Publications by Year: 2005

Andy Tsai, William M Wells III, Simon K Warfield, and Alan S Willsky. 10/2005. “An EM Algorithm for Shape Classification Based on Level Sets.” Med Image Anal, 9, 5, Pp. 491-502.Abstract

In this paper, we propose an expectation-maximization (EM) approach to separate a shape database into different shape classes, while simultaneously estimating the shape contours that best exemplify each of the different shape classes. We begin our formulation by employing the level set function as the shape descriptor. Next, for each shape class we assume that there exists an unknown underlying level set function whose zero level set describes the contour that best represents the shapes within that shape class. The level set function for each example shape in the database is modeled as a noisy measurement of the appropriate shape class's unknown underlying level set function. Based on this measurement model and the judicious introduction of the class labels as the hidden data, our EM formulation calculates the labels for shape classification and estimates the shape contours that best typify the different shape classes. This resulting iterative algorithm is computationally efficient, simple, and accurate. We demonstrate the utility and performance of this algorithm by applying it to two medical applications.

Kilian M Pohl, John Fisher, Ron Kikinis, Eric WL Grimson, and William M Wells. 10/2005. “Shape Based Segmentation of Anatomical Structures in Magnetic Resonance Images.” Comput Vis Biomed Image Appl, 3765, Pp. 489-98.Abstract
Standard image based segmentation approaches perform poorly when there is little or no contrast along boundaries of different regions. In such cases, segmentation is largely performed manually using prior knowledge of the shape and relative location of the underlying structures combined with partially discernible boundaries. We present an automated approach guided by covariant shape deformations of neighboring structures, which is an additional source of prior information. Captured by a shape atlas, these deformations are transformed into a statistical model using the logistic function. Structure boundaries, anatomical labels, and image inhomogeneities are estimated simultaneously within an Expectation-Maximization formulation of the maximum a posteriori probability estimation problem. We demonstrate the approach on 20 brain magnetic resonance images showing superior performance, particularly in cases where purely image based methods fail.
Eric R Cosman and William M Wells III. 7/2005. “Bayesian Population Modeling of Effective Connectivity.” Inf Process Med Imaging, 19, Pp. 39-51.Abstract

A hierarchical model based on the Multivariate Autoregessive (MAR) process is proposed to jointly model neurological time-series collected from multiple subjects, and to characterize the distribution of MAR coefficients across the population from which those subjects were drawn. Thus, inference about effective connectivity between brain regions may be generalized beyond those subjects studied. The posterior on population- and subject-level connectivity parameters are estimated in a Variational Bayesian (VB) framework, and structural model parameters are chosen by the corresponding evidence criteria. The significance of resulting connectivity statistics are evaluated by permutation-based approximations to the null distribution. The method is demonstrated on simulated data and on actual multi-subject neurological time-series.

Marek Kubicki, Hongkun Park, CF Westin, Paul G Nestor, Robert V Mulkern, Stephan E Maier, Margaret Niznikiewicz, Erin Connor, James J Levitt, Melissa Frumin, Ron Kikinis, Ferenc A Jolesz, Robert W McCarley, and Martha E Shenton. 7/2005. “DTI and MTR Abnormalities in Schizophrenia: Analysis of White Matter Integrity.” Neuroimage, 26, 4, Pp. 1109-18.Abstract

Diffusion tensor imaging (DTI) studies in schizophrenia demonstrate lower anisotropic diffusion within white matter due either to loss of coherence of white matter fiber tracts, to changes in the number and/or density of interconnecting fiber tracts, or to changes in myelination, although methodology as well as localization of such changes differ between studies. The aim of this study is to localize and to specify further DTI abnormalities in schizophrenia by combining DTI with magnetization transfer imaging (MTI), a technique sensitive to myelin and axonal alterations in order to increase specificity of DTI findings. 21 chronic schizophrenics and 26 controls were scanned using Line-Scan-Diffusion-Imaging and T1-weighted techniques with and without a saturation pulse (MT). Diffusion information was used to normalize co-registered maps of fractional anisotropy (FA) and magnetization transfer ratio (MTR) to a study-specific template, using the multi-channel daemon algorithm, designed specifically to deal with multidirectional tensor information. Diffusion anisotropy was decreased in schizophrenia in the following brain regions: the fornix, the corpus callosum, bilaterally in the cingulum bundle, bilaterally in the superior occipito-frontal fasciculus, bilaterally in the internal capsule, in the right inferior occipito-frontal fasciculus and the left arcuate fasciculus. MTR maps demonstrated changes in the corpus callosum, fornix, right internal capsule, and the superior occipito-frontal fasciculus bilaterally; however, no changes were noted in the anterior cingulum bundle, the left internal capsule, the arcuate fasciculus, or inferior occipito-frontal fasciculus. In addition, the right posterior cingulum bundle showed MTR but not FA changes in schizophrenia. These findings suggest that, while some of the diffusion abnormalities in schizophrenia are likely due to abnormal coherence, or organization of the fiber tracts, some of these abnormalities may, in fact, be attributed to or coincide with myelin/axonal disruption.

