Whole brain CT perfusion deficits using 320-detector-row CT scanner in TIA patients are associated with ABCD2 score

Abstract

Background: Transient ischemic attacks (TIA) are cerebral ischemic events without infarction. The uses of CT perfusion (CTP) techniques such as cerebral blood volume (CBV), time to peak (TTP), mean transit time (MTT) and cerebral blood flow (CBF) provide real time data about ischemia. It has been shown that CTP changes occur in less sensitive CTP scanners in patients with TIA. Larger detector row CTP (whole brain perfusion studies) may show that CTP abnormalities are more prevalent than previously noted. It is also unclear if these changes are associated with TIA severity. Objective: To demonstrate that TIA patients are associated with perfusion deficits using whole brain 320-detector-row CT perfusion, and to determine an association between ABCD2 score and perfusion deficit using whole brain perfusion. Methods: We retrospectively reviewed all TIA patients for CTP deficits from 2008–2010. Perfusion imaging was reviewed at admission; and it was determined if a perfusion deficit was present along with vascular territory involved. Results: Of 364 TIA patients, 62 patients had CTP deficits. The largest group of patients had MCA territory involved with 48 of 62 patients (77.42%). The most common perfusion abnormality was increased TTP with 46 patients (74.19%). The ABCD2 score was reviewed in association with perfusion deficit. Increased age >60, severe hypertension (>180/100 mmHg), patients with speech abnormalities, and duration of symptoms >10 min were associated with a perfusion deficit but history of diabetes or minimal/moderate hypertension (140/90–179/99 mmHg) was not. There was no association between motor deficit and perfusion abnormality. Conclusion: Perfusion deficits are found in TIA patients using whole brain CTP and associated with components of the ABCD2 score.

KEYWORDS: :

• CT perfusion
• transient ischemic attack
• ABCD2 score
• TIA
• stroke

Acknowledgements

The authors would like to thank Ellen Baker, Debbie Steck and Karen Olsen for their work on the stroke database.