Evidence map›Paper›PMID 35324002›Full record

ArticleMedical physics2022

Data-driven gated CT: An automated respiratory gating method to enable data-driven gated PET/CT.

Tinsu Pan, M Allan Thomas, Dershan Luo

Open access · greenAbstract read
In one paragraph

Article in Medical physics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.2field-weighted citation impact, top 13% of its field
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

11 citing papers in PubMed, 17 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Tinsu PanDepartment of Imaging Physics, M.D. Anderson Cancer Center, University of Texas, Houston, Texas, USA.
M Allan ThomasDepartment of Imaging Physics, M.D. Anderson Cancer Center, University of Texas, Houston, Texas, USA.
Dershan LuoDepartment of Radiation Physics, M.D. Anderson Cancer Center, University of Texas, Houston, Texas, USA.
The University of Texas MD Anderson Cancer Center · US

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
Proton Therapy to Reduce Heart Damage for Lung Cancer PatientsR21CA222749 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LIAO, ZHONGXING · 2019 to 2020
$388k
Optimization of PET Image Reconstruction for Lesion DetectionR03EB030280 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI GONG, KUANG · 2020 to 2021
$184k
NCI NIH HHS R21 CA222749NHLBI NIH HHS R01 HL157273NIBIB NIH HHS R03 EB030280NIH HHS R01-HL157273-01NIH HHS R03-EB030280-01NIH HHS R21-CA222749-01A1
6 · The paper itself

Abstract

backgroundThe accuracy of positron emission tomography (PET) quantification and localization can be compromised if a misregistered computed tomography (CT) is used for attenuation correction (AC) in PET/CT. As data-driven gating (DDG) continues to grow in clinical use, these issues are becoming more relevant with respect to solutions for gated CT. PURPOSE: In this work, a new automated DDG CT method was developed to provide average CT and DDG CT for AC of PET and DDG PET, respectively.

methodsAn automatic DDG CT was developed to provide the end-expiratory (EE) and end-inspiratory (EI) phases of images from low-dose cine CT images, with all phases being averaged to generate an average CT. The respiratory phases of EE and EI were determined according to lung region Hounsfield unit (HU) values and body outline contours. The average CT was used for AC of baseline PET and DDG CT at EE phase was used for AC of DDG PET at the quiescent or EE phase. The EI and EE phases obtained with DDG CT were used for assessing the magnitude of respiratory motion. The proposed DDG CT was compared to two commercial CT gating methods: (1) 4D CT (external device based) and (2) D4D CT (DDG based) in 38 patient datasets with respect to respiratory phase image selection, lung HU, lung volume, and image artifacts. In a separate set of twenty consecutive PET/CT studies containing a mix of

resultsIn the EE phase, the images selected by DDG CT and 4D CT were identical 62.5% ± 21.6% of the time, whereas DDG CT and D4D CT were 6.5% ± 9.7%, and 4D CT and D4D CT were 8.6% ± 12.2%. These differences in EE phase image selection were significant (p < 0.0001). In the EI phase, the images selected by DDG CT and 4D CT were identical 68.2% ± 18.9% of the time, DDG CT and D4D CT were 63.9% ± 18.8%, and 4D CT and D4D CT were 61.2% ± 19.8%. These differences were not significant. The mean lung HU and volumes were not statistically different (p > 0.1) among the three methods. In some studies, DDG CT was better than D4D or 4D CT in the appropriate selection of the EE and EI phases, and D4D CT was found to reverse the EE and EI phases or not select the correct images by visual inspection. A statistically significant improvement of DDG CT over D4D CT for AC of DDG PET was also demonstrated with PET quantification analysis. When irregular breath cycles were present in the cine CT, DDG CT could be used to replace average CT for the improved AC of baseline PET.

conclusionA new automatic DDG CT was developed to tackle the issues of misregistration and tumor motion in PET/CT imaging. DDG CT was significantly more consistent than D4D CT in selecting the EE phase images as the clinical standard of 4D CT. When compared to both commercial gated CT methods of 4D CT and D4D CT, DDG CT appeared to be more robust in the lower lung and upper diaphragm regions where misregistration and tumor motion often occur. DDG CT offered improved AC for DDG PET relative to D4D CT. In cases with irregular respiratory motion, DDG CT improved AC over average CT for baseline PET. The new DDG CT provides the benefits of 4D CT without the need for external device gating.

Indexed as

Four-Dimensional Computed TomographyPositron Emission Tomography Computed TomographyHumansMotionPositron-Emission TomographyRadionuclide Imagingcopper dotatate CU-64DDG CTDDG PET/CTmisregistrationrespiratory motion

Identifiers

PMID35324002
PMCPMC9187617
OpenAlexW4220772662

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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.