Development of a novel automated algorithm for patient dosimetry in computed tomography: a step towards the facilitation of size-specific dose estimates and organs dosimetry estimations in a busy clinical workflow

Abstract Accurate dosimetry in computed tomography (CT) is essential for patient safety and effective radiation management. This study presents the development of an automated algorithm designed to enhance patient dosimetry by facilitating size-specific dose estimates (SSDE) and organ dose estimations. Utilizing a Python-based script, the proposed method integrates advanced image preprocessing, contour detection, and mathematical calculations to quantify key metrics from CT images. This automated approach addresses the limitations of manual measurement techniques. A retrospective analysis was conducted on CT axial images from examinations acquired with an 80-detector scanner. The algorithm processes DICOM images, converts pixel values to Hounsfield Units, applies Gaussian smoothing, windowing, and thresholding, followed by morphological operations to refine segmentation. It measures the water equivalent diameter (Dw) and estimates both region SSDE and organ doses, incorporating tissue attenuation. Validation was performed using an adult anthropomorphic ATOM phantom, with organ doses measured by optically stimulated luminescence dosimeters. The results demonstrated the algorithm’s potential in estimating SSDE and organ doses. Validation of the automated method revealed strong correlations for Dw and SSDE between the proposed method and manual measurements of five expert reviewers ranging from 0.86 to 0.99 for determination coefficient. Comparative analysis of organ doses showed close agreement between results from experimental setup against the proposed algorithm. The automated algorithm estimated brain dose with a mean of 21.8 mGy, while measurements from the ATOM phantom and CT Expo indicated 19.74 mGy and 23.05 mGy, respectively. For lung doses, the automated algorithm estimated 12.5 mGy compared to 11.0 mGy from the ATOM phantom and 13.1 mGy from CT Expo. Liver doses were measured at 12.7 mGy by the automated method, versus 12.1 mGy from the ATOM phantom and 11.1 mGy from CT Expo. This study shows the potential of automated image analysis techniques in enhancing dosimetry accuracy in CT examinations.

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Publication Details

Journal
Physica Scripta
Published
2024-10-25
DOI
https://doi.org/10.1088/1402-4896/ad8b86
Citations
10
Primary Topic
Radiation Dose and Imaging
Type
article
Field-Weighted Citation Impact
4.04
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article

Development of a novel automated algorithm for patient dosimetry in computed tomography: a step towards the facilitation of size-specific dose estimates and organs dosimetry estimations in a busy clinical workflow

Zakaria Tahiri, Imane Rhouch, Mohammed Talbi, H. Sekkat et al.
10 citations
Physica Scripta
Radiation Dose and Imaging
4.04
article

Development of a novel automated algorithm for patient dosimetry in computed tomography: a step towards the facilitation of size-specific dose estimates and organs dosimetry estimations in a busy clinical workflow

Zakaria Tahiri, Imane Rhouch, Mohammed Talbi, H. Sekkat, A. Khallouqi, Youssef Madkouri, Omar El Rhazouani, W. El Atifi, Abdellah Halimi
article en
10 citations

Abstract

Abstract Accurate dosimetry in computed tomography (CT) is essential for patient safety and effective radiation management. This study presents the development of an automated algorithm designed to enhance patient dosimetry by facilitating size-specific dose estimates (SSDE) and organ dose estimations. Utilizing a Python-based script, the proposed method integrates advanced image preprocessing, contour detection, and mathematical calculations to quantify key metrics from CT images. This automated approach addresses the limitations of manual measurement techniques. A retrospective analysis was conducted on CT axial images from examinations acquired with an 80-detector scanner. The algorithm processes DICOM images, converts pixel values to Hounsfield Units, applies Gaussian smoothing, windowing, and thresholding, followed by morphological operations to refine segmentation. It measures the water equivalent diameter (Dw) and estimates both region SSDE and organ doses, incorporating tissue attenuation. Validation was performed using an adult anthropomorphic ATOM phantom, with organ doses measured by optically stimulated luminescence dosimeters. The results demonstrated the algorithm’s potential in estimating SSDE and organ doses. Validation of the automated method revealed strong correlations for Dw and SSDE between the proposed method and manual measurements of five expert reviewers ranging from 0.86 to 0.99 for determination coefficient. Comparative analysis of organ doses showed close agreement between results from experimental setup against the proposed algorithm. The automated algorithm estimated brain dose with a mean of 21.8 mGy, while measurements from the ATOM phantom and CT Expo indicated 19.74 mGy and 23.05 mGy, respectively. For lung doses, the automated algorithm estimated 12.5 mGy compared to 11.0 mGy from the ATOM phantom and 13.1 mGy from CT Expo. Liver doses were measured at 12.7 mGy by the automated method, versus 12.1 mGy from the ATOM phantom and 11.1 mGy from CT Expo. This study shows the potential of automated image analysis techniques in enhancing dosimetry accuracy in CT examinations.

Physica ScriptaVol. 99(12)
Abdelmalek Essaâdi University (MA), Université Ibn-Tofail (MA), Instituts Supérieurs des Professions Infirmières et Techniques de Santé (MA), Centre Hospitalier Universitaire Ibn Rochd (MA), Université Hassan 1er (MA), Hassania School of Public Works (MA), University of Hassan II Casablanca (MA)
Openalex Percentile: Top 6%
Radiation Dose and Imaging
4.04
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