Simon K Warfield, Steven J Haker, Ion-Florin Talos, Corey A Kemper, Neil Weisenfeld, Andrea UJ Mewes, Daniel Goldberg-Zimring, Kelly H Zou, Carl-Fredrik Westin, William M Wells III, Clare M Tempany, Alexandra Golby, Peter M Black, Ferenc A Jolesz, and Ron Kikinis. 4/2005. “Capturing Intraoperative Deformations: Research Experience at Brigham and Women's Hospital.” Med Image Anal, 9, 2, Pp. 145-62.Abstract

During neurosurgical procedures the objective of the neurosurgeon is to achieve the resection of as much diseased tissue as possible while achieving the preservation of healthy brain tissue. The restricted capacity of the conventional operating room to enable the surgeon to visualize critical healthy brain structures and tumor margin has lead, over the past decade, to the development of sophisticated intraoperative imaging techniques to enhance visualization. However, both rigid motion due to patient placement and nonrigid deformations occurring as a consequence of the surgical intervention disrupt the correspondence between preoperative data used to plan surgery and the intraoperative configuration of the patient's brain. Similar challenges are faced in other interventional therapies, such as in cryoablation of the liver, or biopsy of the prostate. We have developed algorithms to model the motion of key anatomical structures and system implementations that enable us to estimate the deformation of the critical anatomy from sequences of volumetric images and to prepare updated fused visualizations of preoperative and intraoperative images at a rate compatible with surgical decision making. This paper reviews the experience at Brigham and Women's Hospital through the process of developing and applying novel algorithms for capturing intraoperative deformations in support of image guided therapy.

Leslie Wolfson, Xingchang Wei, Charles B Hall, Victoria Panzer, Dorothy Wakefield, Randall R Benson, Julia A Schmidt, Simon K Warfield, and Charles RG Guttmann. 2005. “Accrual of MRI white matter abnormalities in elderly with normal and impaired mobility.” J Neurol Sci, 232, 1-2, Pp. 23-7.Abstract
White matter signal abnormality (WMSA) is often present in the MRIs of older persons with mobility impairment. We examined the relationship between impaired mobility and the progressive accrual of WMSA. Mobility was assessed with the Short Physical Performance Battery (SPPB) and quantitative measures of gait and balance. Fourteen subjects had baseline and follow-up MRI scans performed 20 months apart. WMSA was detected and quantified using automated computer algorithms. In the control subjects, WMSA volume increased by 0.02+/-0.05% ICCV (percent intracranial cavity volume)/year while the WMSA of mobility impaired subjects increased five-times faster (0.10+/-0.10 ICCV/year, p=0.03). WMSA volume was related to some of the mobility measures and was sensitive to change which was not true of the other MRI variables. The study demonstrates the sensitivity of longitudinal automated volumetric analysis of WMSA to differentiate differences in the accrual rate of WMSA in groups selected on the basis of mobility. Based on these results, we propose that a subset of subjects with mobility impairment have accelerated, disease related WMSA accrual, thus explaining the rapid progression of mobility impairment in some older persons without apparent cause. This study demonstrates that quantitative MRI and performance measures can provide valuable insight into the rate of progression and pathophysiologic abnormalities underlying mobility impairment.
Mahnaz Maddah, Andrea UJ Mewes, Steven Haker, Eric WL Grimson, and Simon K Warfield. 2005. “Automated atlas-based clustering of white matter fiber tracts from DTMRI.” Med Image Comput Comput Assist Interv, 8, Pt 1, Pp. 188-95.Abstract
A new framework is presented for clustering fiber tracts into anatomically known bundles. This work is motivated by medical applications in which variation analysis of known bundles of fiber tracts in the human brain is desired. To include the anatomical knowledge in the clustering, we invoke an atlas of fiber tracts, labeled by the number of bundles of interest. In this work, we construct such an atlas and use it to cluster all fiber tracts in the white matter. To build the atlas, we start with a set of labeled ROIs specified by an expert and extract the fiber tracts initiating from each ROI. Affine registration is used to project the extracted fiber tracts of each subject to the atlas, whereas their B-spline representation is used to efficiently compare them to the fiber tracts in the atlas and assign cluster labels. Expert visual inspection of the result confirms that the proposed method is very promising and efficient in clustering of the known bundles of fiber tracts.
