• 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

相似文献

1
Vol-PACT: A Foundation for the NIH Public-Private Partnership That Supports Sharing of Clinical Trial Data for the Development of Improved Imaging Biomarkers in Oncology.Vol-PACT:美国国立卫生研究院公私合作伙伴关系的基础,该伙伴关系支持共享临床试验数据以开发改进的肿瘤影像生物标志物。
JCO Clin Cancer Inform. 2018 Dec;2:1-12. doi: 10.1200/CCI.17.00137.
2
The project data sphere initiative: accelerating cancer research by sharing data.项目数据领域计划:通过数据共享加速癌症研究
Oncologist. 2015 May;20(5):464-e20. doi: 10.1634/theoncologist.2014-0431. Epub 2015 Apr 15.
3
Trial design and reporting standards for intra-arterial cerebral thrombolysis for acute ischemic stroke.急性缺血性脑卒中动脉内脑溶栓的试验设计与报告标准。
Stroke. 2003 Aug;34(8):e109-37. doi: 10.1161/01.STR.0000082721.62796.09. Epub 2003 Jul 17.
4
Assessment of lung cancer response after nonoperative therapy: tumor diameter, bidimensional product, and volume. A serial CT scan-based study.非手术治疗后肺癌反应的评估:肿瘤直径、二维乘积和体积。一项基于CT扫描序列的研究。
Int J Radiat Oncol Biol Phys. 2001 Sep 1;51(1):56-61. doi: 10.1016/s0360-3016(01)01615-7.
5
A radiomics approach to assess tumour-infiltrating CD8 cells and response to anti-PD-1 or anti-PD-L1 immunotherapy: an imaging biomarker, retrospective multicohort study.一种基于放射组学的方法来评估肿瘤浸润 CD8 细胞与抗 PD-1 或抗 PD-L1 免疫治疗反应的关系:一项影像学生物标志物、回顾性多队列研究。
Lancet Oncol. 2018 Sep;19(9):1180-1191. doi: 10.1016/S1470-2045(18)30413-3. Epub 2018 Aug 14.
6
A Web-Based Response-Assessment System for Development and Validation of Imaging Biomarkers in Oncology.一种用于肿瘤学成像生物标志物开发与验证的基于网络的反应评估系统。
Tomography. 2019 Mar;5(1):220-225. doi: 10.18383/j.tom.2019.00006.
7
Volumetric CT in lung cancer: an example for the qualification of imaging as a biomarker.肺癌容积 CT:影像学作为生物标志物的一个实例。
Acad Radiol. 2010 Jan;17(1):107-15. doi: 10.1016/j.acra.2009.06.019.
8
District decision-making for health in low-income settings: a qualitative study in Uttar Pradesh, India, on engaging the private health sector in sharing health-related data.低收入环境下的地区卫生决策:印度北方邦关于促使私营卫生部门共享健康相关数据的一项定性研究
Health Policy Plan. 2016 Sep;31 Suppl 2(Suppl 2):ii35-ii46. doi: 10.1093/heapol/czv117.
9
Bridging the communication gap between public and private radiology services.弥合公私营放射服务之间的沟通鸿沟。
Med J Aust. 2009 Nov 16;191(10):558-60. doi: 10.5694/j.1326-5377.2009.tb03310.x.
10
The use of volumetric CT as an imaging biomarker in lung cancer.容积 CT 在肺癌中的应用作为成像生物标志物。
Acad Radiol. 2010 Jan;17(1):100-6. doi: 10.1016/j.acra.2009.07.030.

