Evidence map›Paper›PMID 39040434›Full record

ReviewPhysics and imaging in radiation oncology2024

Data-driven gated positron emission tomography/computed tomography for radiotherapy.

Tinsu Pan, Dershan Luo

Abstract readReview
In one paragraph

Review in Physics and imaging in radiation oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Tinsu PanDepartment of Imaging Physics, M.D. Anderson Cancer Center, University of Texas, United States.
Dershan LuoDepartment of Radiation Physics, M.D. Anderson Cancer Center, University of Texas, United States.

Funding

Risk prediction and longitudinal assessment of cardiotoxicity and functional capacity trajectory in NSCLC patientsR01HL157273 · NHLBI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LIAO, ZHONGXING · 2021 to 2025
$3.8M
Reducing Bias in AI Algorithms for Gallium-68 PET: A Bioethical Perspective Using Transfer LearningR01EB034692 · NIBIB · UNIVERSITY OF FLORIDA · PI Kuang Gong · 2024 to 2026
$1.8M
NHLBI NIH HHS R01 HL157273NIBIB NIH HHS R01 EB034692
6 · The paper itself

Abstract

Purpose: Software-based data-driven gated (DDG) positron emission tomography/computed tomography (PET/CT) has replaced hardware-based 4D PET/CT. The purpose of this article was to review DDG PET/CT, which could improve the accuracy of treatment response assessment, tumor motion evaluation, and target tumor contouring with whole-body (WB) PET/CT for radiotherapy (RT). Material and methods: This review covered the topics of 4D PET/CT with hardware gating, advancements in PET instrumentation, DDG PET, DDG CT, and DDG PET/CT based on a systematic literature review. It included a discussion of the large axial field-of-view (AFOV) PET detector and a review of the clinical results of DDG PET and DDG PET/CT. Results: DDG PET matched or outperformed 4D PET with hardware gating. DDG CT was more compatible with DDG PET than 4D CT, which required hardware gating. DDG CT could replace 4D CT for RT. DDG PET and DDG CT for DDG PET/CT can be incorporated in a WB PET/CT of less than 15 min scan time on a PET/CT scanner of at least 25 cm AFOV PET detector. Conclusions: DDG PET/CT could correct the misregistration and tumor motion artifacts in a WB PET/CT and provide the quantitative PET and tumor motion information of a registered PET/CT for RT.

Indexed as

Data-driven gated CTData-driven gated PETData-driven gated PET/CTMisregistration correctionPET/CTRespiratory gatingRespiratory motionTumor motion

Identifiers

PMID39040434
PMCPMC11261283

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.