Long-axial field-of-view PET/CT improves radiomics feature reliability.

Digital PET High sensitivity Long-axial field-of-view Positron-emission-tomography Radiomics Textural analysis Total-body Whole-body PET/CT

Journal

European journal of nuclear medicine and molecular imaging
ISSN: 1619-7089
Titre abrégé: Eur J Nucl Med Mol Imaging
Pays: Germany
ID NLM: 101140988

Informations de publication

Date de publication:
31 Oct 2024
Historique:
received: 04 12 2023
accepted: 11 09 2024
medline: 31 10 2024
pubmed: 31 10 2024
entrez: 31 10 2024
Statut: aheadofprint

Résumé

To assess the influence of long-axial field-of-view (LAFOV) PET/CT systems on radiomics feature reliability, to assess the suitability for short-duration or low-activity acquisitions for textural feature analysis and to investigate the influence of acceptance angle. 34 patients were analysed: twelve patients underwent oncological 2-[18F]-FDG PET/CT, fourteen [18F]PSMA-1007 and eight [68Ga]Ga-DOTATOC. Data were obtained using a 106 cm LAFOV system for 10 min. Sinograms were generated from list-mode data corresponding to scan durations of 2, 5, 10, 20, 30, 60, 120, 240, 360 and 600s using both standard (minimum ring difference MRD 85 crystals) and maximum acceptance angles (MRD 322). Target lesions were segmented and radiomics features were calculated. To assess feature correlation, Pearson's product-moment correlation coefficient (PPMCC) was calculated with respect to the full duration acquisition for MRD 85 and 322 respectively. The number of features with excellent (r > 0.9), moderate (r > 0.7 and < 0.9) and poor (r ≤ 0.7) correlation was compared as a measure of feature stability. Intra-class heterogeneity was assessed by means of the quartile coefficient of dispersion. As expected, PPMCC improved with acquisition time for all features. By 240s almost all features showed at least moderate agreement with the full count (C100%) data, and by 360s almost all showed excellent agreement. Compared to standard-axial field of view (SAFOV) equivalent scans, fewer features showed moderate or poor agreement, and this was most pronounced for [68Ga]Ga-DOTATOC. Data obtained at C100% at MRD 322 were better able to capture between-patient heterogeneities. The improved feature reliability at longer acquisition times and higher MRD demonstrate the advantages of high sensitivity LAFOV systems for reproducible and low-noise data. High fidelity between MRD 85 and MRD 322 was seen at all scan durations > 2s. When contrasted with data comparable to a simulated SAFOV acquisition, full-count and full-MRD data were better able to capture underlying feature heterogeneities.

Identifiants

pubmed: 39477863
doi: 10.1007/s00259-024-06921-5
pii: 10.1007/s00259-024-06921-5
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

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Auteurs

Ian L Alberts (IL)

Molecular Imaging and Therapy, BC Cancer - Vancouver, 600 West 10th Ave, Vancouver, BC, V5Z 1H5, Canada. ialberts@mail.ubc.ca.
Department of Nuclear Medicine, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland. ialberts@mail.ubc.ca.

Song Xue (S)

Department of Nuclear Medicine, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland.

Hasan Sari (H)

Department of Nuclear Medicine, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland.
Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland.

Lara Cavinato (L)

Department of Nuclear Medicine, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland.
Laboratory for Modelling and Scientific Computing, Department of Mathematics, Politecnico di Milano, Milan, 20133, Italy.

George Prenosil (G)

Department of Nuclear Medicine, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland.

Ali Afshar-Oromieh (A)

Department of Nuclear Medicine, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland.

Clemens Mingels (C)

Department of Nuclear Medicine, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland.

Kuangyu Shi (K)

Department of Nuclear Medicine, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland.

Federico Caobelli (F)

Department of Nuclear Medicine, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland.

Arman Rahmim (A)

Molecular Imaging and Therapy, BC Cancer - Vancouver, 600 West 10th Ave, Vancouver, BC, V5Z 1H5, Canada.
Department of Radiology, University of British Columbia, Vancouver, BC, V5Z 1M9, Canada.

Thomas Pyka (T)

Department of Nuclear Medicine, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland.

Axel Rominger (A)

Department of Nuclear Medicine, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland.

Classifications MeSH