Micro-CT versus synchrotron radiation phase contrast imaging of human cochlea.

High-resolution images of the cochlea are used to develop atlases to extract anatomical features from low-resolution clinical computed tomography (CT) images. We compare visualization and contrast of conventional absorption-based micro-CT to synchrotron radiation phase contrast imaging (SR-PCI) images of whole unstained, nondecalcified human cochleae. Three cadaveric cochleae were imaged using SR-PCI and micro-CT. Images were visually compared and contrast-to-noise ratios (CNRs) were computed from n = 27 regions-of-interest (enclosing soft tissue) for quantitative comparisons. Three-dimensional (3D) models of cochlear internal structures were constructed from SR-PCI images using a semiautomatic segmentation method. SR-PCI images provided superior visualization of soft tissue microstructures over conventional micro-CT images. CNR improved from 7.5 ± 2.5 in micro-CT images to 18.0 ± 4.3 in SR-PCI images (p < 0.0001). The semiautomatic segmentations yielded accurate reconstructions of 3D models of the intracochlear anatomy. The improved visualization, contrast and modelling achieved using SR-PCI images are very promising for developing atlas-based segmentation methods for postoperative evaluation of cochlear implant surgery.

Iodine potassium iodide improves the contrast-to-noise ratio of micro-computed tomography images of the human middle ear.

High-resolution imaging of middle-ear geometry is necessary for finite-element modeling. Although micro-computed tomography (microCT) is widely used because of its ability to image bony structures of the middle ear, it is difficult to visualize soft tissues - including the tympanic membrane and the suspensory ligaments/tendons - because of lack of contrast. The objective of this research is to quantitatively evaluate the efficacy of iodine potassium iodide (IKI) solution as a contrast agent. Six human temporal bones were used in this experiment, which were obtained in right-left pairs, from three cadaveric heads. All bones were fixed using formaldehyde. Three bones (one from each pair) were stained in IKI solution for 2 days, whereas the other three were not stained. Samples were scanned using a microCT system at a resolution of 20 µm. Eight soft tissues in the middle ear were segmented: anterior mallear ligament, incudomallear joint, lateral mallear ligament, posterior incudal ligament, stapedial annular ligament, stapedius muscle, tympanic membrane and tensor tympani muscle. Contrast-to-noise ratios (CNRs) of each soft tissue were calculated for each temporal bone. Combined CNRs of the soft tissues in unstained samples were 6.1 ± 3.0, whereas they were 8.1 ± 2.7 in stained samples. Results from Welch's t-test indicate significant difference between the two groups at a 95% confidence interval. Results for paired t-tests for each of the individual soft tissues also indicated significant improvement of contrast in all tissues after staining. Relatively large soft tissues in the middle ear such as the tympanic membrane and the tensor tympani muscle were impacted by staining more than smaller tissues such as the stapedial annular ligament. The increase in contrast with IKI solution confirms its potential application in automatic segmentation of the middle-ear soft tissues.

Effect of black blood MR image quality on vessel wall segmentation.

Black blood MRI has become a popular technique for measuring arterial wall area as an indicator of plaque size. Computer-assisted techniques for segmenting vessel boundaries have been developed to increase measurement precision. In this study, the carotid arteries of four normal subjects were imaged at seven different fields of view (FOVs), keeping all other imaging parameters fixed, to determine whether spatial resolution could be increased at the expense of image quality without sacrificing precision. Wall areas were measured via computer-assisted segmentation of the vessel boundaries performed repeatedly by two operators. Analysis of variance (ANOVA) demonstrated that the variability of wall area measurements was below 1.5 mm(2) for in-plane spatial resolutions between 0.22 mm and 0.37 mm. An inverse relationship between operator variability and the signal difference-to-noise ratio (SDNR) demonstrated that semi-automatic segmentation of the wall boundaries was robust for SDNR >3, defining a criterion above which subjective image quality can be degraded without an appreciable loss of information content. Our study also suggested that spatial resolutions higher than 0.3 mm may be required to quantify normal wall areas to within 10% accuracy, but that the reduced SNR associated with the higher resolution may be tolerated by semi-automated wall segmentation without an appreciable loss of precision.

A semi-automatic technique for measurement of arterial wall from black blood MRI.

Black blood magnetic resonance imaging (MRI) has become a popular technique for imaging the artery wall in vivo. Its noninvasiveness and high resolution make it ideal for studying the progression of early atherosclerosis in normal volunteers or asymptomatic patients with mild disease. However, the operator variability inherent in the manual measurement of vessel wall area from MR images hinders the reliable detection of relatively small changes in the artery wall over time. In this paper we present a semi-automatic method for segmenting the inner and outer boundary of the artery wall, and evaluate its operator variability using analysis of variance (ANOVA). In our approach, a discrete dynamic contour is approximately initialized by an operator, deformed to the inner boundary, dilated, and then deformed to the outer boundary. A group of four operators performed repeated measurements on 12 images from normal human subjects using both our semiautomatic technique and a manual approach. Results from the ANOVA indicate that the inter-operator standard error of measurement (SEM) of total wall area decreased from 3.254 mm2 (manual) to 1.293 mm2 (semi-automatic), and the intra-operator SEM decreased from 3.005 mm2 to 0.958 mm2. Operator reliability coefficients increased from less than 69% to more than 91% (inter-operator) and 95% (intra-operator). The minimum detectable change in wall area improved from more than 8.32 mm2 (intra-operator, manual) to less than 3.59 mm2 (inter-operator, semi-automatic), suggesting that it is better to have multiple operators measure wall area with our semi-automatic technique than to have a single operator make repeated measurements manually. Similar improvements in wall thickness and lumen radius measurements were also recorded. Since the semi-automatic technique has effectively ruled out the effect of the operator on these measurements, it may be possible to use such techniques to expand prospective studies of atherogenesis to multiple centers so as to increase access to real patient data without sacrificing reliability.

