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Diagnosing growth in low-grade gliomas with and without longitudinal volume measurements: A retrospective observational study

BACKGROUND: Low-grade gliomas cause significant neurological morbidity by brain invasion. There is no universally accepted objective technique available for detection of enlargement of low-grade gliomas in the clinical setting; subjective evaluation by clinicians using visual comparison of longitudi...

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Autores principales: Fathallah-Shaykh, Hassan M., DeAtkine, Andrew, Coffee, Elizabeth, Khayat, Elias, Bag, Asim K., Han, Xiaosi, Warren, Paula Province, Bredel, Markus, Fiveash, John, Markert, James, Bouaynaya, Nidhal, Nabors, Louis B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6538148/
https://www.ncbi.nlm.nih.gov/pubmed/31136584
http://dx.doi.org/10.1371/journal.pmed.1002810
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author Fathallah-Shaykh, Hassan M.
DeAtkine, Andrew
Coffee, Elizabeth
Khayat, Elias
Bag, Asim K.
Han, Xiaosi
Warren, Paula Province
Bredel, Markus
Fiveash, John
Markert, James
Bouaynaya, Nidhal
Nabors, Louis B.
author_facet Fathallah-Shaykh, Hassan M.
DeAtkine, Andrew
Coffee, Elizabeth
Khayat, Elias
Bag, Asim K.
Han, Xiaosi
Warren, Paula Province
Bredel, Markus
Fiveash, John
Markert, James
Bouaynaya, Nidhal
Nabors, Louis B.
author_sort Fathallah-Shaykh, Hassan M.
collection PubMed
description BACKGROUND: Low-grade gliomas cause significant neurological morbidity by brain invasion. There is no universally accepted objective technique available for detection of enlargement of low-grade gliomas in the clinical setting; subjective evaluation by clinicians using visual comparison of longitudinal radiological studies is the gold standard. The aim of this study is to determine whether a computer-assisted diagnosis (CAD) method helps physicians detect earlier growth of low-grade gliomas. METHODS AND FINDINGS: We reviewed 165 patients diagnosed with grade 2 gliomas, seen at the University of Alabama at Birmingham clinics from 1 July 2017 to 14 May 2018. MRI scans were collected during the spring and summer of 2018. Fifty-six gliomas met the inclusion criteria, including 19 oligodendrogliomas, 26 astrocytomas, and 11 mixed gliomas in 30 males and 26 females with a mean age of 48 years and a range of follow-up of 150.2 months (difference between highest and lowest values). None received radiation therapy. We also studied 7 patients with an imaging abnormality without pathological diagnosis, who were clinically stable at the time of retrospective review (14 May 2018). This study compared growth detection by 7 physicians aided by the CAD method with retrospective clinical reports. The tumors of 63 patients (56 + 7) in 627 MRI scans were digitized, including 34 grade 2 gliomas with radiological progression and 22 radiologically stable grade 2 gliomas. The CAD method consisted of tumor segmentation, computing volumes, and pointing to growth by the online abrupt change-of-point method, which considers only past measurements. Independent scientists have evaluated the segmentation method. In 29 of the 34 patients with progression, the median time to growth detection was only 14 months for CAD compared to 44 months for current standard of care radiological evaluation (p < 0.001). Using CAD, accurate detection of tumor enlargement was possible with a median of only 57% change in the tumor volume as compared to a median of 174% change of volume necessary to diagnose tumor growth using standard of care clinical methods (p < 0.001). In the radiologically stable group, CAD facilitated growth detection in 13 out of 22 patients. CAD did not detect growth in the imaging abnormality group. The main limitation of this study was its retrospective design; nevertheless, the results depict the current state of a gold standard in clinical practice that allowed a significant increase in tumor volumes from baseline before detection. Such large increases in tumor volume would not be permitted in a prospective design. The number of glioma patients (n = 56) is a limitation; however, it is equivalent to the number of patients in phase II clinical trials. CONCLUSIONS: The current practice of visual comparison of longitudinal MRI scans is associated with significant delays in detecting growth of low-grade gliomas. Our findings support the idea that physicians aided by CAD detect growth at significantly smaller volumes than physicians using visual comparison alone. This study does not answer the questions whether to treat or not and which treatment modality is optimal. Nonetheless, early growth detection sets the stage for future clinical studies that address these questions and whether early therapeutic interventions prolong survival and improve quality of life.
