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Spreadsheet program for estimating recovery coefficient to get partial volume corrected standardized uptake value in clinical positron emission tomography-computed tomography studies

PURPOSE: To develop a spreadsheet program for estimation of recovery coefficient (RC) to get partial volume corrected (PVC) standardized uptake value (SUV) in clinical positron emission tomography-computed tomography (PET-CT) studies. MATERIALS AND METHODS: For formulation of this program we used da...

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Detalles Bibliográficos
Autores principales: Pandey, Anil Kumar, Sharma, Punit, Pandey, Manjesh, Aswathi, KK, Malhotra, Arun, Kumar, Rakesh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3665153/
https://www.ncbi.nlm.nih.gov/pubmed/23723579
http://dx.doi.org/10.4103/0972-3919.110688
Descripción
Sumario:PURPOSE: To develop a spreadsheet program for estimation of recovery coefficient (RC) to get partial volume corrected (PVC) standardized uptake value (SUV) in clinical positron emission tomography-computed tomography (PET-CT) studies. MATERIALS AND METHODS: For formulation of this program we used data from a phantom study conducted at our center in which a phantom with a sphere assembly (seven spheres-different diameters) was filled with 18F-Fluorodeoxyglucose solution to get a sphere/background ratio of 8:1, 10:1 and 12:1. PET-CT images were acquired. RC was then calculated from processed PET-CT images. We plotted graph of RC versus lesion-size at different sphere/background ratio using MS Excel function. There was logarithmic increase in RC with increase in lesion size. We fitted the data with a logarithmic equation and found optimum fit (least-square fit). We then validated this program with clinical data using 42 lung nodules in five patients. RESULTS: The program estimates the value of RC and object to background ratio in PET-CT for the input lesion-size and displays graph with trendline. When the user enters SUV and background activity measured in clinical PET-CT, it provides the value of RC and PVC SUV. It also validates the data entry and displays appropriate message. It is consistent, reproducible, accurate and provides output for wide range of lesion-sizes (71% of lesions evaluated); however, program does not give output for lesion-size < 9 mm. CONCLUSION: The present spreadsheet program is a useful and easy tool for calculating PVC SUV of clinical PET-CT lesions.