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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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Chen C, Turco S, Kapetas P, Mann R, Wijkstra H, de Korte C, Mischi M. Spatiotemporal analysis of contrast-enhanced ultrasound for differentiating between malignant and benign breast lesions. Eur Radiol 2024; 34:4764-4773. [PMID: 38112765 DOI: 10.1007/s00330-023-10500-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 10/02/2023] [Accepted: 10/29/2023] [Indexed: 12/21/2023]
Abstract
OBJECTIVES The aim of this study was to apply spatiotemporal analysis of contrast-enhanced ultrasound (CEUS) loops to quantify the enhancement heterogeneity for improving the differentiation between benign and malignant breast lesions. MATERIALS AND METHODS This retrospective study included 120 women (age range, 18-82 years; mean, 52 years) scheduled for ultrasound-guided biopsy. With the aid of brightness-mode images, the border of each breast lesion was delineated in the CEUS images. Based on visual evaluation and quantitative metrics, the breast lesions were categorized into four grades of different levels of contrast enhancement. Grade-1 (hyper-enhanced) and grade-2 (partly-enhanced) breast lesions were included in the analysis. Four parameters reflecting enhancement heterogeneity were estimated by spatiotemporal analysis of neighboring time-intensity curves (TICs). By setting the threshold on mean parameter, the diagnostic performance of the four parameters for differentiating benign and malignant lesions was evaluated. RESULTS Sixty-four of the 120 patients were categorized as grade 1 or 2 and used for estimating the four parameters. At the pixel level, mutual information and conditional entropy present significantly different values between the benign and malignant lesions (p < 0.001 in patients of grade 1, p = 0.002 in patients of grade 1 or 2). For the classification of breast lesions, mutual information produces the best diagnostic performance (AUC = 0.893 in patients of grade 1, AUC = 0.848 in patients of grade 1 or 2). CONCLUSIONS The proposed spatiotemporal analysis for assessing the enhancement heterogeneity shows promising results to aid in the diagnosis of breast cancer by CEUS. CLINICAL RELEVANCE STATEMENT The proposed spatiotemporal method can be developed as a standardized software to automatically quantify the enhancement heterogeneity of breast cancer on CEUS, possibly leading to the improved diagnostic accuracy of differentiation between benign and malignant lesions. KEY POINTS • Advanced spatiotemporal analysis of ultrasound contrast-enhanced loops for aiding the differentiation of malignant or benign breast lesions. • Four parameters reflecting the enhancement heterogeneity were estimated in the hyper- and partly-enhanced breast lesions by analyzing the neighboring pixel-level time-intensity curves. • For the classification of hyper-enhanced breast lesions, mutual information produces the best diagnostic performance (AUC = 0.893).
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Affiliation(s)
- Chuan Chen
- Eindhoven University of Technology, Eindhoven, Netherlands.
- Southeast University, Nanjing, China.
| | - Simona Turco
- Eindhoven University of Technology, Eindhoven, Netherlands
| | | | - Ritse Mann
- Radboud University Medical Center, Nijmegen, Netherlands
| | | | - Chris de Korte
- Medical University of Vienna, Vienna, Austria
- University of Twente, Enschede, Netherlands
| | - Massimo Mischi
- Eindhoven University of Technology, Eindhoven, Netherlands
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Wildeboer RR, van Sloun RJG, Wijkstra H, Mischi M. Artificial intelligence in multiparametric prostate cancer imaging with focus on deep-learning methods. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2020; 189:105316. [PMID: 31951873 DOI: 10.1016/j.cmpb.2020.105316] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Revised: 12/09/2019] [Accepted: 01/04/2020] [Indexed: 05/16/2023]
Abstract
Prostate cancer represents today the most typical example of a pathology whose diagnosis requires multiparametric imaging, a strategy where multiple imaging techniques are combined to reach an acceptable diagnostic performance. However, the reviewing, weighing and coupling of multiple images not only places additional burden on the radiologist, it also complicates the reviewing process. Prostate cancer imaging has therefore been an important target for the development of computer-aided diagnostic (CAD) tools. In this survey, we discuss the advances in CAD for prostate cancer over the last decades with special attention to the deep-learning techniques that have been designed in the last few years. Moreover, we elaborate and compare the methods employed to deliver the CAD output to the operator for further medical decision making.
