Cargando…

Noninvasive molecular diagnosis of craniopharyngioma with MRI-based radiomics approach

BACKGROUND: Frequent somatic mutations of BRAF and CTNNB1 were identified in both histological subtypes of craniopharyngioma (adamantinomatous and papillary) which shed light on target therapy to cure this oncogenic disease. The aim of this study was to investigate the noninvasive MRI-based radiomic...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Xi, Tong, Yusheng, Shi, Zhifeng, Chen, Hong, Yang, Zhong, Wang, Yuanyuan, Chen, Liang, Yu, Jinhua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6322318/
https://www.ncbi.nlm.nih.gov/pubmed/30616515
http://dx.doi.org/10.1186/s12883-018-1216-z
_version_ 1783385598184128512
author Chen, Xi
Tong, Yusheng
Shi, Zhifeng
Chen, Hong
Yang, Zhong
Wang, Yuanyuan
Chen, Liang
Yu, Jinhua
author_facet Chen, Xi
Tong, Yusheng
Shi, Zhifeng
Chen, Hong
Yang, Zhong
Wang, Yuanyuan
Chen, Liang
Yu, Jinhua
author_sort Chen, Xi
collection PubMed
description BACKGROUND: Frequent somatic mutations of BRAF and CTNNB1 were identified in both histological subtypes of craniopharyngioma (adamantinomatous and papillary) which shed light on target therapy to cure this oncogenic disease. The aim of this study was to investigate the noninvasive MRI-based radiomics diagnosis to detect BRAF and CTNNB1 mutations in craniopharyngioma patients. METHODS: Forty-four patients pathologically diagnosed as adamantinomatous craniopharyngioma (ACP) or papillary craniopharyngioma (PCP) were retrospectively studied. High-throughput features were extracted from manually segmented tumors in MR images of each case. The modifications-robustness in region of interests and Random Forest-based feature selection methods were adopted to select the most significant features. Random forest classifier with 10-fold cross-validation was applied to build our radiomics model. RESULTS: Four features were selected to make pathological diagnosis between ACP and PCP with area under the receiver operating characteristic curve (AUC) of 0.89, accurancy (ACC) of 0.86, sensitivity (SENS) of 0.89 and specificity (SPEC) of 0.85. The other two features were applied to estimate BRAF V600E mutation with AUC of 0.91, ACC of 0.93, SENS of 0.83 and SPEC of 0.97. Accurate predication of CTNNB1 mutation by three selected features was realized with AUC of 0.93, ACC of 0.86, SENS of 0.86 and SPEC of 0.86. CONCLUSIONS: We developed a reliable MRI-based radiomics approach to perform pathological and molecular diagnosis in craniopharyngioma patients with considerably accurate prediction, which could offer potential guidance for clinical decision-making. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12883-018-1216-z) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-6322318
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-63223182019-01-10 Noninvasive molecular diagnosis of craniopharyngioma with MRI-based radiomics approach Chen, Xi Tong, Yusheng Shi, Zhifeng Chen, Hong Yang, Zhong Wang, Yuanyuan Chen, Liang Yu, Jinhua BMC Neurol Research Article BACKGROUND: Frequent somatic mutations of BRAF and CTNNB1 were identified in both histological subtypes of craniopharyngioma (adamantinomatous and papillary) which shed light on target therapy to cure this oncogenic disease. The aim of this study was to investigate the noninvasive MRI-based radiomics diagnosis to detect BRAF and CTNNB1 mutations in craniopharyngioma patients. METHODS: Forty-four patients pathologically diagnosed as adamantinomatous craniopharyngioma (ACP) or papillary craniopharyngioma (PCP) were retrospectively studied. High-throughput features were extracted from manually segmented tumors in MR images of each case. The modifications-robustness in region of interests and Random Forest-based feature selection methods were adopted to select the most significant features. Random forest classifier with 10-fold cross-validation was applied to build our radiomics model. RESULTS: Four features were selected to make pathological diagnosis between ACP and PCP with area under the receiver operating characteristic curve (AUC) of 0.89, accurancy (ACC) of 0.86, sensitivity (SENS) of 0.89 and specificity (SPEC) of 0.85. The other two features were applied to estimate BRAF V600E mutation with AUC of 0.91, ACC of 0.93, SENS of 0.83 and SPEC of 0.97. Accurate predication of CTNNB1 mutation by three selected features was realized with AUC of 0.93, ACC of 0.86, SENS of 0.86 and SPEC of 0.86. CONCLUSIONS: We developed a reliable MRI-based radiomics approach to perform pathological and molecular diagnosis in craniopharyngioma patients with considerably accurate prediction, which could offer potential guidance for clinical decision-making. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12883-018-1216-z) contains supplementary material, which is available to authorized users. BioMed Central 2019-01-07 /pmc/articles/PMC6322318/ /pubmed/30616515 http://dx.doi.org/10.1186/s12883-018-1216-z Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Chen, Xi
Tong, Yusheng
Shi, Zhifeng
Chen, Hong
Yang, Zhong
Wang, Yuanyuan
Chen, Liang
Yu, Jinhua
Noninvasive molecular diagnosis of craniopharyngioma with MRI-based radiomics approach
title Noninvasive molecular diagnosis of craniopharyngioma with MRI-based radiomics approach
title_full Noninvasive molecular diagnosis of craniopharyngioma with MRI-based radiomics approach
title_fullStr Noninvasive molecular diagnosis of craniopharyngioma with MRI-based radiomics approach
title_full_unstemmed Noninvasive molecular diagnosis of craniopharyngioma with MRI-based radiomics approach
title_short Noninvasive molecular diagnosis of craniopharyngioma with MRI-based radiomics approach
title_sort noninvasive molecular diagnosis of craniopharyngioma with mri-based radiomics approach
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6322318/
https://www.ncbi.nlm.nih.gov/pubmed/30616515
http://dx.doi.org/10.1186/s12883-018-1216-z
work_keys_str_mv AT chenxi noninvasivemoleculardiagnosisofcraniopharyngiomawithmribasedradiomicsapproach
AT tongyusheng noninvasivemoleculardiagnosisofcraniopharyngiomawithmribasedradiomicsapproach
AT shizhifeng noninvasivemoleculardiagnosisofcraniopharyngiomawithmribasedradiomicsapproach
AT chenhong noninvasivemoleculardiagnosisofcraniopharyngiomawithmribasedradiomicsapproach
AT yangzhong noninvasivemoleculardiagnosisofcraniopharyngiomawithmribasedradiomicsapproach
AT wangyuanyuan noninvasivemoleculardiagnosisofcraniopharyngiomawithmribasedradiomicsapproach
AT chenliang noninvasivemoleculardiagnosisofcraniopharyngiomawithmribasedradiomicsapproach
AT yujinhua noninvasivemoleculardiagnosisofcraniopharyngiomawithmribasedradiomicsapproach