Deep Learning-Based Signal Amplification of T1-Weighted Single-Dose Images Improves Metastasis Detection in Brain MRI.

IF 8 1区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Investigative Radiology Pub Date : 2025-08-01 Epub Date: 2025-02-18 DOI:10.1097/RLI.0000000000001166
Robert Haase, Thomas Pinetz, Erich Kobler, Zeynep Bendella, Stefan Zülow, Arndt-Hendrik Schievelkamp, Frederic Carsten Schmeel, Sarah Panahabadi, Anna Magdalena Stylianou, Daniel Paech, Martha Foltyn-Dumitru, Verena Wagner, Kai Schlamp, Gudula Heussel, Mathias Holtkamp, Claus Peter Heussel, Martin Vahlensieck, Julian A Luetkens, Heinz-Peter Schlemmer, Johannes Haubold, Alexander Radbruch, Alexander Effland, Cornelius Deuschl, Katerina Deike
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Abstract

Objectives: Double-dose contrast-enhanced brain imaging improves tumor delineation and detection of occult metastases but is limited by concerns about gadolinium-based contrast agents' effects on patients and the environment. The purpose of this study was to test the benefit of a deep learning-based contrast signal amplification in true single-dose T1-weighted (T-SD) images creating artificial double-dose (A-DD) images for metastasis detection in brain magnetic resonance imaging.

Materials and methods: In this prospective, multicenter study, a deep learning-based method originally trained on noncontrast, low-dose, and T-SD brain images was applied to T-SD images of 30 participants (mean age ± SD, 58.5 ± 11.8 years; 23 women) acquired externally between November 2022 and June 2023. Four readers with different levels of experience independently reviewed T-SD and A-DD images for metastases with 4 weeks between readings. A reference reader reviewed additionally acquired true double-dose images to determine any metastases present. Performances were compared using Mid-p McNemar tests for sensitivity and Wilcoxon signed rank tests for false-positive findings.

Results: All readers found more metastases using A-DD images. The 2 experienced neuroradiologists achieved the same level of sensitivity using T-SD images (62 of 91 metastases, 68.1%). While the increase in sensitivity using A-DD images was only descriptive for 1 of them (A-DD: 65 of 91 metastases, +3.3%, P = 0.424), the second neuroradiologist benefited significantly with a sensitivity increase of 12.1% (73 of 91 metastases, P = 0.008). The 2 less experienced readers (1 resident and 1 fellow) both found significantly more metastases on A-DD images (resident, T-SD: 61.5%, A-DD: 68.1%, P = 0.039; fellow, T-SD: 58.2%, A-DD: 70.3%, P = 0.008). They were therefore able to use A-DD images to increase their sensitivity to the neuroradiologists' initial level on regular T-SD images. False-positive findings did not differ significantly between sequences. However, readers showed descriptively more false-positive findings on A-DD images. The benefit in sensitivity particularly applied to metastases ≤5 mm (5.7%-17.3% increase in sensitivity).

Conclusions: A-DD images can improve the detectability of brain metastases without a significant loss of precision and could therefore represent a potentially valuable addition to regular single-dose brain imaging.

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基于深度学习的t1加权单剂量图像信号放大提高脑MRI转移检测。
目的:双剂量对比增强脑成像改善了肿瘤的描绘和隐匿性转移的检测,但由于对钆基对比剂对患者和环境的影响的担忧而受到限制。本研究的目的是测试基于深度学习的对比信号放大在真正的单剂量t1加权(T-SD)图像中创建人工双剂量(a - dd)图像用于脑磁共振成像中转移检测的益处。材料和方法:在这项前瞻性、多中心的研究中,一种基于深度学习的方法最初训练于非对比、低剂量和T-SD脑图像,应用于30名参与者的T-SD图像(平均年龄±SD, 58.5±11.8岁;23名女性)在2022年11月至2023年6月期间从外部收购。四名具有不同经验水平的阅读者独立阅读T-SD和A-DD图像的转移,阅读间隔4周。参考读者回顾了额外获得的真实双剂量图像,以确定是否存在转移。使用Mid-p McNemar检验灵敏度和Wilcoxon符号秩检验假阳性结果进行比较。结果:所有读者均发现更多的A-DD图像转移。2名经验丰富的神经放射学家使用T-SD图像获得了相同水平的敏感性(91例转移中有62例,68.1%)。虽然使用a - dd图像的敏感性增加仅对其中1人具有描述性(a - dd: 91例转移患者中的65例,+3.3%,P = 0.424),但第二位神经放射学家受益显著,敏感性增加12.1%(91例转移患者中的73例,P = 0.008)。2名经验不足的读者(1名住院患者和1名非住院患者)在A-DD图像上均发现更多转移灶(住院患者,T-SD: 61.5%, A-DD: 68.1%, P = 0.039;T-SD: 58.2%, A-DD: 70.3%, P = 0.008)。因此,他们能够使用A-DD图像来提高他们对神经放射学家对常规T-SD图像的初始水平的敏感度。假阳性结果在不同序列间无显著差异。然而,读者在A-DD图像上表现出更多的假阳性结果。敏感性的获益尤其适用于≤5mm的转移瘤(敏感性增加5.7%-17.3%)。结论:a - dd图像可以提高脑转移的可检测性,而不会显著降低准确性,因此可能是常规单剂量脑成像的潜在有价值的补充。
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来源期刊
Investigative Radiology
Investigative Radiology 医学-核医学
CiteScore
15.10
自引率
16.40%
发文量
188
审稿时长
4-8 weeks
期刊介绍: Investigative Radiology publishes original, peer-reviewed reports on clinical and laboratory investigations in diagnostic imaging, the diagnostic use of radioactive isotopes, computed tomography, positron emission tomography, magnetic resonance imaging, ultrasound, digital subtraction angiography, and related modalities. Emphasis is on early and timely publication. Primarily research-oriented, the journal also includes a wide variety of features of interest to clinical radiologists.
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