Nonrigid registration of three-dimensional ultrasound and magnetic resonance images of the carotid arteries

Characteristics and evaluation of atherosclerotic plaques: an overview of state-of-the-art techniques

Atherosclerosis is an important cause of cerebrovascular and cardiovascular disease (CVD). Lipid infiltration, inflammation, and altered vascular stress are the critical mechanisms that cause atherosclerotic plaque formation. The hallmarks of the progression of atherosclerosis include plaque ulceration, rupture, neovascularization, and intraplaque hemorrhage, all of which are closely associated with the occurrence of CVD. Assessing the severity of atherosclerosis and plaque vulnerability is crucial for the prevention and treatment of CVD. Integrating imaging techniques for evaluating the characteristics of atherosclerotic plaques with computer simulations yields insights into plaque inflammation levels, spatial morphology, and intravascular stress distribution, resulting in a more realistic and accurate estimation of plaque state. Here, we review the characteristics and advancing techniques used to analyze intracranial and extracranial atherosclerotic plaques to provide a comprehensive understanding of atheroma.

Integrating Morphological Edge Detection and Mutual Information for Nonrigid Registration of Medical Images

Background:

Medical images are widely used within healthcare and medical research. There is an increased interest in precisely correlating information in these images through registration techniques for investigative and therapeutic purposes. This work proposes and evaluates an improved measure function for registration of carotid ultrasound and magnetic resonance images (MRI) taken at different times.

Methods:

To achieve this, a morphological edge detection operator has been designed to extract the vital edge information from images which is integrated with the Mutual Information (MI) to carry out the registration process. The improved performance of proposed registration measure function is demonstrated using four quality metrics: Correlation Coefficient (CC), Structural Similarity Index (SSIM), Visual Information Fidelity (VIF) and Gradient Magnitude Similarity Deviation (GMSD). The qualitative validation has also been done through visual inspection of the registered image pairs by clinical radiologists.

Results:

The experimental results showed that the proposed method outperformed the existing method (based on integrated MI and standard edge detection) for both ultrasound and MR images in terms of CC by about 4.67%, SSIM by 3.21%, VIF by 18.5%, and decreased GMSD by 37.01%. Whereas, in comparison to the standard MI based method, the proposed method has increased CC by 16.29%, SSIM by 16.13%, VIF by 52.56% and decreased GMSD by 66.06%, approximately.

Conclusion:

Thus, the proposed method improves the registration accuracy when the original images are corrupted by noise, have low intensity values or missing data.

Automated Registration of Freehand B-Mode Ultrasound and Magnetic Resonance Imaging of the Carotid Arteries Based on Geometric Features

An automated method for registering B-mode ultrasound (US) and magnetic resonance imaging (MRI) of the carotid arteries is proposed. The registration uses geometric features, namely, lumen centerlines and lumen segmentations, which are extracted fully automatically from the images after manual annotation of three seed points in US and MRI. The registration procedure starts with alignment of the lumen centerlines using a point-based registration algorithm. The resulting rigid transformation is used to initialize a rigid and subsequent non-rigid registration procedure that jointly aligns centerlines and segmentations by minimizing a weighted sum of the Euclidean distance between centerlines and the dissimilarity between segmentations. The method was evaluated in 28 carotid arteries from eight patients and six healthy volunteers. First, the automated US lumen segmentation method was validated and optimized in a cross-validation experiment. Next, the effect of the weighting parameter of the proposed registration dissimilarity metric and the control point spacing in the non-rigid registration was evaluated. Finally, the proposed registration method was evaluated in comparison to an existing intensity-and-point-based method, a registration using only the centerlines and a registration using manual US lumen segmentations. Registration accuracy was measured in terms of the mean surface distance between manual US segmentations and the registered MRI segmentations. The average mean surface distance was 0.78 ± 0.34 mm for all subjects, 0.65 ± 0.09 mm for healthy volunteers and 0.87 ± 0.42 mm for patients. The results for the complete set were significantly better (Wilcoxon test, p < 0.01) than the results for the intensity-and-point-based method and the centerline-based registration method. We conclude that the proposed method can robustly and accurately register US and MR images of the carotid artery, allowing multimodal analysis of the carotid plaque to improve plaque assessment.

