Quantitative Assessment of Cancer Vascular Architecture by Skeletonization of High-resolution 3-D Contrast-enhanced Ultrasound Images: Role of Liposomes and Microbubbles.

The accurate characterization and description of the vascular network of a cancer lesion is of paramount importance in clinical practice and cancer research in order to improve diagnostic accuracy or to assess the effectiveness of a treatment. The aim of this study was to show the effectiveness of liposomes as an ultrasound contrast agent to describe the 3-D vascular architecture of a tumor. Eight C57BL/6 mice grafted with syngeneic B16-F10 murine melanoma cells were injected with a bolus of 1,2-Distearoyl-sn-glycero-3-phosphocoline (DSPC)-based non-targeted liposomes and with a bolus of microbubbles. 3-D contrast-enhanced images of the tumor lesions were acquired in three conditions: pre-contrast, after the injection of micro bubbles, and after the injection of liposomes. By using a previously developed reconstruction and characterization image processing technique, we obtained the 3-D representation of the vascular architecture in these three conditions. Six descriptive parameters of these networks were also computed: the number of vascular trees (NT), the vascular density (VD), the number of branches, the 2-D curvature measure, the number of vascular flexes of the vessels, and the 3-D curvature. Results showed that all the vascular descriptors obtained by liposome-based images were statistically equal to those obtained by using microbubbles, except the VD which was found to be lower for liposome images. All the six descriptors computed in pre-contrast conditions had values that were statistically lower than those computed in presence of contrast, both for liposomes and microbubbles. Liposomes have already been used in cancer therapy for the selective ultrasound-mediated delivery of drugs. This work demonstrated their effectiveness also as vascular diagnostic contrast agents, therefore proving that liposomes can be used as efficient “theranostic” (i.e. therapeutic 1 diagnostic) ultrasound probes

Association of automated carotid IMT measurement and HbA1c in Japanese patients with coronary artery disease

AIMS: The purpose of this study was to evaluate whether carotid IMT (cIMT) identified using automated software is associated with HbA1c in Japanese patients with coronary artery disease. METHODS: 370 consecutive patients (males 218; median age 69 years±11) who underwent carotid-US and first coronary angiography were prospectively analyzed. After ultrasonographic examinations were performed, the plaque score (PS) was calculated and automated IMT analysis was obtained with a dedicated algorithm. Pearson correlation analysis was performed to calculate the association between automated IMT, PS and HbA1c. RESULTS: The mean value of cIMT was 1.00±0.47mm for the right carotid and 1.04±0.49mm for the left carotid; the average bilateral value was 1.02±0.43mm. No significant difference of cIMT was detected between men and women. We found a direct correlation between cIMT values and HbA1c (p=0.0007) whereas the plaque score did not correlate with the HbA1c values (p>0.05) CONCLUSION: The results of our study confirm that automated cIMT values and levels of HbA1c in Japanese patients with coronary artery disease are correlated whereas the plaque score does not show a statistically significant correlation

Automated IMT estimation and BMI correlation using a low-quality carotid ultrasound image database from India.

This paper presents AtheroEdgeLowRes (AELR), an extention of AtheroEdge™ from AtheroPoint™, and a solution to carotid ultrasound IMT measurement in low-resolution and overall low quality images. The images were collected using a low-end ultrasound machine during a screening study in India. We aim to demonstrate the accuracy and reproducibility of the AELR system by benchmarking it against an expert Reader's manual tracing and to show the correlation between the automatically measured intima media thickness (IMT) and the subjects' cardiovascular risk factors (i.e. body mass index - BMI). We introduced an innovative penalty function (PF) to our dual-snake segmentation technique, necessary due to the low image resolution. We processed 512 images from 256 patients, and correlated the AELR IMT values with the patients' age and BMI. AELR processed all 512 images, and the IMT measurement error was 0.011±0.099 mm with the PF correction and 0.173±0.127 mm without. AELR IMT values correlated with the Reader's values (r = 0.883) and also correlated with the subject's BMI and age. The AELR system showed accuracy and reproducibility levels that make it suitable to be used in large epidemiological and screening studies in emerging countries

Completely automated robust edge snapper for carotid ultrasound IMT measurement on a multi-institutional database of 300 images

The carotid intima-media thickness (IMT) is the most used marker for the progression of atherosclerosis and onset of cardiovascular diseases. Computer-aided measurements improve accuracy and precision, but usually require user interaction. In this paper we characterized a new and completely automated technique for carotid segmentation and IMT measurement based on the merits of two previously developed techniques. We used an integrated approach of intelligent image feature extraction and line fitting for automatically locating the carotid artery in the image frame, followed by wall interfaces extraction based on a Gaussian edge operator. We called our system—CARES. We validated CARES on a multi-institutional database of 300 carotid ultrasound images. The IMT measurement bias was 0.032 ± 0.141 mm. Our novel approach of CARES processed 96% of the images in the database taken from two different institutions. In order to evaluate its performance, the figure-of-merit (FoM) was defined as the percent ratio between the average IMT computed by CARES and the one obtained from manual tracings by expert sonographers. The estimated FoM by CARES was 95.7%. Comparing the IMT bias of CARES with our previously published method CALEX that showed an IMT bias equal to 0.099 ± 0.137 mm, CARES improved the IMT accuracy by 67%, while increasing the standard deviation by 3%. CARES could be a useful research tool for processing large datasets in multi-center studies involving atherosclerosi

