A semi-automated segmentation method for detection of pulmonary embolism in True-FISP MRI sequences
This addresses the need for a non-ionizing, accurate diagnostic method for pulmonary embolism in clinical settings, representing an incremental improvement over existing MRI techniques.
The researchers tackled the problem of detecting pulmonary embolism in True-FISP MRI sequences, which is prone to artifacts that reduce diagnostic accuracy to 94%, by proposing a segmentation algorithm that increased diagnostic accuracy by 6% to match standard CT angiography levels.
Pulmonary embolism (PE) is a highly mortal disease, currently assessed by pulmonary CT angiography. True-FISP MRI has emerged as an innocuous alternative that does not hold many of the limitations of x-ray imaging. However, True-FISP MRI is very sensitive to turbulent blood flow, generating artifacts that may resemble fake clots in the pulmonary vasculature. These misinterpretations reduce its overall diagnostic accuracy to 94%, limiting a wider use in clinical environments. A new segmentation algorithm is proposed to confirm the presence of real pulmonary clots in True-FISP MR images by quantitative means, measuring the shape, intensity, and solidity of the formation. The algorithm was evaluated in 37 patients. The developed method increased the diagnostic accuracy of expert observers assessing Pulmonary True-FISP MRI sequences by 6% without the use of ionizing radiation, achieving a diagnostic accuracy comparable to standard CT angiography.