Nanjing University, The School of Electronic Science and Engineering, Nanjing, China.
Nanjing University, The School of Electronic Science and Engineering, Nanjing, China.
Comput Biol Med. 2023 Nov;166:107581. doi: 10.1016/j.compbiomed.2023.107581. Epub 2023 Oct 16.
Cervical cancer poses a serious threat to the health of women and radiotherapy is one of the primary treatment methods for this condition. However, this treatment is associated with a high risk of causing acute hematologic toxicity. Delineating the bone marrow (BM) for sparing based on computer tomography (CT) images before radiotherapy can effectively avoid this risk. Unfortunately, compared to magnetic resonance (MR) images, CT images lack the ability to express the activity of BM. Therefore, medical practitioners currently manually delineate the BM on CT images by corresponding to MR images. However, the manual delineation of BM is time-consuming and cannot guarantee accuracy due to the inconsistency of the CT-MR multimodal images. This study proposes a multimodal image-oriented automatic registration method for pelvic BM sparing. The proposed method includes three-dimensional (3D) bone point clouds reconstruction and an iterative closest point registration based on a local spherical system for marking BM on CT images. By introducing a joint coordinate system that combines the global Cartesian coordinate system with the local point clouds' spherical coordinate system, the increasement of point descriptive dimension avoids the local optimal registration and improves the registration accuracy. Experiments on the dataset of patients demonstrate that our proposed method can enhance the multimodal image registration accuracy and efficiency for medical practitioners in BM-sparing of cervical cancer radiotherapy. The method proposed in this contribution might also provide a solution to multimodal registration, especially in multimodal sequential images in other clinical applications, such as the diagnosis of cervical cancer and the preservation of normal organs during radiotherapy.
宫颈癌对女性健康构成严重威胁，放疗是治疗宫颈癌的主要方法之一。然而，这种治疗方法存在导致急性血液毒性的高风险。在放疗前根据计算机断层扫描（CT）图像对骨髓（BM）进行勾画以进行保护，可以有效避免这种风险。不幸的是，与磁共振（MR）图像相比，CT 图像缺乏表达 BM 活性的能力。因此，医学从业者目前通过对应 MR 图像手动在 CT 图像上勾画 BM。然而，由于 CT-MR 多模态图像的不一致性，BM 的手动勾画既耗时又不能保证准确性。本研究提出了一种基于多模态图像的骨盆 BM 保护自动配准方法。该方法包括三维（3D）骨点云重建和基于局部球坐标系的迭代最近点配准，用于在 CT 图像上标记 BM。通过引入一个结合全局笛卡尔坐标系和局部点云球坐标系的联合坐标系，增加点描述维度避免了局部最优配准，提高了配准精度。对患者数据集的实验表明，我们提出的方法可以提高 BM 保护宫颈癌放疗中多模态图像配准的准确性和效率。本研究提出的方法也可能为多模态配准提供一种解决方案，特别是在其他临床应用中的多模态序列图像中，如宫颈癌的诊断和放疗中正常器官的保护。
