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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., (Copyright © 2018 World Federation for Ultrasound in Medicine and Biology. Published by Elsevier Inc. All rights reserved.)

Objectives: The aim of this study is to improve the accuracy of dynamic contrast-enhanced ultrasound (DCE-US) for prostate cancer (PCa) localization by means of a multiparametric approach., Materials and Methods: Thirteen different parameters related to either perfusion or dispersion were extracted pixel-by-pixel from 45 DCE-US recordings in 19 patients referred for radical prostatectomy. Multiparametric maps were retrospectively produced using a Gaussian mixture model algorithm. These were subsequently evaluated on their pixel-wise performance in classifying 43 benign and 42 malignant histopathologically confirmed regions of interest, using a prostate-based leave-one-out procedure., Results: The combination of the spatiotemporal correlation (r), mean transit time (μ), curve skewness (κ), and peak time (PT) yielded an accuracy of 81% ± 11%, which was higher than the best performing single parameters: r (73%), μ (72%), and wash-in time (72%). The negative predictive value increased to 83% ± 16% from 70%, 69% and 67%, respectively. Pixel inclusion based on the confidence level boosted these measures to 90% with half of the pixels excluded, but without disregarding any prostate or region., Conclusions: Our results suggest multiparametric DCE-US analysis might be a useful diagnostic tool for PCa, possibly supporting future targeting of biopsies or therapy. Application in other types of cancer can also be foreseen., Key Points: • DCE-US can be used to extract both perfusion and dispersion-related parameters. • Multiparametric DCE-US performs better in detecting PCa than single-parametric DCE-US. • Multiparametric DCE-US might become a useful tool for PCa localization.

Prostate cancer care can benefit from accurate and cost-efficient imaging modalities that are able to reveal prognostic indicators for cancer. Angiogenesis is known to play a central role in the growth of tumors towards a metastatic or a lethal phenotype. With the aim of localizing angiogenic activity in a non-invasive manner, Dynamic Contrast Enhanced Ultrasound (DCE-US) has been widely used. Usually, the passage of ultrasound contrast agents thought the organ of interest is analyzed for the assessment of tissue perfusion. However, the heterogeneous nature of blood flow in angiogenic vasculature hampers the diagnostic effectiveness of perfusion parameters. In this regard, quantification of the heterogeneity of flow may provide a relevant additional feature for localizing angiogenesis. Statistics based on flow magnitude as well as its orientation can be exploited for this purpose. In this paper, we estimate the microbubble velocity fields from a standard bolus injection and provide a first statistical characterization by performing a spatial entropy analysis. By testing the method on 24 patients with biopsy-proven prostate cancer, we show that the proposed method can be applied effectively to clinically acquired DCE-US data. The method permits estimation of the in-plane flow vector fields and their local intricacy, and yields promising results (receiver-operating-characteristic curve area of 0.85) for the detection of prostate cancer.

Prostate cancer (PCa) is the second-leading cause of cancer death in men; however, reliable tools for detection and localization are still lacking. Dynamic Contrast Enhanced UltraSound (DCE-US) is a diagnostic tool that is suitable for analysis of vascularization, by imaging an intravenously injected microbubble bolus. The localization of angiogenic vascularization associated with the development of tumors is of particular interest. Recently, methods for the analysis of the bolus convective dispersion process have shown promise to localize angiogenesis. However, independent estimation of dispersion was not possible due to the ambiguity between convection and dispersion. Therefore, in this study we propose a new method that considers the vascular network as a dynamic linear system, whose impulse response can be locally identified. To this end, model-based parameter estimation is employed, that permits extraction of the apparent dispersion coefficient (D), velocity (v), and Péclet number (Pe) of the system. Clinical evaluation using data recorded from 25 patients shows that the proposed method can be applied effectively to DCE-US, and is able to locally characterize the hemodynamics, yielding promising results (receiver-operating-characteristic curve area of 0.84) for prostate cancer localization., (Copyright © 2016 Elsevier B.V. All rights reserved.)

