Cargando…

Impact of partial-volume correction in oncological PET studies: a systematic review and meta-analysis

PURPOSE: Positron-emission tomography can be useful in oncology for diagnosis, (re)staging, determining prognosis, and response assessment. However, partial-volume effects hamper accurate quantification of lesions <2–3× the PET system’s spatial resolution, and the clinical impact of this is not e...

Descripción completa

Detalles Bibliográficos
Autores principales:	Cysouw, Matthijs C. F., Kramer, Gerbrand M., Schoonmade, Linda J., Boellaard, Ronald, de Vet, Henrica C. W., Hoekstra, Otto S.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Springer Berlin Heidelberg 2017
Materias:	Review Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5656693/ https://www.ncbi.nlm.nih.gov/pubmed/28776088 http://dx.doi.org/10.1007/s00259-017-3775-4

Ejemplares similares

Partial volume correction strategies for quantitative FDG PET in oncology
por: Hoetjes, Nikie J., et al.
Publicado: (2010)

Partial-volume correction in dynamic PET-CT: effect on tumor kinetic parameter estimation and validation of simplified metrics
por: Cysouw, M. C. F., et al.
Publicado: (2019)

Sensitivity of (18)F-fluorodihydrotestosterone PET-CT to count statistics and reconstruction protocol in metastatic castration-resistant prostate cancer
por: Cysouw, Matthijs C. F., et al.
Publicado: (2019)

Comparing lesion and feature selections to predict progression in newly diagnosed DLBCL patients with FDG PET/CT radiomics features
por: Eertink, Jakoba J., et al.
Publicado: (2022)

Repeatability of [(18)F]FDG PET/CT total metabolic active tumour volume and total tumour burden in NSCLC patients
por: Kolinger, Guilherme D., et al.
Publicado: (2019)

A method for model-free partial volume correction in oncological PET
por: Hofheinz, Frank, et al.
Publicado: (2012)

Partial volume correction of brain PET studies using iterative deconvolution in combination with HYPR denoising
por: Golla, Sandeep S. V., et al.
Publicado: (2017)

Machine learning-based analysis of [(18)F]DCFPyL PET radiomics for risk stratification in primary prostate cancer
por: Cysouw, Matthijs C. F., et al.
Publicado: (2020)

A Partial Volume Effect Correction Tailored for (18)F-FDG-PET Oncological Studies
por: Gallivanone, F., et al.
Publicado: (2013)

Optimizing Workflows for Fast and Reliable Metabolic Tumor Volume Measurements in Diffuse Large B Cell Lymphoma
por: Burggraaff, Coreline N., et al.
Publicado: (2020)

Metabolically active tumour volume segmentation from dynamic [(18)F]FLT PET studies in non-small cell lung cancer
por: Hoyng, Lieke L, et al.
Publicado: (2015)

Repeatability of Radiomic Features in Non-Small-Cell Lung Cancer [(18)F]FDG-PET/CT Studies: Impact of Reconstruction and Delineation
por: van Velden, Floris H. P., et al.
Publicado: (2016)

(18)F-FDG PET baseline radiomics features improve the prediction of treatment outcome in diffuse large B-cell lymphoma
por: Eertink, Jakoba J., et al.
Publicado: (2021)

External validation: a simulation study to compare cross-validation versus holdout or external testing to assess the performance of clinical prediction models using PET data from DLBCL patients
por: Eertink, Jakoba J., et al.
Publicado: (2022)

Updating PET/CT performance standards and PET/CT interpretation criteria should go hand in hand
por: Boellaard, Ronald, et al.
Publicado: (2019)

Repeatability of two semi-automatic artificial intelligence approaches for tumor segmentation in PET
por: Pfaehler, Elisabeth, et al.
Publicado: (2021)

Evaluation of a cumulative SUV-volume histogram method for parameterizing heterogeneous intratumoural FDG uptake in non-small cell lung cancer PET studies
por: van Velden, Floris H. P., et al.
Publicado: (2011)