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Affiliation(s)
- Rogier R Wildeboer
- Lab of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, De Zaale, 5600 MB, Eindhoven, the Netherlands.
| | - Ruud J G van Sloun
- Lab of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, De Zaale, 5600 MB, Eindhoven, the Netherlands.
| | - Hessel Wijkstra
- Lab of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, De Zaale, 5600 MB, Eindhoven, the Netherlands; Department of Urology, Amsterdam University Medical Centers, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, the Netherlands
| | - Massimo Mischi
- Lab of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, De Zaale, 5600 MB, Eindhoven, the Netherlands
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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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Jin Y, Heo H, Walker E, Krokhin A, Choi TY, Neogi A. The effects of temperature and frequency dispersion on sound speed in bulk poly (vinyl alcohol) poly (N-isopropylacrylamide) hydrogels caused by the phase transition. ULTRASONICS 2020; 104:105931. [PMID: 32156431 DOI: 10.1016/j.ultras.2019.05.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Revised: 03/26/2019] [Accepted: 05/10/2019] [Indexed: 06/10/2023]
Abstract
Bulk Poly (Vinyl Alcohol) (PVA) Poly (N-isopropyl acrylamide) (PNIPAm) hydrogel, one of the thermally responsive phase transitive hydrogels, is a versatile material due to its sharp volumetric phase transition and anomalous behaviors with facile tunability by thermal stimulation. At the lower critical solution temperature (LCST) of 33 °C, the hydrogels undergo a volumetric phase transition that causes drastic, non-monotonic change in the elastic modulus, viscosity, stiffness, and speed of sound. Here, we report the temperature and frequency dependence of the speed of sound in bulk PVA-PNIPAm hydrogel as measured by means of a planar resonant cavity. The linear response theory is applied for calculation of frequency dependent speed of sound. Comparisons find standard time of flight techniques underestimate the speed of sound by up to 6%, with variation in the frequency dependent speed of sound reaching as high as 200 m/s in the ultrasonic range of 0.2-0.8 MHz. The first characterization of frequency dependent speed of sound in PVA-PNIPAm hydrogel is addressed and delineated into its phase transition behaviors as connected to temperature. The findings can lead to better characterization of mechanical properties using ultrasonic spectroscopy, and higher resolution in ultrasonic imaging applications with dispersive media.
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Affiliation(s)
- Y Jin
- Department of Mechanical and Energy Engineering, University of North Texas, 3940 North Elm Suite F101, Denton, TX 76207, USA
| | - H Heo
- Department of Mechanical and Energy Engineering, University of North Texas, 3940 North Elm Suite F101, Denton, TX 76207, USA; Department of Physics, University of North Texas, P.O. Box 311427, Denton, TX 76203, USA
| | - E Walker
- Echonovus Inc., 1800 South Loop 288 STE 396 #234, Denton, TX 76205, USA
| | - A Krokhin
- Department of Physics, University of North Texas, P.O. Box 311427, Denton, TX 76203, USA
| | - T Y Choi
- Department of Mechanical and Energy Engineering, University of North Texas, 3940 North Elm Suite F101, Denton, TX 76207, USA.
| | - A Neogi
- Department of Physics, University of North Texas, P.O. Box 311427, Denton, TX 76203, USA; Advanced Materials and Manufacturing Processes Institute, University of North Texas, 3940 North Elm Street, Box Q, Discovery Park Annex, Denton, TX 76207, USA.
