Evidence map›Paper›PMID 35239613›Full record

ArticleInvestigative radiology2022

Cone-Beam Computed Tomography-Based Spatial Prediction of Drug Dose After Transarterial Chemoembolization Using Radiopaque Drug-Eluting Beads in Woodchuck Hepatocellular Carcinoma.

Andrew S Mikhail, William F Pritchard, Ayele H Negussie, Gazi Inkiyad, Dilara J Long, Michal Mauda-Havakuk, Paul G Wakim, William van der Sterren, Elliot B Levy, Andrew L Lewis and 2 more

Open access · greenAbstract read
In one paragraph

Article in Investigative radiology, 2022. 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
1.0field-weighted citation impact, top 27% 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, 7 citations in OpenAlex.

  1. Trial
  2. Article
  3. 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

12 authors at 4 institutions in 3 countries.

Andrew S MikhailFrom the Center for Interventional Oncology, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD.ORCID 0000-0001-9206-5765
William F PritchardFrom the Center for Interventional Oncology, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD.ORCID 0000-0001-5805-5344
Ayele H NegussieFrom the Center for Interventional Oncology, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD.ORCID 0000-0003-3340-3351
Gazi InkiyadBiomedical Engineering Summer Internship Program, Center for Interventional Oncology, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD.
Dilara J LongFrom the Center for Interventional Oncology, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD.ORCID 0000-0002-5564-4773
Michal Mauda-HavakukORCID 0000-0002-8810-3455
Paul G WakimBiostatistics and Clinical Epidemiology Service, Clinical Center, National Institutes of Health, Bethesda, MD.
William van der SterrenIGT Systems Innovation, Philips, Best, the Netherlands.
Elliot B LevyFrom the Center for Interventional Oncology, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD.
Andrew L LewisOwen Mumford Ltd, Woodstock, Oxfordshire, United Kingdom.ORCID 0000-0001-5779-5631
John W KaranianFrom the Center for Interventional Oncology, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD.
Bradford J WoodFrom the Center for Interventional Oncology, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD.
National Institutes of Health Clinical Center · USNational Institutes of Health · USOwen Mumford (United Kingdom) · GBPhilips (Netherlands) · NL

Funding

Center for Interventional OncologyZIDBC011242 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI WOOD, BRADFORD J · 2009 to 2025
$18.7M
Navigation Tools for Image Guided Minimally invasive TherapiesZIACL040011 · CLC · CLINICAL CENTER · PI WOOD, BRADFORD · 2009 to 2025
$0k
Interventional OncologyZIACL040015 · CLC · CLINICAL CENTER · PI WOOD, BRADFORD · 2009 to 2025
$0k
Optical and electromagnetic tracking guidance for hepatic interventionsZIACL090073 · CLC · CLINICAL CENTER · PI WOOD, BRADFORD · 2020 to 2024
$0k
Intramural NIH HHS Z99 CL999999Intramural NIH HHS ZID BC011242
6 · The paper itself

Abstract

objectivesThe aims of this study were to develop a model to estimate drug dose delivered to tumors after transarterial chemoembolization (TACE) with radiopaque drug-eluting beads (DEBs) based on DEB density on cone-beam computed tomography (CT) and to evaluate drug penetration into tissue in a woodchuck hepatoma model. MATERIALS AND

methodsTransarterial chemoembolization was performed in woodchucks with hepatocellular carcinoma (N = 5) using DEBs (70-150 μm, LC Bead LUMI) loaded with doxorubicin. Livers were resected 45 minutes after embolization, immediately frozen, and cut using liver-specific, 3D-printed sectioning molds. Doxorubicin levels in tumor specimens were measured by high-performance liquid chromatography and correlated with DEB iodine content that was measured using prototype cone-beam CT-based embolization treatment planning software. Doxorubicin penetration into tissue surrounding DEBs was assessed by fluorescence microscopy of tumor sections. Fluorescence intensity was converted into doxorubicin concentration using calibration standards. Intensity-thresholded color heatmaps were generated representing extravascular drug penetration.

resultsConsistent segmentation of DEBs on cone-beam CT was achieved using a semiautomated intensity thresholding method. A positive linear correlation (0.96) was found between DEB iodine content measured on cone-beam CT and the amount of doxorubicin measured in tumor specimens. Prediction of doxorubicin levels in tumor sections that were not included in model development was accurate, with a root-mean-square error of 0.08 mg of doxorubicin. Tumor penetration of eluted doxorubicin resulted in concentration gradients where drug content decreased with increasing distance from blood vessels containing DEBs. Drug penetration was greater for blood vessels containing DEB clusters compared with single DEB, with higher doxorubicin concentrations extending further away from the vessels.

conclusionsEstimation of drug dose delivered during transarterial chemoembolization in a woodchuck hepatocellular carcinoma model was possible using DEB radiopacity on cone-beam CT as a surrogate marker. Doxorubicin penetration was greatest adjacent to vessels containing DEB clusters compared with single DEB. Intraprocedural estimation of the spatial distribution of drug dose within the tumor could enable real-time adjustments to DEB delivery, to maximize treatment coverage or identify regions of tumor at risk for undertreatment.

Indexed as

Carcinoma, HepatocellularChemoembolization, TherapeuticIodineLiver NeoplasmsAnimalsAntibiotics, AntineoplasticCone-Beam Computed TomographyDoxorubicinMarmotaTreatment OutcomeAntibiotics, AntineoplasticDoxorubicinIodine

Identifiers

PMID35239613
PMCPMC11493181
OpenAlexW4214811978

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.