Evidence map›Paper›PMID 36625713›Full record

ArticleMedical physics2023

Monte Carlo-derived

Benjamin P Lopez, S Cheenu Kappadath

Abstract read
In one paragraph

Article in Medical physics, 2023. 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
–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

2 citing papers in PubMed.

  1. Current and future perspectives of molecular breast imaging with [European journal of nuclear medicine and molecular imaging · 2026
    Review
  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

2 authors.

Benjamin P LopezDepartment of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
S Cheenu KappadathDepartment of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID https://orcid.org/0000-0003-4643-7745

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Fabien Delerue · 1985 to 2026
$290.8M
NCI NIH HHS P30 CA016672
6 · The paper itself

Abstract

backgroundCurrent molecular breast imaging (MBI) images are limited to qualitative evaluation, not absolute measurement, of PURPOSE: This work assesses the accuracy of previously-published and newly-proposed tumor and normal breast tissue

methodsQuantification techniques were tested in over 4000 simulated acquisitions of spherical and ellipsoid tumors with clinically relevant uptake conditions using a validated Monte Carlo application of the GE Discovery NM750b system. The evaluated techniques consisted of four tumor total activity methodologies (two single-detector-based and two geometric-mean-based), two tumor MBI volume methodologies (diameter-based and ROI-based), and two normal tissue activity concentration methodologies (single-detector-based and geometric-mean-based). The most accurate of these techniques were then used to estimate tumor activity concentrations and tumor to normal tissue relative activity concentrations (RC).

resultsSingle-detector techniques for tumor total activity quantification achieved mean (standard deviation) relative errors of 0.2% (4.3%) and 1.6% (4.4%) when using the near and far detector images, respectively and were more accurate and precise than the measured 8.1% (5.8%) errors of a previously published geometric-mean technique. Using these activity estimates and the true tumor volumes resulted in tumor activity concentration and RC errors within 10% of simulated values. The precision of tumor activity concentration and RC when using only MBI measurements were largely driven by the errors in estimating tumor MBI volume using planar images (± 30% inter-quartile range).

conclusionsPlanar MBI images were shown to accurately and reliably be used to estimate tumor total activities and normal tissue activity concentrations in this simulation study. However, volumetric tumor uptake measurements (i.e., absolute and relative concentrations) are limited by inaccuracies in MBI volume estimation using two-dimensional images, highlighting the need for either tomographic MBI acquisitions or anatomical volume estimates for accurate three-dimensional tumor uptake estimates.

Indexed as

NeoplasmsBreastComputer SimulationHumansMammographyPhantoms, ImagingRadionuclide Imagingabsolute quantificationmolecular breast imaging

Identifiers

PMID36625713
PMCPMC10331527

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Registered trials

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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.