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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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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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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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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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12
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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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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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Wang D, Xu S, Zhang K, Zhang X, Yang X, Xiao M, Su Q, Wan M. A fast scheme for renal microvascular perfusion functional imaging: Assessed by an imaging quality evaluation model. Med Phys 2018; 46:738-745. [PMID: 30585642 DOI: 10.1002/mp.13358] [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: 08/07/2018] [Revised: 11/14/2018] [Accepted: 12/14/2018] [Indexed: 11/09/2022] Open
Abstract
PURPOSE This study aimed to develop a fast scheme of multiparametric perfusion functional imaging (PFI) based on dynamic contrast-enhanced ultrasound (DCEUS) for assessing renal microvascular hemodynamics. METHOD The flow process in the DCEUS-based PFI was modified step-by-step to improve its operational efficiency, which was validated through in vivo renal perfusion experiments. A multiparametric model with a comprehensive coefficient of imaging quality (CIQ) was then built on four terms of the average information entropy, contrast, gray, and noise coefficient of PFIs to evaluate the sacrifice of imaging quality during modifications of DCEUS-based PFI. RESULTS The multiparametric model successfully evaluated modifications of DCEUS-based PFI from multiple perspectives (R2 = 0.73, P < 0.01). Compared with the raw scheme in the renal sagittal and coronal planes, the fast PFI scheme significantly improved its operational efficiency by 62.82 ± 1.07% (P < 0.01) and the nine PFIs simultaneously maintained a similar CIQ of 0.26 ± 0.06. CONCLUSIONS The inhomogeneous hemodynamic distributions with a ring-like feature in the renal microvasculature were accurately and efficiently characterized by the fast PFI scheme. The fast PFI scheme can be applied for early diagnosis, follow-up evaluation and monitoring treatment of chronic kidney disease.
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Affiliation(s)
- Diya Wang
- Department of Biomedical Engineering, School of Life Science and Technology, Xi' an Jiaotong University, Xi' an, 710049, China.,Department of Radiology, Radio-Oncology and Nuclear Medicine, Institute of Biomedical Engineering, University of Montreal, Montreal, QC, H2X 0A9, Canada
| | - Shanshan Xu
- Department of Biomedical Engineering, School of Life Science and Technology, Xi' an Jiaotong University, Xi' an, 710049, China
| | - Kejia Zhang
- Department of Plastic and Cosmetic Surgery, The Eastern Division of The First Hospital of Jilin University, Changchun, 130031, China
| | - Xinyu Zhang
- Department of Biomedical Engineering, School of Life Science and Technology, Xi' an Jiaotong University, Xi' an, 710049, China
| | - Xuan Yang
- Department of Biomedical Engineering, School of Life Science and Technology, Xi' an Jiaotong University, Xi' an, 710049, China
| | - Mengnan Xiao
- Department of Biomedical Engineering, School of Life Science and Technology, Xi' an Jiaotong University, Xi' an, 710049, China
| | - Qiang Su
- Department of Oncology, Beijing Friendship Hospital, Capital Medical University, Beijing, 1000050, China
| | - Mingxi Wan
- Department of Biomedical Engineering, School of Life Science and Technology, Xi' an Jiaotong University, Xi' an, 710049, China
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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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16
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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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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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Wang D, Xiao M, Hu H, Zhang Y, Su Z, Xu S, Zong Y, Wan M. DCEUS-based focal parametric perfusion imaging of microvessel with single-pixel resolution and high contrast. ULTRASONICS 2018; 84:392-403. [PMID: 29245119 DOI: 10.1016/j.ultras.2017.11.018] [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: 01/09/2017] [Revised: 11/23/2017] [Accepted: 11/29/2017] [Indexed: 06/07/2023]
Abstract
This study aimed to develop a focal microvascular contrast-enhanced ultrasonic parametric perfusion imaging (PPI) scheme to overcome the tradeoff between the resolution, contrast, and accuracy of focal PPI in the tumor. Its resolution was limited by the low signal-to-clutter ratio (SCR) of time-intensity-curves (TICs) induced by multiple limitations, which deteriorated the accuracy and contrast of focal PPI. The scheme was verified by the in-vivo perfusion experiments. Single-pixel TICs were first extracted to ensure PPI with the highest resolution. The SCR of focal TICs in the tumor was improved using respiratory motion compensation combined with detrended fluctuation analysis. The entire and focal PPIs of six perfusion parameters were then accurately created after filtrating the valid TICs and targeted perfusion parameters. Compared with those of the conventional PPIs, the axial and lateral resolutions of focal PPIs were improved by 30.29% (p < .05) and 32.77% (p < .05), respectively; the average contrast and accuracy evaluated by SCR improved by 7.24 ± 4.90 dB (p < .05) and 5.18 ± 1.28 dB (p < .05), respectively. The edge, morphostructure, inhomogeneous hyper-enhanced distribution, and ring-like perfusion features in intratumoral microvessel were accurately distinguished and highlighted by the focal PPIs. The developed focal PPI can assist clinicians in making confirmed diagnoses and in providing appropriate therapeutic strategies for liver tumor.
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Affiliation(s)
- Diya Wang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi' an Jiaotong University, Xi' an, PR China; Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center, Montreal, QC, Canada
| | - Mengnan Xiao
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi' an Jiaotong University, Xi' an, PR China
| | - Hong Hu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi' an Jiaotong University, Xi' an, PR China
| | - Yu Zhang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi' an Jiaotong University, Xi' an, PR China
| | - Zhe Su
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi' an Jiaotong University, Xi' an, PR China
| | - Shanshan Xu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi' an Jiaotong University, Xi' an, PR China
| | - Yujin Zong
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi' an Jiaotong University, Xi' an, PR China
| | - Mingxi Wan
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi' an Jiaotong University, Xi' an, PR China.
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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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20
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Postema AW, Scheltema MJV, Mannaerts CK, Van Sloun RJG, Idzenga T, Mischi M, Engelbrecht MRE, De la Rosette JJMCH, Wijkstra H. The prostate cancer detection rates of CEUS-targeted versus MRI-targeted versus systematic TRUS-guided biopsies in biopsy-naïve men: a prospective, comparative clinical trial using the same patients. BMC Urol 2017; 17:27. [PMID: 28381220 PMCID: PMC5382402 DOI: 10.1186/s12894-017-0213-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2016] [Accepted: 03/22/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The current standard for Prostate Cancer (PCa) detection in biopsy-naïve men consists of 10-12 systematic biopsies under ultrasound guidance. This approach leads to underdiagnosis and undergrading of significant PCa while insignificant PCa may be overdiagnosed. The recent developments in MRI and Contrast Enhanced Ultrasound (CEUS) imaging have sparked an increasing interest in PCa imaging with the ultimate goal of replacing these "blind" systematic biopsies with reliable imaging-based targeted biopsies. METHODS/DESIGN In this trial, we evaluate and compare the PCa detection rates of multiparametric (mp)MRI-targeted biopsies, CEUS-targeted biopsies and systematic biopsies under ultrasound guidance in the same patients. After informed consent, 299 biopsy-naïve men will undergo mpMRI scanning and CEUS imaging 1 week prior to the prostate biopsy procedure. During the biopsy procedure, a systematic transrectal 12-core biopsy will be performed by one operator blinded for the imaging results and targeted biopsy procedure. Subsequently a maximum of 4 CEUS-targeted biopsies and/or 4 mpMRI-targeted biopsies of predefined locations determined by an expert CEUS reader using quantification techniques and an expert radiologist, respectively, will be taken by a second operator using an MRI-US fusion device. The primary outcome is the detection rate of PCa (all grades) and clinically significant PCa (defined as Gleason score ≥7) compared between the three biopsy protocols. DISCUSSION This trial compares the detection rate of (clinically significant) PCa, between both traditional systematic biopsies and targeted biopsies based on predefined regions of interest identified by two promising imaging technologies. It follows published recommendations on study design for the evaluation of imaging guided prostate biopsy techniques, minimizing bias and allowing data pooling. It is the first trial to combine mpMRI imaging and advanced CEUS imaging with quantification. TRIAL REGISTRATION The Dutch Central Committee on Research Involving Human Subjects registration number NL52851.018.15, registered on 3 Nov 2015. Clinicaltrials.gov database registration number NCT02831920 , retrospectively registered on 5 July 2016.
