Comparison of Diagnostic Test Accuracy of Cone-Beam Breast Computed Tomography and Digital Breast Tomosynthesis for Breast Cancer: A Systematic Review and Meta-Analysis Approach
Background: Cone-beam breast computed tomography (CBBCT) and digital breast tomosynthesis (DBT) remain the main 3D modalities for X-ray breast imaging. This study aimed to systematically evaluate and meta-analyze the comparison of diagnostic accuracy of CBBCT and DBT to characterize breast cancers....
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| Format: | Article |
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MDPI AG
2022-05-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/9/3594 |
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| author | Temitope Emmanuel Komolafe Cheng Zhang Oluwatosin Atinuke Olagbaju Gang Yuan Qiang Du Ming Li Jian Zheng Xiaodong Yang |
| author_facet | Temitope Emmanuel Komolafe Cheng Zhang Oluwatosin Atinuke Olagbaju Gang Yuan Qiang Du Ming Li Jian Zheng Xiaodong Yang |
| author_sort | Temitope Emmanuel Komolafe |
| collection | DOAJ |
| description | Background: Cone-beam breast computed tomography (CBBCT) and digital breast tomosynthesis (DBT) remain the main 3D modalities for X-ray breast imaging. This study aimed to systematically evaluate and meta-analyze the comparison of diagnostic accuracy of CBBCT and DBT to characterize breast cancers. Methods: Two independent reviewers identified screening on diagnostic studies from 1 January 2015 to 30 December 2021, with at least reported sensitivity and specificity for both CBBCT and DBT. A univariate pooled meta-analysis was performed using the random-effects model to estimate the sensitivity and specificity while other diagnostic parameters like the area under the ROC curve (AUC), positive likelihood ratio (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>L</mi><msup><mi>R</mi><mo>+</mo></msup></mrow></semantics></math></inline-formula>), and negative likelihood ratio (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>L</mi><msup><mi>R</mi><mo>−</mo></msup></mrow></semantics></math></inline-formula>) were estimated using the bivariate model. Results: The pooled sensitivity specificity, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>L</mi><msup><mi>R</mi><mo>+</mo></msup></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>L</mi><msup><mi>R</mi><mo>−</mo></msup></mrow></semantics></math></inline-formula> and AUC at 95% confidence interval are 86.7% (80.3–91.2), 87.0% (79.9–91.8), 6.28 (4.40–8.96), 0.17 (0.12–0.25) and 0.925 for the 17 included studies in DBT arm, respectively, while, 83.7% (54.6–95.7), 71.3% (47.5–87.2), 2.71 (1.39–5.29), 0.20 (0.04–1.05), and 0.831 are the pooled sensitivity specificity, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>L</mi><msup><mi>R</mi><mo>+</mo></msup></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>L</mi><msup><mi>R</mi><mo>−</mo></msup></mrow></semantics></math></inline-formula> and AUC for the five studies in the CBBCT arm, respectively. Conclusions: Our study demonstrates that DBT shows improved diagnostic performance over CBBCT regarding all estimated diagnostic parameters; with the statistical improvement in the AUC of DBT over CBBCT. The CBBCT might be a useful modality for breast cancer detection, thus we recommend more prospective studies on CBBCT application. |
| first_indexed | 2024-03-10T03:40:16Z |
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| id | doaj.art-9da6016c99d542e3830746cf7e8aa512 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T03:40:16Z |
| publishDate | 2022-05-01 |
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| series | Sensors |
| spelling | doaj.art-9da6016c99d542e3830746cf7e8aa5122023-11-23T09:20:52ZengMDPI AGSensors1424-82202022-05-01229359410.3390/s22093594Comparison of Diagnostic Test Accuracy of Cone-Beam Breast Computed Tomography and Digital Breast Tomosynthesis for Breast Cancer: A Systematic Review and Meta-Analysis ApproachTemitope Emmanuel Komolafe0Cheng Zhang1Oluwatosin Atinuke Olagbaju2Gang Yuan3Qiang Du4Ming Li5Jian Zheng6Xiaodong Yang7Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, ChinaDepartment of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, ChinaMolecular Imaging Research Center, Harbin Medical University, Harbin 150028, ChinaDepartment of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, ChinaDepartment of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, ChinaDepartment