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Differentiating between non-functioning pituitary macroadenomas and sellar meningiomas using ADC

INTRODUCTION AND AIM: It is difficult to distinguish between non-functioning pituitary macroadenomas (NFPMAs) and sellar meningiomas because of their overlapping imaging manifestations on routine MRI, especially in cases of meningiomas growing into the saddle. Here, we aimed to differentiate between...

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Autores principales: Zhang, Jing, Zhao, Zhiyong, Dong, Li, Han, Tao, Zhang, Guojin, Cao, Yuntai, Zhou, Junlin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Bioscientifica Ltd 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7774768/
https://www.ncbi.nlm.nih.gov/pubmed/33112805
http://dx.doi.org/10.1530/EC-20-0434
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author Zhang, Jing
Zhao, Zhiyong
Dong, Li
Han, Tao
Zhang, Guojin
Cao, Yuntai
Zhou, Junlin
author_facet Zhang, Jing
Zhao, Zhiyong
Dong, Li
Han, Tao
Zhang, Guojin
Cao, Yuntai
Zhou, Junlin
author_sort Zhang, Jing
collection PubMed
description INTRODUCTION AND AIM: It is difficult to distinguish between non-functioning pituitary macroadenomas (NFPMAs) and sellar meningiomas because of their overlapping imaging manifestations on routine MRI, especially in cases of meningiomas growing into the saddle. Here, we aimed to differentiate between these two tumors using apparent diffusion coefficient (ADC) values and MRI characteristics. METHODS: A total of 60 NFPMA and 52 sellar meningioma cases confirmed by the pathological analysis were retrospectively reviewed. All patients were examined via routine MRI and diffusion-weighted imaging (DWI) before undergoing surgery. The clinical characteristics, MRI characteristics, and max ADC (ADCmax), average ADC (ADCmean), and minimum ADC (ADCmin) values were compared between the two tumors via Chi-square test and two sample t-tests. Receiver operating characteristic (ROC) curve and binary logistic regression analyses were conducted to determine the discrimination ability. RESULTS: The ADCmax, ADCmean, and ADCmin values were significantly higher in NFPMAs compared to sellar meningiomas (P < 0.001 for all). Among ADC values, ADCmax demonstrated good performance with an AUC of 0.896 (95% CI, 0.823–0.969) and accuracy of 88.7%. A cut-off value of 0.97 × 10(−3) mm(2)/s was used for ADCmax for differentiation between tumors. A combination of ADCmax values and clinicoradiological features showed the best discrimination ability for differential diagnosis between the two tumors, with an AUC of 0.981 (95% CI, 0.958–1.000) and accuracy of 96.9%. CONCLUSION: A combination of ADCmax and clinicoradiological features demonstrates good discrimination ability and high accuracy for differentiation between NFPMAs and sellar meningiomas, and is a potential quantitative tool to aid in the selection of surgical techniques.
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spelling pubmed-77747682021-01-05 Differentiating between non-functioning pituitary macroadenomas and sellar meningiomas using ADC Zhang, Jing Zhao, Zhiyong Dong, Li Han, Tao Zhang, Guojin Cao, Yuntai Zhou, Junlin Endocr Connect Research INTRODUCTION AND AIM: It is difficult to distinguish between non-functioning pituitary macroadenomas (NFPMAs) and sellar meningiomas because of their overlapping imaging manifestations on routine MRI, especially in cases of meningiomas growing into the saddle. Here, we aimed to differentiate between these two tumors using apparent diffusion coefficient (ADC) values and MRI characteristics. METHODS: A total of 60 NFPMA and 52 sellar meningioma cases confirmed by the pathological analysis were retrospectively reviewed. All patients were examined via routine MRI and diffusion-weighted imaging (DWI) before undergoing surgery. The clinical characteristics, MRI characteristics, and max ADC (ADCmax), average ADC (ADCmean), and minimum ADC (ADCmin) values were compared between the two tumors via Chi-square test and two sample t-tests. Receiver operating characteristic (ROC) curve and binary logistic regression analyses were conducted to determine the discrimination ability. RESULTS: The ADCmax, ADCmean, and ADCmin values were significantly higher in NFPMAs compared to sellar meningiomas (P < 0.001 for all). Among ADC values, ADCmax demonstrated good performance with an AUC of 0.896 (95% CI, 0.823–0.969) and accuracy of 88.7%. A cut-off value of 0.97 × 10(−3) mm(2)/s was used for ADCmax for differentiation between tumors. A combination of ADCmax values and clinicoradiological features showed the best discrimination ability for differential diagnosis between the two tumors, with an AUC of 0.981 (95% CI, 0.958–1.000) and accuracy of 96.9%. CONCLUSION: A combination of ADCmax and clinicoradiological features demonstrates good discrimination ability and high accuracy for differentiation between NFPMAs and sellar meningiomas, and is a potential quantitative tool to aid in the selection of surgical techniques. Bioscientifica Ltd 2020-10-19 /pmc/articles/PMC7774768/ /pubmed/33112805 http://dx.doi.org/10.1530/EC-20-0434 Text en © 2020 The authors http://creativecommons.org/licenses/by-nc/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. (http://creativecommons.org/licenses/by-nc/4.0/)
spellingShingle Research
Zhang, Jing
Zhao, Zhiyong
Dong, Li
Han, Tao
Zhang, Guojin
Cao, Yuntai
Zhou, Junlin
Differentiating between non-functioning pituitary macroadenomas and sellar meningiomas using ADC
title Differentiating between non-functioning pituitary macroadenomas and sellar meningiomas using ADC
title_full Differentiating between non-functioning pituitary macroadenomas and sellar meningiomas using ADC
title_fullStr Differentiating between non-functioning pituitary macroadenomas and sellar meningiomas using ADC
title_full_unstemmed Differentiating between non-functioning pituitary macroadenomas and sellar meningiomas using ADC
title_short Differentiating between non-functioning pituitary macroadenomas and sellar meningiomas using ADC
title_sort differentiating between non-functioning pituitary macroadenomas and sellar meningiomas using adc
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7774768/
https://www.ncbi.nlm.nih.gov/pubmed/33112805
http://dx.doi.org/10.1530/EC-20-0434
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