Can New Ultrasound Imaging Techniques Improve Breast Lesion Characterization? Prospective Comparison between Ultrasound BI-RADS and Semi-Automatic Software “SmartBreast”, Strain Elastography, and Shear Wave Elastography
Background: Ultrasound plays a crucial role in early diagnosis of breast cancer. The aim of this research is to evaluate the diagnostic performance of BI-RADS classification in comparison with new semi-automatic software Resona R9, Mindray, “SmartBreast” and strain elastography (SE), point shear wav...
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| Format: | Article |
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MDPI AG
2023-06-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/11/6764 |
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| author | Olga Guiban Antonello Rubini Gianfranco Vallone Corrado Caiazzo Marco Di Serafino Federica Pediconi Laura Ballesio Federica Trenta Corrado De Vito Arenta Shkelqimi Ludovica Costanzo Daniele Fresilli Veronica Rizzo Vito Cantisani Massimo Vergine |
| author_facet | Olga Guiban Antonello Rubini Gianfranco Vallone Corrado Caiazzo Marco Di Serafino Federica Pediconi Laura Ballesio Federica Trenta Corrado De Vito Arenta Shkelqimi Ludovica Costanzo Daniele Fresilli Veronica Rizzo Vito Cantisani Massimo Vergine |
| author_sort | Olga Guiban |
| collection | DOAJ |
| description | Background: Ultrasound plays a crucial role in early diagnosis of breast cancer. The aim of this research is to evaluate the diagnostic performance of BI-RADS classification in comparison with new semi-automatic software Resona R9, Mindray, “SmartBreast” and strain elastography (SE), point shear wave (pSWE), and 2D shear wave (2D SWE) Elastography for breast lesion differentiation. Methods: Ninety-two breast nodules classified according to BI-RADS lexicon by an expert radiologist were evaluated by a second investigator with B-mode ultrasound, color Doppler, “SmartBreast”, and elastography. Histopathology was considered the gold standard. Results: The agreement between software and investigator was excellent in the identification of the posterior features of breast masses (Cohen’s k = 0.94), good for shape and vascular signal (Cohen’s k, respectively, of 0.6 and 0.65), poor for orientation, margins, and echo pattern (Cohen’s k, respectively, of 0.28, 0.33 and 0.48), moderate for dimensions (Lin’s correlation coefficient of 0.90, <i>p</i> = 0.07). SE showed a greater area under curve (AUC) than pSWE and 2D SWE (0.84, 0.64, and 0.61, respectively), with a greater specificity and a comparable sensitivity to pSWE (respectively, of 0.86 and 0.55, 0.81 and 0.84). Conclusions: SE improved the diagnostic performance of BI-RADS classification more than pSWE and 2D SWE; “SmartBreast” showed good agreement only for shape and vascularization but not for the other ultrasound features of breast lesions. |
| first_indexed | 2024-03-11T03:11:48Z |
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| id | doaj.art-c2cba7beb4f44b389cf6a8a242f1bc7c |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T03:11:48Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-c2cba7beb4f44b389cf6a8a242f1bc7c2023-11-18T07:36:26ZengMDPI AGApplied Sciences2076-34172023-06-011311676410.3390/app13116764Can New Ultrasound Imaging Techniques Improve Breast Lesion Characterization? Prospective Comparison between Ultrasound BI-RADS and Semi-Automatic Software “SmartBreast”, Strain Elastography, and Shear Wave ElastographyOlga Guiban0Antonello Rubini1Gianfranco Vallone2Corrado Caiazzo3Marco Di Serafino4Federica Pediconi5Laura Ballesio6Federica Trenta7Corrado De Vito8Arenta Shkelqimi9Ludovica Costanzo10Daniele Fresilli11Veronica Rizzo12Vito Cantisani13Massimo Vergine14Department of Radiological Sciences, Oncology and Pathology, Policlinico Umberto I, Sapienza University of Rome, 00100 Rome, ItalyDivision of Radiology and Diagnostic Imaging, ASL Rome, 00184 Rome, ItalyDepartment of Life and Health, University of Molise “V. Tiberio”, 86100 Campobasso, ItalyRadiology Unit, PSP Corso Vittorio Emanuele ASL Napoli 1, 80122 Naples, ItalyDepartment of General and Emergency Radiology, “Antonio Cardarelli” Hospital, 80131 Naples, ItalyDepartment of Radiological Sciences, Oncology and Pathology, Policlinico Umberto I, Sapienza University of Rome, 00100 Rome, ItalyDepartment of Radiological Sciences, Oncology and Pathology, Policlinico Umberto I, Sapienza University of Rome, 00100 Rome, ItalyDepartment of Radiological Sciences, Oncology and Pathology, Policlinico Umberto I, Sapienza University of Rome, 00100 Rome, ItalyDepartment of Public