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基于CE增强黑血CT技术评估胰腺导管腺癌的血管侵犯情况。

Assessment of vascular invasion of pancreatic ductal adenocarcinoma based on CE-boost black blood CT technique.

作者信息

Lin Yue, Liu Tongxi, Hu Yingying, Xu Yinghao, Wang Jian, Guo Sijia, Xie Sheng, Sun Hongliang

机构信息

Department of Radiology, China-Japan Friendship Hospital, Beijing, China.

CT Clinical Research Department, CT Business Unit, Canon Medical Systems (China) Co., Ltd., Beijing, China.

出版信息

Insights Imaging. 2024 Dec 5;15(1):293. doi: 10.1186/s13244-024-01870-x.

Abstract

OBJECTIVES

To explore the diagnostic efficacy of advanced intelligent clear-IQ engine (AiCE) and adaptive iterative dose reduction 3D (AIDR 3D), combination with and without the black blood CT technique (BBCT), for detecting vascular invasion in patients diagnosed with nonmetastatic pancreatic ductal adenocarcinoma (PDAC).

METHODS

A total of 35 consecutive patients diagnosed with PDAC, proceeding with contrast-enhanced abdominal CT scans, were enrolled in this study. The arterial and portal venous phase images were reconstructed using AiCE and AIDR 3D. The corresponding BBCT images were established as AiCE-BBCT and AIDR 3D-BBCT, respectively. Two observers scored the image quality independently. Cohen's kappa (k) value or intraclass correlation coefficient (ICC) was used to analyze consistency. The diagnostic performance of four algorithms in detecting vascular invasion in PDAC patients was assessed using the area under the curve (AUC).

RESULTS

The AiCE and AiCE-BBCT groups demonstrated superior image noise and diagnostic acceptability compared with AIDR 3D and AIDR 3D-BBCT groups (all p < 0.001), and the k value was 0.861-0.967 for both reviewers. In terms of diagnostic capability for vascular invasion in PDAC, the AiCE-BBCT group exhibited higher specificity (95.0%) and sensitivity (93.3%) compared to the AIDR 3D and AIDR 3D-BBCT groups, with an AUC of 0.942 (95% CI: 0.849-1.000, p < 0.05). Furthermore, all vascular evaluations conducted using AiCE-BBCT demonstrated better consistency (ICC: 0.847-0.935).

CONCLUSION

The BBCT technique in conjunction with AiCE could lead to notable enhancements in both the image quality of PDAC images and the diagnostic performance for tumor vascular invasion.

CRITICAL RELEVANCE STATEMENT

Better diagnostic accuracy of vascular invasion of PDAC based on BBCT in combination with an AiCE is a critical factor in determining treatment strategies and patient outcomes.

KEY POINTS

Identifying vascular invasion of PDAC is important for prognostication. Combined images provide improved image quality and higher diagnostic accuracy. Combined images can excellently display the vascular wall and invasion.

摘要

目的

探讨高级智能清晰-IQ引擎(AiCE)和自适应迭代剂量降低3D(AIDR 3D)联合或不联合黑血CT技术(BBCT)对诊断非转移性胰腺导管腺癌(PDAC)患者血管侵犯的诊断效能。

方法

本研究纳入35例连续诊断为PDAC且进行了腹部增强CT扫描的患者。使用AiCE和AIDR 3D重建动脉期和门静脉期图像。相应的BBCT图像分别确定为AiCE-BBCT和AIDR 3D-BBCT。两名观察者独立对图像质量进行评分。采用Cohen's kappa(k)值或组内相关系数(ICC)分析一致性。使用曲线下面积(AUC)评估四种算法检测PDAC患者血管侵犯的诊断性能。

结果

与AIDR 3D和AIDR 3D-BBCT组相比,AiCE和AiCE-BBCT组表现出更好的图像噪声和诊断可接受性(所有p < 0.001),两位观察者的k值均为0.861 - 0.967。在PDAC血管侵犯的诊断能力方面,与AIDR 3D和AIDR 3D-BBCT组相比,AiCE-BBCT组表现出更高的特异性(95.0%)和敏感性(93.3%),AUC为0.942(95%CI:0.849 - 1.000,p < 0.05)。此外,使用AiCE-BBCT进行的所有血管评估显示出更好的一致性(ICC:0.847 - 0.935)。

结论

BBCT技术与AiCE联合可显著提高PDAC图像的质量和肿瘤血管侵犯的诊断性能。

关键相关性声明

基于BBCT联合AiCE提高PDAC血管侵犯的诊断准确性是确定治疗策略和患者预后的关键因素。

要点

识别PDAC的血管侵犯对预后评估很重要。联合图像可提高图像质量和诊断准确性。联合图像能出色地显示血管壁和侵犯情况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83c6/11621291/0ba0a87c96b8/13244_2024_1870_Fig1_HTML.jpg

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