Novel contrast-enhanced ultrasound imaging in prostate cancer

The purposes of this paper were to present the current status of contrast-enhanced transrectal ultrasound imaging and to discuss the latest achievements and techniques now under preclinical testing. Although grayscale transrectal ultrasound is the standard method for prostate imaging, it lacks accuracy in the detection and localization of prostate cancer. With the introduction of contrast-enhanced ultrasound (CEUS), perfusion imaging of the microvascularization became available. By this, cancer-induced neovascularisation can be visualized with the potential to improve ultrasound imaging for prostate cancer detection and localization significantly. For example, several studies have shown that CEUS-guided biopsies have the same or higher PCa detection rate compared with systematic biopsies with less biopsies needed. This paper describes the current status of CEUS and discusses novel quantification techniques that can improve the accuracy even further. Furthermore, quantification might decrease the user-dependency, opening the door to use in the routine clinical environment. A new generation of targeted microbubbles is now under pre-clinical testing and showed avidly binding to VEGFR-2, a receptor up-regulated in prostate cancer due to angiogenesis. The first publications regarding a targeted microbubble ready for human use will be discussed. Ultrasound-assisted drug delivery gives rise to a whole new set of therapeutic options, also for prostate cancer. A major breakthrough in the future can be expected from the clinical use of targeted microbubbles for drug delivery for prostate cancer diagnosis as well as treatmen

Dynamic contrast-enhanced ultrasound parametric imaging for the detection of prostate cancer

\u3cp\u3eOBJECTIVE: To investigate the value of dynamic contrast-enhanced (DCE)-ultrasonography (US) and software-generated parametric maps in predicting biopsy outcome and their potential to reduce the amount of negative biopsy cores.\u3c/p\u3e\u3cp\u3eMATERIALS AND METHODS: For 651 prostate biopsy locations (82 consecutive patients) we correlated the interpretation of DCE-US recordings with and without parametric maps with biopsy results. The parametric maps were generated by software which extracts perfusion parameters that differentiate benign from malignant tissue from DCE-US recordings. We performed a stringent analysis (all tumours) and a clinical analysis (clinically significant tumours). We calculated the potential reduction in biopsies (benign on imaging) and the resultant missed positive biopsies (false-negatives). Additionally, we evaluated the performance in terms of sensitivity, specificity negative predictive value (NPV) and positive predictive value (PPV) on a per-prostate level.\u3c/p\u3e\u3cp\u3eRESULTS: Based on DCE-US, 470/651 (72.2%) of biopsy locations appeared benign, resulting in 40 false-negatives (8.5%), considering clinically significant tumours only. Including parametric maps, 411/651 (63.1%) of the biopsy locations appeared benign, resulting in 23 false-negatives (5.6%). In the per-prostate clinical analysis, DCE-US classified 38/82 prostates as benign, missing eight diagnoses. Including parametric maps, 31/82 prostates appeared benign, missing three diagnoses. Sensitivity, specificity, PPV and NPV were 73, 58, 50 and 79%, respectively, for DCE-US alone and 91, 56, 57 and 90%, respectively, with parametric maps.\u3c/p\u3e\u3cp\u3eCONCLUSION: The interpretation of DCE-US with parametric maps allows good prediction of biopsy outcome. A two-thirds reduction in biopsy cores seems feasible with only a modest decrease in cancer diagnosis.\u3c/p\u3

3D contrast ultrasound dispersion imaging by mutual information for prostate cancer localization

Prostate cancer (PCa) is the most occurring type of cancer in the Western World. Yet, the most common diagnostic tool, systematic biopsy, is invasive and has low sensitivity. Recently, contrast-ultrasound dispersion imaging (CUDI) by spatiotemporal similarity analysis on contrast-enhanced ultrasound (CEUS) has been proposed as a promising, non-invasive alternative for PCa localization. It was shown that increased mutual information (MutI) between the indicator dilution curves in a block kernel and its central pixel relates to the presence of PCa. However, until now CUDI by MutI has been investigated in 2-D only, requiring a separate contrast injection for each imaging plane. Moreover, out-of-plane contrast flow could not be taken into account. In this work, we implemented CUDI by MutI using 4-D CEUS to overcome the aforementioned issues. We tested its feasibility to perform 3-D CUDI by comparison with 12-core systematic biopsies in 3 patients. The mean MutI for the patient with only one positive biopsy sample was significantly lower than that for the other two patients with more than 6 positive samples. This result encourages refinement and validation of the presented method in a larger patient group

3D surface-based registration of ultrasound and histology in prostate cancer imaging

\u3cp\u3eSeveral transrectal ultrasound (TRUS)-based techniques aiming at accurate localization of prostate cancer are emerging to improve diagnostics or to assist with focal therapy. However, precise validation prior to introduction into clinical practice is required. Histopathology after radical prostatectomy provides an excellent ground truth, but needs accurate registration with imaging. In this work, a 3D, surface-based, elastic registration method was developed to fuse TRUS images with histopathologic results. To maximize the applicability in clinical practice, no auxiliary sensors or dedicated hardware were used for the registration. The mean registration errors, measured in vitro and in vivo, were 1.5±0.2 and 2.1±0.5mm, respectively.\u3c/p\u3

4-D spatiotemporal analysis of ultrasound contrast agent dispersion for prostate cancer localization: a feasibility study

Currently, nonradical treatment for prostate cancer is hampered by the lack of reliable diagnostics. Contrastultrasound dispersion imaging (CUDI) has recently shown great potential as a prostate cancer imaging technique. CUDI estimates the local dispersion of intravenously injected contrast agents, imaged by transrectal dynamic contrast-enhanced ultrasound (DCE-US), to detect angiogenic processes related to tumor growth. The best CUDI results have so far been obtained by similarity analysis of the contrast kinetics in neighboring pixels. To date, CUDI has been investigated in 2-D only. In this paper, an implementation of 3-D CUDI based on spatiotemporal similarity analysis of 4-D DCE-US is described. Different from 2-D methods, 3-D CUDI permits analysis of the entire prostate using a single injection of contrast agent. To perform 3-D CUDI, a new strategy was designed to estimate the similarity in the contrast kinetics at each voxel, and data processing steps were adjusted to the characteristics of 4-D DCE-US images. The technical feasibility of 4-D DCE-US in 3-D CUDI was assessed and confirmed. Additionally, in a preliminary validation in two patients, dispersion maps by 3-D CUDI were quantitatively compared with those by 2-D CUDI and with 12-core systematic biopsies with promising result