Longitudinal in silico imaging study comparing digital mammography and digital breast tomosynthesis systems.
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| Title: | Longitudinal in silico imaging study comparing digital mammography and digital breast tomosynthesis systems. |
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| Authors: | Lago, Miguel A.1 (AUTHOR) miguel.lago@fda.hhs.gov, Badano, Aldo1 (AUTHOR) |
| Source: | Medical Physics. Mar2025, Vol. 52 Issue 3, p1960-1968. 9p. |
| Subjects: | Digital mammography, Tomosynthesis, Clinical trials, Image quality analysis, Receiver operating characteristic curves, Breast imaging, Digital technology |
| Abstract: | Background: In silico clinical trials are becoming more sophisticated and allow for realistic assessment and comparisons of medical image system models. These fully computational models enable fast and affordable trial designs that can closely capture trends seen on real clinical trials. Purpose: To evaluate three breast imaging system models for digital mammography (DM) and digital breast tomosynthesis (DBT) in a fully‐in‐silico longitudinal study. Methods: We developed in silico models for three different breast imaging systems by modeling relevant characteristics such as detector technology, pixel size, number of projections, and angular span. We use a computational image reader to detect masses at different growing stages to compute the relative system performance. Similarly, we compare calcification cluster detectability across systems. The Detectability area under the ROC curve (AUC) was calculated for each combination of breast density, device model, lesion size and type, and search area. We compared the absolute and relative AUC values for DM and DBT. The trial consisted of 45 000 simulated images corresponding to 750 virtual digital patient models. Results: We observed proportional AUC values with increasing mass size. On the other hand, higher breast densities showed lower AUC values. For masses, we found significant performance differences between device models. The highest average AUC difference between DBT and DM was 0.109, benefiting DBT. For calcifications, DM showed higher performance than DBT, especially in highly dense breasts. The highest AUC difference on a model was –0.055, benefiting DM. Conclusions: In this fully‐in‐silico imaging trial, we compared three imaging systems with different detector technologies on the same cohort of virtual digital patient models. We found that breast device systems can lead to visibility differences in masses and calcifications. Our longitudinal, multi‐device in silico study was possible because of the versatility and flexibility of in silico methods. This study shows the advantages of this in silico methodology in lowering the resources needed for device development, optimization, and regulatory evaluation. [ABSTRACT FROM AUTHOR] |
| Copyright of Medical Physics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 183916803 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Longitudinal in silico imaging study comparing digital mammography and digital breast tomosynthesis systems. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Lago%2C+Miguel+A%2E%22">Lago, Miguel A.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> miguel.lago@fda.hhs.gov</i><br /><searchLink fieldCode="AR" term="%22Badano%2C+Aldo%22">Badano, Aldo</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Medical+Physics%22">Medical Physics</searchLink>. Mar2025, Vol. 52 Issue 3, p1960-1968. 9p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Digital+mammography%22">Digital mammography</searchLink><br /><searchLink fieldCode="DE" term="%22Tomosynthesis%22">Tomosynthesis</searchLink><br /><searchLink fieldCode="DE" term="%22Clinical+trials%22">Clinical trials</searchLink><br /><searchLink fieldCode="DE" term="%22Image+quality+analysis%22">Image quality analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Receiver+operating+characteristic+curves%22">Receiver operating characteristic curves</searchLink><br /><searchLink fieldCode="DE" term="%22Breast+imaging%22">Breast imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+technology%22">Digital technology</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Background: In silico clinical trials are becoming more sophisticated and allow for realistic assessment and comparisons of medical image system models. These fully computational models enable fast and affordable trial designs that can closely capture trends seen on real clinical trials. Purpose: To evaluate three breast imaging system models for digital mammography (DM) and digital breast tomosynthesis (DBT) in a fully‐in‐silico longitudinal study. Methods: We developed in silico models for three different breast imaging systems by modeling relevant characteristics such as detector technology, pixel size, number of projections, and angular span. We use a computational image reader to detect masses at different growing stages to compute the relative system performance. Similarly, we compare calcification cluster detectability across systems. The Detectability area under the ROC curve (AUC) was calculated for each combination of breast density, device model, lesion size and type, and search area. We compared the absolute and relative AUC values for DM and DBT. The trial consisted of 45 000 simulated images corresponding to 750 virtual digital patient models. Results: We observed proportional AUC values with increasing mass size. On the other hand, higher breast densities showed lower AUC values. For masses, we found significant performance differences between device models. The highest average AUC difference between DBT and DM was 0.109, benefiting DBT. For calcifications, DM showed higher performance than DBT, especially in highly dense breasts. The highest AUC difference on a model was –0.055, benefiting DM. Conclusions: In this fully‐in‐silico imaging trial, we compared three imaging systems with different detector technologies on the same cohort of virtual digital patient models. We found that breast device systems can lead to visibility differences in masses and calcifications. Our longitudinal, multi‐device in silico study was possible because of the versatility and flexibility of in silico methods. This study shows the advantages of this in silico methodology in lowering the resources needed for device development, optimization, and regulatory evaluation. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Medical Physics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/mp.17571 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 9 StartPage: 1960 Subjects: – SubjectFull: Digital mammography Type: general – SubjectFull: Tomosynthesis Type: general – SubjectFull: Clinical trials Type: general – SubjectFull: Image quality analysis Type: general – SubjectFull: Receiver operating characteristic curves Type: general – SubjectFull: Breast imaging Type: general – SubjectFull: Digital technology Type: general Titles: – TitleFull: Longitudinal in silico imaging study comparing digital mammography and digital breast tomosynthesis systems. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Lago, Miguel A. – PersonEntity: Name: NameFull: Badano, Aldo IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 00942405 Numbering: – Type: volume Value: 52 – Type: issue Value: 3 Titles: – TitleFull: Medical Physics Type: main |
| ResultId | 1 |
