TY - JOUR ID - 20002 TI - Radiomics in IOERT of Unilateral Breast Cancer as a Biological Dosimetry JO - Iranian Journal of Medical Physics JA - IJMP LA - en SN - AU - Bagherpour, Zahra AU - Enferadi, Milad AU - Reiazi, Reza AU - Jajroudi, Mahdie AU - Nafissi, Nahid AU - Mahdavi, Seied Rabi AD - Department of Medical Physics, School of Medicine, Iran University of Medical Sciences, Tehran, Iran AD - Department of Radiology, Mayo Clinic, 4500 San Pablo Rd, Jacksonville, FL 32224, USA AD - Department of Radiation Physics, Division of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA AD - Pharmaceutical Research Center, Mashhad University of Medical Sciences, Mashhad, Iran AD - Department of General Surgery, School of Medicine, Iran University of Medical Sciences, Tehran, Iran AD - Radiation Biology Research Center, Iran University of Medical Sciences, Tehran, Iran Y1 - 2022 PY - 2022 VL - 19 IS - 6 SP - 322 EP - 328 KW - Radiomics KW - Breast Cancer KW - IOERT KW - CT Scan KW - Dosimetry DO - 10.22038/ijmp.2022.61659.2040 N2 - Introduction: In this study, Radiomic features analysis of CT scan images of the irradiated breast compared to the contralateral breast after a 12 Gy boost radiation dose in IOERT was conducted to obtain radiation-sensitive indicators (parameters) biological markers or biological dosimeters.Material and Methods: 35 contrast chest CT scans (with unilateral ductal carcinoma in situ (DCIS) who had undergone boost IOERT) were used in this study. The total number of 259 CT radiomic features (first-order, textural, gradient, and autoregressive model-based features) were extracted using Mazda software. The features that were significantly different in the two breasts were selected. A score was assigned to each of the features and the highest scores were characterized (according to the level of significant differences). The feature selection process was performed using the hybrid feature selection method.Results: CT Texture analysis indicated that radiation dose causes significant changes in some radiomic features of the breast tissue. Conclusion: With more research in the future, we can fit the Delta-Radiomics values with the received radiation dose and achieve a biological dosimeter to detect low-dose radiation. UR - https://ijmp.mums.ac.ir/article_20002.html L1 - https://ijmp.mums.ac.ir/article_20002_4a3fd5688252d25fcbe76909c157f568.pdf ER -