Ankle images digital analysis (AIDA): digital measurement of joint space width and subchondral sclerosis on standard radiographs

OBJECTIVE

Reliable evaluation of joint space width and subchondral sclerosis of osteoarthritic joints is difficult. The present study describes a new digital method to analyse standard radiographs of the ankle.

DESIGN

Standardized radiographs were taken of the ankle of 12 patients with severe osteoarthritis (OA) under full weight-bearing conditions, before treatment and 1 year after initiation of treatment. Treatment consisted of 3 months distraction of the tibio-talar joint, for which clinical benefit has been shown previously. The width of the joint space was measured on digitized images of the radiographs by means of the newly developed semi-automatic digital technique called AIDA (Ankle Images Digital Analysis) and by means of the most widely used conventional analogue measurements. In addition, AIDA was used to assess subchondral sclerosis by measuring the intensity of the radiograph at fixed positions at the bone-cartilage interface.

RESULTS

AIDA appeared to be a reliable method for measuring small changes in joint space width and subchondral sclerosis because the intra- and interobserver variation was small. Mean JSW for two observers was 1.96 and 2.00 mm, with mean differences between two observations of 0.05 and -0.01, respectively. Mean subchondral sclerosis in the tibia was 1.52 and 1.61 with mean differences between two observations of, respectively, 0.00 and 0.03. In addition to conventional measurements, AIDA could demonstrate a decrease in subchondral sclerosis as a result of joint distraction of 71% and 69% after 1 year for talus and tibia, respectively.

CONCLUSION

The use of AIDA is preferable to the conventional analogue method for evaluating the severity of ankle OA, because the method provides quantitative data not only for the joint space width but also for subchondral sclerosis.

Reduction of patient motion artifacts in digital subtraction angiography: evaluation of a fast and fully automatic technique

The performance of an automatic technique for the reduction of patient motion artifacts in digital subtraction angiography was evaluated. Four observers assessed the quality of 104 cerebral digital subtraction angiographic images that were processed by means of both the automatic technique and manual pixel shifting. The automatic technique resulted in better image quality and was considerably less time-consuming.

Registration, segmentation, and visualization of multimodal brain images

This paper gives an overview of the studies performed at our institute over the last decade on the processing and visualization of brain images, in the context of international developments in the field. The focus is on multimodal image registration and multimodal visualization, while segmentation is touched upon as a preprocessing step for visualization. The state-of-the-art in these areas is discussed and suggestions for future research are given.

Correcting partial volume artifacts of the arterial input function in quantitative cerebral perfusion MRI

To quantify cerebral perfusion with dynamic susceptibility contrast MRI (DSC-MRI), one needs to measure the arterial input function (AIF). Conventionally, one derives the contrast concentration from the DSC sequence by monitoring changes in either the amplitude or the phase signal on the assumption that the signal arises completely from blood. In practice, partial volume artifacts are inevitable because a compromise has to be reached between the temporal and spatial resolution of the DSC acquisition. As the concentration of the contrast agent increases, the vector of the complex blood signal follows a spiral-like trajectory. In the case of a partial-volume voxel, the spiral is located around the static contribution of the surrounding tissue. If the static contribution of the background tissue is disregarded, estimations of the contrast concentration will be incorrect. By optimizing the correspondence between phase information and amplitude information one can estimate the origin of the spiral, and thereupon correct for partial volume artifacts. This correction is shown to be accurate at low spatial resolutions for phantom data and to improve the AIF determination in a clinical example. Magn Reson Med 45:477-485, 2001.

Improvement of image resolution and quantitative accuracy in clinical Single Photon Emission Computed Tomography

