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van den Kroonenberg DL, Jager A, Garrido-Utrilla A, Reitsma JB, Postema AW, Beerlage HP, Oddens JR. Clinical Validation of Multiparametric Ultrasound for Detecting Clinically Significant Prostate Cancer Using Computer-Aided Diagnosis: A Direct Comparison with the Magnetic Resonance Imaging Pathway. EUR UROL SUPPL 2024; 66:60-66. [PMID: 39050912 PMCID: PMC11267110 DOI: 10.1016/j.euros.2024.06.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/19/2024] [Indexed: 07/27/2024] Open
Abstract
We present the protocol for a study testing the hypothesis that a computer-aided diagnosis (CAD) system for three-dimensional multiparametric ultrasound (3D mpUS) is noninferior to magnetic resonance imaging (MRI) in guiding prostate biopsies for detection of clinically significant prostate cancer (csPCa). The prospective study has a fully paired design for assessment of diagnostic accuracy and is registered on ClinicalTrials.gov as NCT06281769. A total of 438 biopsy-naïve men scheduled for prostate MRI evaluation because of an abnormal digital rectal examination and/or elevated serum prostate-specific antigen will be included. All patients will undergo both MRI (multiparametric or biparametric) and 3D mpUS with CAD (PCaVision). Suspicious lesions will be independently identified using each imaging technique. MRI targeted biopsy (TBx) and/or PCaVision TBx will be performed if suspicious lesions are identified on imaging. When both PCaVision and MRI identify lesions in an individual patient, the TBx order for this patient will be randomized. Three TBx samples per lesion will be taken for a maximum of two lesions per modality. The primary objective is the detection rate for csPCa (International Society of Urological Pathology grade group [GG] ≥2) with the PCaVision versus the MRI TBx pathway. The noninferiority margin for the absolute difference in detection rates is set at a difference of 5%. Secondary outcomes are the proportion of men in whom TBx could have been safely omitted in each pathway. Additional diagnostic accuracy analyses will be performed for different definitions of PCa (GG ≥3; GG ≥2 with cribriform growth and/or intraductal carcinoma; and GG 1). The frequency of insufficient image quality for the two pathways will also be assessed. Lastly, we will determine the diagnostic performance for csPCa detection at various 3D mpUS image quality thresholds for PCaVision.
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Affiliation(s)
| | - Auke Jager
- Department of Urology, Amsterdam UMC, Amsterdam, The Netherlands
| | | | - Johannes B. Reitsma
- Julius Center for Health Sciences and Primary Care, UMC Utrecht, Utrecht, The Netherlands
| | - Arnoud W. Postema
- Department of Urology, Leids Universitair Medisch Centrum, Leiden, The Netherlands
| | | | - Jorg R. Oddens
- Department of Urology, Amsterdam UMC, Amsterdam, The Netherlands
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2
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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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De Rosa L, L’Abbate S, Kusmic C, Faita F. Applications of Deep Learning Algorithms to Ultrasound Imaging Analysis in Preclinical Studies on In Vivo Animals. Life (Basel) 2023; 13:1759. [PMID: 37629616 PMCID: PMC10455134 DOI: 10.3390/life13081759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 07/28/2023] [Accepted: 08/08/2023] [Indexed: 08/27/2023] Open
Abstract
BACKGROUND AND AIM Ultrasound (US) imaging is increasingly preferred over other more invasive modalities in preclinical studies using animal models. However, this technique has some limitations, mainly related to operator dependence. To overcome some of the current drawbacks, sophisticated data processing models are proposed, in particular artificial intelligence models based on deep learning (DL) networks. This systematic review aims to overview the application of DL algorithms in assisting US analysis of images acquired in in vivo preclinical studies on animal models. METHODS A literature search was conducted using the Scopus and PubMed databases. Studies published from January 2012 to November 2022 that developed DL models on US images acquired in preclinical/animal experimental scenarios were eligible for inclusion. This review was conducted according to PRISMA guidelines. RESULTS Fifty-six studies were enrolled and classified into five groups based on the anatomical district in which the DL models were used. Sixteen studies focused on the cardiovascular system and fourteen on the abdominal organs. Five studies applied DL networks to images of the musculoskeletal system and eight investigations involved the brain. Thirteen papers, grouped under a miscellaneous category, proposed heterogeneous applications adopting DL systems. Our analysis also highlighted that murine models were the most common animals used in in vivo studies applying DL to US imaging. CONCLUSION DL techniques show great potential in terms of US images acquired in preclinical studies using animal models. However, in this scenario, these techniques are still in their early stages, and there is room for improvement, such as sample sizes, data preprocessing, and model interpretability.