Health and Infectious Diseases, Sapienza University, 00189 Rome, ItalyDepartment of Radiological Sciences, Oncology and Pathology, Policlinico Umberto I, Sapienza University of Rome, 00100 Rome, ItalyDepartment of Surgical Sciences, Sapienza University, 00189 Rome, ItalyDepartment of Radiological Sciences, Oncology and Pathology, Policlinico Umberto I, Sapienza University of Rome, 00100 Rome, ItalyDepartment of Radiological Sciences, Oncology and Pathology, Policlinico Umberto I, Sapienza University of Rome, 00100 Rome, ItalyDepartment of Radiological Sciences, Oncology and Pathology, Policlinico Umberto I, Sapienza University of Rome, 00100 Rome, ItalyDepartment of Surgical Sciences, Sapienza University, 00189 Rome, ItalyBackground: Ultrasound plays a crucial role in early diagnosis of breast cancer. The aim of this research is to evaluate the diagnostic performance of BI-RADS classification in comparison with new semi-automatic software Resona R9, Mindray, “SmartBreast” and strain elastography (SE), point shear wave (pSWE), and 2D shear wave (2D SWE) Elastography for breast lesion differentiation. Methods: Ninety-two breast nodules classified according to BI-RADS lexicon by an expert radiologist were evaluated by a second investigator with B-mode ultrasound, color Doppler, “SmartBreast”, and elastography. Histopathology was considered the gold standard. Results: The agreement between software and investigator was excellent in the identification of the posterior features of breast masses (Cohen’s k = 0.94), good for shape and vascular signal (Cohen’s k, respectively, of 0.6 and 0.65), poor for orientation, margins, and echo pattern (Cohen’s k, respectively, of 0.28, 0.33 and 0.48), moderate for dimensions (Lin’s correlation coefficient of 0.90, <i>p</i> = 0.07). SE showed a greater area under curve (AUC) than pSWE and 2D SWE (0.84, 0.64, and 0.61, respectively), with a greater specificity and a comparable sensitivity to pSWE (respectively, of 0.86 and 0.55, 0.81 and 0.84). Conclusions: SE improved the diagnostic performance of BI-RADS classification more than pSWE and 2D SWE; “SmartBreast” showed good agreement only for shape and vascularization but not for the other ultrasound features of breast lesions.https://www.mdpi.com/2076-3417/13/11/6764ultrasoundcomputer-aided diagnosis“SmartBreast”strain elastographyshear wave elastographypSWE |
| spellingShingle | Olga Guiban Antonello Rubini Gianfranco Vallone Corrado Caiazzo Marco Di Serafino Federica Pediconi Laura Ballesio Federica Trenta Corrado De Vito Arenta Shkelqimi Ludovica Costanzo Daniele Fresilli Veronica Rizzo Vito Cantisani Massimo Vergine Can New Ultrasound Imaging Techniques Improve Breast Lesion Characterization? Prospective Comparison between Ultrasound BI-RADS and Semi-Automatic Software “SmartBreast”, Strain Elastography, and Shear Wave Elastography Applied Sciences ultrasound computer-aided diagnosis “SmartBreast” strain elastography shear wave elastography pSWE |
| title | Can New Ultrasound Imaging Techniques Improve Breast Lesion Characterization? Prospective Comparison between Ultrasound BI-RADS and Semi-Automatic Software “SmartBreast”, Strain Elastography, and Shear Wave Elastography |
| title_full | Can New Ultrasound Imaging Techniques Improve Breast Lesion Characterization? Prospective Comparison between Ultrasound BI-RADS and Semi-Automatic Software “SmartBreast”, Strain Elastography, and Shear Wave Elastography |
| title_fullStr | Can New Ultrasound Imaging Techniques Improve Breast Lesion Characterization? Prospective Comparison between Ultrasound BI-RADS and Semi-Automatic Software “SmartBreast”, Strain Elastography, and Shear Wave Elastography |
| title_full_unstemmed | Can New Ultrasound Imaging Techniques Improve Breast Lesion Characterization? Prospective Comparison between Ultrasound BI-RADS and Semi-Automatic Software “SmartBreast”, Strain Elastography, and Shear Wave Elastography |
| title_short | Can New Ultrasound Imaging Techniques Improve Breast Lesion Characterization? Prospective Comparison between Ultrasound BI-RADS and Semi-Automatic Software “SmartBreast”, Strain Elastography, and Shear Wave Elastography |
| title_sort | can new ultrasound imaging techniques improve breast lesion characterization prospective comparison between ultrasound bi rads and semi automatic software smartbreast strain elastography and shear wave elastography |
| topic | ultrasound computer-aided diagnosis “SmartBreast” strain elastography shear wave elastography pSWE |
| url | https://www.mdpi.com/2076-3417/13/11/6764 |
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