Evidence map›Paper›PMID 40478365›Full record

ArticleEJNMMI physics2025

3D printing of radioactive wall-less PET phantoms improves threshold-based target delineation and quantification.

Adrian Jun Zounek, Nico Maximilian Joerg, Felix Lindheimer, Artem Zatcepin, Giovanna Palumbo, Rosel Oos, Astrid Delker, Franz Josef Gildehaus, Andreas Bollenbacher, Guido Boening and 5 more

Abstract read
In one paragraph

Article in EJNMMI physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Applications of artificial intelligence in nuclear medicine.Zeitschrift fur medizinische Physik · 2026
    Review
  2. Enhancing PET/CT target assessment with porous 3D printed grids: a pilot study.Physical and engineering sciences in medicine · 2026
    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

15 authors.

Adrian Jun ZounekDepartment of Nuclear Medicine, LMU University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany. Adrian.Zounek@med.uni-muenchen.de.ORCID http://orcid.org/0000-0001-8765-1276
Nico Maximilian JoergDepartment of Nuclear Medicine, LMU University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
Felix LindheimerDepartment of Nuclear Medicine, LMU University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
Artem ZatcepinDepartment of Nuclear Medicine, LMU University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
Giovanna PalumboDepartment of Nuclear Medicine, LMU University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
Rosel OosDepartment of Nuclear Medicine, LMU University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
Astrid DelkerDepartment of Nuclear Medicine, LMU University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
Franz Josef GildehausDepartment of Nuclear Medicine, LMU University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
Andreas BollenbacherDepartment of Nuclear Medicine, LMU University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
Guido BoeningDepartment of Nuclear Medicine, LMU University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
Peter BartensteinDepartment of Nuclear Medicine, LMU University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
Matthias BrendelDepartment of Nuclear Medicine, LMU University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
Nathalie Lisa AlbertDepartment of Nuclear Medicine, LMU University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
Sibylle ZieglerDepartment of Nuclear Medicine, LMU University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
Lena KaiserDepartment of Nuclear Medicine, LMU University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.

Funding

Deutsche Forschungsgemeinschaft 390857198Deutsche Forschungsgemeinschaft 403161218Deutsche Forschungsgemeinschaft 421887978Friedrich-Baur-Stiftung 1172
6 · The paper itself

Abstract

backgroundValidation of threshold-based PET segmentation and PET quantification is typically performed with fillable phantoms. Theoretical considerations show that the inactive walls of the phantom cavities introduce a contrast dependence of the volume-reproducing threshold (VRT), potentially leading to segmentation errors and therefore miscalculations of target volumes. The goal of this study was to experimentally show the contrast independence of the VRT when using wall-less phantoms.

resultsRadioactive spheres were produced according to NEMA specifications (D = 10/13/17/22/28/37 mm) using a stereolithographic (SLA) 3D printer. For comparison, hollow spheres were filled with a similar activity concentration. Image data from both sphere types were acquired with five different signal-to-background ratios (SBR = 2/4/6/8/10) using a Siemens mCT 20 and a Biograph 64 TruePoint PET/CT system. Results from wall-less and fillable spheres were compared to evaluate contrast dependence and segmentation accuracy based on VRT and intensity profiles. Wall-less phantoms demonstrated consistent VRT values, with a coefficient of variation of 2% over all SBRs, indicating independence from contrast. Conversely, fillable phantoms exhibited significant VRT variability, with a coefficient of variation (CV) of 9% over all SBRs and up to 40% volume overestimation at low contrast. Additionally, activity distribution in the printed spheres was evaluated using PET-based statistical analysis and autoradiography. The PET intensity distribution in the printed material was highly uniform (CV = 4.2%), with a Kullback-Leibler divergence near zero and no statistically significant difference to the fillable spheres. Autoradiography revealed microscopic regions with elevated counts, showing a CV of 11.7%, which was effectively reduced to 2.4% after Gaussian filtering.

conclusionsThe theoretical predictions of a significant influence of inactive walls in low-contrast images and contrast-independent VRT in wall-less phantoms were successfully confirmed. SLA 3D printing of phantoms is a promising method for the reliable evaluation of PET quantification methods, particularly in low-contrast scenarios commonly encountered in clinical settings.

Indexed as

3D printingPETPhantomsSegmentation

Identifiers

PMID40478365
PMCPMC12144006

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Registered trials

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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.