Clinical Single Photon Emission Computed Tomography (SPECT) is a scanning technique which acquires gamma-camera images ('projections') over a range of angles around a patient. These projections allow the reconstruction of cross sectional ('tomographic') images of the gamma-radiating pharmaceutical distribution in the patient, thus providing interesting information about the functioning of organs and tissues.SPECT images are seriously affected by a variety of image degrading processes. Restrictions on the amount of radio-pharmaceutical that can be administered to a patient cause noise in the projections and the limited spatial resolution of the gamma-camera results in blurring of the projections. In addition to these image degradations, the reconstruction of cross-sections is complicated by Compton scattering of gamma-photons in tissue, which causes attenuation of the photon flux received by the gamma-camera and causes improper detection of photons which have been scattered in tissue. This results in some additional blurring and loss of accuracy of the SPECT images in predicting activity concentrations. Tremendous efforts have been made to improve the quantitative accuracy and the spatial resolution of SPECT, and to reduce the noise in the reconstructed images. These efforts have resulted in corrective reconstruction algorithms, which are generally based on incorporation of accurate models of the main image degrading factors. Improvements of the data acquisition hardware can further increase image quality. In this paper, the image formation process of SPECT, including image-degrading factors, is explained. In addition, reconstruction algorithms and hardware modifications are reviewed, and their effects on image quality are illustrated with physical phantom and simulation experiments.

MR imaging of vascular stents: effects of susceptibility, flow, and radiofrequency eddy currents

PURPOSE

The purpose of this in vitro study was to examine the various sources of artifacts in magnetic resonance (MR) imaging and angiography of vascular stents.

MATERIALS AND METHODS

Five low-artifact stents-Wallstent (cobalt alloy), Memotherm (nitinol), Perflex (stainless steel), Passager (tantalum), and Smart (nitinol)-were imaged in a vascular flow phantom, consisting of a thin-walled cellulose vessel model connected to a pump system. The echo time and the angulation of the stents with respect to the direction of the main magnetic field were varied. Spin echo and gradient echo images as well as three-dimensional MR angiograms were obtained to study the effects of flow, magnetic susceptibility, and radiofrequency-induced eddy currents.

RESULTS

Susceptibility artifacts were restricted to the stents' direct environment and were mildest at short echo times and with the stents aligned with the main magnetic field. Nitinol stents showed less artifacts than steel stents did. Radiofrequency artifacts obscuring the stent lumen and flow-related lumen displacement were seen in all stents. The extent to which these occurred depended on strut geometry and orientation.

CONCLUSIONS

For low-artifact stents, the material the stent is made of is not the only important factor in the process of artifact formation. Susceptibility artifacts, radiofrequency eddy currents and flow-related artifacts all contribute to the image distortion, and are dependent on the geometry and orientation of the struts and on the orientation of the stent in the main magnetic field.

Prognostic value of perfusion- and diffusion-weighted MR imaging in first 3 days of stroke

The aim of this study was to evaluate the differences in cerebral perfusion seen on mean transit time (MTT) and cerebral blood volume (CBV) maps and to assess the subsequent prognostic value of the MTT-DWI (diffusion-weighted MRI) and CBV-DWI mismatch in the first three days of stroke on lesion enlargement and clinical outcome. In 38 patients, imaged 1-46 h after onset of symptoms, lesion volumes on proton-density (PD)-weighted MRI, DWI and PWI (both MTT and CBV maps) were compared with lesion volumes on follow-up PD-weighted scans, and to clinical outcome (National Institutes of Health Stroke Scale, Barthel index, and Rankin scale). The MTT-CBV, MTT-DWI and CBV-DWI mismatches were compared with change in lesion volume between initial and follow-up PD-weighted scans. Lesion volume on both DWI and PWI correlated significantly with clinical outcome parameters (p < 0.001) with strongest correlation for lesion volume on CBV. Perfusion-diffusion mismatches were found for both CBV and MTT and correlated significantly with lesion enlargement on PDweighted imaging with strongest correlation for the CBV-DWI mismatch. The CBV-DWI mismatch has the highest accuracy in predicting lesion size on follow-up imaging and in predicting clinical outcome. Lesion volume measurements on CBV maps have a higher specificity than on PD-weighted, MTT or DWI images in predicting clinical follow-up imaging and in predicting clinical outcome.

Repeated quantitative perfusion and contrast permeability measurement in the MRI examination of a CNS tumor

This study reports on the results of quantitative MRI perfusion and contrast permeability measurement on two occasions in one patient. The measurements were separated 81 days in time. The tumor grew considerably in this period, but no change was found with respect to perfusion and contrast permeability. Non-involved white matter values were reproduced to demonstrate repeatability. The presented approach to dynamic susceptibility contrast MRI allows fast and repeatable quantitative assessment of perfusion and is easily integrated in a conventional brain tumor protocol.