Adam Wittek, Ron Kikinis, Simon K Warfield, and Karol Miller. 2005. “Brain shift computation using a fully nonlinear biomechanical model.” Med Image Comput Comput Assist Interv, 8, Pt 2, Pp. 583-90.Abstract
In the present study, fully nonlinear (i.e. accounting for both geometric and material nonlinearities) patient specific finite element brain model was applied to predict deformation field within the brain during the craniotomy-induced brain shift. Deformation of brain surface was used as displacement boundary conditions. Application of the computed deformation field to align (i.e. register) the preoperative images with the intraoperative ones indicated that the model very accurately predicts the displacements of gravity centers of the lateral ventricles and tumor even for very limited information about the brain surface deformation. These results are sufficient to suggest that nonlinear biomechanical models can be regarded as one possible way of complementing medical image processing techniques when conducting nonrigid registration. Important advantage of such models over the linear ones is that they do not require unrealistic assumptions that brain deformations are infinitesimally small and brain tissue stress-strain relationship is linear.
Polina Golland, Eric WL Grimson, Martha E Shenton, and Ron Kikinis. 2005. “Detection and analysis of statistical differences in anatomical shape.” Med Image Anal, 9, 1, Pp. 69-86.Abstract
We present a computational framework for image-based analysis and interpretation of statistical differences in anatomical shape between populations. Applications of such analysis include understanding developmental and anatomical aspects of disorders when comparing patients versus normal controls, studying morphological changes caused by aging, or even differences in normal anatomy, for example, differences between genders. Once a quantitative description of organ shape is extracted from input images, the problem of identifying differences between the two groups can be reduced to one of the classical questions in machine learning of constructing a classifier function for assigning new examples to one of the two groups while making as few misclassifications as possible. The resulting classifier must be interpreted in terms of shape differences between the two groups back in the image domain. We demonstrate a novel approach to such interpretation that allows us to argue about the identified shape differences in anatomically meaningful terms of organ deformation. Given a classifier function in the feature space, we derive a deformation that corresponds to the differences between the two classes while ignoring shape variability within each class. Based on this approach, we present a system for statistical shape analysis using distance transforms for shape representation and the support vector machines learning algorithm for the optimal classifier estimation and demonstrate it on artificially generated data sets, as well as real medical studies.
Daniel Goldberg-Zimring, Andrea UJ Mewes, Mahnaz Maddah, and Simon K Warfield. 2005. “Diffusion tensor magnetic resonance imaging in multiple sclerosis.” J Neuroimaging, 15, 4 Suppl, Pp. 68S-81S.Abstract
Multiple sclerosis (MS), a demyelinating disease, occurs principally in the white matter (WM) of the central nervous system. Conventional magnetic resonance imaging (MRI) is sensitive to some, but not all, brain changes associated with MS. Diffusion-weighted imaging (DWI) provides information about water diffusion in tissue and diffusion tensor MRI (DT-MRI) about fiber direction, allowing for the identification of WM abnormalities that are not apparent on conventional MRI images. These techniques can quantitatively characterize the local microstructure of tissues. MS-associated disease processes lead to regions characterized by an increased amount of water diffusion and a decrease in the anisotropy of diffusion direction. These changes have been found to produce different patterns in MS patients presenting different courses of the disease. Changes in water diffusion may allow examination of the type, appearance, enhancement, and location of lesions not readily visible by other means. Ongoing studies of MS are integrating conventional MRI and DT-MRI measures with connectivity-based regional assessment, aiming to provide a better understanding of the nature and the location of WM lesions. This integration and the development of novel image-processing and visualization techniques may improve the understanding of WM architecture and its disruption in MS. This article presents a brief history of DWI, its basic principles and applications in the study of MS, a review of the properties and applications of DT-MRI, and their use in the study of MS. In addition, this article illustrates the methodology for the analysis of DT-MRI in ongoing studies of MS.
