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Chen P, Turco S, Wang Y, Jager A, Daures G, Wijkstra H, Zwart W, Huang P, Mischi M. Can 3D Multiparametric Ultrasound Imaging Predict Prostate Biopsy Outcome? ULTRASOUND IN MEDICINE & BIOLOGY 2024; 50:1194-1202. [PMID: 38734528 DOI: 10.1016/j.ultrasmedbio.2024.04.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 03/16/2024] [Accepted: 04/14/2024] [Indexed: 05/13/2024]
Abstract
OBJECTIVES To assess the value of 3D multiparametric ultrasound imaging, combining hemodynamic and tissue stiffness quantifications by machine learning, for the prediction of prostate biopsy outcomes. METHODS After signing informed consent, 54 biopsy-naïve patients underwent a 3D dynamic contrast-enhanced ultrasound (DCE-US) recording, a multi-plane 2D shear-wave elastography (SWE) scan with manual sweeping from base to apex of the prostate, and received 12-core systematic biopsies (SBx). 3D maps of 18 hemodynamic parameters were extracted from the 3D DCE-US quantification and a 3D SWE elasticity map was reconstructed based on the multi-plane 2D SWE acquisitions. Subsequently, all the 3D maps were segmented and subdivided into 12 regions corresponding to the SBx locations. Per region, the set of 19 computed parameters was further extended by derivation of eight radiomic features per parameter. Based on this feature set, a multiparametric ultrasound approach was implemented using five different classifiers together with a sequential floating forward selection method and hyperparameter tuning. The classification accuracy with respect to the biopsy reference was assessed by a group-k-fold cross-validation procedure, and the performance was evaluated by the Area Under the Receiver Operating Characteristics Curve (AUC). RESULTS Of the 54 patients, 20 were found with clinically significant prostate cancer (csPCa) based on SBx. The 18 hemodynamic parameters showed mean AUC values varying from 0.63 to 0.75, and SWE elasticity showed an AUC of 0.66. The multiparametric approach using radiomic features derived from hemodynamic parameters only produced an AUC of 0.81, while the combination of hemodynamic and tissue-stiffness quantifications yielded a significantly improved AUC of 0.85 for csPCa detection (p-value < 0.05) using the Gradient Boosting classifier. CONCLUSIONS Our results suggest 3D multiparametric ultrasound imaging combining hemodynamic and tissue-stiffness features to represent a promising diagnostic tool for biopsy outcome prediction, aiding in csPCa localization.
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Affiliation(s)
- Peiran Chen
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands.
| | - Simona Turco
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
| | - Yao Wang
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University, Hangzhou, China
| | - Auke Jager
- Department of Urology, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Gautier Daures
- Angiogenesis Analytics, JADS Venture Campus, Netherlands
| | - Hessel Wijkstra
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands; Department of Urology, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Wim Zwart
- Angiogenesis Analytics, JADS Venture Campus, Netherlands
| | - Pintong Huang
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University, Hangzhou, China
| | - Massimo Mischi
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
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Hristov D, Mustonen L, von Eyben R, Gotschel S, Minion M, El Kaffas A. Dynamic Contrast-Enhanced Ultrasound Modeling of an Analog to Pseudo-Diffusivity in Intravoxel Incoherent Motion Magnetic Resonance Imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING 2022; 41:3824-3834. [PMID: 35939460 PMCID: PMC10101718 DOI: 10.1109/tmi.2022.3197363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Tumor perfusion and vascular properties are important determinants of cancer response to therapy and thus various approaches for imaging perfusion are being explored. In particular, Intravoxel Incoherent Motion (IVIM) MRI has been actively researched as an alternative to Dynamic-Contrast-Enhanced (DCE) CT and DCE-MRI as it offers non-ionizing, non-contrast-based perfusion imaging. However, for repetitive treatment assessment in a short time period, high cost, limited access, and inability to scan at the bedside remain disadvantages of IVIM MRI. We propose an analysis framework that may enable 3D DCE Ultrasound (DCE-US) - low cost, bedside imaging with excellent safety record - as an alternative modality to IVIM MRI for the generation of DCE-US based pseudo-diffusivity maps in acoustically accessible anatomy and tumors. Modelling intravascular contrast propagation as a convective-diffusive process, we reconstruct parametric maps of pseudo-diffusivity by solving a large-scale fully coupled inverse problem without any assumptions regarding local constancy of the reconstructed parameters. In a mouse tumor model, we demonstrate that the 3D DCE-US pseudo-diffusivity is repeatable, sensitive to treatment with an antiangiogenic agent, and moderately correlated to histological measures of perfusion and angiogenesis.
