建立造影剂增强超声波和 Gd-EOB-DTPA 增强 MRI 对肝细胞癌血管包裹肿瘤簇模式的提名图预测模型

IF 5.7 4区 生物学 Q1 BIOLOGY Bioscience trends Pub Date : 2024-07-09 Epub Date: 2024-06-12 DOI:10.5582/bst.2024.01112
Feiqian Wang, Kazushi Numata, Akihiro Funaoka, Xi Liu, Takafumi Kumamoto, Kazuhisa Takeda, Makoto Chuma, Akito Nozaki, Litao Ruan, Shin Maeda
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引用次数: 0

摘要

利用肝细胞癌(HCC)患者术前对比增强超声波(CEUS)和钆乙氧苄基二乙烯三胺五乙酸磁共振成像(EOB-MRI)建立血管包裹肿瘤簇(VETC)模式的临床预测模型。研究共纳入了 101 名患者的 111 个切除的 HCC 病灶。从病历中收集了术前CEUS和EOB-MRI成像特征、术后复发和生存信息。采用最佳子集回归和多变量 Cox 回归选择变量建立预测模型。据统计,VETC阳性组的生存率低于VETC阴性组。所选变量包括 EOB-MRI 上动脉期(AP)和肝胆期(HBP)的瘤周强化、CEUS AP 的瘤内分支强化、CEUS 门脉期的瘤内低强化、不完整囊和肿瘤大小。结果得出了一个提名图。以 168 分为临界值的高分和低分提名图显示了不同的无复发生存率和总生存率。曲线下面积(AUC)和准确率分别为 0.804 和 0.820,显示出良好的区分度。决策曲线分析显示了良好的临床净效益(阈值概率>5%),而 Hosmer-Lemeshow 检验得出了极好的校准结果(P = 0.6759)。结合 EOB-MRI 和 CEUS 的提名图模型的 AUC 值高于仅包含 EOB-MRI 因素的模型(0.767)和仅包含 CEUS 因素的模型(0.7)。通过引导法验证的提名图显示的 AUC 和校准曲线与提名图模型相似。基于 CEUS 和 EOB-MRI 的预测模型对 VETC 的术前无创诊断是有效的。
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Establishment of nomogram prediction model of contrast-enhanced ultrasound and Gd-EOB-DTPA-enhanced MRI for vessels encapsulating tumor clusters pattern of hepatocellular carcinoma.

To establish clinical prediction models of vessels encapsulating tumor clusters (VETC) pattern using preoperative contrast-enhanced ultrasound (CEUS) and gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid magnetic resonance imaging (EOB-MRI) in patients with hepatocellular carcinoma (HCC). A total of 111 resected HCC lesions from 101 patients were included. Preoperative imaging features of CEUS and EOB-MRI, postoperative recurrence, and survival information were collected from medical records. The best subset regression and multivariable Cox regression were used to select variables to establish the prediction model. The VETC-positive group had a statistically lower survival rate than the VETC-negative group. The selected variables were peritumoral enhancement in the arterial phase (AP), hepatobiliary phase (HBP) on EOB-MRI, intratumoral branching enhancement in the AP of CEUS, intratumoral hypoenhancement in the portal phase of CEUS, incomplete capsule, and tumor size. A nomogram was developed. High and low nomogram scores with a cutoff value of 168 points showed different recurrence-free survival rates and overall survival rates. The area under the curve (AUC) and accuracy were 0.804 and 0.820, respectively, indicating good discrimination. Decision curve analysis showed a good clinical net benefit (threshold probability > 5%), while the Hosmer-Lemeshow test yielded excellent calibration (P = 0.6759). The AUC of the nomogram model combining EOB-MRI and CEUS was higher than that of the models with EOB-MRI factors only (0.767) and CEUS factors only (0.7). The nomogram verified by bootstrapping showed AUC and calibration curves similar to those of the nomogram model. The Prediction model based on CEUS and EOB-MRI is effective for preoperative noninvasive diagnosis of VETC.

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来源期刊
CiteScore
13.60
自引率
1.80%
发文量
47
审稿时长
>12 weeks
期刊介绍: BioScience Trends (Print ISSN 1881-7815, Online ISSN 1881-7823) is an international peer-reviewed journal. BioScience Trends devotes to publishing the latest and most exciting advances in scientific research. Articles cover fields of life science such as biochemistry, molecular biology, clinical research, public health, medical care system, and social science in order to encourage cooperation and exchange among scientists and clinical researchers.
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