guest ::
| Home > Publications database > 3D printing of radioactive wall-less PET phantoms improves threshold-based target delineation and quantification. > print |
| Home > Publications database > 3D printing of radioactive wall-less PET phantoms improves threshold-based target delineation and quantification. > print |
| 001 | 301901 | ||
| 005 | 20250610113540.0 | ||
| 024 | 7 | _ | |a 10.1186/s40658-025-00768-x |2 doi |
| 024 | 7 | _ | |a pmid:40478365 |2 pmid |
| 024 | 7 | _ | |a pmc:PMC12144006 |2 pmc |
| 037 | _ | _ | |a DKFZ-2025-01171 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Zounek, Adrian Jun |0 0000-0001-8765-1276 |b 0 |
| 245 | _ | _ | |a 3D printing of radioactive wall-less PET phantoms improves threshold-based target delineation and quantification. |
| 260 | _ | _ | |a Heidelberg |c 2025 |b SpringerOpen |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1749542157_29233 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a Validation 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.Radioactive 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.The 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. |
| 536 | _ | _ | |a 899 - ohne Topic (POF4-899) |0 G:(DE-HGF)POF4-899 |c POF4-899 |f POF IV |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de |
| 650 | _ | 7 | |a 3D printing |2 Other |
| 650 | _ | 7 | |a PET |2 Other |
| 650 | _ | 7 | |a Phantoms |2 Other |
| 650 | _ | 7 | |a Segmentation |2 Other |
| 700 | 1 | _ | |a Joerg, Nico Maximilian |b 1 |
| 700 | 1 | _ | |a Lindheimer, Felix |b 2 |
| 700 | 1 | _ | |a Zatcepin, Artem |b 3 |
| 700 | 1 | _ | |a Palumbo, Giovanna |b 4 |
| 700 | 1 | _ | |a Oos, Rosel |b 5 |
| 700 | 1 | _ | |a Delker, Astrid |b 6 |
| 700 | 1 | _ | |a Gildehaus, Franz Josef |b 7 |
| 700 | 1 | _ | |a Bollenbacher, Andreas |b 8 |
| 700 | 1 | _ | |a Boening, Guido |b 9 |
| 700 | 1 | _ | |a Bartenstein, Peter |b 10 |
| 700 | 1 | _ | |a Brendel, Matthias |0 P:(DE-HGF)0 |b 11 |
| 700 | 1 | _ | |a Albert, Nathalie Lisa |0 P:(DE-HGF)0 |b 12 |
| 700 | 1 | _ | |a Ziegler, Sibylle |b 13 |
| 700 | 1 | _ | |a Kaiser, Lena |b 14 |
| 773 | _ | _ | |a 10.1186/s40658-025-00768-x |g Vol. 12, no. 1, p. 53 |0 PERI:(DE-600)2768912-8 |n 1 |p 53 |t EJNMMI Physics |v 12 |y 2025 |x 2197-7364 |
| 909 | C | O | |o oai:inrepo02.dkfz.de:301901 |p VDB |
| 910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 11 |6 P:(DE-HGF)0 |
| 910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 12 |6 P:(DE-HGF)0 |
| 913 | 1 | _ | |a DE-HGF |b Programmungebundene Forschung |l ohne Programm |1 G:(DE-HGF)POF4-890 |0 G:(DE-HGF)POF4-899 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-800 |4 G:(DE-HGF)POF |v ohne Topic |x 0 |
| 914 | 1 | _ | |y 2025 |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b EJNMMI PHYS : 2022 |d 2024-12-31 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2024-12-31 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2024-12-31 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0501 |2 StatID |b DOAJ Seal |d 2024-04-10T15:38:06Z |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0500 |2 StatID |b DOAJ |d 2024-04-10T15:38:06Z |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b DOAJ : Anonymous peer review |d 2024-04-10T15:38:06Z |
| 915 | _ | _ | |a Creative Commons Attribution CC BY (No Version) |0 LIC:(DE-HGF)CCBYNV |2 V:(DE-HGF) |b DOAJ |d 2024-04-10T15:38:06Z |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0600 |2 StatID |b Ebsco Academic Search |d 2024-12-31 |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b ASC |d 2024-12-31 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2024-12-31 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2024-12-31 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1110 |2 StatID |b Current Contents - Clinical Medicine |d 2024-12-31 |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0113 |2 StatID |b Science Citation Index Expanded |d 2024-12-31 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2024-12-31 |
| 915 | _ | _ | |a IF < 5 |0 StatID:(DE-HGF)9900 |2 StatID |d 2024-12-31 |
| 915 | _ | _ | |a Article Processing Charges |0 StatID:(DE-HGF)0561 |2 StatID |d 2024-12-31 |
| 915 | _ | _ | |a Fees |0 StatID:(DE-HGF)0700 |2 StatID |d 2024-12-31 |
| 920 | 1 | _ | |0 I:(DE-He78)MU01-20160331 |k MU01 |l DKTK Koordinierungsstelle München |x 0 |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a I:(DE-He78)MU01-20160331 |
| 980 | _ | _ | |a UNRESTRICTED |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|