A Segmentation-based Automated Calculation of Patient Size and Size-specific Dose Estimates in Pediatric Computed Tomography Scans

Background and Purpose: Size-specific dose estimates (SSDE) have been introduced into computed tomography (CT) dosimetry to tailor patients' unique sizes to facilitate accurate CT radiation dose quantification and optimization. The purpose of this study was to develop and validate an automated...

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Bibliographic Details
Published in:Journal of medical physics Vol. 49; no. 3; pp. 456 - 463
Main Authors: Abdulkadir, Muhammad Kabir, Osman, Noor Diyana, Achuthan, Anusha, Nasirudin, Radin A., Ahmad, Muhammad Zabidi, Zain, Noor Hasyima Mat, Shuaib, Ibrahim Lutfi
Format: Journal Article
Language:English
Published: India Wolters Kluwer - Medknow 01.07.2024
Medknow Publications and Media Pvt. Ltd
Medknow Publications & Media Pvt. Ltd
Wolters Kluwer Medknow Publications
Edition:2
Subjects:
Agreements
algorithm
Algorithms
Automation
body size
Children
Computed tomography
computed tomography scan
Correlation coefficients
CT imaging
Diagnostic imaging
Error analysis
Estimates
Health aspects
Image processing
Image segmentation
Mechanization
Medical imaging
Medical Imaging Physics
Medical research
Medicine, Experimental
Original
Original Article
pediatric
Pediatrics
Radiation dosage
size-specific dose estimate
Software development
Thorax
Tomography
Malaysia
computed tomography scan
automation
image segmentation
radiation dosage
body size
Algorithm
size-specific dose estimate
pediatric
ISSN:0971-6203, 1998-3913
Online Access:Get full text
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Summary:Background and Purpose: Size-specific dose estimates (SSDE) have been introduced into computed tomography (CT) dosimetry to tailor patients' unique sizes to facilitate accurate CT radiation dose quantification and optimization. The purpose of this study was to develop and validate an automated algorithm for the determination of patient size (effective diameter) and SSDE. Materials and Methods: A MATLAB platform was used to develop software of algorithms based on image segmentation techniques to automate the calculation of patient size and SSDE. The algorithm was used to automatically estimate the individual size and SSDE of four CT dose index phantoms and 80 CT images of pediatric patients comprising head, thorax, and abdomen scans. For validation, the American Association of Physicists in Medicine (AAPM) manual methods were used to determine the patient's size and SSDE for the same subjects. The accuracy of the proposed algorithm in size and SSDE calculation was evaluated for agreement with the AAPM's estimations (manual) using Bland-Altman's agreement and Pearson's correlation coefficient. The normalized error, system bias, and limits of agreement (LOA) between methods were derived. Results: The results demonstrated good agreement and accuracy between the automated and AAPM's patient size estimations with an error rate of 1.9% and 0.27% on the patient and phantoms study, respectively. A 1% percentage difference was found between the automated and manual (AAPM) SSDE estimates. A strong degree of correlation was seen with a narrow LOA between methods for clinical study (r > 0.9771) and phantom study (r > 0.9999). Conclusion: The proposed automated algorithm provides an accurate estimation of patient size and SSDE with negligible error after validation.
Bibliography:Address for correspondence: Dr. Muhammad Kabir Abdulkadir, Department of Radiography, Faculty of Basic Clinical Sciences, University of Ilorin, Ilorin 240213, Nigeria. Advanced Medical and Dental Institute, Universiti Sains Malaysia, Bertam, Penang 13200, Malaysia. E-mail: kabirkad@yahoo.com
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ISSN:0971-6203
1998-3913
DOI:10.4103/jmp.jmp_26_24