Academic Journal
Multi‐echo quantitative susceptibility mapping: how to combine echoes for accuracy and precision at 3 Tesla
| Τίτλος: | Multi‐echo quantitative susceptibility mapping: how to combine echoes for accuracy and precision at 3 Tesla |
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| Συγγραφείς: | Marco Battiston, Francesco Grussu, Karin Shmueli, Anita Karsa, David L. Thomas, Marios C. Yiannakas, Emma Biondetti |
| Συνεισφορές: | Institut Català de la Salut, [Biondetti E] Institute for Advanced Biomedical Technologies, Department of Neuroscience, Imaging and Clinical Sciences, 'D’Annunzio University' of Chieti-Pescara, Chieti, Italy. Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom. [Karsa A, Shmueli K] Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom. [Grussu F] NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom. Radiomics Group, Vall d’Hebron Institute of Oncology (VHIO), Barcelona, Spain. [Battiston M, Yiannakas MC] NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom. [Thomas DL] Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom. Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom, Vall d'Hebron Barcelona Hospital Campus |
| Πηγή: | Magn Reson Med Scientia Scientia. Dipòsit d'Informació Digital del Departament de Salut instname Magnetic Resonance in Medicine |
| Στοιχεία εκδότη: | Wiley, 2021. |
| Έτος έκδοσης: | 2021 |
| Θεματικοί όροι: | quantitative susceptibility mapping, Brain Mapping, Phantoms, Imaging, Otros calificadores::Otros calificadores::Otros calificadores::/diagnóstico por imagen, Other subheadings::Other subheadings::Other subheadings::/diagnostic imaging, TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS::diagnóstico::técnicas y procedimientos diagnósticos::diagnóstico por imagen::tomografía::imagen por resonancia magnética, Brain, Cervell - Imatgeria, multi-echo QSM, Magnetic Resonance Imaging, White Matter, Cartografia cerebral, ANATOMY::Nervous System::Central Nervous System::Brain, TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS::diagnóstico::técnicas y procedimientos diagnósticos::diagnóstico por imagen::neuroimágenes::neuroimágenes funcionales::mapeo encefálico, 03 medical and health sciences, 0302 clinical medicine, MRI, Image Processing, Computer-Assisted, Imatgeria per ressonància magnètica, Humans, Research Articles–Imaging Methodology, ANATOMÍA::sistema nervioso::sistema nervioso central::encéfalo, ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT::Diagnosis::Diagnostic Techniques and Procedures::Diagnostic Imaging::Tomography::Magnetic Resonance Imaging, ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT::Diagnosis::Diagnostic Techniques and Procedures::Diagnostic Imaging::Neuroimaging::Functional Neuroimaging::Brain Mapping |
| Περιγραφή: | PurposeTo compare different multi‐echo combination methods for MRI QSM. Given the current lack of consensus, we aimed to elucidate how to optimally combine multi‐echo gradient‐recalled echo signal phase information, either before or after applying Laplacian‐base methods (LBMs) for phase unwrapping or background field removal.MethodsMulti‐echo gradient‐recalled echo data were simulated in a numerical head phantom, and multi‐echo gradient‐recalled echo images were acquired at 3 Tesla in 10 healthy volunteers. To enable image‐based estimation of gradient‐recalled echo signal noise, 5 volunteers were scanned twice in the same session without repositioning. Five QSM processing pipelines were designed: 1 applied nonlinear phase fitting over TEs before LBMs; 2 applied LBMs to the TE‐dependent phase and then combined multiple TEs via either TE‐weighted or SNR‐weighted averaging; and 2 calculated TE‐dependent susceptibility maps via either multi‐step or single‐step QSM and then combined multiple TEs via magnitude‐weighted averaging. Results from different pipelines were compared using visual inspection; summary statistics of susceptibility in deep gray matter, white matter, and venous regions; phase noise maps (error propagation theory); and, in the healthy volunteers, regional fixed bias analysis (Bland–Altman) and regional differences between the means (nonparametric tests).ResultsNonlinearly fitting the multi‐echo phase over TEs before applying LBMs provided the highest regional accuracy of and the lowest phase noise propagation compared to averaging the LBM‐processed TE‐dependent phase. This result was especially pertinent in high‐susceptibility venous regions.ConclusionFor multi‐echo QSM, we recommend combining the signal phase by nonlinear fitting before applying LBMs. |
| Τύπος εγγράφου: | Article Other literature type |
| Περιγραφή αρχείου: | application/pdf |
| Γλώσσα: | English |
| ISSN: | 1522-2594 0740-3194 |
| DOI: | 10.1002/mrm.29365 |
| DOI: | 10.1101/2021.06.14.448385 |
| Σύνδεσμος πρόσβασης: | https://www.biorxiv.org/content/biorxiv/early/2021/06/14/2021.06.14.448385.full.pdf https://pubmed.ncbi.nlm.nih.gov/35766450 https://hdl.handle.net/11351/8177 https://biorxiv.org/content/10.1101/2021.06.14.448385v1.full.pdf https://europepmc.org/article/PPR/PPR356951 https://www.biorxiv.org/content/10.1101/2021.06.14.448385v1 http://www.biorxiv.org/content/10.1101/2021.06.14.448385v1 https://hdl.handle.net/11564/798313 https://onlinelibrary.wiley.com/doi/10.1002/mrm.29365 https://doi.org/10.1002/mrm.29365 https://discovery-pp.ucl.ac.uk/id/eprint/10151363/ |
| Rights: | CC BY CC BY NC ND |
| Αριθμός Καταχώρησης: | edsair.doi.dedup.....91ee1480921e8748a7e064b0191ddecb |
| Βάση Δεδομένων: | OpenAIRE |
| ISSN: | 15222594 07403194 |
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| DOI: | 10.1002/mrm.29365 |