Julia Gerhardt1, Nico Sollmann2, Patrick Hiepe3, Jan S Kirschke4, Bernhard Meyer5, Sandro M Krieg6, Florian Ringel7. 1. Department of Neurosurgery, Klinikum rechts der Isar, Technische Universität München, Ismaninger Str. 22, 81675, Munich, Germany. Electronic address: julegerhardt@web.de. 2. Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Ismaninger Str. 22, 81675, Munich, Germany; TUM-Neuroimaging Center, Klinikum rechts der Isar, Technische Universität München, Munich, Germany. Electronic address: Nico.Sollmann@tum.de. 3. R&D Anatomical Mapping, Brainlab AG, Olof-Palme-Str. 9, 81829, Munich, Germany. Electronic address: Patrick.Hiepe@brainlab.com. 4. Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Ismaninger Str. 22, 81675, Munich, Germany; TUM-Neuroimaging Center, Klinikum rechts der Isar, Technische Universität München, Munich, Germany. Electronic address: Jan.Kirschke@tum.de. 5. Department of Neurosurgery, Klinikum rechts der Isar, Technische Universität München, Ismaninger Str. 22, 81675, Munich, Germany. Electronic address: Bernhard.Meyer@tum.de. 6. Department of Neurosurgery, Klinikum rechts der Isar, Technische Universität München, Ismaninger Str. 22, 81675, Munich, Germany; TUM-Neuroimaging Center, Klinikum rechts der Isar, Technische Universität München, Munich, Germany. Electronic address: Sandro.Krieg@tum.de. 7. Department of Neurosurgery, Klinikum rechts der Isar, Technische Universität München, Ismaninger Str. 22, 81675, Munich, Germany. Electronic address: Florian.Ringel@unimedizin-mainz.de.
Abstract
OBJECTIVE: Diffusion tensor imaging (DTI) based on echo-planar imaging (EPI) can suffer from geometric image distortions in comparison to conventional anatomical magnetic resonance imaging (MRI). Therefore, DTI-derived information, such as fiber tractography (FT) used for treatment planning of brain tumors, might be associated with spatial inaccuracies when linearly projected on anatomical MRI. Hence, a non-linear, semi-elastic image fusion shall be evaluated in this study that aims at correcting for image distortions in DTI. PATIENTS AND METHODS: In a sample of 27 patient datasets, 614 anatomical landmark pairs were retrospectively defined in DTI and T1- or T2-weighted three-dimensional (3D) MRI data. The datasets were processed by a commercial software package (Elements Image Fusion .0; Brainlab AG, Munich, Germany) providing rigid and semi-elastic fusion functionalities, such as DTI distortion correction. To quantify the displacement prior to and after semi-elastic fusion, the Euclidian distances of rigidly and elastically fused landmarks were evaluated by means of descriptive statistics and Bland-Altman plot. RESULTS: For rigid and semi-elastic fusion mean target registration errors of 3.03 ± 2.29 mm and 2.04 ± 1.95 mm were found, respectively, with 91% of the evaluated landmarks moving closer to their position determined in T1- or T2-weighted 3D MRI data after distortion correction. Most efficient correction was achieved for non-superficial landmarks showing distortions up to 1 cm. CONCLUSION: This study indicates that semi-elastic image fusion can be used for retrospective distortion correction of DTI data acquired for image guidance, such as DTI FT as used for a broad range of clinical indications.
OBJECTIVE: Diffusion tensor imaging (DTI) based on echo-planar imaging (EPI) can suffer from geometric image distortions in comparison to conventional anatomical magnetic resonance imaging (MRI). Therefore, DTI-derived information, such as fiber tractography (FT) used for treatment planning of brain tumors, might be associated with spatial inaccuracies when linearly projected on anatomical MRI. Hence, a non-linear, semi-elastic image fusion shall be evaluated in this study that aims at correcting for image distortions in DTI. PATIENTS AND METHODS: In a sample of 27 patient datasets, 614 anatomical landmark pairs were retrospectively defined in DTI and T1- or T2-weighted three-dimensional (3D) MRI data. The datasets were processed by a commercial software package (Elements Image Fusion .0; Brainlab AG, Munich, Germany) providing rigid and semi-elastic fusion functionalities, such as DTI distortion correction. To quantify the displacement prior to and after semi-elastic fusion, the Euclidian distances of rigidly and elastically fused landmarks were evaluated by means of descriptive statistics and Bland-Altman plot. RESULTS: For rigid and semi-elastic fusion mean target registration errors of 3.03 ± 2.29 mm and 2.04 ± 1.95 mm were found, respectively, with 91% of the evaluated landmarks moving closer to their position determined in T1- or T2-weighted 3D MRI data after distortion correction. Most efficient correction was achieved for non-superficial landmarks showing distortions up to 1 cm. CONCLUSION: This study indicates that semi-elastic image fusion can be used for retrospective distortion correction of DTI data acquired for image guidance, such as DTI FT as used for a broad range of clinical indications.
Authors: Jonas Ort; Hussam Aldin Hamou; Julius M Kernbach; Karlijn Hakvoort; Christian Blume; Philipp Lohmann; Norbert Galldiks; Dieter Henrik Heiland; Felix M Mottaghy; Hans Clusmann; Georg Neuloh; Karl-Josef Langen; Daniel Delev Journal: J Neurooncol Date: 2021-10-01 Impact factor: 4.130
Authors: Tizian Rosenstock; Mehmet Salih Tuncer; Max Richard Münch; Peter Vajkoczy; Thomas Picht; Katharina Faust Journal: Front Oncol Date: 2021-05-21 Impact factor: 6.244
Authors: Matthew Muir; Sarah Prinsloo; Hayley Michener; Jeffrey I Traylor; Rajan Patel; Ron Gadot; Dhiego Chaves de Almeida Bastos; Vinodh A Kumar; Sherise Ferguson; Sujit S Prabhu Journal: Cancers (Basel) Date: 2022-01-11 Impact factor: 6.639