Investigation of total-body applicable compartment models for kinetic modeling in total body 15O-water perfusion PET imaging
| dc.contributor.author | Rainio, Oona | |
| dc.contributor.author | Knuuti, Juhani | |
| dc.contributor.author | Klén, Riku | |
| dc.contributor.organization | fi=InFLAMES Lippulaiva|en=InFLAMES Flagship| | |
| dc.contributor.organization | fi=PET-keskus|en=Turku PET Centre| | |
| dc.contributor.organization | fi=tyks, vsshp|en=tyks, varha| | |
| dc.contributor.organization-code | 1.2.246.10.2458963.20.14646305228 | |
| dc.contributor.organization-code | 1.2.246.10.2458963.20.68445910604 | |
| dc.converis.publication-id | 491759223 | |
| dc.converis.url | https://research.utu.fi/converis/portal/Publication/491759223 | |
| dc.date.accessioned | 2025-08-28T01:03:10Z | |
| dc.date.available | 2025-08-28T01:03:10Z | |
| dc.description.abstract | <p><strong>Abstract</strong></p><p>Dynamic total-body positron emission tomography (PET) imaging has recently become possible due to the introduction of new-generation imaging systems with increased axial field of view. This enables evaluation of kinetic modeling approaches using compartment models for the entire body simultaneously. Systematic evaluation of the conventionally used approaches is needed to find the best candidates among different compartment models for total body modeling of <sup>15</sup>O-water perfusion PET images. Six variations of the 1-tissue-compartment model (1TCM) are evaluated. The models are systematically fitted to mean time activity curves of 20 anatomic structures of interest extracted from a dynamic <sup>15</sup>O-water PET rest perfusion images of 58 human subjects, using an image-derived input function from the aorta. The impact of additional parameters for time delay correction (TDC), arterial volume fraction (AVF), and perfusable tissue fraction (PTF) is assessed. The models are evaluated with mean squared error, mean relative error (MRE), and Akaike information criterion (AIC) and by performing Wilcoxon signed-rank tests to see whether the found differences are statistically significant. For 11 out of the 20 anatomic structures, the best model in terms of median AIC was the 1TCM with AVF and TDC but without PTF. The use of TDC resulted in significantly lower AICs for all anatomic structures while the AVF and PTF parameters significantly improved the model performance only occasionally. Between the different organs, the models of pancreas, spleen, myocardium, the example rib, and brain performed very well in terms of MRE. In comparison, the investigated models worked poorly for liver and lung lobes. This paper serves as an initial attempt to evaluate potential approaches to derive an appropriate model for kinetic modeling in total body <sup>15</sup>O-water PET perfusion imaging. According to our research, the suitability of 1TCM using a single input function from the aorta in <sup>15</sup>O-water PET images depends on the organ of interest. Our results suggest that the use of 1TCM is justified for most anatomic structures and can be used to estimate the cerebral, myocardial, renal, and splenic blood flow. However, we recommend different models for quantification of hepatic and pulmonary blood flow.</p> | |
| dc.identifier.eissn | 2192-6670 | |
| dc.identifier.jour-issn | 2192-6662 | |
| dc.identifier.olddbid | 206927 | |
| dc.identifier.oldhandle | 10024/189954 | |
| dc.identifier.uri | https://www.utupub.fi/handle/11111/49482 | |
| dc.identifier.url | https://doi.org/10.1007/s13721-025-00515-3 | |
| dc.identifier.urn | URN:NBN:fi-fe2025082791430 | |
| dc.language.iso | en | |
| dc.okm.affiliatedauthor | Rainio, Oona | |
| dc.okm.affiliatedauthor | Knuuti, Juhani | |
| dc.okm.affiliatedauthor | Klén, Riku | |
| dc.okm.affiliatedauthor | Dataimport, tyks, vsshp | |
| dc.okm.discipline | 113 Computer and information sciences | en_GB |
| dc.okm.discipline | 217 Medical engineering | en_GB |
| dc.okm.discipline | 3126 Surgery, anesthesiology, intensive care, radiology | en_GB |
| dc.okm.discipline | 113 Tietojenkäsittely ja informaatiotieteet | fi_FI |
| dc.okm.discipline | 217 Lääketieteen tekniikka | fi_FI |
| dc.okm.discipline | 3126 Kirurgia, anestesiologia, tehohoito, radiologia | fi_FI |
| dc.okm.internationalcopublication | not an international co-publication | |
| dc.okm.internationality | International publication | |
| dc.okm.type | A1 ScientificArticle | |
| dc.publisher | Springer Nature | |
| dc.publisher.country | Austria | en_GB |
| dc.publisher.country | Itävalta | fi_FI |
| dc.publisher.country-code | AT | |
| dc.relation.articlenumber | 22 | |
| dc.relation.doi | 10.1007/s13721-025-00515-3 | |
| dc.relation.ispartofjournal | Network Modeling Analysis in Health Informatics and Bioinformatics | |
| dc.relation.volume | 14 | |
| dc.source.identifier | https://www.utupub.fi/handle/10024/189954 | |
| dc.title | Investigation of total-body applicable compartment models for kinetic modeling in total body 15O-water perfusion PET imaging | |
| dc.year.issued | 2025 |
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