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Pregnancy complications are associated with insufficient adaptation of the maternal autonomic nervous system to the physiological demands of pregnancy. Consequently, assessing maternal heart rate variability (mHRV)—which reflects autonomic regulation—is a promising tool for detecting early deterioration in maternal health. However, before mHRV can be used to screen for complications, an understanding of the factors influencing mHRV during healthy pregnancy is needed. In this retrospective observational study, we develop regression models to unravel the effects of maternal demographics (age, body mass index (BMI), gestational age (GA), and parity), cardiorespiratory factors (heart rate and breathing rate), and inter-subject variation on mHRV. We develop these models using two datasets which are comprised of, respectively, single measurements in 290 healthy pregnant women and repeated measurements (median = 8) in 29 women with healthy pregnancies. Our most consequential finding is that between one-third and two-thirds of the variation in mHRV can be attributed to inter-subject variability. Additionally, median heart rate dominantly affects mHRV (p p

Although mechanical ventilation is a lifesaving intervention in the ICU, it has harmful side-effects, such as barotrauma and volutrauma. These harms can occur due to asynchronies. Asynchronies are defined as a mismatch between the ventilator timing and patient respiratory effort. Automatic detection of these asynchronies, and subsequent feedback, would improve lung ventilation and reduce the probability of lung damage. Neural networks to detect asynchronies provide a promising new approach but require large annotated data sets, which are difficult to obtain and require complex monitoring of inspiratory effort. In this work, we propose a model-based approach to generate a synthetic data set for machine learning and educational use by extending an existing lung model with a first-order ventilator model. The physiological nature of the derived lung model allows adaptation to various disease archetypes, resulting in a diverse data set. We generated a synthetic data set using 9 different patient archetypes, which are derived from measurements in the literature. The model and synthetic data quality have been verified by comparison with clinical data, review by a clinical expert, and an artificial intelligence model that was trained on experimental data. The evaluation showed it was possible to generate patient-ventilator waveforms including asynchronies that have the most important features of experimental patient-ventilator waveforms.

Despite showing promise, the sensitivity of contrast enhanced ultrasound (CEUS) for prostate cancer diagnosis is still limited. The introduction of novel microbubbles (MBs) targeted to the vascualar endhotelial growth receptor factor 2 has opened new possibilites for molecular imaging of prostate cancer. However, the detection rate in a phase-0 clinical trial was still limited to 65%. More effective contrast agents are needed to improve diagnostic accuracy. Recently, ultrasound nanobubbles (NBs) are emerging as promising agents for improved cancer diagnostics and therapy. Thanks to their reduced diameter, which is about 10 times smaller than MBs, they can cross the vascular endhotelium, providing greater possibilities for targeted imaging and therapy, including targets no longer limited to the vessel wall. In this context, a long-circulating NB targeted to the prostate-specific membrane antigent (PSMA) was recently developed, showing promise for selective accumulation in tumors expressing PSMA. In this work, we propose pharmacokinetic modeling of the kinetics of PSMA-targeted NBs by the simplified reference tissue model. While this model has been originially developed for receptor kinetic studies in nuclear medicine, it is here adapted for CEUS, enabling quantitative assessment of PSMA expression by estimation of the binding potential BP. The model is validated by comparing the estimated binding parameter obtained for three different US contrast agents (conventional MBs, non-targeted NBs, and PSMA-targeted NBs) in a dual tumor mouse model, carrying a PSMA-positive tumor in one flank, and a PSMA-negative tumor in the other flank.

Non-targeted transrectal-ultrasound-guided 12-core systematic biopsy (SBx) is the current guideline-recommended clinical pathway for prostate cancer (PCa) diagnosis, despite being associated with a risk of complications as well as un-derdiagnosis or overtreatment. Quantification algorithms for dynamic contrast-enhanced ultrasound (DCE-US) have shown good potential for PCa localisation in two dimensions (2D), and a few have recently been expanded to 3D. In this work, we present a 3D implementation of all estimators in the contrast ultrasound dispersion imaging (CUDI) family and exploit combinations of the extracted parameters to predict individual SBx-core outcomes. We show that machine-learning approaches can improve the classification performance compared to individual CUDI parameters and foresee potential for further development in image-based PCa localisation.

