应用术后图像估计颅骨切除术表面积。

IF 3.3 Q2 ENGINEERING, BIOMEDICAL
International Journal of Biomedical Imaging Pub Date : 2018-06-03 eCollection Date: 2018-01-01 DOI:10.1155/2018/5237693
Meng-Yin Ho, Wei-Lung Tseng, Furen Xiao
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引用次数: 7

摘要

减压颅骨切除术(DC)是一种神经外科手术,用于缓解脑肿胀引起的颅内压。然而,没有一种简单而准确的方法来确定颅骨切除术的表面积。在本研究中,我们实施并比较了三种估算颅骨切除术表面积以评估减压效果的方法。我们收集了2009年4月至2011年4月期间接受颅骨切除术的患者的118组术前和术后脑计算机断层扫描图像。使用行进立方体和准蒙特卡罗方法估计与每次颅骨切除术相关的表面积。采用简单的AC法估算表面积,该方法通过将颅骨切除长度(a)乘以其高度(C)计算面积。估算表面积范围为9.46 ~ 205.32 cm2,中位数为134.80 cm2。行进立方体法与拟蒙特卡罗法的均方根偏差(RMSD)为7.53 cm2。行军立方体法与AC法的均方根偏差为14.45 cm2,拟蒙特卡罗法与AC法的均方根偏差为12.70 cm2。配对t检验显示这些方法之间无统计学差异。行进立方体和准蒙特卡罗方法也得到了类似的结果。用交流法计算的结果在临床上也可用于估计直流表面积。我们的结果有助于进一步研究减压努力与颅骨切除术效果的关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Estimation of the Craniectomy Surface Area by Using Postoperative Images.

Estimation of the Craniectomy Surface Area by Using Postoperative Images.

Estimation of the Craniectomy Surface Area by Using Postoperative Images.

Estimation of the Craniectomy Surface Area by Using Postoperative Images.

Decompressive craniectomy (DC) is a neurosurgical procedure performed to relieve the intracranial pressure engendered by brain swelling. However, no easy and accurate method exists for determining the craniectomy surface area. In this study, we implemented and compared three methods of estimating the craniectomy surface area for evaluating the decompressive effort. We collected 118 sets of preoperative and postoperative brain computed tomography images from patients who underwent craniectomy procedures between April 2009 and April 2011. The surface area associated with each craniectomy was estimated using the marching cube and quasi-Monte Carlo methods. The surface area was also estimated using a simple AC method, in which the area is calculated by multiplying the craniectomy length (A) by its height (C). The estimated surface area ranged from 9.46 to 205.32 cm2, with a median of 134.80 cm2. The root-mean-square deviation (RMSD) between the marching cube and quasi-Monte Carlo methods was 7.53 cm2. Furthermore, the RMSD was 14.45 cm2 between the marching cube and AC methods and 12.70 cm2 between the quasi-Monte Carlo and AC methods. Paired t-tests indicated no statistically significant difference between these methods. The marching cube and quasi-Monte Carlo methods yield similar results. The results calculated using the AC method are also clinically acceptable for estimating the DC surface area. Our results can facilitate additional studies on the association of decompressive effort with the effect of craniectomy.

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来源期刊
CiteScore
12.00
自引率
0.00%
发文量
11
审稿时长
20 weeks
期刊介绍: The International Journal of Biomedical Imaging is managed by a board of editors comprising internationally renowned active researchers. The journal is freely accessible online and also offered for purchase in print format. It employs a web-based review system to ensure swift turnaround times while maintaining high standards. In addition to regular issues, special issues are organized by guest editors. The subject areas covered include (but are not limited to): Digital radiography and tomosynthesis X-ray computed tomography (CT) Magnetic resonance imaging (MRI) Single photon emission computed tomography (SPECT) Positron emission tomography (PET) Ultrasound imaging Diffuse optical tomography, coherence, fluorescence, bioluminescence tomography, impedance tomography Neutron imaging for biomedical applications Magnetic and optical spectroscopy, and optical biopsy Optical, electron, scanning tunneling/atomic force microscopy Small animal imaging Functional, cellular, and molecular imaging Imaging assays for screening and molecular analysis Microarray image analysis and bioinformatics Emerging biomedical imaging techniques Imaging modality fusion Biomedical imaging instrumentation Biomedical image processing, pattern recognition, and analysis Biomedical image visualization, compression, transmission, and storage Imaging and modeling related to systems biology and systems biomedicine Applied mathematics, applied physics, and chemistry related to biomedical imaging Grid-enabling technology for biomedical imaging and informatics
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