3D estimation of soft biological tissue deformation from radio-frequency ultrasound volume acquisitions

The current research and development of 2D (matrix-shaped) transducer arrays to acquire 3D ultrasound data sets provides new insights into medical ultrasound applications and in particular into elastography. Until very recently, tissue strain estimation techniques commonly used in elastography were...

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Veröffentlicht in:	Medical image analysis Jg. 13; H. 1; S. 116 - 127
Hauptverfasser:	Deprez, Jean-François, Brusseau, Elisabeth, Schmitt, Cédric, Cloutier, Guy, Basset, Olivier
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Netherlands Elsevier B.V 01.02.2009 Elsevier
Schlagworte:	Acoustics Algorithms Bioengineering Biomechanics Breast Neoplasms - diagnostic imaging Breast Neoplasms - physiopathology Computer Science Elastic Modulus Elasticity Imaging Techniques - methods Elastography Engineering Sciences Female Fluid mechanics Fluids mechanics Humans Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image Processing Imaging Imaging, Three-Dimensional - methods Life Sciences Mechanics Mechanics of materials Medical Imaging Physics Radio Waves Reproducibility of Results Sensitivity and Specificity Signal and Image Processing Strain estimation Stress, Mechanical Ultrasonography, Mammary - methods Ultrasound Strain estimation Image processing Elastography Ultrasound
ISSN:	1361-8415, 1361-8423, 1361-8423
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Abstract	The current research and development of 2D (matrix-shaped) transducer arrays to acquire 3D ultrasound data sets provides new insights into medical ultrasound applications and in particular into elastography. Until very recently, tissue strain estimation techniques commonly used in elastography were mainly 1D or 2D methods. In this paper, a 3D technique estimating biological soft tissue deformation under load from ultrasound radiofrequency volume acquisitions is introduced. This method locally computes axial strains, while considering lateral and elevational motions. Optimal deformation parameters are estimated as those maximizing a similarity criterion, defined as the normalized correlation coefficient, between an initial region and its deformed version, when the latter is compensated for according to these parameters. The performance of our algorithm was assessed with numerical data reproducing the configuration of breast cancer, as well as a physical phantom mimicking a pressure ulcer. Simulation results show that the estimated strain fields are very close to the theoretical values, perfectly discriminating between the harder lesion and the surrounding medium. Experimental strain images of the physical phantom demonstrated the different structures of the medium, even though they are not all detectable on the ultrasound scans. Finally, both simulated and experimental results demonstrate the ability of our algorithm to provide good-quality elastograms, even in the conditions of significant out-of-plane motion.
AbstractList	The current research and development of 2D (matrix-shaped) transducer arrays to acquire 3D ultrasound data sets provides new insights into medical ultrasound applications and in particular into elastography. Until very recently, tissue strain estimation techniques commonly used in elastography were mainly 1D or 2D methods. In this paper, a 3D technique estimating biological soft tissue deformation under load from ultrasound radiofrequency volume acquisitions is introduced. This method locally computes axial strains, while considering lateral and elevational motions. Optimal deformation parameters are estimated as those maximizing a similarity criterion, defined as the normalized correlation coefficient, between an initial region and its deformed version, when the latter is compensated for according to these parameters. The performance of our algorithm was assessed with numerical data reproducing the configuration of breast cancer, as well as a physical phantom mimicking a pressure ulcer. Simulation results show that the estimated strain fields are very close to the theoretical values, perfectly discriminating between the harder lesion and the surrounding medium. Experimental strain images of the physical phantom demonstrated the different structures of the medium, even though they are not all detectable on the ultrasound scans. Finally, both simulated and experimental results demonstrate the ability of our algorithm to provide good-quality elastograms, even in the conditions of significant out-of-plane motion.The current research and development of 2D (matrix-shaped) transducer arrays to acquire 3D ultrasound data sets provides new insights into medical ultrasound applications and in particular into elastography. Until very recently, tissue strain estimation techniques commonly used in elastography were mainly 1D or 2D methods. In this paper, a 3D technique estimating biological soft tissue deformation under load from ultrasound radiofrequency volume acquisitions is introduced. This method locally computes axial strains, while considering lateral and elevational motions. Optimal deformation parameters are estimated as those maximizing a similarity criterion, defined as the normalized correlation coefficient, between an initial region and its deformed version, when the latter is compensated for according to these parameters. The performance of our algorithm was assessed with numerical data reproducing the configuration of breast cancer, as well as a physical phantom mimicking a pressure ulcer. Simulation results show that the estimated strain fields are very close to the theoretical values, perfectly discriminating between the harder lesion and the surrounding medium. Experimental strain images of the physical phantom demonstrated the different structures of the medium, even though they are not all detectable on the ultrasound scans. Finally, both simulated and experimental results demonstrate the ability of our algorithm to provide good-quality elastograms, even in the conditions of significant out-of-plane motion. The current research and development of 2D (matrix-shaped) transducer arrays to acquire 3D ultrasound data sets provides new insights into medical ultrasound applications and in particular into elastography. Until very recently, tissue strain estimation techniques commonly used in elastography were mainly 1D or 2D methods. In this paper, a 3D technique estimating biological soft tissue deformation under load from ultrasound radiofrequency volume acquisitions is introduced. This method locally computes axial strains, while considering lateral and elevational motions. Optimal deformation parameters are estimated as those maximizing a similarity criterion, defined as the normalized correlation coefficient, between an initial region and its deformed version, when the latter is compensated for according to these parameters. The performance of our algorithm was assessed with numerical data reproducing the configuration of breast cancer, as well as a physical phantom mimicking a pressure ulcer. Simulation results show that the estimated strain fields are very close to the theoretical values, perfectly discriminating between the harder lesion and the surrounding medium. Experimental strain images of the physical phantom demonstrated the different structures of the medium, even though they are not all detectable on the ultrasound scans. Finally, both simulated and experimental results demonstrate the ability of our algorithm to provide good-quality elastograms, even in the conditions of significant out-of-plane motion. The current research and development of 2D (matrix-shaped) transducer arrays to acquire 3D ultrasound data sets provides new insights into medical ultrasound applications and in particular into elastography. Until very recently, tissue strain estimation techniques commonly used in elastography were mainly 1D or 2D methods. In this paper, a 3D technique estimating biological soft tissue deformation under load from ultrasound radiofrequency volume acquisitions is introduced. This method locally computes axial strains, while considering lateral and elevational motions. Optimal deformation parameters are estimated as those maximizing a similarity criterion, defined as the normalized correlation coefficient, between an initial region and its deformed version, when the latter is compensated for according to these parameters. The performance of our algorithm was assessed with numerical data reproducing the configuration of breast cancer, as well as a physical phantom mimicking a pressure ulcer. Simulation results show that the estimated strain fields are very close to the theoretical values, perfectly discriminating between the harder lesion and the surrounding medium. Experimental strain images of the physical phantom demonstrated the different structures of the medium, even though they are not all detectable on the ultrasound scans. Finally, both simulated and experimental results demonstrate the ability of our algorithm to provide good-quality elastograms, even in the conditions of significant out-of-plane motion.
