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从体模到患者:在正电子发射断层扫描/磁共振成像中改进扩散加权成像与氟代脱氧葡萄糖正电子发射断层扫描的融合及体素级分析以用于联合代谢-扩散率指数(cDMI)

From Phantoms to Patients: Improved Fusion and Voxel-Wise Analysis of Diffusion-Weighted Imaging and FDG-Positron Emission Tomography in Positron Emission Tomography/Magnetic Resonance Imaging for Combined Metabolic-Diffusivity Index (cDMI).

作者信息

Deininger Katharina, Korf Patrick, Lauber Leonard, Grimm Robert, Strecker Ralph, Steinacker Jochen, Lisson Catharina S, Mühling Bernd M, Schmidtke-Schrezenmeier Gerlinde, Rasche Volker, Speidel Tobias, Glatting Gerhard, Beer Meinrad, Beer Ambros J, Thaiss Wolfgang

机构信息

Department of Nuclear Medicine, University Hospital Ulm, 89081 Ulm, Germany.

Siemens Healthineers AG, 91052 Erlangen, Germany.

出版信息

Diagnostics (Basel). 2024 Aug 16;14(16):1787. doi: 10.3390/diagnostics14161787.

DOI:10.3390/diagnostics14161787
PMID:39202275
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11353375/
Abstract

Hybrid positron emission tomography/magnetic resonance imaging (PET/MR) opens new possibilities in multimodal multiparametric (m2p) image analyses. But even the simultaneous acquisition of positron emission tomography (PET) and magnetic resonance imaging (MRI) does not guarantee perfect voxel-by-voxel co-registration due to organs and distortions, especially in diffusion-weighted imaging (DWI), which would be, however, crucial to derive biologically meaningful information. Thus, our aim was to optimize fusion and voxel-wise analyses of DWI and standardized uptake values (SUVs) using a novel software for m2p analyses. Using research software, we evaluated the precision of image co-registration and voxel-wise analyses including the rigid and elastic 3D registration of DWI and [18F]-Fluorodeoxyglucose (FDG)-PET from an integrated PET/MR system. We analyzed DWI distortions with a volume-preserving constraint in three different 3D-printed phantom models. A total of 12 PET/MR-DWI clinical datasets (bronchial carcinoma patients) were referenced to the T1 weighted-DIXON sequence. Back mapping of scatterplots and voxel-wise registration was performed and compared to the non-optimized datasets. Fusion was rated using a 5-point Likert scale. Using the 3D-elastic co-registration algorithm, geometric shapes were restored in phantom measurements; the measured ADC values did not change significantly (F = 1.12, = 0.34). Reader assessment showed a significant improvement in fusion precision for DWI and morphological landmarks in the 3D-registered datasets (4.3 ± 0.2 vs. 4.6 ± 0.2, = 0.009). Most pronounced differences were noted for the chest wall ( = 0.006), tumor ( = 0.007), and skin contour ( = 0.014). Co-registration increased the number of plausible ADC and SUV combinations by 25%. The volume-preserving elastic 3D registration of DWI significantly improved the precision of fusion with anatomical sequences in phantom and clinical datasets. The research software allowed for a voxel-wise analysis and visualization of [18F]FDG-PET/MR data as a "combined diffusivity-metabolic index" (cDMI). The clinical value of the optimized PET/MR biomarker can thus be tested in future PET/MR studies.

摘要

混合正电子发射断层扫描/磁共振成像(PET/MR)为多模态多参数(m2p)图像分析带来了新的可能性。但由于器官和畸变的存在,即使同时采集正电子发射断层扫描(PET)和磁共振成像(MRI),也无法保证逐体素的完美配准,尤其是在扩散加权成像(DWI)中,然而,这对于获取具有生物学意义的信息至关重要。因此,我们的目标是使用一种用于m2p分析的新型软件,优化DWI和标准化摄取值(SUV)的融合及逐体素分析。使用研究软件,我们评估了图像配准和逐体素分析的精度,包括来自集成PET/MR系统的DWI和[18F] - 氟脱氧葡萄糖(FDG)-PET的刚性和弹性三维配准。我们在三种不同的3D打印体模模型中,采用体积保持约束分析了DWI畸变。总共12个PET/MR-DWI临床数据集(支气管癌患者)以T1加权DIXON序列为参考。进行了散点图的反向映射和逐体素配准,并与未优化的数据集进行比较。使用5点李克特量表对融合进行评分。使用三维弹性配准算法,在体模测量中恢复了几何形状;测量的表观扩散系数(ADC)值没有显著变化(F = 1.12,P = 0.34)。读者评估显示,在三维配准数据集中,DWI和形态学标志的融合精度有显著提高(4.3±0.2对4.6±0.2,P = 0.009)。在胸壁(P = 0.006)、肿瘤(P = 0.007)和皮肤轮廓(P = 0.014)方面观察到最明显的差异。配准使合理的ADC和SUV组合数量增加了25%。DWI的体积保持弹性三维配准显著提高了体模和临床数据集中与解剖序列融合的精度。该研究软件允许对[18F]FDG-PET/MR数据进行逐体素分析和可视化,作为“联合扩散率-代谢指数”(cDMI)。因此,优化后的PET/MR生物标志物的临床价值可在未来的PET/MR研究中进行测试。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c7f/11353375/e63e0d800a64/diagnostics-14-01787-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c7f/11353375/a4ff44c8d63b/diagnostics-14-01787-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c7f/11353375/0704504c759a/diagnostics-14-01787-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c7f/11353375/747f36276d10/diagnostics-14-01787-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c7f/11353375/4020b4add0ba/diagnostics-14-01787-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c7f/11353375/32a6e3eb7cc9/diagnostics-14-01787-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c7f/11353375/e63e0d800a64/diagnostics-14-01787-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c7f/11353375/a4ff44c8d63b/diagnostics-14-01787-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c7f/11353375/0704504c759a/diagnostics-14-01787-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c7f/11353375/747f36276d10/diagnostics-14-01787-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c7f/11353375/4020b4add0ba/diagnostics-14-01787-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c7f/11353375/32a6e3eb7cc9/diagnostics-14-01787-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c7f/11353375/e63e0d800a64/diagnostics-14-01787-g006.jpg

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