Fully Automated Muscle Ultrasound Analysis (MUSA): Robust and Accurate Muscle Thickness Measurement

Musculoskeletal ultrasound imaging allows non-invasive measurement of skeletal muscle thickness. Current techniques generally suffer from manual operator dependency, while all the computer-aided approaches are limited to be semi-automatic or specifically optimized for a single muscle. The aim of this study was to develop and validate a fully automatic method, named MUSA (Muscle UltraSound Analysis), for measurement of muscle thickness on longitudinal ultrasound images acquired from different skeletal muscles. The MUSA algorithm was tested on a database of 200 B-mode ultrasound images of rectus femoris, vastus lateralis, tibialis anterior and medial gastrocnemius. The automatic muscle thickness measurements were compared to the manual measurements obtained by three operators. The MUSA algorithm achieved a 100% segmentation success rate, with mean differences between the automatic and manual measurements in the range of 0.06–0.45 mm. MUSA performance was statistically equal to the operators and its measurement accuracy was independent of the muscle thickness value

Completely automated robust edge snapper for carotid ultrasound IMT measurement on a multi-institutional database of 300 images

The carotid intima-media thickness (IMT) is the most used marker for the progression of atherosclerosis and onset of cardiovascular diseases. Computer-aided measurements improve accuracy and precision, but usually require user interaction. In this paper we characterized a new and completely automated technique for carotid segmentation and IMT measurement based on the merits of two previously developed techniques. We used an integrated approach of intelligent image feature extraction and line fitting for automatically locating the carotid artery in the image frame, followed by wall interfaces extraction based on a Gaussian edge operator. We called our system—CARES. We validated CARES on a multi-institutional database of 300 carotid ultrasound images. The IMT measurement bias was 0.032 ± 0.141 mm. Our novel approach of CARES processed 96% of the images in the database taken from two different institutions. In order to evaluate its performance, the figure-of-merit (FoM) was defined as the percent ratio between the average IMT computed by CARES and the one obtained from manual tracings by expert sonographers. The estimated FoM by CARES was 95.7%. Comparing the IMT bias of CARES with our previously published method CALEX that showed an IMT bias equal to 0.099 ± 0.137 mm, CARES improved the IMT accuracy by 67%, while increasing the standard deviation by 3%. CARES could be a useful research tool for processing large datasets in multi-center studies involving atherosclerosis

Carotid ultrasound in-vivo strain imaging: is there a liposomes induced vascular effect?

Liposomes are nanoparticles that are gaining increasing importance as targeting agents, molecular probes, and drug carriers. In this work, we evaluated the vascular effect of a liposomes bolus injected intravenously in mice. Ultrasound high-resolution cineloops of the mice's carotid artery were acquired and used to measure the radial and longitudinal strains thanks to a speckle tracking algorithm. Control mice were injected with a bolus of saline solution. The strain imaging revealed that higher amplitude displacements were observable after the bolus injection of liposomes, whereas after the injection of saline, the amplitude displacements did not change significantly. This study is a first step for the quantification of the vascular endothelial effect of liposomes injectio

CARES 2.0: Completely Automated Robust Edge Snapper for CIMT measurement in 300 ultrasound images—A two stage paradigm

The carotid intima-media thickness (IMT) is a widely used marker associated to the risk of cardiovascular diseases and to atherosclerosis progression. IMT measurement requires high accuracy and reproducibility. Computer-aided measurements improve accuracy and precision, but usually require user interaction. In this paper we proposed an improved method (called CARES 2.0) over the previously developed technique (called CARES 1.0). CARES 2.0 is a two stage process: Stage-I adapts an integrated approach of intelligent image feature extraction and line fitting for far adventitia border detection. Stage-II is a first order absolute moment (FOAM 1.0) coupled to a novel and improved heuristic search for the lumen-intima (LI) and media-adventitia (MA) peaks. CARES 2.0 brings in two novel scientific contributions: (a) ability to improve Stage-I to compare jugular vein versus carotid artery and (b) introduction bi-directional and robust FOAM. The improved method is a fully automated IMT measurement technique, and was validated on a multi-institutional database of 300 images exhibiting normal and pathologic carotids. We benchmarked CARES 2.0 against previously developed CALEX 1.0 and user-driven FOAM 1.0. CARES 2.0 showed an IMT measurement bias equal to -0.032 +/- 0.178 mm, which was better than CALEX 1.0 (0.070 +/- 0.331 mm), FOAM 1.0 (-0.091 +/- 0.161 mm) and CARES 1.0 (0.035 +/- 0.198 mm), respectively. Thus CARES 2.0 showed an improvement of 54% over CALEX 1.0, 65% over stand alone FOAM 1.0 and 9% over CARES 1.0. Compared to CARES 1.0, CARES 2.0 improved the reproducibility by 10%. CARES 2.0 ensured complete automation and increased the reproducibility of the IMT measurement, a step closer for clinical usage