引用本文的文献

1
Comparing quantitative imaging biomarker alliance volumetric CT classifications with RECIST response categories.比较定量成像生物标志物联盟的容积CT分类与RECIST反应类别。
Radiol Adv. 2025 Jan 6;2(1):umaf001. doi: 10.1093/radadv/umaf001. eCollection 2025 Jan.
2
Modeling Tumor Growth Using Partly Conditional Survival Models: A Case Study in Colorectal Cancer.使用部分条件生存模型对肿瘤生长进行建模:结直肠癌的案例研究。
JCO Clin Cancer Inform. 2023 Sep;7:e2200203. doi: 10.1200/CCI.22.00203.
3
Ethnic diversity in treatment response for colorectal cancer: proof of concept for radiomics-driven enrichment trials.结直肠癌治疗反应的种族多样性:基于放射组学的富集试验的概念验证。
Eur Radiol. 2023 Dec;33(12):9254-9261. doi: 10.1007/s00330-023-09862-z. Epub 2023 Jun 27.
4
Radiomic and Volumetric Measurements as Clinical Trial Endpoints-A Comprehensive Review.作为临床试验终点的影像组学和体积测量——全面综述
Cancers (Basel). 2022 Oct 17;14(20):5076. doi: 10.3390/cancers14205076.
5
An imaging signature to predict outcome in metastatic colorectal cancer using routine computed tomography scans.使用常规计算机断层扫描成像预测转移性结直肠癌患者的预后。
Eur J Cancer. 2022 Jan;161:138-147. doi: 10.1016/j.ejca.2021.10.029. Epub 2021 Dec 13.
6
Deep learning for the prediction of early on-treatment response in metastatic colorectal cancer from serial medical imaging.深度学习在转移性结直肠癌治疗早期应答预测中的应用:基于系列医学影像学研究。
Nat Commun. 2021 Nov 17;12(1):6654. doi: 10.1038/s41467-021-26990-6.
7
Comparing RECIST 1.1 and iRECIST in advanced melanoma patients treated with pembrolizumab in a phase II clinical trial.比较 II 期临床试验中接受 pembrolizumab 治疗的晚期黑色素瘤患者的 RECIST 1.1 和 iRECIST。
Eur Radiol. 2021 Apr;31(4):1853-1862. doi: 10.1007/s00330-020-07249-y. Epub 2020 Sep 30.
8
Enhanced Detection of Treatment Effects on Metastatic Colorectal Cancer with Volumetric CT Measurements for Tumor Burden Growth Rate Evaluation.利用容积 CT 测量评估肿瘤负担增长率,增强转移性结直肠癌治疗效果的检测。
Clin Cancer Res. 2020 Dec 15;26(24):6464-6474. doi: 10.1158/1078-0432.CCR-20-1493. Epub 2020 Sep 28.
9
Radiomics Response Signature for Identification of Metastatic Colorectal Cancer Sensitive to Therapies Targeting EGFR Pathway.放射组学反应特征可识别对靶向 EGFR 通路治疗敏感的转移性结直肠癌。
J Natl Cancer Inst. 2020 Sep 1;112(9):902-912. doi: 10.1093/jnci/djaa017.
10
Progress and Opportunities to Advance Clinical Cancer Therapeutics Using Tumor Dynamic Models.利用肿瘤动态模型推进癌症临床治疗的进展和机遇。
Clin Cancer Res. 2020 Apr 15;26(8):1787-1795. doi: 10.1158/1078-0432.CCR-19-0287. Epub 2019 Dec 23.

本文引用的文献

1
A Response Assessment Platform for Development and Validation of Imaging Biomarkers in Oncology.一个用于肿瘤学成像生物标志物开发与验证的反应评估平台。
Tomography. 2016 Dec;2(4):406-410. doi: 10.18383/j.tom.2016.00223.
2
iRECIST: guidelines for response criteria for use in trials testing immunotherapeutics.iRECIST:免疫治疗试验中使用的疗效评估标准指南。
Lancet Oncol. 2017 Mar;18(3):e143-e152. doi: 10.1016/S1470-2045(17)30074-8. Epub 2017 Mar 2.
3
Reproducibility of radiomics for deciphering tumor phenotype with imaging.用于通过成像解读肿瘤表型的放射组学的可重复性。
Sci Rep. 2016 Mar 24;6:23428. doi: 10.1038/srep23428.
4
Response Rate as a Regulatory End Point in Single-Arm Studies of Advanced Solid Tumors.在晚期实体瘤单臂研究中,缓解率作为监管终点。
JAMA Oncol. 2016 Jun 1;2(6):772-9. doi: 10.1001/jamaoncol.2015.6315.
5
Comparative Effects of CT Imaging Measurement on RECIST End Points and Tumor Growth Kinetics Modeling.CT成像测量对RECIST终点和肿瘤生长动力学建模的比较效果
Clin Transl Sci. 2016 Feb;9(1):43-50. doi: 10.1111/cts.12384. Epub 2016 Jan 21.
6
Semiautomatic segmentation of liver metastases on volumetric CT images.基于容积CT图像的肝脏转移瘤半自动分割
Med Phys. 2015 Nov;42(11):6283-93. doi: 10.1118/1.4932365.
7
Pseudoprogression and Immune-Related Response in Solid Tumors.实体瘤中的假性进展与免疫相关反应
J Clin Oncol. 2015 Nov 1;33(31):3541-3. doi: 10.1200/JCO.2015.61.6870. Epub 2015 Aug 10.
8
Pembrolizumab versus investigator-choice chemotherapy for ipilimumab-refractory melanoma (KEYNOTE-002): a randomised, controlled, phase 2 trial.帕博利珠单抗对比研究者选择的化疗用于伊匹单抗难治性黑色素瘤(KEYNOTE-002):一项随机、对照、2期试验
Lancet Oncol. 2015 Aug;16(8):908-18. doi: 10.1016/S1470-2045(15)00083-2. Epub 2015 Jun 23.
9
Pembrolizumab versus Ipilimumab in Advanced Melanoma.帕博利珠单抗对比伊匹单抗用于晚期黑色素瘤。
N Engl J Med. 2015 Jun 25;372(26):2521-32. doi: 10.1056/NEJMoa1503093. Epub 2015 Apr 19.
10
Final results from PRIME: randomized phase III study of panitumumab with FOLFOX4 for first-line treatment of metastatic colorectal cancer.PRIME 研究的最终结果:帕尼单抗联合 FOLFOX4 一线治疗转移性结直肠癌的随机 III 期研究。
Ann Oncol. 2014 Jul;25(7):1346-1355. doi: 10.1093/annonc/mdu141. Epub 2014 Apr 8.

