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

Quantitative Ultrasound and Photoacoustic Imaging Techniques for the Assessment of Architectural and Vascular Parameters

The work in this final dissertation can be divided into two macro areas: (1) morphological vascular studies based on the development of quantitative imaging techniques for the use with clinical B-mode ultrasound images, and (2) preclinical architectural vascular studies based on quantitative imaging techniques for ultrasounds and photoacoustics. The first section, which makes up the second and third chapters of this thesis, focuses on the development and validation of quantitative techniques for the assessment of vascular morphological parameters that can be extracted from B-mode ultrasound longitudinal images of the common carotid artery. In chapter 2, results from numerous past studies are presented, ranging from the validation of techniques for correctly locating the CCA in B-mode ultrasound images, the development and implementation of novel completely automated techniques for the IMT measurement and plaque segmentation, and the validation and association of the automatically measured IMT value with clinical parameters. Chapter 3 focuses instead on the validation of the intima-media thickness variability parameter. Recent studies have shown that the IMT variation along the carotid artery wall has a stronger correlation with atherosclerosis than the nominal intima-media thickness value itself, so this chapter presents an in-depth study of the IMT variability (IMTV) parameter, determining (1) if the IMTV value depends on the number of points making up the LI and MA profiles, (2) if it depends on the nominal IMT value, (3) which distance metric should be used, and finally (4), if manual segmentations of the far wall can be considered reliable for the IMTV measurement. The second section, the fourth and fifth chapters of this thesis, instead emphasizes quantitative imaging techniques for the assessment of architectural parameters of vasculature that can be extracted from 3D volumes, using first of all contrast-enhanced ultrasound (CEUS) imaging and, secondly, photoacoustic imaging without the administration of any contrast agent. More specifically, chapter 4 demonstrates how the characterization and description of the vascular network of a cancer lesion in mouse models can be effectively determined using both traditional microbubbles and liposomes. Eight mice were administered both microbubbles and liposomes and 3D CEUS volumes were acquired. Vascular architectural descriptors were calculated after a skeletonization technique was applied. Chapter 5 focuses on the development and validation of a skeletonization technique for the quantitative assessment of vascular architecture in burn wounds using completely non-invasive photoacoustic imaging, thus not requiring any contrast agent administration. It was shown how this technique can provide quantitative information about the vascular network from photoacoustic images that can distinguish healthy from diseased tissue. A summarizing discussion (chapter 6) concludes this thesis

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

CAROTID WALL MEASUREMENT AND ASSESSMENT BASED ON PIXEL-BASED AND LOCAL TEXTURE DESCRIPTORS

Aim of this paper is to develop an automated system for the classification and characterization of carotid wall status and to develop a robust system based on local texture descriptors. A database of 200 longitudinal ultrasound images of carotid artery is used. One-hundred images with Intima-Media Thickness (IMT) value higher than 0.8mm are considered as high risk. Six different rectangular pixel neighborhoods were considered: four areas centered on the selected element, with sizes 7 15, 15 7, 7 3, and 3 7 pixels, and two noncentered areas with sizes 7 3 pixels upwards and downwards. We have extracted various texture descriptors (31 based on the co-occurrence gray level matrix, 13 based on the spatial gray level dependence matrix, and 20 based on the gray level run length matrix) from neighborhood. We have used Quick Reduct Algorithm to select 12 most discriminant features from extracted 211 features. Each pixel is then assigned to the vessel lumen, to the intima-media complex, or to the adventitia by using an integrated system of three feed-forward neural networks. The boundaries between the three regions are used to estimate the IMT value. The texture features associated with GLRLM are found to be clinically most significant. We have obtained an overall classification accuracy of 79.5%, sensitivity of 87%, and specificity of 72%. We observed a unique classification pattern between low risk and high risk images: in the latter ones, a considerable number of pixels of the intima–media complex (31.2% +- 14.4%) was classified as belonging to the adventitia. This percentage is statistically higher than that of low risk images (18.2% +- 11.8%; p < 0:001). Locally extracted and pixel-based descriptors are able to capture the inner characteristics of the carotid wall. The presence of misclassified pixels in the intima– media complex is associated to higher cardiovascular risk

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