Thomas Lindner1, Friederike Austein2, Olav Jansen2, Michael Helle3. 1. Department of Radiology and Neuroradiology, University Hospital Schleswig-Holstein Campus Kiel, Arnold-Heller-Str. 3, 24103, Kiel, Germany. Thomas.Lindner@uksh.de. 2. Department of Radiology and Neuroradiology, University Hospital Schleswig-Holstein Campus Kiel, Arnold-Heller-Str. 3, 24103, Kiel, Germany. 3. Philips GmbH Innovative Technologies Research Laboratories, Röntgenstraße 24-26, 22335, Hamburg, Germany.
Abstract
OBJECTIVES: Arterial spin labelling (ASL) is a method of non-contrast-enhanced perfusion imaging that is generally based on the acquisition of two images which must be subtracted in order to obtain perfusion-weighted images. This is also the case for some flow territory mapping approaches that require the acquisition of two images for each artery of interest, thereby prolonging scan time and yielding largely redundant information. The aim of this study is to accelerate flow territory mapping using ASL by eliminating the acquisition of a control condition. METHODS: Using super-selective ASL, only one artery of interest is tagged, while the contralateral arteries are in a state similar to the control condition. By using an arithmetic combination of the label images of all territories, selective images of flow territories can be obtained without the need to acquire an additional control condition. This approach for obtaining artery-selective perfusion-weighted images without acquiring a control condition is presented in this study and is referred to as "self-controlled super-selective ASL". RESULTS: Quantitative perfusion measurements were similar to conventional super-selective and non-selective perfusion imaging across all subjects. CONCLUSION: Super-selective arterial spin labelling can be performed without acquiring a control image. KEY POINTS: • An accelerated method of flow territory mapping is presented. • Super-selective arterial spin labelling is performed without a control condition. • A new approach for calculating individual flow territories is presented. • The presented technique is compared to established approaches. • The outcome is similar to that using conventional techniques.
OBJECTIVES: Arterial spin labelling (ASL) is a method of non-contrast-enhanced perfusion imaging that is generally based on the acquisition of two images which must be subtracted in order to obtain perfusion-weighted images. This is also the case for some flow territory mapping approaches that require the acquisition of two images for each artery of interest, thereby prolonging scan time and yielding largely redundant information. The aim of this study is to accelerate flow territory mapping using ASL by eliminating the acquisition of a control condition. METHODS: Using super-selective ASL, only one artery of interest is tagged, while the contralateral arteries are in a state similar to the control condition. By using an arithmetic combination of the label images of all territories, selective images of flow territories can be obtained without the need to acquire an additional control condition. This approach for obtaining artery-selective perfusion-weighted images without acquiring a control condition is presented in this study and is referred to as "self-controlled super-selective ASL". RESULTS: Quantitative perfusion measurements were similar to conventional super-selective and non-selective perfusion imaging across all subjects. CONCLUSION: Super-selective arterial spin labelling can be performed without acquiring a control image. KEY POINTS: • An accelerated method of flow territory mapping is presented. • Super-selective arterial spin labelling is performed without a control condition. • A new approach for calculating individual flow territories is presented. • The presented technique is compared to established approaches. • The outcome is similar to that using conventional techniques.
Authors: Michael Helle; Susanne Rüfer; Matthias J P van Osch; Olav Jansen; David G Norris Journal: Magn Reson Med Date: 2011-12-28 Impact factor: 4.668
Authors: Varsha Jain; Jeffrey Duda; Brian Avants; Mariel Giannetta; Sharon X Xie; Timothy Roberts; John A Detre; Hallam Hurt; Felix W Wehrli; Danny J J Wang Journal: Radiology Date: 2012-05 Impact factor: 11.105
Authors: Nolan S Hartkamp; Esben T Petersen; Jill B De Vis; Reinoud P H Bokkers; Jeroen Hendrikse Journal: NMR Biomed Date: 2012-07-15 Impact factor: 4.044
Authors: Michael Helle; Susanne Rüfer; Matthias J P van Osch; Arya Nabavi; Karsten Alfke; David G Norris; Olav Jansen Journal: J Magn Reson Imaging Date: 2013-03-22 Impact factor: 4.813
Authors: O Togao; M Obara; K Kikuchi; M Helle; K Arimura; A Nishimura; T Wada; H Murazaki; M Van Cauteren; A Hiwatashi; K Ishigami Journal: AJNR Am J Neuroradiol Date: 2022-03-03 Impact factor: 3.825