Search

Aim: Calcium burden measurement in internal carotid artery (ICA) plaque could play an important role in assessing stroke risk and stenosis quantification in the ICA. We propose an automatic method for labelling calcified plaques in ICA in CT images., Methods: Our approach builds upon the mean shift paradigm via an adaptive thresholding strategy. The data consists of single CT slices from 75 patients, with variety of plaque sizes and number of calcium regions. The manual measurements were carried out by a neuroradiologist for benchmarking. The calcium burden was measured as the area of the labelled plaque. Various metrics were employed to compare manual and automated measurements including correlation coefficient (CC), dice similarity (DS), Jacard Index (JI), polyline distance metric (PDM) and precision of merit (PoM)., Results: We found that our automated method of calcium area characterization performed accurately compared to manual measurements with CC=0.978, and PoM=0.915. The PDM, DS, and JI, also indicate a good performance with a mean DS=0.85 (SD=0.085), a mean JI=0.747 (SD=0.12), and a mean PDM=0.195 (SD=0.177)., Conclusion: The proposed approach for calcium burden measurement, yields reasonably accurate labelling of calcified plaque when benchmarked against manual measurements. The approach is independent of the number and size of calcium regions, and the prototype design shows encouraging results to be adaptable to clinical practice.

Aim: Carotid intima-media thickness (cIMT) measurements during clinical trials need to have a fixed reference point (also called as bulb edge points) in the anatomy from which the cIMT can be measured. Identification of the bulb edge points in carotid ultrasound images faces the challenge to be detected automatically due to low image quality and variations in ultrasound images, motion artefacts, image acquisition protocols, position of the patient, and orientation of the linear probe with respect to bulb and ultrasound gain controls during acquisition., Methods: This paper presents a patented comprehensive methodology for carotid bulb localization and bulb edge detection as a reference point. The method consists of estimating the lumen-intima borders accurately using classification paradigm. Transition points are located automatically based on curvature characteristics. Further we verify and validate the locations of bulb edge points using combination of several local image processing methods such as (i) lumen-intima shapes, (ii) bulb slopes, (iii) bulb curvature, (iv) mean lumen thickness and its variations, and (v) geometric shape fitting., Results: Our database consists of 155 ultrasound bulb images taken from various ultrasound machines with varying resolutions and imaging conditions. Further we run our automated system blindly to spot out the bulbs in a mixture database of 336 images consisting of bulbs and no-bulbs. We are able to detect the bulbs in the bulb database with 100% accuracy having 92% as close as to a neurologists's bulb location. Our mean lumen-intima error is 0.0133 mm with precision against the manual tracings to be 98.92%. Our bulb detection system is fast and takes on an average 9 seconds per image for detection for the bulb edge points and 4 seconds for verification/validation of the bulb edge points.

Aim: Establishing relationship between coronary calcium volumes from Intravascular Ultrasound (IVUS) and automated carotid intima-media thickness (cIMT) helps in understanding the genetic nature of atherosclerosis disease. In this research, we have quantified the detected calcium from IVUS video frames and associated a relationship between coronary calcium volumes computed and automated cIMT from B-mode ultrasound., Methods: Coronary calcium volume is computed from IVUS and auto cIMTs are computed using B-mode ultrasound. An automated computer based application is developed and tested on 100 patient volumes (an average of 2549 frames per volume) to calculate lesion area and normalized coronary calcium volume. We use an integrated approach for volume computation which is based on lesion area per frame. We have measured the normalized volume from the calcium detected video frames using proposed integration method. The cIMT of 100 carotids were measured with novel and dedicated automated software analysis (AtheroEdge™ from AtheroPoint™ LLC, Roseville, CA, USA)., Results: The computer-based coronary calcium volume (from IVUS) showed a correlation coefficient with respect to cIMT for left and right carotids as 9.1% and 13.9%, respectively., Conclusion: Coronary calcium volume computed from IVUS and auto cIMT are moderately correlated. The association between auto cIMT (right side) vs. computer-based coronary calcium volume (IVUS) is stronger than the association between auto cIMT (left side) vs. computer-based coronary calcium volume.

Aim: The purpose of this study was to evaluate whether the automated carotid intima-media thickness (CIMT) identified by using automated software could predict the SYNTAX score for coronary artery disease (CAD) patients., Methods: Three-hundred-seventy consecutive patients (males 218; median age 69±11 years) who underwent carotid-ultrasound and coronary angiography were analyzed. Two experienced interventional cardiologists calculated the SYNTAX score from the carotid angiograms. After ultrasonographic examinations were performed, the plaque score (PS) was calculated and automated carotid IMT analysis was obtained by a fully automated algorithm. Correlation and stepwise logistic regression analysis were calculated and also the receiver operating characteristics (ROC) curve analysis was computed., Results: The mean SYNTAX score was 8.1±14.4; the PS was 7.1±14.4 and the mean CIMT was 0.86±0.23 mm (Normality rejected with a P-value of 0.001). A statistically significant correlation was found between the CIMT and SYNTAX score (r=0.323; P=0.0001) and between the PS and SYNTAX score (r=0.583; P=0.0001). The area under the ROC curve (Az) between CIMT and coronary artery disease was 0.648 (P=0.0001) and the CIMT of 1 mm or more was associated with the presence coronary artery disease with a specificity of 90.5%. Logistic regression analysis confirmed the association between CIMT and SYNTAX score (P=0.0002)., Conclusions: Results of our study using an automated algorithm showed a statistical significant association between CIMT and SYNTAX score and indicated that CIMT may be considered a reliable parameter for prediction of SYNTAX score in coronary artery disease patient population from Japan.

