Assessment of automated TICI scoring during endovascular treatment in patients with an ischemic stroke.

BACKGROUND: The extended Thrombolysis in Cerebral Infarction (eTICI) score is used in digital subtraction angiography (DSA) to quantify reperfusion grade in patients with an ischemic stroke who undergo endovascular thrombectomy (EVT). A previously developed automatic TICI score (autoTICI), which quantifies the ratio of reperfused pixels after EVT, demonstrates good correlation with eTICI. OBJECTIVE: To evaluate the autoTICI model in a large multicenter registry of patients with an ischemic stroke, investigate the association with visual eTICI, and compare prediction of functional outcome between autoTICI and eTICI. METHODS: Patients in the MR CLEAN Registry with an internal carotid artery, M1, and M2 occlusion were selected if both anteroposterior and lateral views were present in pre- and post-EVT DSA scans. The autoTICI score was compared with eTICI in predicting favorable functional outcome (modified Rankin Scale score 0-2), using area under the receiver operating characteristics curve (AUC) with a multivariable logistic regression model including known prognostic characteristics. RESULTS: In total 421 of 3637 patients were included. AutoTICI was significantly associated with eTICI non-linearly (below 70% cOR=2.3 (95% CI 2.1 to 2.5), above 70% cOR=1.6 (95% CI 1.6 to 1.7) per 10% increment). The AUC of the model predicting favorable functional outcome was similar for autoTICI and eTICI (0.86, 95% CI 0.82 to 0.92 vs 0.86, 95% CI 0.83 to 0.90, P=0.73) and was higher than for a model with prognostic patient characteristics alone (0.86 vs 0.84, P=0.01). CONCLUSION: Automatic quantitative assessment of reperfusion after EVT is associated with eTICI, and prediction of functional outcome is similar to that with visual eTICI. Therefore, autoTICI could be used as an alternative or additional review for visual reperfusion assessment to facilitate reproducible and uniform reporting.

Clinical consequence of vessel perforations during endovascular treatment of acute ischemic stroke.

PURPOSE: Endovascular treatment (EVT) of acute ischemic stroke can be complicated by vessel perforation. We studied the incidence and determinants of vessel perforations. In addition, we studied the association of vessel perforations with functional outcome, and the association between location of perforation on digital subtraction angiography (DSA) and functional outcome, using a large EVT registry. METHODS: We included all patients in the MR CLEAN Registry who underwent EVT. We used DSA to determine whether EVT was complicated by a vessel perforation. We analyzed the association with baseline clinical and interventional parameters using logistic regression models. Functional outcome was measured using the modified Rankin Scale at 90 days. The association between vessel perforation and angiographic imaging features and functional outcome was studied using ordinal logistic regression models adjusted for prognostic parameters. These associations were expressed as adjusted common odds ratios (acOR). RESULTS: Vessel perforation occurred in 74 (2.6%) of 2794 patients who underwent EVT. Female sex (aOR 2.0 (95% CI 1.2-3.2)) and distal occlusion locations (aOR 2.2  (95% CI 1.3-3.5)) were associated with increased risk of vessel perforation. Functional outcome was worse in patients with vessel perforation (acOR 0.38 (95% CI 0.23-0.63)) compared to patients without a vessel perforation. No significant association was found between location of perforation and functional outcome. CONCLUSION: The incidence of vessel perforation during EVT in this cohort was low, but has severe clinical consequences. Female patients and patients treated at distal occlusion locations are at higher risk.

Augmented reality in craniomaxillofacial surgery: added value and proposed recommendations through a systematic review of the literature.

This systematic review provides an overview of augmented reality (AR) and its benefits in craniomaxillofacial surgery in an attempt to answer the question: Is AR beneficial for craniomaxillofacial surgery? This review includes a description of the studies conducted, the systems used and their technical characteristics. The search was performed in four databases: PubMed, Cochrane Library, Embase, and Web of Science. All journal articles published during the past 11 years related to AR, mixed reality, craniomaxillofacial, and surgery were considered in this study. From a total of 7067 articles identified using AR- and surgery-related keywords, 39 articles were finally selected. Based on these articles, a classification of study types, surgery types, devices used, metrics reported, and benefits were collected. The findings of this review indicate that AR could provide various benefits, addressing the challenges of conventional navigation systems, such as hand-eye coordination and depth perception. However, three main concerns were raised while performing this study: (1) it is complicated to aggregate the metrics reported in the articles, (2) it is difficult to obtain statistical value from the current studies, and (3) user evaluation studies are lacking. This article concludes with recommendations for future studies by addressing the latter points.