Ultrasound intima-media thickness measurement of the carotid artery using ant colony optimization combined with a curvelet-based orientation-selective filter

PURPOSE

Automatic measurement of the intima-media thickness (IMT) from ultrasound carotid images is an important task in clinical diagnosis. Many computer-based techniques for IMT measurement have been proposed to overcome the limits of manual segmentation. However, the robustness of the algorithms would be influenced by the inherent speckle noise of ultrasound image. This paper proposed a curvelet guided ant colony optimization (CGACO) strategy that could achieve satisfied accuracy for IMT measurement with improved robustness to noise.

METHODS

The curvelet-based orientation-selective (CBOS) filter was first introduced for speckle removal and edge enhancement. Different from conventional methods, CBOS filter processes the curvelet coefficients by orientations rather than by magnitude. Then, a specially designed two-leg ant colony optimization technique, combined with Otsu thresholding and Sobel edge detector, was proposed as a novel segmentation method to extract the media-adventitia (MA) and the lumen-intima (LI) boundaries. Finally, a coupled snake model was employed to further smooth the contours of MA and LI.

RESULTS

In addition to 224 carotid artery images acquired from 34 participants, simulated speckled images with nine levels of noise were also included in the database. The mean absolute distance errors of CGACO for LI interface tracings, MA interface tracings, and IMT measurements were 0.030 ± 0.027, 0.039 ± 0.036, and 0.041 ± 0.036 mm, respectively. Besides, CGACO had a correlation coefficient as high as 0.992 and a bias as low as -0.008. All these measures were comparable to or better than a previous technique and the manual segmentation. On the other hand, CGACO had the highest success rate of 98.7% in the segmentation of real data. It also maintained a much higher success rate in the segmentation of simulated images with different levels of speckle noise.

CONCLUSIONS

The proposed technique showed accurate IMT measurement results. Furthermore, benefiting from the CBOS filter, the robustness to noise of the algorithm was substantially improved. Therefore, CGACO could provide a reliable way to segment the carotid artery from ultrasound images and could be used in clinical practice of IMT measurement, particularly in early atherosclerotic stages.

A Robust and Accurate Two-Step Auto-Labeling Conditional Iterative Closest Points (TACICP) Algorithm for Three-Dimensional Multi-Modal Carotid Image Registration

Atherosclerosis is among the leading causes of death and disability. Combining information from multi-modal vascular images is an effective and efficient way to diagnose and monitor atherosclerosis, in which image registration is a key technique. In this paper a feature-based registration algorithm, Two-step Auto-labeling Conditional Iterative Closed Points (TACICP) algorithm, is proposed to align three-dimensional carotid image datasets from ultrasound (US) and magnetic resonance (MR). Based on 2D segmented contours, a coarse-to-fine strategy is employed with two steps: rigid initialization step and non-rigid refinement step. Conditional Iterative Closest Points (CICP) algorithm is given in rigid initialization step to obtain the robust rigid transformation and label configurations. Then the labels and CICP algorithm with non-rigid thin-plate-spline (TPS) transformation model is introduced to solve non-rigid carotid deformation between different body positions. The results demonstrate that proposed TACICP algorithm has achieved an average registration error of less than 0.2mm with no failure case, which is superior to the state-of-the-art feature-based methods.

3-D registration on carotid artery imaging data: MRI for different timesteps

A common problem which is faced by the researchers when dealing with arterial carotid imaging data is the registration of the geometrical structures between different imaging modalities or different timesteps. The use of the "Patient Position" DICOM field is not adequate to achieve accurate results due to the fact that the carotid artery is a relatively small structure and even imperceptible changes in patient position and/or direction make it difficult. While there is a wide range of simple/advanced registration techniques in the literature, there is a considerable number of studies which address the geometrical structure of the carotid artery without using any registration technique. On the other hand the existence of various registration techniques prohibits an objective comparison of the results using different registration techniques. In this paper we present a method for estimating the statistical significance that the choice of the registration technique has on the carotid geometry. One-Way Analysis of Variance (ANOVA) showed that the p-values were <;0.0001 for the distances of the lumen from the centerline for both right and left carotids of the patient case that was studied.

