深度学习在弥散性中线脑胶质瘤 H3 K27M 突变状态的磁共振成像无创评估中的应用。

Deep Learning for Noninvasive Assessment of H3 K27M Mutation Status in Diffuse Midline Gliomas Using MR Imaging.

机构信息

Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, People's Republic of China.

Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, People's Republic of China.

出版信息

J Magn Reson Imaging. 2023 Sep;58(3):850-861. doi: 10.1002/jmri.28606. Epub 2023 Jan 24.

DOI:10.1002/jmri.28606

PMID:36692205

Abstract

BACKGROUND

Determination of H3 K27M mutation in diffuse midline glioma (DMG) is key for prognostic assessment and stratifying patient subgroups for clinical trials. MRI can noninvasively depict morphological and metabolic characteristics of H3 K27M mutant DMG.

PURPOSE

This study aimed to develop a deep learning (DL) approach to noninvasively predict H3 K27M mutation in DMG using T2-weighted images.

STUDY TYPE

Retrospective and prospective.

POPULATION

For diffuse midline brain gliomas, 341 patients from Center-1 (27 ± 19 years, 184 males), 42 patients from Center-2 (33 ± 19 years, 27 males) and 35 patients (37 ± 18 years, 24 males). For diffuse spinal cord gliomas, 133 patients from Center-1 (30 ± 15 years, 80 males).

FIELD STRENGTH/SEQUENCE: 5T and 3T, T2-weighted turbo spin echo imaging.

ASSESSMENT

Conventional radiological features were independently reviewed by two neuroradiologists. H3 K27M status was determined by histopathological examination. The Dice coefficient was used to evaluate segmentation performance. Classification performance was evaluated using accuracy, sensitivity, specificity, and area under the curve.

STATISTICAL TESTS

Pearson's Chi-squared test, Fisher's exact test, two-sample Student's t-test and Mann-Whitney U test. A two-sided P value <0.05 was considered statistically significant.

RESULTS

In the testing cohort, Dice coefficients of tumor segmentation using DL were 0.87 for diffuse midline brain and 0.81 for spinal cord gliomas. In the internal prospective testing dataset, the predictive accuracies, sensitivities, and specificities of H3 K27M mutation status were 92.1%, 98.2%, 82.9% in diffuse midline brain gliomas and 85.4%, 88.9%, 82.6% in spinal cord gliomas. Furthermore, this study showed that the performance generalizes to external institutions, with predictive accuracies of 85.7%-90.5%, sensitivities of 90.9%-96.0%, and specificities of 82.4%-83.3%.

DATA CONCLUSION

In this study, an automatic DL framework was developed and validated for accurately predicting H3 K27M mutation using T2-weighted images, which could contribute to the noninvasive determination of H3 K27M status for clinical decision-making.

EVIDENCE LEVEL

2 Technical Efficacy: Stage 2.

摘要

背景

弥漫性中线脑胶质瘤（DMG）中 H3 K27M 突变的确定是进行预后评估和为临床试验分层患者亚组的关键。磁共振成像（MRI）可以非侵入性地描绘 H3 K27M 突变 DMG 的形态和代谢特征。

目的

本研究旨在开发一种深度学习（DL）方法，通过 T2 加权图像无创预测 DMG 中的 H3 K27M 突变。

研究类型

回顾性和前瞻性。

人群

对于弥漫性中线脑胶质瘤，来自中心 1 的 341 名患者（27±19 岁，184 名男性），来自中心 2 的 42 名患者（33±19 岁，27 名男性）和来自中心 1 的 35 名患者（37±18 岁，24 名男性）。对于弥漫性脊髓胶质瘤，来自中心 1 的 133 名患者（30±15 岁，80 名男性）。

场强/序列：5T 和 3T，T2 加权涡轮自旋回波成像。

评估

两名神经放射科医生独立评估常规放射学特征。通过组织病理学检查确定 H3 K27M 状态。使用 Dice 系数评估分割性能。使用准确性、灵敏度、特异性和曲线下面积评估分类性能。

统计检验

Pearson 卡方检验、Fisher 确切检验、两样本学生 t 检验和 Mann-Whitney U 检验。双侧 P 值<0.05 被认为具有统计学意义。

结果

在测试队列中，使用 DL 进行肿瘤分割的 Dice 系数为弥漫性中线脑胶质瘤 0.87，脊髓胶质瘤 0.81。在内部前瞻性测试数据集，H3 K27M 突变状态的预测准确性、灵敏度和特异性在弥漫性中线脑胶质瘤中分别为 92.1%、98.2%、82.9%，在脊髓胶质瘤中分别为 85.4%、88.9%、82.6%。此外，本研究表明该方法的性能可推广到外部机构，预测准确率为 85.7%-90.5%，灵敏度为 90.9%-96.0%，特异性为 82.4%-83.3%。