Magnetic Resonance Imaging as a Diagnostic Tool for Ilio-Femoro-Caval Deep Venous Thrombosis.
Lisbeth LyhneKim Christian HoulindJohnny ChristensenRadu L VijdeaMeinhard R HansenMalene Roland Vils PedersenHelle PrechtPublished in: Journal of imaging (2024)
This study aimed to test the accuracy of a magnetic resonance imaging (MRI)-based method to detect and characterise deep venous thrombosis (DVT) in the ilio-femoro-caval veins. Patients with verified DVT in the lower extremities with extension of the thrombi to the iliac veins, who were suitable for catheter-based venous thrombolysis, were included in this study. Before the intervention, magnetic resonance venography (MRV) was performed, and the ilio-femoro-caval veins were independently evaluated for normal appearance, stenosis, and occlusion by two single-blinded observers. The same procedure was used to evaluate digital subtraction phlebography (DSP), considered to be the gold standard, which made it possible to compare the results. A total of 123 patients were included for MRV and DSP, resulting in 246 image sets to be analysed. In total, 496 segments were analysed for occlusion, stenosis, or normal appearance. The highest sensitivity compared occlusion with either normal or stenosis (0.98) in MRV, while the lowest was found between stenosis and normal (0.84). Specificity varied from 0.59 (stenosis >< occlusion) to 0.94 (occlusion >< normal). The Kappa statistic was calculated as a measure of inter-observer agreement. The kappa value for MRV was 0.91 and for DSP, 0.80. In conclusion, MRV represents a sensitive method to analyse DVT in the pelvis veins with advantages such as no radiation and contrast and the possibility to investigate the anatomical relationship in the area.
Keyphrases
- inferior vena cava
- magnetic resonance imaging
- magnetic resonance
- contrast enhanced
- pulmonary embolism
- vena cava
- computed tomography
- randomized controlled trial
- nuclear factor
- end stage renal disease
- ejection fraction
- newly diagnosed
- machine learning
- deep learning
- minimally invasive
- radiation therapy
- diffusion weighted imaging
- patient reported outcomes
- acute ischemic stroke