Quantitative Diffusion and Spectroscopic Neuroimaging Combined with a Novel Early-Developmental Assessment Improves Models for 1-Year Developmental Outcomes.

BACKGROUND AND PURPOSE: Preterm infants are at risk for overt and silent CNS injury, with developmental consequences that are difficult to predict. The novel Specific Test of Early Infant Motor Performance, administered in preterm infants at term age, is indicative of later developmental gross motor and cognitive scores at 12 months. Here, we assessed whether functional performance on this early assessment correlates with CNS integrity via MR spectroscopy or diffusional kurtosis imaging and whether these quantitative neuroimaging methods improve predictions for future 12-month developmental scores. MATERIALS AND METHODS: MR spectroscopy and quantitative diffusion MR imaging data were acquired in preterm infants (n = 16) at term. Testing was performed at term and 3 months using the Specific Test of Early Infant Motor Performance and the Bayley Scales of Infant and Toddler Development, Third Edition, at 12 months. We modeled the relationship of MR spectroscopy and diffusion MR imaging data with both test scores via multiple linear regression. RESULTS: MR spectroscopy NAA ratios at a TE of 270 ms in the frontal WM and basal ganglia and kurtosis metrics in major WM tracts correlated strongly with total Specific Test of Early Infant Motor Performance scores. The addition of MR spectroscopy and diffusion separately improved the functional predictions of 12-month outcomes. CONCLUSIONS: Microstructural integrity of the major WM tracts and metabolism in the basal ganglia and frontal WM strongly correlate with early developmental performance, suggesting that the Specific Test of Early Infant Motor Performance reflects CNS integrity after preterm birth. This study demonstrates that combining quantitative neuroimaging and early functional movement improves the prediction of 12-month outcomes in premature infants.

Quantitative assessment of iron accumulation in the deep gray matter of multiple sclerosis by magnetic field correlation imaging.

BACKGROUND AND PURPOSE: Deposition of iron has been recognized recently as an important factor of pathophysiologic change including neurodegenerative processes in multiple sclerosis (MS). We propose that there is an excess accumulation of iron in the deep gray matter in patients with MS that can be measured with a newly developed quantitative MR technique--magnetic field correlation (MFC) imaging. MATERIALS AND METHODS: With a 3T MR system, we studied 17 patients with relapsing-remitting MS and 14 age-matched healthy control subjects. We acquired MFC imaging using an asymmetric single-shot echo-planar imaging sequence. Regions of interest were selected in both deep gray matter and white matter regions, and the mean MFC values were compared between patients and controls. We also correlated the MFC data with lesion load and neuropsychologic tests in the patients. RESULTS: MFC measured in the deep gray matter in patients with MS was significantly higher than that in the healthy controls (P < or = .03), with an average increase of 24% in the globus pallidus, 39.5% in the putamen, and 30.6% in the thalamus. The increased iron deposition measured with MFC in the deep gray matter in the patients correlated positively with the total number of MS lesions (thalamus: r = 0.61, P = .01; globus pallidus: r = 0.52, P = .02). A moderate but significant correlation between the MFC value in the deep gray matter and the neuropsychologic tests was also found. CONCLUSION: Quantitative measurements of iron content with MFC demonstrate increased accumulation of iron in the deep gray matter in patients with MS, which may be associated with the disrupted iron outflow pathway by lesions. Such abnormal accumulation of iron may contribute to neuropsychologic impairment and have implications for neurodegenerative processes in MS.

Quantitative model for the interecho time dependence of the CPMG relaxation rate in iron-rich gray matter.

A quantitative model is proposed for computing the dependence on the interecho time of the NMR relaxation rate in iron-rich gray matter obtained with a Carr-Purcell-Meiboom-Gill sequence. The model consists of representing oligodendrocytes as identical magnetic spheres arranged in a spatially random pattern, and in approximating water diffusion as isotropic and unrestricted. Predictions of the model are calculated numerically using a Monte Carlo technique and, for the weak field limit, using an analytic formula. The model is shown to provide a good fit to experimental measurements of in vitro samples of monkey brain at field levels of 1.0 T and 1.5 T. These field levels are not sufficient to fully determine the model parameters, but it is argued that this may be possible at 3.0 T. The model is potentially of value for multiple-spin-echo MRI studies of iron-related neurodegenerative disorders, such as Parkinson's disease. In particular, the model can be applied to correlate MRI data with the cellular distribution of iron in gray matter. Magn Reson Med 46:159-165, 2001.

Strong field behavior of the NMR signal from magnetically heterogeneous tissues.

A theory for the behavior of the nuclear magnetic resonance (NMR) signal obtained from magnetically heterogeneous tissues is developed for the limit of a strong external magnetic field. If BO is the magnitude of the external magnetic field, it is found that a free-induction signal decays in a time scaling as 1/Bo, a single-spin echo signal decays in a time scaling as 1/Bo(2/3), and a multiple-spin echo signal decays in a time scaling as 1/Bo(2). Moreover, it is shown that the form of the signal decay for a multiple-spin echo sequence may deviate significantly from an exponential. Numerical results for a model consisting of randomly distributed magnetic spheres are used to confirm the theory. In addition, good agreement is demonstrated between the theory and experimental measurements obtained with particle suspensions. The validity and application of the theory to biological tissues are discussed.