Improved PRF-based MR thermometry using k-space energy spectrum analysis.
Magn Reson Med
; 84(6): 3325-3332, 2020 12.
Article
em En
| MEDLINE
| ID: mdl-32588485
ABSTRACT
PURPOSE:
Proton resonance frequency (PRF) thermometry encodes information in the phase of MRI signals. A multiplicative factor converts phase changes into temperature changes, and this factor includes the TE. However, phase variations caused by B0 and/or B1 inhomogeneities can effectively change TE in ways that vary from pixel to pixel. This work presents how spatial phase variations affect temperature maps and how to correct for corresponding errors.METHODS:
A method called "k-space energy spectrum analysis" was used to map regions in the object domain to regions in the k-space domain. Focused ultrasound heating experiments were performed in tissue-mimicking gel phantoms under two scenarios with and without proper shimming. The second scenario, with deliberately de-adjusted shimming, was meant to emulate B0 inhomogeneities in a controlled manner. The TE errors were mapped and compensated for using k-space energy spectrum analysis, and corrected results were compared with reference results. Furthermore, a volunteer was recruited to help evaluate the magnitude of the errors being corrected.RESULTS:
The in vivo abdominal results showed that the TE and heating errors being corrected can readily exceed 10%. In phantom results, a linear regression between reference and corrected temperatures results provided a slope of 0.971 and R2 of 0.9964. Analysis based on the Bland-Altman method provided a bias of -0.0977°C and 95% limits of agreement that were 0.75°C apart.CONCLUSION:
Spatially varying TE errors, such as caused by B0 and/or B1 inhomogeneities, can be detected and corrected using the k-space energy spectrum analysis method, for increased accuracy in proton resonance frequency thermometry.Palavras-chave
Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Prótons
/
Termometria
Limite:
Humans
Idioma:
En
Revista:
Magn Reson Med
Assunto da revista:
DIAGNOSTICO POR IMAGEM
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
China