Differentiation Between Primary Central Nervous System Lymphoma and Atypical Glioblastoma Based on MRI Morphological Feature and Signal Intensity Ratio: A Retrospective Multicenter Study
ObjectivesTo investigate the value of morphological feature and signal intensity ratio (SIR) derived from conventional magnetic resonance imaging (MRI) in distinguishing primary central nervous system lymphoma (PCNSL) from atypical glioblastoma (aGBM).MethodsPathology-confirmed PCNSLs (n = 93) or aG...
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| Language: | English |
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Frontiers Media S.A.
2022-01-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2022.811197/full |
| _version_ | 1828136779598790656 |
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| author | Yu Han Zi-Jun Wang Wen-Hua Li Yang Yang Jian Zhang Xi-Biao Yang Lin Zuo Gang Xiao Sheng-Zhong Wang Lin-Feng Yan Guang-Bin Cui |
| author_facet | Yu Han Zi-Jun Wang Wen-Hua Li Yang Yang Jian Zhang Xi-Biao Yang Lin Zuo Gang Xiao Sheng-Zhong Wang Lin-Feng Yan Guang-Bin Cui |
| author_sort | Yu Han |
| collection | DOAJ |
| description | ObjectivesTo investigate the value of morphological feature and signal intensity ratio (SIR) derived from conventional magnetic resonance imaging (MRI) in distinguishing primary central nervous system lymphoma (PCNSL) from atypical glioblastoma (aGBM).MethodsPathology-confirmed PCNSLs (n = 93) or aGBMs (n = 48) from three institutions were retrospectively enrolled and divided into training cohort (n = 98) and test cohort (n = 43). Morphological features and SIRs were compared between PCNSL and aGBM. Using linear discriminant analysis, multiple models were constructed with SIRs and morphological features alone or jointly, and the diagnostic performances were evaluated via receiver operating characteristic (ROC) analysis. Areas under the curves (AUCs) and accuracies (ACCs) of the models were compared with the radiologists’ assessment.ResultsIncision sign, T2 pseudonecrosis sign, reef sign and peritumoral leukomalacia sign were associated with PCNSL (training and overall cohorts, P < 0.05). Increased T1 ratio, decreased T2 ratio and T2/T1 ratio were predictive of PCNSL (all P < 0.05). ROC analysis showed that combination of morphological features and SIRs achieved the best diagnostic performance for differentiation of PCNSL and aGBM with AUC/ACC of 0.899/0.929 for the training cohort, AUC/ACC of 0.794/0.837 for the test cohort and AUC/ACC of 0.869/0.901 for the overall cohort, respectively. Based on the overall cohort, two radiologists could distinguish PCNSL from aGBM with AUC/ACC of 0.732/0.724 for radiologist A and AUC/ACC of 0.811/0.829 for radiologist B.ConclusionMRI morphological features can help differentiate PCNSL from aGBM. When combined with SIRs, the diagnostic performance was better than that of radiologists’ assessment. |
| first_indexed | 2024-04-11T18:09:41Z |
| format | Article |
| id | doaj.art-62bad759181c48f98591369b1bba79b6 |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-04-11T18:09:41Z |
| publishDate | 2022-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-62bad759181c48f98591369b1bba79b62022-12-22T04:10:09ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2022-01-011210.3389/fonc.2022.811197811197Differentiation Between Primary Central Nervous System Lymphoma and Atypical Glioblastoma Based on MRI Morphological Feature and Signal Intensity Ratio: A Retrospective Multicenter StudyYu Han0Zi-Jun Wang1Wen-Hua Li2Yang Yang3Jian Zhang4Xi-Biao Yang5Lin Zuo6Gang Xiao7Sheng-Zhong Wang8Lin-Feng Yan9Guang-Bin Cui10Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, Xi’an, ChinaBattalion of the First Regiment of cadets of Basic Medicine, Fourth Military Medical University, Xi’an, ChinaBattalion of the Second Regiment of cadets of Basic Medicine, Fourth Military Medical University, Xi’an, ChinaDepartment of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, Xi’an, ChinaDepartment of Radiology, Xi’an XD Group Hospital, Shaanxi University of Chinese Medicine, Xi’an, ChinaDepartment of Radiology, West China Hospital, Sichuan University, Chengdu, ChinaDepartment of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, Xi’an, ChinaDepartment