• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

使用正电子发射断层扫描/计算机断层扫描对可手术的非小细胞肺癌患者进行大体肿瘤体积自动勾画的最佳标准化摄取值阈值:与病理肿瘤大小的比较。

Optimal Standardized Uptake Value Threshold for Auto contouring of Gross Tumor Volume using Positron Emission Tomography/Computed Tomography in Patients with Operable Nonsmall-Cell Lung Cancer: Comparison with Pathological Tumor Size.

作者信息

Tibdewal Anil, Patil Mangesh, Misra Shagun, Purandare Nilendu, Rangarajan Venkatesh, Mummudi Naveen, Karimundackal George, Jiwnani Sabita, Agarwal Jaiprakash

机构信息

Department of Radiation Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, Maharashtra, India.

Department of Nuclear Medicine, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, Maharashtra, India.

出版信息

Indian J Nucl Med. 2021 Jan-Mar;36(1):7-13. doi: 10.4103/ijnm.IJNM_134_20. Epub 2021 Mar 4.

DOI:10.4103/ijnm.IJNM_134_20
PMID:34040289
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8130683/
Abstract

PURPOSE

Incorporating F-fluorodeoxyglucose positron emission tomography-computed tomography (F-FDG-PET/CT) for gross tumor volume (GTV) delineation is challenging due to varying tumor edge based on the set threshold of the standardized uptake value (SUV). This study aims to determine an optimal SUV threshold that correlates best with the pathological tumor size.

MATERIALS AND METHODS

From January 2013 to July 2014, 25 consecutive patients of operable nonsmall-cell lung cancer (NSCLC) who underwent stagingF-FDG-PET/CT before surgical resection were included in the test cohort and 12 patients in the validation cohort. GTVs were delineated on the staging PET/CT by automatic delineation using various percentage threshold of maximum SUV (SUVmax) and absolute SUV. The maximum pathological tumor diameter was then matched with the maximum auto-delineated tumor diameter with varying SUV thresholds. First-order linear regression and Bland-Altman plots were used to obtain an optimal SUV threshold for each patient. Three radiation oncologists with varying degrees of experiences also delineated GTVs with the visual aid of PET/CT to assess interobserver variation in delineation.

RESULTS

In the test set, the mean optimal percentage threshold for GTV was SUVmax of 35.6%±18.6% and absolute SUV of 4.35 ± 1.7. In the validation set, the mean optimal percentage threshold SUV and absolute SUV were 36.9 ± 16.9 and 4.1 ± 1.6, respectively. After a combined analysis of all 37 patients, the mean optimal threshold was 36% ± 17.9% and 4.27 ± 1.7, respectively. Using Bland-Altman plots, auto-contouring with 40% SUVmax and SUV 4 was in greater agreement with the pathological tumor diameter.

CONCLUSION

Automatic GTV delineation on PETCT in NSCLC with percentage threshold SUV of 40% and absolute SUV of 4 correlated best with pathological tumor size. Auto-contouring using these thresholds will increase the precision of radiotherapy contouring of GTV and will save time.

摘要

目的

由于基于标准化摄取值(SUV)设定的阈值不同,肿瘤边缘各异,因此将氟脱氧葡萄糖正电子发射断层扫描 - 计算机断层扫描(F-FDG-PET/CT)纳入大体肿瘤体积(GTV)勾画具有挑战性。本研究旨在确定与病理肿瘤大小相关性最佳的最佳SUV阈值。

材料与方法

2013年1月至2014年7月,将25例手术切除前接受分期F-FDG-PET/CT检查的可手术切除的非小细胞肺癌(NSCLC)患者纳入测试队列,12例患者纳入验证队列。通过使用最大SUV(SUVmax)和绝对SUV的各种百分比阈值进行自动勾画,在分期PET/CT上勾画GTV。然后将最大病理肿瘤直径与具有不同SUV阈值的最大自动勾画肿瘤直径进行匹配。使用一阶线性回归和Bland-Altman图为每位患者获得最佳SUV阈值。三位经验程度不同的放射肿瘤学家也借助PET/CT的视觉辅助来勾画GTV,以评估勾画过程中的观察者间差异。

