RESUMEN
BACKGROUND: Advanced magnetic resonance imaging (MRI) techniques provide a window into pathological processes in multiple sclerosis (MS). Nevertheless, to date only few studies have performed sodium MRI in MS. OBJECTIVES: We analysed total sodium concentration (TSC) in hyperacute, acute and chronic lesions in MS with (23)Na MRI. METHODS: (23)Na MRI and (1)H MRI were performed in 65 MS patients and 10 healthy controls (HC). Mean TSC was quantified in all MS lesions with a diameter of >5 mm and in the normal appearing white and grey matter (NAWM, NAGM). RESULTS: TSC in the NAWM and the NAGM of MS patients was significantly higher compared to HC (WM: 37.51 ± 2.65 mM versus 35.17 ± 3.40 mM; GM: 43.64 ± 2.75 mM versus 40.09 ± 4.64 mM). Acute and chronic MS lesions showed elevated TSC levels of different extent (contrast-enhancing lesions (49.07 ± 6.99 mM), T1 hypointense lesions (45.06 ± 6.26 mM) and remaining T1 isointense lesions (39.88 ± 5.54 mM)). However, non-enhancing hyperacute lesions with a reduced apparent diffusion coefficient showed a TSC comparable to the NAWM (37.22 ± 4.62 mM). CONCLUSIONS: TSC is not only a sensitive marker of the severity of chronic tissue abnormalities in MS but is also highly sensitive to opening of the blood-brain barrier and vasogenic tissue oedema in contrast-enhancing lesions.
Asunto(s)
Imagen de Difusión por Resonancia Magnética/métodos , Sustancia Gris/diagnóstico por imagen , Esclerosis Múltiple/diagnóstico por imagen , Isótopos de Sodio/metabolismo , Sustancia Blanca/diagnóstico por imagen , Adolescente , Adulto , Estudios de Casos y Controles , Medios de Contraste/administración & dosificación , Estudios Transversales , Femenino , Sustancia Gris/metabolismo , Sustancia Gris/patología , Humanos , Masculino , Persona de Mediana Edad , Esclerosis Múltiple/metabolismo , Esclerosis Múltiple/patología , Valor Predictivo de las Pruebas , Isótopos de Sodio/administración & dosificación , Sustancia Blanca/metabolismo , Sustancia Blanca/patología , Adulto JovenRESUMEN
PURPOSE: To reduce noise and artifacts in (23)Na MRI with a Compressed Sensing reconstruction and a learned dictionary as sparsifying transform. METHODS: A three-dimensional dictionary-learning compressed sensing reconstruction algorithm (3D-DLCS) for the reconstruction of undersampled 3D radial (23)Na data is presented. The dictionary used as the sparsifying transform is learned with a K-singular-value-decomposition (K-SVD) algorithm. The reconstruction parameters are optimized on simulated data, and the quality of the reconstructions is assessed with peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The performance of the algorithm is evaluated in phantom and in vivo (23)Na MRI data of seven volunteers and compared with nonuniform fast Fourier transform (NUFFT) and other Compressed Sensing reconstructions. RESULTS: The reconstructions of simulated data have maximal PSNR and SSIM for an undersampling factor (USF) of 10 with numbers of averages equal to the USF. For 10-fold undersampling, the PSNR is increased by 5.1 dB compared with the NUFFT reconstruction, and the SSIM by 24%. These results are confirmed by phantom and in vivo (23)Na measurements in the volunteers that show markedly reduced noise and undersampling artifacts in the case of 3D-DLCS reconstructions. CONCLUSION: The 3D-DLCS algorithm enables precise reconstruction of undersampled (23)Na MRI data with markedly reduced noise and artifact levels compared with NUFFT reconstruction. Small structures are well preserved.