Accurate, Robust, and Automated Longitudinal and Cross-Sectional Brain Change Analysis

• Published in: NeuroImage (Orlando, Fla.) Vol. 17; no. 1; pp. 479 - 489
• Main Authors: Smith, Stephen M., Zhang, Yongyue, Jenkinson, Mark, Chen, Jacqueline, Matthews, P.M., Federico, Antonio, De Stefano, Nicola
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.09.2002; Elsevier Limited
• Subjects: Algorithms; Atrophy; atrophy measurement; Brain - anatomy & histology; Brain - physiology; Cross-Sectional Studies; Epilepsy - pathology; Epilepsy - surgery; Frontal Lobe - anatomy & histology; Frontal Lobe - surgery; Humans; Image Processing, Computer-Assisted - methods; Longitudinal Studies; Magnetic Resonance Imaging; Neurosurgical Procedures; normalized registration; Reproducibility of Results; Skull - anatomy & histology; structural brain analysis; Time Factors; normalized registration; structural brain analysis; atrophy measurement
• ISSN: 1053-8119; 1095-9572
• DOI: 10.1006/nimg.2002.1040

Quantitative measurement of brain size, shape, and temporal change (for example, in order to estimate atrophy) is increasingly important in biomedical image analysis applications. New methods of structural analysis attempt to improve robustness, accuracy, and extent of automation. A fully automated method of longitudinal (temporal change) analysis, SIENA, was presented previously. In this paper, improvements to this method are described, and also an extension of SIENA to a new method for cross-sectional (single time point) analysis. The methods are fully automated, robust, and accurate: 0.15% brain volume change error (longitudinal): 0.5–1% brain volume accuracy for single-time point (cross-sectional). A particular advantage is the relative insensitivity to differences in scanning parameters. The methods provide easy manual review of their output by the automatic production of summary images which show the results of the brain extraction, registration, tissue segmentation, and final atrophy estimation.