The Experts below are selected from a list of 34179 Experts worldwide ranked by ideXlab platform

Gregory J. Czarnota - One of the best experts on this subject based on the ideXlab platform.

  • Breast-Lesion Characterization using Textural Features of Quantitative Ultrasound Parametric Maps
    Scientific Reports, 2017
    Co-Authors: Ali Sadeghi-naini, Harini Suraweera, William Tyler Tran, Farnoosh Hadizad, Rashin Fallah Rastegar, Belinda Curpen, Gianni Bruni, Gregory J. Czarnota
    Abstract:

    This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant Breast Lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious Breast Lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant Lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p 

  • Breast Lesion characterization using textural features of quantitative ultrasound parametric maps
    Scientific Reports, 2017
    Co-Authors: Ali Sadeghinaini, Harini Suraweera, William Tyler Tran, Farnoosh Hadizad, Rashin Fallah Rastegar, Belinda Curpen, Giancarlo Bruni, Gregory J. Czarnota
    Abstract:

    This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant Breast Lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious Breast Lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant Lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p < 0.05) between the two Lesion types. A hybrid biomarker developed using a stepwise feature selection method could classify the legions with a sensitivity of 96%, a specificity of 84%, and an AUC of 0.97. Findings from this study pave the way towards adapting novel QUS-based frameworks for Breast cancer screening and rapid diagnosis in clinic.

William Tyler Tran - One of the best experts on this subject based on the ideXlab platform.

  • Breast-Lesion Characterization using Textural Features of Quantitative Ultrasound Parametric Maps
    Scientific Reports, 2017
    Co-Authors: Ali Sadeghi-naini, Harini Suraweera, William Tyler Tran, Farnoosh Hadizad, Rashin Fallah Rastegar, Belinda Curpen, Gianni Bruni, Gregory J. Czarnota
    Abstract:

    This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant Breast Lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious Breast Lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant Lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p 

  • Breast Lesion characterization using textural features of quantitative ultrasound parametric maps
    Scientific Reports, 2017
    Co-Authors: Ali Sadeghinaini, Harini Suraweera, William Tyler Tran, Farnoosh Hadizad, Rashin Fallah Rastegar, Belinda Curpen, Giancarlo Bruni, Gregory J. Czarnota
    Abstract:

    This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant Breast Lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious Breast Lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant Lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p < 0.05) between the two Lesion types. A hybrid biomarker developed using a stepwise feature selection method could classify the legions with a sensitivity of 96%, a specificity of 84%, and an AUC of 0.97. Findings from this study pave the way towards adapting novel QUS-based frameworks for Breast cancer screening and rapid diagnosis in clinic.

Mathias Fink - One of the best experts on this subject based on the ideXlab platform.

  • quantitative assessment of Breast Lesion viscoelasticity initial clinical results using supersonic shear imaging
    Ultrasound in Medicine and Biology, 2008
    Co-Authors: Mickael Tanter, Jeremy Bercoff, A Athanasiou, Thomas Deffieux, Jeanluc Gennisson, G Montaldo, Marie Muller, A Tardivon, Mathias Fink
    Abstract:

    Abtract This paper presents an initial clinical evaluation of in vivo elastography for Breast Lesion imaging using the concept of supersonic shear imaging. This technique is based on the combination of a radiation force induced in tissue by an ultrasonic beam and an ultrafast imaging sequence capable of catching in real time the propagation of the resulting shear waves. The local shear wave velocity is recovered using a time-offlight technique and enables the 2-D mapping of shear elasticity. This imaging modality is implemented on a conventional linear probe driven by a dedicated ultrafast echographic device. Consequently, it can be performed during a standard echographic examination. The clinical investigation was performed on 15 patients, which corresponded to 15 Lesions (4 cases BI-RADS 3, 7 cases BI-RADS 4 and 4 cases BI-RADS 5). The ability of the supersonic shear imaging technique to provide a quantitative and local estimation of the shear modulus of abnormalities with a millimetric resolution is illustrated on several malignant (invasive ductal and lobular carcinoma) and benign cases (fibrocystic changes and viscous cysts). In the investigated cases, malignant Lesions were found to be significantly different from benign solid Lesions with respect to their elasticity values. Cystic Lesions have shown no shear wave propagate at all in the Lesion (because shear waves do not propage in liquid). These preliminary clinical results directly demonstrate the clinical feasibility of this new elastography technique in providing quantitative assessment of relative stiffness of Breast tissues. This technique of evaluating tissue elasticity gives valuable information that is complementary to the B-mode morphologic information. More extensive studies are necessary to validate the assumption that this new mode potentially helps the physician in both false-positive and false-negative rejection. (E-mail: Mickael.tanter@espci.fr )

