Advanced ultrasound in prostate cancer care: Diagnostic and therapeutic possibilities

Prostate cancer is the most common solid tumor among western men. However, only recently has improving prostate cancer imaging capabilities initiated a transition towards image guided triage, biopsy procedures, therapies and follow-up. This thesis describes this transition, the role for MRI, and foremost: the development of advanced ultrasound for prostate cancer imaging. Contrast enhanced ultrasound allows the detection of microvascular changes associated with prostate cancer. Computer-aided parametric analysis can be employed to facilitate interpretation. The research in this thesis shows these techniques can be used to predict biopsy outcome, to actively target lesions in biopsy procedures and to localize tumors within the prostate using prostatectomy specimens as the reference standard. Furthermore, a 3D registration technique that facilitates matching pathology and imaging results is presented. Contrast enhanced ultrasound can be combined with other modalities such as b-mode and elastography into multiparametric ultrasound. The promise is improved discriminatory power although the available literature is scarce. Focal therapy is a treatment strategy in which only the prostate zone harboring the tumor is treated. The prospect is oncological control with reduced side effects. A Delphi-consensus project is conducted to achieve standardization in definitions and outcomes in focal therapy research. Lastly, this thesis describes the preliminary experience with ablation zone imaging following focal therapy using irreversible electroporation

Multiparametric dynamic contrast-enhanced ultrasound classification of prostate cancer

Although prostate cancer (PCa) is the most common non-cutaneous form of cancer among Western men, available diagnostic imaging methods are not yet sufficiently reliable to avoid systematic biopsy. In this work, we aim at improving the accuracy of transrectal dynamic contrast-enhanced ultrasonography (DCE-US) for PCa localization by combining local perfusion and dispersion parameters. To this end, ten of these parameters were extracted pixel-by-pixel from 45 DCE-US recordings distributed over 19 patients that were scheduled for radical prostatectomy. Based on 43 benign and 42 malignant histologically-confirmed regions of interest, we produced multiparametric maps using a Gaussian Mixture Model (GMM) algorithm. All possible combinations of one to four parameters were evaluated to select the most suitable subset of parameters. We also tested the GMM algorithm's ability to determine the classification confidence for each pixel and the impact of excluding low-confidence pixels from the images. An accuracy and negative predictive value of 81% and 83%, respectively, are obtained, which improved after pixel exclusion. Even though extended validation on a larger patient group is recommended, multiparametric DCE-US shows high potential in localizing PCa and might become an important tool for guiding targeted biopsy or planning of focal treatment

Multiparametric dynamic contrast-enhanced ultrasound imaging of prostate cancer

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

Entropy of ultrasound-contrast-agent velocity fields for angiogenesis imaging in prostate cancer

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 noninvasive manner, Dynamic Contrast Enhanced Ultrasound (DCEUS) 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 biopsyproven 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 (receiveroperating- characteristic curve area of 0.85) for the detection of prostate cancer

Transabdominal contrast-enhanced ultrasound imaging of the prostate

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 r2 = 0.91 (r2 > 0.75 for 78.6% of all prostate pixels) compared with r2 = 0.91 (r2 > 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. Key Words Prostate cancer; Contrast-enhanced ultrasound; Ultrasound contrast agents; Dilution curve; Transabdominal ultrasound; Transrectal ultrasound; Perfusio

PT162 - Multiparametric ultrasound for the diagnosis of prostate cancer: Greyscale, shearwave elastography and contrast-enhanced imaging in comparison with radical prostatectomy specimens

Introduction & Objectives: The diagnostic pathway for prostate cancer (PCa) is advancing towards an imaging-driven approach. The introduction of new ultrasound (US) modalities, such as quantitative contrast-enhanced US (CEUS), shear wave elastography (SWE) and the combination of different US modalities shows promise but a structured comparison with gold standard radical prostatectomy (RP) specimens is still lacking. The primary objective of this study is to determine the diagnostic performance of greyscale US (GS), SWE, CEUS and their combination, multiparametric US (mpUS) for the detection and localization of clinically significant (cs)PCa by comparison with corresponding RP histopathology

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 non-invasive 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 ultrasoundcontrast- 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 TICs 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