MRI-based radiomics in breast cancer: feature robustness with respect to inter-observer segmentation variability

被引:56
作者
Granzier, R. W. Y. [1 ,2 ]
Verbakel, N. M. H. [1 ]
Ibrahim, A. [2 ,3 ,4 ,5 ,6 ,7 ]
van Timmeren, J. E. [2 ,3 ,4 ]
van Nijnatten, T. J. A. [3 ]
Leijenaar, R. T. H. [2 ,4 ]
Lobbes, M. B. I. [2 ,3 ,8 ]
Smidt, M. L. [1 ,2 ]
Woodruff, H. C. [2 ,3 ,4 ]
机构
[1] Maastricht Univ, Med Ctr, Dept Surg, POB 5800, NL-6202 AZ Maastricht, Netherlands
[2] Maastricht Univ, GROW Sch Oncol & Dev Biol, Maastricht, Netherlands
[3] Maastricht Univ, Med Ctr, Dept Radiol & Nucl Med, Maastricht, Netherlands
[4] Maastricht Univ, Dept Precis Med, D Lab, Maastricht, Netherlands
[5] Hosp Ctr Univ Liege, Div Nucl Med & Oncol Imaging, Dept Med Phys, Liege, Belgium
[6] Rhein Westfal TH Aachen, Univ Hosp, Dept Nucl Med, Aachen, Germany
[7] Rhein Westfal TH Aachen, Univ Hosp, Comprehens Diagnost Ctr Aachen CDCA, Aachen, Germany
[8] Zuyderland Med Ctr, Dept Med Imaging, Sittard Geleen, Netherlands
关键词
TUMOR DELINEATION; RECTAL-CANCER; IMAGES; REPRODUCIBILITY; STABILITY; LESIONS; SYSTEM;
D O I
10.1038/s41598-020-70940-z
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Radiomics is an emerging field using the extraction of quantitative features from medical images for tissue characterization. While MRI-based radiomics is still at an early stage, it showed some promising results in studies focusing on breast cancer patients in improving diagnoses and therapy response assessment. Nevertheless, the use of radiomics raises a number of issues regarding feature quantification and robustness. Therefore, our study aim was to determine the robustness of radiomics features extracted by two commonly used radiomics software with respect to variability in manual breast tumor segmentation on MRI. A total of 129 histologically confirmed breast tumors were segmented manually in three dimensions on the first post-contrast T1-weighted MR exam by four observers: a dedicated breast radiologist, a resident, a Ph.D. candidate, and a medical student. Robust features were assessed using the intraclass correlation coefficient (ICC>0.9). The inter-observer variability was evaluated by the volumetric Dice Similarity Coefficient (DSC). The mean DSC for all tumors was 0.81 (range 0.19-0.96), indicating a good spatial overlap of the segmentations based on observers of varying expertise. In total, 41.6% (552/1328) and 32.8% (273/833) of all RadiomiX and Pyradiomics features, respectively, were identified as robust and were independent of inter-observer manual segmentation variability.
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页数:11
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