Evidence map›Paper›PMID 35014900›Full record

ArticleRadiology2022

Reduced-Dose Deep Learning Reconstruction for Abdominal CT of Liver Metastases.

Corey T Jensen, Shiva Gupta, Mohammed M Saleh, Xinming Liu, Vincenzo K Wong, Usama Salem, Wei Qiao, Ehsan Samei, Nicolaus A Wagner-Bartak

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 1 pooled it
13.1field-weighted citation impact, top 1% 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

56 citing papers in PubMed, 1 synthesis or guideline pooled it, 98 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

9 authors at 2 institutions in 1 country.

Corey T JensenFrom the Departments of Abdominal Imaging (C.T.J., S.G., M.M.S., V.K.W., U.S., N.A.W.B.), Physics (X.L.), and Biostatistics (W.Q.), the University of Texas MD Anderson Cancer Center, 1400 Pressler St, Unit 1473, Houston, TX 77030-4009; and Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Clinical Imaging Physics Group, Medical Physics Graduate Program, Departments of Radiology, Physics, Biomedical Engineering, and Electrical and Computer Engineering, Duke University Medical Center, Durham, NC (E.S.).ORCID 0000-0001-6540-8961
Shiva GuptaFrom the Departments of Abdominal Imaging (C.T.J., S.G., M.M.S., V.K.W., U.S., N.A.W.B.), Physics (X.L.), and Biostatistics (W.Q.), the University of Texas MD Anderson Cancer Center, 1400 Pressler St, Unit 1473, Houston, TX 77030-4009; and Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Clinical Imaging Physics Group, Medical Physics Graduate Program, Departments of Radiology, Physics, Biomedical Engineering, and Electrical and Computer Engineering, Duke University Medical Center, Durham, NC (E.S.).ORCID 0000-0002-4758-8118
Mohammed M SalehFrom the Departments of Abdominal Imaging (C.T.J., S.G., M.M.S., V.K.W., U.S., N.A.W.B.), Physics (X.L.), and Biostatistics (W.Q.), the University of Texas MD Anderson Cancer Center, 1400 Pressler St, Unit 1473, Houston, TX 77030-4009; and Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Clinical Imaging Physics Group, Medical Physics Graduate Program, Departments of Radiology, Physics, Biomedical Engineering, and Electrical and Computer Engineering, Duke University Medical Center, Durham, NC (E.S.).ORCID 0000-0002-8574-4695
Xinming LiuFrom the Departments of Abdominal Imaging (C.T.J., S.G., M.M.S., V.K.W., U.S., N.A.W.B.), Physics (X.L.), and Biostatistics (W.Q.), the University of Texas MD Anderson Cancer Center, 1400 Pressler St, Unit 1473, Houston, TX 77030-4009; and Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Clinical Imaging Physics Group, Medical Physics Graduate Program, Departments of Radiology, Physics, Biomedical Engineering, and Electrical and Computer Engineering, Duke University Medical Center, Durham, NC (E.S.).ORCID 0000-0001-6328-4803
Vincenzo K WongFrom the Departments of Abdominal Imaging (C.T.J., S.G., M.M.S., V.K.W., U.S., N.A.W.B.), Physics (X.L.), and Biostatistics (W.Q.), the University of Texas MD Anderson Cancer Center, 1400 Pressler St, Unit 1473, Houston, TX 77030-4009; and Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Clinical Imaging Physics Group, Medical Physics Graduate Program, Departments of Radiology, Physics, Biomedical Engineering, and Electrical and Computer Engineering, Duke University Medical Center, Durham, NC (E.S.).ORCID 0000-0002-8256-4760
Usama SalemFrom the Departments of Abdominal Imaging (C.T.J., S.G., M.M.S., V.K.W., U.S., N.A.W.B.), Physics (X.L.), and Biostatistics (W.Q.), the University of Texas MD Anderson Cancer Center, 1400 Pressler St, Unit 1473, Houston, TX 77030-4009; and Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Clinical Imaging Physics Group, Medical Physics Graduate Program, Departments of Radiology, Physics, Biomedical Engineering, and Electrical and Computer Engineering, Duke University Medical Center, Durham, NC (E.S.).ORCID 0000-0002-1982-1429
Wei QiaoFrom the Departments of Abdominal Imaging (C.T.J., S.G., M.M.S., V.K.W., U.S., N.A.W.B.), Physics (X.L.), and Biostatistics (W.Q.), the University of Texas MD Anderson Cancer Center, 1400 Pressler St, Unit 1473, Houston, TX 77030-4009; and Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Clinical Imaging Physics Group, Medical Physics Graduate Program, Departments of Radiology, Physics, Biomedical Engineering, and Electrical and Computer Engineering, Duke University Medical Center, Durham, NC (E.S.).ORCID 0000-0002-0922-0726
Ehsan SameiFrom the Departments of Abdominal Imaging (C.T.J., S.G., M.M.S., V.K.W., U.S., N.A.W.B.), Physics (X.L.), and Biostatistics (W.Q.), the University of Texas MD Anderson Cancer Center, 1400 Pressler St, Unit 1473, Houston, TX 77030-4009; and Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Clinical Imaging Physics Group, Medical Physics Graduate Program, Departments of Radiology, Physics, Biomedical Engineering, and Electrical and Computer Engineering, Duke University Medical Center, Durham, NC (E.S.).ORCID 0000-0001-7451-3309
Nicolaus A Wagner-BartakFrom the Departments of Abdominal Imaging (C.T.J., S.G., M.M.S., V.K.W., U.S., N.A.W.B.), Physics (X.L.), and Biostatistics (W.Q.), the University of Texas MD Anderson Cancer Center, 1400 Pressler St, Unit 1473, Houston, TX 77030-4009; and Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Clinical Imaging Physics Group, Medical Physics Graduate Program, Departments of Radiology, Physics, Biomedical Engineering, and Electrical and Computer Engineering, Duke University Medical Center, Durham, NC (E.S.).ORCID 0000-0002-5484-8424
The University of Texas MD Anderson Cancer Center · USDuke Medical Center · US