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Despite being the solid tumor with the highest incidence in western men, prostate cancer (PCa) still lacks reliable imaging solutions that can overcome the need for systematic biopsies. Dynamic Contrast-Enhanced Ultrasound Imaging (DCEUS) allows us to quantitatively characterize the vascular bed in the prostate, due to its ability to visualize an intravenously administered bolus of contrast agents. Previous research has demonstrated that DCE-US parameters related to the vascular architecture are useful markers for the localization of PCa lesions. In this work, we propose a novel method to assess the convective dispersion (D) and velocity (v) of the contrast bolus spreading through the prostate from three-dimensional (3D) DCE-US recordings. By assuming that D and v are locally constant, we solve the convective-dispersion equation by minimizing the corresponding regularized least-squares problem. 3D multiparametric maps of D and v were compared to 3D histopathology retrieved from the radical prostatectomy specimens of six patients. With a pixel-wise area under the Receiver Operating Characteristic curve of 0.72 and 0.80, respectively, the method shows diagnostic value for the localization of PCa.

Imaging technologies that allow assessment of the elastic properties of soft tissue provide clinicians with an important asset for several diagnostic applications. A quantitative measure of stiffness can be obtained by shear-wave (SW) elasticity imaging, a method that uses acoustic radiation force to produce laterally-propagating shear waves that can be tracked to obtain the velocity, which in turn is related to the shear modulus. If one considers the medium to be purely elastic, its local shear modulus can be estimated by determining the local SW velocity. However, this assumption does not hold for many tissue types, whenever the shear viscosity plays an important role. In fact, there is increasing evidence that viscosity itself could be an important marker for malignancy [1]. In this work, we therefore aim at providing a joint local estimate of tissue elasticity and viscosity based on SW elastography.

Super-resolution ultrasound enables detailed assessment of the fine vascular network by pinpointing individual microbubbles, using ultrasound contrast agents. The fidelity and achieved resolution of this technique is determined by the density of localized microbubbles and their localization accuracy. To obtain high densities, one can evaluate extremely sparse subsets of microbubbles across thousands of frames by using a very low microbubble dose and imaging for a very long time, which is impractical for clinical routine. While ultrafast imaging somewhat alleviates this problem, long acquisition times are still required to enhance the full vascular bed. As a result, localization accuracy remains hampered by patient motion. Recently, sparsity-based ultrasonic super resolution hemodynamic imaging was proposed, featuring a high spatial as well as temporal resolution by exploiting the temporal correlation structure of flowing microbubbles. However, when using clinical scanners operating at low framerates, this pixel-wise correlation across imaging frames may vanish. The aim of this work is hence twofold. First, to attain high microbubble localization accuracy on dense contrast-enhanced ultrasound data using a clinical dose of ultrasound contrast agents and a standard clinical scanner. Second, to retain a high resolution by adequate motion compensation.

Cancer growth and development requires angiogenesis, i.e., the formation of a blood supply to feed the tumor and enable metastatic spreading [1]. In cancer angiogenesis, pro-angiogenic factors are secreted to trigger the growth of new blood vessels and the recruitment of pre-existing vessels from surrounding tissue. The resulting vasculature is characterized by a chaotic network of abnormal micro-vessels exhibiting increased tortuosity and permeability, irregular diameters and branching, and arterio-venous shunting. This has led to a shift both in cancer diagnostics, whereby several in-vivo non-invasive imaging methods have been developed to assess the structural, functional, and molecular changes occurring due to cancer angiogenesis [2], and in cancer therapeutics, with the development of novel drugs aimed at inhibiting angiogenic processes and/or disrupting angiogenic tumor vasculature [3]