We report on the first study demonstrating the ability of a recently-developed, contrast-enhanced, ultrasound imaging method, referred to as cumulative phase delay imaging (CPDI), to image and quantify ultrasound contrast agent (UCA) kinetics. Unlike standard ultrasound tomography, which exploits changes in speed of sound and attenuation, CPDI is based on a marker specific to UCAs, thus enabling dynamic contrast-specific ultrasound tomography (DCS-UST). For breast imaging, DCS-UST will lead to a more practical, faster, and less operator-dependent imaging procedure compared to standard echo-contrast, while preserving accurate imaging of contrast kinetics. Moreover, a linear relation between CPD values and ultrasound second-harmonic intensity was measured (coefficient of determination = 0.87). DCS-UST can find clinical applications as a diagnostic method for breast cancer localization, adding important features to multi-parametric ultrasound tomography of the breast.

Standard dynamic-contrast enhanced ultrasound (DCE-US) imaging detects and estimates ultrasound-contrast-agent (UCA) concentration based on the amplitude of the nonlinear (harmonic) components generated during ultrasound (US) propagation through UCAs. However, harmonic components generation is not specific to UCAs, as it also occurs for US propagating through tissue. Moreover, nonlinear artifacts affect standard DCE-US imaging, causing contrast to tissue ratio reduction, and resulting in possible misclassification of tissue and misinterpretation of UCA concentration. Furthermore, no contrast-specific modality exists for DCE-US tomography; in particular speed-of-sound changes due to UCAs are well within those caused by different tissue types. Recently, a new marker for UCAs has been introduced. A cumulative phase delay (CPD) between the second harmonic and fundamental component is in fact observable for US propagating through UCAs, and is absent in tissue. In this paper, tomographic US images based on CPD are for the first time presented and compared to speed-of-sound US tomography. Results show the applicability of this marker for contrast specific US imaging, with cumulative phase delay imaging (CPDI) showing superior capabilities in detecting and localizing UCA, as compared to speed-of-sound US tomography. Cavities (filled with UCA) which were down to 1 mm in diameter were clearly detectable. Moreover, CPDI is free of the above mentioned nonlinear artifacts. These results open important possibilities to DCE-US tomography, with potential applications to breast imaging for cancer localization.

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.

Numerous age-related pathologies affect the prostate gland, the most menacing of which is prostate cancer (PCa). The diagnostic tools for prostate investigation are invasive, requiring biopsies when PCa is suspected. Novel dynamic contrast-enhanced ultrasound (DCE-US) imaging approaches have been proposed recently and appear promising for minimally invasive localization of PCa. Ultrasound imaging of the prostate is traditionally performed with a transrectal probe because the location of the prostate allows for high-resolution images using high-frequency transducers. However, DCE-US imaging requires lower frequencies to induce bubble resonance and, thus, improve contrast-to-tissue ratio. For this reason, in this study we investigate the feasibility of quantitative DCE-US imaging of the prostate via the abdomen. The study included 10 patients (age = 60.7 ± 5.7 y) referred for a needle biopsy study. After having given informed consent, patients underwent DCE-US with both transabdominal and transrectal probes. Time-intensity contrast curves were derived using both approaches and their model-fit quality was compared. Although further improvements are expected by optimization of the transabdominal settings, the results of transabdominal and transrectal DCE-US are closely comparable, confirming the feasibility of transabdominal DCE-US; transabdominal curve fitting revealed an average determination coefficient r(2) = 0.91 (r(2) > 0.75 for 78.6% of all prostate pixels) compared with r(2) = 0.91 (r(2) > 0.75 for 81.6% of all prostate pixels) by the transrectal approach. Replacing the transrectal approach with more acceptable transabdominal scanning for prostate investigation is feasible. This approach would improve patient comfort and represent a useful option for PCa localization and monitoring., (Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.)