• 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

正电子发射断层扫描(PET)纹理分析与放射组学在癌症中的系统评价

A Systematic Review of PET Textural Analysis and Radiomics in Cancer.

作者信息

Piñeiro-Fiel Manuel, Moscoso Alexis, Pubul Virginia, Ruibal Álvaro, Silva-Rodríguez Jesús, Aguiar Pablo

机构信息

Molecular Imaging and Medical Physics Group, Radiology Department, Faculty of Medicine, Universidade de Santiago de Compostela, 15706 Santiago de Compostela, Spain.

Molecular Imaging Research Group, Nuclear Medicine Department, University Hospital and Health Research Institute of Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain.

出版信息

Diagnostics (Basel). 2021 Feb 23;11(2):380. doi: 10.3390/diagnostics11020380.

DOI:10.3390/diagnostics11020380
PMID:33672285
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7926413/
Abstract

BACKGROUND

Although many works have supported the utility of PET radiomics, several authors have raised concerns over the robustness and replicability of the results. This study aimed to perform a systematic review on the topic of PET radiomics and the used methodologies.

METHODS

PubMed was searched up to 15 October 2020. Original research articles based on human data specifying at least one tumor type and PET image were included, excluding those that apply only first-order statistics and those including fewer than 20 patients. Each publication, cancer type, objective and several methodological parameters (number of patients and features, validation approach, among other things) were extracted.

RESULTS

A total of 290 studies were included. Lung (28%) and head and neck (24%) were the most studied cancers. The most common objective was prognosis/treatment response (46%), followed by diagnosis/staging (21%), tumor characterization (18%) and technical evaluations (15%). The average number of patients included was 114 (median = 71; range 20-1419), and the average number of high-order features calculated per study was 31 (median = 26, range 1-286).

CONCLUSIONS

PET radiomics is a promising field, but the number of patients in most publications is insufficient, and very few papers perform in-depth validations. The role of standardization initiatives will be crucial in the upcoming years.

摘要

背景

尽管许多研究支持PET放射组学的实用性,但一些作者对结果的稳健性和可重复性表示担忧。本研究旨在对PET放射组学主题及其使用的方法进行系统评价。

方法

检索截至2020年10月15日的PubMed。纳入基于人类数据、指定至少一种肿瘤类型和PET图像的原始研究文章,排除仅应用一阶统计的文章以及患者少于20例的文章。提取每篇出版物、癌症类型、目的以及几个方法学参数(患者数量和特征、验证方法等)。

结果

共纳入290项研究。肺癌(28%)和头颈癌(24%)是研究最多的癌症。最常见的目的是预后/治疗反应(46%),其次是诊断/分期(21%)、肿瘤特征描述(18%)和技术评估(15%)。纳入的患者平均数量为114例(中位数=71;范围20 - 1419),每项研究计算的高阶特征平均数量为31个(中位数=26,范围1 - 286)。

结论

PET放射组学是一个有前景的领域,但大多数出版物中的患者数量不足,而且很少有论文进行深入验证。标准化举措在未来几年将至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/185a/7926413/dbfe761e2766/diagnostics-11-00380-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/185a/7926413/4a18ac75c6c1/diagnostics-11-00380-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/185a/7926413/f05517954cdd/diagnostics-11-00380-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/185a/7926413/7e6df6dd7b14/diagnostics-11-00380-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/185a/7926413/19b055b36279/diagnostics-11-00380-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/185a/7926413/66a374552b9a/diagnostics-11-00380-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/185a/7926413/dbfe761e2766/diagnostics-11-00380-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/185a/7926413/4a18ac75c6c1/diagnostics-11-00380-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/185a/7926413/f05517954cdd/diagnostics-11-00380-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/185a/7926413/7e6df6dd7b14/diagnostics-11-00380-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/185a/7926413/19b055b36279/diagnostics-11-00380-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/185a/7926413/66a374552b9a/diagnostics-11-00380-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/185a/7926413/dbfe761e2766/diagnostics-11-00380-g006.jpg

