Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States of America.
Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States of America.
PLoS One. 2021 Jan 13;16(1):e0241682. doi: 10.1371/journal.pone.0241682. eCollection 2021.
Numerical body models of children are used for designing medical devices, including but not limited to optical imaging, ultrasound, CT, EEG/MEG, and MRI. These models are used in many clinical and neuroscience research applications, such as radiation safety dosimetric studies and source localization. Although several such adult models have been reported, there are few reports of full-body pediatric models, and those described have several limitations. Some, for example, are either morphed from older children or do not have detailed segmentations. Here, we introduce a 29-month-old male whole-body native numerical model, "MARTIN", that includes 28 head and 86 body tissue compartments, segmented directly from the high spatial resolution MRI and CT images. An advanced auto-segmentation tool was used for the deep-brain structures, whereas 3D Slicer was used to segment the non-brain structures and to refine the segmentation for all of the tissue compartments. Our MARTIN model was developed and validated using three separate approaches, through an iterative process, as follows. First, the calculated volumes, weights, and dimensions of selected structures were adjusted and confirmed to be within 6% of the literature values for the 2-3-year-old age-range. Second, all structural segmentations were adjusted and confirmed by two experienced, sub-specialty certified neuro-radiologists, also through an interactive process. Third, an additional validation was performed with a Bloch simulator to create synthetic MR image from our MARTIN model and compare the image contrast of the resulting synthetic image with that of the original MRI data; this resulted in a "structural resemblance" index of 0.97. Finally, we used our model to perform pilot MRI safety simulations of an Active Implantable Medical Device (AIMD) using a commercially available software platform (Sim4Life), incorporating the latest International Standards Organization guidelines. This model will be made available on the Athinoula A. Martinos Center for Biomedical Imaging website.
儿童的数值体模型被用于设计医疗设备，包括但不限于光学成像、超声、CT、EEG/MEG 和 MRI。这些模型被用于许多临床和神经科学研究应用，如辐射安全剂量学研究和源定位。虽然已经有几个这样的成人模型被报道，但很少有全身儿科模型的报道，而且那些描述的模型有几个局限性。例如，有些是从年龄较大的儿童变形而来的，或者没有详细的分割。在这里，我们介绍一个 29 个月大的男性全身原始数值模型“MARTIN”，它包括 28 个头部和 86 个身体组织区室，直接从高空间分辨率 MRI 和 CT 图像分割而来。一个先进的自动分割工具用于深部脑结构，而 3D Slicer 用于分割非脑结构，并细化所有组织区室的分割。我们的 MARTIN 模型是通过三种独立的方法，通过迭代过程开发和验证的，如下所述。首先，计算选定结构的体积、重量和尺寸，并将其调整和确认在 2-3 岁年龄段文献值的 6%以内。其次，通过交互过程，由两名有经验的、专业认证的神经放射科医生对所有结构分割进行调整和确认。第三，使用 Bloch 模拟器进行额外的验证，从我们的 MARTIN 模型创建合成磁共振图像，并比较合成图像与原始 MRI 数据的图像对比度，这导致了 0.97 的“结构相似性”指数。最后，我们使用模型在商业可用的软件平台（Sim4Life）上对有源植入式医疗器械（AIMD）进行了磁共振成像安全模拟，该模型采用了最新的国际标准化组织指南。该模型将在 Athinoula A. Martinos 生物医学成像中心网站上提供。