Integrated volume visualization of functional image data and anatomical surfaces using normal fusion

A generic method, called normal fusion, for integrated three-dimensional (3D) visualization of functional data with surfaces extracted from anatomical image data is described. The first part of the normal fusion method derives quantitative values from functional input data by sampling the latter along a path determined by the (inward) normal of a surface extracted from anatomical data; the functional information is thereby projected onto the anatomical surface independently of the viewpoint. Fusion of the anatomical and functional information is then performed with a color-encoding scheme based on the HSV model. This model is preferred over the RGB model to allow easy, rapid, and intuitive retrospective manipulation of the color encoding of the functional information in the integrated display, and two possible strategies for this manipulation are explained. The results first show several clinical examples that are used to demonstrate the viability of the normal fusion method. These same examples are then used to evaluate the two HSV color manipulation strategies. Furthermore, five nuclear medicine physicians used several other clinical cases to evaluate the overall approach for manipulation of the color encoded functional contribution to an integrated 3D visualization. The integrated display using the normal fusion technique combined with the added functionality provided by the retrospective color manipulation was highly appreciated by the clinicians and can be considered an important asset in the investigation of data from multiple modalities.

Quantitative analysis of vascular morphology from 3D MR angiograms: In vitro and in vivo results

A 3D model-based approach for quantification of vascular morphology from several MRA acquisition protocols was evaluated. Accuracy, reproducibility, and influence of the image acquisition techniques were studied via in vitro experiments with ground truth diameters and the measurements of two expert readers as reference. The performance of the method was similar to or more accurate than the manual assessments and reproducibility was also improved. The methodology was applied to stenosis grading of carotid arteries from CE MRA data. In 11 patients, the approach was compared to manual scores (NASCET criterion) on CE MRA and DSA images, with the result that the model-based technique correlates better with DSA than the manual scores. Spearman's correlation coefficient was 0.91 (P < 0.001) for the model-based technique and DSA vs. 0.80 and 0.84 (P < 0.001) between the manual scores and DSA. From the results it can be concluded that the approach is a promising objective technique to assess geometrical vascular parameters, including degree of stenosis. Magn Reson Med 45:311-322, 2001.

Localization of implanted EEG electrodes in a virtual-reality environment

In the planning of epilepsy surgery procedures, intracranial electrodes are implanted in a significant fraction of the patients. Accurate localization of the individual electrode contacts with respect to the brain cortex is imperative. Because the manual tracking of an EEG electrode in a CT scan in a slice-by-slice fashion is cumbersome and subjective, the goal of this study was to develop an easier and more accurate way to localize implanted EEG electrodes. In this paper, we present our solution in the form of a virtual-reality environment with interactive tools to assist the clinician with EEG localization. With the help of a high-quality and fast volume renderer, a view is created of the inside of the patient's skull to obtain an overview of the electrodes in relation to the cortical structures. Depth, grid, and reed electrodes are characterized semi-interactively using different methods. For depth electrodes, the contacts (which are not visible in the CT scan) are derived by measuring off the theoretical distance between the contact and the end of the electrode from the central axis produced by a three-dimensional (3D) line tracker. For grid electrodes, the contacts are visible in a CT, so the 3D view is merely used to find the contacts and to resolve the overlap of grids with other grids, tail wires, or bone ridges. For reed electrodes, the contacts, which are again not visible in this case, are calculated from a line model fitted to the positions of lead markers. After letting the user place artificial spheres on the lead markers and wire, a B-spline is fitted to the spheres' centers to estimate the positions of the contacts. The approach was evaluated by applying it to CT scans of seven patients. It appeared that the method is generally applicable (even crossing electrodes or electrodes with gaps were correctly characterized), and that the display via 3D views and slices is so good that manual placement of spheres performed as well as semi-automatic placement. From computer experiments, it appeared that the final localization error in the position of EEG contacts could be estimated to lie in the order of the dimensions of one voxel.

