Evidence map›Paper›PMID 37293394›Full record

ArticleJournal of biomedical optics2023

Analysis of relative error in perturbation Monte Carlo simulations of radiative transport.

Mahsa Parsanasab, Carole Hayakawa, Jerome Spanier, Yanning Shen, Vasan Venugopalan

Open access · goldAbstract read
In one paragraph

Article in Journal of biomedical optics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 29% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. 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.

Mahsa ParsanasabUniversity of California, Irvine, Department of Chemical and Biomolecular Engineering, Irvine, California, United States.ORCID 0000-0002-1397-706X
Carole HayakawaUniversity of California, Irvine, Department of Chemical and Biomolecular Engineering, Irvine, California, United States.ORCID 0000-0001-5696-160X
Jerome SpanierUniversity of California, Irvine, Department of Chemical and Biomolecular Engineering, Irvine, California, United States.
Yanning ShenUniversity of California, Irvine, Department of Electrical Engineering and Computer Science, Irvine, California, United States.
Vasan VenugopalanUniversity of California, Irvine, Department of Chemical and Biomolecular Engineering, Irvine, California, United States.ORCID 0000-0003-4781-1049
Beckman Laser Institute and Medical Clinic · USUniversity of California, Irvine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Significance: Perturbation and differential Monte Carlo (pMC/dMC) methods, used in conjunction with nonlinear optimization methods, have been successfully applied to solve inverse problems in diffuse optics. Application of pMC to systems over a large range of optical properties requires optimal "placement" of baseline conventional Monte Carlo (cMC) simulations to minimize the pMC variance. The inability to predict the growth in pMC solution uncertainty with perturbation size limits the application of pMC, especially for multispectral datasets where the variation of optical properties can be substantial. Aim: We aim to predict the variation of pMC variance with perturbation size without explicit computation of perturbed photon weights. Our proposed method can be used to determine the range of optical properties over which pMC predictions provide sufficient accuracy. This method can be used to specify the optical properties for the reference cMC simulations that pMC utilizes to provide accurate predictions over a desired optical property range. Approach: We utilize a conventional error propagation methodology to calculate changes in pMC relative error for Monte Carlo simulations. We demonstrate this methodology for spatially resolved diffuse reflectance measurements with ±20% scattering perturbations. We examine the performance of our method for reference simulations spanning a broad range of optical properties relevant for diffuse optical imaging of biological tissues. Our predictions are computed using the variance, covariance, and skewness of the photon weight, path length, and collision distributions generated by the reference simulation. Results: We find that our methodology performs best when used in conjunction with reference cMC simulations that utilize Russian Roulette (RR) method. Specifically, we demonstrate that for a proximal detector placed immediately adjacent to the source, we can estimate the pMC relative error within 5% of the true value for scattering perturbations in the range of Conclusions: These findings indicate that reference simulations utilizing continuous absorption weighting (CAW) with the Russian Roulette method and executed using optical properties with a low

Indexed as

Optics and PhotonicsPhotonsComputer SimulationMonte Carlo MethodScattering, Radiationinverse problemsMonte Carlo simulationmultispectral analysisoptical imagingperturbation methodsradiative transportuncertainty estimation

Identifiers

PMID37293394
PMCPMC10245552
OpenAlexW4379792838

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.