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Affiliation(s)
- Laura De Rosa
- Institute of Clinical Physiology, National Research Council (CNR), 56124 Pisa, Italy; (L.D.R.); (F.F.)
- Department of Information Engineering and Computer Science, University of Trento, 38123 Trento, Italy
| | - Serena L’Abbate
- Institute of Life Sciences, Scuola Superiore Sant’Anna, 56124 Pisa, Italy;
| | - Claudia Kusmic
- Institute of Clinical Physiology, National Research Council (CNR), 56124 Pisa, Italy; (L.D.R.); (F.F.)
| | - Francesco Faita
- Institute of Clinical Physiology, National Research Council (CNR), 56124 Pisa, Italy; (L.D.R.); (F.F.)
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Chen C, Perera R, Kolios MC, Wijkstra H, Mischi M, Exner AA, Turco S. Pharmacokinetic modeling of PSMA-targeted nanobubbles for quantification of extravasation and binding in mice models of prostate cancer. Med Phys 2022; 49:6547-6559. [PMID: 36049109 PMCID: PMC9588563 DOI: 10.1002/mp.15962] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Revised: 06/20/2022] [Accepted: 08/19/2022] [Indexed: 12/24/2022] Open
Abstract
PURPOSE Contrast-enhanced ultrasound (CEUS) by injection of microbubbles (MBs) has shown promise as a cost-effective imaging modality for prostate cancer (PCa) detection. More recently, nanobubbles (NBs) have been proposed as novel ultrasound contrast agents. Unlike MBs, which are intravascular ultrasound contrast agents, the smaller diameter of NBs allows them to cross the vessel wall and target specific receptors on cancer cells such as the prostate-specific membrane antigen (PSMA). It has been demonstrated that PSMA-targeted NBs can bind to the receptors of PCa cells and show a prolonged retention effect in dual-tumor mice models. However, the analysis of the prolonged retention effect has so far been limited to qualitative or semi-quantitative approaches. METHODS This work introduces two pharmacokinetics models for quantitative analysis of time-intensity curves (TICs) obtained from the CEUS loops. The first model is based on describing the vascular input by the modified local density random walk (mLDRW) model and independently interprets TICs from each tumor lesion. Differently, the second model is based on the reference-tissue model, previously proposed in the context of nuclear imaging, and describes the binding kinetics of an indicator in a target tissue by using a reference tissue where binding does not occur. RESULTS Our results show that four estimated parameters, β,β / λ $\beta /\lambda $ ,β + / β - ${\beta }_ + /{\beta }_ - $ , for the mLDRW-input model, and γ for the reference-based model, were significantly different (p-value <0.05) between free NBs and PSMA-NBs. These parameters estimated by the two models demonstrate different behaviors between PSMA-targeted and free NBs. CONCLUSIONS These promising results encourage further quantitative analysis of targeted NBs for improved cancer diagnostics and characterization.
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Affiliation(s)
- Chuan Chen
- Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Reshani Perera
- Case Western Reserve University, Cleveland, Ohio, United States
| | | | - Hessel Wijkstra
- Eindhoven University of Technology, Eindhoven, the Netherlands
- Universtity Medical Center Amsterdam, Amsterdam, the Netherlands
| | - Massimo Mischi
- Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Agata A. Exner
- Case Western Reserve University, Cleveland, Ohio, United States
| | - Simona Turco
- Eindhoven University of Technology, Eindhoven, the Netherlands
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5
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Gurwin A, Kowalczyk K, Knecht-Gurwin K, Stelmach P, Nowak Ł, Krajewski W, Szydełko T, Małkiewicz B. Alternatives for MRI in Prostate Cancer Diagnostics-Review of Current Ultrasound-Based Techniques. Cancers (Basel) 2022; 14:1859. [PMID: 35454767 PMCID: PMC9028694 DOI: 10.3390/cancers14081859] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Revised: 04/01/2022] [Accepted: 04/06/2022] [Indexed: 02/04/2023] Open
Abstract
The purpose of this review is to present the current role of ultrasound-based techniques in the diagnostic pathway of prostate cancer (PCa). With overdiagnosis and overtreatment of a clinically insignificant PCa over the past years, multiparametric magnetic resonance imaging (mpMRI) started to be recommended for every patient suspected of PCa before performing a biopsy. It enabled targeted sampling of the suspicious prostate regions, improving the accuracy of the traditional systematic biopsy. However, mpMRI is associated with high costs, relatively low availability, long and separate procedure, or exposure to the contrast agent. The novel ultrasound modalities, such as shear wave elastography (SWE), contrast-enhanced ultrasound (CEUS), or high frequency micro-ultrasound (MicroUS), may be capable of maintaining the performance of mpMRI without its limitations. Moreover, the real-time lesion visualization during biopsy would significantly simplify the diagnostic process. Another value of these new techniques is the ability to enhance the performance of mpMRI by creating the image fusion of multiple modalities. Such models might be further analyzed by artificial intelligence to mark the regions of interest for investigators and help to decide about the biopsy indications. The dynamic development and promising results of new ultrasound-based techniques should encourage researchers to thoroughly study their utilization in prostate imaging.
