Quantitative analysis of image quality and radiation dosage between digital breast tomosynthesis with 2D-synthetic mammography and full-field digital mammography

2022 Fiscal Year Final Research Report

• Project/Area Number: 20K16739
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 52040:Radiological sciences-related
• Research Institution: Nippon Medical School
• Principal Investigator: TANI HITOMI 日本医科大学, 医学部, 非常勤講師 (20809636)
• Project Period (FY): 2020-04-01 – 2023-03-31
• Keywords: 乳房デジタルトモシンセシス

Outline of Final Research Achievements

We examined the image characteristics and diagnostic accuracy of digital breast tomosynthesis (DBT) and synthesized 2D mammography (SM) from both a basic and clinical perspective. Using a PMMA phantom experiment, we confirmed that both conventional digital mammography (DM) and SM imaging had similar characteristics, and there was no difference in image quality evaluation in basic experiments between the two imaging methods. SM images obtained from DBT had equal or better lesion detection ability than DM images, and were shown to be superior to DM in terms of visibility scores for calcified breast cancer or high-density breast tissue. In addition, in clinical examinations comparing DBT and SM images, it was confirmed that the diagnostic accuracy with the use of AI was not significantly different from that of radiologists alone, and the reading time was significantly reduced.

Free Research Field

放射線医学

Academic Significance and Societal Importance of the Research Achievements

乳房デジタルトモシンセシス（DBT）は、従来のデジタルマンモグラフィ（DM）よりも正確に乳癌を検出し、偽陽性を減少させる。しかし、DBT＋DMを併用すると被曝量が増加し、導入が躊躇されることがある。本研究成果からは、合成2D画像（SM）がDM画像と同等の臨床的有用性を持つことが示されており、SM画像を使用したDBT単独での乳癌診断の可能性が示唆された。今後、被曝量の抑制によってDBTの臨床導入が促進されれば、SM画像を用いた乳癌診断が普及し、乳癌検出率の向上や特異度上昇による不必要な精密検査の減少によるプログラムコストの減少、不要な心配や苦悩を経験する女性も減少する等の社会的貢献が期待できる。