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Improving the lesion appearance on FLAIR images synthetized from quantitative MRI: a fast, hybrid approach.
Xu, Fei; Mandija, Stefano; Kleinloog, Jordi P D; Liu, Hongyan; van der Heide, Oscar; van der Kolk, Anja G; Dankbaar, Jan Willem; van den Berg, Cornelis A T; Sbrizzi, Alessandro.
Afiliación
  • Xu F; Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands. f.xu@umcutrecht.nl.
  • Mandija S; Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands. f.xu@umcutrecht.nl.
  • Kleinloog JPD; Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Liu H; Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands.
  • van der Heide O; Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.
  • van der Kolk AG; Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Dankbaar JW; Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.
  • van den Berg CAT; Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Sbrizzi A; Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.
MAGMA ; 2024 Aug 24.
Article en En | MEDLINE | ID: mdl-39180686
ABSTRACT

OBJECTIVE:

The image quality of synthetized FLAIR (fluid attenuated inversion recovery) images is generally inferior to its conventional counterpart, especially regarding the lesion contrast mismatch. This work aimed to improve the lesion appearance through a hybrid methodology. MATERIALS AND

METHODS:

We combined a full brain 5-min MR-STAT acquisition followed by FLAIR synthetization step with an ultra-under sampled conventional FLAIR sequence and performed the retrospective and prospective analysis of the proposed method on the patient datasets and a healthy volunteer.

RESULTS:

All performance metrics of the proposed hybrid FLAIR images on patient datasets were significantly higher than those of the physics-based FLAIR images (p < 0.005), and comparable to those of conventional FLAIR images. The small difference between prospective and retrospective analysis on a healthy volunteer demonstrated the validity of the retrospective analysis of the hybrid method as presented for the patient datasets.

DISCUSSION:

The proposed hybrid FLAIR achieved an improved lesion appearance in the clinical cases with neurological diseases compared to the physics-based FLAIR images, Future prospective work on patient data will address the validation of the method from a diagnostic perspective by radiological inspection of the new images over a larger patient cohort.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: MAGMA Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2024 Tipo del documento: Article País de afiliación: Países Bajos Pais de publicación: Alemania

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: MAGMA Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2024 Tipo del documento: Article País de afiliación: Países Bajos Pais de publicación: Alemania