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Affiliation(s)
- Adam Gurwin
- University Center of Excellence in Urology, Department of Minimally Invasive and Robotic Urology, Wroclaw Medical University, 50-556 Wroclaw, Poland; (K.K.); (P.S.); (Ł.N.); (W.K.); (T.S.)
| | - Kamil Kowalczyk
- University Center of Excellence in Urology, Department of Minimally Invasive and Robotic Urology, Wroclaw Medical University, 50-556 Wroclaw, Poland; (K.K.); (P.S.); (Ł.N.); (W.K.); (T.S.)
| | - Klaudia Knecht-Gurwin
- Department of Dermatology, Venereology and Allergology, Wroclaw Medical University, 50-368 Wroclaw, Poland;
| | - Paweł Stelmach
- University Center of Excellence in Urology, Department of Minimally Invasive and Robotic Urology, Wroclaw Medical University, 50-556 Wroclaw, Poland; (K.K.); (P.S.); (Ł.N.); (W.K.); (T.S.)
| | - Łukasz Nowak
- University Center of Excellence in Urology, Department of Minimally Invasive and Robotic Urology, Wroclaw Medical University, 50-556 Wroclaw, Poland; (K.K.); (P.S.); (Ł.N.); (W.K.); (T.S.)
| | - Wojciech Krajewski
- University Center of Excellence in Urology, Department of Minimally Invasive and Robotic Urology, Wroclaw Medical University, 50-556 Wroclaw, Poland; (K.K.); (P.S.); (Ł.N.); (W.K.); (T.S.)
| | - Tomasz Szydełko
- University Center of Excellence in Urology, Department of Minimally Invasive and Robotic Urology, Wroclaw Medical University, 50-556 Wroclaw, Poland; (K.K.); (P.S.); (Ł.N.); (W.K.); (T.S.)
| | - Bartosz Małkiewicz
- University Center of Excellence in Urology, Department of Minimally Invasive and Robotic Urology, Wroclaw Medical University, 50-556 Wroclaw, Poland; (K.K.); (P.S.); (Ł.N.); (W.K.); (T.S.)
