Evidence map›Paper›PMID 39570368›Full record

SynthesisEuropean radiology2025

Automatic patient centering in computed tomography: a systematic review and meta-analysis.

Yasser H Hadi, Lauren Keaney, Andrew England, Niamh Moore, Mark McEntee

Abstract readMeta-AnalysisSystematic Review
PubMed Publisher
In one paragraph

Synthesis in European radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
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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

5 authors.

Yasser H HadiDiscipline of Medical Imaging and Radiation Therapy, School of Medicine, University College Cork, Cork, Ireland. hadi.y@umail.ucc.ie.ORCID http://orcid.org/0000-0001-8570-1161
Lauren KeaneyDiscipline of Medical Imaging and Radiation Therapy, School of Medicine, University College Cork, Cork, Ireland.
Andrew EnglandDiscipline of Medical Imaging and Radiation Therapy, School of Medicine, University College Cork, Cork, Ireland.
Niamh MooreDiscipline of Medical Imaging and Radiation Therapy, School of Medicine, University College Cork, Cork, Ireland.
Mark McEnteeDiscipline of Medical Imaging and Radiation Therapy, School of Medicine, University College Cork, Cork, Ireland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo comprehensively examine the influence of auto-patient centering technologies on positioning accuracy, radiation dose, image quality, and time efficiency of computed tomography (CT) scans. MATERIALS AND

methodsA systematic search of peer-reviewed English publications was performed between January 2000 and November 2023 in PubMed, Embase, CINAHL, Scopus, and Web of Science. Two postgraduate students and an academic lecturer independently reviewed the articles to verify adherence to the inclusion criteria. The QUADAS-2 tool was employed to evaluate study quality. We derived summary estimates on positioning accuracy, radiation dose reduction, image quality, and time efficiency using proportion and meta-analysis methodologies.

resultsNine studies were identified comparing automatic and manual CT positioning. Automatic positioning improved accuracy by reducing vertical offsets to 7 mm and 4 mm for thorax and abdominal CTs, compared to 19 mm and 18 mm with manual methods. Most studies showed significant reductions in radiation dose, ranging from 5.71 to 31%. Image quality results were mixed, automatic methods generally produced images with less noise, but differences were minimal. Time efficiency was better, with automatic positioning reducing preparation time from 0.48 min versus 0.67 min for manual positioning.

conclusionsThis review confirms that automatic patient-centering technologies enhance positioning accuracy and decrease preparation times in CT scans. While reductions in radiation doses and some improvements in image quality were observed, the evidence remains mixed. Findings support integrating these technologies into clinical practice to optimize patient care. KEY POINTS: Question Does automatic patient centering in CT enhance positioning accuracy, reduce radiation exposure, and improve image quality? Findings Findings indicate that automatic centering can optimize image quality, reduce examination times and contribute to overall improvements in imaging efficiency. Clinical relevance Automatic patient centering in CT improves positioning accuracy, minimizes radiation exposure, enhances image quality, and accelerates imaging workflows, contributing to safer, more efficient imaging procedures that benefit patient care.

Indexed as

Patient PositioningTomography, X-Ray ComputedHumansRadiation DosageImage qualityPatient positioningRadiation dosageTime efficiencyTomography (X-ray computed)

Identifiers

What OpenQuestion holds

Textmetadata
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.