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Evaluation of RANO Criteria for the Assessment of Tumor Progression for Lower-Grade Gliomas

SIMPLE SUMMARY: Low-grade gliomas (LGGs) are relatively slow-growing primary brain tumors where the clinical criteria for tumor diagnosis and progression assessment include both qualitative and quantitative analytics. The Response Assessment in Neuro-Oncology (RANO) criteria for LGGs define tumor pr...

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Autores principales: Raman, Fabio, Mullen, Alexander, Byrd, Matthew, Bae, Sejong, Kim, Jinsuh, Sotoudeh, Houman, Morón, Fanny E., Fathallah-Shaykh, Hassan M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10340202/
https://www.ncbi.nlm.nih.gov/pubmed/37444384
http://dx.doi.org/10.3390/cancers15133274
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author Raman, Fabio
Mullen, Alexander
Byrd, Matthew
Bae, Sejong
Kim, Jinsuh
Sotoudeh, Houman
Morón, Fanny E.
Fathallah-Shaykh, Hassan M.
author_facet Raman, Fabio
Mullen, Alexander
Byrd, Matthew
Bae, Sejong
Kim, Jinsuh
Sotoudeh, Houman
Morón, Fanny E.
Fathallah-Shaykh, Hassan M.
author_sort Raman, Fabio
collection PubMed
description SIMPLE SUMMARY: Low-grade gliomas (LGGs) are relatively slow-growing primary brain tumors where the clinical criteria for tumor diagnosis and progression assessment include both qualitative and quantitative analytics. The Response Assessment in Neuro-Oncology (RANO) criteria for LGGs define tumor progression as ≥25% change in the T2/FLAIR signal area based on an operator’s discretion of the perpendicular diameter of the largest tumor cross-section. However, sources of error exist, including the limitation of 2D quantification, operator selection of both the tumor cross-section and perpendicular diameters, and the inability to quantify satellite tumor components. The aim of this retrospective study was to assess the accuracy and reproducibility of RANO in LGGs. In a heterogeneous population of 63 participants with different subtypes of LGGs, we showed that the accuracy of RANO compared to visual and volumetric gold standards was, at best, 67% and 57%, respectively. Reproducibility varied widely, even between board-certified neuroradiologists. Our results suggest that advanced approaches, such as computer-assisted tumor segmentation and annotation tools, are necessary to accurately assess LGG progression by reducing human variability. ABSTRACT: Purpose: The Response Assessment in Neuro-Oncology (RANO) criteria for lower-grade gliomas (LGGs) define tumor progression as ≥25% change in the T2/FLAIR signal area based on an operator’s discretion of the perpendicular diameter of the largest tumor cross-section. Potential sources of error include acquisition inconsistency of 2D slices, operator selection variabilities in both representative tumor cross-section and measurement line locations, and the inability to quantify infiltrative tumor margins and satellite lesions. Our goal was to assess the accuracy and reproducibility of RANO in LG. Materials and Methods: A total of 651 FLAIR MRIs from 63 participants with LGGs were retrospectively analyzed by three blinded attending physicians and three blinded resident trainees using RANO criteria, 2D visual assessment, and computer-assisted 3D volumetric assessment. Results: RANO product measurements had poor-to-moderate inter-operator reproducibility (r(2) = 0.28–0.82; coefficient of variance (CV) = 44–110%; mean percent difference (diff) = 0.4–46.8%) and moderate-to-excellent intra-operator reproducibility (r(2) = 0.71–0.88; CV = 31–58%; diff = 0.3–23.9%). When compared to 2D visual ground truth, the accuracy of RANO compared to previous and baseline scans was 66.7% and 65.1%, with an area under the ROC curve (AUC) of 0.67 and 0.66, respectively. When comparing to volumetric ground truth, the accuracy of RANO compared to previous and baseline scans was 21.0% and 56.5%, with an AUC of 0.39 and 0.55, respectively. The median time delay at diagnosis was greater for false negative cases than for false positive cases for the RANO assessment compared to previous (2.05 > 0.50 years, p = 0.003) and baseline scans (1.08 > 0.50 years, p = 0.02). Conclusion: RANO-based assessment of LGGs has moderate reproducibility and poor accuracy when compared to either visual or volumetric ground truths.
