Multiparametric MRI ISODATA Ischemic Lesion Analysis

Abstract

Background and Purpose— The purpose of this study was to show that the computer segmentation algorithm Iterative Self-Organizing Data Analysis Technique (ISODATA), which integrates multiple MRI parameters (diffusion-weighted imaging [DWI], T2-weighted imaging [T2WI], and T1-weighted imaging [T1WI]) into a single composite image, is capable of defining the ischemic lesion in a time-independent manner equally as well as the MRI techniques considered the best for each phase after stroke onset (ie, perfusion weighted imaging [PWI] and DWI for the acute phase and T2WI for the outcome phase). Methods— We measured MRI parameters of PWI, DWI, T2WI, and T1WI from patients at the acute phase (Results— We included 11 patients; 9 (82%) were women, and 7 (64%) were black. The mean±SD age was 65.5±9.3 years (range, 45 to 82 years). The median NIHSS score was 15 (minimum, 4; maximum, 24)at the acute phase and 3 (minimum, 0; maximum, 22) at the outcome phase. The median time interval from stroke symptom onset to the acute MRI study was 10 hours (range, 6 to 29 hours), and the mean time interval to the outcome study was 93±11 days (range, 72 to 106 days). In the acute phase, the ISODATA lesion size had high correlation with the PWI lesion size ( r =0.95; 95% CI, 0.89 to 0.98; P r =0.83; 95% CI, 0.66 to 0.92; P r =0.67; 95% CI, 0.39 to 0.84; P =0.008) and moderate correlation with NIHSS score ( r =0.59; 95% CI, 0.02 to 0.88; P =0.06). In the outcome phase, the ISODATA lesion size had high correlation with the T2WI lesion size ( r =0.97; 95% CI, 0.94 to 0.99; P r =0.78; 95% CI, 0.34 to 0.94; P =0.004). Conclusions— The integrated ISODATA method can identify and characterize the ischemic lesion independently of time elapsed since stroke onset. The ISODATA lesion size highly correlates with the PWI and DWI lesion size in the acute phase and with the T2WI lesion size in the outcome phase of ischemic stroke, as well as with the clinical neurological status of the patient.