相似文献

1
A Systematic Review of PET Textural Analysis and Radiomics in Cancer.正电子发射断层扫描(PET)纹理分析与放射组学在癌症中的系统评价
Diagnostics (Basel). 2021 Feb 23;11(2):380. doi: 10.3390/diagnostics11020380.
2
Radiomics in Oncological PET Imaging: A Systematic Review-Part 1, Supradiaphragmatic Cancers.肿瘤PET成像中的放射组学:系统综述 - 第1部分,膈上癌症
Diagnostics (Basel). 2022 May 27;12(6):1329. doi: 10.3390/diagnostics12061329.
3
CT radiomics and PET radiomics: ready for clinical implementation?CT影像组学与PET影像组学:准备好应用于临床了吗?
Q J Nucl Med Mol Imaging. 2019 Dec;63(4):355-370. doi: 10.23736/S1824-4785.19.03192-3. Epub 2019 Sep 13.
4
F-FDG PET radiomics approaches: comparing and clustering features in cervical cancer.F-FDG PET 影像组学方法:宫颈癌特征的比较与聚类
Ann Nucl Med. 2017 Nov;31(9):678-685. doi: 10.1007/s12149-017-1199-7. Epub 2017 Aug 16.
5
Evaluation of the Prognostic Value of FDG PET/CT Parameters for Patients With Surgically Treated Head and Neck Cancer: A Systematic Review.评估 FDG PET/CT 参数对手术治疗头颈部癌症患者预后的价值:系统评价。
JAMA Otolaryngol Head Neck Surg. 2020 May 1;146(5):471-479. doi: 10.1001/jamaoto.2020.0014.
6
On the impact of smoothing and noise on robustness of CT and CBCT radiomics features for patients with head and neck cancers.关于平滑和噪声对头部和颈部癌症患者 CT 和 CBCT 放射组学特征稳健性的影响。
Med Phys. 2017 May;44(5):1755-1770. doi: 10.1002/mp.12188. Epub 2017 Apr 17.
7
Multi-site quality and variability analysis of 3D FDG PET segmentations based on phantom and clinical image data.基于体模和临床图像数据的3D FDG PET分割的多中心质量与变异性分析
Med Phys. 2017 Feb;44(2):479-496. doi: 10.1002/mp.12041.
8
Rapid review: radiomics and breast cancer.快速回顾:放射组学与乳腺癌。
Breast Cancer Res Treat. 2018 Jun;169(2):217-229. doi: 10.1007/s10549-018-4675-4. Epub 2018 Feb 2.
9
Radiomics in Oncological PET Imaging: A Systematic Review-Part 2, Infradiaphragmatic Cancers, Blood Malignancies, Melanoma and Musculoskeletal Cancers.肿瘤PET成像中的放射组学:系统综述 - 第2部分,膈下癌症、血液恶性肿瘤、黑色素瘤和肌肉骨骼肿瘤
Diagnostics (Basel). 2022 May 27;12(6):1330. doi: 10.3390/diagnostics12061330.
10
Quantitative radiomics: Validating image textural features for oncological PET in lung cancer.定量放射组学:验证肺癌肿瘤 PET 成像纹理特征。
Radiother Oncol. 2018 Nov;129(2):209-217. doi: 10.1016/j.radonc.2018.09.009. Epub 2018 Sep 29.

引用本文的文献

1
Texture Analysis of 68Ga-DOTATOC PET/CT Images for the Prediction of Outcome in Patients with Neuroendocrine Tumors.用于预测神经内分泌肿瘤患者预后的68Ga-DOTATOC PET/CT图像纹理分析
Biomedicines. 2025 May 23;13(6):1286. doi: 10.3390/biomedicines13061286.
2
Texture analysis and metabolic parameters of F-FDG PET/CT to predict primary tumour response and prognosis of paediatric soft tissue sarcomas.¹⁸F-FDG PET/CT的纹理分析和代谢参数用于预测小儿软组织肉瘤的原发肿瘤反应和预后
Eur J Nucl Med Mol Imaging. 2025 May 26. doi: 10.1007/s00259-025-07359-z.
3
Practical use of radiomic features as a metric for image quality discrimination in [F] FDG-PET: a pilot study.