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spelling pubmed-103402022023-07-14 Evaluation of RANO Criteria for the Assessment of Tumor Progression for Lower-Grade Gliomas Raman, Fabio Mullen, Alexander Byrd, Matthew Bae, Sejong Kim, Jinsuh Sotoudeh, Houman Morón, Fanny E. Fathallah-Shaykh, Hassan M. Cancers (Basel) Article SIMPLE SUMMARY: Low-grade gliomas (LGGs) are relatively slow-growing primary brain tumors where the clinical criteria for tumor diagnosis and progression assessment include both qualitative and quantitative analytics. The Response Assessment in Neuro-Oncology (RANO) criteria for LGGs define tumor progression as ≥25% change in the T2/FLAIR signal area based on an operator’s discretion of the perpendicular diameter of the largest tumor cross-section. However, sources of error exist, including the limitation of 2D quantification, operator selection of both the tumor cross-section and perpendicular diameters, and the inability to quantify satellite tumor components. The aim of this retrospective study was to assess the accuracy and reproducibility of RANO in LGGs. In a heterogeneous population of 63 participants with different subtypes of LGGs, we showed that the accuracy of RANO compared to visual and volumetric gold standards was, at best, 67% and 57%, respectively. Reproducibility varied widely, even between board-certified neuroradiologists. Our results suggest that advanced approaches, such as computer-assisted tumor segmentation and annotation tools, are necessary to accurately assess LGG progression by reducing human variability. ABSTRACT: Purpose: The Response Assessment in Neuro-Oncology (RANO) criteria for lower-grade gliomas (LGGs) define tumor progression as ≥25% change in the T2/FLAIR signal area based on an operator’s discretion of the perpendicular diameter of the largest tumor cross-section. Potential sources of error include acquisition inconsistency of 2D slices, operator selection variabilities in both representative tumor cross-section and measurement line locations, and the inability to quantify infiltrative tumor margins and satellite lesions. Our goal was to assess the accuracy and reproducibility of RANO in LG. Materials and Methods: A total of 651 FLAIR MRIs from 63 participants with LGGs were retrospectively analyzed by three blinded attending physicians and three blinded resident trainees using RANO criteria, 2D visual assessment, and computer-assisted 3D volumetric assessment. Results: RANO product measurements had poor-to-moderate inter-operator reproducibility (r(2) = 0.28–0.82; coefficient of variance (CV) = 44–110%; mean percent difference (diff) = 0.4–46.8%) and moderate-to-excellent intra-operator reproducibility (r(2) = 0.71–0.88; CV = 31–58%; diff = 0.3–23.9%). When compared to 2D visual ground truth, the accuracy of RANO compared to previous and baseline scans was 66.7% and 65.1%, with an area under the ROC curve (AUC) of 0.67 and 0.66, respectively. When comparing to volumetric ground truth, the accuracy of RANO compared to previous and baseline scans was 21.0% and 56.5%, with an AUC of 0.39 and 0.55, respectively. The median time delay at diagnosis was greater for false negative cases than for false positive cases for the RANO assessment compared to previous (2.05 > 0.50 years, p = 0.003) and baseline scans (1.08 > 0.50 years, p = 0.02). Conclusion: RANO-based assessment of LGGs has moderate reproducibility and poor accuracy when compared to either visual or volumetric ground truths. MDPI 2023-06-21 /pmc/articles/PMC10340202/ /pubmed/37444384 http://dx.doi.org/10.3390/cancers15133274 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
Raman, Fabio
Mullen, Alexander
Byrd, Matthew
Bae, Sejong
Kim, Jinsuh
Sotoudeh, Houman
Morón, Fanny E.
Fathallah-Shaykh, Hassan M.
Evaluation of RANO Criteria for the Assessment of Tumor Progression for Lower-Grade Gliomas
title Evaluation of RANO Criteria for the Assessment of Tumor Progression for Lower-Grade Gliomas
title_full Evaluation of RANO Criteria for the Assessment of Tumor Progression for Lower-Grade Gliomas
title_fullStr Evaluation of RANO Criteria for the Assessment of Tumor Progression for Lower-Grade Gliomas
title_full_unstemmed Evaluation of RANO Criteria for the Assessment of Tumor Progression for Lower-Grade Gliomas
title_short Evaluation of RANO Criteria for the Assessment of Tumor Progression for Lower-Grade Gliomas
title_sort evaluation of rano criteria for the assessment of tumor progression for lower-grade gliomas
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10340202/
https://www.ncbi.nlm.nih.gov/pubmed/37444384
http://dx.doi.org/10.3390/cancers15133274
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