Comparison of Histogram-based Textural Features between Cancerous and Normal Prostatic Tissue in Multiparametric Magnetic Resonance Images.

In the last decade, multiparametric magnetic resonance imaging (mpMRI) has been expanding its role in prostate cancer detection and characterization. In this work, 19 patients with clinically significant peripheral zone (PZ) tumours were studied. Tumour masks annotated on the whole-mount histology sections were mapped on T2-weighted (T2w) and diffusion-weighted (DW) sequences. Gray-level histograms of tumoral and normal tissue were compared using six first-order texture features. Multivariate analysis of variance (MANOVA) was used to compare group means. Mean intensity signal of ADC showed the highest showed the highest area under the receiver operator characteristics curve (AUC) equal to 0.85. MANOVA analysis revealed that ADC features allows a better separation between normal and cancerous tissue with respect to T2w features (ADC: P = 0.0003, AUC = 0.86; T2w: P = 0.03, AUC = 0.74). MANOVA proved that the combination of T2-weighted and apparent diffusion coefficient (ADC) map features increased the AUC to 0.88. Histogram-based features extracted from invivo mpMRI can help discriminating significant PZ PCa.

Skeletonization algorithm-based blood vessel quantification using in vivo 3D photoacoustic imaging.

Blood vessels are the only system to provide nutrients and oxygen to every part of the body. Many diseases can have significant effects on blood vessel formation, so that the vascular network can be a cue to assess malicious tumor and ischemic tissues. Various imaging techniques can visualize blood vessel structure, but their applications are often constrained by either expensive costs, contrast agents, ionizing radiations, or a combination of the above. Photoacoustic imaging combines the high-contrast and spectroscopic-based specificity of optical imaging with the high spatial resolution of ultrasound imaging, and image contrast depends on optical absorption. This enables the detection of light absorbing chromophores such as hemoglobin with a greater penetration depth compared to purely optical techniques. We present here a skeletonization algorithm for vessel architectural analysis using non-invasive photoacoustic 3D images acquired without the administration of any exogenous contrast agents. 3D photoacoustic images were acquired on rats (n = 4) in two different time points: before and after a burn surgery. A skeletonization technique based on the application of a vesselness filter and medial axis extraction is proposed to extract the vessel structure from the image data and six vascular parameters (number of vascular trees (NT), vascular density (VD), number of branches (NB), 2D distance metric (DM), inflection count metric (ICM), and sum of angles metric (SOAM)) were calculated from the skeleton. The parameters were compared (1) in locations with and without the burn wound on the same day and (2) in the same anatomic location before (control) and after the burn surgery. Four out of the six descriptors were statistically different (VD, NB, DM, ICM, p < 0.05) when comparing two anatomic locations on the same day and when considering the same anatomic location at two separate times (i.e. before and after burn surgery). The study demonstrates an approach to obtain quantitative characterization of the vascular network from 3D photoacoustic images without any exogenous contrast agent which can assess microenvironmental changes related to disease progression.

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 microbubbles, 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.

What is the correct distance measurement metric when measuring carotid ultrasound intima-media thickness automatically?

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.

Automated carotid IMT measurement and its validation in low contrast ultrasound database of 885 patient Indian population epidemiological study: results of AtheroEdge™ Software.

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.