Nuffield Department of Obstetrics and Gynaecology, University of Oxford, Oxford, UK.
Philips Research, Paris, France.
Ultrasound Obstet Gynecol. 2019 Nov;54(5):650-654. doi: 10.1002/uog.20185. Epub 2019 Oct 7.
To evaluate whether an automated tool can recognize a structure of interest and measure fetal head circumference (HC), abdominal circumference (AC) and femur length (FL) on frozen two-dimensional ultrasound images.
Ultrasound examinations were performed in 100 singleton pregnancies between 20 and 40 weeks of gestation, ensuring an even distribution throughout gestational age. In each pregnancy, three standard biometric variables (HC, AC, FL) were measured each in three different images obtained for this purpose (i.e. nine independent image acquisitions). An algorithm (Philips Research) was used to detect the structure of interest and automatically place calipers for measurement. Caliper placement was assessed in two ways. First, subjective clinical assessment was performed to determine whether the caliper placement was correct, and caliper position was classified as 'acceptable for clinical use', 'minor adjustment required' or 'major adjustment required'. Second, the resulting automatic measurements were compared with manual measurements, taken in real time. Mean difference errors were calculated and expressed as percentages to correct for fetal growth with advancing gestation.
After exclusion of one pregnancy due to missing images, a total of 891 images (297 for each biometric variable) from 99 pregnancies were analyzed. The algorithm failed to place calipers for the AC in nine images, whereas there were no failures in caliper placement for measurement of HC and FL. On subjective quality assessment of automatic caliper placement, in 475 (53.3%) images position of the calipers was judged to be clinically acceptable and did not require any adjustment, while in 317 (35.6%) and 90 images (10.1%) minor and major adjustments were required, respectively. The mean error between manual and automatic measurement of HC was -0.21 cm corresponding to a percentage error of -0.81% with 95% limits of agreement (LOA) between -3.73% and 2.12%. For AC and FL measurements, the mean error was, respectively, 0.72 cm (percentage error, 2.40%) with LOA between -9.48% and 14.27%, and 0.21 cm (percentage error, 3.76%) with LOA between -8.38% and 15.91%.
The automated tool identified correctly the biometric variable of interest in 99% of frozen images. The resulting measurements had a high degree of accuracy and compared well with previously published manual-to-manual agreement. The measurements exhibited bias, with the automated tool underestimating biometry; this could be overcome by further improvements in the algorithm. Nevertheless, adjustable calipers for manual correction remains a requirement. Copyright © 2018 ISUOG. Published by John Wiley & Sons Ltd.
评估一个自动化工具是否能够识别感兴趣的结构，并测量冷冻二维超声图像中的胎儿头围（HC）、腹围（AC）和股骨长（FL）。
对 100 例 20 至 40 孕周的单胎妊娠进行超声检查，确保整个孕龄分布均匀。在每例妊娠中，均在为此目的获得的三张标准生物测量图像（即 9 次独立的图像采集）中测量三个标准生物测量变量（HC、AC、FL）。使用一个算法（Philips Research）来检测感兴趣的结构，并自动放置卡尺进行测量。卡尺放置的评估有两种方式。首先，进行主观临床评估以确定卡尺放置是否正确，并将卡尺位置分类为“可用于临床使用”、“需要轻微调整”或“需要较大调整”。其次，将自动测量结果与实时手动测量结果进行比较。计算出平均差异误差，并表示为百分比以校正胎儿随胎龄增长的生长。
排除一张因图像缺失的妊娠后，共分析了 99 例妊娠的 891 张图像（每例生物测量变量 297 张）。在 9 张图像中，算法未能放置 AC 的卡尺，而在 HC 和 FL 的测量中，卡尺放置没有失败。在自动卡尺放置的主观质量评估中，475 张（53.3%）图像的卡尺位置被判断为临床可接受，无需任何调整，而在 317 张（35.6%）和 90 张（10.1%）图像中需要较小和较大的调整。HC 的手动和自动测量之间的平均误差为-0.21cm，相应的百分比误差为-0.81%，95%的一致性区间（LOA）在-3.73%至 2.12%之间。对于 AC 和 FL 的测量，平均误差分别为 0.72cm（百分比误差为 2.40%），LOA 在-9.48%至 14.27%之间，和 0.21cm（百分比误差为 3.76%），LOA 在-8.38%至 15.91%之间。
自动化工具在 99%的冷冻图像中正确识别出感兴趣的生物测量变量。所得到的测量具有高度的准确性，并与之前发表的手动与手动之间的一致性很好地比较。这些测量存在偏差，自动化工具低估了生物计量；可以通过进一步改进算法来克服这一问题。然而，手动校正的可调卡尺仍然是必需的。版权所有©2018 ISUOG。由 John Wiley & Sons Ltd 出版。
