Evidence map›Paper›PMID 42210283›Full record

ArticleRadiation oncology (London, England)2026

Improving workflow efficiency during prostate stereotactic body radiotherapy using real-time adaptive planning associated with reduced intra-fractional target motion.

Ting Chen, David Barbee, Hesheng Wang, Siming Lu, Sangkyu Lee, Ruth Afanador, Stavroula Kolitsopoulos, Matthew Long, Allison McCarthy, Paulina Galavis and 2 more

Abstract read
In one paragraph

Article in Radiation oncology (London, England), 2026. 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. Article
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.

Ting ChenDepartment of Radiation Oncology, Perlmutter Cancer Center, NYU Langone Health, New York, NY, USA.
David BarbeeDepartment of Radiation Oncology, Perlmutter Cancer Center, NYU Langone Health, New York, NY, USA.
Hesheng WangDepartment of Radiation Oncology, Perlmutter Cancer Center, NYU Langone Health, New York, NY, USA.
Siming LuDepartment of Radiation Oncology, Perlmutter Cancer Center, NYU Langone Health, New York, NY, USA.
Sangkyu LeeDepartment of Radiation Oncology, Perlmutter Cancer Center, NYU Langone Health, New York, NY, USA.
Ruth AfanadorDepartment of Radiation Oncology, Perlmutter Cancer Center, NYU Langone Health, New York, NY, USA.
Stavroula KolitsopoulosDepartment of Radiation Oncology, Perlmutter Cancer Center, NYU Langone Health, New York, NY, USA.
Matthew LongDepartment of Radiation Oncology, Perlmutter Cancer Center, NYU Langone Health, New York, NY, USA.
Allison McCarthyDepartment of Radiation Oncology, Perlmutter Cancer Center, NYU Langone Health, New York, NY, USA.
Paulina GalavisDepartment of Radiation Oncology, Perlmutter Cancer Center, NYU Langone Health, New York, NY, USA.
Peter SchiffDepartment of Radiation Oncology, Perlmutter Cancer Center, NYU Langone Health, New York, NY, USA.
Michael J ZelefskyDepartment of Radiation Oncology, Perlmutter Cancer Center, NYU Langone Health, New York, NY, USA. Michael.Zelefsky@nyulangone.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMagnetic resonance (MR) imaging-linear accelerator-based real-time adaptive planning for delivering ultra-hypofractionated stereotactic body radiotherapy (SBRT) has advanced clinical accuracy yet added complexity to the radiotherapy workflow. We retrospectively evaluated whether the addition of a Parallel Automated Contouring module with Enhancement of AI (PACE-AI) reduced contouring time and overall SBRT duration, and its impact on intra-fractional target motion.

methodsThis study included 250 fractions from 90 prostate cancer patients from which fraction time were tracked. All patients received definitive SBRT to the prostate on the 1.5-Tesla Unity (Elekta©) system, through the Adapt-To-Shape (ATS) workflow, which required real-time re-contouring of the normal tissues by the dosimetrists and target contouring by the physician for each of the fractions. We compared the fraction durations for 125 consecutive fractions treated with the incorporation of PACE-AI with 125 fractions previously treated without PACE-AI to determine whether PACE-AI improved efficiency and reduced treatment session duration.

resultsFor the cohort treated without PACE-AI, the overall median duration was 67.6 min, including 23.9 min contouring time. With the incorporation of PACE-AI, the overall median duration was 51.2 min, representing a 24.3% reduction. The average contouring time was reduced by 55% to 10.8 min. In addition, the extent of positional shifts prior to beam delivery was significantly reduced from an average of 1.8 mm to 1.3 mm (p < 0.001) in both superior/inferior (range reduced from 0 to 6.3 mm to 0-4.2 mm) and anterior/posterior directions (range reduced from 0 to 6.6 mm to 0-5.0 mm).

conclusionsThe incorporation of PACE-AI improved workflow efficiency during SBRT. The reduction in treatment duration also helped reduce organ motion during real-time adaptive planning.

Indexed as

Prostatic NeoplasmsRadiosurgeryRadiotherapy Planning, Computer-AssistedWorkflowAgedHumansMagnetic Resonance ImagingMaleMotionOrgans at RiskRadiotherapy DosageRadiotherapy, Intensity-ModulatedRetrospective StudiesAdaptive-planningProstate cancerRadiotherapyStereotactic

Identifiers

PMID42210283
PMCPMC13403397

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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.