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胶质瘤分级和 IDH 状态解码的诊断性能比较:3D 酰胺质子转移 APT 与四种扩散加权 MRI 模型的比较。

Diagnostic performance of gliomas grading and IDH status decoding A comparison between 3D amide proton transfer APT and four diffusion-weighted MRI models.

机构信息

Department of Radiology, The Second Xiangya Hospital, Central South University, No. 139 Middle Renmin Road, Changsha, Hunan, 410011, China.

Department of Radiology Quality Control Center, Hunan Province, Changsha, 410011, China.

出版信息

J Magn Reson Imaging. 2022 Dec;56(6):1834-1844. doi: 10.1002/jmri.28211. Epub 2022 Apr 30.

DOI:10.1002/jmri.28211
PMID:35488516
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9790544/
Abstract

BACKGROUND

The focus of neuro-oncology research has changed from histopathologic grading to molecular characteristics, and medical imaging routinely follows this change.

PURPOSE

To compare the diagnostic performance of amide proton transfer (APT) and four diffusion models in gliomas grading and isocitrate dehydrogenase (IDH) genotype.

STUDY TYPE

Prospective.

POPULATION

A total of 62 participants (37 males, 25 females; mean age, 52 ± 13 years) whose IDH genotypes were mutant in 6 of 14 grade II gliomas, 8 of 20 of grade III gliomas, and 4 of 28 grade IV gliomas.

FIELD STRENGTH/SEQUENCE: APT imaging using sampling perfection with application optimized contrasts by using different flip angle evolutions (SPACE) and DWI with q-space Cartesian grid sampling were acquired at 3 T.

ASSESSMENT

The ability of diffusion kurtosis imaging, diffusion kurtosis imaging, neurite orientation dispersion and density imaging (NODDI), mean apparent propagator (MAP), and APT imaging for glioma grade and IDH status were assessed, with histopathological grade and genetic testing used as a reference standard. Regions of interest (ROIs) were drawn by two neuroradiologists after consensus.

STATISTICAL TESTS

T-test and Mann-Whitney U test; one-way analysis of variance (ANOVA); receiver operating curve (ROC) and area under the curve (AUC); DeLong test. P value < 0.05 was considered statistically significant.

RESULTS

Compared with IDH-mutant gliomas, IDH-wildtype gliomas showed a significantly higher mean, 5th-percentile (APT ), and 95th-percentile from APTw, the 95th-percentile value of axial, mean, and radial diffusivity from DKI, and 95th-percentile value of isotropic volume fraction from NODDI, and no significantly different parameters from DTI and MAP (P = 0.075-0.998). The combined APT model showed a significantly wider area under the curve (AUC 0.870) for IDH status, when compared with DKI and NODDI. APT was significantly different between two of the three groups (glioma II vs. glioma III vs. glioma IV: 1.35 ± 0.75 vs. 2.09 ± 0.93 vs. 2.71 ± 0.81).

DATA CONCLUSION

APT has higher diagnostic accuracy than DTI, DKI, MAP, and NODDI in glioma IDH genotype. APT can effectively identify both tumor grading and IDH genotyping, making it a promising biomarker for glioma classification.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 2.

摘要

背景

神经肿瘤学的研究重点已从组织病理学分级转变为分子特征,医学影像学也随之发生了变化。

目的

比较酰胺质子转移(APT)和四种扩散模型在胶质瘤分级和异柠檬酸脱氢酶(IDH)基因型中的诊断性能。

研究类型

前瞻性。

人群

共 62 名参与者(37 名男性,25 名女性;平均年龄 52±13 岁),其中 6 例 14 级 II 级胶质瘤、8 例 20 级 III 级胶质瘤和 4 例 28 级 IV 级胶质瘤的 IDH 基因型为突变型。

磁场强度/序列:在 3T 上采集采用不同翻转角演化的采样完美应用优化对比(SPACE)的 APT 成像和 q-空间笛卡尔网格采样的 DWI。

评估

评估扩散峰度成像、扩散峰度成像、神经丝取向弥散和密度成像(NODDI)、平均表观扩散系数(MAP)和 APT 成像对胶质瘤分级和 IDH 状态的能力,以组织病理学分级和基因检测作为参考标准。由两名神经放射科医生在达成共识后在感兴趣区域(ROI)进行绘制。

统计学检验

t 检验和曼-惠特尼 U 检验;单因素方差分析(ANOVA);受试者工作特征曲线(ROC)和曲线下面积(AUC);DeLong 检验。P 值<0.05 被认为具有统计学意义。

结果

与 IDH 突变型胶质瘤相比,IDH 野生型胶质瘤的 APTw 的平均、第 5 百分位数(APT)和第 95 百分位数、DKI 的轴向、平均和径向扩散系数的第 95 百分位数和 NODDI 的各向同性体积分数的第 95 百分位数明显更高,而 DTI 和 MAP 的参数没有明显差异(P=0.075-0.998)。与 DKI 和 NODDI 相比,联合 APT 模型对 IDH 状态的 AUC (0.870)具有显著更宽的范围。APT 在三组中的两组之间有显著差异(胶质瘤 II 与胶质瘤 III 与胶质瘤 IV:1.35±0.75 与 2.09±0.93 与 2.71±0.81)。

数据结论

APT 在胶质瘤 IDH 基因型方面比 DTI、DKI、MAP 和 NODDI 具有更高的诊断准确性。APT 可以有效识别肿瘤分级和 IDH 基因分型,是一种很有前途的胶质瘤分类生物标志物。

证据水平

1 技术功效:2 级。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5717/9790544/840d6a4ecb74/JMRI-56-1834-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5717/9790544/4941d2746aeb/JMRI-56-1834-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5717/9790544/de010ea53fb5/JMRI-56-1834-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5717/9790544/94c4f9fd7198/JMRI-56-1834-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5717/9790544/a854443677ad/JMRI-56-1834-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5717/9790544/840d6a4ecb74/JMRI-56-1834-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5717/9790544/4941d2746aeb/JMRI-56-1834-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5717/9790544/de010ea53fb5/JMRI-56-1834-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5717/9790544/94c4f9fd7198/JMRI-56-1834-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5717/9790544/a854443677ad/JMRI-56-1834-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5717/9790544/840d6a4ecb74/JMRI-56-1834-g002.jpg

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