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The application of radiomics in predicting gene mutations in cancer

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

Abstract

With the development of genome sequencing, the role of molecular targeted therapy in cancer is becoming increasingly important. However, genetic testing remains expensive, invasive, and time-consuming, and thus unavailable for all patients. Radiogenomics aims to correlate imaging characteristics with gene expression patterns, gene mutations, and other genome-related characteristics. Due to the noninvasive nature of medical imaging, the field of radiogenomics is rapidly developing and may serve as a substitute tool for genetic testing. In this article, we briefly summarise the current role of radiogenomics in predicting gene mutations in brain, lung, colorectal, breast, and kidney tumours.

Key Points

• The role of molecular targeted therapy in individual cancer-precision therapy is becoming increasingly important with the development of genetic testing.

• Radiogenomics may provide accurate imaging biomarkers as a substitute for genetic testing.

• While the field of radiogenomics holds great promise, there are still a number of limitations that need to be overcome.

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Abbreviations

ALK:

Anaplastic lymphoma kinase

AUC:

Area under curve

BRCA:

Breast-cancer susceptibility gene

CRC:

Colorectal cancer

CT:

X-ray computed tomography

DFS:

Disease-free survival

EGFR:

Epidermal growth factor receptor

GBM:

Glioblastoma

IDH-1:

Isocitrate dehydrogenase-1

MRI:

Magnetic resonance imaging

NSCLC:

Non-small cell lung cancer

OS:

Overall survival

PET:

Positron emission tomography

RCC:

Renal clear cell carcinoma

ROC:

Receiver operating characteristic

ROS1:

ROS proto-oncogene 1

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Funding

This study has received funding by the National Natural Science Foundation of China (ID: 81670046).

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  1. Cancer Therapy and Research Center, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, 324 Jingwuweiqi Road, Jinan, 250021, Shandong, China

    Yana Qi, Tingting Zhao & Mingyong Han

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  1. Yana Qi
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  2. Tingting Zhao
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  3. Mingyong Han
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Correspondence to Mingyong Han.

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Qi, Y., Zhao, T. & Han, M. The application of radiomics in predicting gene mutations in cancer. Eur Radiol 32, 4014–4024 (2022). https://doi.org/10.1007/s00330-021-08520-6

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