Evidence map›Paper›PMID 37790461›Full record

ArticlemedRxiv : the preprint server for health sciences2023

Total-body Dynamic Imaging and Kinetic Modeling of

Negar Omidvari, Jelena Levi, Yasser G Abdelhafez, Yiran Wang, Lorenzo Nardo, Megan E Daly, Guobao Wang, Simon R Cherry

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

Article in medRxiv : the preprint server for health sciences, 2023. 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, 5 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 2 countries.

Negar OmidvariDepartment of Biomedical Engineering, University of California Davis, Davis, CA, USA.ORCID 0000-0002-7589-4745
Jelena LeviCellSight Technologies Inc., San Francisco, CA, USA.
Yasser G AbdelhafezDepartment of Radiology, University of California Davis Medical Center, Sacramento, CA, USA.
Yiran WangDepartment of Radiology, University of California Davis Medical Center, Sacramento, CA, USA.
Lorenzo NardoDepartment of Radiology, University of California Davis Medical Center, Sacramento, CA, USA.
Megan E DalyDepartment of Radiation Oncology, University of California Davis Comprehensive Cancer Center School of Medicine, Sacramento, CA, USA.
Guobao WangDepartment of Radiology, University of California Davis Medical Center, Sacramento, CA, USA.
Simon R CherryDepartment of Biomedical Engineering, University of California Davis, Davis, CA, USA.
University of California Davis Medical Center · USCellSight Technologies (United States) · USUC Davis Comprehensive Cancer CenterUniversity of California, Davis · US

Funding

EXPLORER: Changing the Molecular Imaging Paradigm with Total Body PETR01CA206187 · NCI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI BADAWI, RAMSEY D., CHERRY, SIMON R · 2015 to 2019
$15.5M
Research at the interface of optical and ionizing radiation for innovative cancer imaging and therapyR35CA197608 · NCI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI CHERRY, SIMON R · 2015 to 2021
$4.9M
NCI NIH HHS R01 CA206187NCI NIH HHS R35 CA197608
6 · The paper itself

Abstract

Immunotherapies, especially the checkpoint inhibitors such as anti-PD-1 antibodies, have transformed cancer treatment by enhancing immune system's capability to target and kill cancer cells. However, predicting immunotherapy response remains challenging. Methods: The study consisted of 90-min total-body dynamic scans of four healthy subjects and one non-small cell lung cancer (NSCLC) patient, scanned before and after anti-PD-1 immunotherapy. Compartmental modeling with Akaike information criterion model selection were employed to analyze tracer kinetics in various organs. Additionally, seven sub-regions of the primary lung tumor and four mediastinal lymph nodes were analyzed. Practical identifiability analysis was performed to assess reliability of kinetic parameter estimation. Correlations of SUVmean, SUVR (tissue-to-blood ratio), and Logan plot slope Results: Strong correlations were observed between Conclusion: Our findings highlight the promise of

Indexed as

immunotherapykinetic modelingNSCLCT cellstotal-body PET

Identifiers

PMID37790461
PMCPMC10543042
OpenAlexW4386998822

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.