Technical noteThe accuracy of whole brain N-acetylaspartate quantification
Introduction
The spatial extent of diffuse/multi-focal brain diseases is usually obtained from tissue contrast differences, elicited by enhancing agents and/or MRI pulse-sequences [1]. Unfortunately, conventional imaging is quite nonspecific with different pathologic processes, e.g., edema, demyelination, gliosis and necrosis appear similar [2], [3]. Furthermore, diffuse microscopic disease may be more pervasive than revealed by MRI [4]. To address these issues and provide additional information, MRI is sometimes augmented by localized 1H-MRS, e.g., in studies of multiple sclerosis, traumatic brain injury, Alzheimer’s disease and AIDS [5], [6], [7], [8]. However, localized 1H-MRS suffers from several limitations: (a) uncertainty in the reproducibility of the placement of a small volume-of-interest (VOI) in serial studies; (b) need for image-guidance of the VOI to visible pathologies; and (c) poor signal-to-noise-ratio (SNR) requiring prolonged acquisition.
To avoid these limitations, we recently proposed a 1H-MRS method to evaluate changes in the brain as a whole, through quantification of the total amount of neuronal loss [9]. This is assessable from the level of NAA, an amino-acid derivative present exclusively in neuronal cells [10], [11] and which yields the most prominent peak in the in vivo brain’s 1H spectrum [12], [13]. WBNAA acquisition does not suffer from the problem of serial VOI placement, image-guidance to visible pathologies is unnecessary and the SNR is >300:1, facilitating a quick, <3 min., acquisition [9].
However, it has long been known that magnetic field inhomogeneities, ΔB0s, arising from susceptibility differences at tissue/air and tissue/bone interfaces broaden and shift resonance lines [14], [15], [16], [17]. These regional effects are especially pronounced in the frontal and temporal lobes above the sinuses, in the vicinity of the auditory canals, and near the skull [14], [16], [17]. They can be as large as 2.0 ppm over a 2 × 2×2 cm3 voxel [17] and cannot be removed with the 1st and 2nd order shims found in clinical MR imagers, as noted by Gruetter [18]. Since (a) quantification of NAA involves integrating its peak’s area and (b) it is desirable to keep the integration range, δNAA, narrow to avoid contamination from adjacent lines; it is likely that a fraction of the NAA resonances will be shifted outside δNAA, leading to area underestimation. This paper investigates and quantifies the extent of this error in WBNAA.
Section snippets
Experimental
All the measurements were performed on a cohort of 5 healthy volunteers (2 men & 3 women) ranging in age from 26–32 years old, in a 1.5 Tesla Magnetom 63SP imager with its standard quadrature head-coil (Siemens AG, Erlangen Germany). Our 3D-CSI based auto-shim procedure yielded consistent 10 ± 1.0 Hz full-width-at-half-maximum (fwhm) water line from the whole head [19]. WBNAA was obtained from each volunteer as described previously [9] and its 1H spectrum, at about the 2 ppm region, is shown in
Results and discussion
The overall strategy employed was to assess the effect of ΔB0s to examine its influence on the water signal, in the whole head in general and in the brain in particular. The former provides an overall upper limit to the losses. The latter offers a more refined estimate since the brain’s water occupies approximately (with the exception of the CSF) the same regions as the NAA, hence, experience the same local field variations. Water was chosen as a probe for three reasons: First, since its SNR is
Conclusion
Single voxel-methods typically cover <10 cm3, i.e., <1% of the brain, 2D MRS may cover up to 100 cm3 or ∼10% of that organ and even aggressive 3D MRS covers less than ∼ liter [20], [21]. Since WBNAA estimates within 10% the total amount of NAA in the entire brain, it is comprehensive enough to be referred to as a “whole brain” method. As such, it does not need image guidance, is not susceptible to misregistration in serial studies and its SNR is excellent, making it well suited to investigate
Acknowledgements
This work was supported by NIH grants NS33385, NS37739 and NS29029. We thank Dr. Srirama V. Swaminathan of Fox Chase Cancer Center for technical assistance.
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