Comparative assessment of methods for estimating tumor volume and standardized uptake value in (18)F-FDG PET

Autor: Kaya Doyeux, P. Tylski, Nicolas Grotus, Isabelle Gardin, Bruno Vanderlinden, Irène Buvat, Sébastien Hapdey, Simon Stute
Přispěvatelé: Imagerie et Modélisation en Neurobiologie et Cancérologie (IMNC (UMR_8165)), Université Paris-Sud - Paris 11 (UP11)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), service de radiothérapie et de physique médicale, Centre de Lutte Contre le Cancer Henri Becquerel Normandie Rouen (CLCC Henri Becquerel), Service de médecine nucléaire [Rouen], CRLCC Haute Normandie-Centre de Lutte Contre le Cancer Henri Becquerel Normandie Rouen (CLCC Henri Becquerel), Equipe Quantification en Imagerie Fonctionnelle (QuantIF-LITIS), Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes (LITIS), Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Université Le Havre Normandie (ULH), Normandie Université (NU)-Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Normandie Université (NU), Breton, Céline, Institut Jules Bordet [Bruxelles], Faculté de Médecine [Bruxelles] (ULB), Université libre de Bruxelles (ULB)-Université libre de Bruxelles (ULB), Université Le Havre Normandie (ULH), Normandie Université (NU)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA), CRLCC Henri Becquerel, CRLCC Haute Normandie-CRLCC Henri Becquerel, Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Le Havre Normandie (ULH), Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)
Jazyk: angličtina
Rok vydání: 2010
Předmět:
[SDV]Life Sciences [q-bio]
Standardized uptake value
MESH: Algorithms
[SDV.CAN]Life Sciences [q-bio]/Cancer
MESH: Monte Carlo Method
Imaging phantom
030218 nuclear medicine & medical imaging
MESH: Differential Threshold
03 medical and health sciences
MESH: Software
0302 clinical medicine
MESH: Computer Simulation
[SDV.CAN] Life Sciences [q-bio]/Cancer
MESH: Liver Neoplasms
MESH: Fluorodeoxyglucose F18
MESH: Artificial Intelligence
MESH: Pattern Recognition
Automated
Radiology
Nuclear Medicine and imaging
MESH: Neoplasms
[SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]
Mathematics
MESH: Fluorine Radioisotopes
MESH: Humans
business.industry
Active volume
MESH: Models
Biological
MESH: Positron-Emission Tomography
MESH: Sensitivity and Specificity
MESH: Lung Neoplasms
Volume measurements
MESH: Reproducibility of Results
[SDV] Life Sciences [q-bio]
MESH: Phantoms
Imaging
Volume (thermodynamics)
030220 oncology & carcinogenesis
Anthropomorphic phantom
[SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]
MESH: Image Enhancement
Nuclear medicine
business
Estimation methods
MESH: Image Interpretation
Computer-Assisted
MESH: Radiopharmaceuticals
Tumor segmentation
Zdroj: Journal of Nuclear Medicine
Journal of Nuclear Medicine, Society of Nuclear Medicine, 2010, 51 (2), pp.268-76
Journal of Nuclear Medicine, Society of Nuclear Medicine, 2010, 51 (2), pp.268-76. ⟨10.2967/jnumed.109.066241⟩
Journal of Nuclear Medicine, 2010, 51 (2), pp.268-76. ⟨10.2967/jnumed.109.066241⟩
ISSN: 0161-5505
1535-5667
DOI: 10.2967/jnumed.109.066241⟩
Popis: International audience; In (18)F-FDG PET, tumors are often characterized by their metabolically active volume and standardized uptake value (SUV). However, many approaches have been proposed to estimate tumor volume and SUV from (18)F-FDG PET images, none of them being widely agreed upon. We assessed the accuracy and robustness of 5 methods for tumor volume estimates and of 10 methods for SUV estimates in a large variety of configurations. METHODS: PET acquisitions of an anthropomorphic phantom containing 17 spheres (volumes between 0.43 and 97 mL, sphere-to-surrounding-activity concentration ratios between 2 and 68) were used. Forty-one nonspheric tumors (volumes between 0.6 and 92 mL, SUV of 2, 4, and 8) were also simulated and inserted in a real patient (18)F-FDG PET scan. Four threshold-based methods (including one, T(bgd), accounting for background activity) and a model-based method (Fit) described in the literature were used for tumor volume measurements. The mean SUV in the resulting volumes were calculated, without and with partial-volume effect (PVE) correction, as well as the maximum SUV (SUV(max)). The parameters involved in the tumor segmentation and SUV estimation methods were optimized using 3 approaches, corresponding to getting the best of each method or testing each method in more realistic situations in which the parameters cannot be perfectly optimized. RESULTS: In the phantom and simulated data, the T(bgd) and Fit methods yielded the most accurate volume estimates, with mean errors of 2% +/- 11% and -8% +/- 21% in the most realistic situations. Considering the simulated data, all SUV not corrected for PVE had a mean bias between -31% and -46%, much larger than the bias observed with SUV(max) (-11% +/- 23%) or with the PVE-corrected SUV based on T(bgd) and Fit (-2% +/- 10% and 3% +/- 24%). CONCLUSION: The method used to estimate tumor volume and SUV greatly affects the reliability of the estimates. The T(bgd) and Fit methods yielded low errors in volume estimates in a broad range of situations. The PVE-corrected SUV based on T(bgd) and Fit were more accurate and reproducible than SUV(max).
Databáze: OpenAIRE
Externí odkaz: