Litcius/Paper detail

Machine Learning-Based Noninvasive Quantification of Single-Imaging Session Dual-Tracer <sup>18</sup>F-FDG and <sup>68</sup>Ga-DOTATATE Dynamic PET-CT in Oncology

Wenxiang Ding, Jiangyuan Yu, Chaojie Zheng, Peng Fu, Qiu Huang, Dagan Feng, Zhi Yang, Richard L. Wahl, Yun Zhou

2021IEEE Transactions on Medical Imaging29 citationsDOI

Abstract

<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">68</sup> Ga-DOTATATE PET-CT is routinely used for imaging neuroendocrine tumor (NET) somatostatin receptor subtype 2 (SSTR2) density in patients, and is complementary to FDG PET-CT for improving the accuracy of NET detection, characterization, grading, staging, and predicting/monitoring NET responses to treatment. Performing sequential <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">18</sup> F-FDG and <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">68</sup> Ga-DOTATATE PET scans would require 2 or more days and can delay patient care. To align temporal and spatial measurements of <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">18</sup> F-FDG and <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">68</sup> Ga-DOTATATE PET, and to reduce scan time and CT radiation exposure to patients, we propose a single-imaging session dual-tracer dynamic PET acquisition protocol in the study. A recurrent extreme gradient boosting (rXGBoost) machine learning algorithm was proposed to separate the mixed <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">18</sup> F-FDG and <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">68</sup> Ga-DOTATATE time activity curves (TACs) for the region of interest (ROI) based quantification with tracer kinetic modeling. A conventional parallel multi-tracer compartment modeling method was also implemented for reference. Single-scan dual-tracer dynamic PET was simulated from 12 NET patient studies with <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">18</sup> F-FDG and <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">68</sup> Ga-DOTATATE 45-min dynamic PET scans separately obtained within 2 days. Our experimental results suggested an <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">18</sup> F-FDG injection first followed by <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">68</sup> Ga-DOTATATE with a minimum 5 min delayed injection protocol for the separation of mixed <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">18</sup> F-FDG and <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">68</sup> Ga-DOTATATE TACs using rXGBoost algorithm followed by tracer kinetic modeling is highly feasible.

Topics & Concepts

Nuclear medicinePositron emission tomographyTRACERPET-CTNeuroendocrine tumorsSomatostatin receptorMedicineComputer scienceSomatostatinPhysicsInternal medicineNuclear physicsMedical Imaging Techniques and ApplicationsNeuroendocrine Tumor Research AdvancesNeuroblastoma Research and Treatments
Machine Learning-Based Noninvasive Quantification of Single-Imaging Session Dual-Tracer <sup>18</sup>F-FDG and <sup>68</sup>Ga-DOTATATE Dynamic PET-CT in Oncology | Litcius