Neil R Chatterjee1, Sameer A Ansari1, Parmede Vakil1, Shyam Prabhakaran2, Timothy J Carroll3, Michael C Hurley1. 1. Department of Radiology, Northwestern University Feinberg School of Medicine, 737N Michigan Suite 1600, Chicago, IL, USA. 2. Department of Neurology, Northwestern University Feinberg School of Medicine, Abbott Hall Suite 1123, 710 N Lake Shore Drive, Chicago, IL, USA. 3. Department of Radiology, Northwestern University Feinberg School of Medicine, 737N Michigan Suite 1600, Chicago, IL, USA. Electronic address: t-carroll@northwestern.edu.
Abstract
PURPOSE: To determine the feasibility of automatic vascular territory region of interest (ROI) construction as a method for standardized quantification of cerebral blood flow (CBF) images. MATERIALS AND METHODS: An algorithm for automatic construction of vascular territory ROIs was performed on 10 healthy controls and 25 patients with perfusion abnormalities identified by retrospective chart review. The ROIs were used to quantify perfusion asymmetry for each territory, and perfusion asymmetry was compared in the two cohorts and against blinded neuroradiologist interpretation. The algorithm was additionally applied to a separate cohort of 23 prospectively enrolled patients and perfusion asymmetry was correlated against clinical variables. RESULTS: There was significantly greater perfusion asymmetry in territories graded by neuroradiologists as hypoperfused compared to those graded as normally perfused (p<.05) and compared to healthy volunteers (p<.01). An ROC analysis showed that perfusion asymmetry was sensitive and specific for identifying hypoperfusion in vascular territories (84.9% sensitivity and 90.5% specificity for a threshold asymmetry index of .829). In the prospective cohort, perfusion asymmetry was correlated with initial NIH stroke scale (NIHSS) (p<.01) and length of stay (p<.05). CONCLUSIONS: Automatic construction of vascular territory ROIs and calculation of perfusion asymmetry is a feasible method for analyzing CBF images. Because the technique is rapid and minimizes bias, it can facilitate analysis of larger scale research studies.
PURPOSE: To determine the feasibility of automatic vascular territory region of interest (ROI) construction as a method for standardized quantification of cerebral blood flow (CBF) images. MATERIALS AND METHODS: An algorithm for automatic construction of vascular territory ROIs was performed on 10 healthy controls and 25 patients with perfusion abnormalities identified by retrospective chart review. The ROIs were used to quantify perfusion asymmetry for each territory, and perfusion asymmetry was compared in the two cohorts and against blinded neuroradiologist interpretation. The algorithm was additionally applied to a separate cohort of 23 prospectively enrolled patients and perfusion asymmetry was correlated against clinical variables. RESULTS: There was significantly greater perfusion asymmetry in territories graded by neuroradiologists as hypoperfused compared to those graded as normally perfused (p<.05) and compared to healthy volunteers (p<.01). An ROC analysis showed that perfusion asymmetry was sensitive and specific for identifying hypoperfusion in vascular territories (84.9% sensitivity and 90.5% specificity for a threshold asymmetry index of .829). In the prospective cohort, perfusion asymmetry was correlated with initial NIH stroke scale (NIHSS) (p<.01) and length of stay (p<.05). CONCLUSIONS: Automatic construction of vascular territory ROIs and calculation of perfusion asymmetry is a feasible method for analyzing CBF images. Because the technique is rapid and minimizes bias, it can facilitate analysis of larger scale research studies.
Authors: Manabu Inoue; Michael Mlynash; Matus Straka; Stephanie Kemp; Tudor G Jovin; Aaryani Tipirneni; Scott A Hamilton; Michael P Marks; Roland Bammer; Maarten G Lansberg; Gregory W Albers Journal: Stroke Date: 2013-05-23 Impact factor: 7.914
Authors: Jana Katharina Wrosch; Bastian Volbers; Philipp Gölitz; Daniel Frederic Gilbert; Stefan Schwab; Arnd Dörfler; Johannes Kornhuber; Teja Wolfgang Groemer Journal: Front Neurol Date: 2015-11-19 Impact factor: 4.003