Automated separation of gray and white matter from MR images of the human brain

A simple automatic procedure for segmentation of gray and white matter in high resolution 1.5T T1-weighted MR human brain images was developed and validated. The algorithm is based on histogram shape analysis of MR images that were corrected for scanner nonuniformity. Calibration and validation was done on a set of 80 MR images of human brains. The automatic method's values for the gray and white matter volumes were compared with the values from thresholds set twice by the best three of six raters. The automatic procedure was shown to perform as good as the best rater, where the average result of the best three raters was taken as reference. The method was also compared with two other histogram-based threshold methods, which yielded comparable results. The conclusion of the study thus is that automated threshold based methods can separate gray and white matter from MR brain images as reliably as human raters using a thresholding procedure.

Three-dimensional modeling for functional analysis of cardiac images: a review

Three-dimensional (3-D) imaging of the heart is a rapidly developing area of research in medical imaging. Advances in hardware and methods for fast spatio-temporal cardiac imaging are extending the frontiers of clinical diagnosis and research on cardiovascular diseases. In the last few years, many approaches have been proposed to analyze images and extract parameters of cardiac shape and function from a variety of cardiac imaging modalities. In particular, techniques based on spatio-temporal geometric models have received considerable attention. This paper surveys the literature of two decades of research on cardiac modeling. The contribution of the paper is three-fold: 1) to serve as a tutorial of the field for both clinicians and technologists, 2) to provide an extensive account of modeling techniques in a comprehensive and systematic manner, and 3) to critically review these approaches in terms of their performance and degree of clinical evaluation with respect to the final goal of cardiac functional analysis. From this review it is concluded that whereas 3-D model-based approaches have the capability to improve the diagnostic value of cardiac images, issues as robustness, 3-D interaction, computational complexity and clinical validation still require significant attention.

Automatic morphology-based brain segmentation (MBRASE) from MRI-T1 data

A method called morphology-based brain segmentation (MBRASE) has been developed for fully automatic segmentation of the brain from T1-weighted MR image data. The starting point is a supervised segmentation technique, which has proven highly effective and accurate for quantitation and visualization purposes. The proposed method automates the required user interaction, i.e., defining a seed point and a threshold range, and is based on the simple operations thresholding, erosion, and geodesic dilation. The thresholds are detected in a region growing process and are defined by connections of the brain to other tissues. The method is first evaluated on three computer simulated datasets by comparing the automated segmentations with the original distributions. The second evaluation is done on a total of 30 patient datasets, by comparing the automated segmentations with supervised segmentations carried out by a neuroanatomy expert. The comparison between two binary segmentations is performed both quantitatively and qualitatively. The automated segmentations are found to be accurate and robust. Consequently, the proposed method can be used as a default segmentation for quantitation and visualization of the human brain from T1-weighted MR images in routine clinical procedures.

Selective contrast-enhanced MR angiography

In this study the feasibility of intraarterial contrast administration was investigated. Its use for navigation and treatment evaluation during MR-guided intravascular interventions was explored in phantom and animal experiments. An injection protocol was developed, which accounts for sequence parameters and vessel flow rate. Tracking a bolus of contrast agent was useful to verify the catheter tip position and to assess flow conditions. Compared to intravenous contrast-enhanced magnetic resonance angiography (CE-MRA), selective contrast administration permitted a strongly reduced dose. In two-dimensional (2D) acquisitions overlap of vessels was prevented. Injection and acquisition were easily and accurately synchronized in selective 3D CE-MRA, and a high contrast concentration could be maintained during the entire acquisition. Selective injection is useful in the course of an intervention, to facilitate navigation, provide information on flow conditions, and to evaluate treatment progress repeatedly.

On-line flow quantification by low-resolution phase-contrast MR imaging and model-based postprocessing

Over the past decade, magnetic resonance (MR) imaging has been developed toward a tool for guiding and evaluating diagnostic and therapeutic interventions. Within the field of vascular MR-guided interventions, MR has potential for providing on-line monitoring of the blood volume flow rate, which is relevant during procedures such as balloon angioplasty and stent placement. We recently reported a hardware and software environment for enabling flow quantification every 8 seconds using nontriggered phase-contrast imaging. In the present study, the objective was to increase temporal resolution further to one evaluation per 4 seconds. We achieve this by lowering spatial resolution to 3 pixels per lumen diameter. The accuracy of the measurements is preserved by applying model-based postprocessing for quantification of the volume flow rate. Phantom and volunteer studies are presented, demonstrating the accuracy of the model-driven approach for the applied short acquisitions. The capabilities of the presented approach are illustrated by the results of several hypercapnia experiments and carotid compression tests performed on healthy volunteers.

