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Poster Display session 1

1116 - 3D based texture analysis serving as potential diagnostic factor in discriminating primary central nervous system lymphoma from metastatic brain tumors: A preliminary study

Date

28 Sep 2019

Session

Poster Display session 1

Presenters

Wen Guo

Citation

Annals of Oncology (2019) 30 (suppl_5): v143-v158. 10.1093/annonc/mdz243

Authors

W. Guo1, X. MA2

Author affiliations

  • 1 West China School Of Medicine, West China Hospital, Sichuan University, 610041 - Chengdu/CN
  • 2 Department Of Biotherapy, Cancer Center, State Key Laboratory Of Biotherapy, West China Hospital, Sichuan University, 610041 - Chengdu/CN
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Resources

Abstract 1116

Background

The purpose of current study is to discriminate primary central nervous system lymphoma from metastatic brain tumors with 3D texture features.

Methods

A total number of 120 patients involved this study, 58 with PCNSL and 62 with MBTs. Texture features were retrieved from histogram matrix and GLCM matrix. Mann Whitney U tests were performed to detect if texture feature were significantly different between two type of tumors. Binary logistic regressions were conducted to detect if they could be taken as independent predictors, based on which integrated model was built. ROC curves of each parameter were generated to evaluate the ability in discrimination.

Results

Three texture features (histo-Kurtosis, GLCM-Contrast and GLCM-Dissimilarity from post contrast T1WI) were independent predictors in discrimination, whose AUC were 0.632, 0.742 and 0.706 respectively. The integrated model represented better diagnostic value than any single features. ROC curve suggested the AUC of model was 0.832, representing practical clinical value.

Conclusions

Texture analysis has potential in the differentiation between primary central nervous system lymphoma from metastatic brain tumors. Moreover, combination of single texture shows more promising and effective ability in discrimination.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

Xuelei Ma.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.

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