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Affiliation(s)
- A. W. Postema
- Department of Urology, AMC University Hospital, Amsterdam, The Netherlands
| | - M. J. V. Scheltema
- Department of Urology, AMC University Hospital, Amsterdam, The Netherlands
| | - C. K. Mannaerts
- Department of Urology, AMC University Hospital, Amsterdam, The Netherlands
| | - R. J. G. Van Sloun
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - T. Idzenga
- Department of Urology, AMC University Hospital, Amsterdam, The Netherlands
| | - M. Mischi
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | | | | | - H. Wijkstra
- Department of Urology, AMC University Hospital, Amsterdam, The Netherlands
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, 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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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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23
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Hong-Xia Z, Wen H, Ling-Gang C, Wen-Jia C, Shuo L, Li-Juan D, Hai-Man S, Yang Z. A New Method for Discriminating between Bronchial and Pulmonary Arterial Phases using Contrast-Enhanced Ultrasound. ULTRASOUND IN MEDICINE & BIOLOGY 2016; 42:1441-1449. [PMID: 27067416 DOI: 10.1016/j.ultrasmedbio.2016.01.029] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2015] [Revised: 01/10/2016] [Accepted: 01/23/2016] [Indexed: 06/05/2023]
Abstract
This study aimed to explore the value of a real-time comparative observation method using contrast-enhanced ultrasound (CEUS) for discriminating between bronchial and pulmonary arterial phases in diagnosing lung diseases. Forty-nine patients with 50 pulmonary lesions (45 peripheral lesions and five central lesions with obstructive atelectasis, including 36 malignant tumors, five tuberculomas, four inflammatory pseudotumors and five pneumonia lesions) detected via computed tomography and visible on ultrasonography were enrolled in this study. The arterial phases were determined by comparing contrast agent arrival time (AT) in the peripheral lung lesion with that in adjacent lung tissue, referred to as a real-time comparative observation method. Detection rates of this observation method were 100% (50/50) for pulmonary arterial phase and 88% (44/50) for bronchial arterial phase. Using the instrument's built-in graphing and analysis software, a time-intensity curve was constructed based on a chosen region of interest within the lesion where enhancement was the most obvious. Commonly used perfusion indicators in CEUS, such as AT, time-to-peak and peak intensity, were obtained from the time-intensity curve. Percutaneous puncture biopsies were performed under ultrasound guidance, and specimens of all 50 lesions were examined pathologically. AT was significantly shorter in patients with pneumonia than in those with malignant tumors or chronic inflammation (p < 0.05), whereas no difference was seen between those with malignant tumors and those with chronic inflammation. No significant differences in time-to-peak or peak intensity were seen among those with various lung diseases (p > 0.05). This is the first description of a real-time comparative observation method using CEUS for determining the arterial phases in the lungs. This method is accurate, simple to perform and provides a direct display. It is expected to become a practical and feasible tool for diagnosing lung diseases.
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Affiliation(s)
- Zhang Hong-Xia
- Ultrasonography Department, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - He Wen
- Ultrasonography Department, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
| | - Cheng Ling-Gang
- Ultrasonography Department, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Cai Wen-Jia
- Ultrasonography Department, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Li Shuo
- Ultrasonography Department, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Du Li-Juan
- Ultrasonography Department, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Song Hai-Man
- Ultrasonography Department, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zhao Yang
- Ultrasonography Department, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
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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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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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Postema A, Mischi M, de la Rosette J, Wijkstra H. Multiparametric ultrasound in the detection of prostate cancer: a systematic review. World J Urol 2015; 33:1651-9. [PMID: 25761736 PMCID: PMC4617844 DOI: 10.1007/s00345-015-1523-6] [Citation(s) in RCA: 71] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2015] [Accepted: 02/28/2015] [Indexed: 12/20/2022] Open
Abstract
PURPOSE To investigate the advances and clinical results of the different ultrasound modalities and the progress in combining them into multiparametric UltraSound (mpUS). METHODS A systematic literature search on mpUS and the different ultrasound modalities included: greyscale ultrasound, computerized transrectal ultrasound, Doppler and power Doppler techniques, dynamic contrast-enhanced ultrasound and (shear wave) elastography. RESULTS Limited research available on combining ultrasound modalities has presented improvement in diagnostic performance. The data of two studies suggest that even adding a lower performing ultrasound modality to a better performing modality using crude methods can already improve the sensitivity by 13-51 %. The different modalities detect different tumours. No study has tried to combine ultrasound modalities employing a system similar to the PIRADS system used for mpMRI or more advanced classifying algorithms. CONCLUSION Available evidence confirms that combining different ultrasound modalities significantly improves diagnostic performance.