Assessment of human left ventricle flow using statistical shape modelling and computational fluid dynamics.

Blood flow patterns in the human left ventricle (LV) have shown relation to cardiac health. However, most studies in the literature are limited to a few patients and results are hard to generalize. This study aims to provide a new framework to generate more generalized insights into LV blood flow as a function of changes in anatomy and wall motion. In this framework, we studied the four-dimensional blood flow in LV via computational fluid dynamics (CFD) in conjunction with a statistical shape model (SSM), built from segmented LV shapes of 150 subjects. We validated results in an in-vitro dynamic phantom via time-resolved optical particle image velocimetry (PIV) measurements. This combination of CFD and the SSM may be useful for systematically assessing blood flow patterns in the LV as a function of varying anatomy and has the potential to provide valuable data for diagnosis of LV functionality.

Respiratory motion estimation in x-ray angiography for improved guidance during coronary interventions.

During percutaneous coronary interventions (PCI) catheters and arteries are visualized by x-ray angiography (XA) sequences, using brief contrast injections to show the coronary arteries. If we could continue visualizing the coronary arteries after the contrast agent passed (thus in non-contrast XA frames), we could potentially lower contrast use, which is advantageous due to the toxicity of the contrast agent. This paper explores the possibility of such visualization in mono-plane XA acquisitions with a special focus on respiratory based coronary artery motion estimation. We use the patient specific coronary artery centerlines from pre-interventional 3D CTA images to project on the XA sequence for artery visualization. To achieve this, a framework for registering the 3D centerlines with the mono-plane 2D + time XA sequences is presented. During the registration the patient specific cardiac and respiratory motion is learned. We investigate several respiratory motion estimation strategies with respect to accuracy, plausibility and ease of use for motion prediction in XA frames with and without contrast. The investigated strategies include diaphragm motion based prediction, and respiratory motion extraction from the guiding catheter tip motion. We furthermore compare translational and rigid respiratory based heart motion. We validated the accuracy of the 2D/3D registration and the respiratory and cardiac motion estimations on XA sequences of 12 interventions. The diaphragm based motion model and the catheter tip derived motion achieved 1.58 mm and 1.83 mm median 2D accuracy, respectively. On a subset of four interventions we evaluated the artery visualization accuracy for non-contrast cases. Both diaphragm, and catheter tip based prediction performed similarly, with about half of the cases providing satisfactory accuracy (median error < 2 mm).

Oriented Gaussian mixture models for nonrigid 2D/3D coronary artery registration.

2D/3D registration of patient vasculature from preinterventional computed tomography angiography (CTA) to interventional X-ray angiography is of interest to improve guidance in percutaneous coronary interventions. In this paper we present a novel feature based 2D/3D registration framework, that is based on probabilistic point correspondences, and show its usefulness on aligning 3D coronary artery centerlines derived from CTA images with their 2D projection derived from interventional X-ray angiography. The registration framework is an extension of the Gaussian mixture model (GMM) based point-set registration to the 2D/3D setting, with a modified distance metric. We also propose a way to incorporate orientation in the registration, and show its added value for artery registration on patient datasets as well as in simulation experiments. The oriented GMM registration achieved a median accuracy of 1.06 mm, with a convergence rate of 81% for nonrigid vessel centerline registration on 12 patient datasets, using a statistical shape model. The method thereby outperformed the iterative closest point algorithm, the GMM registration without orientation, and two recently published methods on 2D/3D coronary artery registration.

Standardized evaluation framework for evaluating coronary artery stenosis detection, stenosis quantification and lumen segmentation algorithms in computed tomography angiography.

Though conventional coronary angiography (CCA) has been the standard of reference for diagnosing coronary artery disease in the past decades, computed tomography angiography (CTA) has rapidly emerged, and is nowadays widely used in clinical practice. Here, we introduce a standardized evaluation framework to reliably evaluate and compare the performance of the algorithms devised to detect and quantify the coronary artery stenoses, and to segment the coronary artery lumen in CTA data. The objective of this evaluation framework is to demonstrate the feasibility of dedicated algorithms to: (1) (semi-)automatically detect and quantify stenosis on CTA, in comparison with quantitative coronary angiography (QCA) and CTA consensus reading, and (2) (semi-)automatically segment the coronary lumen on CTA, in comparison with expert's manual annotation. A database consisting of 48 multicenter multivendor cardiac CTA datasets with corresponding reference standards are described and made available. The algorithms from 11 research groups were quantitatively evaluated and compared. The results show that (1) some of the current stenosis detection/quantification algorithms may be used for triage or as a second-reader in clinical practice, and that (2) automatic lumen segmentation is possible with a precision similar to that obtained by experts. The framework is open for new submissions through the website, at http://coronary.bigr.nl/stenoses/.

