Comparative assessment of breast volume using a smartphone device versus MRI
Assessment of breast volume has a relevance for aesthetic surgery and for the prevention and prediction of breast diseases. This study investigated breast volume measurements using a three-dimensional (3D) body surface scanner integrated in a smartphone device in comparison with magnetic resonance i...
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Published in: | Breast cancer (Tokyo, Japan) |
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Main Authors: | , , , , , , , , , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
15-11-2024
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Online Access: | Get full text |
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Summary: | Assessment of breast volume has a relevance for aesthetic surgery and for the prevention and prediction of breast diseases. This study investigated breast volume measurements using a three-dimensional (3D) body surface scanner integrated in a smartphone device in comparison with magnetic resonance imaging (MRI) scans.BACKGROUNDAssessment of breast volume has a relevance for aesthetic surgery and for the prevention and prediction of breast diseases. This study investigated breast volume measurements using a three-dimensional (3D) body surface scanner integrated in a smartphone device in comparison with magnetic resonance imaging (MRI) scans.Breast volume was assessed for 22 women who underwent routine MRI imaging. 3D surface images were acquired using a smartphone's digital texture camera (iPhone 11 Pro Max, Apple, California, USA, 2019). Breast volumes were manually outlined and calculated by two independent investigators using a 3D software tool (Meshmixer 3.5, Autodesk, Inc., 2018). Volume assessments from MRI images were performed by a radiologist using Syngo.via (Siemens Healthcare, Erlangen, Germany, VB50). The agreement between both methods and the inter-observer agreement was calculated with the concordance correlation coefficients and analysed with Bland-Altman plots.METHODSBreast volume was assessed for 22 women who underwent routine MRI imaging. 3D surface images were acquired using a smartphone's digital texture camera (iPhone 11 Pro Max, Apple, California, USA, 2019). Breast volumes were manually outlined and calculated by two independent investigators using a 3D software tool (Meshmixer 3.5, Autodesk, Inc., 2018). Volume assessments from MRI images were performed by a radiologist using Syngo.via (Siemens Healthcare, Erlangen, Germany, VB50). The agreement between both methods and the inter-observer agreement was calculated with the concordance correlation coefficients and analysed with Bland-Altman plots.The mean breast volume as determined by MRI volumetry was 771.0 ml on the left side and 763.9 ml on the right side. Utilizing the 3D body surface volume assessment method, the mean breast volume was measured as 660.3 ml (observer A) and 616.8 ml (observer B) on the left side, and 701.9 ml (observer A) and 638.6 ml (observer B) on the right side. Although a high correlation was observed, differences in volume measurements appeared more pronounced in cases of larger breast volume.RESULTSThe mean breast volume as determined by MRI volumetry was 771.0 ml on the left side and 763.9 ml on the right side. Utilizing the 3D body surface volume assessment method, the mean breast volume was measured as 660.3 ml (observer A) and 616.8 ml (observer B) on the left side, and 701.9 ml (observer A) and 638.6 ml (observer B) on the right side. Although a high correlation was observed, differences in volume measurements appeared more pronounced in cases of larger breast volume.Smartphone-based 3D assessment of breast volume sufficiently agreed with MRI-based breast volume. This new technique could be used for cosmetic breast assessments in a surgical context and possibly in breast cancer risk studies assessing breast volume as outcome parameters.CONCLUSIONSSmartphone-based 3D assessment of breast volume sufficiently agreed with MRI-based breast volume. This new technique could be used for cosmetic breast assessments in a surgical context and possibly in breast cancer risk studies assessing breast volume as outcome parameters. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1340-6868 1880-4233 1880-4233 |
DOI: | 10.1007/s12282-024-01647-6 |