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利用MUSE DWI结合RPG评估子宫癌的图像质量和局部肿瘤浸润情况。

Evaluating the image quality and local tumor invasion of uterine cancer by MUSE DWI with RPG.

作者信息

Zhao Wenjing, Liu Qing, Sun Jining, Pan Wenhui, Pylypenko Dmytro, Wang Wenjuan

机构信息

Department of Radiology, Weifang People's Hospital, Weifang, Shandong, 261041, China.

GE Healthcare, Beijing, China.

出版信息

Heliyon. 2024 Jul 30;10(15):e35440. doi: 10.1016/j.heliyon.2024.e35440. eCollection 2024 Aug 15.

DOI:10.1016/j.heliyon.2024.e35440
PMID:39170139
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11336590/
Abstract

Diffusion-weighted imaging (DWI) is widely utilized for evaluating uterine diseases. However, the prevalent technique, single-shot echo planar imaging (ssEPI), is hindered by notable image distortion and low spatial resolution. Therefore, optimizing uterine DWI sequences is vital for improving image quality. To investigate the efficacy of multiplexed sensitivity encoding (MUSE) combined with reverse polarity gradient (RPG) in enhancing uterine DWI quality and assessing local invasion in endometrial and cervical cancer, we included 149 patients. Each patient underwent DWI of the uterus using ssEPI, MUSE, and RPG-MUSE techniques. We compared these three sequences regarding image quality, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), geometric distortion rate (GDR), ADC values, accuracy in determining the extent of cancer invasion, and the Area Under the Curve (AUC) for identifying endometrial cancer and benign endometrial lesions using ADC values. The results indicated that RPG-MUSE DWI had less artifacts than MUSE and ssEPI ( < 0.05). Lesions were more apparent in MUSE and RPG-MUSE sequences compared to ssEPI (P < 0.05), with RPG-MUSE providing clearer lesion edges ( < 0.05). Additionally, RPG-MUSE DWI demonstrated higher SNR and CNR than ssEPI and MUSE ( < 0.05), along with a lower GDR ( < 0.05). The ADC values did not show significant differences among the three sequences ( > 0.05). Furthermore, the AUC of the ROC for detecting endometrial cancer and benign endometrial lesions using ADC values showed no significant differences across the sequences ( = 0.7609, 0.7186, and 0.8706, respectively). When combining each DWI sequence with T2WI for FIGO staging, RPG-MUSE and MUSE exhibited better alignment with pathology findings compared to ssEPI ( < 0.05). Overall, RPG-MUSE DWI showed fewer artifacts, higher SNR and CNR, reduced geometric distortion, and clearer lesion visualization compared to ssEPI and MUSE, leading to a more precise assessment of endometrial and cervical cancer invasion extent.

摘要

扩散加权成像(DWI)被广泛用于评估子宫疾病。然而,目前普遍使用的技术,即单次激发回波平面成像(ssEPI),受到明显的图像失真和低空间分辨率的限制。因此,优化子宫DWI序列对于提高图像质量至关重要。为了研究多重敏感性编码(MUSE)结合反极性梯度(RPG)在提高子宫DWI质量以及评估子宫内膜癌和宫颈癌局部浸润方面的效果,我们纳入了149例患者。每位患者均使用ssEPI、MUSE和RPG-MUSE技术对子宫进行DWI检查。我们比较了这三种序列在图像质量、信噪比(SNR)、对比噪声比(CNR)、几何失真率(GDR)、ADC值、确定癌症浸润范围的准确性以及使用ADC值鉴别子宫内膜癌和良性子宫内膜病变的曲线下面积(AUC)等方面的差异。结果表明,RPG-MUSE DWI的伪影比MUSE和ssEPI少(<0.05)。与ssEPI相比,病变在MUSE和RPG-MUSE序列中更明显(P<0.05),RPG-MUSE的病变边缘更清晰(<0.05)。此外,RPG-MUSE DWI的SNR和CNR高于ssEPI和MUSE(<0.05),GDR更低(<0.05)。三种序列的ADC值无显著差异(>0.05)。此外,使用ADC值检测子宫内膜癌和良性子宫内膜病变的ROC曲线的AUC在各序列间无显著差异(分别为=0.7609、0.7186和0.8706)。当将每个DWI序列与T2WI联合用于国际妇产科联盟(FIGO)分期时,与ssEPI相比,RPG-MUSE和MUSE与病理结果的一致性更好(<0.05)。总体而言,与ssEPI和MUSE相比,RPG-MUSE DWI的伪影更少,SNR和CNR更高,几何失真更小且病变显示更清晰,从而能够更精确地评估子宫内膜癌和宫颈癌的浸润范围。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f73/11336590/1f4ccffbfab5/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f73/11336590/00fc984768d5/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f73/11336590/613f9833b0bc/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f73/11336590/41ec18bc5203/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f73/11336590/09c85ae5198f/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f73/11336590/91e19e04539f/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f73/11336590/8d7e214ab1dc/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f73/11336590/1f4ccffbfab5/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f73/11336590/00fc984768d5/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f73/11336590/613f9833b0bc/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f73/11336590/41ec18bc5203/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f73/11336590/09c85ae5198f/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f73/11336590/91e19e04539f/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f73/11336590/8d7e214ab1dc/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f73/11336590/1f4ccffbfab5/gr7.jpg

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