Statistical coronary motion models for 2D+t/3D registration of X-ray coronary angiography and CTA.

Accurate alignment of intra-operative X-ray coronary angiography (XA) and pre-operative cardiac CT angiography (CTA) may improve procedural success rates of minimally invasive coronary interventions for patients with chronic total occlusions. It was previously shown that incorporating patient specific coronary motion extracted from 4D CTA increases the robustness of the alignment. However, pre-operative CTA is often acquired with gating at end-diastole, in which case patient specific motion is not available. For such cases, we investigate the possibility of using population based coronary motion models to provide constraints for the 2D+t/3D registration. We propose a methodology for building statistical motion models of the coronary arteries from a training population of 4D CTA datasets. We compare the 2D+t/3D registration performance of the proposed statistical models with other motion estimates, including the patient specific motion extracted from 4D CTA, the mean motion of a population, the predicted motion based on the cardiac shape. The coronary motion models, constructed on a training set of 150 patients, had a generalization accuracy of 1mm root mean square point-to-point distance. Their 2D+t/3D registration accuracy on one cardiac cycle of 12 monoplane XA sequences was similar to, if not better than, the 4D CTA based motion, irrespective of which respiratory model and which feature based 2D/3D distance metric was used. The resulting model based coronary motion estimate showed good applicability for registration of a subsequent cardiac cycle.

Automatic carotid artery distensibility measurements from CTA using nonrigid registration.

The distensibility of a blood vessel is a marker of atherosclerotic disease. In this paper we investigate the feasibility of measuring carotid artery distensibility on 4D CTA, both manually and using a new automatic method. On 4D CTA datasets manual (n=38) and automatic (n=76) measurements of the carotid distensibility were performed. A subset (n=10) of the manual annotations were repeated by a second observer. The interobserver variability was assessed using a Bland-Altman analysis and appeared to be too large to reliably measure the distensibility using manual annotation. We compared two versions of the automatic method: one using 3D registration and one using a 4D registration method. The latter resulted in a more smooth deformation over time. The automatic method was evaluated using a synthetic deformation and by investigating whether known relations with cardiovascular risk factors could be reproduced. The relation between distensibility and cardiovascular risk factors was tested with a Mann-Whitney U test. Automatic measurements revealed an association with hypertension whereas the manual measurements did not. This relation has been found by other studies too. We conclude that carotid artery distensibility measurements should be performed automatically and that the method described in this paper is suitable for that. All CTA datasets and related clinical data used in this study can be downloaded from our website (http://ctadist.bigr.nl).

Statistical shape model-based femur kinematics from biplane fluoroscopy.

Studying joint kinematics is of interest to improve prosthesis design and to characterize postoperative motion. State of the art techniques register bones segmented from prior computed tomography or magnetic resonance scans with X-ray fluoroscopic sequences. Elimination of the prior 3D acquisition could potentially lower costs and radiation dose. Therefore, we propose to substitute the segmented bone surface with a statistical shape model based estimate. A dedicated dynamic reconstruction and tracking algorithm was developed estimating the shape based on all frames, and pose per frame. The algorithm minimizes the difference between the projected bone contour and image edges. To increase robustness, we employ a dynamic prior, image features, and prior knowledge about bone edge appearances. This enables tracking and reconstruction from a single initial pose per sequence. We evaluated our method on the distal femur using eight biplane fluoroscopic drop-landing sequences. The proposed dynamic prior and features increased the convergence rate of the reconstruction from 71% to 91%, using a convergence limit of 3 mm. The achieved root mean square point-to-surface accuracy at the converged frames was 1.48 ± 0.41 mm. The resulting tracking precision was 1-1.5 mm, with the largest errors occurring in the rotation around the femoral shaft (about 2.5° precision).

Comprehensive visualization of multimodal cardiac imaging data for assessment of coronary artery disease: first clinical results of the SMARTVis tool.

