Contrast-enhanced ultrasound with dispersion analysis for the localization of prostate cancer: correlation with radical prostatectomy specimens.

PURPOSE: To determine the value of two-dimensional (2D) contrast-enhanced ultrasound (CEUS) imaging and the additional value of contrast ultrasound dispersion imaging (CUDI) for the localization of clinically significant prostate cancer (csPCa). METHODS: In this multicentre study, subjects scheduled for a radical prostatectomy underwent 2D CEUS imaging preoperatively. CUDI maps were generated from the CEUS recordings. Both CEUS recordings and CUDI maps were scored on the likelihood of presenting csPCa (any Gleason ≥ 4 + 3 and Gleason 3 + 4 larger than 0.5 mL) by five observers and compared to radical prostatectomy histopathology. An automated three-dimensional (3D) fusion protocol was used to match imaging with histopathology. Receiver operator curve (ROC) analysis was performed per observer and imaging modality. RESULTS: 133 of 216 (62%) patients were included in the final analysis. Average area under the ROC for all five readers for CEUS, CUDI and the combination was 0.78, 0.79 and 0.78, respectively. This yields a sensitivity and specificity of 81 and 64% for CEUS, 83 and 56% for CUDI and 83 and 55% for the combination. Interobserver agreement for CEUS, CUDI and the combination showed kappa values of 0.20, 0.18 and 0.18 respectively. CONCLUSION: The sensitivity and specificity of 2D CEUS and CUDI for csPCa localization are moderate. Despite compressing CEUS in one image, CUDI showed a similar performance to 2D CEUS. With a sensitivity of 83% at cutoff point 3, it could become a useful imaging procedure, especially with 4D acquisition, improved quantification and combination with other US imaging techniques such as elastography.

3-D Quantitative Dynamic Contrast Ultrasound for Prostate Cancer Localization.

To investigate quantitative 3-D dynamic contrast-enhanced ultrasound (DCE-US) and, in particular 3-D contrast-ultrasound dispersion imaging (CUDI), for prostate cancer detection and localization, 43 patients referred for 10-12-core systematic biopsy underwent 3-D DCE-US. For each 3-D DCE-US recording, parametric maps of CUDI-based and perfusion-based parameters were computed. The parametric maps were divided in regions, each corresponding to a biopsy core. The obtained parameters were validated per biopsy location and after combining two or more adjacent regions. For CUDI by correlation (r) and for the wash-in time (WIT), a significant difference in parameter values between benign and malignant biopsy cores was found (p < 0.001). In a per-prostate analysis, sensitivity and specificity were 94% and 50% for r, and 53% and 81% for WIT. Based on these results, it can be concluded that quantitative 3-D DCE-US could aid in localizing prostate cancer. Therefore, we recommend follow-up studies to investigate its value for targeting biopsies.

Contrast-enhanced ultrasound tractography for 3D vascular imaging of the prostate.

Diffusion tensor tractography (DTT) enables visualization of fiber trajectories in soft tissue using magnetic resonance imaging. DTT exploits the anisotropic nature of water diffusion in fibrous structures to identify diffusion pathways by generating streamlines based on the principal diffusion vector. Anomalies in these pathways can be linked to neural deficits. In a different field, contrast-enhanced ultrasound is used to assess anomalies in blood flow with the aim of locating cancer-induced angiogenesis. Like water diffusion, blood flow and transport of contrast agents also shows a principal direction; however, this is now determined by the local vasculature. Here we show how the tractographic techniques developed for magnetic resonance imaging DTT can be translated to contrast-enhanced ultrasound, by first estimating contrast flow velocity fields from contrast-enhanced ultrasound acquisitions, and then applying tractography. We performed 4D in-vivo contrast-enhanced ultrasound of three human prostates, proving the feasibility of the proposed approach with clinically acquired datasets. By comparing the results to histopathology after prostate resection, we observed qualitative agreement between the contrast flow tracts and typical markers of cancer angiogenic microvasculature: higher densities and tortuous geometries in tumor areas. The method can be used in-vivo using a standard contrast-enhanced ultrasound protocol, opening up new possibilities in the area of vascular characterization for cancer diagnostics.

Contrast-Enhanced Ultrasound Angiogenesis Imaging by Mutual Information Analysis for Prostate Cancer Localization.

OBJECTIVE: The role of angiogenesis in cancer growth has stimulated research aimed at noninvasive cancer detection by blood perfusion imaging. Recently, contrast ultrasound dispersion imaging was proposed as an alternative method for angiogenesis imaging. After the intravenous injection of an ultrasound-contrast-agent bolus, dispersion can be indirectly estimated from the local similarity between neighboring time-intensity curves (TICs) measured by ultrasound imaging. Up until now, only linear similarity measures have been investigated. Motivated by the promising results of this approach in prostate cancer (PCa), we developed a novel dispersion estimation method based on mutual information, thus including nonlinear similarity, to further improve its ability to localize PCa. METHODS: First, a simulation study was performed to establish the theoretical link between dispersion and mutual information. Next, the method's ability to localize PCa was validated in vivo in 23 patients (58 datasets) referred for radical prostatectomy by comparison with histology. RESULTS: A monotonic relationship between dispersion and mutual information was demonstrated. The in vivo study resulted in a receiver operating characteristic (ROC) curve area equal to 0.77, which was superior (p = 0.21-0.24) to that obtained by linear similarity measures (0.74-0.75) and (p <; 0.05) to that by conventional perfusion parameters (≤0.70). CONCLUSION: Mutual information between neighboring time-intensity curves can be used to indirectly estimate contrast dispersion and can lead to more accurate PCa localization. SIGNIFICANCE: An improved PCa localization method can possibly lead to better grading and staging of tumors, and support focal-treatment guidance. Moreover, future employment of the method in other types of angiogenic cancer can be considered.

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

Several 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.

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 results.