Evidence map›Paper›PMID 28273348›Full record

ArticleMedical physics2017

Performance evaluation of

Qian Wang, Debanti Sengupta, Tae Jin Kim, Guillem Pratx

Abstract read
In one paragraph

Article in Medical physics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Development of a Lensless Radiomicroscope for Cellular-Resolution Radionuclide Imaging.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2023
    Article
  2. High-resolution radioluminescence microscopy of FDG uptake in an engineered 3D tumor-stoma model.European journal of nuclear medicine and molecular imaging · 2021
    Article
  3. Article
  4. Article
  5. Review
  6. 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

4 authors.

Qian WangDepartment of Radiation Oncology, Stanford University, Stanford, CA, 94304, USA.
Debanti SenguptaDepartment of Radiation Oncology, Stanford University, Stanford, CA, 94304, USA.
Tae Jin KimDepartment of Radiation Oncology, Stanford University, Stanford, CA, 94304, USA.
Guillem PratxDepartment of Radiation Oncology, Stanford University, Stanford, CA, 94304, USA.

Funding

Quantitative Imaging of Cancer Drug Resistance via Radioluminescence MicroarraysR01CA186275 · NCI · STANFORD UNIVERSITY · PI PRATX, GUILLEM · 2014 to 2018
$1.7M
NCI NIH HHS R01 CA186275
6 · The paper itself

Abstract

purposeRadioluminescence microscopy can visualize the distribution of beta-emitting radiotracers in live single cells with high resolution. Here, we perform a computational simulation of

methodsFirst, the transport of charged particles through the cell and scintillator and the resulting scintillation is modeled using the GEANT4 Monte-Carlo simulation. Then, the propagation of the scintillation light through the microscope is modeled by a convolution with a depth-dependent point-spread function, which models the microscope response. Finally, the physical measurement of the scintillation light using an electron-multiplying charge-coupled device (EMCCD) camera is modeled using a stochastic numerical photosensor model, which accounts for various sources of noise. The simulated output of the EMCCD camera is further processed using our ORBIT image reconstruction methodology to evaluate the endpoint images.

resultsThe EMCCD camera model was validated against experimentally acquired images and the simulated noise, as measured by the standard deviation of a blank image, was found to be accurate within 2% of the actual detection. Furthermore, point source simulations found that a reconstructed spatial resolution of 18.5 μm can be achieved near the scintillator. As the source is moved away from the scintillator, spatial resolution degrades at a rate of 3.5 μm per μm distance. These results agree well with the experimentally measured spatial resolution of 30-40 μm (live cells). The simulation also shows that the system sensitivity is 26.5%, which is also consistent with our previous experiments. Finally, an image of a simulated sparse set of single cells is visually similar to the measured cell image.

conclusionsOur simulation methodology agrees with experimental measurements taken with radioluminescence microscopy. This in silico approach can be used to guide further instrumentation developments and to provide a framework for improving image reconstruction.

Indexed as

Image Processing, Computer-AssistedMicroscopyMonte Carlo MethodComputer SimulationElectronsHumanscomputational simulationimager performance evaluationpositron imagingradioluminescence microscopy

Identifiers

PMID28273348
PMCPMC5462448

What OpenQuestion holds

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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.