The relationship between carotid intima-media thickness and carotid plaque in the Northern Manhattan Study

OBJECTIVE

Carotid intima-media thickness (cIMT) and carotid plaque (CP) are proposed biomarkers of subclinical atherosclerosis associated with stroke risk. Whether cIMT and CP are distinct phenotypes or single traits at different stages of atherosclerotic development is unclear. We explored the relationship between these markers in the population-based Northern Manhattan Study.

METHODS

We used high-resolution ultrasound and validated imaging protocols to study the cross-sectional (N = 1788 stroke-free participants) and prospective relationship (N = 768 with follow-up scan; mean years between examinations = 3.5) between CP and cIMT measured in plaque-free areas.

RESULTS

The mean age was 66 ± 9 (40% male, 19% black, 17% white, 61% Hispanic). The mean baseline cIMT was 0.92 ± 0.09 mm, 0.94 ± 0.09 mm among the 58% with prevalent plaque, 0.90 ± 0.08 mm among the 42% without prevalent plaque (p < 0.0001). Each 0.1 mm increase in baseline cIMT was associated with a 1.72-fold increased odds of plaque presence (95%CI = 1.50-1.97), increased plaque thickness (effect on the median = 0.46 mm, p < 0.0001), and increased plaque area (effect on the median = 3.45 mm(2), p < 0.0001), adjusting for demographics and vascular risk factors. Elevated baseline cIMT was associated with an increased risk of new plaque in any location at follow-up, but after adjusting for demographics and vascular risk factors this association was no longer present. No association was observed in carotid segment-specific analyses.

CONCLUSION

Increased cIMT was associated with baseline prevalent plaque but did not predict incident plaque independent of other vascular risk factors. This finding suggests that increased cIMT is not an independent predictor of plaque development although these atherosclerotic phenotypes often coexist and share some common vascular determinants.

Joint intensity-and-point based registration of free-hand B-mode ultrasound and MRI of the carotid artery

PURPOSE

To introduce a semiautomatic algorithm to perform the registration of free-hand B-Mode ultrasound (US) and magnetic resonance imaging (MRI) of the carotid artery.

METHODS

The authors' approach combines geometrical features and intensity information. The only user interaction consists of placing three seed points in US and MRI. First, the lumen centerlines are used as landmarks for point based registration. Subsequently, in a joint optimization the distance between centerlines and the dissimilarity of the image intensities is minimized. Evaluation is performed in left and right carotids from six healthy volunteers and five patients with atherosclerosis. For the validation, the authors measure the Dice similarity coefficient (DSC) and the mean surface distance (MSD) between carotid lumen segmentations in US and MRI after registration. The effect of several design parameters on the registration accuracy is investigated by an exhaustive search on a training set of five volunteers and three patients. The optimum configuration is validated on the remaining images of one volunteer and two patients.

RESULTS

On the training set, the authors achieve an average DSC of 0.74 and a MSD of 0.66 mm on volunteer data. For the patient data, the authors obtain a DSC of 0.77 and a MSD of 0.69 mm. In the independent set composed of patient and volunteer data, the DSC is 0.69 and the MSD is 0.87 mm. The experiments with different design parameters show that nonrigid registration outperforms rigid registration, and that the combination of intensity and point information is superior to approaches that use intensity or points only.

CONCLUSIONS

The proposed method achieves an accurate registration of US and MRI, and may thus enable multimodal analysis of the carotid plaque.

