BACKGROUND AND PURPOSE: In the clinical setting, there is a need to perform mismatch measurements quickly and easily on the MR imaging scanner to determine the specific amount of treatable penumbra. The objective of this study was to quantify the agreement of the ABC/2 method with the established planimetric method. MATERIALS AND METHODS: Patients (n = 193) were selected from the NINDS Natural History Stroke Registry if they 1) were treated with standard intravenous rtPA, 2) had a pretreatment MR imaging with evaluable DWI and PWI, and 3) had an acute ischemic stroke lesion. A rater placed the linear diameters to measure the largest DWI and MTT lesion areas in 3 perpendicular axes-A, B, and C-and then used the ABC/2 formula to calculate lesion volumes. A separate rater measured the planimetric volumes. Multiple mismatch thresholds were used, including MTT volume - DWI volume ≥50 mL versus ≥60 mL and (MTT volume - DWI volume)/MTT volume ≥20% versus MTT/DWI = 1.8. RESULTS: Compared with the planimetric method, the ABC/2 method had high sensitivity (0.91), specificity (0.90), accuracy (0.91), PPV (0.90), and NPV (0.91) to quantify mismatch by use of the ≥50 mL definition. The Spearman correlation coefficients were 0.846 and 0.876, respectively, for the DWI and MTT measurements. The inter-rater Bland-Altman plots demonstrated 95%, 95%, and 97% agreement for the DWI, MTT, and mismatch measurements. CONCLUSIONS: The ABC/2 method is highly reliable and accurate for quantifying the specific amount of MR imaging-determined mismatch and therefore is a potential tool to quickly calculate a treatable mismatch pattern.
BACKGROUND AND PURPOSE: In the clinical setting, there is a need to perform mismatch measurements quickly and easily on the MR imaging scanner to determine the specific amount of treatable penumbra. The objective of this study was to quantify the agreement of the ABC/2 method with the established planimetric method. MATERIALS AND METHODS:Patients (n = 193) were selected from the NINDS Natural History Stroke Registry if they 1) were treated with standard intravenous rtPA, 2) had a pretreatment MR imaging with evaluable DWI and PWI, and 3) had an acute ischemic stroke lesion. A rater placed the linear diameters to measure the largest DWI and MTT lesion areas in 3 perpendicular axes-A, B, and C-and then used the ABC/2 formula to calculate lesion volumes. A separate rater measured the planimetric volumes. Multiple mismatch thresholds were used, including MTT volume - DWI volume ≥50 mL versus ≥60 mL and (MTT volume - DWI volume)/MTT volume ≥20% versus MTT/DWI = 1.8. RESULTS: Compared with the planimetric method, the ABC/2 method had high sensitivity (0.91), specificity (0.90), accuracy (0.91), PPV (0.90), and NPV (0.91) to quantify mismatch by use of the ≥50 mL definition. The Spearman correlation coefficients were 0.846 and 0.876, respectively, for the DWI and MTT measurements. The inter-rater Bland-Altman plots demonstrated 95%, 95%, and 97% agreement for the DWI, MTT, and mismatch measurements. CONCLUSIONS: The ABC/2 method is highly reliable and accurate for quantifying the specific amount of MR imaging-determined mismatch and therefore is a potential tool to quickly calculate a treatable mismatch pattern.
Authors: K S Butcher; M Parsons; L MacGregor; P A Barber; J Chalk; C Bladin; C Levi; T Kimber; D Schultz; J Fink; B Tress; G Donnan; S Davis Journal: Stroke Date: 2005-06 Impact factor: 7.914
Authors: Hagen B Huttner; Thorsten Steiner; Marius Hartmann; Martin Köhrmann; Eric Juettler; Stephan Mueller; Johannes Wikner; Uta Meyding-Lamade; Peter Schramm; Stefan Schwab; Peter D Schellinger Journal: Stroke Date: 2005-12-22 Impact factor: 7.914
Authors: Gregory W Albers; Vincent N Thijs; Lawrence Wechsler; Stephanie Kemp; Gottfried Schlaug; Elaine Skalabrin; Roland Bammer; Wataru Kakuda; Maarten G Lansberg; Ashfaq Shuaib; William Coplin; Scott Hamilton; Michael Moseley; Michael P Marks Journal: Ann Neurol Date: 2006-11 Impact factor: 10.422
Authors: Marie Luby; Katherine D Ku; Lawrence L Latour; José G Merino; Amie W Hsia; John K Lynch; Steven Warach Journal: Stroke Date: 2011-02-10 Impact factor: 7.914
Authors: Stephen M Davis; Geoffrey A Donnan; Mark W Parsons; Christopher Levi; Kenneth S Butcher; Andre Peeters; P Alan Barber; Christopher Bladin; Deidre A De Silva; Graham Byrnes; Jonathan B Chalk; John N Fink; Thomas E Kimber; David Schultz; Peter J Hand; Judith Frayne; Graeme Hankey; Keith Muir; Richard Gerraty; Brian M Tress; Patricia M Desmond Journal: Lancet Neurol Date: 2008-02-28 Impact factor: 44.182
Authors: Werner Hacke; Anthony J Furlan; Yasir Al-Rawi; Antoni Davalos; Jochen B Fiebach; Franz Gruber; Markku Kaste; Leslie J Lipka; Salvador Pedraza; Peter A Ringleb; Howard A Rowley; Dietmar Schneider; Lee H Schwamm; Joaquin Serena Leal; Mariola Söhngen; Phil A Teal; Karin Wilhelm-Ogunbiyi; Max Wintermark; Steven Warach Journal: Lancet Neurol Date: 2008-12-25 Impact factor: 44.182
Authors: J R Sims; L Rezai Gharai; P W Schaefer; M Vangel; E S Rosenthal; M H Lev; L H Schwamm Journal: Neurology Date: 2009-06-16 Impact factor: 9.910
Authors: Michael T Mullen; Ashwin B Parthasarathy; Ali Zandieh; Wesley B Baker; Rickson C Mesquita; Caitlin Loomis; Jose Torres; Wensheng Guo; Christopher G Favilla; Steven R Messé; Arjun G Yodh; John A Detre; Scott E Kasner Journal: J Stroke Cerebrovasc Dis Date: 2019-08-13 Impact factor: 2.136
Authors: Saeed A Alqahtani; Marie Luby; Zurab Nadareishvili; Richard T Benson; Amie W Hsia; Richard Leigh; John K Lynch Journal: J Stroke Cerebrovasc Dis Date: 2017-04-27 Impact factor: 2.136
Authors: Xuling Lin; Mariza Daras; Elena Pentsova; Craig P Nolan; Igor T Gavrilovic; Lisa M DeAngelis; Thomas J Kaley Journal: Neurooncol Pract Date: 2016-12-09
Authors: Adrienne N Dula; Marie Luby; Ben T King; Sunil A Sheth; Alejandro Magadán; Lisa A Davis; Gretchel A Gealogo; José G Merino; Amie W Hsia; Lawrence L Latour; Steven J Warach Journal: Ann Clin Transl Neurol Date: 2019-02-21 Impact factor: 4.511