Cargando…

Real-time fully automated dosimetric computation for CT images in the clinical workflow: A feasibility study

BACKGROUND: Currently, the volume computed tomography dose index (CTDI(vol)), the most-used quantity to express the output dose of a computed tomography (CT) patient’s dose, is not related to the real size and attenuation properties of each patient. The size-specific dose estimates (SSDE), based on...

Descripción completa

Detalles Bibliográficos
Autores principales: Porzio, Massimiliano, Anam, Choirul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9403986/
https://www.ncbi.nlm.nih.gov/pubmed/36033538
http://dx.doi.org/10.3389/fonc.2022.798460
_version_ 1784773505153236992
author Porzio, Massimiliano
Anam, Choirul
author_facet Porzio, Massimiliano
Anam, Choirul
author_sort Porzio, Massimiliano
collection PubMed
description BACKGROUND: Currently, the volume computed tomography dose index (CTDI(vol)), the most-used quantity to express the output dose of a computed tomography (CT) patient’s dose, is not related to the real size and attenuation properties of each patient. The size-specific dose estimates (SSDE), based on the water-equivalent diameter (D (W)) overcome those issues. The proposed methods found in the literature do not allow real-time computation of D (W) and SSDE. PURPOSE: This study aims to develop a software to compute D (W) and SSDE in a real-time clinical workflow. METHOD: In total, 430 CT studies and scans of a water-filled funnel phantom were used to compute accuracy and evaluate the times required to compute the D (W) and SSDE. Two one-sided tests (TOST) equivalence test, Bland–Altman analysis, and bootstrap-based confidence interval estimations were used to evaluate the differences between actual diameter and D (W) computed automatically and between D (W) computed automatically and manually. RESULTS: The mean difference between the D (W) computed automatically and the actual water diameter for each slice is −0.027% with a TOST confidence interval equal to [−0.087%, 0.033%]. Bland–Altman bias is −0.009% [−0.016%, −0.001%] with lower limits of agreement (LoA) equal to −0.0010 [−0.094%, −0.068%] and upper LoA equal to 0.064% [0.051%, 0.077%]. The mean difference between D (W) computed automatically and manually is −0.014% with a TOST confidence interval equal to [−0.056%, 0.028%] on phantom and 0.41% with a TOST confidence interval equal to [0.358%, 0.462%] on real patients. The mean time to process a single image is 13.99 ms [13.69 ms, 14.30 ms], and the mean time to process an entire study is 11.5 s [10.62 s, 12.63 s]. CONCLUSION: The system shows that it is possible to have highly accurate D (W) and SSDE in almost real-time without affecting the clinical workflow of CT examinations.
format Online
Article
Text
id pubmed-9403986
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-94039862022-08-26 Real-time fully automated dosimetric computation for CT images in the clinical workflow: A feasibility study Porzio, Massimiliano Anam, Choirul Front Oncol Oncology BACKGROUND: Currently, the volume computed tomography dose index (CTDI(vol)), the most-used quantity to express the output dose of a computed tomography (CT) patient’s dose, is not related to the real size and attenuation properties of each patient. The size-specific dose estimates (SSDE), based on the water-equivalent diameter (D (W)) overcome those issues. The proposed methods found in the literature do not allow real-time computation of D (W) and SSDE. PURPOSE: This study aims to develop a software to compute D (W) and SSDE in a real-time clinical workflow. METHOD: In total, 430 CT studies and scans of a water-filled funnel phantom were used to compute accuracy and evaluate the times required to compute the D (W) and SSDE. Two one-sided tests (TOST) equivalence test, Bland–Altman analysis, and bootstrap-based confidence interval estimations were used to evaluate the differences between actual diameter and D (W) computed automatically and between D (W) computed automatically and manually. RESULTS: The mean difference between the D (W) computed automatically and the actual water diameter for each slice is −0.027% with a TOST confidence interval equal to [−0.087%, 0.033%]. Bland–Altman bias is −0.009% [−0.016%, −0.001%] with lower limits of agreement (LoA) equal to −0.0010 [−0.094%, −0.068%] and upper LoA equal to 0.064% [0.051%, 0.077%]. The mean difference between D (W) computed automatically and manually is −0.014% with a TOST confidence interval equal to [−0.056%, 0.028%] on phantom and 0.41% with a TOST confidence interval equal to [0.358%, 0.462%] on real patients. The mean time to process a single image is 13.99 ms [13.69 ms, 14.30 ms], and the mean time to process an entire study is 11.5 s [10.62 s, 12.63 s]. CONCLUSION: The system shows that it is possible to have highly accurate D (W) and SSDE in almost real-time without affecting the clinical workflow of CT examinations. Frontiers Media S.A. 2022-08-11 /pmc/articles/PMC9403986/ /pubmed/36033538 http://dx.doi.org/10.3389/fonc.2022.798460 Text en Copyright © 2022 Porzio and Anam https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Porzio, Massimiliano
Anam, Choirul
Real-time fully automated dosimetric computation for CT images in the clinical workflow: A feasibility study
title Real-time fully automated dosimetric computation for CT images in the clinical workflow: A feasibility study
title_full Real-time fully automated dosimetric computation for CT images in the clinical workflow: A feasibility study
title_fullStr Real-time fully automated dosimetric computation for CT images in the clinical workflow: A feasibility study
title_full_unstemmed Real-time fully automated dosimetric computation for CT images in the clinical workflow: A feasibility study
title_short Real-time fully automated dosimetric computation for CT images in the clinical workflow: A feasibility study
title_sort real-time fully automated dosimetric computation for ct images in the clinical workflow: a feasibility study
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9403986/
https://www.ncbi.nlm.nih.gov/pubmed/36033538
http://dx.doi.org/10.3389/fonc.2022.798460
work_keys_str_mv AT porziomassimiliano realtimefullyautomateddosimetriccomputationforctimagesintheclinicalworkflowafeasibilitystudy
AT anamchoirul realtimefullyautomateddosimetriccomputationforctimagesintheclinicalworkflowafeasibilitystudy