Evidence map›Paper›PMID 38436493›Full record

ArticleMedical physics2024

Linear Boltzmann equation solver for voxel-level dosimetry in radiopharmaceutical therapy: Comparison with Monte Carlo and kernel convolution.

Gunjan Kayal, Benjamin Van, George Andl, Cheng Tu, Todd Wareing, Scott Wilderman, Justin Mikell, Yuni K Dewaraja

Open access · hybridAbstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Medical physics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
2.4field-weighted citation impact, top 12% 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

1 citing paper in PubMed, 6 citations in OpenAlex.

  1. Review
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

8 authors at 3 institutions in 1 country.

Gunjan KayalDepartment of Radiology, University of Michigan, Ann Arbor, Michigan, USA.
Benjamin VanDepartment of Radiology, University of Michigan, Ann Arbor, Michigan, USA.
George AndlVarian Medical Systems, Atlanta, Georgia, USA.
Cheng TuVarian Medical Systems, Atlanta, Georgia, USA.
Todd WareingVarian Medical Systems, Atlanta, Georgia, USA.
Scott WildermanDepartment of Radiology, University of Michigan, Ann Arbor, Michigan, USA.
Justin MikellDepartment of Radiation Oncology, Washington University in St. Louis, St. Louis, Missouri, USA.
Yuni K DewarajaDepartment of Radiology, University of Michigan, Ann Arbor, Michigan, USA.
University of Michigan–Ann Arbor · USVarian Medical Systems (United States) · USWashington University in St. Louis · US

Funding

Imaging and Dosimetry of Yttrium-90 for Personalized Cancer TreatmentR01EB022075 · NIBIB · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI DEWARAJA, YUNI K · 2016 to 2023
$4.7M
Bringing Capacity for Theranostic Dosimetry Planning to the Nuclear Medicine ClinicR01CA240706 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI DEWARAJA, YUNI K · 2020 to 2024
$3.0M
NCI NIH HHS R01 CA240706NIBIB NIH HHS R01 EB022075
6 · The paper itself

Abstract

backgroundWith recent interest in patient-specific dosimetry for radiopharmaceutical therapy (RPT) and selective internal radiation therapy (SIRT), an increasing number of voxel-based algorithms are being evaluated. Monte Carlo (MC) radiation transport, generally considered to be the most accurate among different methods for voxel-level absorbed dose estimation, can be computationally inefficient for routine clinical use. PURPOSE: This work demonstrates a recently implemented grid-based linear Boltzmann transport equation (LBTE) solver for fast and accurate voxel-based dosimetry in RPT and SIRT and benchmarks it against MC.

methodsA deterministic LBTE solver (Acuros MRT) was implemented within a commercial RPT dosimetry package (Velocity 4.1). The LBTE is directly discretized using an adaptive mesh refined grid and then the coupled photon-electron radiation transport is iteratively solved inside specified volumes to estimate radiation doses from both photons and charged particles in heterogeneous media. To evaluate the performance of the LBTE solver for RPT and SIRT applications,

resultsIn the phantom inserts/compartments, the LBTE solver versus MC and DVK convolution demonstrated good agreement with mean absorbed dose and DVH metrics agreeing to within 5% except for the D90 and D70 metrics of a very low activity concentration insert of

conclusionHaving established good agreement between the LBTE solver and MC for RPT and SIRT applications, the LBTE solver is a viable option for voxel dosimetry that can be faster than MC. Further analysis is being performed to encompass the broad range of radionuclides and conditions encountered clinically.

Indexed as

Monte Carlo MethodRadiometryRadiopharmaceuticalsAlgorithmsHumansPhantoms, ImagingPositron Emission Tomography Computed TomographyRadiotherapy DosageSingle Photon Emission Computed Tomography Computed TomographyYttrium RadioisotopesRadiopharmaceuticalsYttrium-90Yttrium RadioisotopesdosimetryIodine‐131LBTE solverLutetium‐177radiopharmaceutical therapytheranosticsYttrium‐90

Identifiers

PMID38436493
PMCPMC11321934
OpenAlexW4392375601

What OpenQuestion holds

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LicenceCC BY-NC
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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.