Objective quantification of the motion of soft tissues in the orbit

Orbital soft-tissue motion analysis aids in the localization and diagnosis of orbital disorders. A technique has been developed to objectively quantify and visualize motion in the orbit during gaze. T1-weighted MR volume sequences are acquired during gaze and soft-tissue motion is quantified using optical flow techniques. The flow field is visualized using color-coding: orientation of the flow vector is coded by hue and magnitude by saturation of the pixel. Current clinical circumstances limit MR image acquisition to short sequences and short acquisition times. The effect of these limitations on the performance of optical flow computation has been studied for four representative optical flow algorithms: on short (nine frames) and long (21 frames) simulated sequences of rotation of a magnetic resonance (MR) imaged object, on short measured MR sequences of controlled rotation of the same object and on short MR sequences of motion in the orbit. On the short simulated and motion-controlled sequences, the Lucas and Kanade algorithm showed the best performance with respect to both accuracy and robustness. These motion estimates were accurate to within 20%. Motion in the orbit ranged between 0.05 and 0.25 mm/degree gaze. Color-coding was found to be attractive as a visualization technique, because it shows both magnitude and orientation of all flow vectors without cluttering.

Placement of an inferior vena cava filter in a pig guided by high-resolution MR fluoroscopy at 1.5 T

Percutaneous placement of an inferior vena cava filter is a means for long-term prevention of pulmonary thromboembolism. In this study we investigated the magnetic resonance (MR) imaging properties of a Nitinol vena cava filter, in various anatomic and angiographic scans, as well as the feasibility of placing this filter under near real-time, high-resolution MR fluoroscopy. We made use of the passive tracking strategy, with on-line image processing and visualization, both in vitro and in a pig. The artifacts provoked by the metallic filter were such that the position and orientation of the filter were well depicted in all scans. Considerable radiofrequency caging obscured the interior of the filter. Our experiments showed that an MR-guided vena cava filter placement, with sufficient temporal and spatial resolution, is possible. Three-dimensional phase contrast MRA allowed direct evaluation of the filter placement procedure, without the use of contrast agent.

Image registration by maximization of combined mutual information and gradient information

Mutual information has developed into an accurate measure for rigid and affine monomodality and multimodality image registration. The robustness of the measure is questionable, however. A possible reason for this is the absence of spatial information in the measure. The present paper proposes to include spatial information by combining mutual information with a term based on the image gradient of the images to be registered. The gradient term not only seeks to align locations of high gradient magnitude, but also aims for a similar orientation of the gradients at these locations. Results of combining both standard mutual information as well as a normalized measure are presented for rigid registration of three-dimensional clinical images [magnetic resonance (MR), computed tomography (CT), and positron emission tomography (PET)]. The results indicate that the combined measures yield a better registration function does mutual information or normalized mutual information per se. The registration functions are less sensitive to low sampling resolution, do not contain incorrect global maxima that are sometimes found in the mutual information function, and interpolation-induced local minima can be reduced. These characteristics yield the promise of more robust registration measures. The accuracy of the combined measures is similar to that of mutual information-based methods.

Simultaneous quantitative cerebral perfusion and Gd-DTPA extravasation measurement with dual-echo dynamic susceptibility contrast MRI

Quantification of cerebral perfusion using dynamic susceptibility contrast MRI generally relies on the assumption of an intact blood-brain barrier. The present study proposes a method to correct the tissue response function that does not require this assumption, thus, allowing perfusion studies in, for example, high-grade brain tumors. The correction for contrast extravasation in the tissue during the bolus passage is based on a two-compartment kinetic model. The method separates the intravascular hemodynamic response and the extravascular component and returns the corrected tissue response function for perfusion quantification as well as the extravasation rate constant of the vasculature. Results of simulation experiments with different degrees of contrast extravasation are presented. The clinical potential is illustrated by determination of the perfusion and extravasation of a glioblastoma multiforme. The correction scheme proves to be fast and reliable even in cases of low signal-to-noise ratio. It is applicable whether extravasation occurs or not. When extravasation is present, application of the proposed method is mandatory for accurate cerebral blood volume measurements. Magn Reson Med 43:820-827, 2000.

