Qualitative and Quantitative Assessments of Cardiac Sarcoidosis Using &lt;sup&gt;18&lt;/sup&gt;F-FDG PET

Manabe, Osamu; Ohira, Hiroshi; Yoshinaga, Keiichiro; Naya, Masanao; Oyama‐Manabe, Noriko; Tamaki, Nagara

doi:10.17996/anc.17-00015

Cited by 15 publications

(9 citation statements)

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“…Sarcoidosis is a multisystem disease pathologically characterized by non-caseating granuloma [ 1 – 6 ]. Cardiac sarcoidosis (CS) occasionally causes cardiac death via congestive heart failure, ventricular tachyarrhythmia, and advanced conduction disturbance [ 1 – 5 ].…”

Section: Introductionmentioning

confidence: 99%

“…18 F-Fluorodeoxyglucose (FDG) is widely used as a positron emission tomography (PET) tracer to assess malignant and active inflammatory diseases. The main advantage of FDG PET is its ability to visualize metabolic activity to complement anatomic imaging [ 6 , 7 ]. Previous studies have demonstrated the usefulness of FDG PET in diagnosing CS and monitoring treatment response [ 1 – 3 ].…”

Section: Introductionmentioning

confidence: 99%

“…In the context of FDG PET, SUVmax reflects only the value of a single voxel and does not reflect the metabolism of the entire target lesion. Volume-based parameters such as cardiac metabolic volume (CMV) or cardiac metabolic activity (CMA) have emerged as a novel measure, mainly for assessing the metabolism of CS [ 6 , 8 , 9 ]. CMV was defined as the volume of the cardiac FDG accumulation within a given boundary determined using a threshold such as the liver uptake, the blood pool SUV, and the fixed value of SUV [ 9 – 11 ].…”

Section: Introductionmentioning

confidence: 99%

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Which is the proper reference tissue for measuring the change in FDG PET metabolic volume of cardiac sarcoidosis before and after steroid therapy?

et al. 2018

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BackgroundCardiac sarcoidosis (CS) is a rare but potentially life-threatening disease that causes conduction disturbance, systolic dysfunction, and, most notably, sudden cardiac death. 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) plays important roles not only in diagnosing CS but also in evaluating the effects of anti-inflammatory therapy. A volume-based analysis of parameters measured by FDG PET, so-called cardiac metabolic volume (CMV), has emerged as a new assessment tool. CMV is measured as the volume within the boundary determined by a reference tissue such as the liver and the blood pool uptake. However, there is a possibility that oral steroid therapy could lead to variations of the liver and the blood pool uptake. Here, we attempted to evaluate the steroid effects on the liver and the blood pool uptake.A total of 38 CS patients who underwent FDG PET/CT before and during steroid therapy were retrospectively enrolled. Volumes of interest (VOIs) were placed in the right lobe of the liver and descending aorta (DA). The maximum standardized uptake value (SUVmax), SUVmean, and SUVpeak of the liver and DA were compared between time points before and during steroid therapy.ResultsThe SUVmax, SUVmean, and SUVpeak of the liver during steroid therapy significantly increased from the time point before the therapy (SUVmax 3.5 ± 0.4 vs. 3.8 ± 0.6, p = 0.014; SUVmean 2.7 ± 0.3 vs. 3.0 ± 0.5, p = 0.0065; SUVpeak 3.0 ± 0.4 vs. 3.4 ± 0.6, p = 0.006). However, the SUVmax, SUVmean, and SUVpeak in the DA did not significantly change (SUVmax 2.2 ± 0.3 vs. 2.2 ± 0.4, p = 0.46; SUVmean 1.9 ± 0.3 vs. 2.0 ± 0.4, p = 0.56; SUVpeak 2.0 ± 0.3 vs. 2.0 ± 0.3, p = 0.70).ConclusionsWe measured FDG uptake in the liver and blood pool before and during steroid therapy. Steroid therapy increased the liver uptake but not the blood pool uptake. Our findings suggested that the DA uptake is a more suitable threshold than liver uptake to evaluate therapeutic effects using volume-based analysis of cardiac FDG PET.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Which is the proper reference tissue for measuring the change in FDG PET metabolic volume of cardiac sarcoidosis before and after steroid therapy?

