Evidence map›Paper›PMID 35626315›Full record

ArticleDiagnostics (Basel, Switzerland)2022

Image Quantification for TSPO PET with a Novel Image-Derived Input Function Method.

Yu-Hua Dean Fang, Jonathan E McConathy, Talene A Yacoubian, Yue Zhang, Richard E Kennedy, David G Standaert

Open access · goldAbstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.0field-weighted citation impact, top 27% 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

7 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Review
  3. [European journal of nuclear medicine and molecular imaging · 2023
    Article
  4. Brain and Systemic Inflammation in De Novo Parkinson's Disease.Movement disorders : official journal of the Movement Disorder Society · 2023
    Article
  5. Review
  6. Article
  7. Editorial on Special Issue "Quantitative PET and SPECT".Diagnostics (Basel, Switzerland) · 2022
    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

6 authors at 1 institution in 1 country.

Yu-Hua Dean FangDepartment of Radiology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA.
Jonathan E McConathyDepartment of Radiology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA.
Talene A YacoubianCenter for Neurodegeneration and Experimental Therapeutics, Department of Neurology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA.ORCID 0000-0003-2227-7310
Yue ZhangDepartment of Medicine, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA.
Richard E KennedyDepartment of Medicine, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA.
David G StandaertCenter for Neurodegeneration and Experimental Therapeutics, Department of Neurology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA.
University of Alabama at Birmingham · US

Funding

Project 3: LRRK2 mediated macrophage responses in PDP50NS108675 · NINDS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI STANDAERT, DAVID G. · 2018 to 2022
$9.9M
NIH HHS NS108675NINDS NIH HHS P50 NS108675
6 · The paper itself

Abstract

There is a growing interest in using 18F-DPA-714 PET to study neuroinflammation and microglial activation through imaging the 18-kDa translocator protein (TSPO). Although quantification of 18F-DPA-714 binding can be achieved through kinetic modeling analysis with an arterial input function (AIF) measured with blood sampling procedures, the invasiveness of such procedures has been an obstacle for wide application. To address these challenges, we developed an image-derived input function (IDIF) that noninvasively estimates the arterial input function from the images acquired for 18F-DPA-714 quantification. Methods: The method entails three fully automatic steps to extract the IDIF, including a segmentation of voxels with highest likelihood of being the arterial blood over the carotid artery, a model-based matrix factorization to extract the arterial blood signal, and a scaling optimization procedure to scale the extracted arterial blood signal into the activity concentration unit. Two cohorts of human subjects were used to evaluate the extracted IDIF. In the first cohort of five subjects, arterial blood sampling was performed, and the calculated IDIF was validated against the measured AIF through the comparison of distribution volumes from AIF (VT,AIF) and IDIF (VT,IDIF). In the second cohort, PET studies from twenty-eight healthy controls without arterial blood sampling were used to compare VT,IDIF with VT,REF measured using a reference region-based analysis to evaluate whether it can distinguish high-affinity (HAB) and mixed-affinity (MAB) binders. Results: In the arterial blood-sampling cohort, VT derived from IDIF was found to be an accurate surrogate of the VT from AIF. The bias of VT, IDIF was −5.8 ± 7.8% when compared to VT,AIF, and the linear mixed effect model showed a high correlation between VT,AIF and VT, IDIF (p < 0.001). In the nonblood-sampling cohort, VT, IDIF showed a significance difference between the HAB and MAB healthy controls. VT, IDIF and standard uptake values (SUV) showed superior results in distinguishing HAB from MAB subjects than VT,REF. Conclusions: A novel IDIF method for 18F-DPA-714 PET quantification was developed and evaluated in this study. This IDIF provides a noninvasive alternative measurement of VT to quantify the TSPO binding of 18F-DPA-714 in the human brain through dynamic PET scans.

Indexed as

image-derived input functionkinetic modeling analysisneuroinflammationTSPO PET

Identifiers

PMID35626315
PMCPMC9140104
OpenAlexW4229332310

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.