Evidence map›Paper›PMID 38155237›Full record

ArticleEuropean journal of nuclear medicine and molecular imaging2024

MIDOS: a novel stochastic model towards a treatment planning system for microsphere dosimetry in liver tumors.

Carlos Huesa-Berral, Julia D Withrow, Robert J Dawson, Chris Beekman, Wesley E Bolch, Harald Paganetti, Eric Wehrenberg-Klee, Alejandro Bertolet

Open access · greenAbstract read
In one paragraph

Article in European journal of nuclear medicine and molecular imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.2field-weighted citation impact, top 19% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

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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 2 institutions in 1 country.

Carlos Huesa-BerralDepartment of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA. chuesaberral@mgh.harvard.edu.ORCID 0000-0003-2290-0176
Julia D WithrowJ. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA.ORCID 0000-0001-6265-3355
Robert J DawsonJ. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA.ORCID 0000-0002-0984-4088
Chris BeekmanDepartment of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.ORCID 0000-0002-0061-5473
Wesley E BolchJ. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA.ORCID 0000-0002-7175-9968
Harald PaganettiDepartment of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.ORCID 0000-0002-6257-2413
Eric Wehrenberg-KleeDivision of Interventional Radiology, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.ORCID 0000-0002-4712-3986
Alejandro BertoletDepartment of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA. abertoletreina@mgh.harvard.edu.ORCID 0000-0002-9890-693X
Harvard University · USUniversity of Florida · US

Funding

Developing whole-body computational phantoms for blood dosimetry to model the impact of radiation on the immune systemR01CA248901 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI BOLCH, WESLEY E, PAGANETTI, HARALD · 2020 to 2024
$2.4M
Biomarker Identification to Increase Adjunctive Cryoablation and Checkpoint-Inhibitor Immunotherapy ResponseK08CA245257 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI WEHRENBERG-KLEE, ERIC · 2020 to 2024
$1.3M
Radiation dosimetry for alpha-particle radiopharmaceutical therapy and application to pediatric neuroblastomaR00CA267560 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI BERTOLET REINA, ALEJANDRO · 2023 to 2025
$721k
NCI NIH HHS K08 CA245257NCI NIH HHS R00 CA267560NCI NIH HHS R01 CA248901
6 · The paper itself

Abstract

purposeTransarterial radioembolization (TARE) procedures treat liver tumors by injecting radioactive microspheres into the hepatic artery. Currently, there is a critical need to optimize TARE towards a personalized dosimetry approach. To this aim, we present a novel microsphere dosimetry (MIDOS) stochastic model to estimate the activity delivered to the tumor(s), normal liver, and lung.

methodsMIDOS incorporates adult male/female liver computational phantoms with the hepatic arterial, hepatic portal venous, and hepatic venous vascular trees. Tumors can be placed in both models at user discretion. The perfusion of microspheres follows cluster patterns, and a Markov chain approach was applied to microsphere navigation, with the terminal location of microspheres determined to be in either normal hepatic parenchyma, hepatic tumor, or lung. A tumor uptake model was implemented to determine if microspheres get lodged in the tumor, and a probability was included in determining the shunt of microspheres to the lung. A sensitivity analysis of the model parameters was performed, and radiation segmentectomy/lobectomy procedures were simulated over a wide range of activity perfused. Then, the impact of using different microspheres, i.e., SIR-Sphere®, TheraSphere®, and QuiremSphere®, on the tumor-to-normal ratio (TNR), lung shunt fraction (LSF), and mean absorbed dose was analyzed.

resultsHighly vascularized tumors translated into increased TNR. Treatment results (TNR and LSF) were significantly more variable for microspheres with high particle load. In our scenarios with 1.5 GBq perfusion, TNR was maximum for TheraSphere® at calibration time in segmentectomy/lobar technique, for SIR-Sphere® at 1-3 days post-calibration, and regarding QuiremSphere® at 3 days post-calibration.

conclusionThis novel approach is a decisive step towards developing a personalized dosimetry framework for TARE. MIDOS assists in making clinical decisions in TARE treatment planning by assessing various delivery parameters and simulating different tumor uptakes. MIDOS offers evaluation of treatment outcomes, such as TNR and LSF, and quantitative scenario-specific decisions.

Indexed as

Liver NeoplasmsMicrospheresRadiometryRadiotherapy Planning, Computer-AssistedStochastic ProcessesEmbolization, TherapeuticFemaleHumansMaleModels, BiologicalMicrospheresRadioembolizationSegmentectomyTumor uptakeYttrium-90

Identifiers

PMID38155237
PMCPMC11043005
OpenAlexW4390368293

What OpenQuestion holds

Textmetadata
LicenceTDM
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.