ArticleNeuroImage. Clinical2016
Application of texture analysis to DAT SPECT imaging: Relationship to clinical assessments.
Article in NeuroImage. Clinical, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 2 of them syntheses that pooled it.
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Who cites it
38 citing papers in PubMed, 2 syntheses or guidelines pooled it, 80 citations in OpenAlex.
- The differential diagnosis value of radiomics-based machine learning in Parkinson's disease: a systematic review and meta-analysis.Frontiers in aging neuroscience · 2023Pooled it
- EANM practice guideline/SNMMI procedure standard for dopaminergic imaging in Parkinsonian syndromes 1.0.European journal of nuclear medicine and molecular imaging · 2020Guideline
- Multivariate radiomics models based onEuropean journal of nuclear medicine and molecular imaging · 2021Trial
- Robustness of Radiomic Features in [Molecular imaging and biology · 2016Trial
- A stacked multi-classifier for multi-modal data fusion in transcranial sonography-based Parkinson's disease assessment.NPJ Parkinson's disease · 2026Article
- Prediction of impulse control disorders in Parkinson's disease through a longitudinal machine learning study.NPJ Parkinson's disease · 2026Article
- Robustness of textural analysis features in quantitativeEJNMMI physics · 2025Article
- Myocardial perfusion SPECT radiomic features reproducibility assessment: Impact of image reconstruction and harmonization.Medical physics · 2025Article
- The application of radiomics in the diagnosis and evaluation of cognitive impairment related to neurological diseases.Frontiers in neuroscience · 2025Review
- Radiomics score derived from T1-w/T2-w ratio image can predict motor symptom progression in Parkinson's disease.European radiology · 2024Article
- Disease-modifying therapies for Parkinson disease: lessons from multiple sclerosis.Nature reviews. Neurology · 2024Review
- Radiomics incorporating deep features for predicting Parkinson's disease inEJNMMI physics · 2024Article
- The effect of harmonization on the variability of PET radiomic features extracted using various segmentation methods.Annals of nuclear medicine · 2024Article
- Robustness of radiomic features in 123I-ioflupane-dopamine transporter single-photon emission computer tomography scan.PloS one · 2024Article
- Article
- Relevance ofEJNMMI research · 2023Article
- How Radiomics Can Improve Breast Cancer Diagnosis and Treatment.Journal of clinical medicine · 2023Review
- Real-world evidence on levodopa dose escalation in patients with Parkinson's disease treated with istradefylline.PloS one · 2023Article
- Radiomics insight into the neurodegenerative "Frontiers in nuclear medicine · 2023Review
- Development and validation of a radiomic model for the diagnosis of dopaminergic denervation on [18F]FDOPA PET/CT.European journal of nuclear medicine and molecular imaging · 2022Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Dopamine transporter (DAT) SPECT imaging is increasingly utilized for diagnostic purposes in suspected Parkinsonian syndromes. We performed a cross-sectional study to investigate whether assessment of texture in DAT SPECT radiotracer uptake enables enhanced correlations with severity of motor and cognitive symptoms in Parkinson's disease (PD), with the long-term goal of enabling clinical utility of DAT SPECT imaging, beyond standard diagnostic tasks, to tracking of progression in PD. Quantitative analysis in routine DAT SPECT imaging, if performed at all, has been restricted to assessment of mean regional uptake. We applied a framework wherein textural features were extracted from the images. Notably, the framework did not require registration to a common template, and worked in the subject-native space. Image analysis included registration of SPECT images onto corresponding MRI images, automatic region-of-interest (ROI) extraction on the MRI images, followed by computation of Haralick texture features. We analyzed 141 subjects from the Parkinson's Progressive Marker Initiative (PPMI) database, including 85 PD and 56 healthy controls (HC) (baseline scans with accompanying 3 T MRI images). We performed univariate and multivariate regression analyses between the quantitative metrics and different clinical measures, namely (i) the UPDRS (part III - motor) score, disease duration as measured from (ii) time of diagnosis (DD-diag.) and (iii) time of appearance of symptoms (DD-sympt.), as well as (iv) the Montreal Cognitive Assessment (MoCA) score. For conventional mean uptake analysis in the putamen, we showed significant correlations with clinical measures only when both HC and PD were included (Pearson correlation
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.