Evidence map›Paper›PMID 39310635›Full record

ReviewCureus2024

Techniques and Strategies to Minimize Radiation Exposure in Pediatric Computed Tomography (CT) Abdominal Examinations: A Review.

Inayatullah Shah Sayed, Muhammad Irfan Mohd Yusof

Abstract readReview
In one paragraph

Review in Cureus, 2024. 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. Review
  2. Article
  3. Article
  4. Article
  5. 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

2 authors.

Inayatullah Shah SayedDepartment of Diagnostic Imaging and Radiotherapy, Kulliyyah of Allied Health Sciences, International Islamic University Malaysia, Kuantan, MYS.
Muhammad Irfan Mohd YusofDepartment of Diagnostic Imaging and Radiotherapy, Kulliyyah of Allied Health Sciences, International Islamic University Malaysia, Kuantan, MYS.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As children are more vulnerable to radiation-induced cancers and have longer life expectancies, it is essential to implement strict radiation protection measures in pediatric imaging. This study aimed to review radiation dose-minimizing measures in pediatric abdominal computed tomography (CT) examinations. A systematic search across various databases, including Web of Science, PubMed, SpringerLink, ScienceDirect, and Google Scholar, yielded a total of 7,314 articles. The search used keywords that aligned with the objectives of the study. This study included 77 publications after applying the criteria for inclusion and exclusion. We carefully reviewed these selected articles for compliance with the inclusion criteria and excluded them if they did not meet the specified criteria. Only 12 articles fulfilled the strict criteria. An in-depth review of 12 selected articles demonstrated the radiation dose reduction techniques and strategies, which include prefiltering and post-processing algorithms, careful adjustment of exposure parameters such as tube voltage (kVp) and current (mAs), and the establishment of diagnostic reference levels (DRL). Reduction of radiation exposure in pediatric CT imaging demands multifaceted approaches. To reduce the ionizing radiation dose while still obtaining high-quality diagnostic images, healthcare practitioners should adhere to DRL, adjust exposure factors, implement prefiltration, employ AI, and use post-processing algorithms.

Indexed as

abdominal ctalarapediatricradiation-induced malignanciesradiation protection

Identifiers

PMID39310635
PMCPMC11416189

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.