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Jager A, Vilanova JC, Michi M, Wijkstra H, Oddens JR. The challenge of prostate biopsy guidance in the era of mpMRI detected lesion: ultrasound-guided versus in-bore biopsy. Br J Radiol 2022; 95:20210363. [PMID: 34324383 PMCID: PMC8978231 DOI: 10.1259/bjr.20210363] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
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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Affiliation(s)
- Auke Jager
- Department of Urology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Joan C Vilanova
- Department of Radiology, Clinica Girona, Diagnostic Imaging Institute (IDI), University of Girona, Girona, Spain
| | - Massimo Michi
- Lab of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
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Wildeboer RR, Sammali F, van Sloun RJG, Huang Y, Chen P, Bruce M, Rabotti C, Shulepov S, Salomon G, Schoot BC, Wijkstra H, Mischi M. Blind Source Separation for Clutter and Noise Suppression in Ultrasound Imaging: Review for Different Applications. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2020; 67:1497-1512. [PMID: 32091998 DOI: 10.1109/tuffc.2020.2975483] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
Blind source separation (BSS) refers to a number of signal processing techniques that decompose a signal into several "source" signals. In recent years, BSS is increasingly employed for the suppression of clutter and noise in ultrasonic imaging. In particular, its ability to separate sources based on measures of independence rather than their temporal or spatial frequency content makes BSS a powerful filtering tool for data in which the desired and undesired signals overlap in the spectral domain. The purpose of this work was to review the existing BSS methods and their potential in ultrasound imaging. Furthermore, we tested and compared the effectiveness of these techniques in the field of contrast-ultrasound super-resolution, contrast quantification, and speckle tracking. For all applications, this was done in silico, in vitro, and in vivo. We found that the critical step in BSS filtering is the identification of components containing the desired signal and highlighted the value of a priori domain knowledge to define effective criteria for signal component selection.
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Turco S, Frinking P, Wildeboer R, Arditi M, Wijkstra H, Lindner JR, Mischi M. Contrast-Enhanced Ultrasound Quantification: From Kinetic Modeling to Machine Learning. ULTRASOUND IN MEDICINE & BIOLOGY 2020; 46:518-543. [PMID: 31924424 DOI: 10.1016/j.ultrasmedbio.2019.11.008] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Revised: 11/13/2019] [Accepted: 11/14/2019] [Indexed: 05/14/2023]
Abstract
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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Affiliation(s)
- Simona Turco
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
| | | | - Rogier Wildeboer
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Marcel Arditi
- École polytechnique fédérale de Lausanne, Lausanne, Switzerland
| | - Hessel Wijkstra
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Jonathan R Lindner
- Knight Cardiovascular Center, Oregon Health & Science University, Portland, Oregon, USA
| | - Massimo Mischi
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
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Wildeboer RR, van Sloun RJG, Huang P, Wijkstra H, Mischi M. 3-D Multi-parametric Contrast-Enhanced Ultrasound for the Prediction of Prostate Cancer. ULTRASOUND IN MEDICINE & BIOLOGY 2019; 45:2713-2724. [PMID: 31300222 DOI: 10.1016/j.ultrasmedbio.2019.05.017] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Revised: 04/23/2019] [Accepted: 05/16/2019] [Indexed: 05/14/2023]
Abstract
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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Affiliation(s)
- Rogier R Wildeboer
- Lab of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
| | - Ruud J G van Sloun
- Lab of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Pintong Huang
- Department of Ultrasonography, Second Affiliated Hospital of Zhejiang University, Hangzhou, China
| | - Hessel Wijkstra
- Lab of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; Department of Urology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Massimo Mischi
- Lab of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
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7
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Panfilova A, Shelton SE, Caresio C, van Sloun RJG, Molinari F, Wijkstra H, Dayton PA, Mischi M. On the Relationship between Dynamic Contrast-Enhanced Ultrasound Parameters and the Underlying Vascular Architecture Extracted from Acoustic Angiography. ULTRASOUND IN MEDICINE & BIOLOGY 2019; 45:539-548. [PMID: 30509785 PMCID: PMC6352898 DOI: 10.1016/j.ultrasmedbio.2018.08.018] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2018] [Revised: 08/22/2018] [Accepted: 08/27/2018] [Indexed: 05/23/2023]
Abstract
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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Affiliation(s)
- Anastasiia Panfilova
- Department of Electrical Engineering, Technical University of Eindhoven, Eindhoven, The Netherlands.
| | - Sarah E Shelton
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill and North Carolina State University, Chapel Hill, North Carolina, USA
| | | | - Ruud J G van Sloun
- Department of Electrical Engineering, Technical University of Eindhoven, Eindhoven, The Netherlands
| | | | - Hessel Wijkstra
- Department of Electrical Engineering, Technical University of Eindhoven, Eindhoven, The Netherlands; Urology Department, AMC University Hospital, Amsterdam, The Netherlands
| | - Paul A Dayton
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill and North Carolina State University, Chapel Hill, North Carolina, USA
| | - Massimo Mischi
- Department of Electrical Engineering, Technical University of Eindhoven, Eindhoven, The Netherlands
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8
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Yuan Y, Liu Y, Zhu XM, Hu J, Zhao CY, Jiang F. Six-Transmembrane Epithelial Antigen of the Prostate-1 (STEAP-1)-Targeted Ultrasound Imaging Microbubble Improves Detection of Prostate Cancer In Vivo. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2019; 38:299-305. [PMID: 30027616 DOI: 10.1002/jum.14689] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2017] [Revised: 03/23/2018] [Accepted: 04/21/2018] [Indexed: 06/08/2023]
Abstract
PURPOSE To investigate the feasibility of the 6-transmembrane epithelial antigen of the prostate-1 (STEAP-1)-targeted microbubbles for enhancing ultrasound imaging of prostate tumors in the nude mouse xenograft models. METHODS Contrast agents were established by conjugating biotinylated STEAP-1 monoclonal antibodies with streptavidin coated SonoVue microbubbles. Then, ordinary SonoVue (Bracco, Milan, Italy) microbubble and STEAP-1-targeted SonoVue microbubble were used, respectively, for contrast-enhanced sonography to detect prostate tumors in the nude mouse xenograft models. The characteristics, including peak intensity, time to peak, area under the curve, and mean transit time, were measured. RESULTS The biological characteristics of STEAP-1-targeted SonoVue microbubbles were stable. STEAP-1-targeted SonoVue microbubbles can successfully conjugate to prostate cancer cell lines in vitro. Enhancement of ultrasound signal intensity was determined after injection of STEAP-1-targeted SonoVue microbubble, compared with ordinary SonoVue microbubble. Higher intensities of ultrasound signals in xenograft tumor of prostate cancer were associated with increased levels of STEAP-1 expression. CONCLUSION Our results suggest that SonoVue microbubble carrying STEAP-1 monoclonal antibody could improve the ultrasound visualization of prostate cancer and identify the tumor more effectively in vivo. A prospective study is required to validate our finding in patients with prostate cancer.
