Value of Patlak Ki images from 18F-FDG-PET/CT for evaluation of the relationships between disease activity and clinical events in cardiac sarcoidosis

Nakajo, Masatoyo; Ojima, Satoko; Kawakami, Hirofumi; Tani, Akio; Hirayama, Akira; Jinguji, Megumi; Kubozono, Takuro; Ohishi, Mitsuru; Yamada, Takashi

doi:10.1038/s41598-021-82217-0

Cited by 10 publications

(4 citation statements)

References 35 publications

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“…There was good correlation between tumour SUV mean and K i indicating that the tumour [ 18 F]FDG concentration was dominated by irreversible uptake in the 20-60 min period used for Patlak analysis [15]. Given the increases in SUV mean that occurred over time we hypothesised that SUV mean measured at earlier times would underestimate K i but this was not the case.…”

Section: Discussionmentioning

confidence: 98%

Optimisation of animal handing and timing of 2-deoxy-2-[18F]fluoro-D-glucose PET tumour imaging in mice

Hesketh,

Lewis,

Brindle

2024

Preprint

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Purpose In humans, 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) tumour-to-background contrast continues to increase long after a typical uptake period of 45–60 min. Similar studies have not been performed in mice and the static imaging time point for most studies is arbitrarily set at 30–60 min post-injection of [18F]FDG. Ideally, static PET imaging should be performed after the initial period of rapid uptake but this period has not been defined in mice, with previous dynamic studies in mice being limited to 60 min. This study aimed to define the kinetics of [18F]FDG biodistribution over periods of 3–4 h in different murine tumour models, both subcutaneous and autochthonous, and to further refine fasting and warming protocols used prior to imaging. Procedures Dynamic [18F]FDG PET-CT scans lasting 3 or 4 h were performed with C57BL/6J and Balb/c nude mice bearing subcutaneous EL4 murine T-cell lymphoma and Colo205 human colorectal tumours, respectively, and with transgenic Eµ-Myc lymphoma mice. Prior to [18F]FDG injection, four combinations of different animal handling conditions were used: warming for 1 h at 31°C; maintenance at room temperature (20–24°C), fasting for 6–10 h and a fed state. Results Tumour mean standardised uptake value (SUVmean) peaked at 147 ± 48 min post injection in subcutaneous tumours and 74 ± 31 min in autochthonous Eµ-Myc lymphomas. The tumour-to-blood ratio (TBR) peaked at 171 ± 57 and 83 ± 33 min in subcutaneous and autochthonous Eµ-Myc tumours, respectively. Fasting increased tumour [18F]FDG uptake and suppressed myocardial uptake in EL4 tumour-bearing mice. There was a good correlation between tumour SUVmean and Ki calculated using an input function (IDIF) derived from the inferior vena cava. Conclusions Delayed static [18F]FDG-PET imaging (> 60 min) in both autochthonous and subcutaneous tumours in improved tumour-to-background contrast and increased reproducibility.

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Section: Discussionmentioning

confidence: 98%

Optimisation of animal handing and timing of 2-deoxy-2-[18F]fluoro-D-glucose PET tumour imaging in mice

Hesketh,

Lewis,

Brindle

2024

Preprint

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“…In a previous study [ 15 ], the usefulness of Patlak Ki images extracted from dynamic 18 F-FDG-PET/CT scan for evaluating the risk of clinical events in CS was examined. The previous study enrolled 21 patients with CS who underwent 30 18 F-FDG-PET/CT scan, which included pretreatment, undertreatment, and follow-up scans, between April 2019 and January 2020.…”

Section: Methodsmentioning

confidence: 99%

Machine learning approach using 18F-FDG-PET-radiomic features and the visibility of right ventricle 18F-FDG uptake for predicting clinical events in patients with cardiac sarcoidosis

Nakajo,

Hirahara,

Jinguji

et al. 2024

Jpn J Radiol

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Objectives To investigate the usefulness of machine learning (ML) models using pretreatment 18F-FDG-PET-based radiomic features for predicting adverse clinical events (ACEs) in patients with cardiac sarcoidosis (CS). Materials and methods This retrospective study included 47 patients with CS who underwent 18F-FDG-PET/CT scan before treatment. The lesions were assigned to the training (n = 38) and testing (n = 9) cohorts. In total, 49 18F-FDG-PET-based radiomic features and the visibility of right ventricle 18F-FDG uptake were used to predict ACEs using seven different ML algorithms (namely, decision tree, random forest [RF], neural network, k-nearest neighbors, Naïve Bayes, logistic regression, and support vector machine [SVM]) with tenfold cross-validation and the synthetic minority over-sampling technique. The ML models were constructed using the top four features ranked by the decrease in Gini impurity. The AUCs and accuracies were used to compare predictive performances. Results Patients who developed ACEs presented with a significantly higher surface area and gray level run length matrix run length non-uniformity (GLRLM_RLNU), and lower neighborhood gray-tone difference matrix_coarseness and sphericity than those without ACEs (each, p < 0.05). In the training cohort, all seven ML algorithms had a good classification performance with AUC values of > 0.80 (range: 0.841–0.944). In the testing cohort, the RF algorithm had the highest AUC and accuracy (88.9% [8/9]) with a similar classification performance between training and testing cohorts (AUC: 0.945 vs 0.889). GLRLM_RLNU was the most important feature of the modeling process of this RF algorithm. Conclusion ML analyses using 18F-FDG-PET-based radiomic features may be useful for predicting ACEs in patients with CS.

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“…24 A recent study by Nakajo et al first demonstrated an association of higher K i constants with higher event adverse cardiac event rates in 21 patients with known cardiac sarcoidosis. 25 Overall, parametric imaging offers an opportunity to increase specificity of FDG-PET for CS.…”

Section: Limitations Of Fdg-pet Imaging For Cs Cardiac Metabolic Plasticitymentioning

confidence: 99%

Potential novel imaging targets of inflammation in cardiac sarcoidosis

Park

Young

Miller

2022

Journal of Nuclear Cardiology

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Cardiac sarcoidosis (CS) is an inflammatory disease with high morbidity and mortality, with a pathognomonic feature of non-caseating granulomatous inflammation. While 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is a well-established modality to image inflammation and diagnose CS, there are limitations to its specificity and reproducibility. Imaging focused on the molecular processes of inflammation including the receptors and cellular microenvironments present in sarcoid granulomas provides opportunities to improve upon FDG-PET imaging for CS. This review will highlight the current limitations of FDG-PET imaging for CS while discussing emerging new nuclear imaging molecular targets for the imaging of cardiac sarcoidosis. (J Nucl Cardiol 2021) Key Words: Tracer development AE sarcoid heart disease AE inflammation Abbreviations CS Cardiac sarcoidosis FDG Fluorodeoxyglucose PET Positron emission tomography FLT Fluorodeoxythymidine F-MISO Fluoromisonidazole SSTR Somatostatin receptor CXCR CXC chemokine receptor

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Value of Patlak Ki images from 18F-FDG-PET/CT for evaluation of the relationships between disease activity and clinical events in cardiac sarcoidosis

Cited by 10 publications

References 35 publications

Optimisation of animal handing and timing of 2-deoxy-2-[18F]fluoro-D-glucose PET tumour imaging in mice

Optimisation of animal handing and timing of 2-deoxy-2-[18F]fluoro-D-glucose PET tumour imaging in mice

Machine learning approach using 18F-FDG-PET-radiomic features and the visibility of right ventricle 18F-FDG uptake for predicting clinical events in patients with cardiac sarcoidosis

Potential novel imaging targets of inflammation in cardiac sarcoidosis

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