A computational approach for analysis of intratumoral heterogeneity and standardized uptake value in PET/CT images1.

IF 1.7 3区 医学 Q3 INSTRUMENTS & INSTRUMENTATION Journal of X-Ray Science and Technology Pub Date : 2024-01-01 DOI:10.3233/XST-230095
Khalaf Alshamrani, Hassan A Alshamrani
{"title":"A computational approach for analysis of intratumoral heterogeneity and standardized uptake value in PET/CT images1.","authors":"Khalaf Alshamrani, Hassan A Alshamrani","doi":"10.3233/XST-230095","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>By providing both functional and anatomical information from a single scan, digital imaging technologies like PET/CT and PET/MRI hybrids are gaining popularity in medical imaging industry. In clinical practice, the median value (SUVmed) receives less attention owing to disagreements surrounding what defines a lesion, but the SUVmax value, which is a semi-quantitative statistic used to analyse PET and PET/CT images, is commonly used to evaluate lesions.</p><p><strong>Objective: </strong>This study aims to build an image processing technique with the purpose of automatically detecting and isolating lesions in PET/CT images, as well as measuring and assessing the SUVmed.</p><p><strong>Methods: </strong>The pictures are separated into their respective lesions using mathematical morphology and the crescent region, which are both part of the image processing method. In this research, a total of 18 different pictures of lesions were evaluated.</p><p><strong>Results: </strong>The findings of the study reveal that the threshold is satisfied by both the SUVmax and the SUVmed for most of the lesion types. However, in six instances, the SUVmax and SUVmed values are found to be in different courts.</p><p><strong>Conclusion: </strong>The new information revealed by this study needs to be further investigated to determine if it has any practical value in diagnosing and monitoring lesions. However, results of this study suggest that SUVmed should receive more attention in the evaluation of lesions in PET and CT images.</p>","PeriodicalId":49948,"journal":{"name":"Journal of X-Ray Science and Technology","volume":" ","pages":"123-139"},"PeriodicalIF":1.7000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of X-Ray Science and Technology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3233/XST-230095","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"INSTRUMENTS & INSTRUMENTATION","Score":null,"Total":0}
引用次数: 0

Abstract

Background: By providing both functional and anatomical information from a single scan, digital imaging technologies like PET/CT and PET/MRI hybrids are gaining popularity in medical imaging industry. In clinical practice, the median value (SUVmed) receives less attention owing to disagreements surrounding what defines a lesion, but the SUVmax value, which is a semi-quantitative statistic used to analyse PET and PET/CT images, is commonly used to evaluate lesions.

Objective: This study aims to build an image processing technique with the purpose of automatically detecting and isolating lesions in PET/CT images, as well as measuring and assessing the SUVmed.

Methods: The pictures are separated into their respective lesions using mathematical morphology and the crescent region, which are both part of the image processing method. In this research, a total of 18 different pictures of lesions were evaluated.

Results: The findings of the study reveal that the threshold is satisfied by both the SUVmax and the SUVmed for most of the lesion types. However, in six instances, the SUVmax and SUVmed values are found to be in different courts.

Conclusion: The new information revealed by this study needs to be further investigated to determine if it has any practical value in diagnosing and monitoring lesions. However, results of this study suggest that SUVmed should receive more attention in the evaluation of lesions in PET and CT images.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
用于分析 PET/CT 图像中瘤内异质性和标准化摄取值的计算方法1。
背景:正电子发射计算机断层显像(PET/CT)和正电子发射计算机断层显像/磁共振成像(PET/MRI)混合成像等数字成像技术可通过一次扫描提供功能和解剖信息,因此在医学成像行业越来越受欢迎。在临床实践中,由于对病变的定义存在分歧,中位值(SUVmed)较少受到关注,但用于分析 PET 和 PET/CT 图像的半定量统计量 SUVmax 值常用于评估病变:本研究旨在建立一种图像处理技术,以自动检测和分离 PET/CT 图像中的病灶,并测量和评估 SUVmed:方法:使用数学形态学和新月区域将图片分离成各自的病灶,这两种方法都是图像处理方法的一部分。本研究共评估了 18 张不同的病变图片:研究结果显示,对于大多数病变类型,SUVmax 和 SUVmed 都能满足阈值要求。然而,有六次发现 SUVmax 和 SUVmed 值处于不同的阈值:本研究揭示的新信息在诊断和监测病变方面是否具有实用价值,还需要进一步研究。不过,本研究的结果表明,SUVmed 在 PET 和 CT 图像的病变评估中应受到更多关注。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
4.90
自引率
23.30%
发文量
150
审稿时长
3 months
期刊介绍: Research areas within the scope of the journal include: Interaction of x-rays with matter: x-ray phenomena, biological effects of radiation, radiation safety and optical constants X-ray sources: x-rays from synchrotrons, x-ray lasers, plasmas, and other sources, conventional or unconventional Optical elements: grazing incidence optics, multilayer mirrors, zone plates, gratings, other diffraction optics Optical instruments: interferometers, spectrometers, microscopes, telescopes, microprobes
期刊最新文献
Industrial digital radiographic image denoising based on improved KBNet. Research on the effectiveness of multi-view slice correction strategy based on deep learning in high pitch helical CT reconstruction. A fully linearized ADMM algorithm for optimization based image reconstruction. A reconstruction method for ptychography based on residual dense network. Can AI generate diagnostic reports for radiologist approval on CXR images? A multi-reader and multi-case observer performance study.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1