Evidence map›Paper›PMID 41474339›Full record

ArticleHealth physics2026

Statistical Uncertainty of Inhalation Dose Coefficients: Impact of Particle Deposition in ICRP 66 Human Respiratory Tract Model.

D Margot, E M Mate-Kole, L D Cochran, C Jelsema, M Graffigna, L Buchbinder Shadur, A Kalinowski, S A Dewji

Abstract read
In one paragraph

Article in Health physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

D MargotNuclear and Radiological Engineering and Medical Physics Programs, Georgia Institute of Technology, 770 State Street NW, Atlanta, GA, 30332-0405.
E M Mate-KoleNuclear and Radiological Engineering and Medical Physics Programs, Georgia Institute of Technology, 770 State Street NW, Atlanta, GA, 30332-0405.
L D CochranSandia National Laboratories, P.O. Box 5800, Albuquerque, NM 87185-0791, United States.
C JelsemaSandia National Laboratories, P.O. Box 5800, Albuquerque, NM 87185-0791, United States.
M GraffignaNuclear and Radiological Engineering and Medical Physics Programs, Georgia Institute of Technology, 770 State Street NW, Atlanta, GA, 30332-0405.
L Buchbinder ShadurNuclear and Radiological Engineering and Medical Physics Programs, Georgia Institute of Technology, 770 State Street NW, Atlanta, GA, 30332-0405.
A KalinowskiSandia National Laboratories, P.O. Box 5800, Albuquerque, NM 87185-0791, United States.
S A DewjiNuclear and Radiological Engineering and Medical Physics Programs, Georgia Institute of Technology, 770 State Street NW, Atlanta, GA, 30332-0405.

Funding

Project 4: Post-Exposure Biomarkers and Remediation of Radionuclide ContaminantsP01AI165380 · NIAID · NORTHWESTERN UNIVERSITY AT CHICAGO · PI WESLEY E BOLCH · 2022 to 2026
$12.9M
DOD W81XWH-21-1-0984NIAID NIH HHS P01 AI165380US Department of Energy SNL21-CM-420US NRC AWARD 31310023M0043
6 · The paper itself

Abstract

Inhaled radioactive materials can pose a long-term health concern, as the material can be incorporated into the body's metabolic pathways and remain in organs and tissues for extended durations. During the retention period, the radioactive material may localize in a source organ and irradiate adjacent target organs and tissues. Distribution of these materials changes over time, requiring biokinetic modeling to evaluate their movement through various tissues and organs. The evolving distribution depends on multiple inputs characterizing the inhaled material, such as particle size and size distribution, particle density, aspect ratio, specific radionuclide, the chemical form, and solubility. In addition, biological parameters such as breathing rate, breathing type (nasal or nasal/oral), respiratory system morphometry, tidal volume, functional residual capacity, and anatomical dead space all influence material transport. These aerosol properties and physiological characteristics of the respiratory tract jointly define a range of initial conditions that influence the time-dependent distribution of radioactive material. To evaluate both uncertainty in the initial conditions of inhalation exposure and the final output (committed effective dose) from biokinetic models, a Python-based software tool, Radiological Exposure Dose Calculator (REDCAL), was developed to propagate uncertainty within the human respiratory tract model. Focusing on deposition fraction uncertainty, the primary objective was to characterize the initial activity distribution across respiratory regions as a function of anticipated particle sizes and distributions. The impact of the deposition fraction uncertainty was propagated to committed effective dose coefficients for selected radionuclides in a companion publication. For each particle size, a lognormal distribution, characterized by its geometric mean as defined within ICRP Publication 66, serves as the basis for introducing uncertainty into the physical processes governing deposition in various lung regions. This study addresses the deposition process and examines how uncertainty in deposition mechanisms affects activity distribution in the airways, ultimately presenting the expected range and standard deviation of deposited activity as a function of particle size.

Indexed as

Air Pollutants, RadioactiveInhalation ExposureModels, BiologicalRespiratory SystemAerosolsHumansParticle SizeRadiation DosageUncertaintyAerosolsAir Pollutants, Radioactiveexposurehuman organsinhalationInternational Commission on Radiological Protection (ICRP)radiation

Identifiers

PMID41474339
PMCPMC13353032

What Socratic holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.