Introduction The recognition of the key role of angiogenesis for cancer growth has opened new frontiers in oncology1. In cancer therapy, the development of novel drugs aimed at blocking angiogenic processes has spurred the need for imaging biomarkers able to assess and predict the response to therapy. In response, targeted contrast agents have been developed providing selective enhancement in areas of active angiogenesis by binding to specific molecules over-expressed in angiogenic tumor vasculature. In the context of ultrasound molecular imaging (USMI), the first and currently only clinical-translatable targeted ultrasound contrast agent (tUCA) is obtained from conventional UCA by decoration of the microbubble shell with ligands targeting the vascular endothelial growth receptor factor 2 (VEGFR2), over-expressed in several solid tumors1. Assessment of the level of binding has been adopted as an indirect way of quantifying angiogenesis. Semi-quantitatively, this is done by looking at the late-enhancement (LE) several minutes after injection, often in conjunction with the application of a high-pressure US burst to derive the differential targeted enhancement (dTE), i.e., the difference in the acoustic signal before and after the application of the high-pressure burst1,2. For quantitative assessment, we recently proposed pharmacokinetic modeling of the binding kinetics of tUCA by the first-pass binding model (FPB), enabling quantification of angiogenesis by estimation of the microbubble binding rate (Kb)3. Here, we show the feasibility of the method for angiogenesis imaging in 11 rat models of prostate cancer, and for therapy monitoring of colorectal cancer in 17 mice undergoing anti-angiogenic treatment. Methods Time-intensity curves extracted at each pixel/voxel of USMI loops were fitted by the FPB model for estimation of the microbubble binding rate Kb. This was compared to semi-quantitative assessment by LE and dTE for: (i) angiogenesis imaging of prostate cancer by comparing parameter values in cancer and healthy regions of interest (ROIs) in 11 rats; (ii) anti-angiogenic therapy monitoring by comparing parameter values in responders, non-responders, and control mice at 5 time points during anti-angiogenic treatment. Results and Discussion Table I shows the differences in USMI parameters in healthy and tumor ROIs, obtained in 11 prostate-tumor bearing rats. Figure 1 shows the changes in USMI parameters during antiangiogenic treatment, obtained in 17 colorectal cancer-bearing mice. The results suggest the microbubble binding rate Kb to be a promising quantitative biomarker of angiogenesis, enabling the distinction between healthy and cancer tissue, and the early prediction of the response to anti-antiangiogenic therapy.

Objective measures to assess pulmonary circulation status would improve heart failure patient care. We propose a method for the characterization of the transpulmonary circulation by DCE-MRI. Parametric deconvolution was performed between contrast agent fifirst passage time-enhancement curves derived from the right and left ventricular blod pol. The transpulmonary circulation was characterized as a linear system with impulse response modelled as local density random walk model. We tested the method on 32 heart failure patients and 19 healthy volunteers; patients presented longer transpulmonary transit times and more skewed transpulmonary impulse responses.

The assessment of thoracic flfluid status is crucial for diagnosis, management, stratifification, and follow-up of heart failure patients. Indicator dilution theoretical framework allows absolute volume estimation; magnetic resonance contrast agents have been proposed as indicators, with the advantage of a non-invasive detection. In this pilot study, we investigated the changes in intra-thoracic blod volume (ITBV) measured by cardiac magnetic resonance during fluid shifts induced by a pneumatic leg compression device. Preliminary results on 8 healthy volunteers suggest the sensitivity of the proposed measurement technique; a signifificant increase in ITBV after the leg compression was observed.

Ultrasound imaging has found applications in several areas of interventional urology prior to treatment (diagnosis), after treatment (follow-up), and also during treatment (monitoring/guidance). Contrast-enhanced ultrasound (CEUS) imaging and elastographic imaging are the two widely used imaging techniques. CEUS modalities, such as harmonic and multi-pulse imaging, are increasingly applied in interventional urology, because the contrast agents give a clear enhancement of blood vessels in the tissue. Among others, CEUS is used to study the microvasculature of the prostate and kidney for cancer detection to more accurately identify malignant lesions. Elastography is a technique that has been coined in 1991 for the quantification of elastic properties of biological tissue. Various elastographic techniques have been developed, such as Acoustic radiation force imaging (ARFI) and shear wave elastography. These techniques have found various applications in interventional urology such as monitoring the degree of fibrosis in renal allografts after transplantation and the identification of renal masses and prostatic lesions.These enhanced ultrasound modalities represent novel techniques in the evaluation of the prostate and kidney in urology. There are multiple putative benefits of enhanced ultrasound modalities, including improved targeting for prostate biopsy; improved characterization of suspicious renal masses, especially when contrast-enhanced axial imaging (CT or MRI) are contraindicated; and lower cost than CT or MRI. Further investigations and refinements are necessary to define the role of these techniques in current urologic practice.

