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利用约束球反卷积技术在体解析人类舌肌纤维。

Crossing muscle fibers of the human tongue resolved in vivo using constrained spherical deconvolution.

机构信息

Department of Head and Neck Oncology and Surgery, Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, Netherlands.

Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.

出版信息

J Magn Reson Imaging. 2019 Jul;50(1):96-105. doi: 10.1002/jmri.26609. Epub 2019 Jan 16.

DOI:10.1002/jmri.26609
PMID:30648339
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6617996/
Abstract

BACKGROUND

Surgical resection of tongue cancer may impair swallowing and speech. Knowledge of tongue muscle architecture affected by the resection could aid in patient counseling. Diffusion tensor imaging (DTI) enables reconstructions of muscle architecture in vivo. Reconstructing crossing fibers in the tongue requires a higher-order diffusion model.

PURPOSE

To develop a clinically feasible diffusion imaging protocol, which facilitates both DTI and constrained spherical deconvolution (CSD) reconstructions of tongue muscle architecture in vivo.

STUDY TYPE

Cross-sectional study.

SUBJECTS/SPECIMEN: One ex vivo bovine tongue resected en bloc from mandible to hyoid bone. Ten healthy volunteers (mean age 25.5 years; range 21-34 years; four female).

FIELD STRENGTH/SEQUENCE: Diffusion-weighted echo planar imaging at 3 T using a high-angular resolution diffusion imaging scheme acquired twice with opposing phase-encoding for B -field inhomogeneity correction. The scan of the healthy volunteers was divided into four parts, in between which the volunteers were allowed to swallow, resulting in a total acquisition time of 10 minutes.

ASSESSMENT

The ability of resolving crossing muscle fibers using CSD was determined on the bovine tongue specimen. A reproducible response function was estimated and the optimal peak threshold was determined for the in vivo tongue. The quality of tractography of the in vivo tongue was graded by three experts.

STATISTICAL TESTS

The within-subject coefficient of variance was calculated for the response function. The qualitative results of the grading of DTI and CSD tractography were analyzed using a multilevel proportional odds model.

RESULTS

Fiber orientation distributions in the bovine tongue specimen showed that CSD was able to resolve crossing muscle fibers. The response function could be determined reproducibly in vivo. CSD tractography displayed significantly improved tractography compared with DTI tractography (P = 0.015).

DATA CONCLUSION

The 10-minute diffusion imaging protocol facilitates CSD fiber tracking with improved reconstructions of crossing tongue muscle fibers compared with DTI.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:96-105.

摘要

背景

舌癌的手术切除可能会影响吞咽和言语功能。了解切除术后舌肌结构的变化有助于为患者提供咨询。弥散张量成像(DTI)可用于活体肌肉结构的重建。重建舌内交叉纤维需要更高阶的弥散模型。

目的

开发一种临床可行的弥散成像方案,以促进活体舌肌结构的 DTI 和约束球内分解(CSD)重建。

研究类型

横断面研究。

受试者/标本:从下颌骨到舌骨整块切除的 1 个离体牛舌。10 名健康志愿者(平均年龄 25.5 岁;范围 21-34 岁;4 名女性)。

磁场强度/序列:在 3T 下使用高角度分辨率弥散成像方案进行弥散加权回波平面成像,两次采集时采用相反的相位编码以校正 B 场不均匀性。健康志愿者的扫描分为 4 部分,在每部分之间允许志愿者吞咽,总采集时间为 10 分钟。

评估

在牛舌标本上确定使用 CSD 解析交叉肌纤维的能力。估计了可重复的响应函数,并确定了活体舌的最佳峰值阈值。三位专家对活体舌的追踪质量进行了分级。

统计学检验

计算响应函数的个体内方差系数。使用多级比例优势模型分析 DTI 和 CSD 轨迹分级的定性结果。

结果

牛舌标本的纤维方向分布表明 CSD 能够解析交叉肌纤维。活体中可重复地确定响应函数。CSD 追踪显示与 DTI 追踪相比,追踪质量有显著改善(P=0.015)。

数据结论

10 分钟弥散成像方案可促进 CSD 纤维追踪,与 DTI 相比,重建交叉舌肌纤维的效果更好。

证据水平

2 技术功效:1 级

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9261/6617996/b474f21b9378/JMRI-50-96-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9261/6617996/564e9521913a/JMRI-50-96-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9261/6617996/2a9e98f5b8ab/JMRI-50-96-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9261/6617996/f52817c6e1bd/JMRI-50-96-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9261/6617996/9a22cef82dde/JMRI-50-96-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9261/6617996/7a25a8b678f0/JMRI-50-96-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9261/6617996/d1f8edc8e605/JMRI-50-96-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9261/6617996/ef16436342a1/JMRI-50-96-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9261/6617996/b474f21b9378/JMRI-50-96-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9261/6617996/564e9521913a/JMRI-50-96-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9261/6617996/2a9e98f5b8ab/JMRI-50-96-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9261/6617996/f52817c6e1bd/JMRI-50-96-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9261/6617996/9a22cef82dde/JMRI-50-96-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9261/6617996/7a25a8b678f0/JMRI-50-96-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9261/6617996/d1f8edc8e605/JMRI-50-96-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9261/6617996/ef16436342a1/JMRI-50-96-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9261/6617996/b474f21b9378/JMRI-50-96-g008.jpg

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