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Affiliation(s)
- Arnoud Postema
- Department of Urology, Academic Medical Center, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands.
| | - Massimo Mischi
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Jean de la Rosette
- Department of Urology, Academic Medical Center, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
| | - Hessel Wijkstra
- Department of Urology, Academic Medical Center, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
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Mischi M, Wijkstra H. Contrast dispersion imaging for cancer localization. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2015; 2014:4268-71. [PMID: 25570935 DOI: 10.1109/embc.2014.6944567] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Cancer growth is associated with angiogenic processes in many types of cancer. Several imaging strategies have therefore been developed that target angiogenesis as a marker for cancer localization. To this end, intravascular and extravascular tissue perfusion is typically assessed by dynamic contrast enhanced (DCE) ultrasound (US) and MRI. All the proposed strategies, however, overlook important changes in the microvascular architecture that result from angiogenic processes. To overcome these limitations, we have recently introduced a new imaging strategy that analyzes the intravascular dispersion kinetics of contrast agents spreading through the microvasculature. Contrast dispersion is mainly determined by microvascular multi-path trajectories, reflecting the underlying microvascular architecture. This paper reviews the results obtained for prostate cancer localization by US and MRI dispersion imaging, also presenting the latest new developments and future perspectives.
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Schalk SG, Demi L, Smeenge M, Mills DM, Wallace KD, de la Rosette JJMCH, Wijkstra H, Mischi M. 4-D spatiotemporal analysis of ultrasound contrast agent dispersion for prostate cancer localization: a feasibility study. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2015; 62:839-851. [PMID: 25965678 DOI: 10.1109/tuffc.2014.006907] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Currently, nonradical treatment for prostate cancer is hampered by the lack of reliable diagnostics. Contrastultrasound dispersion imaging (CUDI) has recently shown great potential as a prostate cancer imaging technique. CUDI estimates the local dispersion of intravenously injected contrast agents, imaged by transrectal dynamic contrast-enhanced ultrasound (DCE-US), to detect angiogenic processes related to tumor growth. The best CUDI results have so far been obtained by similarity analysis of the contrast kinetics in neighboring pixels. To date, CUDI has been investigated in 2-D only. In this paper, an implementation of 3-D CUDI based on spatiotemporal similarity analysis of 4-D DCE-US is described. Different from 2-D methods, 3-D CUDI permits analysis of the entire prostate using a single injection of contrast agent. To perform 3-D CUDI, a new strategy was designed to estimate the similarity in the contrast kinetics at each voxel, and data processing steps were adjusted to the characteristics of 4-D DCE-US images. The technical feasibility of 4-D DCE-US in 3-D CUDI was assessed and confirmed. Additionally, in a preliminary validation in two patients, dispersion maps by 3-D CUDI were quantitatively compared with those by 2-D CUDI and with 12-core systematic biopsies with promising results.