本文引用的文献

1
Impact of the Tumor Microenvironment on Tumor Heterogeneity and Consequences for Cancer Cell Plasticity and Stemness.肿瘤微环境对肿瘤异质性的影响以及对癌细胞可塑性和干性的后果。
Cancers (Basel). 2020 Dec 11;12(12):3716. doi: 10.3390/cancers12123716.
2
Is FDG-PET texture analysis related to intratumor biological heterogeneity in lung cancer?FDG-PET 纹理分析与肺癌肿瘤内生物学异质性有关吗?
Eur Radiol. 2021 Jun;31(6):4156-4165. doi: 10.1007/s00330-020-07507-z. Epub 2020 Nov 27.
3
Breast Cancer Heterogeneity and Response to Novel Therapeutics.
将放射组学特征作为[F] FDG-PET图像质量鉴别指标的实际应用:一项初步研究。
EJNMMI Rep. 2025 May 8;9(1):16. doi: 10.1186/s41824-025-00243-x.
4
Impact of harmonization and oversampling methods on radiomics analysis of multi-center imbalanced datasets: application to PET-based prediction of lung cancer subtypes.标准化和过采样方法对多中心不均衡数据集的影像组学分析的影响:在基于PET的肺癌亚型预测中的应用
EJNMMI Phys. 2025 Apr 7;12(1):34. doi: 10.1186/s40658-025-00750-7.
5
Illuminating the Shadows: Innovation in Advanced Imaging Techniques for Myeloma Precursor Conditions.照亮阴影:骨髓瘤前驱病症先进成像技术的创新
Diagnostics (Basel). 2025 Jan 18;15(2):215. doi: 10.3390/diagnostics15020215.
6
Current insights on PSMA PET/CT in intermediate-risk prostate cancer: a literature review.当前关于PSMA PET/CT在中危前列腺癌中的见解:一项文献综述。
Ann Nucl Med. 2025 Mar;39(3):247-254. doi: 10.1007/s12149-025-02015-w. Epub 2025 Jan 15.
7
Clinical scoring systems, molecular subtypes and baseline [F]FDG PET/CT image analysis for prognosis of diffuse large B-cell lymphoma.用于弥漫性大B细胞淋巴瘤预后评估的临床评分系统、分子亚型及基线[F]FDG PET/CT图像分析
Cancer Imaging. 2024 Dec 18;24(1):168. doi: 10.1186/s40644-024-00810-8.
8
Coefficient of variation and texture analysis of 18F-FDG PET/CT images for the prediction of outcome in patients with multiple myeloma.18F-FDG PET/CT 图像变异系数和纹理分析预测多发性骨髓瘤患者的预后。
Ann Hematol. 2024 Sep;103(9):3713-3721. doi: 10.1007/s00277-024-05905-7. Epub 2024 Jul 24.
9
Mitigating the impact of image processing variations on tumour [F]-FDG-PET radiomic feature robustness.减轻图像处理变化对肿瘤 [F]-FDG-PET 放射组学特征稳健性的影响。
Sci Rep. 2024 Jul 15;14(1):16294. doi: 10.1038/s41598-024-67239-8.
10
Development and Validation of Prognostic Models Using Radiomic Features from Pre-Treatment Positron Emission Tomography (PET) Images in Head and Neck Squamous Cell Carcinoma (HNSCC) Patients.利用头颈鳞状细胞癌(HNSCC)患者治疗前正电子发射断层扫描(PET)图像的放射组学特征开发和验证预后模型
Cancers (Basel). 2024 Jun 11;16(12):2195. doi: 10.3390/cancers16122195.
乳腺癌的异质性与对新型疗法的反应
Cancers (Basel). 2020 Nov 5;12(11):3271. doi: 10.3390/cancers12113271.
4
Prognostic value of FDG-PET radiomics with machine learning in pancreatic cancer.基于 FDG-PET 影像组学和机器学习的胰腺癌预后预测价值。
Sci Rep. 2020 Oct 12;10(1):17024. doi: 10.1038/s41598-020-73237-3.
5
Integration of PET/CT Radiomics and Semantic Features for Differentiation between Active Pulmonary Tuberculosis and Lung Cancer.基于 PET/CT 影像组学和语义特征融合的方法鉴别活动性肺结核与肺癌
Mol Imaging Biol. 2021 Apr;23(2):287-298. doi: 10.1007/s11307-020-01550-4. Epub 2020 Oct 8.
6
Radiomics Analysis and Correlation With Metabolic Parameters in Nasopharyngeal Carcinoma Based on PET/MR Imaging.基于PET/MR成像的鼻咽癌影像组学分析及其与代谢参数的相关性
Front Oncol. 2020 Sep 8;10:1619. doi: 10.3389/fonc.2020.01619. eCollection 2020.
7
Random survival forest to predict transplant-eligible newly diagnosed multiple myeloma outcome including FDG-PET radiomics: a combined analysis of two independent prospective European trials.随机生存森林预测包括 FDG-PET 放射组学在内的新诊断多发性骨髓瘤移植候选者的结局:两项独立前瞻性欧洲试验的联合分析。
Eur J Nucl Med Mol Imaging. 2021 Apr;48(4):1005-1015. doi: 10.1007/s00259-020-05049-6. Epub 2020 Oct 2.
8
Adding the temporal domain to PET radiomic features.在 PET 放射组学特征中添加时间域。
PLoS One. 2020 Sep 23;15(9):e0239438. doi: 10.1371/journal.pone.0239438. eCollection 2020.
9
Value of volumetric and textural analysis in predicting the treatment response in patients with locally advanced rectal cancer.容积和纹理分析在预测局部晚期直肠癌患者治疗反应中的价值。
Ann Nucl Med. 2020 Dec;34(12):960-967. doi: 10.1007/s12149-020-01527-x. Epub 2020 Sep 19.
10
Value of Shape and Texture Features from F-FDG PET/CT to Discriminate between Benign and Malignant Solitary Pulmonary Nodules: An Experimental Evaluation.F-FDG PET/CT的形状和纹理特征在鉴别良性与恶性孤立性肺结节中的价值:一项实验性评估
Diagnostics (Basel). 2020 Sep 15;10(9):696. doi: 10.3390/diagnostics10090696.