Textural Features of Mouse Glioma Models Measured by Dynamic Contrast-Enhanced MR Images with 3D Isotropic Resolution
Abstract
:1. Introduction
2. Materials and Methods
2.1. Animal Model
2.2. Data Acquisition
2.3. Image Reconstruction and PK Parameter Maps
2.4. Assessment of Isotropic versus Anisotropic Resolution Images
3. Results
3.1. Isotropic vs. Anisotropic Resolution Images
3.2. Anisotropic Resolution Images in Different Orientations
3.3. Texture Features Reported in DCE-MRI Studies
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Study | Acquisition Resolution | Cancer Type | Predicting | Parameter | Feature |
---|---|---|---|---|---|
W. Ma et al. (2018) [26] | 0.98 × 0.49 × 1.8 mm | Breast Cancer | Ki-67 expression | Post-Contrast T1-w DCE | First-Order: Mean, SD, Skewness, and Kurtosis GLCM: Energy (Joint energy), Entropy (Joint entropy), Contrast, Correlation, Homogeneity (Inverse difference), and IDM |
Y. Wang et al. (2019) [15] | 0.89 × 0.89 × 3 mm | Prostate Cancer | Bone Metastases | Post-Contrast T1-w DCE | First-Order: 0.025 quartile GLCM: Auto correlation, Cluster prominence, Difference entropy, Dissimilarity, Homogeneity, IDM, and IDMNGLRLM: Short run low grey level emphasis and Short run high grey level emphasis |
Thibault et al. (2016) [17] | 1 × 1 × 1.4 mm | Breast Cancer | Response to Treatment | Ktrans τi | GLCM: Entropy difference, Contrast, Variance differences, and Inertia GLRLM: Gray-level nonuniformity and Long-run emphasis GLCM: Mean |
ve | GLCM: Contrast and Inertia | ||||
Xie T et al. (2017) [27] | 0.74 × 0.53 × 6.0 mm | Glioma | Grading Ki-67 expression | Ktrans ve, vp, Ktrans, vp | GLCM: Energy (Joint Energy), Entropy (Joint Entropy), Inertia (Contrast), and Correlation IDM GLCM: Energy, Entropy, and IDM GLCM: Energy (Joint Energy) and IDM |
Liu YYG et al. (2020) [28] | 0.6 × 0.8 × 3 mm | Pituitary macroadenoma | Tumor ‘Aggressiveness’ via Heterogeneity in Vasculature | Ktrans ve Ktrans, ve Kep | First-Order: Skewness First-Order: Mean GLRLM: Long-run emphasis, Gray-level non-uniformity, High gray-level run emphasis, and Short run emphasis GLCM: Difference entropy GLRLM: Gray level non-uniformity and Run length non-uniformity |
Zhou X et al. (2020) [29] | 1.4 × 1.3 × 4 mm | Breast Cancer | Benign/malignancy | Ktrans, ve Kep, ve ve | GLCM: Entropy (Joint entropy) GLRLM: Short run low grey level emphasis GLCM: Cluster shade |
vp | GLCM: IDM | ||||
Molecular Subtype | Ktrans, ve Ktrans ve vp | GLCM: Entropy (Joint entropy) GLRLM: Grey level non uniformity and Long run emphasis GLRLM: Short run emphasis First-Order: Entropy GLSZM: Zone percentage GLRLM: Short run high grey level emphasis and Short run low grey level emphasis GLSZM: High grey level emphasis |
Percent of Features Demonstrating Significant Difference from Isotropic Resolution | ||||||
---|---|---|---|---|---|---|
Texture Features (n = 75) | Histogram Features (n = 18) | |||||
1.014 mm | 0.546 mm | 0.234 mm | 1.014 mm | 0.546 mm | 0.234 mm | |
ve | 29.3 | 22.7 | 1.3 | 16.7 | 0.0 | 0.0 |
vp | 24.0 | 13.3 | 5.3 | 33.3 | 22.2 | 16.7 |
FP | 53.3 | 52.0 | 42.7 | 44.4 | 33.3 | 16.7 |
PS | 13.3 | 17.3 | 2.7 | 38.9 | 44.4 | 33.3 |
τi | 33.3 | 34.7 | 30.7 | 55.6 | 61.1 | 44.4 |
Ktrans | 16.0 | 17.3 | 0.0 | 33.3 | 27.8 | 27.8 |
T1-w | 48.0 | 66.7 | 46.7 | 55.6 | 72.2 | 38.9 |
Total | 31.0 | 32.0 | 18.5 | 39.7 | 37.3 | 25.4 |
Ax | Cor | Sag | Ax | Cor | Sag | |
ve | 29.3 | 28.0 | 28.0 | 16.7 | 33.3 | 11.1 |
vp | 24.0 | 18.7 | 24.0 | 33.3 | 38.9 | 38.9 |
FP | 53.3 | 60.0 | 57.3 | 44.4 | 50.0 | 38.9 |
PS | 13.3 | 18.7 | 26.7 | 38.9 | 38.9 | 50.0 |
τi | 33.3 | 32.0 | 33.3 | 55.6 | 72.2 | 66.7 |
Ktrans | 16.0 | 62.7 | 62.7 | 33.3 | 44.4 | 44.4 |
T1-w | 48.0 | 10.7 | 58.7 | 55.6 | 38.9 | 61.1 |
Total | 31.0 | 33.0 | 41.5 | 39.7 | 45.2 | 44.4 |
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Kiser, K.; Zhang, J.; Kim, S.G. Textural Features of Mouse Glioma Models Measured by Dynamic Contrast-Enhanced MR Images with 3D Isotropic Resolution. Tomography 2023, 9, 721-735. https://doi.org/10.3390/tomography9020058
Kiser K, Zhang J, Kim SG. Textural Features of Mouse Glioma Models Measured by Dynamic Contrast-Enhanced MR Images with 3D Isotropic Resolution. Tomography. 2023; 9(2):721-735. https://doi.org/10.3390/tomography9020058
Chicago/Turabian StyleKiser, Karl, Jin Zhang, and Sungheon Gene Kim. 2023. "Textural Features of Mouse Glioma Models Measured by Dynamic Contrast-Enhanced MR Images with 3D Isotropic Resolution" Tomography 9, no. 2: 721-735. https://doi.org/10.3390/tomography9020058
APA StyleKiser, K., Zhang, J., & Kim, S. G. (2023). Textural Features of Mouse Glioma Models Measured by Dynamic Contrast-Enhanced MR Images with 3D Isotropic Resolution. Tomography, 9(2), 721-735. https://doi.org/10.3390/tomography9020058