CT深度学习重建与迭代重建及3-特斯拉MRI表征肝癌的比较

IF 4.7 2区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
European Radiology Pub Date : 2025-07-01 Epub Date: 2025-01-08 DOI:10.1007/s00330-024-11314-1
Clément Malthiery, Gabriela Hossu, Ahmet Ayav, Valérie Laurent
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引用次数: 0

摘要

目的:本研究比较了肝细胞癌(HCC)可疑病变的特征及其在自适应统计迭代重建(ASIR)和深度学习重建(DLR)中的LI-RADS分类与MR图像的特征,以及放射科医生的信心。材料和方法:本前瞻性单中心试验纳入了2023年2月至8月7天内接受四期肝脏CT和多期增强MRI检查的患者。比较两名放射科医师对ASIR、DLR和MRI技术的病变特征、LI-RADS分类和置信度评分。如果患者至少有一种病变,则将其纳入HCC组,否则将其纳入非HCC组。MRI是灵敏度最高的技术,通过ASIR与MRI、DLR与MRI之间的加权kappa计算病变特征和LI-RADS分类的一致性。置信分数表示为均值和标准差。结果:89例患者入组,HCC组52例(67岁±9 [mean±SD], 46例男性),非HCC组37例(68岁±9,33例男性)。ASIR与MRI对LI-RADS分类的一致性系数为0.64 [0.52;0.76],一致性较好,DLR与MRI为0.83 [0.73;0.92],表现出极好的一致性。ASIR诊断置信度分别为3.31±0.95 (mean±SD)和3.0±1.11,DLR诊断置信度分别为3.9±0.88和4.11±0.75,MRI诊断置信度分别为4.46±0.80和4.57±0.80。结论:DLR与MRI具有良好的LI-RADS分类一致性,而ASIR具有良好的一致性。放射科医生的信心在DLR组比在ASIR组更大,但在MR组仍然是最高的。与自适应统计迭代重建(ASIR)相比,使用深度学习重建(DLR)是否提高了LI-RADS对可疑肝细胞癌病变的分类?结果与ASIR相比,DLR显示LI-RADS分类与MRI的一致性更好。它也提供了比ASIR更大的诊断信心。DLR的使用增强了放射科医生观察和描述疑似HCC病变的能力,以及其LI-RADS分类的能力。此外,这也增强了他们解读这些图像的信心。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Characterization of hepatocellular carcinoma with CT with deep learning reconstruction compared with iterative reconstruction and 3-Tesla MRI.

Objectives: This study compared the characteristics of lesions suspicious for hepatocellular carcinoma (HCC) and their LI-RADS classifications in adaptive statistical iterative reconstruction (ASIR) and deep learning reconstruction (DLR) to those of MR images, along with radiologist confidence.

Materials and methods: This prospective single-center trial included patients who underwent four-phase liver CT and multiphasic contrast-enhanced MRI within 7 days from February to August 2023. The lesion characteristics, LI-RADS classifications and confidence scores according to two radiologists on the ASIR, DLR and MRI techniques were compared. If the patient had at least one lesion, he was included in the HCC group, otherwise in the non-HCC group. MRI being the technique with the best sensitivity, concordance of lesions characteristics and LI-RADS classifications were calculated by weighted kappa between the ASIR and MRI and between the DLR and MRI. The confidence scores are expressed as the means and standard deviations.

Results: Eighty-nine patients were enrolled, 52 in the HCC group (67 years ± 9 [mean ± SD], 46 men) and 37 in the non-HCC group (68 years ± 9, 33 men). The concordance coefficient between the LI-RADS classification by ASIR and MRI was 0.64 [0.52; 0.76], showing good agreement, that by DLR and MRI was 0.83 [0.73; 0.92], showing excellent agreement. The diagnostic confidence in ASIR was 3.31 ± 0.95 (mean ± SD) and 3.0 ± 1.11, that in the DLR was 3.9 ± 0.88 and 4.11 ± 0.75, that in the MRI was 4.46 ± 0.80 and 4.57 ± 0.80.

Conclusion: DLR provided excellent LI-RADS classification concordance with MRI, whereas ASIR provided good concordance. The radiologists' confidence was greater in the DLR than in the ASIR but remained highest in the MR group.

Key points: Question Does the use of deep learning reconstructions (DLR) improve LI-RADS classification of suspicious hepatocellular carcinoma lesions compared to adaptive statistical iterative reconstructions (ASIR)? Findings DLR demonstrated superior concordance of LI-RADS classification with MRI compared to ASIR. It also provided greater diagnostic confidence than ASIR. Clinical relevance The use of DLR enhances radiologists' ability to visualize and characterize lesions suspected of being HCC, as well as their LI-RADS classification. Moreover, it also boosts their confidence in interpreting these images.

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来源期刊
European Radiology
European Radiology 医学-核医学
CiteScore
11.60
自引率
8.50%
发文量
874
审稿时长
2-4 weeks
期刊介绍: European Radiology (ER) continuously updates scientific knowledge in radiology by publication of strong original articles and state-of-the-art reviews written by leading radiologists. A well balanced combination of review articles, original papers, short communications from European radiological congresses and information on society matters makes ER an indispensable source for current information in this field. This is the Journal of the European Society of Radiology, and the official journal of a number of societies. From 2004-2008 supplements to European Radiology were published under its companion, European Radiology Supplements, ISSN 1613-3749.
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