of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, ChinaDepartment of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, ChinaDepartment of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, ChinaBackground: Cone-beam breast computed tomography (CBBCT) and digital breast tomosynthesis (DBT) remain the main 3D modalities for X-ray breast imaging. This study aimed to systematically evaluate and meta-analyze the comparison of diagnostic accuracy of CBBCT and DBT to characterize breast cancers. Methods: Two independent reviewers identified screening on diagnostic studies from 1 January 2015 to 30 December 2021, with at least reported sensitivity and specificity for both CBBCT and DBT. A univariate pooled meta-analysis was performed using the random-effects model to estimate the sensitivity and specificity while other diagnostic parameters like the area under the ROC curve (AUC), positive likelihood ratio (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>L</mi><msup><mi>R</mi><mo>+</mo></msup></mrow></semantics></math></inline-formula>), and negative likelihood ratio (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>L</mi><msup><mi>R</mi><mo>−</mo></msup></mrow></semantics></math></inline-formula>) were estimated using the bivariate model. Results: The pooled sensitivity specificity, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>L</mi><msup><mi>R</mi><mo>+</mo></msup></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>L</mi><msup><mi>R</mi><mo>−</mo></msup></mrow></semantics></math></inline-formula> and AUC at 95% confidence interval are 86.7% (80.3–91.2), 87.0% (79.9–91.8), 6.28 (4.40–8.96), 0.17 (0.12–0.25) and 0.925 for the 17 included studies in DBT arm, respectively, while, 83.7% (54.6–95.7), 71.3% (47.5–87.2), 2.71 (1.39–5.29), 0.20 (0.04–1.05), and 0.831 are the pooled sensitivity specificity, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>L</mi><msup><mi>R</mi><mo>+</mo></msup></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>L</mi><msup><mi>R</mi><mo>−</mo></msup></mrow></semantics></math></inline-formula> and AUC for the five studies in the CBBCT arm, respectively. Conclusions: Our study demonstrates that DBT shows improved diagnostic performance over CBBCT regarding all estimated diagnostic parameters; with the statistical improvement in the AUC of DBT over CBBCT. The CBBCT might be a useful modality for breast cancer detection, thus we recommend more prospective studies on CBBCT application.https://www.mdpi.com/1424-8220/22/9/3594breast cancercone-beam computed tomographydigital breast tomosynthesismeta-analysissensitivityspecificity |
| spellingShingle | Temitope Emmanuel Komolafe Cheng Zhang Oluwatosin Atinuke Olagbaju Gang Yuan Qiang Du Ming Li Jian Zheng Xiaodong Yang Comparison of Diagnostic Test Accuracy of Cone-Beam Breast Computed Tomography and Digital Breast Tomosynthesis for Breast Cancer: A Systematic Review and Meta-Analysis Approach Sensors breast cancer cone-beam computed tomography digital breast tomosynthesis meta-analysis sensitivity specificity |
| title | Comparison of Diagnostic Test Accuracy of Cone-Beam Breast Computed Tomography and Digital Breast Tomosynthesis for Breast Cancer: A Systematic Review and Meta-Analysis Approach |
| title_full | Comparison of Diagnostic Test Accuracy of Cone-Beam Breast Computed Tomography and Digital Breast Tomosynthesis for Breast Cancer: A Systematic Review and Meta-Analysis Approach |
| title_fullStr | Comparison of Diagnostic Test Accuracy of Cone-Beam Breast Computed Tomography and Digital Breast Tomosynthesis for Breast Cancer: A Systematic Review and Meta-Analysis Approach |
| title_full_unstemmed | Comparison of Diagnostic Test Accuracy of Cone-Beam Breast Computed Tomography and Digital Breast Tomosynthesis for Breast Cancer: A Systematic Review and Meta-Analysis Approach |
| title_short | Comparison of Diagnostic Test Accuracy of Cone-Beam Breast Computed Tomography and Digital Breast Tomosynthesis for Breast Cancer: A Systematic Review and Meta-Analysis Approach |
| title_sort | comparison of diagnostic test accuracy of cone beam breast computed tomography and digital breast tomosynthesis for breast cancer a systematic review and meta analysis approach |
| topic | breast cancer cone-beam computed tomography digital breast tomosynthesis meta-analysis sensitivity specificity |
| url | https://www.mdpi.com/1424-8220/22/9/3594 |
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