Higher microvascular density with tortuous and irregular vessels are hallmarks of cancer vasculature. These alterations can be captured by contrast ultrasound dispersion imaging (CUDI) and acoustic angiography (AA) at different scales: CUDI aims at obtaining an implicit measure of structural alteration by determining the dispersion kinetics of contrast agents. At a smaller scale, AA images the vascular architecture by detecting the high-frequency components generated with ultrasound contrast agents (UCA). This work shows the performance of these techniques by imaging cancerous and control regions in 3 rat xenograft models. Furthermore, it investigates the diagnostic value of the vascular features extracted using CUDI and AA with the aim to answer the question: does CUDI reveal changes in vascular tortuosity?

Prostate cancer (PCa) is the most common form of cancer among men in the US and the second most common cause of death. It has been observed that an increasing number of newly diagnosed patients exhibit low-risk features and that over-treatment with radical prostatectomy is a growing problem. The feasibility of focal therapy as an organsparing alternative, however, depends on the reliability of imaging techniques to identify, localize and monitor clinically relevant PCa lesions. The aim of this review is to investigate the potential of multiparametric ultrasound (mpUS) for focal therapy. We briefly introduce the most common focal therapies and thoroughly discuss the ability of available ultrasound modalities to localize PCa and reflect tissue properties. The imaging requirements of the focal therapies are studied to put the performance of the US techniques into perspective. We found that transrectal greyscale echography, Doppler sonography, elastography, contrast-enhanced ultrasonography and computerized ultrasound have been studied for the purpose of prostate imaging. Several of these modalities are already frequently used in current clinical practice; to add to the diagnostic process of PCa, to guide and monitor the application of focal therapy or to perform follow-up after treatment. Despite their capability to detect a large fraction of the PCa lesions, none of these modalities is currently considered sufficiently accurate for stand-alone tumour detection and localization. However, although there are only few studies reporting on a combined use of different ultrasound modalities, the results of an mpUS approach seem promising. Several US modalities have been successfully applied as a viable alternative to monitor tissue destruction during and after treatment. In view of the advantages of US and the promising results of a multiparametric approach in PCa detection and localization, researchers are urged to further investigate mpUS for therapeutic purposes

Objectives: Novel quantitative measures of the trans-pulmonary circulation status may allow improvement of heart failure (HF) patient management. In this work, we propose a method for the assessment of the trans-pulmonary circulation using measurements from indicator time-intensity curves, derived from dynamic contrast-enhanced magnetic resonance (DCE-MRI) image series. The derived indicator dilution parameters in healthy volunteers (HV) and HF patients were compared, and repeatability was assessed. Furthermore, we compared the parameters derived using the proposed method with standard measures of cardiovascular function (such as left ventricular volumes and ejection fraction).Materials and methodsIn all, 19 HVs and 33 HF patients underwent a DCE-MRI scan on a 1.5 T MRI scanner using a T1-weigthed spoiled gradient echo sequence. Image loops with one heart-beat temporal resolution were acquired in four-chamber view during ventricular late diastole, after the injection of a 0.1 mmol gadoteriol bolus. On a subset of the patients (8 HF, 2 HV), a second injection of a 0.3 mmol gadoteriol bolus was performed with same imaging settings. The study was approved by the local institutional review board. Indicator dilution curves (IDCs) were derived averaging the MR signal within regions of interest in the right and left ventricle; parametric deconvolution was performed between right and left ventricular (LV) IDCs to identify the impulse response of the trans-pulmonary dilution system. The local density random walk model was used to parametrize the impulse response; pulmonary transit time (PTT) was defined as the mean transit time of the indicator; λ, related to the Peclet number (ratio between convection and diffusion) for the dilution process, was also estimated. Results PTT was significantly prolonged in HF patients (8.70 ± 1.87 s vs. 6.68 ± 1.89 s in HV, p

