Brain atlas deformation in the presence of small and large space-occupying tumors.

Brain atlases contain a wealth of information that could be used in radiation therapy or neurosurgical planning. Until now, however, when large space-occupying tumors and lesions drastically alter the shape of brain structures and substructures, atlas-based methods have been of limited use. In this work, we present a new technique that permits a brain atlas to be warped onto image volumes in which large lesions are present. First we show that a method previously used for atlas-based segmentation of normal brains can also be used for brains with small lesions. We then present an extension of this technique for brains with large lesions. This involves several steps: a global registration to bring the two volumes into approximate correspondence; a local registration to warp the atlas onto the patient volume; the seeding of the warped atlas with a tumor model derived from patient data; and the deformation of the seeded atlas. Global registration is performed using a mutual information criterion. The method we have used for atlas warping is derived from optical flow principles. Preliminary results obtained on real patient images are presented. These results indicate that the proposed method can be used to automatically segment structures of interest in brains with gross deformation. Potential areas of application for this method include automatic labeling of critical structures for radiation therapy and presurgical planning.

Comparison of functional MRI image realignment tools using a computer-generated phantom.

This study discusses the development of a computer-generated phantom to compare the effects of image realignment programs on functional MRI (fMRI) pixel activation. The phantom is a whole-head MRI volume with added random noise, activation, and motion. It allows simulation of realistic head motions with controlled areas of activation. Without motion, the phantom shows the effects of realignment on motion-free data sets. Prior to realignment, the phantom illustrates some activation corruption due to motion. Finally, three widely used realignment packages are examined. The results showed that the most accurate algorithms are able to increase specificity through accurate realignment while maintaining sensitivity through effective resampling techniques. In fact, accurate realignment alone is not a powerful indicator of the most effective algorithm in terms of true activation.

Depth-buffer targeting for spatially accurate 3-D visualization of medical images.

During interactive image-guided surgery (IIGS), a surgeon uses data from medical images to help guide the surgical procedure. At Vanderbilt University, an IIGS software system called Orion has been developed which is capable of displaying up to four 512 x 512 images and the current surgical position using an active optical tracking system. Orion is capable of displaying data from any tomographic image volume and from any NTSC video image. An additional display module has been implemented to display three-dimensional information as well as the tomographic slices. This provides the surgeon with valuable anatomical information that is not readily obtained from the tomographic slices alone. Before the surgery, a set of rendered images is created, each with a different angular view of the tomographic volume in order to surround the site of surgical interest. The major objectives of the display module are to display the appropriate rendered image from the set, identify the current probe position on the selected image, and provide an indication of distance between the probe and the physical point of the anatomy indicated on the image. This can provide the surgeon with vital information such as distance to blood vessels, tumors, or other critical structures.

Image-guided surgery: preliminary feasibility studies of frameless stereotactic liver surgery.

BACKGROUND: Liver surgery can be difficult because there are few external landmarks defining hepatic anatomy and because the liver has significant vascularity. Although preoperative tomographic imaging (computed tomography or magnetic resonance imaging) provides essential anatomical information for operative planning, at present it cannot be used actively for precise localization during surgery. Interactive image-guided surgery involves the simultaneous real-time display of intraoperative instrument location on preoperative images (computed or positron-emission tomography or magnetic resonance imaging). Interactive image-guided surgery has been described for tumor localization in the brain (frameless stereotactic surgery) and allows for interactive use of preoperative images during resections or biopsies. HYPOTHESIS: The application of interactive image-guided surgery (IIGS) is feasible for hepatic procedures from a biomedical engineering standpoint. METHODS: We developed an interactive image-guided surgery system for liver surgery and tested a porcine liver model for tracking liver motion during insufflation; liver motion during respiration in open procedures in patients undergoing hepatic resection; and tracking accuracy of general surgical instruments, including a laparoscope and an ultrasound probe. RESULTS: Liver motion due to insufflation can be quantified; average motion was 2.5+/-1.4 mm. Average total liver motion secondary to respiration in patients was 10.8 +/-2.5 mm. Instruments of varying lengths, including a laparoscope, can be tracked to accuracies ranging from 1.4 to 2.1 mm within a 27-m3 (3 X 3 X 3-m) space. CONCLUSION: Interactive image-guided surgery appears to be feasible for open and laparoscopic hepatic procedures and may enhance future operative localization.

Automatic 3-D segmentation of internal structures of the head in MR images using a combination of similarity and free-form transformations: Part I, Methodology and validation on normal subjects.

The study presented in this paper tests the hypothesis that the combination of a global similarity transformation and local free-form deformations can be used for the accurate segmentation of internal structures in MR images of the brain. To quantitatively evaluate our approach, the entire brain, the cerebellum, and the head of the caudate have been segmented manually by two raters on one of the volumes (the reference volume) and mapped back onto all the other volumes, using the computed transformations. The contours so obtained have been compared to contours drawn manually around the structures of interest in each individual brain. Manual delineation was performed twice by the same two raters to test inter- and intrarater variability. For the brain and the cerebellum, results indicate that for each rater, contours obtained manually and contours obtained automatically by deforming his own atlas are virtually indistinguishable. Furthermore, contours obtained manually by one rater and contours obtained automatically by deforming this rater's own atlas are more similar than contours obtained manually by two raters. For the caudate, manual intra- and interrater similarity indexes remain slightly better than manual versus automatic indexes, mainly because of the spatial resolution of the images used in this study. Qualitative results also suggest that this method can be used for the segmentation of more complex structures, such as the hippocampus.

Automatic 3-D segmentation of internal structures of the head in MR images using a combination of similarity and free-form transformations: Part II, validation on severely atrophied brains.

Studies aimed at quantifying neuroanatomical differences between populations require the volume measurements of individual brain structures. If the study contains a large number of images, manual segmentation is not practical. This study tests the hypothesis that a fully automatic, atlas-based segmentation method can be used to quantify atrophy indexes derived from the brain and cerebellum volumes in normal subjects and chronic alcoholics. This is accomplished by registering an atlas volume with a subject volume, first using a global transformation, and then improving the registration using a local transformation. Segmented structures in the atlas volume are then mapped to the corresponding structures in the subject volume using the combined global and local transformations. This technique has been applied to seven normal and seven alcoholic subjects. Three magnetic resonance volumes were obtained for each subject and each volume was segmented automatically, using the atlas-based method. Accuracy was assessed by manually segmenting regions and measuring the similarity between corresponding regions obtained automatically. Repeatability was determined by comparing volume measurements of segmented structures from each acquisition of the same subject. Results demonstrate that the method is accurate, that the results are repeatable, and that it can provide a method for automatic quantification of brain atrophy, even when the degree of atrophy is large.

Image-guided MR spectroscopy volume of interest localization for longitudinal studies.

Longitudinal magnetic resonance spectroscopy (MRS) studies require accurate repositioning of the volume of interest (VOI) over which measurements are made. In this work we present and evaluate a method for the image-guided repositioning of brain volumes of interest. The point-based registration technique we developed allows the repositioning to be performed on-line (i.e. while the patient is in the scanner). MR image volumes were acquired from six subjects, three scans each over the course of a month. During the first scan, two spectroscopy VOIs are visually selected: one in the frontal white matter, the other in the superior cerebellar vermis. The coordinates of 13 internal brain landmarks are also identified. During both subsequent scans, the same 13 landmarks are identified, and the transformation that registers the first set of landmarks to the subsequent set is computed. This result is used to automatically map the position of the spectroscopy VOIs from the first volume to the current volume. For the six subjects evaluated to date, we show an average repositioning error of the spectroscopy VOIs in the order of 1 mm. This accuracy allows us to conclude that any variations in the MR spectra are unlikely to be due to repositioning error.