Aim: The aims of this study were: 1) to analyze the interobserver carotid intima-media thickness (CIMT) variability using three different measurement metrics on large multi-institutional databases; 2) to evaluate the three kinds of metrics when comparing completely automated CIMT measurement (Auto Edge CIMT) to two manually derived CIMT (manual CIMT)., Methods: Two expert sonographers manually analyzed 665 carotid B-Mode ultrasound images collected from five institutions and using four different scanners. The two readers traced the lumen-intima (LI) and media-adventitia (MA) interfaces. The manual CIMT was computed from the LI/MA tracings by using three different distance measurement metrics: the Hausdorff, the PolyLine, and the Centerline distance metrics. The LI/MA tracings of a completely automated method we previously developed were then compared to manual CIMT., Results: The average CIMT values of Readers 1 and 2 were 1.904±0.650 mm and 1.421±0.394 using Hausdorff, 0.808±0.269 mm and 0.790±0.227 mm using Polyline, and 0.762±0.266 mm and 0.782±0.228 mm using Centerline, respectively. The correlation coefficients were 0.14 (0.07-0.22) for Hausdorff, 0.77 (0.74-0.80) for Polyline, and 0.82 (0.79-0.84) for Centerline. The variation coefficients (CV) were equal to 46.4% (Hausdorff), 2.6 % (Polyline), and 14.1% (Centerline). The Auto Edge CIMT values were: 1.655±0.676 mm using Hausdorff, 0.808±0.282 mm using Polyline, and 0.776±0.275 mm using Centerline., Conclusion: Centerline and Polyline yield very close results and are clinically suitable distance measurement techniques for computing the CIMT from LI/MA profiles.

Aim: The aim of this paper was to demonstrate the usage of an automated computer-based IMT measurement system called - CALEX 3.0 (a class of patented AtheroEdge™ software) on a low contrast and low resolution image database acquired during an epidemiological study from India. The image contrast was very low with pixel density of 12.7 pixels/mm. Further, to demonstrate the accuracy and reproducibility of the AtheroEdge™ software system we compared it with the manual tracings of a vascular surgeon--considered as a gold standard., Methods: We automatically measured the IMT value of 885 common carotid arteries in longitudinal B-Mode images. CALEX 3.0 consisted of a stage for the automatic recognition of the carotid artery and an IMT measurement modulus made of a fuzzy K-means classifier. Performance was assessed by measuring the system accuracy and reproducibility against manual tracings by experts., Results: CALEX 3.0 processed all the 885 images of the dataset (100% success). The average automated obtained IMT measurement by CALEX 3.0 was 0.407±0.083 mm compared with 0.429 ± 0.052 mm for the manual tracings, which led to an IMT bias of 0.022±0.081mm. The IMT measurement accuracy (0.022 mm) was comparable to that obtained on high-resolution images and the reproducibility (0.081 mm) was very low and suitable to clinical application. The Figure-of-Merit defined as the percent agreement between the computer-estimated IMT and manually measured IMT for CALEX 3.0 was 94.7%., Conclusion: CALEX 3.0 had a 100% success in processing low contrast/low-resolution images. CALEX 3.0 is the first technique, which has led to high accuracy and reproducibility on low-resolution images acquired during an epidemiological study. We propose CALEX 3.0 as a generalized framework for IMT measurement on large datasets.

Aim: In this work we present a novel methodology (called CALSFOAM) for the automated segmentation of ultrasound carotid images and intima-media thickness (IMT) measurement. CALSFOAM was developed in order to overcome limitations of a previously developed snake-based technique., Methods: CALSFOAM consists of two stages: Stage-I is an automatic recognition of the carotid artery system in an image frame and Stage-II is a combination of segmentation and IMT measurement sub-system. Stage-I is performed by using local statistics and by automatically tracing the profile of the distal adventitia. Stage-II takes the traced adventitia boundary and builds an ROI for distal wall segmentation that uses a first order absolute moment (FOAM) technique. CALSFOAM was benchmarked against our previous snake based technique and validated on a 300-image multi-institutional dataset., Results: CALSFOAM's lumen-intima (LI) segmentation error was 0.049±0.039 mm, the media-adventitia (MA) error was 0.088±0.054 mm; the IMT measurement bias was 0.125±0.103 mm. To reduce CALSFOAM error, we adopted a GREEDY approach for fusing the boundaries from the two techniques and obtained LI and MA errors equal to 0.02±0.014 mm, 0.023±0.013 mm, and an IMT bias of 0.074±0.068 mm., Conclusion: Even though CALSFOAM's performance was lower than snake-based segmentation techniques, it helped in avoiding possible inaccuracies of snakes and its parameter sensitivities. The very accurate performance obtained by the GREEDY approach demonstrated that the two techniques could be considered as complementary.