OBJECTIVES: Prostate cancer (PCa) is the most common form of cancer among men in the US and the second most common cause of death. It has been observed that an increasing number of newly diagnosed patients exhibit low-risk features and that over-treatment with radical prostatectomy is a growing problem. The feasibility of focal therapy as an organsparing alternative, however, depends on the reliability of imaging techniques to identify, localize and monitor clinically relevant PCa lesions. The aim of this review is to investigate the potential of multiparametric ultrasound (mpUS) for focal therapy. METHODS: We briefly introduce the most common focal therapies and thoroughly discuss the ability of available ultrasound modalities to localize PCa and reflect tissue properties. The imaging requirements of the focal therapies are studied to put the performance of the US techniques into perspective. RESULTS: We found that transrectal greyscale echography, Doppler sonography, elastography, contrast-enhanced ultrasonography and computerized ultrasound have been studied for the purpose of prostate imaging. Several of these modalities are already frequently used in current clinical practice; to add to the diagnostic process of PCa, to guide and monitor the application of focal therapy or to perform follow-up after treatment. Despite their capability to detect a large fraction of the PCa lesions, none of these modalities is currently considered sufficiently accurate for stand-alone tumour detection and localization. However, although there are only few studies reporting on a combined use of different ultrasound modalities, the results of an mpUS approach seem promising. CONCLUSION: Several US modalities have been successfully applied as a viable alternative to monitor tissue destruction during and after treatment. In view of the advantages of US and the promising results of a multiparametric approach in PCa detection and localization, researchers are urged to further investigate mpUS for therapeutic purposes.

Resistance training (RT) is a widely accepted training option for improving neuromuscular performance. However, the high levels of load required in RT limit its applicability in rehabilitation programs. Vibration exercise (VE) is a relatively new and promising training modality, providing several important advantages over conventional strength training. To investigate the underlying mechanism elicited by VE, surface electromyography (EMG) has been widely used to measure the level of neuromuscular activity during VE. However, the EMG spectrum recorded during VE shows sharp peaks at the vibration frequency, whose interpretation (motion artifacts or muscle activity) remains controversial. The aim of the present study is to clarify the nature of the spectral peaks observed during VE. To this end, the conduction velocity of the vibration frequency component (CVVF) was estimated and compared with the CV of the entire EMG (CVEMG) and the acceleration signal (CVACC).

The main topic of this chapter is beamforming by multielement array transducers. After a short introduction on the various types of array transducers, the pressure beam profile is derived for both continuous wave and pulsed wave regimes. The main lobe as well as the side lobes and grating lobes are derived and their effects on image characteristics are discussed. Furthermore, the influence of apodization of the contribution of array elements on the overall beamforming is considered. The specific aspects of beam processing discussed are directional beam steering and the compounding of US (echographic) images. Compounding can be performed by superimposing images from slightly different insonation directions, or from sub-bands of the frequency spectrum of the received echoes. The effects of focusing on both transmission and reception are investigated. Reflection and backscattering contributions to echographic images are considered and the specific aspects of speckle formation by scattering are shown. The relation between spatial resolutions caused by beam characteristics are compared with speckle characteristics and related to image quality. Recent developments such as plane wave imaging and synthetic aperture imaging are outlined.

After a short introduction on generation and propagation of ultrasound waves, this chapter presents and discusses currently available and emerging ultrasound imaging modalities, such as standard modes in one, two, and three dimensions; Doppler and nonlinear imaging, including also the use of ultrasound contrast agents; and quantitative imaging, ranging from tissue characterization by analysis of speckle, strain, and elastic properties of tissue to perfusion imaging quantification. Emerging imaging modalities, such as molecular imaging (and treatment) by targeted agents and hybrid (photo- and magnetoacoustics) imaging, are also presented. Each technique is discussed with the aim of bridging basic principles with implementation and clinical application and relevance.