MRI strain imaging of the carotid artery: present limitations and future challenges

Rupture of atherosclerotic plaques in the carotid artery is a main cause of stroke. Current diagnostics are not sufficient to identify all rupture-prone plaques, and studies have shown that biomechanical factors improve current plaque risk assessment. Strain imaging may be a valuable contribution to this risk assessment. MRI is a versatile imaging technique that offers various methods that are capable of measuring tissue strain. In this review, MR imaging techniques with displacement (DENSE), velocity (PC MRI), or strain (SENC) encoding protocols are discussed, together with post-processing techniques based on time-resolved MRI data. Although several MRI techniques are being developed to improve time-resolved MR imaging, current technical limitations related to spatial and temporal resolutions render MRI strain imaging currently unfit for carotid plaque strain evaluation. A novel approach using non-rigid image registration of MR images to determine strain in carotid arteries based on black blood cine MRI is proposed in this review. This and other post-processing techniques based on time-resolved MRI data may provide a good estimate of plaque strain, but are also dependent on the spatial and temporal resolution of the MR images. However, they seem to be the most promising approach for MRI based plaque strain analysis in the near future.

Characterization of carotid plaques on 3-dimensional ultrasound imaging by registration with multicontrast magnetic resonance imaging

OBJECTIVES

The ability of magnetic resonance imaging (MRI) in carotid plaque component identification has been well established. However, compared to the costly nature of MRI, 3-dimensional (3D) ultrasound imaging is a more cost-effective assessment tool. Thus, an attractive alternative for carotid disease monitoring would be to establish a strategy in which 3D ultrasound imaging is used as a screening tool that precedes MRI. To develop and validate such a protocol, registration between ultrasound and MR images is required. This article introduces a surface-based algorithm for efficient ultrasound imaging-MRI registration.

METHODS

A surface-based 3D iterative closest point registration method was developed to align surfaces reconstructed from outer wall boundaries segmented from 3D ultrasound and MR images. The 3D ultrasound image was transformed according to the registration result and resliced to match corresponding 2-dimensional transverse MR images. Although rigid iterative closest point registration was used, the cross-sectional ultrasound images produced by the reslicing procedure can be moved relative to the MR images by an expert observer using in-house software, making nonrigid registration possible.

RESULTS

We evaluated the registration accuracy associated with the algorithm using a vascular phantom as well as in vivo ultrasound and MR images. Our registration method was shown to have an average error of 0.3 mm in the phantom study and less than 1 mm in the in vivo study. Our findings in terms of the average intensity of each component are consistent with histologically validated results described in previous ultrasound characterization studies.

CONCLUSIONS

We have developed a surface-based algorithm capable of registering ultrasound and MR images with high accuracy. This registration tool will potentially play an important role in a cost-effective screening protocol in which ultrasound is used to identify patients with a suspicion of vulnerable plaques, who are then further studied with MRI.

Texture analysis of carotid artery atherosclerosis from three-dimensional ultrasound images

PURPOSE

To quantitatively evaluate local carotid arterial statin effects in 3D US images using multiclassifier image texture analysis tools.

METHODS

Texture analysis tools were used to evaluate the effect of 80 mg atorvastatin administered daily to patients with carotid stenosis compared to those treated with placebo. Using three-dimensional carotid ultrasound images, 270 texture features from seven texture techniques were extracted from manually segmented carotid arteries based on the intima-media boundary [vessel wall (VW)]. Individual texture features were compared to the previously determined changes in VW volume (VWV) using the distance between classes, the Wilcoxon rank sum test, and accuracy of the classifiers. Texture features that resulted in maximal classification accuracy from each texture technique were selected using Pudil's sequential floating forward selection (SFFS) as a method of ranking each technique. Finally, SFFS-selected texture features from all texture techniques were used in combination with 24 classifier fusion techniques to improve classification accuracy.

RESULTS

Using the measurement of change in VWV, the distance between classes (DBC), Wilcoxon rank sum (WRS) p-value, and median accuracy measures (ACC) were 0.3798, 0.076, and 54.50%, respectively. Texture features improved the detection of statin-related changes using DBC to 0.5199, using WRS to 0.002, and ACC to 63.87%, respectively. The texture techniques that most differentiated between atorvastatin and placebo classes were Fourier power spectrum and Laws texture energy measures. The average classification accuracy between atorvastatin and placebo classes was improved from 57.22 +/- 12.11% using VWV to 97.87 +/- 3.93% using specific texture features. Furthermore, the use of specific texture features resulted in the average area under the receiver-operator characteristic curve (AUC) a value of 0.9988 +/- 0.0069 compared to 0.617 +/- 0.15 using carotid VWV.

