•A texture-based biomarker was developed that detected changes in atherosclerotic plaque due to dietary intervention with high sensitivity.•Established the effect of pomegranate juice and tablets in ...a statistically significant manner for the first time.•The proposed biomarker requires 20 times fewer subjects than total plaque volume (TPV) to detect the effect of pomegranate.
Background and objective: Dietary supplements are expected to confer a smaller beneficial effect than medical treatments. Therefore, there is a need to develop cost-effective biomarkers that can demonstrate the efficacy of such supplements for carotid atherosclerosis. The aim of this study is to develop such a biomarker based on the changes of 376 plaque textural features measured from 3D ultrasound images.
Methods: Since the number of features (376) was greater than the number of subjects (171) in this study, principal component analysis (PCA) was applied to reduce the dimensionality of feature vectors. To generate a scalar biomarker for each subject, elements in the reduced feature vectors produced by PCA were weighted using locality preserving projections (LPP) to capture essential patterns exhibited locally in the feature space. 96 subjects treated by pomegranate juice and tablets, and 75 subjects receiving placebo-matching juice and tablets were evaluated in this study. The discriminative power of the proposed biomarker was evaluated and compared with existing biomarkers using t-tests. As the cost of a clinical trial is directly related to the number of subjects enrolled, the cost-effectiveness of the proposed biomarker was evaluated by sample size estimation.
Results: The proposed biomarker was more able to discriminate plaque changes exhibited by the pomegranate and placebo groups than total plaque volume (TPV) according to the result of t-tests (TPV: p=0.34, Proposed biomarker: p=1.5×10−5). The sample size required by the new biomarker to detect a significant effect was 20 times smaller than that required by TPV.
Conclusion: With the increase in cost-effectiveness afforded by the proposed biomarker, more proof-of-principle studies for novel treatment options could be performed.
Preterm neonates with a very low birth weight of less than 1,500 grams are at increased risk for developing intraventricular hemorrhage (IVH), which is a major cause of brain injury in preterm ...neonates. Quantitative measurements of ventricular dilatation or shrinkage play an important role in monitoring patients and evaluating treatment options. 3D ultrasound (US) has been developed to monitor ventricle volume as a biomarker for ventricular changes. However, ventricle volume as a global indicator does not allow for precise analysis of local ventricular changes, which could be linked to specific neurological problems often seen in the patient population later in life. In this work, a 3D+t spatial-temporal deformable registration approachis proposed, which is applied to the analysis of the detailed local changes of preterm IVH neonatal ventricles from 3D US images. In particular, a novel sequential convex/dual optimization algorithm is introduced to extract the optimal 3D+t spatial-temporal deformable field, which simultaneously optimizes the sequence of 3D deformation fieldswhile enjoying both efficiencyand simplicity in numerics. The developed registration technique was evaluated by comparing two manually extracted ventricle surfaces from the baseline and the registered follow-up images using the metrics of Dice similarity coefficient (DSC), mean absolute surface distance (MAD), and maximum absolute surface distance (MAXD). The performed experiments using 14 patients with 5 time-point images per patient show that the proposed 3D+t registration approach accurately recovered the longitudinal deformation of ventricle surfaces from 3D US images. The proposed approach may be potentially used to analyse the change pattern of cerebral ventricles of IVH patients, their response to different treatment options, and to elucidate the deficiencies that a patient could have later in life. To the best of our knowledge, this paper reports the first study on the longitudinalanalysis of neonatal ventricular system from 3D US images.
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.
Multiparametric magnetic resonance imaging (mpMRI) has been established as the state-of-the-art examination for the detection and localization of prostate cancer lesions. Prostate Imaging-Reporting ...and Data System (PI-RADS) has been established as a scheme to standardize the reporting of mpMRI findings. Although lesion delineation and PI-RADS ratings could be performed manually, human delineation and ratings are subjective and time-consuming. In this article, we developed and validated a self-tuned graph-based model for PI-RADS rating prediction. 34 features were obtained at the pixel level from T2-weighted (T2W), apparent diffusion coefficient (ADC) and dynamic contrast enhanced (DCE) images, from which PI-RADS scores were predicted. Two major innovations were involved in this self-tuned graph-based model. First, graph-based approaches are sensitive to the choice of the edge weight. The proposed model tuned the edge weights automatically based on the structure of the data, thereby obviating empirical edge weight selection. Second, the feature weights were tuned automatically to give heavier weights to features important for PI-RADS rating estimation. The proposed framework was evaluated for its lesion localization performance in mpMRI datasets of 12 patients. In the evaluation, the PI-RADS score distribution map generated by the algorithm and from the observers' ratings were binarized by thresholds of 3 and 4. The sensitivity, specificity and accuracy obtained in these two threshold settings ranged from 65 to 77%, 86 to 93% and 85 to 88% respectively, which are comparable to results obtained in previous studies in which non-clinical T2 maps were available. The proposed algorithm took 10s to estimate the PI-RADS score distribution in an axial image. The efficiency achievable suggests that this technique can be developed into a prostate MR analysis system suitable for clinical use after a thorough validation involving more patients.
