Cargando…

B(0) Correction for 3T Amide Proton Transfer (APT) MRI Using a Simplified Two-Pool Lorentzian Model of Symmetric Water and Asymmetric Solutes

Amide proton transfer (APT)-weighted MRI is a promising molecular imaging technique that has been employed in clinic for detection and grading of brain tumors. MTR(asym), the quantification method of APT, is easily influenced by B(0) inhomogeneity and causes artifacts. Current model-free interpolati...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Yibing, Dang, Xujian, Zhao, Benqi, Zheng, Zhuozhao, He, Xiaowei, Song, Xiaolei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9412582/
https://www.ncbi.nlm.nih.gov/pubmed/36006063
http://dx.doi.org/10.3390/tomography8040165
Descripción
Sumario:Amide proton transfer (APT)-weighted MRI is a promising molecular imaging technique that has been employed in clinic for detection and grading of brain tumors. MTR(asym), the quantification method of APT, is easily influenced by B(0) inhomogeneity and causes artifacts. Current model-free interpolation methods have enabled moderate B(0) correction for middle offsets, but have performed poorly at limbic offsets. To address this shortcoming, we proposed a practical B(0) correction approach that is suitable under time-limited sparse acquisition scenarios and for B(1) ≥ 1 μT under 3T. In this study, this approach employed a simplified Lorentzian model containing only two pools of symmetric water and asymmetric solutes, to describe the Z-spectral shape with wide and ‘invisible’ CEST peaks. The B(0) correction was then performed on the basis of the fitted two-pool Lorentzian lines, instead of using conventional model-free interpolation. The approach was firstly evaluated on densely sampled Z-spectra data by using the spline interpolation of all acquired 16 offsets as the gold standard. When only six offsets were available for B(0) correction, our method outperformed conventional methods. In particular, the errors at limbic offsets were significantly reduced (n = 8, p < 0.01). Secondly, our method was assessed on the six-offset APT data of nine brain tumor patients. Our MTR(asym) (3.5 ppm), using the two-pool model, displayed a similar contrast to the vendor-provided B(0)-orrected MTR(asym) (3.5 ppm). While the vendor failed in correcting B(0) at 4.3 and 2.7 ppm for a large portion of voxels, our method enabled well differentiation of B(0) artifacts from tumors. In conclusion, the proposed approach could alleviate analysis errors caused by B(0) inhomogeneity, which is useful for facilitating the comprehensive metabolic analysis of brain tumors.