Color Mapping using Ultrasound System-integrated Perfusion Software for Evaluation of Focal Liver Lesions: A Possible First Step for More Independent Reading.

Ivor Dropco, Ulrich Kaiser, Lola Wagner, Stefan M Brunner, Hans Jürgen Schlitt, Christian Stroszcynski, Friedrich Jung, Dong Yi, Wolfgang Herr, Ernst Michael Jung
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Abstract

Aims: To assess the value of using integrated parametric ultrasound software for contrast-enhanced ultrasonography (CEUS) of liver tumors.

Methods: 107 patients with liver tumors were studied. CEUS were performed to detect focal lesions. Parametric images were based on continuous CINE LOOPs, from the early-arterial phase (15 s) to the portal-venous phase (1 min) generated by perfusion software. The evaluations of the parametric images and their dignity for liver lesions were performed independently by an experienced and a less-experienced investigator. Computed tomography, magnetic resonance imaging scans or histological analysis were used as references.

Results: High parametric image quality were obtained in all patients. Among the patients, 44% lesions were benign, 56% were malignant. The experienced investigator correctly classified 46 of 47 (98%) as benign, and 60 of 60 (100%) as malignant tumors based on the parametric images. The less-experienced investigator correctly classified 39 of 47 (83%) as benign, and 49 of 60 (82%) malignant tumors, acheaving a high statistical accuracy of 98% with this type of diagnostic.

Conclusion: Parametric imaging for grading the malignant degree of tumor may be a good complement to existing ultrasound techniques and was particularly helpful for improving the assessments of the less-experienced examiner.

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利用超声系统集成灌注软件绘制彩色图谱,评估肝脏病灶:更多自主阅读的第一步。
目的:评估在肝脏肿瘤对比增强超声造影(CEUS)中使用集成参数超声软件的价值。进行CEUS检查以检测病灶。参数图像基于灌注软件生成的从早期动脉期(15 秒)到门-静脉期(1 分钟)的连续 CINE LOOP。一名经验丰富的研究人员和一名经验较少的研究人员分别独立评估参数图像及其对肝脏病变的重要性。计算机断层扫描、磁共振成像扫描或组织学分析作为参考:所有患者均获得了高参数图像质量。其中,44%为良性病变,56%为恶性病变。根据参数图像,经验丰富的研究人员将 47 例中的 46 例(98%)正确分类为良性肿瘤,将 60 例中的 60 例(100%)正确分类为恶性肿瘤。经验较少的研究人员则将 47 例中的 39 例(83%)正确划分为良性肿瘤,将 60 例中的 49 例(82%)正确划分为恶性肿瘤,此类诊断的统计准确率高达 98%:参数成像对肿瘤恶性程度的分级可能是对现有超声技术的良好补充,尤其有助于提高经验不足的检查人员的评估能力。
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