PURPOSE: In clinical practice, both coronary anatomy and myocardial perfusion information are needed to assess coronary artery disease (CAD). The extent and severity of coronary stenoses can be determined using computed tomography coronary angiography (CTCA); the presence and amount of ischemia can be identified using myocardial perfusion imaging, such as perfusion magnetic resonance imaging (PMR). To determine which specific stenosis is associated with which ischemic region, experts use assumptions on coronary perfusion territories. Due to the high variability between patient's coronary artery anatomies, as well as the uncertain relation between perfusion territories and supplying coronary arteries, patient-specific systems are needed. MATERIAL AND METHODS: We present a patient-specific visualization system, called Synchronized Multimodal heART Visualization (SMARTVis), for relating coronary stenoses and perfusion deficits derived from CTCA and PMR, respectively. The system consists of the following comprehensive components: (1) two or three-dimensional fusion of anatomical and functional information, (2) automatic detection and ranking of coronary stenoses, (3) estimation of patient-specific coronary perfusion territories. RESULTS: The potential benefits of the SMARTVis tool in assessing CAD were investigated through a case-study evaluation (conventional vs. SMARTVis tool): two experts analyzed four cases of patients with suspected multivessel coronary artery disease. When using the SMARTVis tool, a more reliable estimation of the relation between perfusion deficits and stenoses led to a more accurate diagnosis, as well as a better interobserver diagnosis agreement. CONCLUSION: The SMARTVis comprehensive visualization system can be effectively used to assess disease status in multivessel CAD patients, offering valuable new options for the diagnosis and management of these patients.

2D-3D shape reconstruction of the distal femur from stereo X-ray imaging using statistical shape models.

Three-dimensional patient specific bone models are required in a range of medical applications, such as pre-operative surgery planning and improved guidance during surgery, modeling and simulation, and in vivo bone motion tracking. Shape reconstruction from a small number of X-ray images is desired as it lowers both the acquisition costs and the radiation dose compared to CT. We propose a method for pose estimation and shape reconstruction of 3D bone surfaces from two (or more) calibrated X-ray images using a statistical shape model (SSM). User interaction is limited to manual initialization of the mean shape. The proposed method combines a 3D distance based objective function with automatic edge selection on a Canny edge map. Landmark-edge correspondences are weighted based on the orientation difference of the projected silhouette and the corresponding image edge. The method was evaluated by rigid pose estimation of ground truth shapes as well as 3D shape estimation using a SSM of the whole femur, from stereo cadaver X-rays, in vivo biplane fluoroscopy image-pairs, and an in vivo biplane fluoroscopic sequence. Ground truth shapes for all experiments were available in the form of CT segmentations. Rigid registration of the ground truth shape to the biplane fluoroscopy achieved sub-millimeter accuracy (0.68mm) measured as root mean squared (RMS) point-to-surface (P2S) distance. The non-rigid reconstruction from the biplane fluoroscopy using the SSM also showed promising results (1.68mm RMS P2S). A feasibility study on one fluoroscopic time series illustrates the potential of the method for motion and shape estimation from fluoroscopic sequences with minimal user interaction.

Evaluation framework for carotid bifurcation lumen segmentation and stenosis grading.

This paper describes an evaluation framework that allows a standardized and objective quantitative comparison of carotid artery lumen segmentation and stenosis grading algorithms. We describe the data repository comprising 56 multi-center, multi-vendor CTA datasets, their acquisition, the creation of the reference standard and the evaluation measures. This framework has been introduced at the MICCAI 2009 workshop 3D Segmentation in the Clinic: A Grand Challenge III, and we compare the results of eight teams that participated. These results show that automated segmentation of the vessel lumen is possible with a precision that is comparable to manual annotation. The framework is open for new submissions through the website http://cls2009.bigr.nl.

Nonrigid registration of dynamic medical imaging data using nD + t B-splines and a groupwise optimization approach.

A registration method for motion estimation in dynamic medical imaging data is proposed. Registration is performed directly on the dynamic image, thus avoiding a bias towards a specifically chosen reference time point. Both spatial and temporal smoothness of the transformations are taken into account. Optionally, cyclic motion can be imposed, which can be useful for visualization (viewing the segmentation sequentially) or model building purposes. The method is based on a 3D (2D+time) or 4D (3D+time) free-form B-spline deformation model, a similarity metric that minimizes the intensity variances over time and constrained optimization using a stochastic gradient descent method with adaptive step size estimation. The method was quantitatively compared with existing registration techniques on synthetic data and 3D+t computed tomography data of the lungs. This showed subvoxel accuracy while delivering smooth transformations, and high consistency of the registration results. Furthermore, the accuracy of semi-automatic derivation of left ventricular volume curves from 3D+t computed tomography angiography data of the heart was evaluated. On average, the deviation from the curves derived from the manual annotations was approximately 3%. The potential of the method for other imaging modalities was shown on 2D+t ultrasound and 2D+t magnetic resonance images. The software is publicly available as an extension to the registration package elastix.

