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Automatic quantitative kinetic analysis in salivary gland scintigraphy.

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Názov: Automatic quantitative kinetic analysis in salivary gland scintigraphy.
Autori: Anton Faria R; Department of Nuclear Medicine, A.C.Camargo Cancer Center, São Paulo, Brazil., Chagas Jaguar G, Nóbrega Pereira Lima E
Zdroj: Nuclear medicine communications [Nucl Med Commun] 2025 Nov 01; Vol. 46 (11), pp. 1104-1114. Date of Electronic Publication: 2025 Jul 28.
Spôsob vydávania: Journal Article
Jazyk: English
Informácie o časopise: Publisher: Lippincott Williams & Wilkins Country of Publication: England NLM ID: 8201017 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1473-5628 (Electronic) Linking ISSN: 01433636 NLM ISO Abbreviation: Nucl Med Commun Subsets: MEDLINE
Imprint Name(s): Publication: London : Lippincott Williams & Wilkins
Original Publication: London : Chapman and Hall in association with the British Nuclear Medicine Society, c1980-
Výrazy zo slovníka MeSH: Salivary Glands*/diagnostic imaging , Salivary Glands*/metabolism , Radionuclide Imaging* , Image Processing, Computer-Assisted*/methods, Humans ; Kinetics ; Automation ; Female ; Middle Aged ; Male
Abstrakt: Salivary gland scintigraphy (SGS) is a valuable imaging modality for assessing major salivary gland function, particularly in patients with Sjögren syndrome, and postradiotherapy conditions. Despite the existence of multiple quantitative analysis methods, clinical practice remains dominated by qualitative interpretation due to the lack of standardization, time-consuming procedures, and absence of user-friendly tools. In this study, we present a fully automated method for quantitative SGS analysis based on kinetic modeling of time-activity curves, implemented without altering standard imaging protocols, using a software we developed in-house on a Xeleris (GE HealthCare) workstation. The curves were segmented into uptake, excretion, and postexcretion phases, each fitted to specific kinetic models. From the fitted parameters, we derived functional variables, including vascular flow, active uptake, uptake velocity, total accumulation, absolute excretion, excretion fraction, and excretion rate. This approach enables rapid and reproducible extraction of functional data, with processing time under 5 s per study. We demonstrate its clinical utility through two case studies, highlighting how kinetic parameters reflect salivary gland function and its longitudinal changes. Our method bridges the gap between complex quantitative analysis and practical clinical application, offering a robust tool for monitoring disease progression and treatment response, potentially improving diagnostic reliability and research scalability.
(Copyright © 2025 Wolters Kluwer Health, Inc. All rights reserved.)
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Contributed Indexing: Keywords: medical image processing; salivary glands; scintigraphy
Entry Date(s): Date Created: 20250728 Date Completed: 20251009 Latest Revision: 20251009
Update Code: 20251010
DOI: 10.1097/MNM.0000000000002037
PMID: 40717667
Databáza: MEDLINE
Popis
Abstrakt:Salivary gland scintigraphy (SGS) is a valuable imaging modality for assessing major salivary gland function, particularly in patients with Sjögren syndrome, and postradiotherapy conditions. Despite the existence of multiple quantitative analysis methods, clinical practice remains dominated by qualitative interpretation due to the lack of standardization, time-consuming procedures, and absence of user-friendly tools. In this study, we present a fully automated method for quantitative SGS analysis based on kinetic modeling of time-activity curves, implemented without altering standard imaging protocols, using a software we developed in-house on a Xeleris (GE HealthCare) workstation. The curves were segmented into uptake, excretion, and postexcretion phases, each fitted to specific kinetic models. From the fitted parameters, we derived functional variables, including vascular flow, active uptake, uptake velocity, total accumulation, absolute excretion, excretion fraction, and excretion rate. This approach enables rapid and reproducible extraction of functional data, with processing time under 5 s per study. We demonstrate its clinical utility through two case studies, highlighting how kinetic parameters reflect salivary gland function and its longitudinal changes. Our method bridges the gap between complex quantitative analysis and practical clinical application, offering a robust tool for monitoring disease progression and treatment response, potentially improving diagnostic reliability and research scalability.<br /> (Copyright © 2025 Wolters Kluwer Health, Inc. All rights reserved.)
ISSN:1473-5628
DOI:10.1097/MNM.0000000000002037