Kusk M W, Stowe J, Hess S, Gerke O, Foley S
Radiography & Diagnostic Imaging, School of Medicine, University College Dublin, Ireland; Department of Radiology and Nuclear Medicine, University Hospital of Southern Denmark, Hospital South West Jutland Esbjerg, Denmark; IRIS - Imaging Research Initiative Southwest, Esbjerg, Denmark.
Radiography & Diagnostic Imaging, School of Medicine, University College Dublin, Ireland.
Radiography (Lond). 2023 Jan;29(1):131-138. doi: 10.1016/j.radi.2022.10.015. Epub 2022 Nov 8.
Accurate cardiac left ventricle (LV) delineation is essential to CT-derived left ventricular ejection fraction (LVEF). To evaluate dose-reduction potential, an anatomically accurate heart phantom, with realistic X-ray attenuation is required. We demonstrated and tested a custom-made phantom using 3D-printing, and examined the influence of image noise on automatically measured LV volumes METHODS: A single coronary CT angiography (CCTA) dataset was segmented and converted to Standard Tessellation Language (STL) mesh, using open-source software. A 3D-printed model, with hollow left heart chambers, was printed and cavities filled with gelatinized contrast media. This was CT-scanned in an anthropomorphic chest phantom, at different exposure conditions. LV and "myocardium" noise and attenuation was measured. LV volume was automatically measured using two different methods. We calculated Spearmans' correlation of LV volume with noise and contrast-noise ratio respectively om 486 scans of the phantom. Source images were compared to one phantom series with similar parameters. This was done using Dice coefficient on LV short-axis segmentations.
Phantom "Myocardium" and LV attenuation was comparable to measurements on source images. Automatic volume measurement succeeded, with mean volume deviation to patient images less than 2 ml. There was a moderate correlation of volume with CNR, and strong correlation of volume with image noise. With papillary muscles included in LV volume, the correlation was positive, but negative when excluded. Variation of volumes was lowest at 90-100 kVp for both methods in the 486 repeat scans. The Dice coefficient was 0.87, indicating high overlap between the single phantom series and source scan. Cost of 3D-printer and materials was 400 and 30 Euro respectively.
Both anatomically and radiologically the phantom mimicked the source scans closely. LV volumetry was reliably performed with automatic algorithms.
Patient-specific cardiac phantoms may be produced at minimal cost and can potentially be used for other anatomies and pathologies. This enables radiographic phantom studies without need for dedicated 3D-labs or expensive commercial phantoms.
准确勾勒心脏左心室（LV）对于基于CT的左心室射血分数（LVEF）至关重要。为了评估剂量降低潜力，需要一个具有逼真X射线衰减的解剖学精确心脏模型。我们展示并测试了一个使用3D打印定制的模型，并研究了图像噪声对自动测量的LV容积的影响。方法：使用开源软件对单个冠状动脉CT血管造影（CCTA）数据集进行分割并转换为标准镶嵌语言（STL）网格。打印一个具有空心左心腔的3D打印模型，并用凝胶化造影剂填充腔室。在不同的曝光条件下，将其在拟人化胸部模型中进行CT扫描。测量LV和“心肌”的噪声及衰减。使用两种不同方法自动测量LV容积。我们分别在对模型的486次扫描中计算了LV容积与噪声以及对比噪声比的斯皮尔曼相关性。将源图像与具有相似参数的一个模型系列进行比较。这是通过对LV短轴分割的骰子系数来完成的。
模型“心肌”和LV的衰减与源图像上的测量结果相当。自动容积测量成功，与患者图像的平均容积偏差小于2毫升。容积与CNR呈中度相关，与图像噪声呈强相关。当LV容积包括乳头肌时，相关性为正，但排除乳头肌时为负。在486次重复扫描中，两种方法在90 - 100 kVp时容积变化最低。骰子系数为0.87，表明单个模型系列与源扫描之间有高度重叠。3D打印机和材料的成本分别为400欧元和30欧元。
该模型在解剖学和放射学上都与源扫描非常相似。使用自动算法可可靠地进行LV容积测量。
可以以最低成本制作患者特异性心脏模型，并且可能用于其他解剖结构和病理情况。这使得无需专门的3D实验室或昂贵的商业模型即可进行射线照相模型研究。
