Computing the orientational-average of diffusion-weighted MRI signals: a comparison of different techniques

Abstract Numerous applications in diffusion MRI involve computing the orientationally-averaged diffusion-weighted signal. Most approaches implicitly assume, for a given b-value, that the gradient sampling vectors are uniformly distributed on a sphere (or ‘shell’), computing the orientationally-avera...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Maryam Afzali, Hans Knutsson, Evren Özarslan, Derek K. Jones
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/ee5d6d54f6734bb9bd4922434d9dc71b
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:ee5d6d54f6734bb9bd4922434d9dc71b
record_format	dspace
spelling	oai:doaj.org-article:ee5d6d54f6734bb9bd4922434d9dc71b2021-12-02T16:08:07ZComputing the orientational-average of diffusion-weighted MRI signals: a comparison of different techniques10.1038/s41598-021-93558-12045-2322https://doaj.org/article/ee5d6d54f6734bb9bd4922434d9dc71b2021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-93558-1https://doaj.org/toc/2045-2322Abstract Numerous applications in diffusion MRI involve computing the orientationally-averaged diffusion-weighted signal. Most approaches implicitly assume, for a given b-value, that the gradient sampling vectors are uniformly distributed on a sphere (or ‘shell’), computing the orientationally-averaged signal through simple arithmetic averaging. One challenge with this approach is that not all acquisition schemes have gradient sampling vectors distributed over perfect spheres. To ameliorate this challenge, alternative averaging methods include: weighted signal averaging; spherical harmonic representation of the signal in each shell; and using Mean Apparent Propagator MRI (MAP-MRI) to derive a three-dimensional signal representation and estimate its ‘isotropic part’. Here, these different methods are simulated and compared under different signal-to-noise (SNR) realizations. With sufficiently dense sampling points (61 orientations per shell), and isotropically-distributed sampling vectors, all averaging methods give comparable results, (MAP-MRI-based estimates give slightly higher accuracy, albeit with slightly elevated bias as b-value increases). As the SNR and number of data points per shell are reduced, MAP-MRI-based approaches give significantly higher accuracy compared with the other methods. We also apply these approaches to in vivo data where the results are broadly consistent with our simulations. A statistical analysis of the simulated data shows that the orientationally-averaged signals at each b-value are largely Gaussian distributed.Maryam AfzaliHans KnutssonEvren ÖzarslanDerek K. JonesNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-16 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Maryam Afzali Hans Knutsson Evren Özarslan Derek K. Jones Computing the orientational-average of diffusion-weighted MRI signals: a comparison of different techniques
description	Abstract Numerous applications in diffusion MRI involve computing the orientationally-averaged diffusion-weighted signal. Most approaches implicitly assume, for a given b-value, that the gradient sampling vectors are uniformly distributed on a sphere (or ‘shell’), computing the orientationally-averaged signal through simple arithmetic averaging. One challenge with this approach is that not all acquisition schemes have gradient sampling vectors distributed over perfect spheres. To ameliorate this challenge, alternative averaging methods include: weighted signal averaging; spherical harmonic representation of the signal in each shell; and using Mean Apparent Propagator MRI (MAP-MRI) to derive a three-dimensional signal representation and estimate its ‘isotropic part’. Here, these different methods are simulated and compared under different signal-to-noise (SNR) realizations. With sufficiently dense sampling points (61 orientations per shell), and isotropically-distributed sampling vectors, all averaging methods give comparable results, (MAP-MRI-based estimates give slightly higher accuracy, albeit with slightly elevated bias as b-value increases). As the SNR and number of data points per shell are reduced, MAP-MRI-based approaches give significantly higher accuracy compared with the other methods. We also apply these approaches to in vivo data where the results are broadly consistent with our simulations. A statistical analysis of the simulated data shows that the orientationally-averaged signals at each b-value are largely Gaussian distributed.
format	article
author	Maryam Afzali Hans Knutsson Evren Özarslan Derek K. Jones
author_facet	Maryam Afzali Hans Knutsson Evren Özarslan Derek K. Jones
author_sort	Maryam Afzali
title	Computing the orientational-average of diffusion-weighted MRI signals: a comparison of different techniques
title_short	Computing the orientational-average of diffusion-weighted MRI signals: a comparison of different techniques
title_full	Computing the orientational-average of diffusion-weighted MRI signals: a comparison of different techniques
title_fullStr	Computing the orientational-average of diffusion-weighted MRI signals: a comparison of different techniques
title_full_unstemmed	Computing the orientational-average of diffusion-weighted MRI signals: a comparison of different techniques
title_sort	computing the orientational-average of diffusion-weighted mri signals: a comparison of different techniques
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/ee5d6d54f6734bb9bd4922434d9dc71b
work_keys_str_mv	AT maryamafzali computingtheorientationalaverageofdiffusionweightedmrisignalsacomparisonofdifferenttechniques AT hansknutsson computingtheorientationalaverageofdiffusionweightedmrisignalsacomparisonofdifferenttechniques AT evrenozarslan computingtheorientationalaverageofdiffusionweightedmrisignalsacomparisonofdifferenttechniques AT derekkjones computingtheorientationalaverageofdiffusionweightedmrisignalsacomparisonofdifferenttechniques
_version_	1718384628492926976

Computing the orientational-average of diffusion-weighted MRI signals: a comparison of different techniques

Ejemplares similares