结果

在测试集中,GTV的平均最佳百分比阈值为SUVmax 35.6%±18.6%,绝对SUV为4.35±1.7。在验证集中,平均最佳百分比阈值SUV和绝对SUV分别为36.9±16.9和4.1±1.6。对所有37例患者进行综合分析后,平均最佳阈值分别为36%±17.9%和4.27±1.7。使用Bland-Altman图,SUVmax 40%和SUV 4的自动轮廓与病理肿瘤直径的一致性更高。

结论

在NSCLC的PETCT上,SUV百分比阈值为40%且绝对SUV为4时自动勾画GTV与病理肿瘤大小的相关性最佳。使用这些阈值进行自动轮廓勾画将提高GTV放射治疗轮廓勾画的精度并节省时间。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/efb4/8130683/00d74345a8d3/IJNM-36-7-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/efb4/8130683/9d312568d4c7/IJNM-36-7-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/efb4/8130683/a2c9b60eb1a5/IJNM-36-7-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/efb4/8130683/c8a83b296257/IJNM-36-7-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/efb4/8130683/00d74345a8d3/IJNM-36-7-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/efb4/8130683/9d312568d4c7/IJNM-36-7-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/efb4/8130683/a2c9b60eb1a5/IJNM-36-7-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/efb4/8130683/c8a83b296257/IJNM-36-7-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/efb4/8130683/00d74345a8d3/IJNM-36-7-g004.jpg

相似文献

1
Optimal Standardized Uptake Value Threshold for Auto contouring of Gross Tumor Volume using Positron Emission Tomography/Computed Tomography in Patients with Operable Nonsmall-Cell Lung Cancer: Comparison with Pathological Tumor Size.使用正电子发射断层扫描/计算机断层扫描对可手术的非小细胞肺癌患者进行大体肿瘤体积自动勾画的最佳标准化摄取值阈值:与病理肿瘤大小的比较。
Indian J Nucl Med. 2021 Jan-Mar;36(1):7-13. doi: 10.4103/ijnm.IJNM_134_20. Epub 2021 Mar 4.
2
The clinical application of 4D 18F-FDG PET/CT on gross tumor volume delineation for radiotherapy planning in esophageal squamous cell cancer.4D18F-FDG PET/CT 在食管鳞癌放疗计划中大体肿瘤体积勾画的临床应用。
J Radiat Res. 2012 Jul;53(4):594-600. doi: 10.1093/jrr/rrs009. Epub 2012 Jun 5.
3
18F-FDG PET definition of gross tumor volume for radiotherapy of non-small cell lung cancer: is a single standardized uptake value threshold approach appropriate?18F-FDG PET对非小细胞肺癌放疗大体肿瘤体积的定义:单一标准化摄取值阈值方法是否合适?
J Nucl Med. 2006 Nov;47(11):1808-12.
4
The contribution of integrated PET/CT to the evolving definition of treatment volumes in radiation treatment planning in lung cancer.PET/CT融合技术在肺癌放射治疗计划中对不断演变的治疗靶区定义的贡献。
Int J Radiat Oncol Biol Phys. 2005 Nov 15;63(4):1016-23. doi: 10.1016/j.ijrobp.2005.04.021. Epub 2005 Jun 24.
5
Defining a radiotherapy target with positron emission tomography.用正电子发射断层扫描定义放射治疗靶区。
Int J Radiat Oncol Biol Phys. 2004 Nov 15;60(4):1272-82. doi: 10.1016/j.ijrobp.2004.06.254.
6
Variation in background intensity affects PET-based gross tumor volume delineation in non-small-cell lung cancer: the need for individualized information.背景强度的变化会影响非小细胞肺癌基于 PET 的大体肿瘤体积勾画:需要个体化信息。
Radiother Oncol. 2013 Oct;109(1):71-6. doi: 10.1016/j.radonc.2013.08.033. Epub 2013 Sep 20.
7
Correlation of PET standard uptake value and CT window-level thresholds for target delineation in CT-based radiation treatment planning.基于CT的放射治疗计划中PET标准摄取值与用于靶区勾画的CT窗宽-窗位阈值的相关性
Int J Radiat Oncol Biol Phys. 2007 Mar 1;67(3):720-6. doi: 10.1016/j.ijrobp.2006.09.039.
8
Intra-tumour 18F-FDG uptake heterogeneity decreases the reliability on target volume definition with positron emission tomography/computed tomography imaging.肿瘤内18F-FDG摄取异质性降低了正电子发射断层扫描/计算机断层扫描成像在靶体积定义上的可靠性。
J Med Imaging Radiat Oncol. 2015 Jun;59(3):338-45. doi: 10.1111/1754-9485.12289. Epub 2015 Feb 23.
9
Comparison of tumor volumes as determined by pathologic examination and FDG-PET/CT images of non-small-cell lung cancer: a pilot study.非小细胞肺癌病理检查与FDG-PET/CT图像测定肿瘤体积的比较:一项初步研究。
Int J Radiat Oncol Biol Phys. 2009 Dec 1;75(5):1468-74. doi: 10.1016/j.ijrobp.2009.01.019. Epub 2009 May 21.
10
[F18] FDG-PET/CT for manual or semiautomated GTV delineation of the primary tumor for radiation therapy planning in patients with esophageal cancer: is it useful?[F18] 氟代脱氧葡萄糖正电子发射断层扫描/计算机断层扫描用于手动或半自动勾画食管癌放射治疗计划中肿瘤原发灶的大体肿瘤靶区:是否有用?
Strahlenther Onkol. 2021 Sep;197(9):780-790. doi: 10.1007/s00066-020-01701-0. Epub 2020 Oct 26.

