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A nomogram strategy for identifying the subclassification of IDH mutation and ATRX expression loss in lower-grade gliomas

  • Imaging Informatics and Artificial Intelligence
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

To construct a radiomics nomogram based on multiparametric MRI data for predicting isocitrate dehydrogenase 1 mutation (IDH +) and loss of nuclear alpha thalassemia/mental retardation syndrome X‐linked expression (ATRX −) in patients with lower‐grade gliomas (LrGG; World Health Organization [WHO] 2016 grades II and III).

Methods

A total of 111 LrGG patients (76 mutated IDH and 35 wild-type IDH) were enrolled, divided into a training set (n = 78) and a validation set (n = 33) for predicting IDH mutation. IDH + LrGG patients were further stratified into the ATRX − (n = 38) and ATRX + (n = 38) subtypes. A total of 250 radiomics features were extracted from the region of interest of each tumor, including that from T2 fluid-attenuated inversion recovery (T2 FLAIR), contrast-enhanced T1 WI, ASL-derived cerebral blood flow (CBF), DWI-derived ADC, and exponential ADC (eADC). A radiomics signature was selected using the Elastic Net regression model, and a radiomics nomogram was finally constructed using the age, gender information, and above features.

Results

The radiomics nomogram identified LrGG patients for IDH mutation (C-index: training sets = 0.881, validation sets = 0.900) and ATRX loss (C-index: training sets = 0.863, validation sets = 0.840) with good calibration. Decision curve analysis further confirmed the clinical usefulness of the two nomograms for predicting IDH and ATRX status.

Conclusions

The nomogram incorporating age, gender, and the radiomics signature provided a clinically useful approach in noninvasively predicting IDH and ATRX mutation status for LrGG patients. The proposed method could facilitate MRI-based clinical decision-making for the LrGG patients.

Key Points

• Non-invasive determination of IDH and ATRX gene status of LrGG patients can be obtained with a radiomics nomogram.

• The proposed nomogram is constructed by radiomics signature selected from 250 radiomics features, combined with age and gender.

• The proposed radiomics nomogram exhibited good calibration and discrimination for IDH and ATRX gene mutation stratification of LrGG patients in both training and validation sets.

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Abbreviations

ATRX:

Alpha thalassemia/mental retardation syndrome X-linked

CBF:

Cerebral blood flow

DCA:

Decision curve analysis

FLAIR:

Fluid-attenuated inversion recovery

GLCM:

Gray-level co-occurrence matrix

GLRLM:

Gray-level run-length matrix

GLSZM:

Gray-level size zone matrix

IDH:

Isocitrate dehydrogenase

LrGG:

Lower-grade gliomas

NGDTM:

Neighborhood gray-tone difference matrix

T1 C:

Contrast-enhanced T1-weighted imaging

T E :

Echo time

T R :

Repetition time

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Acknowledgements

This study is supported by Shanghai Science and Technology Commission (No. 18411967300).

Funding

This study has received funding from Shanghai Science and Technology Commission (No. 18411967300).

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Author notes

  1. Shiman Wu and Xi Zhang contributed equally to this work

Authors and Affiliations

  1. Department of Radiology, Huashan Hospital, Fudan University, Jing’an District, 12 Middle Urumqi Road, Shanghai, 200040, People’s Republic of China

    Shiman Wu, Wenting Rui, Yaru Sheng, Yang Yu, Zhenwei Yao & Yan Ren

  2. Department of Biomedical Engineering, Fourth Military Medical University, Xi’an, Shaanxi, People’s Republic of China

    Xi Zhang

  3. GE Healthcare, Shanghai, People’s Republic of China

    Yong Zhang

  4. Department of Neurosurgery, Huashan Hospital, Fudan University, Jing’an District, 12 Middle Urumqi Road, Shanghai, 200040, People’s Republic of China

    Tianming Qiu

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Correspondence to Tianming Qiu or Yan Ren.

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The scientific guarantor of this publication is Yan Ren.

Conflict of Interest

One of the authors (Yong Zhang) is an employee of GE Healthcare. The remaining authors declare no relationships with any companies whose products or services may be related to the subject matter of the article.

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No complex statistical methods were necessary for this paper.

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Study subjects or cohorts overlap

Fifty-seven study subjects have been previously reported in Journal of Magnetic Resonance Imaging (2019, 49(3):808–817).

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• retrospective.

• diagnostic or prognostic study.

• performed at one institution.

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Wu, S., Zhang, X., Rui, W. et al. A nomogram strategy for identifying the subclassification of IDH mutation and ATRX expression loss in lower-grade gliomas. Eur Radiol 32, 3187–3198 (2022). https://doi.org/10.1007/s00330-021-08444-1

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