Aloys du Bois d'Aische, Mathieu De Craene, Xavier Geets, Vincent Gregoire, Benoit Macq, and Simon K Warfield. 2005. “Efficient multi-modal dense field non-rigid registration: alignment of histological and section images.” Med Image Anal, 9, 6, Pp. 538-46.Abstract
We describe a new algorithm for non-rigid registration capable of estimating a constrained dense displacement field from multi-modal image data. We applied this algorithm to capture non-rigid deformation between digital images of histological slides and digital flat-bed scanned images of cryotomed sections of the larynx, and carried out validation experiments to measure the effectiveness of the algorithm. The implementation was carried out by extending the open-source Insight ToolKit software. In diagnostic imaging of cancer of the larynx, imaging modalities sensitive to both anatomy (such as MRI and CT) and function (PET) are valuable. However, these modalities differ in their capability to discriminate the margins of tumor. Gold standard tumor margins can be obtained from histological images from cryotomed sections of the larynx. Unfortunately, the process of freezing, fixation, cryotoming and staining the tissue to create histological images introduces non-rigid deformations and significant contrast changes. We demonstrate that the non-rigid registration algorithm we present is able to capture these deformations and the algorithm allows us to align histological images with scanned images of the larynx. Our non-rigid registration algorithm constructs a deformation field to warp one image onto another. The algorithm measures image similarity using a mutual information similarity criterion, and avoids spurious deformations due to noise by constraining the estimated deformation field with a linear elastic regularization term. The finite element method is used to represent the deformation field, and our implementation enables us to assign inhomogeneous material characteristics so that hard regions resist internal deformation whereas soft regions are more pliant. A gradient descent optimization strategy is used and this has enabled rapid and accurate convergence to the desired estimate of the deformation field. A further acceleration in speed without cost of accuracy is achieved by using an adaptive mesh refinement strategy.
Marc Niethammer, Patricio A Vela, and Allen Tannenbaum. 2005. “On the Evolution of Vector Distance Functions of Closed Curves.” Int J Comput Vis, 65, 1-2, Pp. 5-27.Abstract
Inspired by the work by Gomes et al., we describe and analyze a vector distance function approach for the implicit evolution of closed curves of codimension larger than one. The approach is set up in complete generality, and then applied to the evolution of dynamic geometric active contours in [Formula: see text] (codimension three case). In order to carry this out one needs an explicit expression for the zero level set for which we propose a discrete connectivity method. This leads us to make connections with the new theory of cubical homology. We provide some explicit simulation results in order to illustrate the methodology.
Motoaki Nakamura, Robert W McCarley, Marek Kubicki, Chandlee C Dickey, Margaret A Niznikiewicz, Martina M Voglmaier, Larry J Seidman, Stephan E Maier, Carl-Fredrik Westin, Ron Kikinis, and Martha E Shenton. 2005. “Fronto-temporal disconnectivity in schizotypal personality disorder: a diffusion tensor imaging study.” Biol Psychiatry, 58, 6, Pp. 468-78.Abstract
BACKGROUND: Using diffusion tensor imaging (DTI), we previously reported abnormalities in two critical white matter tracts in schizophrenia, the uncinate fasciculus (UF) and the cingulum bundle (CB), both related to fronto-temporal connectivity. Here, we investigate these two bundles in unmedicated subjects with schizotypal personality disorder (SPD). METHODS: Fifteen male SPD subjects and 15 male control subjects were scanned with line-scan DTI. Fractional anisotropy (FA) and mean diffusivity (D(m)) were used to quantify water diffusion, and cross-sectional area was defined with a directional threshold method. Exploratory correlation analyses were evaluated with Spearman's rho, followed by post hoc hierarchical regression analyses. RESULTS: We found bilaterally reduced FA in the UF of SPD subjects. For CB, there was no significant group difference for FA or D(m) measures. Additionally, in SPD, reduced FA in the right UF was correlated with clinical symptoms, including ideas of reference, suspiciousness, restricted affect, and social anxiety. In contrast, left UF area was correlated with measures of cognitive function, including general intelligence, verbal and visual memory, and executive performance. CONCLUSIONS: These findings in SPD suggest altered fronto-temporal connectivity through the UF, similar to findings in schizophrenia, and intact neocortical-limbic connectivity through the CB, in marked contrast with what has been reported in schizophrenia.