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Affiliation(s)
- Yun Yuan
- Department of Ultrasound, The First Affiliated Hospital of Wanan Medical College, Wuhu, Anhui China
| | - Ying Liu
- Department of Ultrasound, Zhejiang Province People's Hospital, Hangzhou, Zhejiang China
| | - Xiang-Ming Zhu
- Department of Ultrasound, The First Affiliated Hospital of Wanan Medical College, Wuhu, Anhui China
| | - Jing Hu
- Department of Ultrasound, The First Affiliated Hospital of Wanan Medical College, Wuhu, Anhui China
| | - Chen-Yang Zhao
- Department of Ultrasound, The First Affiliated Hospital of Wanan Medical College, Wuhu, Anhui China
| | - Feng Jiang
- Department of Ultrasound, The First Affiliated Hospital of Wanan Medical College, Wuhu, Anhui China
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9
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Wildeboer RR, Van Sloun RJG, Schalk SG, Mannaerts CK, Van Der Linden JC, Huang P, Wijkstra H, Mischi M. Convective-Dispersion Modeling in 3D Contrast-Ultrasound Imaging for the Localization of Prostate Cancer. IEEE TRANSACTIONS ON MEDICAL IMAGING 2018; 37:2593-2602. [PMID: 29993539 DOI: 10.1109/tmi.2018.2843396] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
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 (DCE-US) 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 paper, 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 with 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.
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10
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van Sloun RJG, Demi L, Schalk SG, Caresio C, Mannaerts C, Postema AW, Molinari F, van der Linden HC, Huang P, Wijkstra H, Mischi M. Contrast-enhanced ultrasound tractography for 3D vascular imaging of the prostate. Sci Rep 2018; 8:14640. [PMID: 30279545 PMCID: PMC6168586 DOI: 10.1038/s41598-018-32982-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Accepted: 09/19/2018] [Indexed: 02/02/2023] Open
Abstract
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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Affiliation(s)
- Ruud J G van Sloun
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
| | - Libertario Demi
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Department of Information Engineering and Computer Science, University of Trento, Trento, Italy
| | - Stefan G Schalk
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Department of Urology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Cristina Caresio
- Department of Electronics and Telecommunications, Biolab, Polytechnic University of Turin, Turin, Italy
| | - Christophe Mannaerts
- Department of Urology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Arnoud W Postema
- Department of Urology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Filippo Molinari
- Department of Electronics and Telecommunications, Biolab, Polytechnic University of Turin, Turin, Italy
| | - Hans C van der Linden
- Department of Pathology/DNA laboratories, Jeroen Bosch Hospital, 's-Hertogenbosch, The Netherlands
| | - Pingtong Huang
- Department of Ultrasound, Second Affiliated University Hospital, Zhejiang University School of Medicine, Hangzhou, PR China
| | - Hessel Wijkstra
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Department of Urology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Massimo Mischi
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
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11
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Schalk SG, Huang J, Li J, Demi L, Wijkstra H, Huang P, Mischi M. 3-D Quantitative Dynamic Contrast Ultrasound for Prostate Cancer Localization. ULTRASOUND IN MEDICINE & BIOLOGY 2018; 44:807-814. [PMID: 29395678 DOI: 10.1016/j.ultrasmedbio.2017.12.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/30/2017] [Revised: 11/10/2017] [Accepted: 12/03/2017] [Indexed: 06/07/2023]
Abstract
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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Affiliation(s)
- Stefan G Schalk
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; Department of Urology, Academic Medical Center, Amsterdam, The Netherlands.
