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Texture analysis on conventional MRI images accurately predicts early malignant transformation of low-grade gliomas

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单位: [1]Huazhong Univ Sci & Technol, Tongji Med Coll, Tongji Hosp, Dept Radiol, 1095 Jiefang Ave, Wuhan 430030, Hubei, Peoples R China [2]Weill Cornell Med, Dept Radiol, 407 E 61st St,Suite 107, New York, NY 10065 USA [3]Weill Cornell Med, Dept Neurol, New York, NY USA [4]Weill Cornell Med, Dept Neurol Surg, New York, NY USA [5]St Louis Univ, Dept Radiol, St Louis, MO 63103 USA [6]Cornell Univ, Dept Biomed Engn, Ithaca, NY USA
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关键词: Magnetic resonance imaging Glioma Astrocytoma Computer-assisted image analysis

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ObjectivesTexture analysis performed on MRI images can provide additional quantitative information that is invisible to human assessment. This study aimed to evaluate the feasibility of texture analysis on preoperative conventional MRI images in predicting early malignant transformation from low- to high-grade glioma and compare its utility to histogram analysis alone.MethodsA total of 68 patients with low-grade glioma (LGG) were included in this study, 15 of which showed malignant transformation. Patients were randomly divided into training (60%) and testing (40%) sets. Texture analyses were performed to obtain the most discriminant factor (MDF) values for both training and testing data. Receiver operating characteristic (ROC) curve analyses were performed on MDF values and 9 histogram parameters in the training data to obtain cutoff values for determining the correct rates of discrimination between two groups in the testing data.ResultsThe ROC analyses on MDF values resulted in an area under the curve (AUC) of 0.90 (sensitivity 85%, specificity 84%) for T2w FLAIR, 0.92 (86%, 94%) for ADC, 0.96 (97%, 84%) for T1w, and 0.82 (78%, 75%) for T1w + Gd and correctly discriminated between the two groups in 93%, 100%, 93%, and 92% of cases in testing data, respectively. In the astrocytoma subgroup, AUCs were 0.92 (88%, 83%) for T2w FLAIR and 0.90 (92%, 74%) for T1w + Gd and correctly discriminated two groups in 100% and 92% of cases. The MDF outperformed all 9 of the histogram parameters.ConclusionTexture analysis on conventional preoperative MRI images can accurately predict early malignant transformation of LGGs, which may guide therapeutic planning.Key Points center dot Texture analysis performed on MRI images can provide additional quantitative information that is invisible to human assessment.center dot Texture analysis based on conventional preoperative MR images can accurately predict early malignant transformation from low- to high-grade glioma.center dot Texture analysis is a clinically feasible technique that may provide an alternative and effective way of determining the likelihood of early malignant transformation and help guide therapeutic decisions.

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出版当年[2018]版:
大类 | 2 区 医学
小类 | 2 区 核医学
最新[2025]版:
大类 | 2 区 医学
小类 | 2 区 核医学
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出版当年[2017]版:
Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
最新[2024]版:
Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

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第一作者单位: [1]Huazhong Univ Sci & Technol, Tongji Med Coll, Tongji Hosp, Dept Radiol, 1095 Jiefang Ave, Wuhan 430030, Hubei, Peoples R China [2]Weill Cornell Med, Dept Radiol, 407 E 61st St,Suite 107, New York, NY 10065 USA
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