Evaluation of a multi-atlas based method for segmentation of cardiac CTA data: a large-scale, multicenter, and multivendor study.

PURPOSE: Computed tomography angiography (CTA) is increasingly used for the diagnosis of coronary artery disease (CAD). However, CTA is not commonly used for the assessment of ventricular and atrial function, although functional information extracted from CTA data is expected to improve the diagnostic value of the examination. In clinical practice, the extraction of ventricular and atrial functional information, such as stroke volume and ejection fraction, requires accurate delineation of cardiac chambers. In this paper, we investigated the accuracy and robustness of cardiac chamber delineation using a multiatlas based segmentation method on multicenter and multivendor CTA data. METHODS: A fully automatic multiatlas based method for segmenting the whole heart (i.e., the outer surface of the pericardium) and cardiac chambers from CTA data is presented and evaluated. In the segmentation approach, eight atlas images are registered to a new patient's CTA scan. The eight corresponding manually labeled images are then propagated and combined using a per voxel majority voting procedure, to obtain a cardiac segmentation. RESULTS: The method was evaluated on a multicenter/multivendor database, consisting of (1) a set of 1380 Siemens scans from 795 patients and (2) a set of 60 multivendor scans (Siemens, Philips, and GE) from different patients, acquired in six different institutions worldwide. A leave-one-out 3D quantitative validation was carried out on the eight atlas images; we obtained a mean surface-to-surface error of 0.94 +/- 1.12 mm and an average Dice coefficient of 0.93 was achieved. A 2D quantitative evaluation was performed on the 60 multivendor data sets. Here, we observed a mean surface-to-surface error of 1.26 +/- 1.25 mm and an average Dice coefficient of 0.91 was achieved. In addition to this quantitative evaluation, a large-scale 2D and 3D qualitative evaluation was performed on 1380 and 140 images, respectively. Experts evaluated that 49% of the 1380 images were very accurately segmented (below 1 mm error) and that 29% were accurately segmented (error between 1 and 3 mm), which demonstrates the robustness of the presented method. CONCLUSIONS: A fully automatic method for whole heart and cardiac chamber segmentation was presented and evaluated using multicenter/multivendor CTA data. The accuracy and robustness of the method were demonstrated by successfully applying the method to 1420 multicenter/ multivendor data sets.

Coronary centerline extraction from CT coronary angiography images using a minimum cost path approach.

PURPOSE: The application and large-scale evaluation of minimum cost path approaches for coronary centerline extraction from computed tomography coronary angiography (CTCA) data and the development and evaluation of a novel method to reduce the user-interaction time. METHODS: A semiautomatic method based on a minimum cost path approach is evaluated for two different cost functions. The first cost function is based on a frequently used vesselness measure and intensity information, and the second is a recently proposed cost function based on region statistics. User interaction is minimized to one or two mouse clicks distally in the coronary artery. The starting point for the minimum cost path search is automatically determined using a newly developed method that finds a point in the center of the aorta in one of the axial slices. This step ensures that all computationally expensive parts of the algorithm can be precomputed. RESULTS: The performance of the aorta localization procedure was demonstrated by a success rate of 100% in 75 images. The success rate and accuracy of centerline extraction was quantitatively evaluated on 48 coronary arteries in 12 images by comparing extracted centerlines with a manually annotated reference standard. The method was able to extract 88% and 47% of the vessel center-lines correctly using the vesselness/intensity and region statistics cost function, respectively. For only the proximal part of the vessels these values were 97% and 86%, respectively. Accuracy of centerline extraction, defined as the average distance from correctly automatically extracted parts of the centerline to the reference standard, was 0.64 mm for the vesselness/intensity and 0.51 mm for the region statistics cost function. The interobserver variability was 99% for the success rate measure and 0.42 mm for the accuracy measure. Qualitative evaluation using the best performing cost function resulted in successful centerline extraction for 233 out of the 252 coronaries (92%) in 63 additional CTCA images. CONCLUSIONS: The presented results, in combination with minimal user interaction and low computation time, show that minimum cost path approaches can effectively be applied as a preprocessing step for subsequent analysis in clinical practice and biomedical research.

