Author:
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
Abstract
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.
Funder
University of Innsbruck and Medical University of Innsbruck
Publisher
Springer Science and Business Media LLC
Subject
Cancer Research,Neurology (clinical),Neurology,Oncology
Cited by
2 articles.
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