Automated whole-brain N-acetylaspartate proton MRS quantification

• Published in: NMR in biomedicine Vol. 27; no. 11; pp. 1275 - 1284
• Main Authors: Soher, Brian J., Wu, William E., Tal, Assaf, Storey, Pippa, Zhang, Ke, Babb, James S., Kirov, Ivan I., Lui, Yvonne W., Gonen, Oded
• Format: Journal Article
• Language: English
• Published: England Blackwell Publishing Ltd 01.11.2014; Wiley Subscription Services, Inc
• Subjects: Adult; Aspartic Acid - analogs & derivatives; Aspartic Acid - analysis; Automation; Brain - anatomy & histology; Brain Chemistry; Computer Simulation; Female; Humans; Male; MRI segmentation; MRS quantification; N-acetylaspartate (NAA); Neurons - metabolism; Organ Size; Phantoms, Imaging; Proton Magnetic Resonance Spectroscopy - instrumentation; Proton Magnetic Resonance Spectroscopy - methods; Protons; Reference Values; whole-brain NAA concentration (WBNAA); N-acetylaspartate (NAA); MRI segmentation; whole-brain NAA concentration (WBNAA); MRS quantification
• ISSN: 0952-3480; 1099-1492; 1099-1492
• DOI: 10.1002/nbm.3185

Concentration of the neuronal marker, N‐acetylaspartate (NAA), a quantitative metric for the health and density of neurons, is currently obtained by integration of the manually defined peak in whole‐head proton (1H)‐MRS. Our goal was to develop a full spectral modeling approach for the automatic estimation of the whole‐brain NAA concentration (WBNAA) and to compare the performance of this approach with a manual frequency‐range peak integration approach previously employed. MRI and whole‐head 1H‐MRS from 18 healthy young adults were examined. Non‐localized, whole‐head 1H‐MRS obtained at 3 T yielded the NAA peak area through both manually defined frequency‐range integration and the new, full spectral simulation. The NAA peak area was converted into an absolute amount with phantom replacement and normalized for brain volume (segmented from T1‐weighted MRI) to yield WBNAA. A paired‐sample t test was used to compare the means of the WBNAA paradigms and a likelihood ratio test used to compare their coefficients of variation. While the between‐subject WBNAA means were nearly identical (12.8 ± 2.5 mm for integration, 12.8 ± 1.4 mm for spectral modeling), the latter's standard deviation was significantly smaller (by ~50%, p = 0.026). The within‐subject variability was 11.7% (±1.3 mm) for integration versus 7.0% (±0.8 mm) for spectral modeling, i.e., a 40% improvement. The (quantifiable) quality of the modeling approach was high, as reflected by Cramer–Rao lower bounds below 0.1% and vanishingly small (experimental ‐ fitted) residuals. Modeling of the whole‐head 1H‐MRS increases WBNAA quantification reliability by reducing its variability, its susceptibility to operator bias and baseline roll, and by providing quality‐control feedback. Together, these enhance the usefulness of the technique for monitoring the diffuse progression and treatment response of neurological disorders. Copyright © 2014 John Wiley & Sons, Ltd. Our goal was to develop an automated, full spectral modeling of the whole‐head proton (1H)‐MRS to estimate the whole‐brain N‐acetylaspartate (WBNAA) concentration, and to compare its performance with a previous, manually defined NAA peak integration approach. MRI and non‐localizing, whole‐head 1H‐MRS were acquired at 3 T from 18 healthy volunteers, and their total NAA peak areas [comprising the NAA + N‐acetylaspartyl‐glutamate (NAAG) resonances] were obtained with both old and new methods, shown in the figure. The latter was shown to increase the reliability of WBNAA quantification by reducing susceptibility to operator and baseline bias, thereby enhancing its utility for monitoring the global progression and treatment response of diffuse neurological disorders.