FDG-PET combined with learning vector quantization allows classification of neurodegenerative diseases and reveals the trajectory of idiopathic REM sleep behavior disorder

Veen, Rick van; Meles, Sanne K.; Renken, Remco; Reesink, Fransje E.; Oertel, Wolfgang H.; Janzen, Annette; Vries, Gert-Jan de; Leenders, Klaus L.; Biehl, Michael

doi:10.1016/j.cmpb.2022.107042

Cited by 18 publications

(13 citation statements)

References 53 publications

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“…[ 56 ] showed that their 3-Sniffin'-Tick model had potential practicability and could be used to screen patients with RBD. Besides aforementioned studies, these studies [ 57 , 58 , 59 , 60 ] also showed that mathematical approaches or artificial intelligence analysis had a great prospect in RBD diagnosis.…”

Section: Discussionmentioning

confidence: 99%

The treatment efficacy of pharmacotherapies for rapid eye movement sleep behavior disorder with polysomnography evaluation: A systematic review and meta-analysis

Que

Zheng

Zhang

et al. 2022

Heliyon

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Section: Discussionmentioning

confidence: 99%

The treatment efficacy of pharmacotherapies for rapid eye movement sleep behavior disorder with polysomnography evaluation: A systematic review and meta-analysis

Que

Zheng

Zhang

et al. 2022

Heliyon

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“…SPM single-subject approach is applied mainly in neuroimaging research and clinical settings with an established role for differential diagnosis and prognosis at the individual level. On the other hand, because the differential diagnosis of neurodegenerative diseases comprises a complex, multi-class problem, SSM/PCA features may be the best with machine learning methods in the future ( van Veen et al, 2022 ).…”

Section: Discussionmentioning

confidence: 99%

Comparison of univariate and multivariate analyses for brain [18F]FDG PET data in α-synucleinopathies

Carli

Meles

Reesink

et al. 2023

NeuroImage: Clinical

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“…However, in addition to the DLBCL-specific changes, a wide range of overlapped brain regions was detected between the canonical PDRP and our proposed DLBCLRP. Other neurodegenerative disorders would exhibit greater variability with DLBCL in the disease-related metabolic pattern [ 49 , 51 – 53 ]. Furthermore, though we found that the established DLBCLRP could not be applied in another common type of lymphoma, HL, it is still unable to easily draw such a conclusion that this metabolic brain pattern can serve as a robust metabolic marker for the diagnosis of DLBCL.…”

Section: Discussionmentioning

confidence: 99%

The remodeling of metabolic brain pattern in patients with extracranial diffuse large B-cell lymphoma

Liu,

Tang,

Zhu

et al. 2023

EJNMMI Res

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Background Owing to the advances in diagnosis and therapy, survival or remission rates for lymphoma have improved prominently. Apart from the lymphoma- and chemotherapy-related somatic symptom burden, increasing attention has been drawn to the health-related quality of life. The application of 18F-fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG PET/CT) has been routinely recommended for the staging and response assessment of FDG-avid lymphoma. However, up till now, only a few researches have investigated the brain metabolic impairments in patients with pre-treatment lymphoma. The determination of the lymphoma-related metabolic brain pattern would facilitate exploring the tailored therapeutic regimen to alleviate not only the physiological, but also the psychological symptoms. In this retrospective study, we aimed to establish the diffuse large B-cell lymphoma-related pattern (DLBCLRP) of metabolic brain network and investigate the correlations between DLBCLRP and several indexes of the staging and response assessment. Results The established DLBCLRP was characterized by the increased metabolic activity in bilateral cerebellum, brainstem, thalamus, striatum, hippocampus, amygdala, parahippocampal gyrus and right middle temporal gyrus and by the decreased metabolic activity in bilateral occipital lobe, parietal lobe, anterior cingulate gyrus, midcingulate cortex and medial frontal gyrus. Significant difference in the baseline expression of DLBCLRP was found among complete metabolic response (CMR), partial metabolic response (PMR) and progressive metabolic disease (PMD) groups (P < 0.01). DLBCLRP expressions were also significantly or tended to be positively correlated with international prognostic index (IPI) (rs = 0.306, P < 0.05), lg(total metabolic tumor volume, TMTV) (r = 0.298, P < 0.05) and lg(total lesion glycolysis, TLG) (r = 0.233, P = 0.064). Though no significant correlation of DLBCLRP expression was found with Ann Arbor staging or tumor SUVmax (P > 0.05), the post-treatment declines of DLBCLRP expression were significantly positively correlated with Ann Arbor staging (rs = 0.284, P < 0.05) and IPI (rs = 0.297, P < 0.05). Conclusions The proposed DLBCLRP would lay the foundation for further investigating the cerebral dysfunction related to DLBCL itself and/or treatments. Besides, the expression of DLBCLRP was associated with the tumor burden of lymphoma, implying a potential biomarker for prognosis.

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FDG-PET combined with learning vector quantization allows classification of neurodegenerative diseases and reveals the trajectory of idiopathic REM sleep behavior disorder

Cited by 18 publications

References 53 publications

The treatment efficacy of pharmacotherapies for rapid eye movement sleep behavior disorder with polysomnography evaluation: A systematic review and meta-analysis

The treatment efficacy of pharmacotherapies for rapid eye movement sleep behavior disorder with polysomnography evaluation: A systematic review and meta-analysis

Comparison of univariate and multivariate analyses for brain [18F]FDG PET data in α-synucleinopathies

The remodeling of metabolic brain pattern in patients with extracranial diffuse large B-cell lymphoma

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