Measurement and analysis of brain deformation during neurosurgery.

Recent studies have shown that the surface of the brain is deformed by up to 20 mm after the skull is opened during neurosurgery, which could lead to substantial error in commercial image-guided surgery systems. We quantitatively analyze the intraoperative brain deformation of 24 subjects to investigate whether simple rules can describe or predict the deformation. Interventional magnetic resonance images acquired at the start and end of the procedure are registered nonrigidly to obtain deformation values throughout the brain. Deformation patterns are investigated quantitatively with respect to the location and magnitude of deformation, and to the distribution and principal direction of the displacements. We also measure the volume change of the lateral ventricles by manual segmentation. Our study indicates that brain shift occurs predominantly in the hemisphere ipsi-lateral to the craniotomy, and that there is more brain deformation during resection procedures than during biopsy or functional procedures. However, the brain deformation patterns are extremely complex in this group of subjects. This paper quantitatively demonstrates that brain deformation occurs not only at the surface, but also in deeper brain structure, and that the principal direction of displacement does not always correspond with the direction of gravity. Therefore, simple computational algorithms that utilize limited intraoperative information (e.g., brain surface shift) will not always accurately predict brain deformation at the lesion.

Measures of folding applied to the development of the human fetal brain.

Previous work has suggested the existence of differences between the cerebral cortex of normal individuals, and those of patients with diseases such as epilepsy and schizophrenia. These shape abnormalities may be of developmental origin. Improved shape measures could provide useful tools for neuroscience research and patient diagnosis. We consider the theoretically desirable properties of measures of brain shape. We have implemented seven measures, three from the neuroscience literature, and four new to this field. Three of the measures are zero-order and four are second-order with respect to the surface. We validate the measures using simple geometrical shapes, and a collection of magnetic resonance scans of ten histologically normal ex vivo fetal brains with gestational ages from 19-42 weeks. We then apply the measures to MR scans from two histologically abnormal ex vivo brains. We demonstrate that our implementation of the measures is sensitive to anatomical variability rather than to the discreteness of the image data. All the measures were sensitive to changes in shape during fetal development. Several of the measures could distinguish between the normal and abnormal fetal brains. We propose a multivariate approach to studying the shape of the cerebral cortex, in which both zero-order and second-order measures are used to quantify folding.

Objective assessment of phantom image quality in mammography: a feasibility study.

The need for test objects in mammography quality control programmes to provide an objective measure of image quality pertinent to clinical problems is well documented. However, interobserver variations may be greater than the fluctuations in image quality that the quality control programme is seeking to detect. We have developed a computer algorithm to score a number of features in the Leeds TOR(MAX) mammography phantom. Threshold scoring techniques have been applied in the first instance; scoring schemes which utilize measures such as signal-to-noise ratio and modulation have also been formulated. This fully automatic algorithm has been applied to a set of 10 films which have been digitized at 25 microns resolution using a Joyce-Loebl scanning microdensitometer. The films were chosen retrospectively from quality control test films to demonstrate: (a) a range of optimized imaging systems, and (b) variation from the optimum. The performance of the algorithm has been compared with that of five experienced observers, and has been shown to be as consistent as individual observers, but more consistent than a pool of observers. Problems have been encountered with the detection of small details, indicating that a more sophisticated localization technique is desirable. The computer performs more successfully with the scoring scheme which utilizes the full imaging information available, rather than with the threshold-determined one. However, both the observers and the computer algorithm failed to identify the non-optimum films, suggesting that the sensitivity of the TOR(MAX) test object may not be adequate for modern mammography imaging systems.