CONCLUSIONS

Based on DBC, WRS, ACC, and AUC texture features derived from 3D carotid ultrasound were observed to be more sensitive in detecting statin-related changes in carotid atherosclerosis than VWV suggesting that texture classifiers can be used to detect changes in carotid atherosclerosis after therapy.

The use of contrast enhanced ultrasound in carotid arterial disease

Traditionally, stroke risk stratification has centred on the degree of internal carotid artery stenosis, and the presence of focal neurological symptoms. However, degree of stenosis alone is a relatively poor predictor of future stroke in asymptomatic patients; the Asymptomatic Carotid Surgery Trial highlighting the need to identify a subgroup of asymptomatics that may benefit from intervention. Attempting to define this subgroup has inspired imaging research to identify, in vivo, high-risk plaques. In addition to pre-operative risk stratification of carotid stenosis, contrast enhanced ultrasound (CEUS) may be employed in monitoring response to plaque-stabilising therapies. Unlike most contrast agents used for computed tomography and magnetic resonance imaging, microbubbles used in CEUS remain within the vascular space and can hence be used to study the vasculature. In addition to improving current carotid structural scans, CEUS has potential to add extra information on plaque characteristics. Furthermore, by targeting microbubbles to specific ligands expressed on vascular endothelium, CEUS may have the ability to probe plaque biology. This review describes the current carotid ultrasound examination and the need to improve it, rationale for imaging neovascularisation, use of CEUS to image neovascularisation, microbubbles in improving the structural imaging of plaque, potential problems with CEUS, and future directions.

Spatial registration of temporally separated whole breast 3D ultrasound images

The purpose of this study was to evaluate the potential for use of image volume based registration (IVBaR) to aid in measurement of changes in the tumor during chemotherapy of breast cancer. Successful IVBaR could aid in the detection of such changes in response to neoadjuvant chemotherapy and potentially be useful for routine breast cancer screening and diagnosis. IVBaR was employed in a new method of automated estimation of tumor volume in studies following the radiologist identification of the tumor region in the prechemotherapy scan. The authors have also introduced a new semiautomated method for validation of registration based on Doppler ultrasound (U.S.) signals that are independent of the grayscale signals used for registration. This Institutional Review Board approved study was conducted on 10 patients undergoing chemotherapy and 14 patients with a suspicious/unknown mass scheduled to undergo biopsy. Reasonably reproducible mammographic positioning and nearly whole breast U.S. imaging were achieved. The image volume was registered offline with a mutual information cost function and global interpolation based on a thin-plate spline using MIAMI FUSE software developed at the University of Michigan. The success and accuracy of registration of the three dimensional (3D) U.S. image volume were measured by means of mean registration error (MRE). IVBaR was successful with MRE of 4.3 +/- 1.7 mm in 9 out of 10 reproducibility automated breast ultrasound (ABU) studies and in 12 out of 17 ABU image pairs collected before, during, or after 115 +/- 14 days of chemotherapy. Semiautomated tumor volume estimation was performed on registered image volumes giving 86 +/- 8% mean accuracy compared to the radiologist hand-segmented tumor volume on seven cases. Doppler studies yielded fractional volume of color pixels in the region surrounding the lesion and its change with changing breast compression. The Doppler study of patients with detectable blood flow included five patients with suspicious masses and three undergoing chemotherapy. Spatial alignment of the 3D blood vessel data from the Doppler studies provided independent measures for the validation of registration. In 15 Doppler image volume pairs scanned with differing breast compression, the mean centerline separation value was 1.5 +/- 0.6 mm, while MRE based on a few identifiable structural points common to the two grayscale image volumes was 1.1 +/- 0.6 mm. Another measure, the overlap ratio of blood vessels, was shown to increase from 0.32 to 0.59 (+84%) with IVBaR for pairs at various compression levels. These results show that successful registration of ABU scans may be accomplished for comparison and integration of information.