Evidence map›Paper›PMID 23526701›Full record

ArticleAmerican journal of nuclear medicine and molecular imaging2013

In situ study of the impact of inter- and intra-reader variability on region of interest (ROI) analysis in preclinical molecular imaging.

Frezghi Habte, Shradha Budhiraja, Shay Keren, Timothy C Doyle, Craig S Levin, David S Paik

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Article in American journal of nuclear medicine and molecular imaging, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

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0cells of the map it votes in
8citing 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

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3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Observational
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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

6 authors.

Frezghi HabteMolecular Imaging Program at Stanford (MIPS), Stanford University Stanford, CA, USA ; Department of Radiology, Stanford University Stanford, CA, USA.
Shradha Budhiraja
Shay Keren
Timothy C Doyle
Craig S Levin
David S Paik

Funding

Stanford Nanocharacterization LaboratoryU54CA119367 · NCI · STANFORD UNIVERSITY · PI GAMBHIR, SANJIV S · 2006 to 2010
$19.8M
Small Animal ImagingP50CA114747 · NCI · STANFORD UNIVERSITY · PI RAO, JIANGHONG · 2005 to 2014
$18.2M
NCI NIH HHS P50 CA114747NCI NIH HHS U54 CA119367
6 · The paper itself

Abstract

We estimated reader-dependent variability of region of interest (ROI) analysis and evaluated its impact on preclinical quantitative molecular imaging. To estimate reader variability, we used five independent image datasets acquired each using microPET and multispectral fluorescence imaging (MSFI). We also selected ten experienced researchers who utilize molecular imaging in the same environment that they typically perform their own studies. Nine investigators blinded to the data type completed the ROI analysis by drawing ROIs manually that delineate the tumor regions to the best of their knowledge and repeated the measurements three times, non-consecutively. Extracted mean intensities of voxels within each ROI are used to compute the coefficient of variation (CV) and characterize the inter- and intra-reader variability. The impact of variability was assessed through random samples iterated from normal distributions for control and experimental groups on hypothesis testing and computing statistical power by varying subject size, measured difference between groups and CV. The results indicate that inter-reader variability was 22.5% for microPET and 72.2% for MSFI. Additionally, mean intra-reader variability was 10.1% for microPET and 26.4% for MSFI. Repeated statistical testing showed that a total variability of CV < 50% may be needed to detect differences < 50% between experimental and control groups when six subjects (n = 6) or more are used and statistical power is adequate (80%). Surprisingly high variability has been observed mainly due to differences in the ROI placement and geometry drawn between readers, which may adversely affect statistical power and erroneously lead to negative study outcomes.

Indexed as

microPETMolecular imagingmultispectral fluorescence imagingpreclinicalregion of interest analysisvariability

Identifiers

PMID23526701
PMCPMC3601477

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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.