InspirationOnly: synthesizing expiratory CT from inspiratory CT to estimate parametric response map.

IF 2.6 4区 医学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Tiande Zhang, Haowen Pang, Yanan Wu, Jiaxuan Xu, Zhenyu Liang, Shuyue Xia, Chenwang Jin, Rongchang Chen, Shouliang Qi
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引用次数: 0

Abstract

Chronic obstructive pulmonary disease (COPD) is a highly heterogeneous disease with various phenotypes. Registered inspiratory and expiratory CT images can generate the parametric response map (PRM) that characterizes phenotypes' spatial distribution and proportions. However, increased radiation dosage, scan time, quality control, and patient cooperation requirements limit the utility of PRM. This study aims to synthesize a PRM using only inspiratory CT scans. First, a CycleGAN with perceptual loss and a multiscale discriminator (MPCycleGAN) is proposed and trained to synthesize registered expiratory CT images from inspiratory images. Next, a strategy named InspirationOnly is introduced, where synthesized images replace actual expiratory CT images. The image synthesizer outperformed state-of-the-art models, achieving a mean absolute error of 105.66 ± 36.64 HU, a peak signal-to-noise ratio of 21.43 ± 1.87 dB, and a structural similarity of 0.84 ± 0.02. The intraclass correlation coefficients of emphysema, fSAD, and normal proportions between the InspirationOnly and ground truth were 0.995, 0.829, and 0.914, respectively. The proposed MPCycleGAN enables the InspirationOnly strategy to yield PRM using only inspiratory CT. The estimated COPD phenotypes are consistent with those from dual-phase CT and correlated with the spirometry parameters. This offers a potential tool for characterizing phenotypes of COPD, particularly when expiratory CT images are unavailable.

InspirationOnly:从吸气CT合成呼气CT,估计参数响应图。
慢性阻塞性肺疾病(COPD)是一种具有多种表型的高度异质性疾病。注册的吸气和呼气CT图像可以生成表征表型空间分布和比例的参数响应图(PRM)。然而,放射剂量、扫描时间、质量控制和患者配合要求的增加限制了PRM的应用。本研究旨在仅使用吸气式CT扫描合成PRM。首先,提出并训练了具有感知损失和多尺度判别器的CycleGAN (MPCycleGAN),用于从吸气图像合成配准的呼气CT图像。接下来,介绍了一种名为InspirationOnly的策略,即合成图像取代实际呼气CT图像。该图像合成器的平均绝对误差为105.66±36.64 HU,峰值信噪比为21.43±1.87 dB,结构相似度为0.84±0.02。肺气肿、fSAD和正常比例的类内相关系数分别为0.995、0.829和0.914。提出的MPCycleGAN使仅使用吸气CT的InspirationOnly策略产生PRM。估计的COPD表型与双期CT结果一致,并与肺量测定参数相关。这为表征COPD的表型提供了一个潜在的工具,特别是在呼气CT图像不可用的情况下。
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来源期刊
Medical & Biological Engineering & Computing
Medical & Biological Engineering & Computing 医学-工程:生物医学
CiteScore
6.00
自引率
3.10%
发文量
249
审稿时长
3.5 months
期刊介绍: Founded in 1963, Medical & Biological Engineering & Computing (MBEC) continues to serve the biomedical engineering community, covering the entire spectrum of biomedical and clinical engineering. The journal presents exciting and vital experimental and theoretical developments in biomedical science and technology, and reports on advances in computer-based methodologies in these multidisciplinary subjects. The journal also incorporates new and evolving technologies including cellular engineering and molecular imaging. MBEC publishes original research articles as well as reviews and technical notes. Its Rapid Communications category focuses on material of immediate value to the readership, while the Controversies section provides a forum to exchange views on selected issues, stimulating a vigorous and informed debate in this exciting and high profile field. MBEC is an official journal of the International Federation of Medical and Biological Engineering (IFMBE).
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