Department of Radiotherapy, Division of Imaging and Oncology, University Medical Center Utrecht, Utrecht, The Netherlands.
Computational Imaging Group for MR Therapy and Diagnostics, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.
Magn Reson Med. 2024 Mar;91(3):1190-1199. doi: 10.1002/mrm.29904. Epub 2023 Oct 24.
Several reconstruction methods for MR-based electrical properties tomography (EPT) have been developed. However, the lack of common data makes it difficult to objectively compare their performances. This is, however, a necessary precursor for standardizing and introducing this technique in the clinical setting. To enable objective comparison of the performances of reconstruction methods and provide common data for their training and testing, we created ADEPT, a database of simulated data for brain MR-EPT reconstructions.
ADEPT is a database containing in silico data for brain EPT reconstructions. This database was created from 25 different brain models, with and without tumors. Rigid geometric augmentations were applied, and different electrical properties were assigned to white matter, gray matter, CSF, and tumors to generate 120 different brain models. These models were used as input for finite-difference time-domain simulations in Sim4Life, used to compute the electromagnetic fields needed for MR-EPT reconstructions.
Electromagnetic fields from 84 healthy and 36 tumor brain models were simulated. The simulated fields relevant for MR-EPT reconstructions (transmit and receive RF fields and transceive phase) and their ground-truth electrical properties are made publicly available through ADEPT. Additionally, nonattainable fields such as the total magnetic field and the electric field are available upon request.
ADEPT will serve as reference database for objective comparisons of reconstruction methods and will be a first step toward standardization of MR-EPT reconstructions. Furthermore, it provides a large amount of data that can be exploited to train data-driven methods. It can be accessed from https://doi.org/10.34894/V0HBJ8.
已经开发了几种基于磁共振的电特性层析成像（EPT）重建方法。然而，缺乏通用数据使得难以客观比较它们的性能。然而，这是在临床环境中标准化和引入该技术的必要前提。为了能够客观比较重建方法的性能并为其训练和测试提供通用数据，我们创建了 ADEPT，这是一个用于脑磁共振 EPT 重建的模拟数据数据库。
ADEPT 是一个包含脑 EPT 重建的计算机数据的数据库。该数据库由 25 个不同的大脑模型创建，这些模型有或没有肿瘤。进行了刚性几何增强，并将不同的电特性分配给白质、灰质、CSF 和肿瘤，以生成 120 个不同的大脑模型。这些模型被用作 Sim4Life 中的有限差分时域模拟的输入，用于计算用于磁共振 EPT 重建的电磁场。
模拟了 84 个健康大脑模型和 36 个肿瘤大脑模型的电磁场。与磁共振 EPT 重建相关的模拟电磁场（发射和接收射频场以及收发相位）及其真实电特性通过 ADEPT 公开提供。此外，非可达电磁场，如总磁场和电场，可应要求提供。
ADEPT 将作为重建方法的客观比较的参考数据库，并将成为磁共振 EPT 重建标准化的第一步。此外，它提供了大量可用于训练数据驱动方法的数据。可以从 https://doi.org/10.34894/V0HBJ8 访问它。
