular
- emergency department
- palliative care
- label free
- sensitive detection
- real time pcr
- emergency medicine
- high throughput
- chronic pain
- high resolution
- computed tomography
- contrast enhanced ultrasound
- atrial fibrillation
- contrast enhanced
- trauma patients