Clinical validation of an automated vessel-segmentation software of the extracranial-carotid arteries based on 3D-MRA: A prospective study

OBJECTIVES: To determine the accuracy of automated vessel-segmentation software for vessel-diameter measurements based on three-dimensional contrast-enhanced magnetic resonance angiography (3D-MRA). METHOD: In 10 patients with high-grade carotid stenosis, automated measurements of both carotid arteries were obtained with 3D-MRA by two independent investigators and compared with manual measurements obtained by digital subtraction angiography (DSA) and 2D maximum-intensity projection (2D-MIP) based on MRA and duplex ultrasonography (US). In 42 patients undergoing carotid endarterectomy (CEA), intraoperative measurements (IOP) were compared with postoperative 3D-MRA and US. RESULTS: Mean interoperator variability was 8% for measurements by DSA and 11% by 2D-MIP, but there was no interoperator variability with the automated 3D-MRA analysis. Good correlations were found between DSA (standard of reference), manual 2D-MIP (rP=0.6) and automated 3D-MRA (rP=0.8). Excellent correlations were found between IOP, 3D-MRA (rP=0.93) and US (rP=0.83). CONCLUSION: Automated 3D-MRA-based vessel segmentation and quantification result in accurate measurements of extracerebral-vessel dimensions.

An integral conservative gridding--algorithm using Hermitian curve interpolation

The problem of re-sampling spatially distributed data organized into regular or irregular grids to finer or coarser resolution is a common task in data processing. This procedure is known as 'gridding' or 're-binning'. Depending on the quantity the data represents, the gridding-algorithm has to meet different requirements. For example, histogrammed physical quantities such as mass or energy have to be re-binned in order to conserve the overall integral. Moreover, if the quantity is positive definite, negative sampling values should be avoided. The gridding process requires a re-distribution of the original data set to a user-requested grid according to a distribution function. The distribution function can be determined on the basis of the given data by interpolation methods. In general, accurate interpolation with respect to multiple boundary conditions of heavily fluctuating data requires polynomial interpolation functions of second or even higher order. However, this may result in unrealistic deviations (overshoots or undershoots) of the interpolation function from the data. Accordingly, the re-sampled data may overestimate or underestimate the given data by a significant amount. The gridding-algorithm presented in this work was developed in order to overcome these problems. Instead of a straightforward interpolation of the given data using high-order polynomials, a parametrized Hermitian interpolation curve was used to approximate the integrated data set. A single parameter is determined by which the user can control the behavior of the interpolation function, i.e. the amount of overshoot and undershoot. Furthermore, it is shown how the algorithm can be extended to multidimensional grids. The algorithm was compared to commonly used gridding-algorithms using linear and cubic interpolation functions. It is shown that such interpolation functions may overestimate or underestimate the source data by about 10-20%, while the new algorithm can be tuned to significantly reduce these interpolation errors. The accuracy of the new algorithm was tested on a series of x-ray CT-images (head and neck, lung, pelvis). The new algorithm significantly improves the accuracy of the sampled images in terms of the mean square error and a quality index introduced by Wang and Bovik (2002 IEEE Signal Process. Lett. 9 81-4).

Finite element 3D reconstruction of the pulmonary acinus imaged by synchrotron X-ray tomography

The alveolated structure of the pulmonary acinus plays a vital role in gas exchange function. Three-dimensional (3D) analysis of the parenchymal region is fundamental to understanding this structure-function relationship, but only a limited number of attempts have been conducted in the past because of technical limitations. In this study, we developed a new image processing methodology based on finite element (FE) analysis for accurate 3D structural reconstruction of the gas exchange regions of the lung. Stereologically well characterized rat lung samples (Pediatr Res 53: 72-80, 2003) were imaged using high-resolution synchrotron radiation-based X-ray tomographic microscopy. A stack of 1,024 images (each slice: 1024 x 1024 pixels) with resolution of 1.4 mum(3) per voxel were generated. For the development of FE algorithm, regions of interest (ROI), containing approximately 7.5 million voxels, were further extracted as a working subunit. 3D FEs were created overlaying the voxel map using a grid-based hexahedral algorithm. A proper threshold value for appropriate segmentation was iteratively determined to match the calculated volume density of tissue to the stereologically determined value (Pediatr Res 53: 72-80, 2003). The resulting 3D FEs are ready to be used for 3D structural analysis as well as for subsequent FE computational analyses like fluid dynamics and skeletonization.

