Contrast Transcranial Doppler Can Diagnose Large Patent Foramen Ovale
Background: Contrast transesophageal echocardiography (c-TEE) and contrast transcranial Doppler (c-TCD) are useful diagnostic tools for detecting right-to-left shunts (RLS). However, the diagnostic accuracy of c-TCD for patent foramen ovale (PFO) remains uncertain. We investigated the relationship b...
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Veröffentlicht in: | Cerebrovascular diseases (Basel, Switzerland) Switzerland), 2009-01, Vol.27 (3), p.230-234 |
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Zusammenfassung: | Background: Contrast transesophageal echocardiography (c-TEE) and contrast transcranial Doppler (c-TCD) are useful diagnostic tools for detecting right-to-left shunts (RLS). However, the diagnostic accuracy of c-TCD for patent foramen ovale (PFO) remains uncertain. We investigated the relationship between the size of PFO determined by c-TEE and c-TCD findings and assessed the detectable rate of RLS by c-TCD. Methods: We assessed RLS three times using simultaneous c-TCD and c-TEE in 107 patients (321 examinations). We classified all of ultrasound examinations into three groups by size according to microbubbles on c-TEE, such as no PFO (0 microbubble), small PFO (1–29 microbubbles) and large PFO (≥30 microbubbles). We also calculated the number of microembolic signals (MES) on c-TCD and evaluated the association between PFO size on c-TEE and MES count on c-TCD. Results: In the present study, c-TEE detected RLS in 105 (33%; small PFO, n = 78; large PFO, n = 27), and c-TCD detected RLS in 49 (15%) of 321 examinations. Among 78 examinations with small PFO, MES were found in only 19 (24%) on c-TCD. In contrast, of all 27 examinations with large PFO, MES were found on c-TCD. Also, c-TCD were able to detect MES in 3 of 216 examinations among the no-PFO group. When ≥2 MES on c-TCD was established as the cutoff to predict large PFO on c-TEE, the sensitivity, specificity and accuracy were 96.3, 96.8, and 96.9%, respectively. Conclusion: When two or more MES were determined by c-TCD, large PFO could be accurately diagnosed. |
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ISSN: | 1015-9770 1421-9786 |
DOI: | 10.1159/000196820 |