Suppr超能文献

在18F-氟化物PET/CT中对股骨进行半自动感兴趣区验证。

Semiautomatic region-of-interest validation at the femur in (18)F-fluoride PET/CT.

作者信息

Puri Tanuj, Blake Glen M, Curran Kathleen M, Carr Hamish, Moore Amelia E B, Colgan Niall, O'Connell Martin J, Marsden Paul K, Fogelman Ignac, Frost Michelle L

机构信息

PET Imaging Centre, Imaging Sciences and Biomedical Engineering, St. Thomas' Hospital, King's College London, London, United Kingdom.

出版信息

J Nucl Med Technol. 2012 Sep;40(3):168-74. doi: 10.2967/jnmt.111.100107. Epub 2012 Aug 14.

Abstract

UNLABELLED

The assessment of regional skeletal metabolism using (18)F-fluoride PET ((18)F-PET) requires segmentation of the tissue region of interest (ROI). The aim of this study was to validate a novel approach to define multiple ROIs at the proximal femur similar to those used in dual x-ray absorptiometry. Regions were first drawn on low-dose CT images acquired as a routine part of the PET/CT study and transferred to the (18)F-PET images for the quantitative analysis of bone turnover.

METHODS

Four healthy postmenopausal women with a mean age of 65.1 y (range, 61.8-70.0 y), and with no history of metabolic bone disorder and not currently being administered treatment affecting skeletal metabolism, underwent dynamic (18)F-PET/CT at the hip with an injected activity of 180 MBq. The ROIs at the proximal femur included femoral shaft, femoral neck, and total hip and were segmented using both a semiautomatic method and manually by 8 experts at manual ROI delineation. The mean of the 8 manually drawn ROIs was considered the gold standard against which the performances of the semiautomatic and manual methods were compared in terms of percentage overlap and percentage difference. The time to draw the ROIs was also compared.

RESULTS

The percentage overlaps between the gold standard and the semiautomatic ROIs for total hip, femoral neck, and femoral shaft were 86.1%, 37.8%, and 96.1%, respectively, and the percentage differences were 14.5%, 89.7%, and 4.7%, respectively. In the same order, the percentage overlap between the gold standard and the manual ROIs were 85.2%, 39.1%, and 95.2%, respectively, and the percentage differences were 19.9%, 91.6%, and 12.2%, respectively. The semiautomatic method was approximately 9.5, 2.5, and 67 times faster than the manual method for segmenting total-hip, femoral-neck, and femoral-shaft ROIs, respectively.

CONCLUSION

We have developed and validated a semiautomatic procedure whereby ROIs at the hip are defined using the CT component of an (18)F-PET/CT scan. The percentage overlap and percentage difference results between the semiautomatic method and the manual method for ROI delineation were similar. Two advantages of the semiautomatic method are that it is significantly quicker and eliminates some of the variability associated with operator or reader input. The tube current used for the CT scan was associated with an effective dose 8 times lower than that associated with a typical diagnostic CT scan. These results suggest that it is possible to segment bone ROIs from low-dose CT for later transfer to PET in a single PET/CT procedure without the need for an additional high-resolution CT scan.

摘要

未标注

使用(18)F - 氟化物PET((18)F - PET)评估局部骨骼代谢需要对感兴趣的组织区域(ROI)进行分割。本研究的目的是验证一种在股骨近端定义多个ROI的新方法,类似于双能X线吸收法中使用的方法。首先在作为PET/CT研究常规部分获取的低剂量CT图像上绘制区域,然后将其转移到(18)F - PET图像上进行骨转换的定量分析。

方法

4名平均年龄为65.1岁(范围61.8 - 70.0岁)的健康绝经后女性,无代谢性骨病病史且目前未接受影响骨骼代谢的治疗,接受了髋部动态(18)F - PET/CT检查,注射活度为180 MBq。股骨近端的ROI包括股骨干、股骨颈和全髋,使用半自动方法和由8名手动ROI描绘专家手动分割。将8次手动绘制ROI的平均值视为金标准,根据重叠百分比和差异百分比比较半自动方法和手动方法的性能。还比较了绘制ROI的时间。

结果

全髋、股骨颈和股骨干的金标准与半自动ROI之间的重叠百分比分别为86.1%、37.8%和96.1%,差异百分比分别为14.5%、89.7%和4.7%。按相同顺序,金标准与手动ROI之间的重叠百分比分别为85.2%、39.1%和95.2%,差异百分比分别为19.9%、91.6%和12.2%。半自动方法在分割全髋、股骨颈和股骨干ROI时分别比手动方法快约9.5倍、2.5倍和67倍。

结论

我们已经开发并验证了一种半自动程序,通过该程序使用(18)F - PET/CT扫描的CT组件在髋部定义ROI。半自动方法和手动方法在ROI描绘方面的重叠百分比和差异百分比结果相似。半自动方法的两个优点是速度明显更快,并且消除了与操作员或读者输入相关的一些变异性。用于CT扫描的管电流所产生的有效剂量比典型诊断CT扫描低8倍。这些结果表明,在单次PET/CT程序中,无需额外的高分辨率CT扫描,就可以从低剂量CT分割骨骼ROI,随后转移到PET上。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验