Fast delineation and visualization of vessels in 3-D angiographic images

A method is presented which aids the clinician in obtaining quantitative measures and a three-dimensional (3-D) representation of vessels from 3-D angiographic data with a minimum of user interaction. Based on two user defined starting points, an iterative procedure tracks the central vessel axis. During the tracking process, the minimum diameter and a surface rendering of the vessels are computed, allowing for interactive inspection of the vasculature. Applications of the method to CTA, contrast enhanced (CE)-MRA and phase contrast (PC)-MRA images of the abdomen are shown. In all applications, a long stretch of vessels with varying width is tracked, delineated, and visualized, in less than 10 s on a standard clinical workstation.

Retrospective shading correction based on entropy minimization

Shading is a prominent phenomenon in microscopy, manifesting itself via spurious intensity variations not present in the original scene. The elimination of shading effects is frequently necessary for subsequent image processing tasks, especially if quantitative analysis is the final goal. While most of the shading effects may be minimized by setting up the image acquisition conditions carefully and capturing additional calibration images, object-dependent shading calls for retrospective correction. In this paper a novel method for retrospective shading correction is proposed. Firstly, the image formation process and the corresponding shading effects are described by a linear image formation model, which consists of an additive and a multiplicative parametric component. Secondly, shading correction is performed by the inverse of the image formation model, whose shading components are estimated retrospectively by minimizing the entropy of the acquired images. A number of tests, performed on artificial and real microscopical images, show that this approach is efficient for a variety of differently structured images and as such may have applications in and beyond the field of microscopical imaging.

Estimation of the depth-dependent component of the point spread function of SPECT

The point spread function (PSF) of a gamma camera describes the photon count density distribution at the detector surface when a point source is imaged. Knowledge of the PSF is important for computer simulation and accurate image reconstruction of single photon emission computed tomography (SPECT) images. To reduce the number of measurements required for PSF characterization and the amount of computer memory to store PSF tables, and to enable generalization of the PSF to different collimator-to-source distances, the PSF may be modeled as the two-dimensional (2D) convolution of the depth-dependent component which is free of detector blurring (PSF(ideal)) and the distance-dependent detector response. Owing to limitations imposed by the radioactive strength of point sources, extended sources have to be used for measurements. Therefore, if PSF(ideal) is estimated from measured responses, corrections have to be made for both the detector blurring and for the extent of the source. In this paper, an approach based on maximum likelihood expectation-maximization (ML-EM) is used to estimate PSF(ideal). In addition, a practical measurement procedure which avoids problems associated with commonly used line-source measurements is proposed. To decrease noise and to prevent nonphysical solutions, shape constraints are applied during the estimation of PSF(ideal). The estimates are generalized to depths other than those which have been measured and are incorporated in a SPECT simulator. The method is validated for Tc-99m and T1-201 by means of measurements on physical phantoms. The corrected responses have the desired shapes and simulated responses closely resemble measured responses. The proposed methodology may, consequently, serve as a basis for accurate three-dimensional (3D) SPECT reconstruction.

Model-based quantitation of 3-D magnetic resonance angiographic images

Quantification of the degree of stenosis or vessel dimensions are important for diagnosis of vascular diseases and planning vascular interventions. Although diagnosis from three-dimensional (3-D) magnetic resonance angiograms (MRA's) is mainly performed on two-dimensional (2-D) maximum intensity projections, automated quantification of vascular segments directly from the 3-D dataset is desirable to provide accurate and objective measurements of the 3-D anatomy. A model-based method for quantitative 3-D MRA is proposed. Linear vessel segments are modeled with a central vessel axis curve coupled to a vessel wall surface. A novel image feature to guide the deformation of the central vessel axis is introduced. Subsequently, concepts of deformable models are combined with knowledge of the physics of the acquisition technique to accurately segment the vessel wall and compute the vessel diameter and other geometrical properties. The method is illustrated and validated on a carotid bifurcation phantom, with ground truth and medical experts as comparisons. Also, results on 3-D time-of-flight (TOF) MRA images of the carotids are shown. The approach is a promising technique to assess several geometrical vascular parameters directly on the source 3-D images, providing an objective mechanism for stenosis grading.