Federico Simmross-Wattenberg, Noemí Carranza-Herrezuelo, Cristina Palacios-Camarero, Pablo Casaseca-de-la-Higuera, Miguel Angel Martín-Fernández, Santiago Aja-Fernández, Juan Ruiz-Alzola, Carl-Fredrik Westin, and Carlos Alberola-López. 2005. “Group-Slicer: a collaborative extension of 3D-Slicer.” J Biomed Inform, 38, 6, Pp. 431-42.Abstract
In this paper, we describe a first step towards a collaborative extension of the well-known 3D-Slicer; this platform is nowadays used as a standalone tool for both surgical planning and medical intervention. We show how this tool can be easily modified to make it collaborative so that it may constitute an integrated environment for expertise exchange as well as a useful tool for academic purposes.
Eric Pichon, Carl-Fredrik Westin, and Allen R Tannenbaum. 2005. “A Hamilton-Jacobi-Bellman approach to high angular resolution diffusion tractography.” Med Image Comput Comput Assist Interv, 8, Pt 1, Pp. 180-7.Abstract
This paper describes a new framework for white matter tractography in high angular resolution diffusion data. A direction-dependent local cost is defined based on the diffusion data for every direction on the unit sphere. Minimum cost curves are determined by solving the Hamilton-Jacobi-Bellman using an efficient algorithm. Classical costs based on the diffusion tensor field can be seen as a special case. While the minimum cost (or equivalently the travel time of a particle moving along the curve) and the anisotropic front propagation frameworks are related, front speed is related to particle speed through a Legendre transformation which can severely impact anisotropy information for front propagation techniques. Implementation details and results on high angular diffusion data show that this method can successfully take advantage of the increased angular resolution in high b-value diffusion weighted data despite lower signal to noise ratio.
Yan Yang, Lei Zhu, Steven Haker, Allen R Tannenbaum, and Don P Giddens. 2005. “Harmonic skeleton guided evaluation of stenoses in human coronary arteries.” Med Image Comput Comput Assist Interv, 8, Pt 1, Pp. 490-7.Abstract
This paper presents a novel approach that three-dimensionally visualizes and evaluates stenoses in human coronary arteries by using harmonic skeletons. A harmonic skeleton is the center line of a multi-branched tubular surface extracted based on a harmonic function, which is the solution of the Laplace equation. This skeletonization method guarantees smoothness and connectivity and provides a fast and straightforward way to calculate local cross-sectional areas of the arteries, and thus provides the possibility to localize and evaluate coronary artery stenosis, which is a commonly seen pathology in coronary artery disease.
Olivier Clatz, Hervé Delingette, Ion-Florin Talos, Alexandra J Golby, Ron Kikinis, Ferenc A Jolesz, Nicholas Ayache, and Simon K Warfield. 2005. “Hybrid formulation of the model-based non-rigid registration problem to improve accuracy and robustness.” Med Image Comput Comput Assist Interv, 8, Pt 2, Pp. 295-302.Abstract
We present a new algorithm to register 3D pre-operative Magnetic Resonance (MR) images with intra-operative MR images of the brain. This algorithm relies on a robust estimation of the deformation from a sparse set of measured displacements. We propose a new framework to compute iteratively the displacement field starting from an approximation formulation (minimizing the sum of a regularization term and a data error term) and converging toward an interpolation formulation (least square minimization of the data error term). The robustness of the algorithm is achieved through the introduction of an outliers rejection step in this gradual registration process. We ensure the validity of the deformation by the use of a biomechanical model of the brain specific to the patient, discretized with the finite element method. The algorithm has been tested on six cases of brain tumor resection, presenting a brain shift up to 13 mm.
Catherine Limperopoulos, Janet S Soul, Haissam Haidar, Petra S Huppi, Haim Bassan, Simon K Warfield, Richard L Robertson, Marianne Moore, Patricia Akins, Joseph J Volpe, and Adré J du Plessis. 2005. “Impaired trophic interactions between the cerebellum and the cerebrum among preterm infants.” Pediatrics, 116, 4, Pp. 844-50.Abstract
BACKGROUND: Advanced neuroimaging techniques have brought increasing recognition of cerebellar injury among premature infants. The developmental relationship between early brain injury and effects on the cerebrum and cerebellum remains unclear. OBJECTIVES: To examine whether cerebral parenchymal brain lesions among preterm infants are associated with subsequent decreases in cerebellar volume and, conversely, whether primary cerebellar injury is associated with decreased cerebral brain volumes, with advanced, 3-dimensional, volumetric MRI at term gestational age equivalent. METHODS: Total cerebellar volumes and cerebellar gray and myelinated white matter volumes were determined through manual outlining for 74 preterm infants with unilateral periventricular hemorrhagic infarction (14 infants), bilateral diffuse periventricular leukomalacia (20 infants), cerebellar hemorrhage (10 infants), or normal term gestational age equivalent MRI findings (30 infants). Total brain and right/left cerebral and cerebellar hemispheric volumes were calculated. RESULTS: Unilateral cerebral brain injury was associated with significantly decreased volume of the contralateral cerebellar hemisphere. Conversely, unilateral primary cerebellar injury was associated with a contralateral decrease in supratentorial brain volume. Cerebellar gray matter and myelinated white matter volumes were reduced significantly not only among preterm infants with primary cerebellar hemorrhage but also among infants with cerebral parenchymal brain injury. CONCLUSIONS: These data suggest strongly that both reduction in contralateral cerebellar volume with unilateral cerebral parenchymal injury and reduction in total cerebellar volume with bilateral cerebral lesions are related to trophic transsynaptic effects. Early-life cerebellar injury may contribute importantly to the high rates of cognitive, behavioral, and motor deficits reported for premature infants.
