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European Journal of Nuclear Medicine and Molecular Imaging

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07.04.2021 | Original Article

Multivariate radiomics models based on ¹⁸F-FDG hybrid PET/MRI for distinguishing between Parkinson’s disease and multiple system atrophy

verfasst von: Xuehan Hu, Xun Sun, Fan Hu, Fang Liu, Weiwei Ruan, Tingfan Wu, Rui An, Xiaoli Lan

Erschienen in: European Journal of Nuclear Medicine and Molecular Imaging | Ausgabe 11/2021

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Abstract

Purpose

To construct multivariate radiomics models using hybrid ¹⁸F-FDG PET/MRI for distinguishing between Parkinson’s disease (PD) and multiple system atrophy (MSA).

Methods

Ninety patients (60 with PD and 30 with MSA) were randomized to training and test sets in a 7:3 ratio. All patients underwent ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) PET/MRI to simultaneously obtain metabolic images (¹⁸F-FDG), structural MRI images (T1-weighted imaging (T1WI), T2-weighted imaging (T2WI) and T2-weighted fluid-attenuated inversion recovery (T2/FLAIR)) and functional MRI images (susceptibility-weighted imaging (SWI) and apparent diffusion coefficient). Using PET and five MRI sequences, we extracted 1172 radiomics features from the putamina and caudate nuclei. The radiomics signatures were constructed with the least absolute shrinkage and selection operator algorithm in the training set, with progressive optimization through single-sequence and double-sequence radiomics models. Multivariable logistic regression analysis was used to develop a clinical-radiomics model, combining the optimal multi-sequence radiomics signature with clinical characteristics and SUV values. The diagnostic performance of the models was assessed by receiver operating characteristic and decision curve analysis (DCA).

Results

The radiomics signatures showed favourable diagnostic efficacy. The optimal model comprised structural (T1WI), functional (SWI) and metabolic (¹⁸F-FDG) sequences (Radscore_{FDG_T1WI_SWI}) with the area under curves (AUCs) of the training and test sets of 0.971 and 0.957, respectively. The integrated model, incorporating Radscore_{FDG_T1WI_SWI}, three clinical symptoms (disease duration, dysarthria and autonomic failure) and SUV_max, demonstrated satisfactory calibration and discrimination in the training and test sets (0.993 and 0.994, respectively). DCA indicated the highest clinical benefit of the clinical-radiomics integrated model.

Conclusions

The radiomics signature with metabolic, structural and functional information provided by hybrid ¹⁸F-FDG PET/MRI may achieve promising diagnostic efficacy for distinguishing between PD and MSA. The clinical-radiomics integrated model performed best.

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Titel: Multivariate radiomics models based on 18F-FDG hybrid PET/MRI for distinguishing between Parkinson’s disease and multiple system atrophy
verfasst von: Xuehan Hu
Xun Sun
Fan Hu
Fang Liu
Weiwei Ruan
Tingfan Wu
Rui An
Xiaoli Lan
Publikationsdatum: 07.04.2021
Verlag: Springer Berlin Heidelberg
Erschienen in: European Journal of Nuclear Medicine and Molecular Imaging / Ausgabe 11/2021
Print ISSN: 1619-7070
Elektronische ISSN: 1619-7089
DOI: https://doi.org/10.1007/s00259-021-05325-z

Springer Medizin

Abstract

Purpose

Methods

Results

Conclusions

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