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增强 CT 定量分析在鉴别高分化胰腺神经内分泌肿瘤和低分化神经内分泌癌中的应用。

Quantitative analysis of enhanced CT in differentiating well-differentiated pancreatic neuroendocrine tumors and poorly differentiated neuroendocrine carcinomas.

机构信息

Department of Radiology, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, 310022, China.

Institue of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, 310018, China.

出版信息

Eur Radiol. 2022 Dec;32(12):8317-8325. doi: 10.1007/s00330-022-08891-4. Epub 2022 Jun 27.

Abstract

OBJECTIVE

To identify quantitative CT features for distinguishing well-differentiated pancreatic neuroendocrine tumors (PNETs) from poorly differentiated pancreatic neuroendocrine carcinomas (PNECs).

MATERIALS AND METHODS

Seventeen patients with PNECs and 131 patients with PNETs confirmed by biopsy or surgery were retrospectively included. General demographic (sex, age) and CT quantitative parameters (arterial/portal absolute enhancement, arterial/portal relative enhancement ratio, arterial/portal enhancement ratio) were collected. Univariate and multivariate logistic regression analyses were performed to confirm independent variables for differentiating PNECs from PNETs. Receiver operating characteristic (ROC) curves for each quantitative parameter were generated to determine their diagnostic ability.

RESULTS

PNECs had a much lower mean arterial/portal absolute enhancement value (19.5 ± 11.0 vs. 78.8 ± 47.2; 28.1 ± 15.8 vs. 77.0 ± 39.4), arterial/portal relative enhancement ratio (0.57 ± 0.36 vs. 2.03 ± 1.31; 0.80 ± 0.52 vs. 1.99 ± 1.13), and arterial/portal enhancement ratio (0.62 ± 0.27 vs. 1.22 ± 0.49; 0.74 ± 0.19 vs. 1.21 ± 0.36) than PNETs (all p < 0.001). After multivariable analysis, arterial absolute enhancement (odds ratio [OR]: 0.96, 95% confidence interval [CI]: 0.93, 0.99) and portal absolute enhancement (OR: 0.96, 95% CI: 0.92, 0.99) were independent factors for differentiating PNECs from PNETs. For each quantitative parameter, arterial lesion enhancement yielded the highest diagnostic performance, with an area under the curve (AUC) of 0.922 (95% CI: 0.867-0.960), followed by portal absolute enhancement.

CONCLUSIONS

Arterial/portal absolute enhancements were independent predictors with good diagnostic accuracy for differentiating between PNETs and PNECs. Quantitative parameters of enhanced CT can distinguish PNECs from PNETs.

KEY POINTS

• PNECs were hypovascular and had a much lower enhanced CT attenuation in both arterial and portal phases than well-differentiated PNETs. • Quantitative parameters derived from enhanced CT can be used to distinguish PNECs from PNETs. • Arterial absolute enhancement and portal absolute enhancement were independent predictive factors for differentiating between PNETs and PNECs.

摘要

目的

确定定量 CT 特征,以区分高分化胰腺神经内分泌肿瘤(PNETs)和低分化胰腺神经内分泌癌(PNECs)。

材料与方法

回顾性纳入 17 例经活检或手术证实的 PNEC 患者和 131 例 PNET 患者。收集一般人口统计学(性别、年龄)和 CT 定量参数(动脉/门静脉绝对增强值、动脉/门静脉相对增强比值、动脉/门静脉增强比值)。采用单因素和多因素 logistic 回归分析确定区分 PNEC 和 PNET 的独立变量。生成每个定量参数的受试者工作特征(ROC)曲线,以确定其诊断能力。

结果

PNECs 的平均动脉/门静脉绝对增强值(19.5±11.0 比 78.8±47.2;28.1±15.8 比 77.0±39.4)、动脉/门静脉相对增强比值(0.57±0.36 比 2.03±1.31;0.80±0.52 比 1.99±1.13)和动脉/门静脉增强比值(0.62±0.27 比 1.22±0.49;0.74±0.19 比 1.21±0.36)均明显低于 PNETs(均 p<0.001)。多变量分析后,动脉绝对增强(比值比 [OR]:0.96,95%置信区间 [CI]:0.93,0.99)和门静脉绝对增强(OR:0.96,95%CI:0.92,0.99)是区分 PNEC 和 PNET 的独立因素。对于每个定量参数,动脉病变增强的诊断性能最高,曲线下面积(AUC)为 0.922(95%CI:0.867-0.960),其次是门静脉绝对增强。

结论

动脉/门静脉绝对增强是区分 PNET 和 PNEC 的独立预测因素,具有良好的诊断准确性。增强 CT 的定量参数可用于区分 PNEC 和 PNET。

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