AUTHOR=Indovina Luca , Scolozzi Valentina , Capotosti Amedeo , Sestini Stelvio , Taralli Silvia , Cusumano Davide , Giancipoli Romina Grazia , Ciasca Gabriele , Cardillo Giuseppe , Calcagni Maria Lucia 

TITLE=Short 2-[18F]Fluoro-2-Deoxy-D-Glucose PET Dynamic Acquisition Protocol to Evaluate the Influx Rate Constant by Regional Patlak Graphical Analysis in Patients With Non-Small-Cell Lung Cancer

JOURNAL=Frontiers in Medicine

VOLUME=Volume 8 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2021.725387

DOI=10.3389/fmed.2021.725387

ISSN=2296-858X

ABSTRACT=Purpose:  To test a short 2-[18F]FDG PET dynamic acquisition protocol to calculate Ki using regional Patlak graphical analysis in patients with non-small-cell lung cancer (NSCLC).
Methods: Twenty-four NSCLC patients undergone standard dynamic 2-[18F]FDG acquisitions (60min) were randomly divided in two groups. In group 1 (n=10), Popolation-Based Image-derived input function (pIDIF) was built using a mono-exponential trend (10-60min) and a leave-one-out cross-validation method was performed to validate pIDIF model. In group 2 (n=14), Ki was obtained by standard regional Patlak plot analysis using IDIF (0-60min) and tissue response (10-60min) curves from VOIs placed on descending thoracic aorta and tumor tissue respectively. Moreover, with our method, Patlak analysis was performed to obtain Ki,s using IDIFFitted curve obtained from PET counts (0-10min) followed by a mono-exponential coefficients of pIDIF (10-60min) and tissue response curve obtained from PET counts at 10min and between 40-60min, simulating two short dynamic acquisitions. Both IDIF and IDIFFitted curves were modelled to assume the value of 2-[18F]FDG plasma activity measured in the venous blood sampling performed at 45min in each patient. Spearman’s rank correlation, coefficient of determination, and Passing-Bablok regression were used for the comparison between Ki and Ki,s. Finally, Ki,s was obtained with our method in a separate group of patients (group 3, n=8) that actually perform two short dynamic acquisitions.
Results: pIDIF (10-60 min) was modelled with a monoexponential curve with the following fitted parmeters obtained in group 1: a=9.684, b=16.410 and c=0.068 min-1. The one leave-one-out cros-validation error was 0.4%. In patients of group 2, the mean values of Ki and Ki,s were 0.0442±0.0302 and 0.33±0.0298, respectively (R2=0.9970). The Passing-Bablok regression for comparison between Ki and Ki,s showed a slope of 0.992 (95% CI: 0.94-1.06) and intercept value of -0.0003 (95% CI: -0.0033 – 0.0011). 
Conclusions: Despite several practical limitations, like the need to position the patient twice and to perform two CT scans, our method contemplates two short 2-[18F]FDG dynamic acquisitions, a population-based input function model and a late venous blood sample in order to obtain robust and personalized input function and tissue response curves and to provide reliable regional Ki estimation.