Department of Radiology, Radboud University Nijmegen Medical Centre, 6500 HB Nijmegen, The Netherlands.
Med Phys. 2013 Apr;40(4):041902. doi: 10.1118/1.4791643.
To develop a computer-aided detection (CAD) system for masses in digital breast tomosynthesis (DBT) which can make use of an existing CAD system for detection of breast masses in full-field digital mammography (FFDM). This approach has the advantage that large digital screening databases that are becoming available can be used for training. DBT is currently not used for screening which makes it hard to obtain sufficient data for training.
The proposed CAD system is applied to reconstructed DBT volumes and consists of two stages. In the first stage, an existing 2D CAD system is applied to slabs composed of multiple DBT slices, after processing the slabs to a representation similar to that of the FFDM training data. In the second stage, the authors group detections obtained in the slabs that detect the same object and determine the 3D location of the grouped findings using one of three different approaches, including one that uses a set of features extracted from the DBT slabs. Experiments were conducted to determine performance of the CAD system, the optimal slab thickness for this approach and the best method to establish the 3D location. Experiments were performed using a database of 192 patients (752 DBT volumes). In 49 patients, one or more malignancies were present which were described as a mass, architectural distortion, or asymmetry. Free response receiver operating characteristic analysis and bootstrapping were used for statistical evaluation.
Best performance was obtained when slab thickness was in the range of 1-2 cm. Using the feature based 3D localization procedure developed in the study, accurate 3D localization could be obtained in most cases. Case sensitivities of 80% and 90% were achieved at 0.35 and 0.99 false positives per volume, respectively.
This study indicates that there may be a large benefit in using 2D mammograms for the development of CAD for DBT and that there is no need to exclusively limit development to DBT data.
开发一种用于数字乳腺断层合成（DBT）中肿块的计算机辅助检测（CAD）系统，该系统可以利用现有的全数字化乳腺摄影（FFDM）中乳腺肿块检测的 CAD 系统。这种方法的优点是可以利用现有的大型数字筛查数据库进行培训。DBT 目前不用于筛查，因此很难获得足够的数据进行培训。
所提出的 CAD 系统应用于重建的 DBT 体数据，由两个阶段组成。在第一阶段，将现有的 2D CAD 系统应用于由多个 DBT 切片组成的切片，对切片进行处理，使其表示形式类似于 FFDM 训练数据。在第二阶段，作者将在同一物体上检测到的检测结果分组，并使用三种不同方法中的一种确定分组结果的 3D 位置，包括一种使用从 DBT 切片中提取的一组特征的方法。实验是使用一个由 192 名患者（752 个 DBT 容积）组成的数据库进行的，在 49 名患者中，存在一个或多个恶性肿瘤，这些肿瘤被描述为肿块、结构扭曲或不对称。使用自由响应接收器操作特性分析和引导进行了统计评估。
当切片厚度在 1-2cm 范围内时，获得了最佳性能。使用本研究中开发的基于特征的 3D 定位程序，可以在大多数情况下获得准确的 3D 定位。在 0.35 和 0.99 个假阳性/容积的假阳性率下，获得了 80%和 90%的病例敏感度。
这项研究表明，在开发用于 DBT 的 CAD 时，使用 2D 乳房 X 光片可能会带来很大的好处，并且没有必要专门将开发仅限于 DBT 数据。