Poster

To expand applicability of pulse oximetry in low-acuity ambulatory settings, the impact of motion on extracted parameters as saturation (SpO2) and pulse rate (PR) needs to be reduced. We hypothesized that sensor motion relative to the skin can be used as an artifact reference in a correlation canceller to reduce motion artifacts in photoplethysmograms (PPGs), in order to improve SpO2 and PR measurements. This has been proven true in in vivo measurements, where forehead PPGs have been obtained while subjects are walking on a treadmill and relative sensor motion has been measured via self-mixing interferometry. By using relative motion in a normalized least mean square algorithm, the standard deviation of SpO2 and PR errors is on average reduced by 31 % and 13 %, respectively.

Poster

Despite the development of several efficient focal therapies for prostate cancer, treatment options are often restricted to radical treatments, such as a radical prostatectomy. One of the main obstacles preventing a wider application of focal therapies is the lack of reliable imaging methods for prostate cancer. Contrast-ultrasound dispersion imaging (CUDI) is a recently introduced method for detection and localization of prostate cancer, based on dynamic contrast-enhanced ultrasound (DCE-US) imaging. CUDI aims at localizing prostate cancer by detection of angiogenesis, i.e., the development of a chaotic dense microvascular network that has a proven correlation with prostate cancer aggressiveness. Key features of the microvascular structure, such as microvascular density and tortuosity, are characterized by the dispersion of ultrasound contrast agents (microbubbles) through the microcirculation. A twofold validation of CUDI is performed. The ability of CUDI to differentiate between different microvascular structures is evaluated in an animal study using two xenograft models of human prostate cancer that feature different microvascular structures. Furthermore, a preliminary clinical validation is performed to evaluate the value of CUDI for prostate cancer localization in humans.

Non-invasive pregnancy monitoring has become increasingly relevant in order to prevent complications. Fetal heart-rate (fHR) monitoring and estimation of uterine activity are important means to assess fetal health during pregnancy and delivery. Recent advances in signal processing technology enable pregnancy monitoring using abdominal electrocardiogram (ECG) and electrohysterogram (EHG) recordings [1], [2]. The large number of electrodes required in current noise-robust solutions, however, leads to high power consumption and reduced patient comfort, hampering unobtrusive ambulatory monitoring. To enable pregnancy monitoring in an ambulatory setting, the number of electrodes has to be reduced without compromising signal quality. Therefore, the influence of abdominal electrode positioning on the SNR of various signals of interest for pregnancy monitoring is explored based on measurements. Three measurements on women at full gestation just prior to labor (w39d4 ± 12d), with a total length of 1 hour, were performed using an electrode grid consisting of 12 electrodes. The electrodes are organized in a triangular fashion, which allows for analysis of the recorded signals in six different directions at three different inter-electrode scales, resulting in a total of 18 bi-polar signals for each measurement. To define the ability of all electrode pairs to capture the electrophysiological characteristics of interest, a signal quality criterion for both the fetal and maternal ECG as well as the EHG is defined based on the SNR. The SNR of both ECG signals is defined as the power of the QRS segment divided by the RMS power of the remaining signal. In case of the fetal ECG (fECG), the maternal ECG (mECG) was first removed using the method described in [1]. For the EHG, the signal and noise power are defined as the RMS signal in the 0.34 – 0.8 Hz frequency band in time segments during and in between contractions, respectively. Results show that the SNR of both the fetal and maternal ECG increasing with increase inter-electrode distance and are strongly dependent on measurement direction. In the case of mECG, a horizontal measurement orientation is preferred, while the optimal measurement direction for fECG changes depending on the orientation of the fetus with respect to the electrode grid. Contrary to the ECG, the SNR of the EHG shows an optimum for an electrode distance of 8 – 12 cm, while the optimal electrode orientation changes for every contraction. An electrode grid allowing for optimal detection of both ECG and EHG signals, therefore, should contain inter-electrode distances of both 8 and 16 cm with various orientations. According to our results, a triangular measurement setup with 6 electrodes, therefore, enables recording of mECG, fECG, and EHG signals with a SNR of 12.3 dB, 6.1 dB, and 9.8 dB, respectively.

Based on the established link between cancer growth and angiogenesis [2], in this work we propose a new method for assessment of tumor angiogenesis by dynamic contrast-enhanced magnetic resonance dispersion imaging and we investigate the feasibility of the method for prostate cancer localization.

This paper presents a low-power low-noise amplifier for neural recording applications. A single-stage current-reuse telescopic topology is proposed to achieve high DC gain and improve the noise efficiency factor (NEF) while allowing the amplifier to be scaled for high bandwidth sensing applications and/or to achieve lower thermal noise floor. The design is fabricated in a standard 0.18µm CMOS process and occupies an active area of 0.16mm2. Experimental measurements show a 430nW power consumption from a 1.2V supply, a thermal noise floor of 63.8nV/vHz and a corresponding NEF of 1.5.

Several ultrasound (US) methods for localization of PCa, like contrast-enhanced US imaging [1] and elastography [2], are emerging, but any of these methods need accurate validation prior to introduction into the clinic. The current gold standard for validation is histologic analysis of the prostate after excision, which requires accurate registration between histology slices and US images. This task is complicated by misalignment between histology and US data, as well as deformation of the prostate due to pressure from the transrectal US (TRUS) probe and to the fixation process after excision. Moreover, besides the prostate contours, no reliable landmarks are present in US. In this abstract, a solution to the validation issue is proposed by means of a dedicated 3D surface-based registration algorithm. To reconstruct the prostate shape, contours are manually drawn in a 2D TRUS transversal apex-to-base video. By correlating the mid area of the video with a sagittal image, the 3D location of the contours is estimated. In addition, a 3D reconstruction of the histology, including cancer location, is realized by aligning and interpolating 4-mm-thick prostate slices. From both prostate shapes, triangulated meshes are constructed. The two meshes are registered by a combination of an affine and an elastic transformation. Volumetric deformation is estimated by interpolation of the surface displacements without use of any internal landmark. Preliminary validation was performed by an in vitro experiment with four prostate-mimicking phantoms pierced by five elastic wires. The resulting average registration error was 1.6 mm, which is far below the histology slicing resolution of 4 mm. The method’s feasibility was tested in 12 human prostates for which we were able to overlay data from histopathologic analysis onto US imaging planes. In conclusion, the presented registration algorithm shows promising performance for accurate validation of US-based PCa imaging techniques. Future employment of the method for MRI validation or fusion can also be envisaged

The major role of angiogenesis in cancer development has driven many researchers to investigate the prospects of noninvasive cancer imaging based on assessment of microvascular perfusion. The limited results so far may be caused by the complex and contradictory effects of angiogenesis on perfusion. Alternatively, assessment of ultrasound contrast agent dispersion kinetics, resulting from features such as density and tortuosity, has shown a promising potential to characterize angiogenic effects on the microvascular structure. This method, referred to as contrast-ultrasound dispersion imaging (CUDI), is based on contrast-enhanced ultrasound imaging after an intravenous contrast agent bolus injection. In this paper, we propose a new spatiotemporal correlation analysis to perform CUDI. We provide the rationale for indirect estimation of local dispersion by deriving the analytical relation between dispersion and the correlation coefficient among neighboring time-intensity curves obtained at each pixel. This robust analysis is inherently normalized and does not require curve-fitting. In a preliminary validation of the method for localization of prostate cancer, the results of this analysis show superior cancer localization performance (receiver operating characteristic curve area of 0.89) compared with those of previously reported CUDI implementations and perfusion estimation methods.

Ultrasound is the cornerstone for prostatic imaging and covers diagnostics, therapy monitoring, and follow-up. In the aspect of focal therapy, accurate prostate cancer localization is mandatory. Contrast-enhanced ultrasound (CEUS) is a promising imaging technique which has shown to greatly increase the chances to find prostate cancer in biopsies. At the moment, CEUS is only performed in expert centers because of difficult interpretation and steep learning curves. CEUS quantification techniques can make reliable and objective interpretation, with a high sensitivity, possible outside of expert centers. Focal therapy and active surveillance are increasingly used, but require to be supported by proper imaging techniques. CEUS seems a promising technique for real-time monitoring and follow-up of focal therapy treatment. In the near future, the use of targeted contrast agents will be a major breakthrough in the combat against prostate cancer. They show promising results regarding better visualization and longer lasting contrast enhancement of prostate cancer in in-vitro as well as in in-vivo animal experiments.