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在图像存档与通信系统中测量最大头围:一种全自动方法。

Measuring Maximum Head Circumference Within the Picture Archiving and Communication System: A Fully Automatic Approach.

作者信息

Yepes-Calderon Fernando, Wihardja Frisca, Sloan Andrea, Kim Janet, Nelson Marvin D, McComb J Gordon

机构信息

Strategic Business Platforms LLC, Fort Pierce, FL, United States.

Children's Hospital of Los Angeles, Los Angeles, CA, United States.

出版信息

Front Pediatr. 2021 Jul 19;9:608122. doi: 10.3389/fped.2021.608122. eCollection 2021.

Abstract

This study describes an automatic technique to accurately determine the maximum head circumference (MHC) measurement from MRI studies within the Picture Archiving and Communications System, and can automatically add this measurement to the final radiology report. Participants were selected through a retrospective chart review of patients referred to the neurosurgery clinic. Forty-nine pediatric patients with ages ranging from 5 months to 11 years were included in the study. We created 14 printed ring structures to mirror the head circumference values at various ages along the x-axis of the Nellhaus chart. The 3D-printed structures were used to create MRI phantoms. Analytical obtainment of circumference values from the 3D objects and phantom images allowed for a fair estimation and correction of errors on the image-based-measuring instrument. Then, standard manual MHC measurements were performed and compared to values obtained from the patients' MRI T1 images using the tuned instrument proposed in this document. A -test revealed no statistical difference between the manual assessments and the ones obtained by the automation = 0.357, α = 0.05. This automatic application augments the more error-prone manual MHC measurement, and can add a numerical value to the final radiology report as a standard application.

摘要

本研究描述了一种自动技术,可从图像存档与通信系统中的MRI研究中准确确定最大头围(MHC)测量值,并能自动将此测量值添加到最终的放射学报告中。通过对转诊至神经外科诊所的患者进行回顾性病历审查来选择参与者。该研究纳入了49名年龄在5个月至11岁之间的儿科患者。我们创建了14个打印的环形结构,以沿Nellhaus图表的x轴反映不同年龄的头围值。这些3D打印结构用于创建MRI体模。从3D物体和体模图像中分析获取周长值,有助于对基于图像的测量仪器进行合理的误差估计和校正。然后,进行标准的手动MHC测量,并与使用本文提出的经过调整的仪器从患者的MRI T1图像中获得的值进行比较。t检验显示手动评估与自动化评估之间无统计学差异(P = 0.357,α = 0.05)。这种自动应用改进了更容易出错的手动MHC测量,并可作为标准应用在最终放射学报告中添加一个数值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bbc2/8326831/a9a24a2de40f/fped-09-608122-g0001.jpg

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