ArticleEuropean journal of nuclear medicine and molecular imaging2019
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Article in European journal of nuclear medicine and molecular imaging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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32 citing papers in PubMed, 46 citations in OpenAlex.
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- A study on 18F-FDG PET/CT imaging assessment of the anti-aging efficacy of BMMSCs in the macaque brain.Stem cells translational medicine · 2026Article
- Updates on Cardiac MRI and PET Imaging for the Diagnosis and Monitoring of Cardiac Sarcoidosis.Korean journal of radiology · 2025Review
- The Role of [18F]FDG PET-Based Radiomics and Machine Learning for the Evaluation of Cardiac Sarcoidosis: A Narrative Literature Review.Medicina (Kaunas, Lithuania) · 2025Review
- Noise-aware system generative model (NASGM): positron emission tomography (PET) image simulation framework with observer validation studies.Medical physics · 2025Article
- Review
- Role of Textural Analysis Parameters Derived from FDG PET/CT in Diagnosing Cardiac Sarcoidosis.World journal of nuclear medicine · 2024Article
- Machine learning approach usingJapanese journal of radiology · 2024Article
- CT texture analysis for differentiating between peritoneal carcinomatosis and peritoneal tuberculosis: a cross-sectional study.Abdominal radiology (New York) · 2024Article
- Physiological myocardialAsia Oceania journal of nuclear medicine & biology · 2024Article
- Impact of respiratory gating and ECG gating onJournal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023Article
- Texture analysis of SPECT myocardial perfusion provides prognostic value for dilated cardiomyopathy.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023Article
- MRI-based radiomics features uncover the micro-change of dorsal root ganglia lesion for patients with post-herpetic neuralgia.Frontiers in neurology · 2023Article
- Distinction of Lymphoma from Sarcoidosis onJournal of nuclear medicine : official publication, Society of Nuclear Medicine · 2022Article
- Development and evaluation of a radiomics model of restingAnnals of translational medicine · 2022Article
- Comparison of the Classification Results Accuracy for CT Soft Tissue and Bone Reconstructions in Detecting the Porosity of a Spongy Tissue.Journal of clinical medicine · 2022Article
- Is quantitative fluorine-18 fluorodeoxyglucose PET image analysis the key to Identify cardiac sarcoidosis?Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2022Article
- DWI-related texture analysis for prostate cancer: differences in correlation with histological aggressiveness and data repeatability between peripheral and transition zones.European radiology experimental · 2022Article
- Advances in Diagnostic Imaging for Cardiac Sarcoidosis.Journal of clinical medicine · 2021Review
- Radiomics feature reliability assessed by intraclass correlation coefficient: a systematic review.Quantitative imaging in medicine and surgery · 2021Review
Corrections and comments
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Authors and funding
13 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purpose
methodsThirty-seven CS patients (CS group), and 52 patients who underwent FDG PET/CT to detect malignant tumors with any FDG cardiac uptake (non-CS group) were studied. A total of 36 texture features from the histogram, gray-level co-occurrence matrix (GLCM), gray-level run length matrix (GLRLM), gray-level zone size matrix (GLZSM) and neighborhood gray-level difference matrix (NGLDM), were computed using polar map images. First, the inter-operator and inter-scan reproducibility of the texture features of the CS group were evaluated. Then, texture features of the patients with CS were compared to those without CS lesions.
resultsTwenty-eight of the 36 texture features showed high inter-operator reproducibility with intraclass correlation coefficients (ICCs) over 0.80. In addition, 17 of the 36 showed high inter-scan reproducibility with ICCs over 0.80. The SUVmax showed no difference between the CS and non-CS group [7.36 ± 2.77 vs. 8.78 ± 4.65, p = 0.45, area under the curve (AUC) = 0.60]. By contrast, 16 of the 36 texture features could distinguish CS from non-CS grsoup with AUC > 0.80. Multivariate logistic regression analysis after hierarchical clustering concluded that long-run emphasis (LRE; P = 0.0004) and short-run low gray-level emphasis (SRLGE; P = 0.016) were significant independent factors that could distinguish between the CS and non-CS groups. Specifically, LRE was significantly higher in CS than in non-CS (30.1 ± 25.4 vs. 11.4 ± 4.6, P < 0.0001), with high diagnostic ability (AUC = 0.91), and had high inter-operator reproducibility (ICC = 0.98).
conclusionsThe texture analysis had high inter-operator and high inter-scan reproducibility. Some of texture features showed higher diagnostic value than SUVmax for CS diagnosis. Therefore, texture analysis may have a role in semi-automated systems for diagnosing CS.
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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.