Publications by authors named "Hessel Wijkstra"

120 Publications

The challenge of prostate biopsy guidance in the era of mpMRI detected lesion: ultrasound-guided versus in-bore biopsy.

Br J Radiol 2021 Jul 29:20210363. Epub 2021 Jul 29.

Department of Urology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands.

The current recommendation in patients with a clinical suspicion for prostate cancer is to perform systematic biopsies extended with targeted biopsies, depending on mpMRI results. Following a positive mpMRI [i.e. Prostate Imaging Reporting and Data System (PI-RADS) ≥3], three targeted biopsy approaches can be performed: visual registration of the MRI images with real-time ultrasound imaging; software-assisted fusion of the MRI images and real-time ultrasound images, and in-bore biopsy within the MR scanner. This collaborative review discusses the advantages and disadvantages of each targeting approach and elaborates on future developments. Cancer detection rates seem to mostly depend on practitioner experience and selection criteria (biopsy naïve, previous negative biopsy, prostate-specific antigen (PSA) selection criteria, presence of a lesion on MRI), and to a lesser extent dependent on biopsy technique. There is no clear consensus on the optimal targeting approach. The choice of technique depends on local experience and availability of equipment, individual patient characteristics, and onsite cost-benefit analysis. Innovations in imaging techniques and software-based algorithms may lead to further improvements in this field.
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http://dx.doi.org/10.1259/bjr.20210363DOI Listing
July 2021

A review on B/A measurement methods with a clinical perspective.

J Acoust Soc Am 2021 04;149(4):2200

Electrical Engineering Department, Faculty of Electrical Engineering, Eindhoven University of Technology, Groene Loper 35612 AE, Eindhoven, The Netherlands.

The nonlinear parameter of ultrasound B/A has shown to be a useful diagnostic parameter, reflecting medium content, structure, and temperature. Despite its recognized values, B/A is not yet used as a diagnostic tool in the clinic due to the limitations of current measurement and imaging techniques. This review presents an extensive and comprehensive overview of the techniques developed for B/A measurement of liquid and liquid-like media (e.g., tissue), identifying the methods that are most promising from a clinical perspective. This work summarizes the progress made in the field and the typical challenges on the way to B/A estimation. Limitations and problems with the current techniques are identified, suggesting directions that may lead to further improvement. Since the basic theory of the physics behind the measurement strategies is presented, it is also suited for a reader who is new to nonlinear ultrasound.
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http://dx.doi.org/10.1121/10.0003627DOI Listing
April 2021

Blood flow patterns estimation in the left ventricle with low-rate 2D and 3D dynamic contrast-enhanced ultrasound.

Comput Methods Programs Biomed 2021 Jan 23;198:105810. Epub 2020 Oct 23.

Department of Electrical Engineering, Eindhoven University of Technology, Netherlands.

Background And Objective: Left ventricle (LV) dysfunction always occurs at early heart-failure stages, producing variations in the LV flow patterns. Cardiac diagnostics may therefore benefit from flow-pattern analysis. Several visualization tools have been proposed that require ultrafast ultrasound acquisitions. However, ultrafast ultrasound is not standard in clinical scanners. Meanwhile techniques that can handle low frame rates are still lacking. As a result, the clinical translation of these techniques remains limited, especially for 3D acquisitions where the volume rates are intrinsically low.

Methods: To overcome these limitations, we propose a novel technique for the estimation of LV blood velocity and relative-pressure fields from dynamic contrast-enhanced ultrasound (DCE-US) at low frame rates. Different from other methods, our method is based on the time-delays between time-intensity curves measured at neighbor pixels in the DCE-US loops. Using Navier-Stokes equation, we regularize the obtained velocity fields and derive relative-pressure estimates. Blood flow patterns were characterized with regard to their vorticity, relative-pressure changes (dp/dt) in the LV outflow tract, and viscous energy loss, as these reflect the ejection efficiency.

Results: We evaluated the proposed method on 18 patients (9 responders and 9 non-responders) who underwent cardiac resynchronization therapy (CRT). After CRT, the responder group evidenced a significant (p<0.05) increase in vorticity and peak dp/dt, and a non-significant decrease in viscous energy loss. No significant difference was found in the non-responder group. Relative feature variation before and after CRT evidenced a significant difference (p<0.05) between responders and non-responders for vorticity and peak dp/dt. Finally, the method feasibility is also shown with 3D DCE-US.

Conclusions: Using the proposed method, adequate visualization and quantification of blood flow patterns are successfully enabled based on low-rate DCE-US of the LV, facilitating the clinical adoption of the method using standard ultrasound scanners. The clinical value of the method in the context of CRT is also shown.
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http://dx.doi.org/10.1016/j.cmpb.2020.105810DOI Listing
January 2021

Super-Resolution Ultrasound Localization Microscopy Through Deep Learning.

IEEE Trans Med Imaging 2021 03 2;40(3):829-839. Epub 2021 Mar 2.

Ultrasound localization microscopy has enabled super-resolution vascular imaging through precise localization of individual ultrasound contrast agents (microbubbles) across numerous imaging frames. However, analysis of high-density regions with significant overlaps among the microbubble point spread responses yields high localization errors, constraining the technique to low-concentration conditions. As such, long acquisition times are required to sufficiently cover the vascular bed. In this work, we present a fast and precise method for obtaining super-resolution vascular images from high-density contrast-enhanced ultrasound imaging data. This method, which we term Deep Ultrasound Localization Microscopy (Deep-ULM), exploits modern deep learning strategies and employs a convolutional neural network to perform localization microscopy in dense scenarios, learning the nonlinear image-domain implications of overlapping RF signals originating from such sets of closely spaced microbubbles. Deep-ULM is trained effectively using realistic on-line synthesized data, enabling robust inference in-vivo under a wide variety of imaging conditions. We show that deep learning attains super-resolution with challenging contrast-agent densities, both in-silico as well as in-vivo. Deep-ULM is suitable for real-time applications, resolving about 70 high-resolution patches ( 128×128 pixels) per second on a standard PC. Exploiting GPU computation, this number increases to 1250 patches per second.
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http://dx.doi.org/10.1109/TMI.2020.3037790DOI Listing
March 2021

Detection of clinically significant prostate cancer in biopsy-naïve men: direct comparison of systematic biopsy, multiparametric MRI- and contrast-ultrasound-dispersion imaging-targeted biopsy.

BJU Int 2020 10 13;126(4):481-493. Epub 2020 May 13.

Department of Urology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands.

Objectives: To compare and evaluate a multiparametric magnetic resonance imaging (mpMRI)-targeted biopsy (TBx) strategy, contrast-ultrasound-dispersion imaging (CUDI)-TBx strategy and systematic biopsy (SBx) strategy for the detection of clinically significant prostate cancer (csPCa) in biopsy-naïve men.

Patients And Methods: A prospective, single-centre paired diagnostic study included 150 biopsy-naïve men, from November 2015 to November 2018. All men underwent pre-biopsy mpMRI and CUDI followed by a 12-core SBx taken by an operator blinded from the imaging results. Men with suspicious lesions on mpMRI and/or CUDI also underwent MRI-TRUS fusion-TBx and/or cognitive CUDI-TBx after SBx by a second operator. A non-inferiority analysis of the mpMRI- and CUDI-TBx strategies in comparison with SBx for International Society of Urological Pathology Grade Group [GG] ≥2 PCa in any core with a non-inferiority margin of 1 percentage point was performed. Additional analyses for GG ≥2 PCa with cribriform growth pattern and/or intraductal carcinoma (CR/IDC), and GG ≥3 PCa were performed. Differences in detection rates were tested using McNemar's test with adjusted Wald confidence intervals.

Results: After enrolment of 150 men, an interim analysis was performed. Both the mpMRI- and CUDI-TBx strategies were inferior to SBx for GG ≥2 PCa detection and the study was stopped. SBx found significantly more GG ≥2 PCa: 39% (56/142), as compared with 29% (41/142) and 28% (40/142) for mpMRI-TBx and CUDI-TBx, respectively (P < 0.05). SBx found significantly more GG = 1 PCa: 14% (20/142) compared to 1% (two of 142) and 3% (four of 142) with mpMRI-TBx and CUDI-TBx, respectively (P < 0.05). Detection of GG ≥2 PCa with CR/IDC and GG ≥3 PCa did not differ significantly between the strategies. The mpMRI- and CUDI-TBx strategies were comparable in detection but the mpMRI-TBx strategy had less false-positive findings (18% vs 53%).

Conclusions: In our study in biopsy-naïve men, the mpMRI- and CUDI-TBx strategies had comparable PCa detection rates, but the mpMRI-TBX strategy had the least false-positive findings. Both strategies were inferior to SBx for the detection of GG ≥2 PCa, despite reduced detection of insignificant GG = 1 PCa. Both strategies did not significantly differ from SBx for the detection of GG ≥2 PCa with CR/IDC and GG ≥3 PCa.
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http://dx.doi.org/10.1111/bju.15093DOI Listing
October 2020

Cancer Detection Rates of Systematic and Targeted Prostate Biopsies after Biparametric MRI.

Prostate Cancer 2020 3;2020:4626781. Epub 2020 Apr 3.

Department of Electrical Engineering, Eindhoven University of Technology, De Rondom 70, 5612 AP, Eindhoven, Netherlands.

Objective: To compare prostate cancer detection rates (CDRs) and pathology results with targeted prostate biopsy (TB) and systematic prostate biopsy (SB) in biopsy-naive men.

Methods: An in-patient control study of 82 men undergoing SB and subsequent TB in case of positive prostate MRI between 2015 and 2017 in the Jeroen Bosch Hospital, the Netherlands.

Results: Prostate cancer (PCa) was detected in 54.9% with 70.7% agreement between TB and SB. Significant PCa (Gleason score ≥7) was detected in 24.4%. The CDR with TB and SB was 35.4% and 48.8%, respectively (=0.052). The CDR of significant prostate cancer with TB and SB was both 20.7%. Clinically significant pathology upgrading occurred in 7.3% by adding TB to SB and 22.0% by adding SB to TB.

Conclusions: There is no statistically significant difference between CDRs of SB and TB. Both SB and TB miss significant PCas. Moreover, pathology upgrading occurred more often by adding SB to TB than vice versa. This indicates that the omission of SB in this study population might not be justified.
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http://dx.doi.org/10.1155/2020/4626781DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7157788PMC
April 2020

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

World J Urol 2020 Nov 20;38(11):2811-2818. Epub 2020 Feb 20.

Department of Urology, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands.

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.
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http://dx.doi.org/10.1007/s00345-020-03103-4DOI Listing
November 2020

Artificial intelligence in multiparametric prostate cancer imaging with focus on deep-learning methods.

Comput Methods Programs Biomed 2020 Jun 7;189:105316. Epub 2020 Jan 7.

Lab of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, De Zaale, 5600 MB, Eindhoven, the Netherlands.

Prostate cancer represents today the most typical example of a pathology whose diagnosis requires multiparametric imaging, a strategy where multiple imaging techniques are combined to reach an acceptable diagnostic performance. However, the reviewing, weighing and coupling of multiple images not only places additional burden on the radiologist, it also complicates the reviewing process. Prostate cancer imaging has therefore been an important target for the development of computer-aided diagnostic (CAD) tools. In this survey, we discuss the advances in CAD for prostate cancer over the last decades with special attention to the deep-learning techniques that have been designed in the last few years. Moreover, we elaborate and compare the methods employed to deliver the CAD output to the operator for further medical decision making.
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http://dx.doi.org/10.1016/j.cmpb.2020.105316DOI Listing
June 2020

Contrast-Enhanced Ultrasound Quantification: From Kinetic Modeling to Machine Learning.

Ultrasound Med Biol 2020 03 8;46(3):518-543. Epub 2020 Jan 8.

Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.

Ultrasound contrast agents (UCAs) have opened up immense diagnostic possibilities by combined use of indicator dilution principles and dynamic contrast-enhanced ultrasound (DCE-US) imaging. UCAs are microbubbles encapsulated in a biocompatible shell. With a rheology comparable to that of red blood cells, UCAs provide an intravascular indicator for functional imaging of the (micro)vasculature by quantitative DCE-US. Several models of the UCA intravascular kinetics have been proposed to provide functional quantitative maps, aiding diagnosis of different pathological conditions. This article is a comprehensive review of the available methods for quantitative DCE-US imaging based on temporal, spatial and spatiotemporal analysis of the UCA kinetics. The recent introduction of novel UCAs that are targeted to specific vascular receptors has advanced DCE-US to a molecular imaging modality. In parallel, new kinetic models of increased complexity have been developed. The extraction of multiple quantitative maps, reflecting complementary variables of the underlying physiological processes, requires an integrative approach to their interpretation. A probabilistic framework based on emerging machine-learning methods represents nowadays the ultimate approach, improving the diagnostic accuracy of DCE-US imaging by optimal combination of the extracted complementary information. The current value and future perspective of all these advances are critically discussed.
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http://dx.doi.org/10.1016/j.ultrasmedbio.2019.11.008DOI Listing
March 2020

Automated multiparametric localization of prostate cancer based on B-mode, shear-wave elastography, and contrast-enhanced ultrasound radiomics.

Eur Radiol 2020 Feb 10;30(2):806-815. Epub 2019 Oct 10.

Lab of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, De Rondom 70, 5612 AP, Eindhoven, The Netherlands.

Objectives: The aim of this study was to assess the potential of machine learning based on B-mode, shear-wave elastography (SWE), and dynamic contrast-enhanced ultrasound (DCE-US) radiomics for the localization of prostate cancer (PCa) lesions using transrectal ultrasound.

Methods: This study was approved by the institutional review board and comprised 50 men with biopsy-confirmed PCa that were referred for radical prostatectomy. Prior to surgery, patients received transrectal ultrasound (TRUS), SWE, and DCE-US for three imaging planes. The images were automatically segmented and registered. First, model-based features related to contrast perfusion and dispersion were extracted from the DCE-US videos. Subsequently, radiomics were retrieved from all modalities. Machine learning was applied through a random forest classification algorithm, using the co-registered histopathology from the radical prostatectomy specimens as a reference to draw benign and malignant regions of interest. To avoid overfitting, the performance of the multiparametric classifier was assessed through leave-one-patient-out cross-validation.

Results: The multiparametric classifier reached a region-wise area under the receiver operating characteristics curve (ROC-AUC) of 0.75 and 0.90 for PCa and Gleason > 3 + 4 significant PCa, respectively, thereby outperforming the best-performing single parameter (i.e., contrast velocity) yielding ROC-AUCs of 0.69 and 0.76, respectively. Machine learning revealed that combinations between perfusion-, dispersion-, and elasticity-related features were favored.

Conclusions: In this paper, technical feasibility of multiparametric machine learning to improve upon single US modalities for the localization of PCa has been demonstrated. Extended datasets for training and testing may establish the clinical value of automatic multiparametric US classification in the early diagnosis of PCa.

Key Points: • Combination of B-mode ultrasound, shear-wave elastography, and contrast ultrasound radiomics through machine learning is technically feasible. • Multiparametric ultrasound demonstrated a higher prostate cancer localization ability than single ultrasound modalities. • Computer-aided multiparametric ultrasound could help clinicians in biopsy targeting.
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http://dx.doi.org/10.1007/s00330-019-06436-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6957554PMC
February 2020

Reply by Authors.

J Urol 2019 12 30;202(6):1172-1173. Epub 2019 Aug 30.

Prostate Cancer Center, Martini-Klinik Hamburg, University Hospital Hamburg-Eppendorf, Hamburg, Germany.

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http://dx.doi.org/10.1097/01.JU.0000581796.73447.deDOI Listing
December 2019

3-D Multi-parametric Contrast-Enhanced Ultrasound for the Prediction of Prostate Cancer.

Ultrasound Med Biol 2019 10 10;45(10):2713-2724. Epub 2019 Jul 10.

Lab of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.

Trans-rectal ultrasound-guided 12-core systematic biopsy (SBx) is the standard diagnostic pathway for prostate cancer (PCa) because of a lack of sufficiently accurate imaging. Quantification of 3-D dynamic contrast-enhanced ultrasound (US) might open the way for a targeted procedure in which biopsies are directed at lesions suspicious on imaging. This work describes the expansion of contrast US dispersion imaging algorithms to 3-D and compares its performance against malignant and benign disease. Furthermore, we examined the feasibility of a multi-parametric approach to predict SBx-core outcomes using machine learning. An area under the receiver operating characteristic (ROC) curve of 0.76 and 0.81 was obtained for all PCa and significant PCa, respectively, an improvement over previous US methods. We found that prostatitis, in particular, was a source of false-positive readings.
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http://dx.doi.org/10.1016/j.ultrasmedbio.2019.05.017DOI Listing
October 2019

Validation of the Electronic Version of the International Index of Erectile Function (IIEF-5 and IIEF-15): A Crossover Study.

J Med Internet Res 2019 07 2;21(7):e13490. Epub 2019 Jul 2.

Department of Urology, Amsterdam University Medical Centers, Location Amsterdam Medical Center, University of Amsterdam, Amsterdam, Netherlands.

Background: Patient-reported outcome measures (PROMs) are increasingly used to measure patient's perspective of functional well-being, disease burden, treatment effectiveness, and clinical decision making. Electronic versions are increasingly feasible because of smartphone and tablet usage. However, validation of these electronic PROMs (ePROMs) is warranted for justified implementation. The International Index of Erectile Function (IIEF) 5 and 15 are widely used PROMs in urology to measure erectile dysfunction. Measurement reliability and validity testing of the IIEF ePROMs are essential before clinical application.

Objective: The aim of this study was to assess reliability and validity of an ePROM version of both IIEF-5 and 15.

Methods: This study included 179 patients from our urology outpatient clinic. It also had a randomized crossover design-participants completed either a paper and electronic IIEF-5 or 15 or twice completed an electronic version-with a 5-day delay. Internal consistency was assessed using Cronbach alpha and Spearman-Brown coefficient, test-retest reliability using the intraclass correlation coefficient (ICC), and convergent validity using the Pearson and Spearman correlation coefficient.

Results: A total of 122 participants completed the study. Internal consistency was excellent for the electronic IIEF-5 (ICC 0.902) and good to excellent for the domains of the IIEF-15 (ICC 0.962-0.834). Test-retest reliability was excellent for the IIEF-5 (ICC 0.924) and good to excellent for the domains of the IIEF-15 (ICC 0.950-0.778). Convergent validity was excellent for the IIEF-5 and IIEF-15, with a correlation of r=0.923 and r=0.951, respectively.

Conclusions: We successfully introduced patient-acceptable ePROM versions of the IIEF-5 and IIEF-15. This study's results demonstrate that the ePROM versions of the IIEF-5 and IIEF-15 can be reliably implemented, as outcomes are reliable and in accordance with findings of the paper version.

Trial Registration: ClinicalTrials.gov NCT03222388; https://clinicaltrials.gov/ct2/show/NCT03222388.
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http://dx.doi.org/10.2196/13490DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6634948PMC
July 2019

Exploiting Flow Dynamics for Superresolution in Contrast-Enhanced Ultrasound.

IEEE Trans Ultrason Ferroelectr Freq Control 2019 10 1;66(10):1573-1586. Epub 2019 Jul 1.

Ultrasound (US) localization microscopy offers new radiation-free diagnostic tools for vascular imaging deep within the tissue. Sequential localization of echoes returned from inert microbubbles (MBs) with low concentration within the bloodstream reveals the vasculature with capillary resolution. Despite its high spatial resolution, low MB concentrations dictate the acquisition of tens of thousands of images, over the course of several seconds to tens of seconds, to produce a single superresolved image. Such long acquisition times and stringent constraints on MB concentration are undesirable in many clinical scenarios. To address these restrictions, sparsity-based approaches have recently been developed. These methods reduce the total acquisition time dramatically, while maintaining good spatial resolution in settings with considerable MB overlap. Here, we further improve the spatial resolution and visual vascular reconstruction quality of sparsity-based superresolution US imaging from low-frame rate acquisitions, by exploiting the inherent flow of MBs and utilize their motion kinematics. We also provide quantitative measurements of MB velocities and show that our approach achieves higher MB recall rate than the state-of-the-art techniques, while increasing contrast agents concentration. Our method relies on simultaneous tracking and sparsity-based detection of individual MBs in a frame-by-frame manner, and as such, may be suitable for real-time implementation. The effectiveness of the proposed approach is demonstrated on both simulations and an in vivo contrast-enhanced human prostate scan, acquired with a clinically approved scanner operating at a 10-Hz frame rate.
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http://dx.doi.org/10.1109/TUFFC.2019.2926062DOI Listing
October 2019

Multiparametric Ultrasound for Prostate Cancer Detection and Localization: Correlation of B-mode, Shear Wave Elastography and Contrast Enhanced Ultrasound with Radical Prostatectomy Specimens.

J Urol 2019 12 27;202(6):1166-1173. Epub 2019 Jun 27.

Prostate Cancer Center, Martini-Klinik Hamburg, University Hospital Hamburg-Eppendorf, Hamburg, Germany.

Purpose: Similar to multiparametric magnetic resonance imaging, multiparametric ultrasound represents a promising approach to prostate cancer imaging. We determined the diagnostic performance of B-mode, shear wave elastography and contrast enhanced ultrasound with quantification software as well as the combination, multiparametric ultrasound, for clinically significant prostate cancer localization using radical prostatectomy histopathology as the reference standard.

Materials And Methods: From May 2017 to July 2017, 50 men with biopsy proven prostate cancer underwent multiparametric ultrasound before radical prostatectomy at 1 center. Three readers independently evaluated 12 anatomical regions of interest for the likelihood of clinically significant prostate cancer on a 5-point Likert scale for all separate ultrasound modalities and multiparametric ultrasound. A logistic linear mixed model was used to estimate diagnostic performance for the localization of clinically significant prostate cancer (any tumor with Gleason score 3 + 4 = 7 or greater, tumor volume 0.5 ml or greater, extraprostatic extension or stage pN1) using a Likert score of 3 or greater and 4 or greater as the threshold. To detect the index lesion the readers selected the 2 most suspicious regions of interest.

Results: A total of 48 men were included in the final analysis. The region of interest specific sensitivity of multiparametric ultrasound (Likert 3 or greater) for clinically significant prostate cancer was 74% (95% CI 67-80) compared to 55% (95% CI 47-63), 55% (95% CI 47-63) and 59% (95% CI 51-67) for B-mode, shear wave elastography and contrast enhanced ultrasound, respectively. Multiparametric ultrasound sensitivity was significantly higher for Likert thresholds and all different clinically significant prostate cancer definitions (all p <0.05). Multiparametric ultrasound improved the detection of index lesion prostate cancer.

Conclusions: Multiparametric ultrasound of the prostate, consisting of B-mode, shear wave elastography and contrast enhanced ultrasound with parametric maps, improved localization and index lesion detection of clinically significant prostate cancer compared to single ultrasound modalities, yielding good sensitivity.
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http://dx.doi.org/10.1097/JU.0000000000000415DOI Listing
December 2019

Prostate Cancer Risk Assessment in Biopsy-naïve Patients: The Rotterdam Prostate Cancer Risk Calculator in Multiparametric Magnetic Resonance Imaging-Transrectal Ultrasound (TRUS) Fusion Biopsy and Systematic TRUS Biopsy.

Eur Urol Oncol 2018 06 15;1(2):109-117. Epub 2018 May 15.

Department of Radiology, Jeroen Bosch Hospital, 's-Hertogenbosch, The Netherlands.

Background: The value of multiparametric magnetic resonance imaging (mpMRI) and targeted biopsy (TBx) remains controversial for biopsy-naïve men when compared to transrectal ultrasound (TRUS)-guided systematic biopsy (SBx). Risk-based patient selection could help to selectively identify men with significant prostate cancer (PCa) and thus reduce unnecessary mpMRI and biopsies.

Objectives: To compare PCa detection rates for mpMRI TBx with SBx and to determine the rate of potentially avoided mpMRI and biopsies through risk-based selection using the Rotterdam Prostate Cancer Risk Calculator (RPCRC).

Design, Setting, And Participants: Two-hundred consecutive biopsy-naïve men in two centres underwent mpMRI scanning, 12-core SBx, and subsequent MRI-TRUS TBx in the case of suspicious lesion(s) (Prostate Imaging-Reporting and Data System v.2 score ≥3).

Outcome Measurements And Statistical Analysis: We measured the detection rate for high-grade (Gleason score ≥ 3+4) PCa for TBx and SBx. We carried out a retrospective stratification according to RPCRC biopsy advice to determine the rate of mpMRI and biopsies that could potentially be avoided by RPCRC-based patient selection in relation to the rate of high-grade PCa missed.

Results And Limitations: TBx yielded high-grade PCa in 51 men (26%) and low-grade PCa in 14 men (7%), while SBx yielded high-grade PCa in 63 men (32%) and low-grade PCa in 41 men (21%). Four out of 73 men (5%) with negative RPCRC advice and 63 out of 127 men (50%) with positive advice had high-grade PCa. Upfront RPCRC-based patient selection for mpMRI and TBx would have avoided 73 out of 200 (37%) mpMRI scans, missing two out of 51 (4%) high-grade PCas. Limitations include the RPCRC definition of high- and low-grade PCa and different mpMRI techniques.

Conclusions: mpMRI with TBx detected PCa with high Gleason score and avoided biopsy in low-grade PCa, but failed to detect all high-grade PCa when compared to SBx among biopsy-naïve men. Risk-based patient selection using the RPCRC can avoid one-third of mpMRI scans and SBx in biopsy-naïve men.

Patient Summary: Men with a suspicion of prostate cancer are increasingly undergoing a magnetic resonance imaging (MRI) scan. Although promising, MRI-targeted biopsy is not accurate enough to safely replace systematic prostate biopsy for now. Individualised assessment of prostate cancer risk using the Rotterdam Prostate Cancer Risk Calculator could avoid one-third of MRI scans and systematic prostate biopsies.
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http://dx.doi.org/10.1016/j.euo.2018.02.010DOI Listing
June 2018

Super-Resolution Contrast-Enhanced Ultrasound Methodology for the Identification of In Vivo Vascular Dynamics in 2D.

Invest Radiol 2019 08;54(8):500-516

From the Institute of Biochemistry, Biological Physics, and Bio Engineering, and.

Objectives: The aim of this study was to provide an ultrasound-based super-resolution methodology that can be implemented using clinical 2-dimensional ultrasound equipment and standard contrast-enhanced ultrasound modes. In addition, the aim is to achieve this for true-to-life patient imaging conditions, including realistic examination times of a few minutes and adequate image penetration depths that can be used to scan entire organs without sacrificing current super-resolution ultrasound imaging performance.

Methods: Standard contrast-enhanced ultrasound was used along with bolus or infusion injections of SonoVue (Bracco, Geneva, Switzerland) microbubble (MB) suspensions. An image analysis methodology, translated from light microscopy algorithms, was developed for use with ultrasound contrast imaging video data. New features that are tailored for ultrasound contrast image data were developed for MB detection and segmentation, so that the algorithm can deal with single and overlapping MBs. The method was tested initially on synthetic data, then with a simple microvessel phantom, and then with in vivo ultrasound contrast video loops from sheep ovaries. Tracks detailing the vascular structure and corresponding velocity map of the sheep ovary were reconstructed. Images acquired from light microscopy, optical projection tomography, and optical coherence tomography were compared with the vasculature network that was revealed in the ultrasound contrast data. The final method was applied to clinical prostate data as a proof of principle.

Results: Features of the ovary identified in optical modalities mentioned previously were also identified in the ultrasound super-resolution density maps. Follicular areas, follicle wall, vessel diameter, and tissue dimensions were very similar. An approximately 8.5-fold resolution gain was demonstrated in vessel width, as vessels of width down to 60 μm were detected and verified (λ = 514 μm). Best agreement was found between ultrasound measurements and optical coherence tomography with 10% difference in the measured vessel widths, whereas ex vivo microscopy measurements were significantly lower by 43% on average. The results were mostly achieved using video loops of under 2-minute duration that included respiratory motion. A feasibility study on a human prostate showed good agreement between density and velocity ultrasound maps with the histological evaluation of the location of a tumor.

Conclusions: The feasibility of a 2-dimensional contrast-enhanced ultrasound-based super-resolution method was demonstrated using in vitro, synthetic and in vivo animal data. The method reduces the examination times to a few minutes using state-of-the-art ultrasound equipment and can provide super-resolution maps for an entire prostate with similar resolution to that achieved in other studies.
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http://dx.doi.org/10.1097/RLI.0000000000000565DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6661242PMC
August 2019

Deep Learning for Real-time, Automatic, and Scanner-adapted Prostate (Zone) Segmentation of Transrectal Ultrasound, for Example, Magnetic Resonance Imaging-transrectal Ultrasound Fusion Prostate Biopsy.

Eur Urol Focus 2021 Jan 23;7(1):78-85. Epub 2019 Apr 23.

Laboratory of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.

Background: Although recent advances in multiparametric magnetic resonance imaging (MRI) led to an increase in MRI-transrectal ultrasound (TRUS) fusion prostate biopsies, these are time consuming, laborious, and costly. Introduction of deep-learning approach would improve prostate segmentation.

Objective: To exploit deep learning to perform automatic, real-time prostate (zone) segmentation on TRUS images from different scanners.

Design, Setting, And Participants: Three datasets with TRUS images were collected at different institutions, using an iU22 (Philips Healthcare, Bothell, WA, USA), a Pro Focus 2202a (BK Medical), and an Aixplorer (SuperSonic Imagine, Aix-en-Provence, France) ultrasound scanner. The datasets contained 436 images from 181 men.

Outcome Measurements And Statistical Analysis: Manual delineations from an expert panel were used as ground truth. The (zonal) segmentation performance was evaluated in terms of the pixel-wise accuracy, Jaccard index, and Hausdorff distance.

Results And Limitations: The developed deep-learning approach was demonstrated to significantly improve prostate segmentation compared with a conventional automated technique, reaching median accuracy of 98% (95% confidence interval 95-99%), a Jaccard index of 0.93 (0.80-0.96), and a Hausdorff distance of 3.0 (1.3-8.7) mm. Zonal segmentation yielded pixel-wise accuracy of 97% (95-99%) and 98% (96-99%) for the peripheral and transition zones, respectively. Supervised domain adaptation resulted in retainment of high performance when applied to images from different ultrasound scanners (p > 0.05). Moreover, the algorithm's assessment of its own segmentation performance showed a strong correlation with the actual segmentation performance (Pearson's correlation 0.72, p < 0.001), indicating that possible incorrect segmentations can be identified swiftly.

Conclusions: Fusion-guided prostate biopsies, targeting suspicious lesions on MRI using TRUS are increasingly performed. The requirement for (semi)manual prostate delineation places a substantial burden on clinicians. Deep learning provides a means for fast and accurate (zonal) prostate segmentation of TRUS images that translates to different scanners.

Patient Summary: Artificial intelligence for automatic delineation of the prostate on ultrasound was shown to be reliable and applicable to different scanners. This method can, for example, be applied to speed up, and possibly improve, guided prostate biopsies using magnetic resonance imaging-transrectal ultrasound fusion.
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http://dx.doi.org/10.1016/j.euf.2019.04.009DOI Listing
January 2021

Three-dimensional greyscale transrectal ultrasound-guidance and biopsy core preembedding for detection of prostate cancer: Dutch clinical cohort study.

BMC Urol 2019 Apr 16;19(1):23. Epub 2019 Apr 16.

Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.

Background: To overcome the limitations regarding two dimensional (2D) greyscale (GS) transrectal ultrasound (TRUS)-guided biopsy in prostate cancer (PCa) detection and tissue packaging in biopsy processing, there is an ongoing focus on new imaging and pathology techniques. A three-dimensional (3D) model of the prostate with biopsy needle guidance can be generate by the Navigo™ workstation (UC-care, Israel). The SmartBX™ system (UC-care, Israel) provides a prostate biopsy core preembedding method. The aim of this study was to compare cancer detection rates between the 3D TRUS-guidance and preembedding method with conventional 2D GS TRUS-guidance among patients undergoing prostate biopsies.

Methods: We retrospectively analyzed the records of all patients who underwent prostate biopsies for PCa detection at our institution from 2007 to 2016. The cohort was divided into a 2D GS TRUS-guidance cohort (from 2007 to 2013, n = 1149) and a 3D GS TRUS-guidance with preembedding cohort (from 2013 to 2016, n = 469). Effect of 3D GS TRUS-guidance with preembedding on detection rate of PCa and clinically significant PCa (Gleason score ≥ 7 or > 2 biopsy cores with a Gleason score 6) was compared to 2D GS TRUS-guidance using regression models.

Results: Detection rate of PCa and clinically significant PCa was 39.0 and 24.9% in the 3D GS TRUS cohort compared to 33.5 and 19.0% in the 2D GS TRUS cohort, respectively. On multivariate regression analysis the use of 3D GS TRUS-guidance with preembedding was associated with a significant increase in detection rate of PCa (aOR = 1.33; 95% CI: 1.03-1.72) and clinically significant PCa (aOR = 1.47; 95% CI: 1.09-1.98).

Conclusion: Our results suggest that 3D GS TRUS-guidance with biopsy core preembedding improves PCa and clinically significant PCa detection compared to 2D GS TRUS-guidance. Additional studies are needed to justify the application of these systems in clinical practice.
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http://dx.doi.org/10.1186/s12894-019-0455-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6469087PMC
April 2019

The added value of systematic biopsy in men with suspicion of prostate cancer undergoing multiparametric MRI-targeted biopsy.

Urol Oncol 2019 05 17;37(5):298.e1-298.e9. Epub 2019 Jan 17.

Department of Urology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands; Department of Urology, Jeroen Bosch Hospital, 's-Hertogenbosch, The Netherlands; Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.

Purpose: Incorporation of multiparametric magnetic resonance imaging (mpMRI) and targeted biopsy (TBx) in the diagnostic pathway for prostate cancer (CaP) is rapidly becoming common practice. In men with a prebiopsy positive mpMRI a TBx only approach, thereby omitting transrectal ultrasound-guided systematic biopsy (SBx), has been postulated. In this study we evaluated the additional clinical relevance of SBx in men with a positive prebiopsy mpMRI (Prostate Imaging Reporting and Data System [PI-RADS] ≥ 3) undergoing TBx for CaP detection, Gleason grading and CaP localization.

Material And Methods: Prospective data of 255 consecutive men with a prebiopsy positive mpMRI (PI-RADS ≥ 3) undergoing 12-core SBx and subsequent MRI-transrectal ultrasound fusion TBx in 2 institutions between 2015 and 2018 was obtained. The detection rate for significant CaP (Gleason score [GS] ≥ 3 + 4) for TBx and SBx were compared. The rate of potentially missed significant CaP by a TBx only approach was determined and GS concordance and CaP localization by TBx and SBx was evaluated.

Results: TBx yielded significant CaP in 113 men (44%) while SBx yielded significant CaP in 110 men (43%) (P = 0.856). Insignificant CaP was found in 21 men (8%) by TBx, while SBx detected 34 men (13%) with insignificant CaP (P = 0.035). A TBx only approach, omitting SBx, would have missed significant CaP in 13 of the 126 men (10%) with significant CaP on biopsy. Ten of the 118 men (8%), both positive on TBx and SBx, were upgraded in GS by SBx while 11 men (9%) had higher maximum tumor core involvement on SBx. Nineteen of the 97 men (20%) with significant CaP in both TBx and SBx were diagnosed with unilateral significant CaP on mpMRI and TBx while SBx demonstrated bilateral significant CaP.

Conclusions: In men with a prebiopsy positive mpMRI, TBx detects high-GS CaP while reducing insignificant CaP detection as compared to SBx. SBx and TBx as stand-alone missed significant CaP in 13% and 10% of the men with significant CaP on biopsy, respectively. A combination of SBx and TBx remains necessary for the most accurate assessment of detection, grading, tumor core involvement, and localization of CaP.
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http://dx.doi.org/10.1016/j.urolonc.2019.01.005DOI Listing
May 2019

On the Relationship between Dynamic Contrast-Enhanced Ultrasound Parameters and the Underlying Vascular Architecture Extracted from Acoustic Angiography.

Ultrasound Med Biol 2019 02 30;45(2):539-548. Epub 2018 Nov 30.

Department of Electrical Engineering, Technical University of Eindhoven, Eindhoven, The Netherlands.

Dynamic contrast-enhanced ultrasound (DCE-US) has been proposed as a powerful tool for cancer diagnosis by estimation of perfusion and dispersion parameters reflecting angiogenic vascular changes. This work was aimed at identifying which vascular features are reflected by the estimated perfusion and dispersion parameters through comparison with acoustic angiography (AA). AA is a high-resolution technique that allows quantification of vascular morphology. Three-dimensional AA and 2-D DCE-US bolus acquisitions were used to monitor the growth of fibrosarcoma tumors in nine rats. AA-derived vascular properties were analyzed along with DCE-US perfusion and dispersion to investigate the differences between tumor and control and their evolution in time. AA-derived microvascular density and DCE-US perfusion exhibited good agreement, confirmed by their spatial distributions. No vascular feature was correlated with dispersion. Yet, dispersion provided better cancer classification than perfusion. We therefore hypothesize that dispersion characterizes vessels that are smaller than those visible with AA.
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http://dx.doi.org/10.1016/j.ultrasmedbio.2018.08.018DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6352898PMC
February 2019

Multiparametric ultrasound: evaluation of greyscale, shear wave elastography and contrast-enhanced ultrasound for prostate cancer detection and localization in correlation to radical prostatectomy specimens.

BMC Urol 2018 Nov 8;18(1):98. Epub 2018 Nov 8.

Martini Clinic, Prostate Cancer Center, University Hospital Hamburg-Eppendorf, Hamburg, Germany.

Background: The diagnostic pathway for prostate cancer (PCa) is advancing towards an imaging-driven approach. Multiparametric magnetic resonance imaging, although increasingly used, has not shown sufficient accuracy to replace biopsy for now. The introduction of new ultrasound (US) modalities, such as quantitative contrast-enhanced US (CEUS) and shear wave elastography (SWE), shows promise but is not evidenced by sufficient high quality studies, especially for the combination of different US modalities. The primary objective of this study is to determine the individual and complementary diagnostic performance of greyscale US (GS), SWE, CEUS and their combination, multiparametric ultrasound (mpUS), for the detection and localization of PCa by comparison with corresponding histopathology.

Methods/design: In this prospective clinical trial, US imaging consisting of GS, SWE and CEUS with quantitative mapping on 3 prostate imaging planes (base, mid and apex) will be performed in 50 patients with biopsy-proven PCa before planned radical prostatectomy using a clinical ultrasound scanner. All US imaging will be evaluated by US readers, scoring the four quadrants of each imaging plane for the likelihood of significant PCa based on a 1 to 5 Likert Scale. Following resection, PCa tumour foci will be identified, graded and attributed to the imaging-derived quadrants in each prostate plane for all prostatectomy specimens. Primary outcome measure will be the sensitivity, specificity, negative predictive value and positive predictive value of each US modality and mpUS to detect and localize significant PCa evaluated for different Likert Scale thresholds using receiver operating characteristics curve analyses.

Discussion: In the evaluation of new PCa imaging modalities, a structured comparison with gold standard radical prostatectomy specimens is essential as first step. This trial is the first to combine the most promising ultrasound modalities into mpUS. It complies with the IDEAL stage 2b recommendations and will be an important step towards the evaluation of mpUS as a possible option for accurate detection and localization of PCa.

Trial Registration: The study protocol for multiparametric ultrasound was prospectively registered on Clinicaltrials.gov on 14 March 2017 with the registry name 'Multiparametric Ultrasound-Study for the Detection of Prostate Cancer' and trial registration number NCT03091231.
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http://dx.doi.org/10.1186/s12894-018-0409-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6225621PMC
November 2018

Evaluation of Dispersion MRI for Improved Prostate Cancer Diagnosis in a Multicenter Study.

AJR Am J Roentgenol 2018 11;211(5):W242-W251

1 Department of Electrical Engineering, Eindhoven University of Technology, Groene Loper 19, 5612AZ Eindhoven, The Netherlands.

Objective: The purpose of this study is to compare dispersion MRI and Tofts model (TM) for analysis of quantitative dynamic contrast-enhanced (DCE) MRI (DCE-MRI) for localization of prostate cancer and to assess the correlation between quantitative DCE-MRI parameters and tumor grade.

Materials And Methods: This retrospective multicenter study included 80 patients with biopsy-proven prostate cancer who underwent DCE-MRI followed by radical prostatectomy. DCE-MRI parameters were extracted from dispersion MRI analysis (the dispersion parameter [k], the flux rate [k], and the intravascular mean transit time) and TM analysis (the forward volume transfer constant [K], k, and the extravascular extracellular volume fraction [v]). ROIs representing benign and malignant tissue were drawn on each DCE-MRI slice according to the histopathologic findings, and the diagnostic performance of the estimated parameters for the diagnosis of prostate cancer was evaluated using fivefold cross-validation and ROC curve analysis. Further analysis was conducted for the two most relevant parameters (i.e., k [for dispersion MRI] and k [for TM]), to investigate the correlation between DCE-MRI parameters and tumor grade.

Results: DCE-MRI parameters were significantly different between benign and malignant prostate tissue (p < 0.0001). The dispersion MRI parameter k outperformed all other DCE-MRI parameters for prostate cancer diagnosis, showing the highest area under the ROC curve value (p < 0.0001). Only a weak linear correlation (Pearson r = 0.18; p < 0.05) was found between the dispersion parameter and the Gleason grade group.

Conclusion: Dispersion MRI outperformed TM analysis, improving the diagnostic performance of quantitative DCE-MRI for prostate cancer localization. Of the DCE-MRI parameters, k (for dispersion MRI) and k (for TM) provided only poor characterization of tumor grade.
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http://dx.doi.org/10.2214/AJR.17.19215DOI Listing
November 2018

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

Sci Rep 2018 10 2;8(1):14640. Epub 2018 Oct 2.

Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.

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.
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http://dx.doi.org/10.1038/s41598-018-32982-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6168586PMC
October 2018

Pharmacokinetic Modeling of Targeted Ultrasound Contrast Agents for Quantitative Assessment of Anti-Angiogenic Therapy: a Longitudinal Case-Control Study in Colon Cancer.

Mol Imaging Biol 2019 08;21(4):633-643

Department of Electrical Engineering, Eindhoven University of Technology, Groene Loper 19, 5612 AZ, Eindhoven, The Netherlands.

Purpose: To evaluate quantitative and semi-quantitative ultrasound molecular imaging (USMI) for antiangiogenic therapy monitoring in human colon cancer xenografts in mice.

Procedures: Colon cancer was established in 17 mice by injection of LS174T (N = 9) or CT26 (N = 8) cancer cells to simulate clinical responders and non-responders, respectively. Antiangiogenic treatment (bevacizumab; N = N = 5) or control treatment (saline; N = 4, N = 3) was administered at days 0, 3, and 7. Three-dimensional USMI was performed by injection at days 0, 1, 3, 7, and 10 of microbubbles targeted to the vascular endothelial growth factor receptor 2 (VEGFR2). Microbubble binding rate (k), estimated by first-pass binding model fitting, and semi-quantitative parameters late enhancement (LE) and differential targeted enhancement (dTE) were compared at each day to evaluate their ability to assess and predict the response to therapy. Correlation analysis with the ex-vivo immunohistological quantification of VEGFR2 expression and the percentage blood vessel area was also performed.

Results: Significant changes in the USMI parameters during treatment were observed only in the responders treated with bevacizumab (p-value < 0.05). Prediction of the response to therapy as early as 1 day after treatment was achieved by the quantitative parameter k (p-value < 0.01), earlier than possible by tumor volume quantification. USMI parameters could significantly distinguish between clinical responders and non-responders (p-value << 0.01) and correlated well with the ex-vivo quantification of VEGFR2 expression and the percentage blood vessels area (p-value << 0.01).

Conclusion: USMI (semi)quantitative parameters provide earlier assessment of the response to therapy compared to tumor volume, permit early prediction of non-responders, and correlate well with ex-vivo angiogenesis biomarkers.
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http://dx.doi.org/10.1007/s11307-018-1274-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6616210PMC
August 2019

Accurate validation of ultrasound imaging of prostate cancer: a review of challenges in registration of imaging and histopathology.

J Ultrasound 2018 Sep 30;21(3):197-207. Epub 2018 Jul 30.

Laboratory of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, De Rondom 70, 5612 AP, Eindhoven, The Netherlands.

As the development of modalities for prostate cancer (PCa) imaging advances, the challenge of accurate registration between images and histopathologic ground truth becomes more pressing. Localization of PCa, rather than detection, requires a pixel-to-pixel validation of imaging based on histopathology after radical prostatectomy. Such a registration procedure is challenging for ultrasound modalities; not only the deformations of the prostate after resection have to be taken into account, but also the deformation due to the employed transrectal probe and the mismatch in orientation between imaging planes and pathology slices. In this work, we review the latest techniques to facilitate accurate validation of PCa localization in ultrasound imaging studies and extrapolate a general strategy for implementation of a registration procedure.
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http://dx.doi.org/10.1007/s40477-018-0311-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6113189PMC
September 2018

Use of Contrast-Enhanced Ultrasound in the Assessment of Uterine Fibroids: A Feasibility Study.

Ultrasound Med Biol 2018 08 4;44(8):1901-1909. Epub 2018 May 4.

Department of Obstetrics and Gynaecology, Vrije Universiteit Medical Center, Amsterdam, The Netherlands; Amsterdam Reproduction and Development, Vrie Universiteit Medical Center and Academic Medical Center, Amsterdam, The Netherlands.

Contrast-enhanced ultrasound (CEUS) is an innovative ultrasound technique capable of visualizing both the macro- and microvasculature of tissues. In this prospective pilot study, we evaluated the feasibility of using CEUS to visualize the microvasculature of uterine fibroids and compared CEUS with conventional ultrasound. Four women with fibroids underwent gray-scale ultrasound, sonoelastography and power/color Doppler scans followed by CEUS examination. Analysis of CEUS images revealed initial perfusion of the peripheral rim, that is, a pseudo-capsule, followed by enhancement of the entire lesion through vessels traveling from the exterior to the interior of the fibroid. The pseudo-capsules exhibited slight hyper-enhancement, making a clear delineation of the fibroids possible. The centers of three fibroids exhibited areas lacking vascularization, information not obtainable with the other imaging techniques. CEUS is a feasible technique for imaging and quantifying the microvasculature of fibroids. In comparison with conventional ultrasound imaging modalities, CEUS can provide additional diagnostic information based on the microvasculature.
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http://dx.doi.org/10.1016/j.ultrasmedbio.2018.03.030DOI Listing
August 2018

The EFSUMB Guidelines and Recommendations for the Clinical Practice of Contrast-Enhanced Ultrasound (CEUS) in Non-Hepatic Applications: Update 2017 (Short Version).

Ultraschall Med 2018 Apr 6;39(2):154-180. Epub 2018 Mar 6.

Urology, AMC University Hospital, Amsterdam and Signal Processing Systems, Eindhoven University of Technology, The Netherlands.

The updated version of the EFSUMB guidelines on the application of non-hepatic contrast-enhanced ultrasound (CEUS) deals with the use of microbubble ultrasound contrast outside the liver in the many established and emerging applications.
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http://dx.doi.org/10.1055/s-0044-101254DOI Listing
April 2018

The EFSUMB Guidelines and Recommendations for the Clinical Practice of Contrast-Enhanced Ultrasound (CEUS) in Non-Hepatic Applications: Update 2017 (Long Version).

Ultraschall Med 2018 Apr 6;39(2):e2-e44. Epub 2018 Mar 6.

Urology, AMC University Hospital, Amsterdam and Signal Processing Systems, Eindhoven University of Technology, The Netherlands.

The updated version of the EFSUMB guidelines on the application of non-hepatic contrast-enhanced ultrasound (CEUS) deals with the use of microbubble ultrasound contrast outside the liver in the many established and emerging applications.
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http://dx.doi.org/10.1055/a-0586-1107DOI Listing
April 2018

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

Ultrasound Med Biol 2018 04 12;44(4):807-814. Epub 2018 Feb 12.

Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.

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.
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http://dx.doi.org/10.1016/j.ultrasmedbio.2017.12.005DOI Listing
April 2018
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