clinical study

Initial Experience With an Artificial Intelligence System for Pulmonary Embolism Response Team Activation and Coordination in a Large Urban Health System

Materials & Methods

All CT pulmonary angiograms between Jan. and Aug. 2022, were triaged using an AI-based automated PERT activation algorithm. AI PERT activation was based on the location of clot (central vs. peripheral) and CT evidence of right ventricular strain (RV to LV ratio greater than 1.0). A retrospective review was conducted of all institutional PERT activations over the same period.

Results

Pulmonary embolism was identified on 954 CT pulmonary angiograms, and the AI algorithm sent an automated PERT notification on 155 (16.2%) of these. The institutional PERT was formally activated for 121 patients, of whom 38 underwent at least one intervention beyond anticoagulation alone (three systemic thrombolysis, four surgical thrombectomy, six catheter-directed thrombolysis, 19 percutaneous thrombectomy, 15 inferior vena cava filter, and two ECMO). Thirty-two patients who initially presented to satellite facilities were transferred to a hospital with both endovascular and open cardiothoracic surgery capabilities. The sensitivity and specificity of the AI algorithm for identifying true PERT activations were 62.8% and 90.5% respectively. Among patients requiring transfer for possible intervention, sensitivity was 84.4% and specificity 88.1%. Among patients who underwent any intervention, sensitivity was 78.9% and specificity 86.4%. When catheter-directed intervention is considered separately, sensitivity and specificity were 95.8% and 85.8% respectively.

Conclusions

The system’s initial experience demonstrates high sensitivity and specificity of the AI algorithm in identifying candidates for endovascular pulmonary embolism intervention despite poor correlation with PERT activations overall. Ongoing research will further assess the clinical benefits and optimal uses for this technology.

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