Document Type : Original Research
Authors
- Marziyeh Mirzaeiyan 1
- Simin Hemati 2
- Ali Akhavan 2
- Mahnaz Etehadtavakol 1
- Zahra Sharifonnasabi 3
- Alireza mouheidari 4
- Atoosa Adibi 5
- Hossein Khanahmad 6
- Parvaneh Shokrani 1
1 Department of Medical Physics, Faculty of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
2 Department of Radiotherapy Oncology, Faculty of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
3 Department of Statistics, University of Isfahan, Isfahan, Iran
4 Department of Radiation Oncology, Isfahan Milad Hospital, Isfahan, Iran
5 Department of Radiology, Faculty of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
6 Department of Genetics and Molecular Biology, Faculty of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
Abstract
Background: Dosiomics involves converting 3D dose distribution matrices into quantifiable data for analysis. Evaluating the stability of dosiomics features against different prescribed doses is essential before utilizing them for treatment plan assessment.
Objective: The current study aimed to investigate dosiomics features variability resulting from different prescribed doses in 3D conformal radiotherapy treatment plans of prostate cancer patients.
Material and Methods: This retrospective cross-sectional study is conducted based on data from ten prostate cancer patients, and their dose matrices were analyzed to extract features. The stability of dosiomics features was evaluated using the Coefficient of Variation (CV).
Results: For each patient, 372 features were extracted for each of the five selected regions of interest. Features with a CV>0.25 have been considered with higher variability. Among the Gray Level Size Zone Matrix group, the Planning Target Volume (PTV) exhibited the highest CV value. Overall, 71% of the features had a CV<0.1, while 5.9% of those had a CV>0.25. Less than 2% of the features had a CV>0.5, and only less than 1% had a CV>1. Features with a CV>0.25 were as follows: 33 features in PTV, 60 features in PTV-All, 63 features in PTV-Lymph Node, 65 features in the rectum, and 54 features in the bladder.
Conclusion: The prescribed dose significantly influences the variability of dosiomics features during extraction. Understanding these changes is essential for the optimal application of dosiomics in treatment planning for cancer.
Keywords
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