Evidence map›Paper›PMID 40873456›Full record

ArticleRadiation physics and chemistry (Oxford, England : 1993)2025

Patient-specific organ dose calculation using automatic segmentation and extension of CT scans.

Sergio Morató, Belén Juste, Rafael Miró, Agustín Santos, Andreu Badal, Choonsik Lee, Gumersindo Verdú, Matthew M Mille

Abstract read
In one paragraph

Article in Radiation physics and chemistry (Oxford, England : 1993), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Sergio MoratóDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD 20850, USA.
Belén JusteInstitute for Industrial, Radiophysical and Environmental Safety (ISIRYM), Universitat Politècnica de València, Valencia, ES.
Rafael MiróInstitute for Industrial, Radiophysical and Environmental Safety (ISIRYM), Universitat Politècnica de València, Valencia, ES.
Agustín SantosRadiophysics Service, Provincial Hospital Consortium of Castellón, Castellón, ES.
Andreu BadalCenter for Devices and Radiological Health, Office of Science and Engineering Labs, Division of Imaging, Diagnostics, and Software Reliability, U.S. Food and Drug Administration, Silver Spring, MD, USA.
Choonsik LeeDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD 20850, USA.
Gumersindo VerdúInstitute for Industrial, Radiophysical and Environmental Safety (ISIRYM), Universitat Politècnica de València, Valencia, ES.
Matthew M MilleDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD 20850, USA.

Funding

Intramural NIH HHS Z99 CA999999
6 · The paper itself

Abstract

The primary objective of this study is to develop a fast and automated methodology for calculating personalized radiation organ dose from computed tomography (CT) scans using anatomical models derived from the CT images of the patient obtained during the imaging procedure. To validate this method, a comparison was conducted between experimentally measured dose values in a CT scan and those obtained through Monte Carlo simulation. Multiple point dose measurements were taken within a RANDO phantom during a Siemens Somatom Emotion CT scan, employing Metal Oxide Semiconductor Field Effect Transistor dosimeters. The software tools described in this work facilitate automatic Monte Carlo simulations using DICOM metadata and images from patient CT scans. A personalized patient-specific 3D voxelized model was created based on the DICOM images, and the radiation dose was estimated using the MC-GPU Monte Carlo code, which supports parallelization on a GPU. The required inputs for the simulations were automatically extracted from the DICOM data. Additionally, this study outlines the procedure for calculating the dose in actual patients (where the scans only cover a fraction of the body) and presents a comparison of the results with NCICT dose calculator, which uses a library of computational phantoms. A previously developed anatomical extension technique was applied to realistically extend the partially captured patient anatomy. Without this technique, the mean dose to organs that are only partially included in the CT scan is likely overestimated. Furthermore, a realistic case that uses a complete CT scan anatomy considering 134 anatomical structures or organs is presented. The results demonstrate a consistent trend when comparing simulated and experimental values, with a median difference of 5.7%. When comparing the simulated results with NCICT estimations, we observe similar magnitudes of values overall. However, significant dose differences up to 51% are noted for some organs, underscoring the importance of personalizing the dose calculation.

Indexed as

Anatomical Predictive ExtensionComputed TomographyDosimetryMC-GPUMonte Carlo

Identifiers

PMID40873456
PMCPMC12379956

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