3D SEGMENTATION OF THE LIVER USING FREE-FORM DEFORMATION BASED ON BOOSTING AND DEFORMATION GRADIENTS.

This paper presents a novel automatic 3D hybrid segmentation approach based on free-form deformation. The algorithms incorporate boosting and deformation gradients to achieve reliable liver segmentation of Computed Tomography (CT) scans. A free-form deformable model is deformed under the forces originating from boosting and deformation gradients. The basic idea of the scheme is to combine information from intensity and shape prior knowledge to calculate desired displacements to the liver boundary on vertices of deformable surface. Boosting classifies the 3D image into a binary mask and the edgeflow generates a force field from the mask. The deformable surface deforms iteratively according to the force field. Deformation gradients cast restriction at each deformation step. The deformation converges to a stable status to achieve the final segmentation surface.

Subtraction computed tomographic angiography of calcified arteries: preliminary phantom and clinical studies.

RATIONALE AND OBJECTIVES: The technique of subtraction computed tomographic angiography (sCTA) has been proposed for the evaluation of atherosclerotic disease to address limitations in CTA in highly calcified arteries. However, sCTA has not gained acceptance in clinical practice, in part, due to image artifacts caused by patient motion that occur between the acquisition of the two component images. The purpose of this study was to evaluate the effectiveness of computational image co-registration to obtain sCTA. MATERIALS AND METHODS: The study was conducted using a semi-automated implementation of the mutual information (MI) registration algorithm. The results of sCTA were evaluated quantitatively in a phantom representing a calcified artery. Technical success of sCTA was evaluated in 14 calcified arterial segments in two patients. An observer study was carried out to determine interobserver agreement in the interpretation of sCTA. Qualitative observations were made between sCTA and CTA. RESULTS: Computation time for performing the co-registration for each 2-cm calcification is less than 1 second. The necessary user interaction required minimal expertise. Measurements of the degree of stenosis in the calcified artery phantom agreed to within 8 +/- 4% of gold-standard measurements. Technical success was demonstrated in all calcifications. Strong interobserver agreement was obtained for the detection of hemodynamically significant stenoses (kappa = 0.86). Several apparent pitfalls in the interpretation of CTA in calcified arteries were noted that could potentially be obviated by sCTA. CONCLUSIONS: The study supports the use of a straight-forward implementation of the MI algorithm and provides preliminary evidence validating the use of sCTA in the setting of atherosclerotic disease of the lower extremities.

The paradoxical flow hypothesis of the carotid artery: supporting evidence from phase-contrast magnetic resonance imaging.

OBJECTIVE: Narrowing of the poststenotic internal carotid artery (ICA) has been found to be associated with reduced risk of ipsilateral stroke. A paradoxical mechanism has been hypothesized to explain this finding: narrowing of the distal-normal (reference) ICA is associated with low blood flow rates (Q) in the stenotic ICA, and lower Q causes lower risk of ipsilateral stroke, perhaps by an associated reduction in mechanical stress on the atherosclerotic plaque. The purpose of this study was to confirm that the reference ICA diameter (RICAD) is indeed predictive of Q, a finding that would indirectly support the hypothesis of a relationship between lower Q and lower risk of ipsilateral stroke. METHODS: Magnetic resonance imaging from 38 patients was included in the study. The study included 17 stenotic carotid arteries and 59 normal carotid arteries. All patients underwent contrast-enhanced magnetic resonance angiography from which measurements were obtained of the RICAD and the internal-common carotid diameter ratio. Patients underwent cardiac-gated, velocity-encoded phase-contrast magnetic resonance imaging for measurement of Q. RESULTS: Mean flow rates differed between stenotic (4.3 +/- 1.7 mL/s) and normal (5.4 +/- 1.7 mL/s) arteries (P = .02). RICAD was found to be a predictor of Q for stenotic arteries (P = .009) and for all arteries (P = .025) but not for the group of normal arteries (P = .162). Right-left differences in RICAD were highly predictive of right-left differences in Q in the subgroup of individuals with normal arteries (P < .001) and in the group of all participants (P < .001). Internal-common carotid diameter ratio was not found to be a statistically significant predictor of Q in the subgroup of stenotic arteries (P = .156). CONCLUSIONS: This study demonstrated that, as hypothesized, RICAD is correlated with Q.

Volumetric analysis of liver metastases in computed tomography with the fuzzy C-means algorithm.

Tumor size is often determined from computed tomography (CT) images to assess disease progression. A study was conducted to demonstrate the advantages of the fuzzy C-means (FCM) algorithm for volumetric analysis of colorectal liver metastases in comparison with manual contouring. Intra-and interobserver variability was assessed for manual contouring and the FCM algorithm in a study involving contrast-enhanced helical CT images of 43 hypoattenuating liver lesions from 15 patients with a history of colorectal cancer. Measurement accuracy and interscan variability of the FCM and manual methods were assessed in a phantom study using paraffin pseudotumors. In the clinical imaging study, intra-and interobserver variability was reduced using the FCM algorithm as compared with manual contouring (P = 0.0070 and P = 0.0019, respectively). Accuracy of the measurement of the pseudotumor volume was improved using the FCM method as compared with the manual method (P = 0.047). Interscan variability of the pseudotumor volumes was measured using the FCM method as compared with the manual method (P = 0.04). The FCM algorithm volume was highly correlated with the manual contouring volume (r = 0.9997). Finally, the shorter time spent in calculating tumor volume using the FCM method versus the manual contouring method was marginally statistically significant (P = 0.080). These results suggest that the FCM algorithm has substantial advantages over manual contouring for volumetric measurement of colorectal liver metastases from CT.

