Evaluation of Radiomics Features Stability for Prediction Modeling using MR Image
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- Hirayama Misaki
- Division of Radiological Sciences, Graduate School of Health Sciences, Teikyo University
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- Kamezawa Hidemi
- Department of Radiological Technology, Faculty of Fukuoka Medical Technology, Teikyo University
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- Hiai Yasuhiro
- Department of Radiological Technology, Faculty of Fukuoka Medical Technology, Teikyo University
Bibliographic Information
- Other Title
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- MR画像を用いた予測モデリングのためのレディオミクス特徴量の安定性評価
Abstract
<p>Radiomics has been established to support treatmentdecision making in precision medicine. The radiomic features (RFs) used for prediction must be stable with respect to thevariety of imaging conditions. The purpose was to evaluate the stability of RFsextracted from T1-weighted MR images (T1WIs) using different imaging conditions. Two types of stabilityevaluation (SE) phantoms that canbe used for contrast (C-SE) andresolution (R-SE) assessment werecreated. The T1WIs of each phantom were acquired. Regarding the imagingparameters, the number of excitations (NEX), matrix size (MS),and repetition time (TR) werevaried. A total of 837 RFs were extracted from each T1WI acquired withdifferent parameters. Stability was evaluated using the coefficient ofvariation (CV). The criterion ofstability was employed as the CV < 0.05. The percentage of stable featuresin the C- and R-SE phantoms against individually changes in imaging conditionswere 30.8% and 31.1% for the TR, 34.8% and 39.1% for the NEX, and 35.6% and 38.5% for the MS respectively. Moreover, the percentage of stable features forchanging all conditions were 21.0% for the C-SE phantom and 22.1% for the R-SEphantom. Stable features were found in MR images against changes in imagingconditions.</p>
Journal
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- Medical Imaging and Information Sciences
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Medical Imaging and Information Sciences 40 (4), 114-119, 2023
MEDICAL IMAGING AND INFORMATION SCIENCES
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Keywords
Details 詳細情報について
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- CRID
- 1390298588087131520
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- ISSN
- 18804977
- 09101543
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- Text Lang
- ja
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- Data Source
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- JaLC
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- Abstract License Flag
- Disallowed