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
Women's Cancer Research ProgramP30CA014236 · NCI · DUKE UNIVERSITY · PI DONNA NIEDZWIECKI · 1985 to 2026
$174.8M
NCI NIH HHS P30 CA014236NCI NIH HHS P30 CA016672
6 · The paper itself

Abstract

Background Assessment of liver lesions is constrained as CT radiation doses are lowered; evidence suggests deep learning reconstructions mitigate such effects. Purpose To evaluate liver metastases and image quality between reduced-dose deep learning image reconstruction (DLIR) and standard-dose filtered back projection (FBP) contrast-enhanced abdominal CT. Materials and Methods In this prospective Health Insurance Portability and Accountability Act-compliant study (September 2019 through April 2021), participants with biopsy-proven colorectal cancer and liver metastases at baseline CT underwent standard-dose and reduced-dose portal venous abdominal CT in the same breath hold. Three radiologists detected and characterized lesions at standard-dose FBP and reduced-dose DLIR, reported confidence, and scored image quality. Contrast-to-noise ratios for liver metastases were recorded. Summary statistics were reported, and a generalized linear mixed model was used. Results Fifty-one participants (mean age ± standard deviation, 57 years ± 13; 31 men) were evaluated. The mean volume CT dose index was 65.1% lower with reduced-dose CT (12.2 mGy) than with standard-dose CT (34.9 mGy). A total of 161 lesions (127 metastases, 34 benign lesions) with a mean size of 0.7 cm ± 0.3 were identified. Subjective image quality of reduced-dose DLIR was superior to that of standard-dose FBP (

Indexed as

Deep LearningLiver NeoplasmsAlgorithmsFemaleHumansMaleProspective StudiesRadiation DosageRadiographic Image Interpretation, Computer-AssistedTomography, X-Ray Computed

Identifiers

PMID35014900
PMCPMC8962777
OpenAlexW4206457879

What OpenQuestion holds

Textmetadata
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.