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基于CT的放射组学预后向量(RPV)预测高级别浆液性卵巢癌的生存和间质组织学:一项外部验证研究

CT-based radiomic prognostic vector (RPV) predicts survival and stromal histology in high-grade serous ovarian cancer: an external validation study.

作者信息

Wengert Georg J, Lu Haonan, Aboagye Eric O, Langs Georg, Poetsch Nina, Schwartz Ernst, Bagó-Horváth Zsuzsanna, Fotopoulou Christina, Polterauer Stephan, Helbich Thomas H, Rockall Andrea G

机构信息

Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK.

Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna General Hospital, Vienna, Austria.

出版信息

Eur Radiol. 2025 Jun;35(6):3110-3119. doi: 10.1007/s00330-024-11267-5. Epub 2024 Dec 11.

DOI:10.1007/s00330-024-11267-5
PMID:39661150
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12081573/
Abstract

OBJECTIVES

In women with high-grade serous ovarian cancer (HGSOC), a CT-based radiomic prognostic vector (RPV) predicted stromal phenotype and survival after primary surgery. The study's purpose was to fully externally validate RPV and its biological correlate.

MATERIALS AND METHODS

In this retrospective study, ovarian masses on CT scans of HGSOC patients, who underwent primary cytoreductive surgery in an ESGO-certified Center between 2002 and 2017, were segmented for external RPV score calculation and then correlated with overall survival (OS) and progression-free survival (PFS). A subset of tissue samples subjected to fibronectin immunohistochemistry were evaluated by a gynaeco-pathologist for stromal content. Kaplan-Meier log-rank test and a Cox proportional hazards model were used for outcome analysis.

RESULTS

Among 340 women with HGSOC, 244 ovarian lesions were available for segmentation in 198 women (mean age 59.8 years, range 34-92). Median OS was 48.69 months (IQR: 27.0-102.5) and PFS was 19.3 months (IQR: 13-32.2). Using multivariate Cox analysis, poor OS was associated with RPV-high (HR 3.17; 95% CI: 1.32-7.60; p = 0.0099), post-operative residual disease (HR 2.04; 95% CI: 1.30-3.20; p = 0.0020), and FIGO stage III/IV (HR 1.79; 95% CI: 1.11-2.86; p = 0.016). Age did not influence OS. RPV-high tissue had higher stromal content based on fibronectin expression (mean 48.9%, SD 10.5%) compared to RPV-low cases (mean 14.9%, SD 10.5%, p < 0.0001). RPV score was not significantly associated with PFS.

CONCLUSION

Patients with HGSOC and RPV-high ovarian mass on pre-operative CT had significantly worse OS following primary surgery and a higher stromal content compared to RPV-low masses, externally validating the RPV and its biological interpretation.

KEY POINTS

Question Can the performance of a previously described RPV in women with HGSOC be replicated when licenced to an external institution? Findings External validation of RPV among 244 ovarian lesions demonstrated that, on multivariate analysis, OS was associated with RPV, stage, and postoperative residual disease, replicating previous findings. Clinical relevance External validation of a radiomic tool is an essential step in translation to clinical applicability and provides the basis for prospective validation. In clinical practice, this RPV may allow more personalized decision-making for women with ovarian cancer being considered for extensive cytoreductive surgery.

摘要

目的

在高级别浆液性卵巢癌(HGSOC)女性患者中,基于CT的放射组学预后向量(RPV)可预测初次手术后的基质表型和生存情况。本研究旨在对RPV及其生物学相关性进行全面外部验证。

材料与方法

在这项回顾性研究中,对2002年至2017年期间在一家ESGO认证中心接受初次肿瘤细胞减灭术的HGSOC患者的CT扫描中的卵巢肿块进行分割,以计算外部RPV评分,然后将其与总生存期(OS)和无进展生存期(PFS)相关联。一组接受纤连蛋白免疫组织化学检测的组织样本由妇科病理学家评估其基质含量。采用Kaplan-Meier对数秩检验和Cox比例风险模型进行预后分析。

