RESUMEN
OBJECTIVE: To investigate power of computed tomography venography (CTV) to identify and characterize iliac vein obstruction (IVO) compared with intravascular ultrasound (IVUS) examination in highly symptomatic patients with chronic venous disease (CVD). METHODS: CVD CEAP C3-6 limbs with visual analog scale for pain score of greater than 3 and/or Venous Clinical Severity Scale of greater than 8 were prospectively investigated with CTV and IVUS examination. The segment of maximum IVO was verified and categorically classified: group I, 0% to 49%; group II, 50% to 79%; and group III, 80% or greater. The CTV's screening power to detect the point and degree of maximum IVO was compared with IVUS. RESULTS: The CTV point of maximum IVO was 80% in the left limb, 10% in the right limb, 10% bilaterally; 2% in the inferior vena cava; 91% in the common iliac vein (CIV) confluence (41.6% below the CIV confluence, 34.5 at the CIV confluence, and 23.9% above the CIV confluence); 7% at the external iliac vein (kappa index 0.841; P < .001, when compared with IVUS). The distal venous segment considered free of obstruction was above inguinal ligament: 68% (CIV, 47%; external iliac vein, 21%) 32% below the inguinal ligament (common femoral vein, 26%; deep femoral vein, 6%) (kappa index 0.671; P = .023, when compared with IVUS). The power of CTV to detect an IVO of 50% or greater (groups II and III) when compared with IVUS achieved a sensitivity and specificity ratio of 94.0% and 79.2%, respectively. The positive predictive value was 94%, the negative predictive value was 79.1%, accuracy was 86.7% (kappa, 0.733), and interobserver agreement was 92.1% (95% confidence interval, 87.1-97.7; kappa, 0.899). CONCLUSIONS: CTV is a powerful screening method in determining the precise point of compression and classifying IVO in limbs with symptomatic CVD when compared with IVUS. The prevalence of an obstruction above the iliac vein confluence is significant and should be considered in iliac vein stenting treatment strategy. The tomographic classification system proposed here may help to define the optimum technique of treatment, prognosis, and comparison of outcome results.