Combining MRI with NIHSS Thresholds to Predict Outcome in Acute Ischemic Stroke: Value for Patient Selection

Abstract

Background and Purpose We sought to validate a previously described model combining clinical and MRI thresholds to predict outcome in acute ischemic stroke in a larger cohort, and evaluate effects of reperfusion therapy and stroke side. Materials and Methods 123 consecutive anterior circulation AIS patients underwent MRI within 6 hours of stroke onset. DWI and PWI volumes were measured. Lesion volume and NIH Stroke Scale Score thresholds were used in models predicting good three-month clinical outcome (mRS 0-2). Patients were stratified by treatment and stroke side. Results ROC analysis demonstrated 95.6% and 100% specificity for DWI > 70mL and NIH Stroke Scale Score > 20 to predict poor outcome, and 92.7% and 91.3% specificity for PWI (mean transit time) < 50mL and NIH Stroke Scale Score < 8 to predict good outcome. Combining clinical and imaging thresholds led to 88.8% (71/80) positive predictive value with 65.0% (80/123) prognostic yield. 100 percent specific thresholds for DWI (103 versus 31 mL) and NIHSSS (20 versus 17) to predict poor outcome were significantly higher in treated (intravenous and/or intraarterial) versus untreated patients. Prognostic yield was lower in right versus left-sided strokes for all thresholds (10.4-20.7 vs. 16.9-40.0%). Patients with right-sided strokes had higher 100 percent specific DWI (103.1 vs. 74.8 mL) thresholds for poor outcome, and positive predictive value was lower. Conclusion Our predictive model is validated in a much larger patient cohort. Outcome may be predicted in up to two-thirds of patients, and thresholds are affected by stroke side and reperfusion therapy.

Impact of Leukoaraiosis Burden on Hemispheric Lateralization of the National Institutes of Health Stroke Scale Deficit in Acute Ischemic Stroke

“…6,20 In addition, ongoing efforts are aimed at optimizing patient selection for endovascular stroke therapies based on imaging and clinical parameters. 21,22 Our results emphasize that a single lower NIHSS inclusion threshold may be too restrictive particularly for patients with a right-hemispheric stroke and otherwise good brain health (as indicated by none-to-mild leukoaraiosis). Accordingly, future studies aimed at creating predictive tools for patient selection may be improved by adjusting for the side of infarction 22 and degree of preexisting white matter injury; and one should not refrain from acute stroke therapy in patients particularly with right-hemispheric infarctions and a relatively low NIHSS score.…”

Imaging predictors of procedural and clinical outcome in endovascular acute stroke therapy

“…In a study relating DWI lesion volume to poor outcome (mRS >2), the 95 % specificity lesion volume was 51.8 mL for the left hemisphere compared to 98.5 mL for right hemisphere involvement, indicating that non-dominant hemisphere strokes are better tolerated [16]. While some of this difference relates to an inherent bias of the NIHSS scoring towards dominant hemisphere stroke, it is clear that a dominant hemisphere infarct portends a worse prognosis.…”

“…Cerebral blood volume (CBV) map from the perfusion CT show decreased CBV corresponding to those territories consistent with a large core of completed infarct (e, f). The Tmax maps demonstrate a matched perfusion deficit (g, h) again demonstrating the link between lesion size at presentation and outcome [16]. When measured by MRI at 48 h, the infarct volume is an independent predictor of outcome [18].…”

Effect of color visualization and display hardware on the visual assessment of pseudocolor medical images

“…4,17 One medical imaging modality of current interest that relies on color is the assessment of functional images. [20][21][22][23][24][25][26] Even though significant effort is being directed at developing software for automatic image interpretation, computer-aided diagnosis (CAD) tools are still semiautomatic, and human reader studies are necessary for initial setup and validation as reported in a recent example 27 on the development of an automatic segmentation methodology considering manual tracing as the gold standard.…”

“…Perfusion images have a critical role in the therapy decision tree for stroke patients and in noninvasive diagnosis, staging, and therapy response assessment of tumors. [20][21][22][23][24][25][26] Typical clinical colorbased assessment tasks include comparison between healthy and pathological areas and between the same area at different time points in a sequential study protocol. The usefulness of pseudocolor presentation has also been recently highlighted by Saba et al,28 in the evaluation of noncontrast computed tomography imaging for possible carotid artery dissection.…”