The Effect of Injected and Oral Computed Tomography Contrast Agent on Helical Tomotherapy Dose Calculating in Rectal Cancer

Purpose: This study aimed to evaluate the impact of Contrast-Enhanced Computed Tomography (CECT) on treatment planning for rectal cancer using Helical Tomotherapy (HT). Materials and Methods: A total of patients with known rectal tumors were included, and both CECT and non-CECT images were obtained. Patients adhered to a low-fat diet and received oral and intravenous iodine-based contrast agents. Target volumes, including Gross Tumor Volume (GTV), Clinical Target Volume (CTV), and Planning Target Volume (PTV), were delineated by a radiation oncologist using DICOM images. Intensity-Modulated Radiation Therapy (IMRT) techniques with Simultaneous Integrated Boost (SIB) methods were employed to optimize dose delivery while minimizing exposure to Organs at Risks (OARs). Results: The analysis revealed that the use of CECT significantly increased. Hounsfield Unit (HU) values across all structures, enhancing visibility and accuracy in target volume delineation. Dosimetric evaluations indicated minimal differences in dose distributions between CECT and non-CECT plans. However, certain indices such as Dmax, Dmin, Dmean, Homogeneity Index (HI), and Conformity Index (CI) showed significant changes that could influence clinical outcomes. Conclusion: The incorporation of CECT in radiation therapy planning for rectal cancer improves the delineation of critical structures, potentially leading to better treatment outcomes. The findings underscore the importance of using contrast media in enhancing imaging quality, which is crucial for effective target volume definition and OAR contouring. Future research should explore the long-term clinical implications of these findings on patient outcomes and quality of life post-treatment.

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Publication Details

Journal
Frontiers in biomedical technologies
Published
2025-03-19
DOI
https://doi.org/10.18502/fbt.v12i2.18288
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

The Effect of Injected and Oral Computed Tomography Contrast Agent on Helical Tomotherapy Dose Calculating in Rectal Cancer

Reza Eghdam-Zamiri, Mikaeil Molazadeh, Tohid Mortezazadeh, Niloofar Kargar et al.
Frontiers in biomedical technologies
Radiomics and Machine Learning in Medical Imaging
article

The Effect of Injected and Oral Computed Tomography Contrast Agent on Helical Tomotherapy Dose Calculating in Rectal Cancer

Reza Eghdam-Zamiri, Mikaeil Molazadeh, Tohid Mortezazadeh, Niloofar Kargar, Fatemeh Tabatabayi
article en

Abstract

Purpose: This study aimed to evaluate the impact of Contrast-Enhanced Computed Tomography (CECT) on treatment planning for rectal cancer using Helical Tomotherapy (HT). Materials and Methods: A total of patients with known rectal tumors were included, and both CECT and non-CECT images were obtained. Patients adhered to a low-fat diet and received oral and intravenous iodine-based contrast agents. Target volumes, including Gross Tumor Volume (GTV), Clinical Target Volume (CTV), and Planning Target Volume (PTV), were delineated by a radiation oncologist using DICOM images. Intensity-Modulated Radiation Therapy (IMRT) techniques with Simultaneous Integrated Boost (SIB) methods were employed to optimize dose delivery while minimizing exposure to Organs at Risks (OARs). Results: The analysis revealed that the use of CECT significantly increased. Hounsfield Unit (HU) values across all structures, enhancing visibility and accuracy in target volume delineation. Dosimetric evaluations indicated minimal differences in dose distributions between CECT and non-CECT plans. However, certain indices such as Dmax, Dmin, Dmean, Homogeneity Index (HI), and Conformity Index (CI) showed significant changes that could influence clinical outcomes. Conclusion: The incorporation of CECT in radiation therapy planning for rectal cancer improves the delineation of critical structures, potentially leading to better treatment outcomes. The findings underscore the importance of using contrast media in enhancing imaging quality, which is crucial for effective target volume definition and OAR contouring. Future research should explore the long-term clinical implications of these findings on patient outcomes and quality of life post-treatment.

Frontiers in biomedical technologies
Tabriz University of Medical Sciences (IR)
Openalex Percentile: Top 91%
Radiomics and Machine Learning in Medical Imaging
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