Reprint of "Stereology meets electron tomography: towards quantitative 3D electron microscopy" [J. Struct. Biol. 159 (2007) 443-450]

Stereological tools are the gold standard for accurate (i.e., unbiased) and precise quantification of any microscopic sample. The past decades have provided a broad spectrum of tools to estimate a variety of parameters such as volumes, surfaces, lengths, and numbers. Some of them require pairs of parallel sections that can be produced by either physical or optical sectioning, with optical sectioning being much more efficient when applicable. Unfortunately, transmission electron microscopy could not fully profit from these riches, mainly because of the large depth of field. Hence, optical sectioning was a long-time desire for electron microscopists. This desire was fulfilled with the development of electron tomography that yield stacks of slices from electron microscopic sections. Now, parallel optical slices of a previously unimagined small thickness (2-5nm axial resolution) can be produced. These optical slices minimize problems related to overprojection effects, and allow for direct stereological analysis, e.g., volume estimation with the Cavalieri principle and number estimation with the optical disector method. Here, we demonstrate that the symbiosis of stereology and electron tomography is an easy and efficient way for quantitative analysis at the electron microscopic level. We call this approach quantitative 3D electron microscopy.

Hermitian curve interpolation for CT-data re-sampling

Purpose: Development of an interpolation algorithm for re‐sampling spatially distributed CT‐data with the following features: global and local integral conservation, avoidance of negative interpolation values for positively defined datasets and the ability to control re‐sampling artifacts. Method and Materials: The interpolation can be separated into two steps: first, the discrete CT‐data has to be continuously distributed by an analytic function considering the boundary conditions. Generally, this function is determined by piecewise interpolation. Instead of using linear or high order polynomialinterpolations, which do not fulfill all the above mentioned features, a special form of Hermitian curve interpolation is used to solve the interpolation problem with respect to the required boundary conditions. A single parameter is determined, by which the behavior of the interpolation function is controlled. Second, the interpolated data have to be re‐distributed with respect to the requested grid. Results: The new algorithm was compared with commonly used interpolation functions based on linear and second order polynomial. It is demonstrated that these interpolation functions may over‐ or underestimate the source data by about 10%–20% while the parameter of the new algorithm can be adjusted in order to significantly reduce these interpolation errors. Finally, the performance and accuracy of the algorithm was tested by re‐gridding a series of X‐ray CT‐images. Conclusion: Inaccurate sampling values may occur due to the lack of integral conservation. Re‐sampling algorithms using high order polynomialinterpolation functions may result in significant artifacts of the re‐sampled data. Such artifacts can be avoided by using the new algorithm based on Hermitian curve interpolation

The role of 3D fusion imaging in sentinel lymphadenectomy for vulvar cancer

OBJECTIVES: To evaluate the feasibility of fusion imaging compound tomography (FICT) of CT/MRI and single photon emission tomography (SPECT) versus planar scintigraphy only (plSc) in pre-surgical staging for vulvar cancer. MATERIALS AND METHODS: Analysis of consecutive patients with vulvar cancer who preoperatively underwent sentinel scintigraphy (planar and 3D-SPECT imaging) and CT or MRI. Body markers were used for exact anatomical co-registration and fusion datasets were reconstructed using SPECT and CT/MRI. The number and localisation of all intraoperatively identified and resected sentinel lymph nodes (SLN) were compared between planar and 3D fusion imaging. RESULTS: Twenty six SLN were localized on planar scintigraphy. Twelve additional SLN were identified after SPECT and CT/MRI reconstruction, all of them were confirmed intraoperatively. In seven cases where single foci were identified at plSc, fusion imaging revealed grouped individual nodes and five additional localisations were discovered at fusion imaging. In seven patients both methods identified SLN contra lateral to the primary tumor site, but only fusion imaging allowed to localise iliac SLN in four patients. All SLN predicted on fusion imaging could be localised and resected during surgery. CONCLUSIONS: Fusion imaging using SPECT and CT/MRI can detect SLN in vulvar cancer more precisely than planar imaging regarding number and anatomical localisation. FICT revealed additional information in seven out of ten cases (70%).

3D ultrasound in fetal spina bifida

3D ultrasound can be used to study the fetal spine, but skeletal mode can be inconclusive for the diagnosis of fetal spina bifida. We illustrate a diagnostic approach using 2D and 3D ultrasound and indicate possible pitfalls.

Cord entanglement in monoamniotic twins: 2D and 3D colour Doppler studies

Cord entanglement affects the majority of monoamniotic (MA) twins, accounting for the high proportion of intrauterine deaths of MA twins, and it is often present from early gestation. 3D ultrasound can be used to acquire volume data comprising information on umbilical colour Doppler flow, providing a very graphic depiction of cord entanglement. We have used 2D, "conventional" and a novel 3D display of colour Doppler ultrasound showing cord entanglement.