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3D Density Estimation in Digital Breast Tomosynthesis -Application to Needle Path Planning for Breast Biopsy

机译:数字化乳房断层合成中的3D密度估计-在乳房活检针路径规划中的应用

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Needle insertion planning for digital breast tomosynthesis (DBT) guided biopsy has the potential to improve patient comfort and intervention safety. However, a relevant planning should take into account breast tissue deformation and lesion displacement during the procedure. Deformable models, like finite elements, use the elastic characteristics of the breast to evaluate the deformation of tissue during needle insertion. This paper presents a novel approach to locally estimate the Young's modulus of the breast tissue directly from the DBT data. The method consists in computing the fibroglandular percentage in each of the acquired DBT projection images, then reconstructing the density volume. Finally, this density information is used to compute the mechanical parameters for each finite element of the deformable mesh, obtaining a heterogeneous DBT based breast model. Preliminary experiments were performed to evaluate the relevance of this method for needle path planning in DBT guided biopsy. The results show that the heterogeneous DBT based breast model improves needle insertion simulation accuracy in 71% of the cases, compared to a homogeneous model or a binary fat/fibroglandular tissue model.
机译:用于数字乳腺断层合成(DBT)引导活检的针头插入计划可能会改善患者的舒适度和干预安全性。但是,在手术过程中,相关的计划应考虑到乳房组织的变形和病变的移位。像有限元一样,可变形模型使用乳房的弹性特征来评估针头插入过程中组织的变形。本文提出了一种直接从DBT数据本地估计乳腺组织的杨氏模量的新颖方法。该方法包括计算每个获取的DBT投影图像中的纤维腺百分比,然后重建密度体积。最后,该密度信息用于计算可变形网格的每个有限元的机械参数,从而获得基于异构DBT的乳房模型。进行了初步实验,以评估该方法与DBT引导活检中针路规划的相关性。结果表明,与同质模型或二元脂肪/纤维腺组织模型相比,基于DBT的异质乳房模型在71%的病例中提高了针插入模拟的准确性。

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