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Somatostatin receptor subtype expression and radiomics from DWI-MRI represent SUV of [68Ga]Ga-DOTATOC PET in patients with meningioma.
Iglseder, Sarah; Iglseder, Anna; Beliveau, Vincent; Heugenhauser, Johanna; Gizewski, Elke R; Kerschbaumer, Johannes; Stockhammer, Guenther; Uprimny, Christian; Virgolini, Irene; Dudas, Jozsef; Nevinny-Stickel, Meinhard; Nowosielski, Martha; Scherfler, Christoph.
Afiliación
  • Iglseder S; Department of Neurology, Innsbruck Medical University, Innsbruck, Austria.
  • Iglseder A; Department of Geodesy and Geoinformation, Technical University Vienna, Vienna, Austria.
  • Beliveau V; Department of Neurology, Innsbruck Medical University, Innsbruck, Austria.
  • Heugenhauser J; Neuroimaging Research Core Facility, Innsbruck Medical University, Innsbruck, Austria.
  • Gizewski ER; Department of Neurology, Innsbruck Medical University, Innsbruck, Austria.
  • Kerschbaumer J; Neuroimaging Research Core Facility, Innsbruck Medical University, Innsbruck, Austria.
  • Stockhammer G; Department of Neuroradiology, Innsbruck Medical University, Innsbruck, Austria.
  • Uprimny C; Department of Neurosurgery, Innsbruck Medical University, Innsbruck, Austria.
  • Virgolini I; Department of Neurology, Innsbruck Medical University, Innsbruck, Austria.
  • Dudas J; Department of Nuclear Medicine, Innsbruck Medical University, Innsbruck, Austria.
  • Nevinny-Stickel M; Department of Nuclear Medicine, Innsbruck Medical University, Innsbruck, Austria.
  • Nowosielski M; Department of Otorhinolaryngology, Innsbruck Medical University, Innsbruck, Austria.
  • Scherfler C; Department of Therapeutic Radiology and Oncology, Innsbruck Medical University, Innsbruck, Austria.
J Neurooncol ; 164(3): 711-720, 2023 Sep.
Article en En | MEDLINE | ID: mdl-37707754
ABSTRACT

OBJECTIVE:

This retrospective study aimed to analyse the correlation between somatostatin receptor subtypes (SSTR 1-5) and maximum standardized uptake value (SUVmax) in meningioma patients using Gallium-68 DOTA-D-Phe1-Tyr3-octreotide Positron Emission Tomography ([68Ga]Ga-DOTATOC PET). Secondly, we developed a radiomic model based on apparent diffusion coefficient (ADC) maps derived from diffusion weighted magnetic resonance images (DWI MRI) to reproduce SUVmax.

METHOD:

The study included 51 patients who underwent MRI and [68Ga]Ga-DOTATOC PET before meningioma surgery. SUVmax values were quantified from PET images and tumour areas were segmented on post-contrast T1-weighted MRI and mapped to ADC maps. A total of 1940 radiomic features were extracted from the tumour area on each ADC map. A random forest regression model was trained to predict SUVmax and the model's performance was evaluated using repeated nested cross-validation. The expression of SSTR subtypes was quantified in 18 surgical specimens and compared to SUVmax values.

RESULTS:

The random forest regression model successfully predicted SUVmax values with a significant correlation observed in all 100 repeats (p < 0.05). The mean Pearson's r was 0.42 ± 0.07 SD, and the root mean square error (RMSE) was 28.46 ± 0.16. SSTR subtypes 2A, 2B, and 5 showed significant correlations with SUVmax values (p < 0.001, R2 = 0.669; p = 0.001, R2 = 0.393; and p = 0.012, R2 = 0.235, respectively).

CONCLUSION:

SSTR subtypes 2A, 2B, and 5 correlated significantly with SUVmax in meningioma patients. The developed radiomic model based on ADC maps effectively reproduces SUVmax using [68Ga]Ga-DOTATOC PET.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Compuestos Organometálicos / Neoplasias Meníngeas / Meningioma Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: J Neurooncol Año: 2023 Tipo del documento: Article País de afiliación: Austria

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Compuestos Organometálicos / Neoplasias Meníngeas / Meningioma Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: J Neurooncol Año: 2023 Tipo del documento: Article País de afiliación: Austria