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spelling pubmed-65381482019-06-05 Diagnosing growth in low-grade gliomas with and without longitudinal volume measurements: A retrospective observational study Fathallah-Shaykh, Hassan M. DeAtkine, Andrew Coffee, Elizabeth Khayat, Elias Bag, Asim K. Han, Xiaosi Warren, Paula Province Bredel, Markus Fiveash, John Markert, James Bouaynaya, Nidhal Nabors, Louis B. PLoS Med Research Article BACKGROUND: Low-grade gliomas cause significant neurological morbidity by brain invasion. There is no universally accepted objective technique available for detection of enlargement of low-grade gliomas in the clinical setting; subjective evaluation by clinicians using visual comparison of longitudinal radiological studies is the gold standard. The aim of this study is to determine whether a computer-assisted diagnosis (CAD) method helps physicians detect earlier growth of low-grade gliomas. METHODS AND FINDINGS: We reviewed 165 patients diagnosed with grade 2 gliomas, seen at the University of Alabama at Birmingham clinics from 1 July 2017 to 14 May 2018. MRI scans were collected during the spring and summer of 2018. Fifty-six gliomas met the inclusion criteria, including 19 oligodendrogliomas, 26 astrocytomas, and 11 mixed gliomas in 30 males and 26 females with a mean age of 48 years and a range of follow-up of 150.2 months (difference between highest and lowest values). None received radiation therapy. We also studied 7 patients with an imaging abnormality without pathological diagnosis, who were clinically stable at the time of retrospective review (14 May 2018). This study compared growth detection by 7 physicians aided by the CAD method with retrospective clinical reports. The tumors of 63 patients (56 + 7) in 627 MRI scans were digitized, including 34 grade 2 gliomas with radiological progression and 22 radiologically stable grade 2 gliomas. The CAD method consisted of tumor segmentation, computing volumes, and pointing to growth by the online abrupt change-of-point method, which considers only past measurements. Independent scientists have evaluated the segmentation method. In 29 of the 34 patients with progression, the median time to growth detection was only 14 months for CAD compared to 44 months for current standard of care radiological evaluation (p < 0.001). Using CAD, accurate detection of tumor enlargement was possible with a median of only 57% change in the tumor volume as compared to a median of 174% change of volume necessary to diagnose tumor growth using standard of care clinical methods (p < 0.001). In the radiologically stable group, CAD facilitated growth detection in 13 out of 22 patients. CAD did not detect growth in the imaging abnormality group. The main limitation of this study was its retrospective design; nevertheless, the results depict the current state of a gold standard in clinical practice that allowed a significant increase in tumor volumes from baseline before detection. Such large increases in tumor volume would not be permitted in a prospective design. The number of glioma patients (n = 56) is a limitation; however, it is equivalent to the number of patients in phase II clinical trials. CONCLUSIONS: The current practice of visual comparison of longitudinal MRI scans is associated with significant delays in detecting growth of low-grade gliomas. Our findings support the idea that physicians aided by CAD detect growth at significantly smaller volumes than physicians using visual comparison alone. This study does not answer the questions whether to treat or not and which treatment modality is optimal. Nonetheless, early growth detection sets the stage for future clinical studies that address these questions and whether early therapeutic interventions prolong survival and improve quality of life. Public Library of Science 2019-05-28 /pmc/articles/PMC6538148/ /pubmed/31136584 http://dx.doi.org/10.1371/journal.pmed.1002810 Text en © 2019 Fathallah-Shaykh et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Fathallah-Shaykh, Hassan M.
DeAtkine, Andrew
Coffee, Elizabeth
Khayat, Elias
Bag, Asim K.
Han, Xiaosi
Warren, Paula Province
Bredel, Markus
Fiveash, John
Markert, James
Bouaynaya, Nidhal
Nabors, Louis B.
Diagnosing growth in low-grade gliomas with and without longitudinal volume measurements: A retrospective observational study
title Diagnosing growth in low-grade gliomas with and without longitudinal volume measurements: A retrospective observational study
title_full Diagnosing growth in low-grade gliomas with and without longitudinal volume measurements: A retrospective observational study
title_fullStr Diagnosing growth in low-grade gliomas with and without longitudinal volume measurements: A retrospective observational study
title_full_unstemmed Diagnosing growth in low-grade gliomas with and without longitudinal volume measurements: A retrospective observational study
title_short Diagnosing growth in low-grade gliomas with and without longitudinal volume measurements: A retrospective observational study
title_sort diagnosing growth in low-grade gliomas with and without longitudinal volume measurements: a retrospective observational study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6538148/
https://www.ncbi.nlm.nih.gov/pubmed/31136584
http://dx.doi.org/10.1371/journal.pmed.1002810
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