Axelsson Rebecca, Tomic Hanna, Zackrisson Sophia, Tingberg Anders, Isaksson Hanna, Bakic Predrag R, Dustler Magnus
Lund University, Skåne University Hospital, Medical Radiation Physics, Department of Translational Medicine, Malmö, Sweden.
Lund University, Skåne University Hospital, Diagnostic Radiology, Department of Translational Medicine, Department in Imaging and Functional Medicine, Malmö, Sweden.
J Med Imaging (Bellingham). 2022 May;9(3):033502. doi: 10.1117/1.JMI.9.3.033502. Epub 2022 May 23.
Malignant breast lesions can be distinguished from benign lesions by their mechanical properties. This has been utilized for mechanical imaging in which the stress distribution over the breast is measured. Mechanical imaging has shown the ability to identify benign or normal cases and to reduce the number of false positives from mammography screening. Our aim was to develop a model of mechanical imaging acquisition for simulation purposes. To that end, we simulated mammographic compression of a computer model of breast anatomy and lesions. The breast compression was modeled using the finite element method. Two finite element breast models of different sizes were used and solved using linear elastic material properties in open-source virtual clinical trial (VCT) software. A spherical lesion (15 mm in diameter) was inserted into the breasts, and both the location and stiffness of the lesion were varied extensively. The average stress over the breast and the average stress at the lesion location, as well as the relative mean pressure over lesion area (RMPA), were calculated. The average stress varied 6.2-6.5 kPa over the breast surface and 7.8-11.4 kPa over the lesion, for different lesion locations and stiffnesses. These stresses correspond to an RMPA of 0.80 to 1.46. The average stress was 20% to 50% higher at the lesion location compared with the average stress over the entire breast surface. The average stress over the breast and the lesion location corresponded well to clinical measurements. The proposed model can be used in VCTs for evaluation and optimization of mechanical imaging screening strategies.
恶性乳腺病变可通过其力学特性与良性病变相区分。这已被用于机械成像，即测量乳房上的应力分布。机械成像已显示出能够识别良性或正常病例，并减少乳腺钼靶筛查中的假阳性数量。我们的目标是开发一种用于模拟目的的机械成像采集模型。为此，我们模拟了乳腺解剖结构和病变的计算机模型的乳腺钼靶压迫。使用有限元方法对乳腺压迫进行建模。使用了两个不同尺寸的有限元乳腺模型，并在开源虚拟临床试验（VCT）软件中使用线性弹性材料属性进行求解。将一个球形病变（直径15毫米）插入乳房中，病变的位置和硬度都有很大变化。计算了乳房上的平均应力、病变位置的平均应力以及病变区域的相对平均压力（RMPA）。对于不同的病变位置和硬度，乳房表面的平均应力在6.2 - 6.5千帕之间变化，病变处的平均应力在7.8 - 11.4千帕之间变化。这些应力对应的RMPA为0.80至1.46。病变位置的平均应力比整个乳房表面的平均应力高20%至50%。乳房和病变位置的平均应力与临床测量结果吻合良好。所提出的模型可用于虚拟临床试验，以评估和优化机械成像筛查策略。