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Mischi M, Demi L, Smeenge M, Kuenen MPJ, Postema AW, de la Rosette JJMCH, Wijkstra H. Transabdominal contrast-enhanced ultrasound imaging of the prostate. ULTRASOUND IN MEDICINE & BIOLOGY 2015; 41:1112-1118. [PMID: 25701535 DOI: 10.1016/j.ultrasmedbio.2014.10.014] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2014] [Revised: 10/22/2014] [Accepted: 10/24/2014] [Indexed: 06/04/2023]
Abstract
Numerous age-related pathologies affect the prostate gland, the most menacing of which is prostate cancer (PCa). The diagnostic tools for prostate investigation are invasive, requiring biopsies when PCa is suspected. Novel dynamic contrast-enhanced ultrasound (DCE-US) imaging approaches have been proposed recently and appear promising for minimally invasive localization of PCa. Ultrasound imaging of the prostate is traditionally performed with a transrectal probe because the location of the prostate allows for high-resolution images using high-frequency transducers. However, DCE-US imaging requires lower frequencies to induce bubble resonance and, thus, improve contrast-to-tissue ratio. For this reason, in this study we investigate the feasibility of quantitative DCE-US imaging of the prostate via the abdomen. The study included 10 patients (age = 60.7 ± 5.7 y) referred for a needle biopsy study. After having given informed consent, patients underwent DCE-US with both transabdominal and transrectal probes. Time-intensity contrast curves were derived using both approaches and their model-fit quality was compared. Although further improvements are expected by optimization of the transabdominal settings, the results of transabdominal and transrectal DCE-US are closely comparable, confirming the feasibility of transabdominal DCE-US; transabdominal curve fitting revealed an average determination coefficient r(2) = 0.91 (r(2) > 0.75 for 78.6% of all prostate pixels) compared with r(2) = 0.91 (r(2) > 0.75 for 81.6% of all prostate pixels) by the transrectal approach. Replacing the transrectal approach with more acceptable transabdominal scanning for prostate investigation is feasible. This approach would improve patient comfort and represent a useful option for PCa localization and monitoring.
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Affiliation(s)
- Massimo Mischi
- Electrical Engineering Department, Eindhoven University of Technology, Eindhoven, The Netherlands.
| | - Libertario Demi
- Electrical Engineering Department, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Martijn Smeenge
- Urology Department, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Maarten P J Kuenen
- Electrical Engineering Department, Eindhoven University of Technology, Eindhoven, The Netherlands; Urology Department, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Arnoud W Postema
- Urology Department, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | | | - Hessel Wijkstra
- Electrical Engineering Department, Eindhoven University of Technology, Eindhoven, The Netherlands; Urology Department, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
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Fontanarosa D, van der Meer S, Bamber J, Harris E, O'Shea T, Verhaegen F. Review of ultrasound image guidance in external beam radiotherapy: I. Treatment planning and inter-fraction motion management. Phys Med Biol 2015; 60:R77-114. [PMID: 25592664 DOI: 10.1088/0031-9155/60/3/r77] [Citation(s) in RCA: 72] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
In modern radiotherapy, verification of the treatment to ensure the target receives the prescribed dose and normal tissues are optimally spared has become essential. Several forms of image guidance are available for this purpose. The most commonly used forms of image guidance are based on kilovolt or megavolt x-ray imaging. Image guidance can also be performed with non-harmful ultrasound (US) waves. This increasingly used technique has the potential to offer both anatomical and functional information.This review presents an overview of the historical and current use of two-dimensional and three-dimensional US imaging for treatment verification in radiotherapy. The US technology and the implementation in the radiotherapy workflow are described. The use of US guidance in the treatment planning process is discussed. The role of US technology in inter-fraction motion monitoring and management is explained, and clinical studies of applications in areas such as the pelvis, abdomen and breast are reviewed. A companion review paper (O'Shea et al 2015 Phys. Med. Biol. submitted) will extensively discuss the use of US imaging for intra-fraction motion quantification and novel applications of US technology to RT.
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Affiliation(s)
- Davide Fontanarosa
- Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Developmental Biology, Maastricht University Medical Center (MUMC), Maastricht 6201 BN, the Netherlands. Oncology Solutions Department, Philips Research, High Tech Campus 34, Eindhoven 5656 AE, the Netherlands
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