引用本文的文献

1
Prognostic nomogram combining F-FDG PET/CT radiomics and clinical data for stage III NSCLC survival prediction.结合 F-FDG PET/CT 影像组学和临床数据的 III 期 NSCLC 生存预后列线图。
Sci Rep. 2024 Sep 4;14(1):20557. doi: 10.1038/s41598-024-71003-3.
2
Total metabolic tumor volume on F-FDG PET/CT is a game-changer for patients with metastatic lung cancer treated with immunotherapy.氟代脱氧葡萄糖正电子发射断层扫描/计算机断层扫描的总代谢肿瘤体积是免疫治疗转移性肺癌患者的改变游戏规则的因素。
J Immunother Cancer. 2024 Apr 22;12(4):e007628. doi: 10.1136/jitc-2023-007628.
3
Machine learning for differentiating lung squamous cell cancer from adenocarcinoma using Clinical-Metabolic characteristics and 18F-FDG PET/CT radiomics.

本文引用的文献

1
Stereotactic ablative radiotherapy versus standard radiotherapy in stage 1 non-small-cell lung cancer (TROG 09.02 CHISEL): a phase 3, open-label, randomised controlled trial.立体定向消融放疗与标准放疗治疗Ⅰ期非小细胞肺癌(TROG 09.02 CHISEL):一项 III 期、开放性标签、随机对照临床试验。
Lancet Oncol. 2019 Apr;20(4):494-503. doi: 10.1016/S1470-2045(18)30896-9. Epub 2019 Feb 12.
2
Comparison of SUVmax and SUVpeak based segmentation to determine primary lung tumour volume on FDG PET-CT correlated with pathology data.基于 SUVmax 和 SUVpeak 的分段与基于病理数据的 FDG PET-CT 相关的原发性肺肿瘤体积比较。
Radiother Oncol. 2018 Nov;129(2):227-233. doi: 10.1016/j.radonc.2018.06.028. Epub 2018 Jul 5.
3
基于临床代谢特征与 18F-FDG PET/CT 影像组学鉴别肺鳞癌与腺癌的机器学习研究
PLoS One. 2024 Apr 3;19(4):e0300170. doi: 10.1371/journal.pone.0300170. eCollection 2024.
4
Impact of Tracer Dose Reduction in [18 F]-Labelled Fluorodeoxyglucose-Positron Emission Tomography ([18 F]-FDG)-PET) on Texture Features and Histogram Indices: A Study in Homogeneous Tissues of Phantom and Patient.减少示踪剂剂量对[18 F]-标记氟脱氧葡萄糖正电子发射断层扫描([18 F]-FDG-PET)的纹理特征和直方图指标的影响:体模和患者同质组织的研究。
Tomography. 2023 Sep 27;9(5):1799-1810. doi: 10.3390/tomography9050143.
5
A Prospective Study Comparing Dosimetry between Computed Tomography (CT) based Radiation Planning and Positron Emission Computed Tomography (PET-CT) based Radiation Planning in Treatment of Non-Metastatic Non Small Cell Lung Carcinoma.一项比较非转移性非小细胞肺癌 CT 放疗计划与 PET-CT 放疗计划剂量学的前瞻性研究。
Asian Pac J Cancer Prev. 2023 Jul 1;24(7):2543-2550. doi: 10.31557/APJCP.2023.24.7.2543.
Impact of the EARL harmonization program on automatic delineation of metabolic active tumour volumes (MATVs).
EARL harmonization 程序对代谢活性肿瘤体积(MATV)自动勾画的影响。
EJNMMI Res. 2017 Dec;7(1):30. doi: 10.1186/s13550-017-0279-y. Epub 2017 Mar 31.
4
FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0.氟代脱氧葡萄糖正电子发射断层显像/计算机断层扫描:欧洲核医学与分子影像学会肿瘤显像程序指南:第2.0版。
Eur J Nucl Med Mol Imaging. 2015 Feb;42(2):328-54. doi: 10.1007/s00259-014-2961-x. Epub 2014 Dec 2.
5
A review on segmentation of positron emission tomography images.正电子发射断层成像图像分割研究综述。
Comput Biol Med. 2014 Jul;50:76-96. doi: 10.1016/j.compbiomed.2014.04.014. Epub 2014 Apr 28.
6
What is the best way to contour lung tumors on PET scans? Multiobserver validation of a gradient-based method using a NSCLC digital PET phantom.在 PET 扫描中勾画肺肿瘤的最佳方法是什么?一种基于梯度的 NSCLC 数字 PET 体模多观察者验证方法。
Int J Radiat Oncol Biol Phys. 2012 Mar 1;82(3):1164-71. doi: 10.1016/j.ijrobp.2010.12.055. Epub 2011 Apr 29.
7
Gradient-based delineation of the primary GTV on FDG-PET in non-small cell lung cancer: a comparison with threshold-based approaches, CT and surgical specimens.基于 FDG-PET 的非小细胞肺癌原发肿瘤大体靶区的梯度勾画:与阈值方法、CT 和手术标本的比较。
Radiother Oncol. 2011 Jan;98(1):117-25. doi: 10.1016/j.radonc.2010.10.006. Epub 2010 Nov 11.
8
Microscopic disease extension in three dimensions for non-small-cell lung cancer: development of a prediction model using pathology-validated positron emission tomography and computed tomography features.非小细胞肺癌三维微观疾病扩展:使用经病理验证的正电子发射断层扫描和计算机断层扫描特征建立预测模型。
Int J Radiat Oncol Biol Phys. 2012 Jan 1;82(1):448-56. doi: 10.1016/j.ijrobp.2010.09.001. Epub 2010 Oct 23.
9
Partial volume correction strategies for quantitative FDG PET in oncology.肿瘤定量 FDG PET 的部分容积校正策略。
Eur J Nucl Med Mol Imaging. 2010 Aug;37(9):1679-87. doi: 10.1007/s00259-010-1472-7. Epub 2010 Apr 27.
10
A contrast-oriented algorithm for FDG-PET-based delineation of tumour volumes for the radiotherapy of lung cancer: derivation from phantom measurements and validation in patient data.一种基于FDG-PET的肺癌放疗肿瘤体积勾画的对比导向算法:源自体模测量及患者数据验证
Eur J Nucl Med Mol Imaging. 2008 Nov;35(11):1989-99. doi: 10.1007/s00259-008-0875-1. Epub 2008 Jul 26.