通过呼吸同步框架协同重建的高时空分辨率腹部4D-MRI

IF 3.2 2区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Medical physics Pub Date : 2025-09-10 DOI:10.1002/mp.18101
Yinghui Wang, Lu Wang, Yidan Feng, Zhi Chen, Jing Qin, Tian Li, Jing Cai
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引用次数: 0

摘要

四维磁共振成像(4D-MRI)在腹部放射治疗的精确指导方面具有很大的前景。然而,目前的4D-MRI方法受到空间和时间分辨率之间固有权衡的限制,导致图像质量受损,其特征是低空间分辨率和明显的运动伪影,阻碍了临床应用。尽管最近取得了进展,但现有的方法不能充分利用冗余的帧信息,并且很难从高度欠采样的采集中恢复结构细节。本研究旨在开发一种利用多帧信息来减轻空间欠采样的技术,从而在腹部4D-MRI中实现更高的时空分辨率。方法介绍了一种新的4D-MRI重建方法,利用呼吸同步帧重建目标帧,增强图像质量。具体来说,我们引入了一种多帧协同重建网络(MCR-Net),该网络利用帧间相关性和互补信息进行忠实重建。MCR-Net集成了两个关键机制:帧间相互关注机制(IMM)和结构感知巩固模块(SaCM)。IMM通过利用相邻呼吸同步帧之间的相关性来增强特征提取,从而增强共享的解剖特征,同时抑制随机伪影和噪声。SaCM通过利用上下文感知残差学习、增强高频细节以及在多帧融合过程中过滤无关数据来整合跨帧的结构信息,从而显著提高清晰度和解剖完整性。结果对临床患者数据集(训练:n = 20;验证:n = 6)的实验评估表明,我们的方法在视觉质量和定量准确性方面明显优于九种最先进的重建方法。MCR-Net在MAE、SSIM和PSNR方面表现优异,分别比次优方法高出3.77%、1.03%和6.74%。此外,我们的实验验证了MCR-Net在MAE、SSIM和NCC指标上比原始低质量4D-MRI的配准精度提高了10.66%、3.60%和1.94%。此外,仿真结果表明,即使在欠采样率显著增加的情况下,MCR-Net也能有效地保持高图像质量。我们的研究结果表明,MCR-Net可以有效地抑制伪影,并从采样不足的图像中恢复缺失的解剖结构,强调其在增强4D-MRI时空分辨率和推进腹部放疗临床应用方面的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

High spatiotemporal-resolution abdominal 4D-MRI through respiratory-synchronized frame collaborative reconstruction

High spatiotemporal-resolution abdominal 4D-MRI through respiratory-synchronized frame collaborative reconstruction

High spatiotemporal-resolution abdominal 4D-MRI through respiratory-synchronized frame collaborative reconstruction

Background

Four-dimensional magnetic resonance imaging (4D-MRI) holds great promise for precise abdominal radiotherapy guidance. However, current 4D-MRI methods are limited by an inherent trade-off between spatial and temporal resolutions, resulting in compromised image quality characterized by low spatial resolution and significant motion artifacts, hindering clinical implementation. Despite recent advancements, existing methods inadequately exploit redundant frame information and struggle to restore structural details from highly undersampled acquisitions.

Purpose

This study aims to develop a technique that leverages information across multiple frames to mitigate spatial undersampling, thereby enabling superior spatiotemporal resolution in abdominal 4D-MRI.

Methods

We introduce a novel reconstruction approach for 4D-MRI that leverages respiratory-synchronized frames to reconstruct target frames with enhanced image quality. Specifically, we introduce a multi-frame collaborative reconstruction network (MCR-Net) that capitalizes on inter-frame correlations and complementary information for faithful reconstruction. MCR-Net integrates two key mechanisms: the Inter-frame mutual-attention mechanism (IMM) and the structure-aware consolidation module (SaCM). IMM enhances feature extraction by exploiting correlations among neighboring respiratory-synchronized frames, thereby reinforcing shared anatomical features while suppressing random artifacts and noise. SaCM consolidates structural information across frames by leveraging context-aware residual learning, enhancing high-frequency details, and filtering irrelevant data during multi-frame fusion, thus significantly improving the clarity and anatomical integrity.

Results

Experimental evaluations on clinical patient datasets (training: n = 20; validation: n = 6) demonstrate that our method significantly outperforms nine state-of-the-art reconstruction approaches in both visual quality and quantitative accuracy. MCR-Net achieves superior performance in MAE, SSIM, and PSNR, outperforming the next-best methods by 3.77%, 1.03%, and 6.74%, respectively. Furthermore, our experiments validate that MCR-Net enhances registration accuracy compared to original low-quality 4D-MRI by 10.66%, 3.60%, and 1.94% in MAE, SSIM, and NCC metrics. Additionally, simulations demonstrate that MCR-Net effectively maintains high image quality even under significantly increased undersampling ratios.

Conclusion

Our findings demonstrate that MCR-Net effectively suppresses artifacts and recovers missing anatomical structures from undersampled acquisitions, underscoring its potential to enhance 4D-MRI's spatiotemporal resolution and advance clinical applications in abdominal radiotherapy.

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来源期刊
Medical physics
Medical physics 医学-核医学
CiteScore
6.80
自引率
15.80%
发文量
660
审稿时长
1.7 months
期刊介绍: Medical Physics publishes original, high impact physics, imaging science, and engineering research that advances patient diagnosis and therapy through contributions in 1) Basic science developments with high potential for clinical translation 2) Clinical applications of cutting edge engineering and physics innovations 3) Broadly applicable and innovative clinical physics developments Medical Physics is a journal of global scope and reach. By publishing in Medical Physics your research will reach an international, multidisciplinary audience including practicing medical physicists as well as physics- and engineering based translational scientists. We work closely with authors of promising articles to improve their quality.
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