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Panfilova A, Chen P, van Sloun RJG, Wijkstra H, Postema M, Poortinga AT, Mischi M. Experimental acoustic characterization of an endoskeletal antibubble contrast agent: First results. Med Phys 2021; 48:6765-6780. [PMID: 34580883 PMCID: PMC9293338 DOI: 10.1002/mp.15242] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 09/03/2021] [Accepted: 09/07/2021] [Indexed: 11/11/2022] Open
Abstract
Purpose An antibubble is an encapsulated gas bubble with an incompressible inclusion inside the gas phase. Current‐generation ultrasound contrast agents are bubble‐based: they contain encapsulated gas bubbles with no inclusions. The objective of this work is to determine the linear and nonlinear responses of an antibubble contrast agent in comparison to two bubble‐based ultrasound contrast agents, that is, reference bubbles and SonoVueTM. Methods Side scatter and attenuation of the three contrast agents were measured, using single‐element ultrasound transducers, operating at 1.0, 2.25, and 3.5 MHz. The scatter measurements were performed at acoustic pressures of 200 and 300 kPa for 1.0 MHz, 300 kPa, and 450 kPa for 2.25 MHz, and 370 and 560 kPa for 3.5 MHz. Attenuation measurements were conducted at pressures of 13, 55, and 50 kPa for 1.0, 2.25, and 3.5 MHz, respectively. In addition, a dynamic contrast‐enhanced ultrasound measurement was performed, imaging the contrast agent flow through a vascular phantom with a commercial diagnostic linear array probe. Results Antibubbles generated equivalent or stronger harmonic signal, compared to bubble‐based ultrasound contrast agents. The second harmonic side‐scatter amplitude of the antibubble agent was up to 3 dB greater than that of reference bubble agent and up to 4 dB greater than that of SonoVueTM at the estimated concentration of 8×104 bubbles/mL. For ultrasound with a center transmit frequency of 1.0 MHz, the attenuation coefficient of the antibubble agent was 8.7 dB/cm, whereas the attenuation coefficient of the reference agent was 7.7 and 0.3 dB/cm for SonoVueTM. At 2.25 MHz, the attenuation coefficients were 9.7, 3.0, and 0.6 dB/cm, respectively. For 3.5 MHz, they were 4.4, 1.8, and 1.0 dB/cm, respectively. A dynamic contrast‐enhanced ultrasound recording showed the nonlinear signal of the antibubble agent to be 31% greater than for reference bubbles and 23% lower than SonoVueTM at a high concentration of 2×106 bubbles/mL. Conclusion Endoskeletal antibubbles generate comparable or greater higher harmonics than reference bubbles and SonoVueTM. As a result, antibubbles with liquid therapeutic agents inside the gas phase have high potential to become a traceable therapeutic agent.
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Affiliation(s)
- Anastasiia Panfilova
- Electrical Engineering Department, Faculty of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Peiran Chen
- Electrical Engineering Department, Faculty of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Ruud J G van Sloun
- Electrical Engineering Department, Faculty of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Hessel Wijkstra
- Electrical Engineering Department, Faculty of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.,Department of Urology, Amsterdam University Medical Centers location AMC, Amsterdam, The Netherlands
| | - Michiel Postema
- School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, Braamfontein, South Africa.,BioMediTech, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Albert T Poortinga
- Mechanical Engineering Department, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Massimo Mischi
- Electrical Engineering Department, Faculty of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
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7
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Panfilova A, van Sloun RJG, Wijkstra H, Sapozhnikov OA, Mischi M. A review on B/A measurement methods with a clinical perspective. THE JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA 2021; 149:2200. [PMID: 33940890 DOI: 10.1121/10.0003627] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Accepted: 02/12/2021] [Indexed: 06/12/2023]
Abstract
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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Affiliation(s)
- Anastasiia Panfilova
- Electrical Engineering Department, Faculty of Electrical Engineering, Eindhoven University of Technology, Groene Loper 35612 AE, Eindhoven, The Netherlands
| | - Ruud J G van Sloun
- Electrical Engineering Department, Faculty of Electrical Engineering, Eindhoven University of Technology, Groene Loper 35612 AE, Eindhoven, The Netherlands
| | - Hessel Wijkstra
- Electrical Engineering Department, Faculty of Electrical Engineering, Eindhoven University of Technology, Groene Loper 35612 AE, Eindhoven, The Netherlands
| | - Oleg A Sapozhnikov
- Department of Acoustics, Physics Faculty, Moscow State University, Leninskie Gory, Moscow 119991, Russia
| | - Massimo Mischi
- Electrical Engineering Department, Faculty of Electrical Engineering, Eindhoven University of Technology, Groene Loper 35612 AE, Eindhoven, The Netherlands
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8
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9
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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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10
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Mannaerts CK, Engelbrecht MRW, Postema AW, van Kollenburg RAA, Hoeks CMA, Savci-Heijink CD, Van Sloun RJG, Wildeboer RR, De Reijke TM, Mischi M, Wijkstra H. 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; 126:481-493. [PMID: 32315112 DOI: 10.1111/bju.15093] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
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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Affiliation(s)
- Christophe K Mannaerts
- Department of Urology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Marc R W Engelbrecht
- Department of Radiology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Arnoud W Postema
- Department of Urology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Rob A A van Kollenburg
- Department of Urology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Caroline M A Hoeks
- Department of Radiology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Cemile Dilara Savci-Heijink
- Department of Pathology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Ruud J G Van Sloun
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Rogier R Wildeboer
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Theo M De Reijke
- Department of Urology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Massimo Mischi
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Hessel Wijkstra
- Department of Urology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands.,Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
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11
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Correas JM, Halpern EJ, Barr RG, Ghai S, Walz J, Bodard S, Dariane C, de la Rosette J. Advanced ultrasound in the diagnosis of prostate cancer. World J Urol 2020; 39:661-676. [PMID: 32306060 DOI: 10.1007/s00345-020-03193-0] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Accepted: 03/30/2020] [Indexed: 12/17/2022] Open
Abstract
The diagnosis of prostate cancer (PCa) can be challenging due to the limited performance of current diagnostic tests, including PSA, digital rectal examination and transrectal conventional US. Multiparametric MRI has improved PCa diagnosis and is recommended prior to biopsy; however, mp-MRI does miss a substantial number of PCa. Advanced US modalities include transrectal prostate elastography and contrast-enhanced US, as well as improved B-mode, micro-US and micro-Doppler techniques. These techniques can be combined to define a novel US approach, multiparametric US (mp-US). Mp-US improves PCa diagnosis but is not sufficiently accurate to obviate the utility of mp-MRI. Mp-US using advanced techniques and mp-MRI provide complementary information which will become even more important in the era of focal therapy, where precise identification of PCa location is needed.
