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Neonatal Brain Development assessed by new quantitative Analysis of 3-Tesla MRI and DTI 1,2G Gerig, 2Pierre Fillard, 2M Prastawa, 3W Lin, 1John Gilmore, Departments of 1Psychiatry, 2Computer Science, 3Radiology University of North Carolina, Chapel Hill,NC 27614, USA, [email protected] / http://www.cs.unc.edu/~gerig Diffusion Tensor Imaging (DTI) SUMMARY • Research: Quantitative MRI to study unsedated newborns at risk for neurodevelopmental disorders. • Clinical Study: 120 newborns to e brecruited at UNC, age at MRI about 2 weeks • Motivation: Early detection of abnormalities Possibility for early intervention and therapy. • Imaging: High field (3T Siemens Allegra), high resolution (T1 1mm3, FSE 0.9x0.9x3mm3), high-speed Adult imaging (12’ for T1, FSE and DTI). T1 3D MPRage 1x1x1 mm3 FSE T2w 1x1x3 mm3 Conventional ROI Analysis (one axial slice only) Neonate • Challenge: Very low CNR, heterogeneous tissue, early myelination regions, reverse contrast wm/gm. • Standard brain tissue segmentation fails. FSE PDw 1x1x3 mm3 Structural MRI 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 adult neonate adult neonate Neonates G M fro nt al oc cip it a l In te rn al ca p Adults ge nu sp le ni um FA (%) Fractional Anisotropy Apparent Diffusion Coefficient ADC (mm2/sec) Hypothesis: • DTI reflects degree of myelination and structure of fiber tracts. • Decrease of fractional anisotropy (FA) from interior to the periphery. • Higher ADC values compared to a matured brain (adult). • Lower FA values compared to adults. • DTI reflects degree of axon pruning and myelination. 200 180 160 140 120 100 80 60 40 20 0 Neonates Adults Zhai G, Lin W, Wilber K, Gerig G, Gilmore JH (2003): Comparisons of regional white matter fractional anisotropy in healthy neonates and adults using a 3T head-only scanner. Radiology (in print). New Method: Diffusion along fiber tract via Tractography Tracing of the commissural fiber tracts through the genu in five neonates splenium Approach: • Atlas-moderated EM segmentation (cf. Leemput and Warfield) • Tissue intensity model for white matter (non-myelinated and myelinated wm form bimodal distribution) (cf. Cocosco, Prastawa) Fractional Anisotropy (FA) along splenium/genu bundles FA Building of Atlas Template Template MRI white matter gray matter FA • Fractional Anisotropy (FA) quickly drops with increasing distance from midsagittal plane • Drop off more pronounced in genu than in splenium csf Change of FA along splenium/genu across time Here Text Here Text Tissue Probability Maps • Comparisum adults, 2yrs olds and neonates • FA in neonates significantly lower than in 2 yrs old subjects and adults • 2yrs old subjects show similar values as adults T1-only segmentation white gray csf myelin. hyperintense motor cortex early myelinated corticospinal tract CONCLUSIONS • It is feasible to study brain development in unsedated newborns using 3T MRI • Study will likely provide a vastly improved understanding of early brain development and its relationship to neuropsychiatric disorders. • Novelty: Tissue model for segmentation of myelinated/nonmyel. white matter. • Novelty: Use of tractography for complex regions of interest analysis. Literature • Gilmore JH, Gerig G, Specter B, Charles HC, Wilber JS, Hertzberg BS, Kliewer MA (2001a): Neonatal cerebral ventricle volume: a comparison of 3D ultrasound and magnetic resonance imaging. Ultrasound Med and Biol 27:1143-1146. Preliminary Results UNC Neonate Study Brain Tissue Volume Neonates • Zhai G, Lin W, Wilber K, Gerig G, Gilmore JH (2003): Comparison of regional white matter fractional anisotrophy in healthy neonates and adults using a 3T head-only scanner. Radiology 229, 2003, pp. 673-681 600.00 500.00 400.00 wm-myel 300.00 csf 200.00 gm 100.00 cases n40 n33 n32 n31 n26 n25 n23 n18 n10 n0002 0.00 wm-nonmyel n0001 volume (ml) • Preliminary Study: 20 normal neonates (10 males, 10 females) • Age 16 ± 4 days • Siemens 3T head-only scanner • Neonates were fed prior to scanning, swaddled, fitted with ear protection and had their heads fixed in a vac-fix device • A pulse oximeter was monitored by a physician or research nurse • Most neonates slept during the scan • Motion-free scans in 13-15 infants • Conte Center: Total of 120 infants • Huppi PS, Warfield S, Kikinis R, Barnes PD, Zientara GP, Jolesz FA, Tsuji MK, Volpe JJ (1998b): Quantitative magnetic resonance imaging of brain development in premature and normal newborns. Ann Neurol 43: 224-235. • Warfield, S., Kaus, M., Jolesz, F., Kikinis, R.: Adaptive template moderated spa-tially varying statistical classification. In Wells, W.M.e.a., ed.: Medical Image Computing and Computer-Assisted Intervention (MICCAI’98). Volume 1496 of LNCS., Springer 1998 • Van Leemput, K., Maes, F., Vandermeulen, D., Suetens, P.: Automated model-based tissue classification of MR images of the brain. IEEE Transactions on Medical Imaging 18 (1999) 897–908 • Pierre Fillard, John Gilmore, Weili Lin, Guido Gerig, "Quantitative Analysis of White Matter Fiber Properties along Geodesic Paths", Lecture Notes in Computer Science LNCS #2879 Springer, Nov. 2003, pp. 16-23 • Guido Gerig, Marcel Prastawa, Weili Lin and John Gilmore, "Assessing Early Brain Development in Neonates by Segmentation of High-Resolution 3T MRI", LNCS #2879, Springer, Nov. 2003, Supported by NIH Conte Center MH064065, Neurodevelopmental Disorders Research Center HD 03110 and the Theodore and Vada Stanley Foundation.