Author	Schmitt, Cédric Deprez, Jean-François Cloutier, Guy Brusseau, Elisabeth Basset, Olivier
Author_xml	– sequence: 1 givenname: Jean-François surname: Deprez fullname: Deprez, Jean-François email: deprez@creatis.insa-lyon.fr organization: CREATIS, Université de Lyon, INSA de Lyon, Université Lyon 1, CNRS UMR 5220, INSERM U 630, Bâtiment Blaise Pascal, 7 avenue Jean Capelle, F-69621 Villeurbanne, France – sequence: 2 givenname: Elisabeth surname: Brusseau fullname: Brusseau, Elisabeth organization: CREATIS, Université de Lyon, INSA de Lyon, Université Lyon 1, CNRS UMR 5220, INSERM U 630, Bâtiment Blaise Pascal, 7 avenue Jean Capelle, F-69621 Villeurbanne, France – sequence: 3 givenname: Cédric surname: Schmitt fullname: Schmitt, Cédric organization: Laboratoire de Biorhéologie et d’Ultrasonographie Médicale (LBUM), Centre Hospitalier de l’Universite de Montreal, Hopital Notre-Dame, Pavillon J.A de Seve (Y-1619), 2099 Alexandre de Seve, Montreal, Quebec, Canada H2L 2W5 – sequence: 4 givenname: Guy surname: Cloutier fullname: Cloutier, Guy organization: Laboratoire de Biorhéologie et d’Ultrasonographie Médicale (LBUM), Centre Hospitalier de l’Universite de Montreal, Hopital Notre-Dame, Pavillon J.A de Seve (Y-1619), 2099 Alexandre de Seve, Montreal, Quebec, Canada H2L 2W5 – sequence: 5 givenname: Olivier surname: Basset fullname: Basset, Olivier organization: CREATIS, Université de Lyon, INSA de Lyon, Université Lyon 1, CNRS UMR 5220, INSERM U 630, Bâtiment Blaise Pascal, 7 avenue Jean Capelle, F-69621 Villeurbanne, France
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Cites_doi	10.1109/58.660156 10.1177/016173469101300201 10.1109/58.285465 10.1016/0021-9150(91)90235-U 10.1177/016173460002200202 10.1177/016173460502700102 10.1177/016173469802000403 10.1017/S0962492900002518 10.1109/TUFFC.2007.273 10.1109/TUFFC.2006.1588394 10.1109/ULTSYM.2006.322 10.1109/TMI.2003.823066 10.1109/TUFFC.2003.1244748 10.1161/01.CIR.83.5.1764 10.1109/TMI.2007.897408 10.1016/S0301-5629(98)00109-4 10.1109/TMI.2003.822825 10.1109/58.808863 10.1109/TMI.2004.835604 10.1109/TUFFC.2004.1320827 10.1109/58.646923 10.1016/j.ultras.2006.06.051 10.1134/S1061933X07060117
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Physicochemical properties of poly(vinyl alcohol) cryogels and specific features of their macroporous morphology publication-title: Colloid Journal doi: 10.1134/S1061933X07060117
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Snippet	The current research and development of 2D (matrix-shaped) transducer arrays to acquire 3D ultrasound data sets provides new insights into medical ultrasound...
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SubjectTerms	Acoustics Algorithms Bioengineering Biomechanics Breast Neoplasms - diagnostic imaging Breast Neoplasms - physiopathology Computer Science Elastic Modulus Elasticity Imaging Techniques - methods Elastography Engineering Sciences Female Fluid mechanics Fluids mechanics Humans Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image Processing Imaging Imaging, Three-Dimensional - methods Life Sciences Mechanics Mechanics of materials Medical Imaging Physics Radio Waves Reproducibility of Results Sensitivity and Specificity Signal and Image Processing Strain estimation Stress, Mechanical Ultrasonography, Mammary - methods Ultrasound
Title	3D estimation of soft biological tissue deformation from radio-frequency ultrasound volume acquisitions
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