Evidence map›Paper›PMID 42415282›Full record

ArticleJournal of applied clinical medical physics2026

Geometric distortion in computed tomography scans for radiotherapy: Quantification and quality assurance implications.

Yunfei Hu, Emma Cai, John Shakeshaft, Marius Arnesen, Tina Gorjiara, Mikel Byrne, Tim Markwell, Ben Archidbald-Heeren

Abstract read
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Article in Journal of applied clinical medical 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.

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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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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.

Yunfei HuIcon Cancer Centre Gosford, Gosford, New South Wales, Australia.
Emma CaiIcon Cancer Centre Concord, Concord Repatriation General Hospital, Concord, New South Wales, Australia.
John ShakeshaftIcon Cancer Centre Gold Coast, Southport, Queensland, Australia.
Marius ArnesenIcon Cancer Centre Toowoomba, Rockville, Queensland, Australia.
Tina GorjiaraIcon Cancer Centre Norwest, Bella Vista, New South Wales, Australia.
Mikel ByrneIcon Cancer Centre, South Brisbane, Queensland, Australia.
Tim MarkwellIcon Cancer Centre Hobart, Hobart, Tasmania, Australia.
Ben Archidbald-HeerenIcon Cancer Centre, South Brisbane, Queensland, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundComputed tomography (CT) is widely assumed to be geometrically accurate and is commonly used as the reference standard for quantifying geometric distortion in other imaging modalities, particularly magnetic resonance imaging (MRI). However, geometric distortion in CT has not been comprehensively investigated. PURPOSE: The aim of this study was to characterize the performance of a distortion phantom, establish a reference scan and, on this basis, determine and quantify the presence of geometric distortion in CT scans used for radiotherapy (RT) planning.

methodsA CIRS Model 603A Distortion Phantom was employed to quantify geometric distortion. System reproducibility, as well as the effects of phantom setup, scan parameters, fabrication uncertainty, and temporal variation were systematically evaluated. Additionally, the geometric distortion of CT was compared to that of linac-based cone-beam CT (CBCT). Subsequently, geometric distortion magnitudes from eight CT scanners were retrospectively analyzed against both CBCT and a Computer Aided Design (CAD) model.

resultsCBCT demonstrated consistently smaller distortion variation compared with CT. Retrospective analysis revealed that all eight analyzed CT scanners exhibited measurable distortion magnitudes, with mean magnitudes ranging from 0.13 mm to 0.52 mm and maximum distortion magnitudes ranging from 0.45 mm to 1.09 mm when compared to CBCT, or 0.25 mm to 0.82 mm and 0.58 mm to 1.88 mm when compared to the CAD model. Longitudinal couch inaccuracy or non-linear couch sag may constitute the primary contributors to geometric distortion on CT scanners.

conclusionsContrary to common assumptions, CT scans used for radiotherapy planning exhibit measurable geometric distortion across clinically relevant fields of view (FoVs). However, current CT QA methodologies and tolerances may lack sufficient sensitivity to detect submillimeter distortion levels relevant to stereotactic radiotherapy (SRT). Recognition and rigorous quantification of CT geometric distortion are essential to inform risk assessment and margin design in high-precision RT.

Indexed as

Cone-Beam Computed TomographyImage Processing, Computer-AssistedPhantoms, ImagingQuality Assurance, Health CareRadiotherapy Planning, Computer-AssistedTomography, X-Ray ComputedHumansParticle AcceleratorsRadiotherapy DosageRadiotherapy, Intensity-ModulatedReproducibility of ResultsRetrospective StudiesCTgeometric distortionMRIstereotactic radiotherapy

Identifiers

PMID42415282
PMCPMC13341650

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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.