Purpose:
Intraventricular hemorrhage (IVH) is a major cause of brain injury in preterm neonates. Three dimensional ultrasound (US) imaging systems have been developed to visualize 3D anatomical ...structure of preterm neonatal intracranial ventricular system with IVH and ventricular dilation. To allow quantitative analysis, the ventricle system is required to be segmented accurately and efficiently from 3D US images. Although semiautomatic segmentation algorithms have been developed, local segmentation accuracy and variability associated with these algorithms should be evaluated statistically before they can be applied in clinical settings. This work proposes a statistical framework to quantify the local accuracy and variability and performs statistical tests to identify locations where the semiautomatically segmented surfaces are significantly different from manually segmented surfaces.
Methods:
Three dimensional lateral ventricle US images of preterm neonates were each segmented six times manually and using a semiautomated segmentation algorithm. The local difference between manually and algorithmically segmented surfaces as well as the segmentation variability for each method was computed and superimposed on the ventricular surface of each subject. To summarize the segmentation performance for a whole group of subjects, the subject‐specific local difference and standard deviation maps were registered onto a 3D template ventricular surface using a nonrigid registration algorithm. Pointwise, intersubject average accuracy and pooled variability for the whole group of subjects can be computed and visualized on the template surface, providing a summary of performance of the segmentation algorithm for the whole group of ventricles with highly variable geometry. In addition to pointwise statistical analysis performed on the template surface, statistical conclusion regarding the accuracy of the segmentation algorithm was made for subregions and the whole ventricle with the spatial correlation of pointwise accuracy taken into account.
Results:
Ten 3D US images were involved in this study. Pointwise local difference, ΔS, its absolute value |ΔS| as well as the standard deviations of the manual and algorithm segmentations were computed and superimposed on the each ventricle surface. Regions with lower segmentation accuracy and higher segmentation variability can be identified from these maps, and the localized information was applied to improve the accuracy of the algorithm. Intersubject average ΔS and |ΔS| as well as pooled standard deviations was computed on the template surface. Intersubject average ΔS and |ΔS| indicated that the algorithm underestimated regions in the neighborhood of the tips of anterior, inferior, and posterior horns. Intersubject pooled standard deviations indicated that manual segmentation had a higher segmentation variability than algorithm segmentation over the whole ventricle. Statistical analysis on the template surface showed that there was significant difference between algorithm and manual methods for segmenting the right lateral ventricle but not for the left lateral ventricle.
Conclusions:
A framework was proposed for evaluating, visualizing, and summarizing the local accuracy and variability of a segmentation algorithm. This framework can be used for improving the accuracy of segmentation algorithms, as well as providing useful feedback to improve the manual segmentation performance. More importantly, this framework can be applied for longitudinal monitoring of local ventricular changes of neonates with IVH.
Purpose:
Vessel wall imaging techniques have been introduced to assess the burden of peripheral arterial disease (PAD) in terms of vessel wall thickness, area or volume. Recent advances in a 3D ...black-blood MRI sequence known as the 3D motion-sensitized driven equilibrium (MSDE) prepared rapid gradient echo sequence (3D MERGE) have allowed the acquisition of vessel wall images with up to 50 cm coverage, facilitating noninvasive and detailed assessment of PAD. This work introduces an algorithm that combines 2D slice-based segmentation and 3D user editing to allow for efficient plaque burden analysis of the femoral artery images acquired using 3D MERGE.
