New 3D segmentation algorithm for modeling of kidney in positron emission tomography images

dc.contributor.authorRainio, Oona
dc.contributor.authorLatva-Rasku, Aino
dc.contributor.authorHirvonen, Jussi
dc.contributor.authorKnuuti, Juhani
dc.contributor.authorKlén, Riku
dc.contributor.organizationfi=InFLAMES Lippulaiva|en=InFLAMES Flagship|
dc.contributor.organizationfi=PET-keskus|en=Turku PET Centre|
dc.contributor.organizationfi=kliininen laitos|en=Department of Clinical Medicine|
dc.contributor.organizationfi=kuvantaminen ja kliininen diagnostiikka|en=Imaging and Clinical Diagnostics|
dc.contributor.organizationfi=tyks, vsshp|en=tyks, varha|
dc.contributor.organization-code1.2.246.10.2458963.20.14646305228
dc.contributor.organization-code1.2.246.10.2458963.20.61334543354
dc.contributor.organization-code1.2.246.10.2458963.20.68445910604
dc.contributor.organization-code1.2.246.10.2458963.20.69079168212
dc.converis.publication-id499014664
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/499014664
dc.date.accessioned2026-01-21T12:18:40Z
dc.date.available2026-01-21T12:18:40Z
dc.description.abstract<h3>Background</h3><p><br></p><p>¹⁵O-water positron emission tomography (PET) imaging enables noninvasive quantification of renal blood flow. While there are several existing methods automatically locating the volume of interest (VOI) for a kidney, separate cortex and medulla VOIs are needed for PET modeling due their functional differences. To assist in this, we introduce a new three-dimensional segmentation algorithm for kidney.</p><h3>Materials and methods</h3><p>Our algorithm chooses an initial kidney VOI, finds its longitudinal axis and the direction of the non-convex part, and then creates cortex and medulla VOIs and removes the renal vessel area from them. We evaluated the algorithm by using it to define cortex and medulla VOIs of left and right kidneys in dynamic total-body O-water PET images of 35 human patients. For all the 70 kidneys, we plotted the cross-section of the VOIs from three different anatomic directions and asked two expert physicians to assess their quality. Additionally, we computed cortical and medullary renal blood flow estimates by fitting a compartment model to the mean time-activity curves of our VOIs.</p><h3>Results</h3><p>According to the evaluation by the physicians, the cortex and medulla VOIs were mostly correct in all three directions for 78.6% of the total 70 kidneys and correct in at least one direction for 94.3% of the kidneys. The segmentation inaccuracies were typically caused by the algorithm placing cortex VOI partially outside of the kidney or in the medulla. However, regardless of these inaccuracies, all the VOIs were accurate enough to be used for compartment modeling. The resulting cortical and medullary blood flow were very close to the values reported in earlier studies with similar patient populations.</p><h3>Conclusion</h3><p>Our proposed algorithm can be used to create an automatic pipeline for accurate quantification of cortical and medullary tracer perfusion after a PET scan.</p>
dc.identifier.eissn2192-6670
dc.identifier.jour-issn2192-6662
dc.identifier.olddbid212326
dc.identifier.oldhandle10024/195344
dc.identifier.urihttps://www.utupub.fi/handle/11111/49732
dc.identifier.urlhttps://doi.org/10.1007/s13721-025-00534-0
dc.identifier.urnURN:NBN:fi-fe2025081282351
dc.language.isoen
dc.okm.affiliatedauthorRainio, Oona
dc.okm.affiliatedauthorLatva-Rasku, Aino
dc.okm.affiliatedauthorHirvonen, Jussi
dc.okm.affiliatedauthorKnuuti, Juhani
dc.okm.affiliatedauthorKlén, Riku
dc.okm.affiliatedauthorDataimport, tyks, vsshp
dc.okm.discipline113 Computer and information sciencesen_GB
dc.okm.discipline3121 Internal medicineen_GB
dc.okm.discipline3126 Surgery, anesthesiology, intensive care, radiologyen_GB
dc.okm.discipline113 Tietojenkäsittely ja informaatiotieteetfi_FI
dc.okm.discipline3121 Sisätauditfi_FI
dc.okm.discipline3126 Kirurgia, anestesiologia, tehohoito, radiologiafi_FI
dc.okm.internationalcopublicationnot an international co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA1 ScientificArticle
dc.publisherSPRINGER WIEN
dc.publisher.countryAustriaen_GB
dc.publisher.countryItävaltafi_FI
dc.publisher.country-codeAT
dc.publisher.placeVienna
dc.relation.articlenumber38
dc.relation.doi10.1007/s13721-025-00534-0
dc.relation.ispartofjournalNetwork Modeling Analysis in Health Informatics and Bioinformatics
dc.relation.issue1
dc.relation.volume14
dc.source.identifierhttps://www.utupub.fi/handle/10024/195344
dc.titleNew 3D segmentation algorithm for modeling of kidney in positron emission tomography images
dc.year.issued2025

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