Evidence map›Paper›PMID 39941897›Full record

ArticleCancers2025

A Retrospective Analysis of the First Clinical 5DCT Workflow.

Michael Lauria, Minji Kim, Dylan O'Connell, Yi Lao, Claudia R Miller, Louise Naumann, Peter Boyle, Ann Raldow, Alan Lee, Ricky R Savjani and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

12 authors.

Michael LauriaDepartment of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA 90095, USA.ORCID 0000-0003-1194-0148
Minji KimDepartment of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA 90095, USA.
Dylan O'ConnellDepartment of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA 90095, USA.
Yi LaoDepartment of Radiation Oncology, City of Hope, Duarte, CA 91010, USA.
Claudia R MillerDepartment of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA 90095, USA.ORCID 0000-0002-2556-7893
Louise NaumannDepartment of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA 90095, USA.
Peter BoyleDepartment of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA 90095, USA.ORCID 0000-0001-8513-2608
Ann RaldowDepartment of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA 90095, USA.
Alan LeeDepartment of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA 90095, USA.
Ricky R SavjaniDepartment of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA 90095, USA.ORCID 0000-0003-4763-2796
Drew MoghanakiDepartment of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA 90095, USA.
Daniel A LowDepartment of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA 90095, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectives5DCT was first proposed in 2005 as a motion-compensated CT simulation approach for radiotherapy treatment planning to avoid sorting artifacts that arise in 4DCT when patients breathe irregularly. Since March 2019, 5DCT has been clinically implemented for routine use at our institution to leverage this technological advantage. The clinical workflow includes a quality assurance report that describes the output of primary workflow steps. This study reports on the challenges and quality of the clinical 5DCT workflow using these quality assurance reports.

methodsWe evaluated all thoracic 5DCT simulation datasets consecutively acquired at our institution between March 2019 and December 2022 for thoracic radiotherapy treatment planning. The 5DCT datasets utilized motion models constructed from 25 fast-helical free-breathing computed tomography (FHFBCTs) with simultaneous respiratory bellows signal monitoring to reconstruct individual, user-specified breathing-phase images (termed 5DCT phase images) for internal target volume contouring. Each 5DCT dataset was accompanied by a structured quality assurance report composed of qualitative and quantitative measures of the breathing pattern, image quality, DIR quality, model fitting accuracy, and a validation process by which the original FHFBCT scans were regenerated with the 5DCT model. Measures of breathing irregularity, image quality, and DIR quality were retrospectively categorized on a grading scale from 1 (regular breathing and accurate registration/modeling) to 4 (irregular breathing and inaccurate registration/modeling). The validation process was graded according to the same scale, and this grade was termed the suitability-for-treatment-planning (STP) grade. We correlated the graded variables to the STP grade. In addition to the quality assurance reports, we reviewed the contour sessions to determine how often 5DCT phase images were used for treatment planning and delivery.

resultsThere were 169 5DCT simulation datasets available from 156 patients for analysis. The STP was moderately correlated with breathing irregularity, image quality, and DIR quality (Spearman coefficients: 0.26, 0.30, and 0.50, respectively). Multiple linear regression analysis demonstrated that STP was correlated with regular breathing patterns (

conclusionsThe strongest association with STP was with DIR quality grades, as indicated by both Spearman and multiple linear regression analysis, implying that improvements to DIR accuracy and evaluation may be the best route for further improvement to 5DCT. The high rate of 5DCT phase image use for treatment planning showed that the workflow was reliable, and this has encouraged us to continue to develop and improve the workflow steps.

Indexed as

4DCTimage-guided radiotherapylung radiotherapymodel-based CTmotion management

Identifiers

PMID39941897
PMCPMC11816223

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Registered trials

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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.