Methods:
The 2D slice-based segmentation approach is based on propagating segmentation results of contiguous 2D slices. The 3D image volume was then reformatted using the curved planar reformation (CPR) technique. User editing of the segmented contours was performed on the CPR views taken at different angles. The method was evaluated on six femoral artery images. Vessel wall thickness and area obtained before and after editing on the CPR views were assessed by comparison with manual segmentation. Difference between semiautomatically and manually segmented contours were compared with the difference of the corresponding measurements between two repeated manual segmentations.
Results:
The root-mean-square (RMS) errors of the mean wall thickness (t
mean) and the wall area (WA) of the edited contours were 0.35 mm and 7.1 mm2, respectively, which are close to the RMS difference between two repeated manual segmentations (RMSE: 0.33 mm in t
mean, 6.6 mm2 in WA). The time required for the entire semiautomated segmentation process was only 1%–2% of the time required for manual segmentation.
Conclusions:
The difference between the boundaries generated by the proposed algorithm and the manually segmented boundary is close to the difference between repeated manual segmentations. The proposed method provides accurate plaque burden measurements, while considerably reducing the analysis time compared to manual review.
Carotid plaque surface irregularity and ulcerations play an important role in the risk of ischemic stroke. Ulcerated or fissured plaque, characterized by irregular surface morphology, exposes ...thrombogenic materials to the bloodstream, possibly leading to life- or brain-threatening thrombosis and embolization. Therefore, the quantification of plaque surface irregularity is important to identify high-risk plaques that would likely lead to vascular events. Although a number of studies have characterized plaque surface irregularity using subjective classification schemes with two or more categories, only a few have quantified surface irregularity using an objective and continuous quantity, such as Gaussian or mean curvature. In this work, our goal was to use both Gaussian and mean curvatures for identifying ulcers from 3D carotid ultrasound (US) images of human subjects. Before performing experiments using patient data, we verified the numerical accuracy of the surface curvature computation method using discrete spheres and tori with different sampling intervals. We also showed that three ulcers of the vascular phantom with 2 mm, 3 mm and 4 mm diameters were associated with high Gaussian and mean curvatures, and thus, were easily detected. Finally, we demonstrated the application of the proposed method for detecting ulcers on luminal surfaces, which were segmented from the 3D US images acquired for two human subjects.
To evaluate the image-guidance capabilities of megavoltage computed tomography (MVCT), this article compares the interobserver and intraobserver contouring uncertainty in kilovoltage computed ...tomography (KVCT) used for radiotherapy planning with MVCT acquired with helical tomotherapy.
Five prostate-cancer patients were evaluated. Each patient underwent a KVCT and an MVCT study, a total of 10 CT studies. For interobserver variability analysis, four radiation oncologists, one physicist, and two radiation therapists (seven observers in total) contoured the prostate and seminal vesicles (SV) in the 10 studies. The intraobserver variability was assessed by asking all observers to repeat the contouring of 1 patient's KVCT and MVCT studies. Quantitative analysis of contour variations was performed by use of volumes and radial distances.
The interobserver and intraobserver contouring uncertainty was larger in MVCT compared with KVCT. Observers consistently segmented larger volumes on MVCT where the ratio of average prostate and SV volumes was 1.1 and 1.2, respectively. On average (interobserver and intraobserver), the local delineation variability, in terms of standard deviations Deltasigma = radical(sigma2MVCT-sigma2KVCT), increased by 0.32 cm from KVCT to MVCT.
Although MVCT was inferior to KVCT for prostate delineation, the application of MVCT in prostate radiotherapy remains useful.
Quantitative measurements of the progression (or regression) of carotid plaque burden are important in monitoring patients and evaluating new treatment options. 3D ultrasound (US) has been used to ...monitor the progression of carotid artery plaques in symptomatic and asymptomatic patients, and different methods of measuring various ultrasound phenotypes of atherosclerosis have been developed. We have developed a quantitative metric used to analyze changes in carotid plaque morphology from 3D US. This method matched the vertices on the carotid arterial wall surface with those on the luminal surface.
Vessel–
wall-
plus-
plaque thickness (
VWT) was obtained by computing the distance between each corresponding pair, which was then superimposed on the arterial wall to produce the
VWT map. Since the progression of plaque thickness is important in monitoring patients who are at risk for stroke, we also computed the change of
VWT by comparing the
VWT maps obtained for a patient at two different time points. In this paper, we propose a technique to flatten the 3D
VWT and
VWT-
Change maps in an area-preserving manner, in order to facilitate the visualization and interpretation of these maps.
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