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Affiliation(s)
- Jean-Michel Correas
- Department of Adult Radiology, Paris University and Necker University Hospital, 149 rue de Sèvres, 75015, Paris Cedex 15, France.
| | - Ethan J Halpern
- Department of Radiology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Richard G Barr
- Department of Radiology, Northeastern Ohio Medical University, Rootstown, OH, USA
| | - Sangeet Ghai
- Department of Medical Imaging, Princess Margaret Cancer Centre and University of Toronto, Toronto, ON, Canada
| | - Jochen Walz
- Department of Urology, Institut Paoli-Calmettes Cancer Centre, Marseille, France
| | - Sylvain Bodard
- Department of Adult Radiology, Paris University and Necker University Hospital, 149 rue de Sèvres, 75015, Paris Cedex 15, France
| | - Charles Dariane
- Department of Urology, Paris University and European Hospital Georges Pompidou, Paris, France
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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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13
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Contrast-enhanced ultrasound with dispersion analysis for the localization of prostate cancer: correlation with radical prostatectomy specimens. World J Urol 2020; 38:2811-2818. [PMID: 32078707 DOI: 10.1007/s00345-020-03103-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Accepted: 01/21/2020] [Indexed: 10/25/2022] Open
Abstract
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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14
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Feng Y, Yang F, Zhou X, Guo Y, Tang F, Ren F, Guo J, Ji S. A Deep Learning Approach for Targeted Contrast-Enhanced Ultrasound Based Prostate Cancer Detection. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2019; 16:1794-1801. [PMID: 29993750 DOI: 10.1109/tcbb.2018.2835444] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
The important role of angiogenesis in cancer development has driven many researchers to investigate the prospects of noninvasive cancer diagnosis based on the technology of contrast-enhanced ultrasound (CEUS) imaging. This paper presents a deep learning framework to detect prostate cancer in the sequential CEUS images. The proposed method uniformly extracts features from both the spatial and the temporal dimensions by performing three-dimensional convolution operations, which captures the dynamic information of the perfusion process encoded in multiple adjacent frames for prostate cancer detection. The deep learning models were trained and validated against expert delineations over the CEUS images recorded using two types of contrast agents, i.e., the anti-PSMA based agent targeted to prostate cancer cells and the non-targeted blank agent. Experiments showed that the deep learning method achieved over 91 percent specificity and 90 percent average accuracy over the targeted CEUS images for prostate cancer detection, which was superior ( ) than previously reported approaches and implementations.
