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Nuklearmedizin. Nuclear medicine · 2005

Comparison of manual and automated quantification methods of 123I-ADAM.

Сравнительное исследованиеСтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАTwin StudyНазвание и аннотация: Перевод пока не подготовлен
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Kauppinen T, Koskela A, Diemling M, Keski-Rahkonen A, Sihvola E, Ahonen A

Аннотация

UNLABELLED: 123I-ADAM is a novel radioligand for imaging of the brain serotonin transporters (SERTs). Traditionally, the analysis of brain receptor studies has been based on observer-dependent manual region of interest definitions and visual interpretation. Our aim was to create a template for automated image registrations and volume of interest (VOI) quantifications and to show that an automated quantification method of 123I-ADAM is more repeatable than the manual method.

PATIENTS, METHODS: A template and a predefined VOI map was created from 123I-ADAM scans done for healthy volunteers (n = 15). Scans of another group of healthy persons (HS, n = 12) and patients with bulimia nervosa (BN, n = 10) were automatically fitted to the template and specific binding ratios (SBRs) were calculated by using the VOI map. Manual VOI definitions were done for the HS and BN groups by both one and two observers. The repeatability of the automated method was evaluated by using the BN group.

RESULTS: For the manual method, the interobserver coefficient of repeatability was 0.61 for the HS group and 1.00 for the BN group. The introobserver coefficient of repeatability for the BN group was 0.70. For the automated method, the coefficient of repeatability was 0.13 for SBRs in midbrain.

CONCLUSION: An automated quantification gives valuable information in addition to visual interpretation decreasing also the total image handling time and giving clear advantages for research work. An automated method for analysing 123I-ADAM binding to the brain SERT gives repeatable results for fitting the studies to the template and for calculating SBRs, and could therefore replace manual methods.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты