|Table of Contents|

Research progress of radiomics in the diagnosis of brain metastases in lung cancer

Journal Of Modern Oncology[ISSN:1672-4992/CN:61-1415/R]

Issue:
2024 02
Page:
383-386
Research Field:
Publishing date:

Info

Title:
Research progress of radiomics in the diagnosis of brain metastases in lung cancer
Author(s):
LIN ZeZUO Minjing
Department of Radiology,the Second Affiliated Hospital of Nanchang University,Jiangxi Nanchang 330006,China.
Keywords:
radiomicslung cancerbrain metastasesdiagnosis
PACS:
R734.2
DOI:
10.3969/j.issn.1672-4992.2024.02.034
Abstract:
The incidence and mortality rate of primary lung cancer are at the forefront of malignant tumors,and brain metastasis is one of the common metastatic sites of advanced lung cancer with rapid progress and poor prognosis.As a noninvasive method,radiomics can obtain quantitative information from medical images,combine imaging characteristics with clinical,pathological,genomic and other information,and provide quantitative and objective support for decision-making on cancer diagnosis,treatment and prognosis.This paper reviews the application of radiomics in the diagnosis of lung cancer brain metastases,and provides a new idea for the early diagnosis of lung cancer brain metastases and the identification of primary lesion information of brain metastases.

References:

[1] SUNG H,FERLAY J,SIEGEL RL,et al.Global cancer statistics 2020:GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J].CA Cancer J Clin,2021,71(3):209-249.
[2] CAGNEY DN,MARTIN AM,CATALANO PJ,et al.Incidence and prognosis of patients with brain metastases at diagnosis of systemic malignancy:a population-based study[J].Neuro Oncol,2017,19(11):1511-1521.
[3] MAYERHOEFER ME,MATERKA A,LANGS G,et al.Introduction to radiomics[J].J Nucl Med,2020,61(4):488-495.
[4] GILLIES RJ,KINAHAN PE,HRICAK H.Radiomics:Images are more than pictures,they are data[J].Radiology,2016,278(2):563-577.
[5] PETERS S,BEXELIUS C,MUNK V,et al.The impact of brain metastasis on quality of life,resource utilization and survival in patients with non-small-cell lung cancer[J].Cancer Treat Rev,2016,45:139-162.
[6] 孙爽,门玉,惠周光.非小细胞肺癌脑转移高危因素研究进展[J].中国肺癌杂志,2022,25(03):193-200. SUN S,MEN Y,HUI ZG.Research progress on risk factors of brain metastasis in non-small cell lung cancer[J]. Chinese Journal of Lung Cancer,2022,25(03):193-200.
[7] CHEN A,LU L,PU X,et al.CT-based radiomics model for predicting brain metastasis in category T1 lung adenocarcinoma[J].AJR Am J Roentgenol,2019,213(1):134-139.
[8] DING Z,WANG Y,XIA C,et al.Thoracic CT radiomics analysis for predicting synchronous brain metastasis in patients with lung cancer[J].Diagn Interv Radiol,2022,28(1):39-49.
[9] XU X,HUANG L,CHEN J,et al.Application of radiomics signature captured from pretreatment thoracic CT to predict brain metastases in stage III/IV ALK-positive non-small cell lung cancer patients[J].J Thorac Dis,2019,11(11):4516-4528.
[10] TAKEI H,ROUAH E,ISHIDA Y.Brain metastasis:clinical characteristics,pathological findings and molecular subtyping for therapeutic implications[J].Brain Tumor Pathol,2016,33(1):1-12.
[11] POLYZOIDIS KS,MILIARAS G,PAVLIDIS N.Brain metastasis of unknown primary:a diagnostic and therapeutic dilemma[J].Cancer Treat Rev,2005,31(4):247-255.
[12] ORTIZ-RAMN R,LARROZA A,RUIZ-ESPAA S,et al.Classifying brain metastases by their primary site of origin using a radiomics approach based on texture analysis:a feasibility study[J].Eur Radiol,2018,28(11):4514-4523.
[13] BRESOV M,LARROZA A,ARANA E,et al.2D and 3D texture analysis to differentiate brain metastases on MR images:proceed with caution[J].MAGMA,2018,31(2):285-294.
[14] KNIEP HC,MADESTA F,SCHNEIDER T,et al.Radiomics of brain MRI:Utility in prediction of metastatic tumor type[J].Radiology,2019,290(2):479-487.
[15] REZAEI MK,NOLAN NJ,SCHWARTZ AM.Surgical pathology of lung cancer[J].Semin Respir Crit Care Med,2013,34(6):770-786.
[16] LI Z,MAO Y,LI H,et al.Differentiating brain metastases from different pathological types of lung cancers using texture analysis of T1 postcontrast MR[J].Magn Reson Med,2016,76(5):1410-1419.
[17] ZHANG J,JIN J,AI Y,et al.Differentiating the pathological subtypes of primary lung cancer for patients with brain metastases based on radiomics features from brain CT images[J].Eur Radiol,2021,31(2):1022-1028.
[18] 樊朝昕,傅潇,姚煜.EGFR突变晚期非小细胞肺癌免疫治疗的研究进展[J].现代肿瘤医学,2022,30(11):2069-2073. FAN CX,FU X,YAO Y.Research progress of immunotherapy for advanced NSCLC with EGFR mutation[J].Modern Oncology,2022,30(11):2069-2073.
[19] 许广辉,丁成智,王国磊,等.EGFR突变检测对非小细胞肺癌患者术后复发转移部位的预测价值[J].现代肿瘤医学,2020,28(13):2238-2241. XU GH,DING CZ,WANG GL,et al.EGFR mutations predict site-specific recurrence and metastasis following non-small-cell lung cancer surgery[J].Modern Oncology,2020,28(13):2238-2241.
[20] IUCHI T,SHINGYOJI M,ITAKURA M,et al.Frequency of brain metastases in non-small-cell lung cancer,and their association with epidermal growth factor receptor mutations[J].Int J Clin Oncol,2015,20(4):674-679.
[21] ZHANG Q,ZHANG X,YAN H,et al.Effects of epidermal growth factor receptor-tyrosine kinase inhibitors alone on EGFR-mutant non-small cell lung cancer with brain metastasis[J].Thorac Cancer,2016,7(6):648-654.
[22] GE M,ZHUANG Y,ZHOU X,et al.High probability and frequency of EGFR mutations in non-small cell lung cancer with brain metastases[J].J Neurooncol,2017,135(2):413-418.
[23] CASTELLANOS E,FELD E,HORN L.Driven by mutations:the predictive value of mutation subtype in EGFR-mutated non-small cell lung cancer[J].J Thorac Oncol,2017,12(4):612-623.
[24] TU W,SUN G,FAN L,et al.Radiomics signature:A potential and incremental predictor for EGFR mutation status in NSCLC patients,comparison with CT morphology[J].Lung Cancer,2019,132:28-35.
[25] ZHANG T,XU Z,LIU G,et al.Simultaneous identification of EGFR,KRAS,ERBB2,and TP53 mutations in patients with non-small cell lung cancer by machine learning-derived three-dimensional radiomics[J].Cancers (Basel),2021,13(8):1814.
[26] LE NQK,KHA QH,NGUYEN VH,et al.Machine learning-based radiomics signatures for EGFR and KRAS mutations prediction in non-small-cell lung cancer[J].Int J Mol Sci,2021,22(17):9254.
[27] ZHAO W,WU Y,XU Y,et al.The potential of radiomics nomogram in non-invasively prediction of epidermal growth factor receptor mutation status and subtypes in lung adenocarcinoma[J].Front Oncol,2019,9:1485.
[28] AHN SJ,KWON H,YANG JJ,et al.Contrast-enhanced T1-weighted image radiomics of brain metastases may predict EGFR mutation status in primary lung cancer[J].Sci Rep,2020,10(1):8905.
[29] JUNG WS,PARK CH,HONG CK,et al.Diffusion-weighted imaging of brain metastasis from lung cancer:correlation of MRI parameters with the histologic type and gene mutation status[J].AJNR Am J Neuroradiol,2018,39(2):273-279.
[30] WANG G,WANG B,WANG Z,et al.Radiomics signature of brain metastasis:prediction of EGFR mutation status[J].Eur Radiol,2021,31(7):4538-4547.
[31] LEE CC,SOON YY,TAN CL,et al.Discordance of epidermal growth factor receptor mutation between primary lung tumor and paired distant metastases in non-small cell lung cancer:A systematic review and meta-analysis[J].PLoS One,2019,14(6):e218414.

Memo

Memo:
江西省教育厅科技计划重点项目(编号:GJJ200106);江西省科技厅应用研究培育计划(编号:20212BAG70048)
Last Update: 1900-01-01