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15
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Wildeboer RR, Mannaerts CK, van Sloun RJG, Budäus L, Tilki D, Wijkstra H, Salomon G, Mischi M. Automated multiparametric localization of prostate cancer based on B-mode, shear-wave elastography, and contrast-enhanced ultrasound radiomics. Eur Radiol 2019; 30:806-815. [PMID: 31602512 PMCID: PMC6957554 DOI: 10.1007/s00330-019-06436-w] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2019] [Accepted: 08/27/2019] [Indexed: 12/17/2022]
Abstract
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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Affiliation(s)
- Rogier R Wildeboer
- Lab of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, De Rondom 70, 5612 AP, Eindhoven, The Netherlands.
| | - Christophe K Mannaerts
- Department of Urology, Amsterdam University Medical Centers, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
| | - Ruud J G van Sloun
- Lab of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, De Rondom 70, 5612 AP, Eindhoven, The Netherlands
| | - Lars Budäus
- Martini-Clinic - Prostate Cancer Center, University Hospital Hamburg Eppendorf, Martinistraße 52, 20246, Hamburg, Germany
| | - Derya Tilki
- Martini-Clinic - Prostate Cancer Center, University Hospital Hamburg Eppendorf, Martinistraße 52, 20246, Hamburg, Germany.,Department of Urology, University Hospital Hamburg-Eppendorf, Martinistraße 52, 20251, Hamburg, Germany
| | - Hessel Wijkstra
- Lab of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, De Rondom 70, 5612 AP, Eindhoven, The Netherlands.,Department of Urology, Amsterdam University Medical Centers, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
| | - Georg Salomon
- Martini-Clinic - Prostate Cancer Center, University Hospital Hamburg Eppendorf, Martinistraße 52, 20246, Hamburg, Germany
| | - Massimo Mischi
- Lab of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, De Rondom 70, 5612 AP, Eindhoven, The Netherlands
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16
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Solomon O, van Sloun RJG, Wijkstra H, Mischi M, Eldar YC. Exploiting Flow Dynamics for Superresolution in Contrast-Enhanced Ultrasound. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2019; 66:1573-1586. [PMID: 31265391 DOI: 10.1109/tuffc.2019.2926062] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
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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17
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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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18
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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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19
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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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20
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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; 18:98. [PMID: 30409150 PMCID: PMC6225621 DOI: 10.1186/s12894-018-0409-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Accepted: 10/17/2018] [Indexed: 02/07/2023] Open
Abstract
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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21
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Evaluation of Dispersion MRI for Improved Prostate Cancer Diagnosis in a Multicenter Study. AJR Am J Roentgenol 2018; 211:W242-W251. [DOI: 10.2214/ajr.17.19215] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
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22
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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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Wei C, Li C, Szewczyk-Bieda M, Upreti D, Lang S, Huang Z, Nabi G. Performance Characteristics of Transrectal Shear Wave Elastography Imaging in the Evaluation of Clinically Localized Prostate Cancer: A Prospective Study. J Urol 2018; 200:549-558. [DOI: 10.1016/j.juro.2018.03.116] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/22/2018] [Indexed: 12/01/2022]
Affiliation(s)
- Cheng Wei
- Division of Cancer Research, School of Medicine, University of Dundee, Ninewells Hospital, Dundee, United Kingdom
- School of Science and Engineering, University of Dundee, Dundee, United Kingdom
| | - Chunhui Li
- School of Science and Engineering, University of Dundee, Dundee, United Kingdom
| | | | - Dilip Upreti
- Division of Cancer Research, School of Medicine, University of Dundee, Ninewells Hospital, Dundee, United Kingdom
| | - Stephen Lang
- Department of Pathology, Ninewells Hospital, Dundee, United Kingdom
| | - Zhihong Huang
- School of Science and Engineering, University of Dundee, Dundee, United Kingdom
| | - Ghulam Nabi
- Division of Cancer Research, School of Medicine, University of Dundee, Ninewells Hospital, Dundee, United Kingdom
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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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25
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van Sloun RJ, Demi L, Wijkstra H, Mischi M. Mammography: developing a smarter and safer alternative. Future Oncol 2017; 13:669-671. [PMID: 28266250 DOI: 10.2217/fon-2017-0029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Affiliation(s)
- Ruud Jg van Sloun
- Lab. of Biomedical Diagnostics, Eindhoven University of Technology, The Netherlands
| | | | - Hessel Wijkstra
- Lab. of Biomedical Diagnostics, Eindhoven University of Technology, The Netherlands.,Academical Medical Center, University of Amsterdam, The Netherlands
| | - Massimo Mischi
- Lab. of Biomedical Diagnostics, Eindhoven University of Technology, The Netherlands
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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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Turco S, Tardy I, Frinking P, Wijkstra H, Mischi M. Quantitative ultrasound molecular imaging by modeling the binding kinetics of targeted contrast agent. Phys Med Biol 2017; 62:2449-2464. [DOI: 10.1088/1361-6560/aa5e9a] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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