Evidence map›Paper›PMID 36185820›Full record

ArticleIEEE transactions on radiation and plasma medical sciences2022

Optimized Methodology for Reference Region and Image-Derived Input Function Kinetic Modeling in Preclinical PET.

Jason Bini, Christine R Lattin, Takuya Toyonaga, Sjoerd J Finnema, Richard Carson

Open access · greenAbstract read
In one paragraph

Article in IEEE transactions on radiation and plasma medical sciences, 2022. 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
0.4field-weighted citation impact, top 38% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  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

5 authors at 2 institutions in 1 country.

Jason BiniYale School of Medicine, New Haven, CT, USA.
Christine R LattinLouisiana State Univ., Baton Rouge, LA, USA.
Takuya ToyonagaYale School of Medicine, New Haven, CT, USA.
Sjoerd J FinnemaYale School of Medicine, New Haven, CT, USA Richard E. Carson.
Richard CarsonYale Univ., New Haven, CT, USA.
Yale University · USLouisiana State University · US

Funding

Yale Interdisciplinary Bioengineering Training Grant for Diabetes ResearchT32DK101019 · NIDDK · YALE UNIVERSITY · PI SALTZMAN, W. MARK · 2013 to 2017
$1.5M
Direct measurement of 11beta-hydroxysteroid dehydrogenase type 1 (11beta-HSD1) enzyme levels in obesity using a novel positron emissiontomography radioligandK01DK118005 · NIDDK · YALE UNIVERSITY · PI BINI, JASON · 2019 to 2023
$848k
State-of-the-Art Small Animal PET/CT InstrumentationS10OD010322 · OD · YALE UNIVERSITY · PI CARSON, RICHARD E. · 2013 to 2013
$595k
NIDDK NIH HHS K01 DK118005NIDDK NIH HHS T32 DK101019NIH HHS S10 OD010322
6 · The paper itself

Abstract

PET imaging of small animals is often used for assessing biodistribution of a novel radioligand and pharmacology in small animal models of disease. PET acquisition and processing settings may affect reference region or image-derived input function (IDIF) kinetic modeling estimates. We examined four different factors in comparing quantitative results: 1) effect of reconstruction algorithm, 2) number of MAP iterations, 3) strength of the MAP prior, and 4) Attenuation and scatter. The effect of these parameters has not been explored for small-animal reference region and IDIF kinetic modeling approaches. Dynamic PET/CT scans were performed in 3 species with 3 different tracers: house sparrows with [

Indexed as

attenuationkinetic modelingpositron emission tomography (PET)preclinicalquantificationreconstructionscattersmall animal

Identifiers

PMID36185820
PMCPMC9524424
OpenAlexW3171944614

What OpenQuestion holds

Textmetadata
LicenceTDM
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.