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Fast qualitY conTrol meThod foR derIved diffUsion Metrics (YTTRIUM) in big data analysis: U.K. Biobank 18,608 example

Maximov, Ivan I. ; Meer, Dennis ; Lange, Ann‐Marie G. ; Kaufmann, Tobias ; Shadrin, Alexey ; Frei, Oleksandr ; Wolfers, Thomas ; Westlye, Lars T.

Human brain mapping, 2021-07, Vol.42 (10), p.3141-3155 [Periódico revisado por pares]

Hoboken, USA: John Wiley & Sons, Inc

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Título:
Fast qualitY conTrol meThod foR derIved diffUsion Metrics (YTTRIUM) in big data analysis: U.K. Biobank 18,608 example
Autor: Maximov, Ivan I. ; Meer, Dennis ; Lange, Ann‐Marie G. ; Kaufmann, Tobias ; Shadrin, Alexey ; Frei, Oleksandr ; Wolfers, Thomas ; Westlye, Lars T.
Assuntos: Adult ; Age ; Age Factors ; Aged ; Automation ; Biobanks ; Biological Specimen Banks ; Brain ; Brain architecture ; brain maturation ; Control methods ; Data analysis ; Datasets ; Diffusion ; Diffusion Magnetic Resonance Imaging - methods ; Diffusion Magnetic Resonance Imaging - standards ; diffusion QC ; Diffusion rate ; DKI ; DTI ; Female ; Gene mapping ; Humans ; Imaging techniques ; In vivo methods and tests ; Kurtosis ; Learning algorithms ; Machine Learning ; Magnetic resonance imaging ; Male ; Middle Aged ; Neuroimaging ; Outliers (statistics) ; Quality Control ; Statistical analysis ; Structure-function relationships ; Substantia alba ; U.K. Biobank ; United Kingdom ; White Matter - anatomy & histology ; White Matter - diagnostic imaging ; WMTI ; YTTRIUM
É parte de: Human brain mapping, 2021-07, Vol.42 (10), p.3141-3155
Notas: Funding information
Norges Forskningsråd, Grant/Award Number: 249795
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Funding information Norges Forskningsråd, Grant/Award Number: 249795
Descrição: Deriving reliable information about the structural and functional architecture of the brain in vivo is critical for the clinical and basic neurosciences. In the new era of large population‐based datasets, when multiple brain imaging modalities and contrasts are combined in order to reveal latent brain structural patterns and associations with genetic, demographic and clinical information, automated and stringent quality control (QC) procedures are important. Diffusion magnetic resonance imaging (dMRI) is a fertile imaging technique for probing and visualising brain tissue microstructure in vivo, and has been included in most standard imaging protocols in large‐scale studies. Due to its sensitivity to subject motion and technical artefacts, automated QC procedures prior to scalar diffusion metrics estimation are required in order to minimise the influence of noise and artefacts. However, the QC procedures performed on raw diffusion data cannot guarantee an absence of distorted maps among the derived diffusion metrics. Thus, robust and efficient QC methods for diffusion scalar metrics are needed. Here, we introduce Fast qualitY conTrol meThod foR derIved diffUsion Metrics (YTTRIUM), a computationally efficient QC method utilising structural similarity to evaluate diffusion map quality and mean diffusion metrics. As an example, we applied YTTRIUM in the context of tract‐based spatial statistics to assess associations between age and kurtosis imaging and white matter tract integrity maps in U.K. Biobank data (n = 18,608). To assess the influence of outliers on results obtained using machine learning (ML) approaches, we tested the effects of applying YTTRIUM on brain age prediction. We demonstrated that the proposed QC pipeline represents an efficient approach for identifying poor quality datasets and artefacts and increases the accuracy of ML based brain age prediction. Accurate quality control of diffusion scalar maps in big data. Influence of outliers on brain age gap estimation.
Editor: Hoboken, USA: John Wiley & Sons, Inc
Idioma: Inglês;Norueguês

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Fast qualitY conTrol meThod foR derIved diffUsion Metrics (YTTRIUM) in big data analysis: U.K. Biobank 18,608 example

Maximov, Ivan I. ; Meer, Dennis ; Lange, Ann‐Marie G. ; Kaufmann, Tobias ; Shadrin, Alexey ; Frei, Oleksandr ; Wolfers, Thomas ; Westlye, Lars T.

Hoboken, USA: John Wiley & Sons, Inc

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