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“…In this retrospective study, we analyzed patients who underwent 18 F-FDG PET/CT and were diagnosed as having CS based on the Japanese Society of Sarcoidosis and Other Granulomatous disorders (JSSOG) guidelines [22] during the period from May 2010 to April 2017. Thirty-three CS patients who did not receive oral steroid treatment before 18 F-FDG PET/CT were allocated to a CS group.…”

Section: Study Subjectsmentioning

confidence: 99%

Cardiac sarcoidosis classification with deep convolutional neural network-based features using polar maps

Togo

Hirata

Manabe

et al. 2019

Computers in Biology and Medicine

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Aims: The aim of this study was to determine whether deep convolutional neural network (DCNN)-based features can represent the difference between cardiac sarcoidosis (CS) and non-CS using polar maps. Methods: A total of 85 patients (33 CS patients and 52 non-CS patients) were analyzed as our study subjects. One radiologist reviewed PET/CT images and defined the left ventricle region for the construction of polar maps. We extracted high-level features from the polar maps through the Inception-v3 network and evaluated their effectiveness by applying them to a CS classification task. Then we introduced the ReliefF algorithm in our method. The standardized uptake value (SUV)-based classification method and the coefficient of variance (CoV)-based classification method were used as comparative methods. Results: Sensitivity, specificity and the harmonic mean of sensitivity and specificity of our method with the ReliefF algorithm were 0.839, 0.870 and 0.854, respectively. Those of the SUVmax-based classification method were 0.468, 0.710 and 0.564, respectively, and those of the CoV-based classification method were 0.655, 0.750 and 0.699, respectively. Conclusion: The DCNN-based high-level features may be more effective than low-level features used in conventional quantitative analysis methods for CS classification.

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Section: Study Subjectsmentioning

confidence: 99%

Cardiac Sarcoidosis Classification with Deep Convolutional Neural Network-Based Features Using Polar Maps

Togo

Hirata

Manabe³

et al. 2018

SSRN Journal

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Abbreviations CoV: coefficient of variation CS: cardiac sarcoidosis DCNN: deep convolutional neural network FDG: fluorodeoxyglucose JSSOG: Japanese society of sarcoidosis and other granulomatous disorders LCD: low carbohydrate diet LV: left ventricle PET: positron emission tomography SUV: standardized uptake value SVM: support vector machine 3 Abstract Aims: The aim of this study was to determine whether deep convolutional neural network (DCNN)-based features can represent the difference between cardiac sarcoidosis (CS) and non-CS using polar maps.Methods: A total of 85 patients (33 CS patients and 52 non-CS patients) were analyzed as our study subjects. One radiologist reviewed PET/CT images and defined the left ventricle region for the construction of polar maps. We extracted high-level features from the polar maps through the Inception-v3 network and evaluated their effectiveness by applying them to a CS classification task. Then we introduced the ReliefF algorithm in our method. The standardized uptake value (SUV)-based classification method and the coefficient of variance (CoV)-based classification method were used as comparative methods.Results: Sensitivity, specificity and the harmonic mean of sensitivity and specificity of our method with the ReliefF algorithm were 0.839, 0.870 and 0.854, respectively. Those of the SUVmax-based classification method were 0.468, 0.710 and 0.564, respectively, and those of the CoV-based classification method were 0.655, 0.750 and 0.699, respectively. Conclusion:The DCNN-based high-level features may be more effective than low-level features used in conventional quantitative analysis methods for CS classification.

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Qualitative and Quantitative Assessments of Cardiac Sarcoidosis Using <sup>18</sup>F-FDG PET

Abstract: Sarcoidosis is a multisystem disease pathologically characterized by non-caseating granuloma. Cardiac sarcoidosis (CS) remains an important prognostic factor of sarcoidosis patients.

Cited by 15 publications

References 4 publications

Which is the proper reference tissue for measuring the change in FDG PET metabolic volume of cardiac sarcoidosis before and after steroid therapy?

Which is the proper reference tissue for measuring the change in FDG PET metabolic volume of cardiac sarcoidosis before and after steroid therapy?

Cardiac sarcoidosis classification with deep convolutional neural network-based features using polar maps

Cardiac Sarcoidosis Classification with Deep Convolutional Neural Network-Based Features Using Polar Maps

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