Noise-Induced Variability of Immuno-PET with Zirconium-89-Labeled Antibodies: an Analysis Based on Count-Reduced Clinical Images
por: Jauw, Yvonne W. S., et al.
Publicado: (2018)

Optimization and validation of (18)F-DCFPyL PET radiomics-based machine learning models in intermediate- to high-risk primary prostate cancer
por: Luining, Wietske I., et al.
Publicado: (2023)

Interobserver reproducibility of tumor uptake quantification with (89)Zr-immuno-PET: a multicenter analysis
por: Jauw, Yvonne W. S., et al.
Publicado: (2019)

Measurement of metabolic tumor volume: static versus dynamic FDG scans
por: Cheebsumon, Patsuree, et al.
Publicado: (2011)

Reproducibility of [18F]FDG PET/CT liver SUV as reference or normalisation factor
por: Zwezerijnen, Gerben J. C., et al.
Publicado: (2022)

Effects of Reusing Baseline Volumes of Interest by Applying (Non-)Rigid Image Registration on Positron Emission Tomography Response Assessments
por: van Velden, Floris H. P., et al.
Publicado: (2014)

A Comparison of Partial Volume Correction Techniques for Measuring Change in Serial Amyloid PET SUVR
por: Schwarz, Christopher G., et al.
Publicado: (2019)

Measuring response to therapy using FDG PET: semi-quantitative and full kinetic analysis
por: Cheebsumon, Patsuree, et al.
Publicado: (2011)

PET segmentation of bulky tumors: Strategies and workflows to improve inter-observer variability
por: Pfaehler, Elisabeth, et al.
Publicado: (2020)

Targeting PSMA Revolutionizes the Role of Nuclear Medicine in Diagnosis and Treatment of Prostate Cancer
por: Luining, Wietske I., et al.
Publicado: (2022)

Classification of negative and positive (18)F-florbetapir brain PET studies in subjective cognitive decline patients using a convolutional neural network
por: de Vries, Bart Marius, et al.
Publicado: (2020)

Impact of [(18)F]FDG PET imaging parameters on automatic tumour delineation: need for improved tumour delineation methodology
por: Cheebsumon, Patsuree, et al.
Publicado: (2011)

Guidelines for quality control of PET/CT scans in a multicenter clinical study
por: Hristova, Ivalina, et al.
Publicado: (2017)

A Clinical and Experimental Comparison of Time of Flight PET/MRI and PET/CT Systems
por: Oprea-Lager, Daniela E., et al.
Publicado: (2015)

Pitfalls in quantitative myocardial PET perfusion I: Myocardial partial volume correction
por: Lance Gould, K., et al.
Publicado: (2020)

Effects of Tracer Uptake Time in Non–Small Cell Lung Cancer (18)F-FDG PET Radiomics
por: Kolinger, Guilherme D., et al.
Publicado: (2022)

Volume of interest delineation techniques for (18)F-FDG PET-CT scans during neoadjuvant extremity soft tissue sarcoma treatment in adults: a feasibility study
por: Stevenson, Marc G., et al.
Publicado: (2018)

Convolutional neural networks for automatic image quality control and EARL compliance of PET images
por: Pfaehler, Elisabeth, et al.
Publicado: (2022)

Combining MRI with PET for partial volume correction improves image-derived input functions in mice
por: Evans, Eleanor, et al.
Publicado: (2014)

EANM/EARL harmonization strategies in PET quantification: from daily practice to multicentre oncological studies
por: Aide, Nicolas, et al.
Publicado: (2017)

Quantitative implications of the updated EARL 2019 PET–CT performance standards
por: Kaalep, Andres, et al.
Publicado: (2019)

Impact of PET/CT system, reconstruction protocol, data analysis method, and repositioning on PET/CT precision: An experimental evaluation using an oncology and brain phantom
por: Mansor, Syahir, et al.
Publicado: (2017)

Region-Based Partial Volume Correction Techniques for PET Imaging: Sinogram Implementation and Robustness
por: Sattarivand, Mike, et al.
Publicado: (2013)

Cannot write session to /tmp/vufind_sessions/sess_pc0538lhriiu3mfn9t45claqst