| | - Jing Huang
- Department of Ultrasound, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Jia Li
- Department of Ultrasound, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Libertario Demi
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Hessel Wijkstra
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; Department of Urology, Academic Medical Center, Amsterdam, The Netherlands
| | - Pintong Huang
- Department of Ultrasound, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Massimo Mischi
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
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12
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Denis de Senneville B, Novell A, Arthuis C, Mendes V, Dujardin PA, Patat F, Bouakaz A, Escoffre JM, Perrotin F. Development of a Fluid Dynamic Model for Quantitative Contrast-Enhanced Ultrasound Imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING 2018; 37:372-383. [PMID: 28858788 DOI: 10.1109/tmi.2017.2743099] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Contrast-enhanced ultrasound (CEUS) is a non-invasive imaging technique extensively used for blood perfusion imaging of various organs. This modality is based on the acoustic detection of gas-filled microbubble contrast agents used as intravascular flow tracers. Recent efforts aim at quantifying parameters related to the enhancement in the vascular compartment using time-intensity curve (TIC), and at using these latter as indicators for several pathological conditions. However, this quantification is mainly hampered by two reasons: first, the quantification intrinsically solely relies on temporal intensity variation, the explicit spatial transport of the contrast agent being left out. Second, the exact relationship between the acquired US-signal and the local microbubble concentration is hardly accessible. This paper introduces the use of a fluid dynamic model for the analysis of dynamic CEUS (DCEUS), in order to circumvent the two above-mentioned limitations. A new kinetic analysis is proposed in order to quantify the velocity amplitude of the bolus arrival. The efficiency of proposed methodology is evaluated both in-vitro, for the quantitative estimation of microbubble flow rates, and in-vivo, for the classification of placental insufficiency (control versus ligature) of pregnant rats from DCEUS. Besides, for the in-vivo experimental setup, we demonstrated that the proposed approach outperforms the performance of existing TIC-based methods.
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13
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Wildeboer RR, Postema AW, Demi L, Kuenen MPJ, Wijkstra H, Mischi M. Multiparametric dynamic contrast-enhanced ultrasound imaging of prostate cancer. Eur Radiol 2017; 27:3226-3234. [PMID: 28004162 PMCID: PMC5491563 DOI: 10.1007/s00330-016-4693-8] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2016] [Revised: 11/28/2016] [Accepted: 12/01/2016] [Indexed: 12/29/2022]
Abstract
OBJECTIVES The aim of this study is to improve the accuracy of dynamic contrast-enhanced ultrasound (DCE-US) for prostate cancer (PCa) localization by means of a multiparametric approach. MATERIALS AND METHODS Thirteen different parameters related to either perfusion or dispersion were extracted pixel-by-pixel from 45 DCE-US recordings in 19 patients referred for radical prostatectomy. Multiparametric maps were retrospectively produced using a Gaussian mixture model algorithm. These were subsequently evaluated on their pixel-wise performance in classifying 43 benign and 42 malignant histopathologically confirmed regions of interest, using a prostate-based leave-one-out procedure. RESULTS The combination of the spatiotemporal correlation (r), mean transit time (μ), curve skewness (κ), and peak time (PT) yielded an accuracy of 81% ± 11%, which was higher than the best performing single parameters: r (73%), μ (72%), and wash-in time (72%). The negative predictive value increased to 83% ± 16% from 70%, 69% and 67%, respectively. Pixel inclusion based on the confidence level boosted these measures to 90% with half of the pixels excluded, but without disregarding any prostate or region. CONCLUSIONS Our results suggest multiparametric DCE-US analysis might be a useful diagnostic tool for PCa, possibly supporting future targeting of biopsies or therapy. Application in other types of cancer can also be foreseen. KEY POINTS • DCE-US can be used to extract both perfusion and dispersion-related parameters. • Multiparametric DCE-US performs better in detecting PCa than single-parametric DCE-US. • Multiparametric DCE-US might become a useful tool for PCa localization.
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Affiliation(s)
- Rogier R Wildeboer
- Laboratory of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, PO-Box 513, 5600 MB, Eindhoven, The Netherlands.
| | - Arnoud W Postema
- Department of Urology, Academic Medical Center University Hospital, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
| | - Libertario Demi
- Laboratory of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, PO-Box 513, 5600 MB, Eindhoven, The Netherlands
| | | | - Hessel Wijkstra
- Laboratory of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, PO-Box 513, 5600 MB, Eindhoven, The Netherlands
- Department of Urology, Academic Medical Center University Hospital, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
| | - Massimo Mischi
- Laboratory of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, PO-Box 513, 5600 MB, Eindhoven, The Netherlands
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First-in-Human Ultrasound Molecular Imaging With a VEGFR2-Specific Ultrasound Molecular Contrast Agent (BR55) in Prostate Cancer. Invest Radiol 2017; 52:419-427. [DOI: 10.1097/rli.0000000000000362] [Citation(s) in RCA: 98] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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15
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van Sloun RJG, Demi L, Postema AW, Jmch De La Rosette J, Wijkstra H, Mischi M. Entropy of Ultrasound-Contrast-Agent Velocity Fields for Angiogenesis Imaging in Prostate Cancer. IEEE TRANSACTIONS ON MEDICAL IMAGING 2017; 36:826-837. [PMID: 28113929 DOI: 10.1109/tmi.2016.2629851] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Prostate cancer care can benefit from accurate and cost-efficient imaging modalities that are able to reveal prognostic indicators for cancer. Angiogenesis is known to play a central role in the growth of tumors towards a metastatic or a lethal phenotype. With the aim of localizing angiogenic activity in a non-invasive manner, Dynamic Contrast Enhanced Ultrasound (DCE-US) has been widely used. Usually, the passage of ultrasound contrast agents thought the organ of interest is analyzed for the assessment of tissue perfusion. However, the heterogeneous nature of blood flow in angiogenic vasculature hampers the diagnostic effectiveness of perfusion parameters. In this regard, quantification of the heterogeneity of flow may provide a relevant additional feature for localizing angiogenesis. Statistics based on flow magnitude as well as its orientation can be exploited for this purpose. In this paper, we estimate the microbubble velocity fields from a standard bolus injection and provide a first statistical characterization by performing a spatial entropy analysis. By testing the method on 24 patients with biopsy-proven prostate cancer, we show that the proposed method can be applied effectively to clinically acquired DCE-US data. The method permits estimation of the in-plane flow vector fields and their local intricacy, and yields promising results (receiver-operating-characteristic curve area of 0.85) for the detection of prostate cancer.
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16
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van Sloun RJG, Demi L, Postema AW, de la Rosette JJMCH, Wijkstra H, Mischi M. Ultrasound-contrast-agent dispersion and velocity imaging for prostate cancer localization. Med Image Anal 2017; 35:610-619. [DOI: 10.1016/j.media.2016.09.010] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2016] [Revised: 07/21/2016] [Accepted: 09/26/2016] [Indexed: 11/25/2022]
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17
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Turco S, Wijkstra H, Mischi M. Mathematical Models of Contrast Transport Kinetics for Cancer Diagnostic Imaging: A Review. IEEE Rev Biomed Eng 2016; 9:121-47. [PMID: 27337725 DOI: 10.1109/rbme.2016.2583541] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Angiogenesis plays a fundamental role in cancer growth and the formation of metastasis. Novel cancer therapies aimed at inhibiting angiogenic processes and/or disrupting angiogenic tumor vasculature are currently being developed and clinically tested. The need for earlier and improved cancer diagnosis, and for early evaluation and monitoring of therapeutic response to angiogenic treatment, have led to the development of several imaging methods for in vivo noninvasive assessment of angiogenesis. The combination of dynamic contrast-enhanced imaging with mathematical modeling of the contrast agent kinetics enables quantitative assessment of the structural and functional changes in the microvasculature that are associated with tumor angiogenesis. In this paper, we review quantitative imaging of angiogenesis with dynamic contrast-enhanced magnetic resonance imaging, computed tomography, and ultrasound.
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18
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Schalk SG, Demi L, Bouhouch N, Kuenen MPJ, Postema AW, de la Rosette JJMCH, Wijkstra H, Tjalkens TJ, Mischi M. Contrast-Enhanced Ultrasound Angiogenesis Imaging by Mutual Information Analysis for Prostate Cancer Localization. IEEE Trans Biomed Eng 2016; 64:661-670. [PMID: 28113214 DOI: 10.1109/tbme.2016.2571624] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE The role of angiogenesis in cancer growth has stimulated research aimed at noninvasive cancer detection by blood perfusion imaging. Recently, contrast ultrasound dispersion imaging was proposed as an alternative method for angiogenesis imaging. After the intravenous injection of an ultrasound-contrast-agent bolus, dispersion can be indirectly estimated from the local similarity between neighboring time-intensity curves (TICs) measured by ultrasound imaging. Up until now, only linear similarity measures have been investigated. Motivated by the promising results of this approach in prostate cancer (PCa), we developed a novel dispersion estimation method based on mutual information, thus including nonlinear similarity, to further improve its ability to localize PCa. METHODS First, a simulation study was performed to establish the theoretical link between dispersion and mutual information. Next, the method's ability to localize PCa was validated in vivo in 23 patients (58 datasets) referred for radical prostatectomy by comparison with histology. RESULTS A monotonic relationship between dispersion and mutual information was demonstrated. The in vivo study resulted in a receiver operating characteristic (ROC) curve area equal to 0.77, which was superior (p = 0.21-0.24) to that obtained by linear similarity measures (0.74-0.75) and (p <; 0.05) to that by conventional perfusion parameters (≤0.70). CONCLUSION Mutual information between neighboring time-intensity curves can be used to indirectly estimate contrast dispersion and can lead to more accurate PCa localization. SIGNIFICANCE An improved PCa localization method can possibly lead to better grading and staging of tumors, and support focal-treatment guidance. Moreover, future employment of the method in other types of angiogenic cancer can be considered.
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O'Shea T, Bamber J, Fontanarosa D, van der Meer S, Verhaegen F, Harris E. Review of ultrasound image guidance in external beam radiotherapy part II: intra-fraction motion management and novel applications. Phys Med Biol 2016; 61:R90-137. [PMID: 27002558 DOI: 10.1088/0031-9155/61/8/r90] [Citation(s) in RCA: 66] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Imaging has become an essential tool in modern radiotherapy (RT), being used to plan dose delivery prior to treatment and verify target position before and during treatment. Ultrasound (US) imaging is cost-effective in providing excellent contrast at high resolution for depicting soft tissue targets apart from those shielded by the lungs or cranium. As a result, it is increasingly used in RT setup verification for the measurement of inter-fraction motion, the subject of Part I of this review (Fontanarosa et al 2015 Phys. Med. Biol. 60 R77-114). The combination of rapid imaging and zero ionising radiation dose makes US highly suitable for estimating intra-fraction motion. The current paper (Part II of the review) covers this topic. The basic technology for US motion estimation, and its current clinical application to the prostate, is described here, along with recent developments in robust motion-estimation algorithms, and three dimensional (3D) imaging. Together, these are likely to drive an increase in the number of future clinical studies and the range of cancer sites in which US motion management is applied. Also reviewed are selections of existing and proposed novel applications of US imaging to RT. These are driven by exciting developments in structural, functional and molecular US imaging and analytical techniques such as backscatter tissue analysis, elastography, photoacoustography, contrast-specific imaging, dynamic contrast analysis, microvascular and super-resolution imaging, and targeted microbubbles. Such techniques show promise for predicting and measuring the outcome of RT, quantifying normal tissue toxicity, improving tumour definition and defining a biological target volume that describes radiation sensitive regions of the tumour. US offers easy, low cost and efficient integration of these techniques into the RT workflow. US contrast technology also has potential to be used actively to assist RT by manipulating the tumour cell environment and by improving the delivery of radiosensitising agents. Finally, US imaging offers various ways to measure dose in 3D. If technical problems can be overcome, these hold potential for wide-dissemination of cost-effective pre-treatment dose verification and in vivo dose monitoring methods. It is concluded that US imaging could eventually contribute to all aspects of the RT workflow.
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Affiliation(s)
- Tuathan O'Shea
- Joint Department of Physics, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Sutton, London SM2 5NG, UK
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20
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Turco S, Janssen AJ, Lavini C, de la Rosette JJ, Wijkstra H, Mischi M. Time-efficient estimation of the magnetic resonance dispersion model parameters for quantitative assessment of angiogenesis. Biomed Signal Process Control 2016. [DOI: 10.1016/j.bspc.2015.11.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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21
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Sarkar S, Das S. A Review of Imaging Methods for Prostate Cancer Detection. Biomed Eng Comput Biol 2016; 7:1-15. [PMID: 26966397 PMCID: PMC4777886 DOI: 10.4137/becb.s34255] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2015] [Revised: 01/07/2016] [Accepted: 01/11/2016] [Indexed: 12/21/2022] Open
Abstract
Imaging is playing an increasingly important role in the detection of prostate cancer (PCa). This review summarizes the key imaging modalities-multiparametric ultrasound (US), multiparametric magnetic resonance imaging (MRI), MRI-US fusion imaging, and positron emission tomography (PET) imaging-used in the diagnosis and localization of PCa. Emphasis is laid on the biological and functional characteristics of tumors that rationalize the use of a specific imaging technique. Changes to anatomical architecture of tissue can be detected by anatomical grayscale US and T2-weighted MRI. Tumors are known to progress through angiogenesis-a fact exploited by Doppler and contrast-enhanced US and dynamic contrast-enhanced MRI. The increased cellular density of tumors is targeted by elastography and diffusion-weighted MRI. PET imaging employs several different radionuclides to target the metabolic and cellular activities during tumor growth. Results from studies using these various imaging techniques are discussed and compared.
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Affiliation(s)
| | - Sudipta Das
- Department of Medicine, University of California, San Diego, CA, USA
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22
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Schalk SG, Postema A, Saidov TA, Demi L, Smeenge M, de la Rosette JJMCH, Wijkstra H, Mischi M. 3D surface-based registration of ultrasound and histology in prostate cancer imaging. Comput Med Imaging Graph 2015; 47:29-39. [PMID: 26647110 DOI: 10.1016/j.compmedimag.2015.11.001] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2015] [Revised: 07/13/2015] [Accepted: 11/03/2015] [Indexed: 11/20/2022]
Abstract
Several transrectal ultrasound (TRUS)-based techniques aiming at accurate localization of prostate cancer are emerging to improve diagnostics or to assist with focal therapy. However, precise validation prior to introduction into clinical practice is required. Histopathology after radical prostatectomy provides an excellent ground truth, but needs accurate registration with imaging. In this work, a 3D, surface-based, elastic registration method was developed to fuse TRUS images with histopathologic results. To maximize the applicability in clinical practice, no auxiliary sensors or dedicated hardware were used for the registration. The mean registration errors, measured in vitro and in vivo, were 1.5±0.2 and 2.1±0.5mm, respectively.
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Affiliation(s)
- Stefan G Schalk
- Department of Electrical Engineering, Eindhoven University of Technology, Postbus 513, 5600 MB Eindhoven, The Netherlands.
| | - Arnoud Postema
- Department of Urology, AMC University Hospital, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - Tamerlan A Saidov
- Department of Electrical Engineering, Eindhoven University of Technology, Postbus 513, 5600 MB Eindhoven, The Netherlands
| | - Libertario Demi
- Department of Electrical Engineering, Eindhoven University of Technology, Postbus 513, 5600 MB Eindhoven, The Netherlands
| | - Martijn Smeenge
- Department of Urology, AMC University Hospital, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | | | - Hessel Wijkstra
- Department of Electrical Engineering, Eindhoven University of Technology, Postbus 513, 5600 MB Eindhoven, The Netherlands; Department of Urology, AMC University Hospital, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands
| | - Massimo Mischi
- Department of Electrical Engineering, Eindhoven University of Technology, Postbus 513, 5600 MB Eindhoven, The Netherlands
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