Vol-PACT:美国国立卫生研究院公私合作伙伴关系的基础,该伙伴关系支持共享临床试验数据以开发改进的肿瘤影像生物标志物。

Vol-PACT: A Foundation for the NIH Public-Private Partnership That Supports Sharing of Clinical Trial Data for the Development of Improved Imaging Biomarkers in Oncology.

作者信息

Dercle Laurent, Connors Dana E, Tang Ying, Adam Stacey J, Gönen Mithat, Hilden Patrick, Karovic Sanja, Maitland Michael, Moskowitz Chaya S, Kelloff Gary, Zhao Binsheng, Oxnard Geoffrey R, Schwartz Lawrence H

机构信息

Laurent Dercle, Binsheng Zhao, and Lawrence H. Schwartz, Columbia University Medical Center and New York Presbyterian Hospital; Mithat Gönen, Patrick Hilden, and Chaya S. Moskowitz, Memorial Sloan Kettering Cancer Center, New York, NY; Dana E. Connors and Stacey J. Adam, Foundation for the National Institutes of Health, North Bethesda, MD; Ying Tang, CCS Associates, San Jose, CA; Sanja Karovic and Michael Maitland, Inova Schar Cancer Institute, Fairfax, VA; Gary Kelloff, National Cancer Institute, Rockville, MD; and Geoffrey R. Oxnard, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA.

出版信息

JCO Clin Cancer Inform. 2018 Dec;2:1-12. doi: 10.1200/CCI.17.00137.

DOI:10.1200/CCI.17.00137
PMID:30652552
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6873999/
Abstract

PURPOSE

To develop a public-private partnership to study the feasibility of a new approach in collecting and analyzing clinically annotated imaging data from landmark phase III trials in advanced solid tumors.

PATIENTS AND METHODS

The collection of clinical trials fulfilled the following inclusion criteria: completed randomized trials of > 300 patients, highly measurable solid tumors (non-small-cell lung cancer, colorectal cancer, renal cell cancer, and melanoma), and required sponsor and institutional review board sign-offs. The new approach in analyzing computed tomography scans was to transfer to an academic image analysis laboratory, draw contours semi-automatically by using in-house-developed algorithms integrated into the open source imaging platform Weasis, and perform serial volumetric measurement.

RESULTS

The median duration of contracting with five sponsors was 12 months. Ten trials in 7,085 patients that covered 12 treatment regimens across 20 trial arms were collected. To date, four trials in 3,954 patients were analyzed. Source imaging data were transferred to the academic core from 97% of trial patients (n = 3,837). Tumor imaging measurements were extracted from 82% of transferred computed tomography scans (n = 3,162). Causes of extraction failure were nonmeasurable disease (n = 392), single imaging time point (n = 224), and secondary captured images (n = 59). Overall, clinically annotated imaging data were extracted in 79% of patients (n = 3,055), and the primary trial end point analysis in each trial remained representative of each original trial end point.

CONCLUSION

The sharing and analysis of source imaging data from large randomized trials is feasible and offer a rich and reusable, but largely untapped, resource for future research on novel trial-level response and progression imaging metrics.

摘要

目的

建立公私合作关系,研究一种新方法在收集和分析晚期实体瘤标志性 III 期试验中临床注释影像数据方面的可行性。

患者与方法

临床试验的收集满足以下纳入标准:完成的针对超过 300 名患者的随机试验、高度可测量的实体瘤(非小细胞肺癌、结直肠癌、肾细胞癌和黑色素瘤),且需要申办方和机构审查委员会批准。分析计算机断层扫描的新方法是将其转移至学术影像分析实验室,使用集成到开源影像平台 Weasis 中的内部开发算法半自动绘制轮廓,并进行系列体积测量。

结果

与五个申办方签订合同的中位时长为 12 个月。收集了涉及 20 个试验组 12 种治疗方案的 7085 例患者的 10 项试验。截至目前,分析了 3954 例患者的 4 项试验。97%的试验患者(n = 3837)的源影像数据被转移至学术核心。从 82%的已转移计算机断层扫描(n = 3162)中提取了肿瘤影像测量值。提取失败的原因包括不可测量的疾病(n = 392)、单一影像时间点(n = 224)和二次采集的图像(n = 59)。总体而言,79%的患者(n = 3055)提取了临床注释影像数据,且每项试验的主要试验终点分析仍代表每个原始试验终点。

结论

大型随机试验源影像数据的共享和分析是可行的,为未来关于新的试验水平反应和进展影像指标的研究提供了丰富且可重复使用但很大程度上未被利用的资源。