Estimation of the differential pressure at renal artery stenoses.

Atherosclerotic disease of the renal artery can lead to reduction in arterial caliber and ultimately to conditions including renovascular hypertension. Renal artery stenosis is conventionally assessed, using angiography, according to the severity of the stenosis. However, the severity of a stenosis is not a reliable indicator of functional significance, or associated differential pressure, of a stenosis. A methodology is proposed for estimation of the renal artery differential pressure (RADP) from MR imaging. Realistic computational fluid dynamics (CFD) models are constructed from MR angiography (MRA) and phase-contrast (PC) MR. The CFD model is constructed in a semiautomated manner from the MR images using the Isosurface Deformable Model (IDM) for surface reconstruction and a Marching Front algorithm for construction of the volumetric CFD mesh. Validation of RADP estimation was performed in a realistic physical flow-through model. Under steady flow, the CFD estimate of the differential pressure across a stenosis in the physical flow-through model differed by an average of 5.5 mmHg from transducer measurements of the pressure differential, for differential pressures less than 60 mmHg. These results demonstrate that accurate estimates of differential pressure at stenoses may be possible based only on structural and flow images.

Isosurfaces as deformable models for magnetic resonance angiography.

Vascular disease produces changes in lumenal shape evident in magnetic resonance angiography (MRA). However, quantification of vascular shape from MRA is problematic due to image artifacts. Prior deformable models for vascular surface reconstruction primarily resolve problems of initialization of the surface mesh. However, initialization can be obtained in a trivial manner for MRA using isosurfaces. We propose a methodology for deforming the isosurface to conform to the boundaries of objects in the image with minimal a priori assumptions of object shape. As in conventional methods, external forces attract the surface toward edges in the image. However, smoothing is produced by a moment that aligns the normals of adjacent surface triangles. Notably, the moment produces no translational motion of surface triangles. The deformable isosurface was applied to a digital phantom of a stenotic artery, to MRA of three renal arteries with atherosclerotic disease and MRA of one carotid artery with atherosclerotic disease. Results of the surface reconstruction from the deformable model were compared with conventional X-ray angiography for the renal arteries. Measurement of the degree of stenosis of the renal arteries was within 12% +/- 6%. The deformable model provided improvements over the isosurface in all cases in terms of measurement of the degree of stenosis or improving the surface smoothness.

Estimation of bolus dispersion effects in perfusion MRI using image-based computational fluid dynamics.

Bolus tracking magnetic resonance imaging (MRI) is a powerful technique for measuring perfusion, and is playing an increasing role in the investigation of acute stroke. However, limitations have been reported when assessing patients with steno-occlusive disease. The presence of a steno-occlusive disease in the artery may cause bolus dispersion, which has been shown to introduce significant errors in cerebral blood flow (CBF) quantification. Bolus dispersion is commonly described by a vascular transport function, but the function that properly characterizes the dispersion is unknown. A novel method to quantify bolus dispersion errors on perfusion measurements is presented. A realistic patient-specific model is constructed from anatomical and physiologic MR data, and the arterial blood flow pattern and the transport of the bolus of contrast agent are computed using finite element analysis. The methodology presented was used also to evaluate the accuracy of three simple vascular models. The methodology was tested on MR data from two normal subjects and two subjects with mild carotid artery stenosis. The estimated CBF errors were of the order of 15% to 20%. However, the presence of stenosis did not necessarily introduce larger dispersion (not only the geometrical model but also the particular physiologic conditions influence the degree of bolus dispersion). The method described will contribute to a better understanding of errors introduced by dispersion effects, to the assessment and validation of vascular models, and to the development of new methods for the correction of dispersion errors in CBF quantification.

Blood flow modeling in carotid arteries with computational fluid dynamics and MR imaging.

RATIONALE AND OBJECTIVES: The authors' goal was to develop a noninvasive method for detailed assessment of blood flow patterns from direct in vivo measurements of vessel anatomy and flow rates. MATERIALS AND METHODS: The authors developed a method to construct realistic patient-specific finite element models of blood flow in carotid arteries. Anatomic models are reconstructed from contrast material-enhanced magnetic resonance (MR) angiographic images with a tubular deformable model along each arterial branch. A surface-merging algorithm is used to create a watertight model of the carotid bifurcation for subsequent finite element grid generation, and a fully implicit scheme is used to solve the incompressible Navier-Stokes equations on unstructured grids. Physiologic boundary conditions are derived from cine phase-contrast MR flow velocity measurements at two locations below and above the bifurcation. Vessel wall compliance is incorporated by means of fluid-solid interaction algorithms. RESULTS: The method was tested on imaging data from a healthy subject and a patient with mild stenosis. Finite element grids were successfully generated, and pulsatile blood flow calculations were performed. Computed and measured velocity profiles show good agreement. Flow patterns and wall shear stress distributions were visualized. CONCLUSIONS: Patient-specific computational fluid dynamics modeling based on MR images can be performed robustly and efficiently. Preliminary validation studies in a physical flow-through model suggest that the model is accurate. This method can be used to characterize blood flow patterns in healthy and diseased arteries and may eventually help physicians to supplement imaging-based diagnosis and predict and evaluate the outcome of interventional procedures.