Evidence map›Paper›PMID 40025651›Full record

ArticleJournal of applied clinical medical physics2025

Evaluating auto-contouring accuracy in reduced CT dose images for radiopharmaceutical therapies: Denoising and evaluation of

Hung-Te Yang, Kuan-Yin Ko, Ching-Ching Yang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of applied clinical medical physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. The Role of Artificial Intelligence in Theranostics.Journal of nuclear medicine technology · 2025
    Review
  2. 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

3 authors.

Hung-Te YangDepartment of Radiation Oncology, Kaohsiung Municipal Siaogang Hospital, Kaohsiung, Taiwan.
Kuan-Yin KoDepartment of Nuclear Medicine, National Taiwan University Cancer Center, Taipei, Taiwan.
Ching-Ching YangDepartment of Medical Imaging and Radiological Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan.

Funding

Imaging and Dosimetry of Yttrium-90 for Personalized Cancer TreatmentR01EB022075 · NIBIB · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI DEWARAJA, YUNI K · 2016 to 2023
$4.7M
Bringing Capacity for Theranostic Dosimetry Planning to the Nuclear Medicine ClinicR01CA240706 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI DEWARAJA, YUNI K · 2020 to 2024
$3.0M
National Science and Technology Council in Taiwan NSTC 114-2623-E-037-001-NUNational Science and Technology Council in Taiwan R01CA240706National Science and Technology Council in Taiwan R01EB022075NCI NIH HHS R01 CA240706NIBIB NIH HHS R01 EB022075
6 · The paper itself

Abstract

purposeReducing radiation dose attributed to computed tomography (CT) may compromise the accuracy of organ segmentation, an important step in

methodsThe

resultsBefore denoising, the mean ± standard deviation of PD

conclusionAs dose reduction increased, CT image segmentation gradually deteriorated, which in turn deteriorated the dosimetry accuracy of

Indexed as

Image Processing, Computer-AssistedOctreotideOrganometallic CompoundsRadiopharmaceuticalsRadiotherapy Planning, Computer-AssistedTomography, X-Ray ComputedAlgorithmsDeep LearningHumansOrgans at RiskRadiotherapy DosageRadiotherapy, Intensity-ModulatedSingle Photon Emission Computed Tomography Computed Tomographylutetium Lu 177 dotatateOctreotideOrganometallic CompoundsRadiopharmaceuticalsauto contouringCNN‐based denoisingLu‐177 DOTATATE therapy

Identifiers

PMID40025651
PMCPMC11969114

What OpenQuestion holds

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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.