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使用带有质子密度加权成像序列的无线探测器评估髁突骨质变化。

Evaluation of condylar osseous changes using a wireless detector with proton density-weighted imaging sequences.

作者信息

Ming Xing, Cheng Xinge, Tian Chong, Li Wuchao, Wang Rongpin, Qian Chunqi, Zeng Xianchun

机构信息

Department of Radiology, Guizhou Provincial People's Hospital, Key Laboratory of Intelligent Medical Imaging Analysis and Accurate Diagnosis of Guizhou Province, International Exemplary Cooperation Base of Precision Imaging for Diagnosis and Treatment, Guiyang, China.

Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI, USA.

出版信息

Quant Imaging Med Surg. 2023 Jan 1;13(1):17-26. doi: 10.21037/qims-22-424. Epub 2022 Oct 27.

DOI:10.21037/qims-22-424
PMID:36620157
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9816719/
Abstract

BACKGROUND

Cone-beam computed tomography (CBCT) is the gold standard for evaluating condylar osseous changes. However, the radiation risk and low soft-tissue resolution of CBCT make it unsuitable for evaluating soft tissue such as the articular disc and lateral pterygoid muscle. This study aimed to qualitatively and quantitatively evaluate the feasibility and advantages of using wireless detectors (WD) with proton density-weighted imaging (PDWI) sequences to image condyle changes in patients with temporomandibular disorders (TMD).

METHODS

This study involved 20 patients (male =8, female =12; mean age 31.65 years, SD 12.68 years) with TMD. All participants underwent a closed oblique sagittal PDWI scan with head/neck coupling coiling (HNCC) and wireless detector-HNCC (WD-HNCC) on a 3.0 T magnetic resonance imaging (MRI) scanner. Subsequently, the changes in the condyle bones in the scanned images for the 2 image types were scored subjectively and compared qualitatively. The contrast-to-noise ratio (CNR) of the 2 types of scanned images was compared quantitatively. The comparison of CNR differences between the 2 types of images was performed using the paired -test. The kappa statistic was used to test the consistency of quantitative analyses of MRI images between observers. The subjective scores of condylar osseous changes in the 2 types of images were compared by paired rank-sum test. A P value <0.05 was considered statistically significant.

RESULTS

A total of 40 condyles from 20 patients were scanned. Among them, 8 condyles showed no bone changes, and the other 32 condyles demonstrated condylar osseous changes of varying degrees and nature. These 32 condyles were used in the subsequent analysis. As compared to images acquired by HNCC in the PDWI sequence, the WD-HNCC images more clearly showed mandibular osteophyte, bone cortical erosion, subcortical cystic focus, and bone cortical hyperplasia and thickening. In addition, the WD-HNCC was demonstrated to improve image CNR by 158.9% compared to HNCC (28.17±16.01 10.88±6.53; t=8.63; P=0.001).

CONCLUSIONS

WD-HNCC in PDWI sequences is suitable for imaging the condylar bone changes of patients with TMD and significantly improves the image quality.

摘要

背景

锥形束计算机断层扫描(CBCT)是评估髁突骨质变化的金标准。然而,CBCT的辐射风险和低软组织分辨率使其不适用于评估诸如关节盘和翼外肌等软组织。本研究旨在定性和定量评估使用无线探测器(WD)与质子密度加权成像(PDWI)序列对颞下颌关节紊乱病(TMD)患者的髁突变化进行成像的可行性和优势。

方法

本研究纳入了20例TMD患者(男性8例,女性12例;平均年龄31.65岁,标准差12.68岁)。所有参与者在3.0T磁共振成像(MRI)扫描仪上接受了使用头/颈耦合线圈(HNCC)和无线探测器-HNCC(WD-HNCC)的闭口斜矢状面PDWI扫描。随后,对两种图像类型的扫描图像中髁突骨的变化进行主观评分并进行定性比较。对两种扫描图像的对比噪声比(CNR)进行定量比较。使用配对t检验对两种图像之间的CNR差异进行比较。kappa统计量用于检验观察者之间MRI图像定量分析的一致性。通过配对秩和检验比较两种图像中髁突骨质变化的主观评分。P值<0.05被认为具有统计学意义。

结果

共扫描了20例患者的40个髁突。其中,8个髁突未显示骨质变化,另外32个髁突表现出不同程度和性质的髁突骨质变化。这32个髁突用于后续分析。与PDWI序列中HNCC采集的图像相比,WD-HNCC图像更清晰地显示了下颌骨赘、骨皮质侵蚀、皮质下囊性病灶以及骨皮质增生和增厚。此外,与HNCC相比,WD-HNCC的图像CNR提高了158.9%(28.17±16.01对10.88±6.53;t=8.63;P=0.001)。

结论

PDWI序列中的WD-HNCC适用于对TMD患者的髁突骨变化进行成像,并显著提高图像质量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfd0/9816719/bfb9b06273db/qims-13-01-17-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfd0/9816719/c7c80d57cc47/qims-13-01-17-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfd0/9816719/6d2a8f031258/qims-13-01-17-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfd0/9816719/e842176d951c/qims-13-01-17-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfd0/9816719/7f40f9e5b9e0/qims-13-01-17-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfd0/9816719/3fa2f8a88ef7/qims-13-01-17-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfd0/9816719/bfb9b06273db/qims-13-01-17-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfd0/9816719/c7c80d57cc47/qims-13-01-17-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfd0/9816719/6d2a8f031258/qims-13-01-17-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfd0/9816719/e842176d951c/qims-13-01-17-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfd0/9816719/7f40f9e5b9e0/qims-13-01-17-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfd0/9816719/3fa2f8a88ef7/qims-13-01-17-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfd0/9816719/bfb9b06273db/qims-13-01-17-f6.jpg

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