Enhancing the diagnostic efficacy of right-to-left shunt using robot-assisted transcranial Doppler: a quality improvement project.

Background: Stroke is the leading cause of adult disability worldwide, with approximately 30% of strokes remaining cryptogenic. One potential important etiology is a patent foramen ovale (PFO), which may contribute to stroke through paradoxical thromboembolism or thromboembolus formation. Recent advancements in robot-assisted transcranial Doppler (raTCD) have shown increased sensitivity in detecting right-to-left shunt (RLS) compared to transthoracic echocardiography (TTE), particularly in detecting the large shunts which are associated with higher stroke risk.

Methods: We conducted a retrospective quality improvement project at our regional stroke center to compare the performance of TTE and raTCD in identifying RLS in ischemic stroke patients. The study involved 148 patients admitted between February 2021 and February 2023. All patients underwent TTE and raTCD with agitated saline bubble contrast, with additional transesophageal echocardiography (TEE) at the treatment team's discretion. The primary metrics analyzed included differences in overall RLS detection and large RLS detection rates for raTCD, TTE and TEE.

Results: raTCD detected RLS in 60.1% of patients compared to 37.2% with TTE ( < 0.001), with a 42.6% detection rate for large shunts on raTCD versus 23.0% on TTE ( < 0.001). The sensitivity and specificity of raTCD were 92 and 87.5%, respectively, compared to 78.57 and 71.43% for TTE, using TEE as the gold standard. Nine patients underwent PFO closure, all correctly identified with large shunts by raTCD, while TTE missed or underestimated the PFO size in 44% of the cases.

Conclusion: raTCD significantly outperforms TTE in detecting RLS and large shunts, suggesting its integration into standard PFO workup protocols may enhance secondary stroke prevention. These findings support the adoption of raTCD as a complementary diagnostic tool alongside TTE and TEE for more accurate PFO detection and risk stratification.