结果

在340例HGSOC女性患者中,198例女性(平均年龄59.8岁,范围34 - 92岁)的244个卵巢病变可用于分割。中位OS为48.69个月(IQR:27.0 - 102.5),PFS为19.3个月(IQR:13 - 32.2)。使用多变量Cox分析,OS较差与RPV高(HR 3.17;95% CI:1.32 - 7.60;p = 0.0099)、术后残留病灶(HR 2.04;95% CI:1.30 - 3.20;p = 0.0020)和FIGO III/IV期(HR 1.79;95% CI:1.11 - 2.86;p = 0.016)相关。年龄不影响OS。与RPV低的病例(平均14.9%,SD 10.5%,p < 0.0001)相比,基于纤连蛋白表达,RPV高的组织具有更高的基质含量(平均48.9%,SD 10.5%)。RPV评分与PFS无显著相关性。

结论

术前CT显示RPV高的卵巢肿块的HGSOC患者,初次手术后的OS明显较差,且与RPV低的肿块相比基质含量更高,从而对RPV及其生物学解释进行了外部验证。

关键点

问题 当授权给外部机构时,先前描述的RPV在HGSOC女性中的性能能否被复制? 发现 对244个卵巢病变的RPV进行外部验证表明,在多变量分析中,OS与RPV、分期和术后残留病灶相关,重复了先前的发现。 临床意义 放射组学工具的外部验证是转化为临床适用性的关键步骤,并为前瞻性验证提供基础。在临床实践中,这种RPV可能允许对考虑进行广泛肿瘤细胞减灭术的卵巢癌女性进行更个性化的决策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55f9/12081573/546c061f22e7/330_2024_11267_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55f9/12081573/dfc578734b0b/330_2024_11267_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55f9/12081573/1c78a02b2e13/330_2024_11267_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55f9/12081573/5d73e667b99d/330_2024_11267_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55f9/12081573/546c061f22e7/330_2024_11267_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55f9/12081573/dfc578734b0b/330_2024_11267_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55f9/12081573/1c78a02b2e13/330_2024_11267_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55f9/12081573/5d73e667b99d/330_2024_11267_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55f9/12081573/546c061f22e7/330_2024_11267_Fig4_HTML.jpg

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1
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Radiol Artif Intell. 2022 May 4;4(3):e210064. doi: 10.1148/ryai.210064. eCollection 2022 May.
2
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Br J Cancer. 2022 Apr;126(7):1047-1054. doi: 10.1038/s41416-021-01662-w. Epub 2021 Dec 18.
3
Cancer-associated stroma reveals prognostic biomarkers and novel insights into the tumour microenvironment of colorectal cancer and colorectal liver metastases.
癌症相关基质揭示了结直肠癌和结直肠肝转移瘤肿瘤微环境的预后生物标志物和新见解。
Cancer Med. 2022 Jan;11(2):492-506. doi: 10.1002/cam4.4452. Epub 2021 Dec 7.
4
Pre-operative radiomics model for prognostication in resectable pancreatic adenocarcinoma with external validation.术前放射组学模型对可切除胰腺腺癌的预后预测及外部验证。
Eur Radiol. 2022 Apr;32(4):2492-2505. doi: 10.1007/s00330-021-08314-w. Epub 2021 Nov 10.
5
To buy or not to buy-evaluating commercial AI solutions in radiology (the ECLAIR guidelines).买还是不买——评估放射学中的商业人工智能解决方案(ECLAIR指南)。
Eur Radiol. 2021 Jun;31(6):3786-3796. doi: 10.1007/s00330-020-07684-x. Epub 2021 Mar 5.
6
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Br J Radiol. 2021 Feb 1;94(1118):20201042. doi: 10.1259/bjr.20201042. Epub 2020 Dec 11.
7
Understanding PD-L1 Testing in Breast Cancer: A Practical Approach.了解乳腺癌中的程序性死亡配体1检测:一种实用方法。
Breast Care (Basel). 2020 Oct;15(5):481-490. doi: 10.1159/000510812. Epub 2020 Oct 6.
8
External validation of nodal failure prediction models including radiomics in head and neck cancer.头颈部癌症中包括放射组学在内的淋巴结失败预测模型的外部验证。
Oral Oncol. 2021 Jan;112:105083. doi: 10.1016/j.oraloncology.2020.105083. Epub 2020 Nov 11.
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Eur J Radiol. 2020 Aug;129:109066. doi: 10.1016/j.ejrad.2020.109066. Epub 2020 May 17.
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Med Phys. 2020 Sep;47(9):4125-4136. doi: 10.1002/mp.14308. Epub 2020 Jun 23.