PURPOSE: To compare "standardization," "Gaussian normalization," and "Z-score normalization" intensity transformation techniques in dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) estimates of cerebral blood volume (CBV) in human gliomas. DSC-MRI is a well-established biomarker for CBV in brain tumors; however, DSC-MRI estimates of CBV are semiquantitative. The use of image intensity transformation algorithms provides a mechanism for obtaining quantitatively similar CBV maps with the same intensity scaling. MATERIALS AND METHODS: The coefficient of variance (CV) in normal-appearing white matter and relative contrast between tumor regions and normal tissue was compared between the three CBV transformations across five different MR scanners in 96 patients with gliomas. RESULTS: The results suggest all normalization techniques improved variability and relative tumor contrast of CBV measurements compared with nonnormalized CBV maps. The results suggest Gaussian normalization of CBV maps provided slightly lower CV in normal white matter and provided slightly higher tumor contrast for glioblastomas (WHO grade IV) compared with other techniques. CONCLUSION: The results suggest Gaussian normalization of leakage-corrected CBV maps may be the best choice for image intensity correction for use in large-scale, multicenter clinical trials where MR scanners and protocols vary widely due to ease of implementation, lowest variability, and highest tumor to normal tissue contrast.
PURPOSE: To compare "standardization," "Gaussian normalization," and "Z-score normalization" intensity transformation techniques in dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) estimates of cerebral blood volume (CBV) in humangliomas. DSC-MRI is a well-established biomarker for CBV in brain tumors; however, DSC-MRI estimates of CBV are semiquantitative. The use of image intensity transformation algorithms provides a mechanism for obtaining quantitatively similar CBV maps with the same intensity scaling. MATERIALS AND METHODS: The coefficient of variance (CV) in normal-appearing white matter and relative contrast between tumor regions and normal tissue was compared between the three CBV transformations across five different MR scanners in 96 patients with gliomas. RESULTS: The results suggest all normalization techniques improved variability and relative tumor contrast of CBV measurements compared with nonnormalized CBV maps. The results suggest Gaussian normalization of CBV maps provided slightly lower CV in normal white matter and provided slightly higher tumor contrast for glioblastomas (WHO grade IV) compared with other techniques. CONCLUSION: The results suggest Gaussian normalization of leakage-corrected CBV maps may be the best choice for image intensity correction for use in large-scale, multicenter clinical trials where MR scanners and protocols vary widely due to ease of implementation, lowest variability, and highest tumor to normal tissue contrast.
Authors: Sina Burth; Philipp Kickingereder; Oliver Eidel; Diana Tichy; David Bonekamp; Lukas Weberling; Antje Wick; Sarah Löw; Anne Hertenstein; Martha Nowosielski; Heinz-Peter Schlemmer; Wolfgang Wick; Martin Bendszus; Alexander Radbruch Journal: Neuro Oncol Date: 2016-06-13 Impact factor: 12.300
Authors: David Bonekamp; Kim Mouridsen; Alexander Radbruch; Felix T Kurz; Oliver Eidel; Antje Wick; Heinz-Peter Schlemmer; Wolfgang Wick; Martin Bendszus; Leif Østergaard; Philipp Kickingereder Journal: J Cereb Blood Flow Metab Date: 2016-07-21 Impact factor: 6.200
Authors: L C Bell; M D Does; A M Stokes; L C Baxter; K M Schmainda; A C Dueck; C C Quarles Journal: AJNR Am J Neuroradiol Date: 2017-07-06 Impact factor: 3.825
Authors: Benjamin M Ellingson; Hyun J Kim; Davis C Woodworth; Whitney B Pope; Jonathan N Cloughesy; Robert J Harris; Albert Lai; Phioanh L Nghiemphu; Timothy F Cloughesy Journal: Radiology Date: 2013-11-27 Impact factor: 11.105
Authors: Julio Arevalo-Perez; Amanuel A Kebede; Kyung K Peck; Eli Diamond; Andrei I Holodny; Marc Rosenblum; Jennifer Rubel; Joshua Gaal; Vaios Hatzoglou Journal: J Neuroimaging Date: 2015-12-26 Impact factor: 2.486