Effects of Tracer Uptake Time in Non–Small Cell Lung Cancer 18 F-FDG PET Radiomics

The Journal of Nuclear Medicine

article

Guilherme D. Kolinger¹  David Vállez García¹  Gerbrand Maria Kramer²  Virginie Frings²  Gerben J.C. Zwezerijnen²  Egbert F. Smit³  Adrianus Johannes de Langen⁴  Irène Buvat⁵  Ronald Boellaard¹ 

[1] Medical Imaging Center, University Medical Center Groningen, University of Groningen;Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, VU Medical Center;Department of Pulmonology, Amsterdam University Medical Center, VU Medical Center;Department of Thoracic Oncology, Antoni van Leeuwenhoek Hospital;Laboratoire d’Imagerie Translationnelle en Oncologie, INSERM, Institut Curie, Université Paris-Saclay

关键词: PET;    radiomics;    texture analysis;    repeatability;    dual-time-point;   

DOI  :  10.2967/jnumed.121.262660

学科分类：医学（综合）

来源: Society of Nuclear Medicine

【 摘 要 】

PET radiomics applied to oncology allow the measurement of intratumoral heterogeneity. This quantification can be affected by image protocols; hence, there is an increased interest in understanding how radiomic expression on PET images is affected by different imaging conditions. To address that interest, this study explored how radiomic features are affected by changes in 18F-FDG uptake time, image reconstruction, lesion delineation, and radiomic binning settings. Methods: Ten non–small cell lung cancer patients underwent 18F-FDG PET on 2 consecutive days. On each day, scans were obtained at 60 and 90 min after injection and reconstructed following EARL version 1 and with point-spread-function resolution modeling (PSF-EARL2). Lesions were delineated with an SUV threshold of 4.0, with 40% of SUVmax, and with a contrast-based isocontour. PET image intensity was discretized with both a fixed bin width (FBW) and a fixed bin number before the calculation of the radiomic features. Repeatability of features was measured with the intraclass correlation coefficient, and the change in feature value over time was calculated as a function of its repeatability. Features were then classified into use-case scenarios based on their repeatability and susceptibility to tracer uptake time. Results: With PSF-EARL2 reconstruction, 40% of SUVmax 0.9), 35% being classified for dual-time-point use cases as being sensitive to changes in uptake time, 39% were classified for cross-sectional studies with an unclear dependency on time, 20% were classified for cross-sectional use while being robust to uptake time changes, and 6% were discarded for poor repeatability. EARL version 1 images had 1 fewer repeatable feature (neighborhood gray-level different matrix coarseness) than PSF-EARL2; the contrast-based delineation had the poorest repeatability of the delineation methods, with 45% of features being discarded; and fixed bin number resulted in lower repeatability than FBW (45% and 6% of features were discarded, respectively). Conclusion: Repeatability was maximized with PSF-EARL2 reconstruction, lesion delineation at 40% of SUVmax, and FBW intensity discretization. On the basis of their susceptibility to uptake time, radiomic features were classified into specific non–small cell lung cancer PET radiomics use cases.

【 授权许可】

CC BY