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用于鉴别胶质瘤患者放化疗后假性进展与早期肿瘤进展的FET PET放射组学

FET PET Radiomics for Differentiating Pseudoprogression from Early Tumor Progression in Glioma Patients Post-Chemoradiation.

作者信息

Lohmann Philipp, Elahmadawy Mai A, Gutsche Robin, Werner Jan-Michael, Bauer Elena K, Ceccon Garry, Kocher Martin, Lerche Christoph W, Rapp Marion, Fink Gereon R, Shah Nadim J, Langen Karl-Josef, Galldiks Norbert

机构信息

Institute of Neuroscience and Medicine (INM-3, -4, -11), Research Center Juelich, 52425 Juelich, Germany.

Department of Stereotaxy and Functional Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50937 Cologne, Germany.

出版信息

Cancers (Basel). 2020 Dec 18;12(12):3835. doi: 10.3390/cancers12123835.

DOI:10.3390/cancers12123835
PMID:33353180
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7766151/
Abstract

Currently, a reliable diagnostic test for differentiating pseudoprogression from early tumor progression is lacking. We explored the potential of O-(2-[F]fluoroethyl)-L-tyrosine (FET) positron emission tomography (PET) radiomics for this clinically important task. Thirty-four patients (isocitrate dehydrogenase (IDH)-wildtype glioblastoma, 94%) with progressive magnetic resonance imaging (MRI) changes according to the Response Assessment in Neuro-Oncology (RANO) criteria within the first 12 weeks after completing temozolomide chemoradiation underwent a dynamic FET PET scan. Static and dynamic FET PET parameters were calculated. For radiomics analysis, the number of datasets was increased to 102 using data augmentation. After randomly assigning patients to a training and test dataset, 944 features were calculated on unfiltered and filtered images. The number of features for model generation was limited to four to avoid data overfitting. Eighteen patients were diagnosed with early tumor progression, and 16 patients had pseudoprogression. The FET PET radiomics model correctly diagnosed pseudoprogression in all test cohort patients (sensitivity, 100%; negative predictive value, 100%). In contrast, the diagnostic performance of the best FET PET parameter (TBR) was lower (sensitivity, 81%; negative predictive value, 80%). The results suggest that FET PET radiomics helps diagnose patients with pseudoprogression with a high diagnostic performance. Given the clinical significance, further studies are warranted.

摘要

目前,尚缺乏一种可靠的诊断测试来区分假性进展与早期肿瘤进展。我们探索了O-(2-[F]氟乙基)-L-酪氨酸(FET)正电子发射断层扫描(PET)放射组学在这项临床重要任务中的潜力。34例患者(异柠檬酸脱氢酶(IDH)野生型胶质母细胞瘤,94%)在完成替莫唑胺放化疗后的前12周内,根据神经肿瘤学疗效评估(RANO)标准出现了进行性磁共振成像(MRI)变化,接受了动态FET PET扫描。计算了静态和动态FET PET参数。为了进行放射组学分析,使用数据增强将数据集数量增加到102个。在将患者随机分配到训练和测试数据集后,在未过滤和过滤后的图像上计算了944个特征。为避免数据过度拟合,将用于模型生成的特征数量限制为4个。18例患者被诊断为早期肿瘤进展,16例患者为假性进展。FET PET放射组学模型在所有测试队列患者中正确诊断出假性进展(敏感性,100%;阴性预测值,100%)。相比之下,最佳FET PET参数(TBR)的诊断性能较低(敏感性,81%;阴性预测值,80%)。结果表明,FET PET放射组学有助于以高诊断性能诊断假性进展患者。鉴于其临床意义,有必要进一步研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/907c/7766151/29517cac9e51/cancers-12-03835-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/907c/7766151/d117657f2fe0/cancers-12-03835-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/907c/7766151/29517cac9e51/cancers-12-03835-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/907c/7766151/d117657f2fe0/cancers-12-03835-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/907c/7766151/29517cac9e51/cancers-12-03835-g002.jpg

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3
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EJNMMI Phys. 2025 Jun 6;12(1):54. doi: 10.1186/s40658-025-00767-y.
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