Prostate boundary segmentation from 2D ultrasound images.

Outlining, or segmenting, the prostate is a very important task in the assignment of appropriate therapy and dose for cancer treatment; however, manual outlining is tedious and time-consuming. In this paper, an algorithm is described for semiautomatic segmentation of the prostate from 2D ultrasound images. The algorithm uses model-based initialization and the efficient discrete dynamic contour. Initialization requires the user to select only four points from which the outline of the prostate is estimated using cubic interpolation functions and shape information. The estimated contour is then deformed automatically to better fit the image. The algorithm can easily segment a wide range of prostate images, and contour editing tools are included to handle more difficult cases. The performance of the algorithm with a single user was compared to manual outlining by a single expert observer. The average distance between semiautomatically and manually outlined boundaries was found to be less than 5 pixels (0.63 mm), and the accuracy and sensitivity to area measurements were both over 90%.

Accuracy and variability assessment of a semiautomatic technique for segmentation of the carotid arteries from three-dimensional ultrasound images.

In this paper, we report on a semiautomatic method for segmentation of three-dimensional (3D) carotid vascular ultrasound (US) images. Our method is based on a dynamic balloon model represented by a triangulated mesh. The mesh is manually placed within the interior of the carotid vessels, then is driven outward until it reaches the vessel wall by applying an inflation force to the mesh. Once the mesh is in close proximity to the vessel wall, it is further deformed using an image-based force, in order to better localize the boundary. Since the method requires manual initialization, there is inherent variability in the position and shape of the final segmented boundary. Using a 3D US image of a patient's carotids, we have examined the local variability in boundary position as the initialization position is varied throughout the interior of the carotid vessels in the 3D image. We have compared the semiautomatic segmentation method to a fully manual segmentation method, and found that the semiautomatic approach is less variable than the intraobserver variability for manual segmentation. We have furthermore examined the accuracy of the semiautomatic method by comparing the average surface to an "ideal" surface, determined by the average manually segmented surface. We have found, in general, good agreement between the semiautomatic and manual segmentation methods. For the 3D US image in question, the mean separation between the average segmented surface and the gold standard was found to be 0.35 mm. The two surfaces were determined to agree with each other, within uncertainty, at 65% of the mesh points comprising the two surfaces.

Rapid three-dimensional segmentation of the carotid bifurcation from serial MR images.

The current trend in computational hemodynamics is to employ realistic models derived from ex vivo or in vivo imaging. Such studies typically produce a series of images from which the lumen boundaries must first be individually extracted (i.e., two-dimensional segmentation), and then serially reconstructed to produce the three-dimensional lumen surface geometry. In this paper, we present a rapid three-dimensional segmentation technique that combines these two steps, based on the idea of an expanding virtual balloon. This three-dimensional technique is demonstrated in application to finite element meshing and CFD modeling of flow in the carotid bifurcation of a normal volunteer imaged with black blood MRI. Wall shear stress patterns computed using a mesh generated with the three-dimensional technique agree well with those computed using a mesh generated from conventional two-dimensional segmentation and serial reconstruction. In addition to reducing the time required to extract the lumen surface from hours to minutes, our approach is easy to learn and use and requires minimal user intervention, which can potentially increase the accuracy and precision of quantitative and longitudinal studies of hemodynamics and vascular disease.

Systematic errors in small deformations measured by use of shadow-moiré topography.

Phase-shift shadow-moiré topography is a noncontact optical technique for measuring the shapes of surfaces. Artifactual bands resembling isoheight surface contours are observed during measurement of small changes in shape by use of this technique. The shape-reconstruction algorithm used in shadow-moiré topography is based on a mathematical model of the fringe patterns generated on the surface to be measured. We hypothesize that the observed bands reflect systematic errors caused by ignoring height-dependent terms in the mathematical model of the fringe patterns. We test the assumption by simulating the fringe patterns for a virtual test surface by using a model that contains height-dependent terms and one term that is idealized by ignoring these terms. Small systematic errors in shape are observed only when the surface is reconstructed from fringe patterns simulated with a model containing the height-dependent terms. Shape-error curves are computed as a function of the surface height by the subtraction of the reconstructed shape from the known shape. Simulated shape-error curves agree with experimental measurements in that they show an increase in error with surface height, and both the experimental and the simulated shape-error curves contain ripples. Although the errors are small in comparison with the dimensions of the surface and are negligible in shape measurements and in most deformation measurements, they may show up as noticeable bands in images of small deformations.

Finite-element modeling of the normal and surgically repaired cat middle ear.

In this work, three-dimensional finite-element models of the normal and surgically repaired cat middle ear were developed. The normal middle-ear model was formed by adding explicit representations for the footplate and cochlear load to an existing model of the cat eardrum. The footplate was modeled as a thin plate with a thickened rim. The cochlear load was represented by springs attached along the footplate's periphery. The model is valid for frequencies below 1 kHz and for physiological sound levels. Eardrum and manubrium displacement, and out-of-plane displacements of the footplate's center, were found to compare well with experimental results. The normal model was modified to simulate the effects of two types of middle-ear surgery, both of which are used to repair a discontinuous ossicular chain. Bulging of the footplate was found to occur when a prosthesis made direct contact with the footplate. The location of the prosthesis along the manubrium did not affect the motion of the footplate as long as the joints were all rigid. When the joints were flexible, the largest displacements occurred when the prosthesis was positioned near the upper end of the manubrium.