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Radiomics analysis of apparent diffusion coefficient in cervical cancer: A preliminary study on histological grade evaluation
Ist Teil von
Journal of magnetic resonance imaging, 2019-01, Vol.49 (1), p.280-290
Ort / Verlag
United States: Wiley Subscription Services, Inc
Erscheinungsjahr
2019
Quelle
Wiley-Blackwell Journals
Beschreibungen/Notizen
Background
The role of apparent diffusion coefficient (ADC)‐based radiomics features in evaluating histopathological grade of cervical cancer is unresolved.
Purpose
To determine if there is a difference between radiomics features derived from center‐slice 2D versus whole‐tumor volumetric 3D for ADC measurements in patients with cervical cancer regarding tumor histopathological grade, and systematically assess the impact of the b value on radiomics analysis in ADC quantifications.
Study Type
Prospective.
Subjects
In all, 160 patients with histopathologically confirmed squamous cell carcinoma of uterine cervix.
Field Strength/Sequence
Conventional and diffusion‐weighted MR images (b values = 0, 800, 1000 s/mm2) were acquired on a 3.0T MR scanner.
Assessment
Regions of interest (ROIs) were drawn manually along the margin of tumor on each slice, and then the center slice of the tumor was selected with naked eyes in the course of whole‐tumor segmentation. A total of 624 radiomics features were derived from T2‐weighted images and ADC maps. We randomly selected 50 cases and did the reproducibility analysis.
Statistical Tests
Parameters were compared using Wilcoxon signed rank test, Bland–Altman analysis, t‐test, and least absolute shrinkage and selection operator (LASSO) regression with crossvalidation.
Results
In all, 95 radiomics features were insensitive to ROI variation among T2 images, ADC map of b800, and ADC map of b1000 (P > 0.0002). There was a significant statistical difference between the performances of 2D center‐slice and 3D whole‐tumor radiomics models in both ADC feature sets of b800 and b1000 (P < 0.0001, P < 0.0001). Compared with ADC features of b800 (0.3758 ± 0.0118), the model of b1000 ADC features appeared to be slightly lower in overall misclassification error (0.3642 ± 0.0162) (P = 0.0076).
Data Conclusion
Several radiomics features extracted from T2 images and ADC maps were highly reproducible. Whole‐tumor volumetric 3D radiomics analysis had a better performance than using the 2D center‐slice of tumor in stratifying the histological grade of cervical cancer. A b value of 1000 s/mm2 is suggested as the optimal parameter in pelvic DWI scans.
Level of Evidence: 1
Technical Efficacy: Stage 1
J. Magn. Reson. Imaging 2019;49:280–290.