  • quantitative assessment of Breast Lesion viscoelasticity initial clinical results using supersonic shear imaging
    Ultrasound in Medicine and Biology, 2008
    Co-Authors: Mickael Tanter, Jeremy Bercoff, A Athanasiou, Thomas Deffieux, Jeanluc Gennisson, G Montaldo, Marie Muller, A Tardivon, Mathias Fink
    Abstract:

    This paper presents an initial clinical evaluation of in vivo elastography for Breast Lesion imaging using the concept of supersonic shear imaging. This technique is based on the combination of a radiation force induced in tissue by an ultrasonic beam and an ultrafast imaging sequence capable of catching in real time the propagation of the resulting shear waves. The local shear wave velocity is recovered using a time-offlight technique and enables the 2-D mapping of shear elasticity. This imaging modality is implemented on a conventional linear probe driven by a dedicated ultrafast echographic device. Consequently, it can be performed during a standard echographic examination. The clinical investigation was performed on 15 patients, which corresponded to 15 Lesions (4 cases BI-RADS 3, 7 cases BI-RADS 4 and 4 cases BI-RADS 5). The ability of the supersonic shear imaging technique to provide a quantitative and local estimation of the shear modulus of abnormalities with a millimetric resolution is illustrated on several malignant (invasive ductal and lobular carcinoma) and benign cases (fibrocystic changes and viscous cysts). In the investigated cases, malignant Lesions were found to be significantly different from benign solid Lesions with respect to their elasticity values. Cystic Lesions have shown no shear wave propagate at all in the Lesion (because shear waves do not propage in liquid). These preliminary clinical results directly demonstrate the clinical feasibility of this new elastography technique in providing quantitative assessment of relative stiffness of Breast tissues. This technique of evaluating tissue elasticity gives valuable information that is complementary to the B-mode morphologic information. More extensive studies are necessary to validate the assumption that this new mode potentially helps the physician in both false-positive and false-negative rejection.

Harini Suraweera - One of the best experts on this subject based on the ideXlab platform.

  • Breast-Lesion Characterization using Textural Features of Quantitative Ultrasound Parametric Maps
    Scientific Reports, 2017
    Co-Authors: Ali Sadeghi-naini, Harini Suraweera, William Tyler Tran, Farnoosh Hadizad, Rashin Fallah Rastegar, Belinda Curpen, Gianni Bruni, Gregory J. Czarnota
    Abstract:

    This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant Breast Lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious Breast Lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant Lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p 

  • Breast Lesion characterization using textural features of quantitative ultrasound parametric maps
    Scientific Reports, 2017
    Co-Authors: Ali Sadeghinaini, Harini Suraweera, William Tyler Tran, Farnoosh Hadizad, Rashin Fallah Rastegar, Belinda Curpen, Giancarlo Bruni, Gregory J. Czarnota
    Abstract:

    This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant Breast Lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious Breast Lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant Lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p < 0.05) between the two Lesion types. A hybrid biomarker developed using a stepwise feature selection method could classify the legions with a sensitivity of 96%, a specificity of 84%, and an AUC of 0.97. Findings from this study pave the way towards adapting novel QUS-based frameworks for Breast cancer screening and rapid diagnosis in clinic.

Belinda Curpen - One of the best experts on this subject based on the ideXlab platform.

  • Breast-Lesion Characterization using Textural Features of Quantitative Ultrasound Parametric Maps
    Scientific Reports, 2017
    Co-Authors: Ali Sadeghi-naini, Harini Suraweera, William Tyler Tran, Farnoosh Hadizad, Rashin Fallah Rastegar, Belinda Curpen, Gianni Bruni, Gregory J. Czarnota
    Abstract:

    This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant Breast Lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious Breast Lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant Lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p 

  • Breast Lesion characterization using textural features of quantitative ultrasound parametric maps
    Scientific Reports, 2017
    Co-Authors: Ali Sadeghinaini, Harini Suraweera, William Tyler Tran, Farnoosh Hadizad, Rashin Fallah Rastegar, Belinda Curpen, Giancarlo Bruni, Gregory J. Czarnota
    Abstract:

    This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant Breast Lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious Breast Lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant Lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p < 0.05) between the two Lesion types. A hybrid biomarker developed using a stepwise feature selection method could classify the legions with a sensitivity of 96%, a specificity of 84%, and an AUC of 0.97. Findings from this study pave the way towards adapting novel QUS-based frameworks for Breast cancer screening and rapid diagnosis in clinic.