MagnResonMed_94_(2025)_134-149_[Fortin]—MPRAGElike--A novel approach to generate T1w images from multi-contrast gradient echo images for brain segmentation.pdf
UHF‐MRI; brain segmentation; multi‐contrast; multi‐parameter mapping; neuroimaging; synthetic MPRAGE; Humans; Male; Adult; Female; Algorithms; Reproducibility of Results; Image Enhancement/methods; Signal-To-Noise Ratio; Sensitivity and Specificity; Brain/diagnostic imaging; Brain/anatomy & histology; Magnetic Resonance Imaging/methods; Image Processing, Computer-Assisted/methods; Image Interpretation, Computer-Assisted/methods; Gradient echo; High SNR; Multiparameters; Scan time; SNR values; Brain; Image Enhancement; Image Interpretation, Computer-Assisted; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Radiology, Nuclear Medicine and Imaging
Abstract :
[en] PURPOSE: Brain segmentation and multi-parameter mapping (MPM) are important steps in neurodegenerative disease characterization. However, acquiring both a high-resolution T1w sequence like MPRAGE (standard input to brain segmentation) and an MPM in the same neuroimaging protocol increases scan time and patient discomfort, making it difficult to combine both in clinical examinations.
METHODS: A novel approach to synthesize T1w images from MPM images, named MPRAGElike, is proposed and compared to the standard technique used to produce synthetic MPRAGE images (synMPRAGE). Twenty-three healthy subjects were scanned with the same imaging protocol at three different 7T sites using universal parallel transmit RF pulses. SNR, CNR, and automatic brain segmentation results from both MPRAGElike and synMPRAGE were compared against an acquired MPRAGE.
RESULTS: The proposed MPRAGElike technique produced higher SNR values than synMPRAGE for all regions evaluated while also having higher CNR values for subcortical structures. MPRAGE was still the image with the highest SNR values overall. For automatic brain segmentation, MPRAGElike outperformed synMPRAGE when compared to MPRAGE (median Dice Similarity Coefficient of 0.90 versus 0.29 and Average Asymmetric Surface Distance of 0.33 versus 2.93 mm, respectively), in addition to being simple, flexible, and considerably more robust to low image quality than synMPRAGE.
CONCLUSION: The MPRAGElike technique can provide a better and more reliable alternative to synMPRAGE as a substitute for MPRAGE, especially when automatic brain segmentation is of interest and scan time is limited.
Disciplines :
Radiology, nuclear medicine & imaging
Author, co-author :
Fortin, Marc-Antoine ; Department of Physics, Norwegian University of Science and Technology, Trondheim, Trøndelag, Norway
Stirnberg, Rüdiger ; German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
Völzke, Yannik ; German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
Lamalle, Laurent ; Université de Liège - ULiège > Département de physique
Pracht, Eberhard; German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
Löwen, Daniel ; German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
Stöcker, Tony ; German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany ; Department of Physics and Astronomy, University of Bonn, Bonn, Germany
Goa, Pål Erik ; Department of Physics, Norwegian University of Science and Technology, Trondheim, Trøndelag, Norway ; Department of Radiology and Nuclear Medicine, St. Olavs Hospital HF, Trondheim, Norway
Language :
English
Title :
MPRAGElike: A novel approach to generate T1w images from multi-contrast gradient echo images for brain segmentation.
Norges Forskningsråd BMBF - Bundesministerium für Bildung und Forschung F.R.S.-FNRS - Fonds de la Recherche Scientifique TÜBİTAK - Türkiye Bilimsel ve Teknolojik Araştırma Kurumu
Funding text :
This publication is an outcome of SCAIFIELD, an EU Joint Programme\u2013Neurodegenerative Disease Research (JPND) project (https://www.jpnd.eu). The project is supported through the following funding organizations under the aegis of JPND: Belgium, The Fund for Scientific Research (F.R.S.-FNRS; funding code PINT-MULTI/BEJ R.8006.20); Germany, Federal Ministry of Education and Research (BMBF; funding codes 01ED2109A/B); Norway, The Research Council of Norway (RCN; funding code 322980); Turkey, Scientific and Technological Research Council of Turkey (T\u00DCB\u00CDTAK; funding code 121N028).This publication is an outcome of SCAIFIELD, an EU Joint Programme\u2013Neurodegenerative Disease Research (JPND) project ( https://www.jpnd.eu ). The project is supported through the following funding organizations under the aegis of JPND: Belgium, The Fund for Scientific Research (F.R.S.\u2010FNRS; funding code PINT\u2010MULTI/BEJ R.8006.20); Germany, Federal Ministry of Education and Research (BMBF; funding codes 01ED2109A/B); Norway, The Research Council of Norway (RCN; funding code 322980); Turkey, Scientific and Technological Research Council of Turkey (T\u00DCB\u00CDTAK; funding code 121N028).
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