Cargando…

Radiomic Analysis of Quantitative T2 Mapping and Conventional MRI in Predicting Histologic Grade of Bladder Cancer

We explored the added value of a radiomic strategy based on quantitative transverse relaxation (T2) mapping and conventional magnetic resonance imaging (MRI) to evaluate the histologic grade of bladder cancer (BCa) preoperatively. Patients who were suspected of BCa underwent pelvic MRI (including T2...

Descripción completa

Detalles Bibliográficos
Autores principales: Ye, Lei, Wang, Yayi, Xiang, Wanxin, Yao, Jin, Liu, Jiaming, Song, Bin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10531568/
https://www.ncbi.nlm.nih.gov/pubmed/37762841
http://dx.doi.org/10.3390/jcm12185900
_version_ 1785111749801803776
author Ye, Lei
Wang, Yayi
Xiang, Wanxin
Yao, Jin
Liu, Jiaming
Song, Bin
author_facet Ye, Lei
Wang, Yayi
Xiang, Wanxin
Yao, Jin
Liu, Jiaming
Song, Bin
author_sort Ye, Lei
collection PubMed
description We explored the added value of a radiomic strategy based on quantitative transverse relaxation (T2) mapping and conventional magnetic resonance imaging (MRI) to evaluate the histologic grade of bladder cancer (BCa) preoperatively. Patients who were suspected of BCa underwent pelvic MRI (including T2 mapping and diffusion-weighted imaging (DWI) before any treatment. All patients with histological-proved urothelial BCa were included. We constructed different prediction models using the mean signal values and radiomic features from both T2 mapping and apparent diffusion coefficient (ADC) maps. The diagnostic performance of each model or parameter was assessed using receiver operating characteristic curves. In total, 92 patients were finally included (training cohort, n = 64; testing cohort, n = 28); among these, 71 had high-grade BCa. In the testing cohort, the T2-mapping radiomic model achieved the highest prediction performance (area under the curve (AUC), 0.87; 95% confidence interval (CI), 0.73–1.0) compared with the ADC radiomic model (AUC, 0.77; 95%CI, 0.56–0.97), and the joint radiomic model of 0.78 (95%CI, 0.61–0.96). Our results demonstrated that radiomic mapping could provide more information than direct evaluation of T2 and ADC values in differentiating histological grades of BCa. Additionally, among the radiomic models, the T2-mapping radiomic model outperformed the ADC and joint radiomic models.
format Online
Article
Text
id pubmed-10531568
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-105315682023-09-28 Radiomic Analysis of Quantitative T2 Mapping and Conventional MRI in Predicting Histologic Grade of Bladder Cancer Ye, Lei Wang, Yayi Xiang, Wanxin Yao, Jin Liu, Jiaming Song, Bin J Clin Med Article We explored the added value of a radiomic strategy based on quantitative transverse relaxation (T2) mapping and conventional magnetic resonance imaging (MRI) to evaluate the histologic grade of bladder cancer (BCa) preoperatively. Patients who were suspected of BCa underwent pelvic MRI (including T2 mapping and diffusion-weighted imaging (DWI) before any treatment. All patients with histological-proved urothelial BCa were included. We constructed different prediction models using the mean signal values and radiomic features from both T2 mapping and apparent diffusion coefficient (ADC) maps. The diagnostic performance of each model or parameter was assessed using receiver operating characteristic curves. In total, 92 patients were finally included (training cohort, n = 64; testing cohort, n = 28); among these, 71 had high-grade BCa. In the testing cohort, the T2-mapping radiomic model achieved the highest prediction performance (area under the curve (AUC), 0.87; 95% confidence interval (CI), 0.73–1.0) compared with the ADC radiomic model (AUC, 0.77; 95%CI, 0.56–0.97), and the joint radiomic model of 0.78 (95%CI, 0.61–0.96). Our results demonstrated that radiomic mapping could provide more information than direct evaluation of T2 and ADC values in differentiating histological grades of BCa. Additionally, among the radiomic models, the T2-mapping radiomic model outperformed the ADC and joint radiomic models. MDPI 2023-09-11 /pmc/articles/PMC10531568/ /pubmed/37762841 http://dx.doi.org/10.3390/jcm12185900 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ye, Lei
Wang, Yayi
Xiang, Wanxin
Yao, Jin
Liu, Jiaming
Song, Bin
Radiomic Analysis of Quantitative T2 Mapping and Conventional MRI in Predicting Histologic Grade of Bladder Cancer
title Radiomic Analysis of Quantitative T2 Mapping and Conventional MRI in Predicting Histologic Grade of Bladder Cancer
title_full Radiomic Analysis of Quantitative T2 Mapping and Conventional MRI in Predicting Histologic Grade of Bladder Cancer
title_fullStr Radiomic Analysis of Quantitative T2 Mapping and Conventional MRI in Predicting Histologic Grade of Bladder Cancer
title_full_unstemmed Radiomic Analysis of Quantitative T2 Mapping and Conventional MRI in Predicting Histologic Grade of Bladder Cancer
title_short Radiomic Analysis of Quantitative T2 Mapping and Conventional MRI in Predicting Histologic Grade of Bladder Cancer
title_sort radiomic analysis of quantitative t2 mapping and conventional mri in predicting histologic grade of bladder cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10531568/
https://www.ncbi.nlm.nih.gov/pubmed/37762841
http://dx.doi.org/10.3390/jcm12185900
work_keys_str_mv AT yelei radiomicanalysisofquantitativet2mappingandconventionalmriinpredictinghistologicgradeofbladdercancer
AT wangyayi radiomicanalysisofquantitativet2mappingandconventionalmriinpredictinghistologicgradeofbladdercancer
AT xiangwanxin radiomicanalysisofquantitativet2mappingandconventionalmriinpredictinghistologicgradeofbladdercancer
AT yaojin radiomicanalysisofquantitativet2mappingandconventionalmriinpredictinghistologicgradeofbladdercancer
AT liujiaming radiomicanalysisofquantitativet2mappingandconventionalmriinpredictinghistologicgradeofbladdercancer
AT songbin radiomicanalysisofquantitativet2mappingandconventionalmriinpredictinghistologicgradeofbladdercancer