BACKGROUND:Imaging examinations are crucial for diagnosing acute ischemic stroke, and knowledge of a patient’s body weight is necessary for safe examination. To perform examinations safely and rapidly, estimating body weight using head computed tomography (CT) scout images can be useful. OBJECTIVE:This study aims to develop a new method for estimating body weight using head CT scout images for contrast-enhanced CT examinations in patients with acute ischemic stroke. METHODS:This study investigates three weight estimation techniques. The first utilizes total pixel values from head CT scout images. The second one employs the Xception model, which was trained using 216 images with leave-one-out cross-validation. The third one is an average of the first two estimates. Our primary focus is the weight estimated from this third new method. RESULTS:The third new method, an average of the first two weight estimation methods, demonstrates moderate accuracy with a 95% confidence interval of ±14.7 kg. The first method, using only total pixel values, has a wider interval of ±20.6 kg, while the second method, a deep learning approach, results in a 95% interval of ±16.3 kg. CONCLUSIONS:The presented new method is a potentially valuable support tool for medical staff, such as doctors and nurses, in estimating weight during emergency examinations for patients with acute conditions such as stroke when obtaining accurate weight measurements is not easily feasible.

中文翻译：

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利用头部 CT 侦察图像开发新的体重估计方法

背景：影像学检查对于诊断急性缺血性脑卒中至关重要，并且了解患者的体重对于安全检查是必要的。为了安全、快速地进行检查，使用头部计算机断层扫描 (CT) 侦察图像估计体重可能很有用。目的：本研究旨在开发一种利用头部CT侦察图像估算体重的新方法，用于急性缺血性脑卒中患者的增强CT检查。方法：本研究调查了三种体重估计技术。第一个利用头部 CT 侦察图像的总像素值。第二个模型采用 Xception 模型，该模型使用 216 张图像进行留一交叉验证训练。第三个是前两个估计的平均值。我们的主要关注点是根据第三种新方法估算的重量。结果：第三种新方法是前两种重量估计方法的平均值，显示出中等精度，95% 置信区间为 ±14.7 kg。第一种方法仅使用总像素值，具有更宽的区间 ±20.6 kg，而第二种方法（深度学习方法）则产生 ±16.3 kg 的 95% 区间。结论：所提出的新方法对于医生和护士等医务人员来说是一种潜在有价值的支持工具，可以在对中风等急性疾病患者进行紧急检查时估计体重，因为获得准确的体重测量并不容易。