Laura C Wiegand, Simon K Warfield, James J Levitt, Yoshio Hirayasu, Dean F Salisbury, Stephan Heckers, Sylvain Bouix, Daniel Schwartz, Magdalena Spencer, Chandlee C Dickey, Ron Kikinis, Ferenc A Jolesz, Robert W McCarley, and Martha E Shenton. 2005. “An in vivo MRI study of prefrontal cortical complexity in first-episode psychosis.” Am J Psychiatry, 162, 1, Pp. 65-70.Abstract
OBJECTIVE: The purpose of this study was to investigate abnormalities in the surface complexity of the prefrontal cortex and in the hemispheric asymmetry of cortical complexity in first-episode patients with schizophrenia. METHOD: An estimate of the surface complexity of the prefrontal cortex was derived from the number of voxels along the boundary between gray matter and CSF. Magnetic resonance imaging scans were acquired from patients with a first episode of schizophrenia (N=17), patients with a first episode of affective psychosis (N=17), and normal comparison subjects (N=17), age-matched within a narrow age range (18-29 years). This study group was the focus of a previous study that showed lower prefrontal cortical volume in patients with schizophrenia. RESULTS: Prefrontal cortical complexity was not significantly different among the groups. However, the schizophrenia patients differed significantly from the normal comparison subjects in asymmetry, with the schizophrenia patients showing less left-greater-than-right asymmetry in cortical complexity than the comparison subjects. CONCLUSIONS: An abnormal pattern of asymmetry in the prefrontal cortex of first-episode patients with schizophrenia provides evidence for a neurodevelopmental mechanism in the etiology of schizophrenia.
Catherine Limperopoulos, Janet S Soul, Kimberlee Gauvreau, Petra S Huppi, Simon K Warfield, Haim Bassan, Richard L Robertson, Joseph J Volpe, and Adré J du Plessis. 2005. “Late gestation cerebellar growth is rapid and impeded by premature birth.” Pediatrics, 115, 3, Pp. 688-95.Abstract
OBJECTIVE: Cognitive impairments and academic failure are commonly reported in survivors of preterm birth. Recent studies suggest an important role for the cerebellum in the development of cognitive and social functions. The objective of this study was to examine the impact of prematurity itself, as well as prematurity-related brain injuries, on early postnatal cerebellar growth with quantitative MRI. METHODS: Advanced 3-dimensional volumetric MRI was performed and cerebellar volumes were obtained by manual outlining in preterm (<37 weeks) and healthy term-born infants. Intracranial and total brain volumes were also calculated. RESULTS: A total of 169 preterm and 20 healthy full-term infants were studied; 145 had preterm MRI (pMRI), 75 had term MRI (tMRI), and 51 underwent both pMRI and tMRI. From 28 weeks' postconceptional age to term, mean cerebellar volume (177%) in preterm infants increased at a much faster rate than did mean intracranial (110%) or mean brain (107%) volumes. Smaller cerebellar volume was significantly related to lower gestational age at birth and to intracranial and total brain volumes. Mean cerebellar volume of preterm infants at tMRI was significantly smaller than the volumes of term-born infants. Cerebellar growth impairment was correlated strongly with associated brain injuries, even in the absence of direct cerebellar injury. CONCLUSIONS: Our data suggest that the growth of the immature cerebellum is particularly rapid during late gestation. However, this accelerated growth seems to be impeded by premature birth and associated brain injury. The long-term neurodevelopmental disabilities seen in survivors of premature birth may be attributable in part to impaired cerebellar development.