Space Radiation and Cancer Risk in Astronauts: Models, Evidence, Uncertainties, and Emerging Imaging Perspectives.

Chiara Zanon, Michele Basilicata, Agostino Chiaravalloti, Nicola Giannotti, Amalia Lupi, Filippo Crimì, Emilio Quaia

Abstract readReview

In one paragraph

Review in Tomography (Ann Arbor, Mich.), 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

7 authors.

Chiara ZanonDepartment of Radiology, University of Padova, Via Giustiniani 2, 35128 Padova, Italy.ORCID 0000-0002-7917-5027

Michele BasilicataRadiology Department, UniCamillus-Saint Camillus International University of Health Sciences, 00131 Rome, Italy.

Agostino ChiaravallotiDepartment of Biomedicine and Prevention, University of Rome Tor Vergata, Viale Montpellier 1, 00133 Rome, Italy.ORCID 0000-0002-8017-8858

Nicola GiannottiFaculty of Medicine and Health, The University of Sydney, Sydney, NSW 2006, Australia.ORCID 0000-0003-4349-0401

Amalia LupiDepartment of Radiology, University of Padova, Via Giustiniani 2, 35128 Padova, Italy.ORCID 0000-0002-0743-9214

Filippo CrimìDepartment of Radiology, University of Padova, Via Giustiniani 2, 35128 Padova, Italy.ORCID 0000-0001-6822-1430

Emilio QuaiaDepartment of Radiology, University of Padova, Via Giustiniani 2, 35128 Padova, Italy.ORCID 0000-0003-2020-9365

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer risk estimation remains one of the main unresolved challenges in human spaceflight beyond low Earth orbit, where astronauts are exposed to galactic cosmic rays, solar particle events, and high-linear energy transfer (high-LET) secondary radiation. This narrative review summarizes the principal quantitative models used to estimate radiation-induced cancer risk in astronauts, including particle fluence-based cross-sections, mixture models, risk of exposure-induced death (REID)-based operational frameworks, uncertainty distribution approaches, and ensemble models. Early studies estimated 1-year excess cancer mortality at solar minimum as 1.3% in women and 1.1% in men under 10 g/cm

Indexed as

AstronautsCosmic RadiationNeoplasms, Radiation-InducedSpace FlightFemaleHumansMaleRisk AssessmentRisk FactorsUncertaintyastronautscancer risk estimationgalactic cosmic rayshigh-LET radiationimaging biomarkersquantitative imagingREIDspace radiation

Identifiers

PMID42506871

DOI10.3390/tomography12070106

PMCPMC13431405

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

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 OpenQuestion graph.