Sg Stefan Schalk

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.

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.

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.

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.

Three-dimensional contrast-ultrasound dispersion imaging for prostate cancer localization, a feasibility study

Prostate cancer (PCa) is the type of cancer with the highest incidence in men in Western countries. To date, reliable tools for PCa localization are lacking. Recently, contrast-ultrasound dispersion imaging (CUDI) by spatiotemporal analysis performed on transrectal dynamic contrast-enhanced ultrasound (DCE-US) has been proposed as a promising option for PCa localization. This technique evaluates the spatial similarity between indicator dilution curves in a ring-shaped kernel and its center pixel. Until now, CUDI has been performed in 2D only. Hence, each imaged plane requires a separate bolus injection of contrast agent, motion compensation is limited, and out-of-plane contrast flow cannot be observed. 3D DCE-US can potentially solve the aforementioned issues, permitting the analysis of the entire prostate with a single bolus injection. In this work, we implemented a full 4D spatiotemporal similarity analysis. Its feasibility to localize PCa was evaluated in 2 patients by qualitatively comparing similarity maps obtained by 3D CUDI with those obtained by 2D CUDI in the corresponding planes and with histopathologic results from 12-core systematic biopsies. All results showed good agreement, confirming the feasibility of 3D CUDI for PCa localization and encouraging extension of the study to a larger dataset. Additionally, the characteristics - and in particular the spatial and temporal resolution - of 3D DCE-US were analyzed with respect to the requirements for CUDI. Both the spatial and temporal resolution were considered to be sufficient for CUDI.

3D registration of histology and ultrasound data for validation of prostate cancer imaging

Several ultrasound (US) prostate cancer localization methods are emerging, opening opportunities for targeted biopsies and focal therapy. However, before any of these methods, like elastography or contrast-enhanced US, can be introduced into clinical practice, accurate validation is required. The current gold standard for validation is histological assessment of the prostate after radical prostatectomy. Therefore, a 3D registration of histological and US data is required. This task is complicated by misalignment between histology slices and ultrasound imaging planes, pressure caused by the adopted transrectal US probe, and deformation and volume change during fixation in formalin solution. In this work, we introduce a dedicated 3D algorithm, automatically registering histology and ultrasound data. Because there is no information available between histology slices, and internal landmarks are not consistently present in US images, registration is based on outer-contours shape only. A 3D surface model of the prostate in constructed, based on manually outlined contours in a transrectal sweep video and a longitudinal image. Also, a similar model is constructed from the histology slices, including cancerous areas marked by a pathologist. Registration of the models is then performed in three steps: affine registration, elastic surface registration, and internal registration. In-vitro validation of the algorithm was performed by inserting rubber wires into four prostate mimicking phantoms and applying probe pressure. The resulting registration accuracy was 1.6 mm, which is considerably smaller than the histology slicing resolution of 4 mm.