Evidence map›Paper›PMID 32632928›Full record

ArticleMedical physics2020

Comparison of commercial dosimetric software platforms in patients treated with

Erick Mora-Ramirez, Lore Santoro, Emmanuelle Cassol, Juan C Ocampo-Ramos, Naomi Clayton, Gunjan Kayal, Soufiane Chouaf, Dorian Trauchessec, Jean-Pierre Pouget, Pierre-Olivier Kotzki and 2 more

Open access · hybridAbstract read
In one paragraph

Article in Medical physics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 1 pooled it
3.6field-weighted citation impact, top 5% 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

29 citing papers in PubMed, 1 synthesis or guideline pooled it, 56 citations in OpenAlex.

  1. Dosimetry of [Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2024
    Pooled it
  2. Review
  3. Validation of Simplified Renal Dosimetry Protocols forMolecular imaging and radionuclide therapy · 2026
    Article
  4. Review
  5. Review
  6. OpenDose3D: A Free, Open-Source Clinical Dosimetry Software for Patient-Specific Dosimetry.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2026
    Article
  7. Article
  8. Dosimetry Software for Theranostic Applications: Current Capabilities and Future Prospects.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2025
    Review
  9. MIRD Pamphlet No. 30: MIRDfit-A Tool for Fitting of Biodistribution Time-Activity Data for Internal Dosimetry.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2024
    Article
  10. Article
  11. Review
  12. Automated segmentation of lesions and organs at risk on [Cancer imaging : the official publication of the International Cancer Imaging Society · 2024
    Article
  13. Article
  14. Article
  15. An International Study of Factors Affecting Variability of Dosimetry Calculations, Part 2: Overall Variabilities in Absorbed Dose.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2023
    Article
  16. EANM enabling guide: how to improve the accessibility of clinical dosimetry.European journal of nuclear medicine and molecular imaging · 2023
    Article
  17. Review
  18. Article
  19. Milestones in dosimetry for nuclear medicine therapy.The British journal of radiology · 2022
    Review
  20. 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

12 authors at 7 institutions in 3 countries.

Erick Mora-RamirezCentre de Recherches en Cancérologie de Toulouse, UMR 1037, Toulouse, F-31037, France.
Lore SantoroDépartement de Médecine Nucléaire, Institut Régional du Cancer de Montpellier, Montpellier, F-34298, France.
Emmanuelle CassolCentre de Recherches en Cancérologie de Toulouse, UMR 1037, Toulouse, F-31037, France.
Juan C Ocampo-RamosCentre de Recherches en Cancérologie de Toulouse, UMR 1037, Toulouse, F-31037, France.
Naomi ClaytonCentre de Recherches en Cancérologie de Toulouse, UMR 1037, Toulouse, F-31037, France.
Gunjan KayalCentre de Recherches en Cancérologie de Toulouse, UMR 1037, Toulouse, F-31037, France.
Soufiane ChouafDépartement de Médecine Nucléaire, Institut Régional du Cancer de Montpellier, Montpellier, F-34298, France.
Dorian TrauchessecDépartement de Médecine Nucléaire, Institut Régional du Cancer de Montpellier, Montpellier, F-34298, France.
Jean-Pierre PougetInstitut de Recherche en Cancérologie de Montpellier (IRCM), Inserm U1194, Université de Montpellier, Institut Régional du Cancer de Montpellier (ICM), Montpellier, F-34298, France.
Pierre-Olivier KotzkiDépartement de Médecine Nucléaire, Institut Régional du Cancer de Montpellier, Montpellier, F-34298, France.
Emmanuel DeshayesDépartement de Médecine Nucléaire, Institut Régional du Cancer de Montpellier, Montpellier, F-34298, France.
Manuel BardièsCentre de Recherches en Cancérologie de Toulouse, UMR 1037, Toulouse, F-31037, France.
Centre de Recherche en Cancérologie de Toulouse · FRInstitut Regional du Cancer de Montpellier · FRInserm · FRInstitut de Recherche en Cancérologie de Montpellier · FRUniversidad de Costa Rica · CRUniversité de Montpellier · FRUniversité Toulouse III - Paul Sabatier · FR

Funding

French Institute for Central AmericaUniversity of Costa Rica
6 · The paper itself

Abstract

purposeThe aim of this study was to quantitatively compare five commercial dosimetric software platforms based on the analysis of clinical datasets of patients who benefited from peptide receptor radionuclide therapy (PRRT) with

methodsThe dosimetric analysis was performed on two patients during two cycles of PRRT with

resultsThe majority of organ mass estimates varied by <9.5% between all platforms. The highest variability for TIAC results between platforms was seen for the kidneys (28.2%) for the two patients and the two treatment cycles. Relative standard deviations in mean absorbed doses were slightly higher compared with those observed for TIAC, but remained of the same order of magnitude between all platforms.

conclusionsWhen applying a similar processing approach, results obtained were of the same order of magnitude regardless of the platforms used. However, the comparison of the performances of currently available platforms is still difficult as they do not all address the same parts of the dosimetric analysis workflow. In addition, the way in which data are handled in each part of the chain from data acquisition to absorbed doses may be different, which complicates the comparison exercise. Therefore, the dissemination of commercial solutions for absorbed dose calculation calls for the development of tools and standards allowing for the comparison of the performances between dosimetric software platforms.

Indexed as

Neuroendocrine TumorsHumansOctreotideRadioisotopesRadiopharmaceuticalsReceptors, PeptideSoftwareOctreotideRadioisotopesRadiopharmaceuticalsReceptors, Peptide177Lu-DOTATATEdosimetrydosimetry software platformsPRRT

Identifiers

PMID32632928
PMCPMC7589428
OpenAlexW3039639673

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.