Abstract:The proposed method overcomes some inaccuracies in FA production, providing more accurate estimation of T1 values compared with standard methods, and is applicable for currently available data.
“…This impression is confirmed by the numerical results in Table 3 for brain (frontal and parietal white and gray matter), liver, and kidney (cortex and medulla). Because a comprehensive determination of in vivo data for various tissues is outside the scope of this work, the present results are only compared to some most recent literature findings [16][17][18]. As it turns out all T1 values are close to published data.…”
Abstract:Purpose: To develop a method for T1 mapping at high spatial resolution and for multiple slices.
Methods:The proposed method emerges as a single-shot inversion-recovery experiment which covers the entire spinlattice relaxation process by serial acquisitions of highly undersampled radial FLASH images, either in single-slice or multi-slice mode. Serial image reconstructions are performed in time-reversed order and first involve regularized nonlinear inversion (NLINV) to estimate optimum coil sensitivity profiles. Subsequently, the coil profiles are fixed for the calculation of differently T1-weighted frames and the resulting linear inverse problem is solved by a conjugate gradient (CG) technique. T1 values are obtained by pixelwise fitting with a Deichmann correction modified for multi-slice applications.Results: T1 accuracy was validated for a reference phantom. For human brain, T1 maps were obtained at 0.5 mm resolution for single-slice acquisitions and at 0.75 mm resolution for up to 5 simultaneous slices (5 mm thickness). Corresponding T1 maps of the liver were acquired at 1 mm and 1.5 mm resolution, respectively. All T1 values were in agreement with literature data.
Conclusion:Inversion-recovery sequences with highly undersampled radial FLASH images and NLINV/CG reconstruction allow for fast, robust and accurate T1 mapping at high spatial resolution and for multiple slices.
“…This impression is confirmed by the numerical results in Table 3 for brain (frontal and parietal white and gray matter), liver, and kidney (cortex and medulla). Because a comprehensive determination of in vivo data for various tissues is outside the scope of this work, the present results are only compared to some most recent literature findings [16][17][18]. As it turns out all T1 values are close to published data.…”
Abstract:Purpose: To develop a method for T1 mapping at high spatial resolution and for multiple slices.
Methods:The proposed method emerges as a single-shot inversion-recovery experiment which covers the entire spinlattice relaxation process by serial acquisitions of highly undersampled radial FLASH images, either in single-slice or multi-slice mode. Serial image reconstructions are performed in time-reversed order and first involve regularized nonlinear inversion (NLINV) to estimate optimum coil sensitivity profiles. Subsequently, the coil profiles are fixed for the calculation of differently T1-weighted frames and the resulting linear inverse problem is solved by a conjugate gradient (CG) technique. T1 values are obtained by pixelwise fitting with a Deichmann correction modified for multi-slice applications.Results: T1 accuracy was validated for a reference phantom. For human brain, T1 maps were obtained at 0.5 mm resolution for single-slice acquisitions and at 0.75 mm resolution for up to 5 simultaneous slices (5 mm thickness). Corresponding T1 maps of the liver were acquired at 1 mm and 1.5 mm resolution, respectively. All T1 values were in agreement with literature data.
Conclusion:Inversion-recovery sequences with highly undersampled radial FLASH images and NLINV/CG reconstruction allow for fast, robust and accurate T1 mapping at high spatial resolution and for multiple slices.
“…The T 1 time for blood is between 1 ms to 700 ms, 700 ms to 1170 ms for white matter, 1170 ms to 1800 ms for gray matter, and 1800 ms to 5000 ms for cerebral spinal fluid based on our measurement in the NHP and the previous study in humans60.…”
Section: Methodssupporting
confidence: 52%
“…1E)59. First, the standard line fit method of VFA SPGR60 was used to calculate the pre- and post-T 1 maps after registering the 3D SPGR images of various flip angles to the IST. Then, the Gd concentration map (Fig.…”
Focused ultrasound with microbubbles has been used to noninvasively and selectively deliver pharmacological agents across the blood-brain barrier (BBB) for treating brain diseases. Acoustic cavitation monitoring could serve as an on-line tool to assess and control the treatment. While it demonstrated a strong correlation in small animals, its translation to primates remains in question due to the anatomically different and highly heterogeneous brain structures with gray and white matteras well as dense vasculature. In addition, the drug delivery efficiency and the BBB opening volume have never been shown to be predictable through cavitation monitoring in primates. This study aimed at determining how cavitation activity is correlated with the amount and concentration of gadolinium delivered through the BBB and its associated delivery efficiency as well as the BBB opening volume in non-human primates. Another important finding entails the effect of heterogeneous brain anatomy and vasculature of a primate brain, i.e., presence of large cerebral vessels, gray and white matter that will also affect the cavitation activity associated with variation of BBB opening in different tissue types, which is not typically observed in small animals. Both these new findings are critical in the primate brain and provide essential information for clinical applications.
“…In particular, the bias introduced by the spatial inhomogeneity of the radiofrequency (RF) transmit field () is a well-known source of error (Stikov et al, 2015). Numerous methods exist for obtaining a map (Insko and Bolinger, 1993; Cunningham et al, 2006; Jiru and Klose, 2006; Dowell and Tofts, 2007; Yarnykh, 2007; Lutti et al, 2010; Sacolick et al, 2010; Nehrke and Börnert, 2012) and incorporating this into the T 1 mapping pipeline has been shown to improve the accuracy of the estimated value of the T 1 relaxation times (Venkatesan et al, 1998; Deoni, 2007; Helms et al, 2008; Lutti et al, 2013; Liberman et al, 2014). However, the precision of the map and how this diminishes the precision of the estimated T 1 values has not been thoroughly addressed, especially not in vivo .…”
In magnetic resonance imaging, precise measurements of longitudinal relaxation time (T1) is crucial to acquire useful information that is applicable to numerous clinical and neuroscience applications. In this work, we investigated the precision of T1 relaxation time as measured using the variable flip angle method with emphasis on the noise propagated from radiofrequency transmit field (B1+) measurements. The analytical solution for T1 precision was derived by standard error propagation methods incorporating the noise from the three input sources: two spoiled gradient echo (SPGR) images and a B1+ map. Repeated in vivo experiments were performed to estimate the total variance in T1 maps and we compared these experimentally obtained values with the theoretical predictions to validate the established theoretical framework. Both the analytical and experimental results showed that variance in the B1+ map propagated comparable noise levels into the T1 maps as either of the two SPGR images. Improving precision of the B1+ measurements significantly reduced the variance in the estimated T1 map. The variance estimated from the repeatedly measured in vivo
T1 maps agreed well with the theoretically-calculated variance in T1 estimates, thus validating the analytical framework for realistic in vivo experiments. We concluded that for T1 mapping experiments, the error propagated from the B1+ map must be considered. Optimizing the SPGR signals while neglecting to improve the precision of the B1+ map may result in grossly overestimating the precision of the estimated T1 values.
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