Optimizing image registration and infarct definition in stroke research. Issue 3 (20th January 2017)

• Record Type: Journal Article
• Authors: Harston, George W. J.; Minks, David; Sheerin, Fintan; Payne, Stephen J.; Chappell, Michael; Jezzard, Peter; Jenkinson, Mark; Kennedy, James
• Is Part Of: Annals of clinical and translational neurology. Volume 4:Issue 3(2017)
• Page Start: 166
• Page End: 174
• Publication Date: 2017-01-20
• Subjects: Nervous system -- Diseases -- Periodicals; Neurology -- Periodicals; 616.8005
• DOI: 10.1002/acn3.388
• Languages: English
• ISSNs: 2328-9503

Abstract

Abstract: Objective: Accurate representation of final infarct volume is essential for assessing the efficacy of stroke interventions in imaging‐based studies. This study defines the impact of image registration methods used at different timepoints following stroke, and the implications for infarct definition in stroke research. Methods: Patients presenting with acute ischemic stroke were imaged serially using magnetic resonance imaging. Infarct volume was defined manually using four metrics: 24‐h b1000 imaging; 1‐week and 1‐month T2‐weighted FLAIR; and automatically using predefined thresholds of ADC at 24 h. Infarct overlap statistics and volumes were compared across timepoints following both rigid body and nonlinear image registration to the presenting MRI. The effect of nonlinear registration on a hypothetical trial sample size was calculated. Results: Thirty‐seven patients were included. Nonlinear registration improved infarct overlap statistics and consistency of total infarct volumes across timepoints, and reduced infarct volumes by 4.0 mL (13.1%) and 7.1 mL (18.2%) at 24 h and 1 week, respectively, compared to rigid body registration. Infarct volume at 24 h, defined using a predetermined ADC threshold, was less sensitive to infarction than b1000 imaging. 1‐week T2‐weighted FLAIR imaging was the most accurate representation of final infarct volume. Nonlinear registration reduced hypothetical trial sample size, independent of infarct volume, by an average of 13%. Interpretation: Nonlinear image registration may offer the opportunity of improving the accuracy of infarct definition in serial imaging studies compared to rigid body registration, helping to overcome the challenges of anatomical distortions at subacute timepoints, and reducing sample size for imaging‐based clinical trials.