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Verfasst von:Krammer, Julia [VerfasserIn]   i
 Stsepankou, Dzmitry [VerfasserIn]   i
 Hesser, Jürgen [VerfasserIn]   i
Titel:Evaluation of a new image reconstruction method for digital breast tomosynthesis
Titelzusatz:effects on the visibility of breast lesions and breast density
Verf.angabe:Julia Krammer, Sergei Zolotarev, Inge Hillman, Konstantinos Karalis, Dzmitry Stsepankou, Valeriy Vengrinovich, Jürgen Hesser, Tony M. Svahn
E-Jahr:2019
Jahr:September 05, 2019
Umfang:10 S.
Fussnoten:Gesehen am 04.12.2019
Titel Quelle:Enthalten in: BJR
Ort Quelle:Oxford : Oxford University Press, 1928
Jahr Quelle:2019
Band/Heft Quelle:92(2019,1103) Artikel-Nummer 20190345, 10 Seiten
ISSN Quelle:1748-880X
Abstract:Objective:To compare image quality and breast density of two reconstruction methods, the widely-used filtered-back projection (FBP) reconstruction and the iterative heuristic Bayesian inference reconstruction (Bayesian inference reconstruction plus the method of total variation applied, HBI).Methods:Thirty-two clinical DBT data sets with malignant and benign findings, n = 27 and 17, respectively, were reconstructed using FBP and HBI. Three experienced radiologists evaluated the images independently using a 5-point visual grading scale and classified breast density according to the American College of Radiology Breast Imaging-Reporting And Data System Atlas, fifth edition. Image quality metrics included lesion conspicuity, clarity of lesion borders and spicules, noise level, artifacts surrounding the lesion, visibility of parenchyma and breast density.Results:For masses, the image quality of HBI reconstructions was superior to that of FBP in terms of conspicuity,clarity of lesion borders and spicules (p < 0.01). HBI and FBP were not significantly different in calcification conspicuity. Overall, HBI reduced noise and supressed artifacts surrounding the lesions better (p < 0.01). The visibility of fibroglandular parenchyma increased using the HBI method (p < 0.01). On average, five cases per radiologist were downgraded from BI-RADS breast density category C/D to A/B.Conclusion:HBI significantly improves lesion visibility compared to FBP. HBI-visibility of breast parenchyma increased, leading to a lower breast density rating. Applying the HBIR algorithm should improve the diagnostic performance of DBT and decrease the need for additional imaging in patients with dense breasts.Advances in knowledge:Iterative heuristic Bayesian inference (HBI) image reconstruction substantially improves the image quality of breast tomosynthesis leading to a better visibility of breast carcinomas and reduction of the perceived breast density compared to the widely-used filtered-back projection (FPB) reconstruction. Applying HBI should improve the accuracy of breast tomosynthesis and reduce the number of unnecessary breast biopsies. It may also reduce the radiation dose for the patients, which is especially important in the screening context.
DOI:doi:10.1259/bjr.20190345
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext: https://doi.org/10.1259/bjr.20190345
 Volltext: https://www.birpublications.org/doi/10.1259/bjr.20190345
 DOI: https://doi.org/10.1259/bjr.20190345
Datenträger:Online-Ressource
Sprache:eng
K10plus-PPN:1684378656
Verknüpfungen:→ Zeitschrift

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