动态对比度增强核磁共振成像的放射组学模型用于评估肝细胞癌中包裹肿瘤簇的血管和微血管侵犯情况

IF 3.8 2区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Academic Radiology Pub Date : 2025-01-01 Epub Date: 2024-07-18 DOI:10.1016/j.acra.2024.07.007
Jiawen Yang, Xue Dong, Shengze Jin, Sheng Wang, Yanna Wang, Limin Zhang, Yuguo Wei, Yitian Wu, Lingxia Wang, Lingwei Zhu, Yuyi Feng, Meifu Gan, Hongjie Hu, Wenbin Ji
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引用次数: 0

摘要

理论依据和目标:开发和验证动态对比增强核磁共振成像(DCE-MRI)的临床放射组学模型,用于术前鉴别肝细胞癌(HCC)的血管包裹肿瘤簇(VETC)-微血管侵犯(MVI)和预后。材料和方法:将第一研究所的219名HCC患者分为内部培训组和验证组,并将第二研究所的101名患者分配到外部验证组。组织学证实的VETC-MVI模式将HCC分为VM-HCC+(VETC+/MVI+、VETC-/MVI+、VETC+/MVI-)和VM-HCC-(VETC-/MVI-)。在 DCE-MRI 的动脉期、门静脉期和延迟期(分别为 AP、PP 和 DP),对肿瘤内和肿瘤周围区域进行人工分割。为评估 VM-HCC 建立了六个放射组学模型(DCE-MRI 的 AP、PP 和 DP 阶段的瘤内和瘤周)和一个临床模型。结合瘤内和瘤周特征,建立瘤内和瘤周模型。然后将表现最好的放射组学模型和临床模型整合在一起,创建一个联合模型:结果:在机构 1 中,88 名患者的病理证实为 VM-HCC+(训练集:61 例,验证集:27 例)。在内部测试中,联合模型的AUC为0.85(95% CI:0.76-0.93),在外部验证中AUC达到0.75(95% CI:0.66-0.85)。该模型的预测结果与HCC患者的早期复发和无进展生存期相关:结论:临床放射组学模型提供了一种非侵入性的方法来识别VM-HCC并在术前预测HCC患者的预后,这能为临床医生在决策阶段提供有价值的见解。
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Radiomics Model of Dynamic Contrast-Enhanced MRI for Evaluating Vessels Encapsulating Tumor Clusters and Microvascular Invasion in Hepatocellular Carcinoma.

Rationale and objectives: To develop and validate a clinical-radiomics model of dynamic contrast-enhanced MRI (DCE-MRI) for the preoperative discrimination of Vessels encapsulating tumor clusters (VETC)- microvascular invasion (MVI) and prognosis of hepatocellular carcinoma (HCC).

Materials and methods: 219 HCC patients from Institution 1 were split into internal training and validation groups, with 101 patients from Institution 2 assigned to external validation. Histologically confirmed VETC-MVI pattern categorizing HCC into VM-HCC+ (VETC+/MVI+, VETC-/MVI+, VETC+/MVI-) and VM-HCC- (VETC-/MVI-). The regions of intratumor and peritumor were segmented manually in the arterial, portal-venous and delayed phase (AP, PP, and DP, respectively) of DCE-MRI. Six radiomics models (intratumor and peritumor in AP, PP, and DP of DCE-MRI) and one clinical model were developed for assessing VM-HCC. Establishing intra-tumoral and peri-tumoral models through combining intratumor and peritumor features. The best-performing radiomics model and the clinical model were then integrated to create a Combined model.

Results: In institution 1, pathological VM-HCC+ were confirmed in 88 patients (training set: 61, validation set: 27). In internal testing, the Combined model had an AUC of 0.85 (95% CI: 0.76-0.93), which reached an AUC of 0.75 (95% CI: 0.66-0.85) in external validation. The model's predictions were associated with early recurrence and progression-free survival in HCC patients.

Conclusions: The clinical-radiomics model offers a non-invasive approach to discern VM-HCC and predict HCC patients' prognosis preoperatively, which could offer clinicians valuable insights during the decision-making phase.

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来源期刊
Academic Radiology
Academic Radiology 医学-核医学
CiteScore
7.60
自引率
10.40%
发文量
432
审稿时长
18 days
期刊介绍: Academic Radiology publishes original reports of clinical and laboratory investigations in diagnostic imaging, the diagnostic use of radioactive isotopes, computed tomography, positron emission tomography, magnetic resonance imaging, ultrasound, digital subtraction angiography, image-guided interventions and related techniques. It also includes brief technical reports describing original observations, techniques, and instrumental developments; state-of-the-art reports on clinical issues, new technology and other topics of current medical importance; meta-analyses; scientific studies and opinions on radiologic education; and letters to the Editor.
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