Evidence map›Paper›PMID 37218938›Full record

ArticleTomography (Ann Arbor, Mich.)2023

Radiation Dose Management in Computed Tomography: Introduction to the Practice at a Single Facility.

Yusuke Inoue

Abstract read
In one paragraph

Article in Tomography (Ann Arbor, Mich.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. A Multi-Centre Study:Saudi medical journal · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Assessment of radiographers' knowledge about radiation doses and DRLs in computed tomography departments in Jeddah, Saudi Arabia: A cross-sectional study.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2023
    Article
  8. 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

1 author.

Yusuke InoueDepartment of Diagnostic Radiology, Kitasato University School of Medicine, Sagamihara 252-0374, Japan.ORCID 0000-0001-7250-8303

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although the clinical benefits of computed tomography (CT) are undoubtedly high, radiation doses received by patients are also relatively high; therefore, radiation dose management is mandatory to optimize CT radiation doses and prevent excessive radiation events. This article describes CT dose management practice at a single facility. Many imaging protocols are used in CT depending on the clinical indications, scan region, and CT scanner; thus, managing the protocols is the first step for optimization. The appropriateness of the radiation dose for each protocol and scanner is verified, while answering whether the dose is the minimum to obtain diagnostic-quality images. Moreover, examinations with exceptionally high doses are identified, and the cause and clinical validity of the high dose are assessed. Daily imaging practice should follow standardized procedures, avoiding operator-dependent errors, and information required for radiation dose management should be recorded at each examination. The imaging protocols and procedures are reviewed for continuous improvement based on regular dose analysis and multidisciplinary team collaboration. The participation of many staff members in the dose management process is expected to contribute to promoting radiation safety through increased staff awareness.

Indexed as

Tomography, X-Ray ComputedHumansRadiation DosageTomography Scanners, X-Ray Computedcomputed tomographyexcessive dose eventimaging protocolradiation dose management

Identifiers

PMID37218938
PMCPMC10204378

What OpenQuestion holds

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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.