of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, Xi’an, ChinaDepartment of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, Xi’an, ChinaDepartment of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, Xi’an, ChinaDepartment of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University, Xi’an, ChinaObjectivesTo investigate the value of morphological feature and signal intensity ratio (SIR) derived from conventional magnetic resonance imaging (MRI) in distinguishing primary central nervous system lymphoma (PCNSL) from atypical glioblastoma (aGBM).MethodsPathology-confirmed PCNSLs (n = 93) or aGBMs (n = 48) from three institutions were retrospectively enrolled and divided into training cohort (n = 98) and test cohort (n = 43). Morphological features and SIRs were compared between PCNSL and aGBM. Using linear discriminant analysis, multiple models were constructed with SIRs and morphological features alone or jointly, and the diagnostic performances were evaluated via receiver operating characteristic (ROC) analysis. Areas under the curves (AUCs) and accuracies (ACCs) of the models were compared with the radiologists’ assessment.ResultsIncision sign, T2 pseudonecrosis sign, reef sign and peritumoral leukomalacia sign were associated with PCNSL (training and overall cohorts, P < 0.05). Increased T1 ratio, decreased T2 ratio and T2/T1 ratio were predictive of PCNSL (all P < 0.05). ROC analysis showed that combination of morphological features and SIRs achieved the best diagnostic performance for differentiation of PCNSL and aGBM with AUC/ACC of 0.899/0.929 for the training cohort, AUC/ACC of 0.794/0.837 for the test cohort and AUC/ACC of 0.869/0.901 for the overall cohort, respectively. Based on the overall cohort, two radiologists could distinguish PCNSL from aGBM with AUC/ACC of 0.732/0.724 for radiologist A and AUC/ACC of 0.811/0.829 for radiologist B.ConclusionMRI morphological features can help differentiate PCNSL from aGBM. When combined with SIRs, the diagnostic performance was better than that of radiologists’ assessment.https://www.frontiersin.org/articles/10.3389/fonc.2022.811197/fullprimary central nervous system lymphomaglioblastomamagnetic resonance imagingsignal intensity ratiomorphological feature |
| spellingShingle | Yu Han Zi-Jun Wang Wen-Hua Li Yang Yang Jian Zhang Xi-Biao Yang Lin Zuo Gang Xiao Sheng-Zhong Wang Lin-Feng Yan Guang-Bin Cui Differentiation Between Primary Central Nervous System Lymphoma and Atypical Glioblastoma Based on MRI Morphological Feature and Signal Intensity Ratio: A Retrospective Multicenter Study Frontiers in Oncology primary central nervous system lymphoma glioblastoma magnetic resonance imaging signal intensity ratio morphological feature |
| title | Differentiation Between Primary Central Nervous System Lymphoma and Atypical Glioblastoma Based on MRI Morphological Feature and Signal Intensity Ratio: A Retrospective Multicenter Study |
| title_full | Differentiation Between Primary Central Nervous System Lymphoma and Atypical Glioblastoma Based on MRI Morphological Feature and Signal Intensity Ratio: A Retrospective Multicenter Study |
| title_fullStr | Differentiation Between Primary Central Nervous System Lymphoma and Atypical Glioblastoma Based on MRI Morphological Feature and Signal Intensity Ratio: A Retrospective Multicenter Study |
| title_full_unstemmed | Differentiation Between Primary Central Nervous System Lymphoma and Atypical Glioblastoma Based on MRI Morphological Feature and Signal Intensity Ratio: A Retrospective Multicenter Study |
| title_short | Differentiation Between Primary Central Nervous System Lymphoma and Atypical Glioblastoma Based on MRI Morphological Feature and Signal Intensity Ratio: A Retrospective Multicenter Study |
| title_sort | differentiation between primary central nervous system lymphoma and atypical glioblastoma based on mri morphological feature and signal intensity ratio a retrospective multicenter study |
| topic | primary central nervous system lymphoma glioblastoma magnetic resonance imaging signal intensity ratio morphological feature |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2022.811197/full |
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