Vessel diameter measurements in gadolinium contrast-enhanced three-dimensional MRA of peripheral arteries.

In this study, the possibilities for quantification of vessel diameters of peripheral arteries in gadolinium contrast-enhanced magnetic resonance angiography (Gd CE MRA) were evaluated. Absolute vessel diameter measurements were assessed objectively and semi-automatically in maximum intensity projections (MIPs) of contrast-enhanced T1-weighted 3D spoiled gradient-echo datasets, studied with digital subtraction techniques. In vivo, the complete peripheral arterial bed of six patients was studied, from the aorto-iliac bifurcation down to the distal run-off. By measuring the signal intensity (SI) over the lumen of a vessel in the MIP, an SI-plot was obtained. Next, the vessel boundaries were determined using a threshold algorithm; from these boundary points individual diameter values could be obtained along the trajectory of the vessel. In an in vitro study, an optimal threshold value of 30% of the range of SI-values between the background and the maximal SI in the vessel was obtained for accurate diameter measurement in Gd CE MRA (i.e., full-width 30%-maximum). Furthermore, the relationship between the accuracy of these measurements and the scan resolution was investigated. Accuracy was found to be acceptable (i.e., less than 10% over/underestimation) for vessel sizes covering at least 3 pixels. In six patients, diameters were measured in MIPs of the total datasets (i.e., D(T)) as well as in selective MIPs of the clipped datasets (i.e., D(S)) (n = 209). D(T) and D(S) were statistically significantly correlated (p < 0.01) with a Pearson correlation coefficient rP = 0.98. Measurements in the total MIPs yielded statistically significant (p < 0.01) smaller diameter values compared with measurements in selective MIPs, with a mean difference of 0.15 mm. Diameter values from the selective MIPs of the aorto-iliac arteries were also compared with diameter values measured at corresponding anatomic positions in X-ray angiograms of these patients (i.e., D(x)) (n = 70). D(X) and D(S) were statistically significantly correlated (p < 0.01) with a Pearson correlation coefficient rP = 0.92. Diameters measured in the selective MIPs were smaller than those measured in the X-ray angiograms (mean difference 0.49 mm) and this difference was statistically significant (p < 0.01). In conclusion, diameter values can be evaluated accurately in MIPs of vessels with at least 3 pixels in diameter, using the full-width 30%-maximum criterion.

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.

Advances in three-dimensional diagnostic radiology.

The maturity of current 3D rendering software in combination with recent developments in computer vision techniques enable an exciting range of applications for the visualisation, measurement and interactive manipulation of volumetric data, relevant both for diagnostic imaging and for anatomy. This paper reviews recent work in this area from the Image Sciences Institute at Utrecht University. The processes that yield a useful visual presentation are sequential. After acquisition and before any visualisation, an essential step is to prepare the data properly: this field is known as 'image processing' or 'computer vision' in analogy with the processing in human vision. Examples will be discussed of modern image enhancement and denoising techniques, and the complex process of automatically finding the objects or regions of interest, i.e. segmentation. One of the newer and promising methodologies for image analysis is based on a mathematical analysis of the human (cortical) visual processing: multiscale image analysis. After preprocessing the 3D rendering can be acquired by simulating the 'ray casting' in the computer. New possibilities are presented, such as the integrated visualisation in one image of (accurately registered) datasets of the same patient acquired in different modality scanners. Other examples include colour coding of functional data such as SPECT brain perfusion or functional magnetic resonance (MR) data and even metric data such as skull thickness on the rendered 3D anatomy from MR or computed tomography (CT). Optimal use and perception of 3D visualisation in radiology requires fast display and truly interactive manipulation facilities. Modern and increasingly cheaper workstations ( < $10000) allow this to be a reality. It is now possible to manipulate 3D images of 256 at 15 frames per second interactively, placing virtual reality within reach. The possibilities of modern workstations become increasingly more sophisticated and versatile. Examples presented include the automatic detection of the optimal viewing angle of the neck of aneurysms and the simulation of the design and placement procedure of intra-abdominal aortic stents. Such developments, together with the availability of high-resolution datasets of modern scanners and data such as from the NIH Visible Human project, have a dramatic impact on interactive 3D anatomical atlases.