Use of 18F-FDG PET/CT texture analysis to diagnose cardiac sarcoidosis.

Purpose: 18F-fluorodeoxyglocose positron emission tomography (FDG PET) plays a significant role in the diagnosis of cardiac sarcoidosis (CS). Texture analysis is a group of computational methods for evaluating the inhomogeneity among adjacent pixels or voxels. We investigated whether texture analysi...

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Published in:European Journal of Nuclear Medicine & Molecular Imaging Vol. 46; no. 6; pp. 1240 - 1248
Main Authors: Manabe, Osamu, Ohira, Hiroshi, Hirata, Kenji, Hayashi, Souichiro, Naya, Masanao, Tsujino, Ichizo, Aikawa, Tadao, Koyanagawa, Kazuhiro, Oyama-Manabe, Noriko, Tomiyama, Yuuki, Magota, Keiichi, Yoshinaga, Keiichiro, Tamaki, Nagara
Format: Journal Article
Published: Springer Nature Jun2019
Online Access:View this record in EBSCOhost
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      jtl: European Journal of Nuclear Medicine & Molecular Imaging
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      dt: Jun2019
      vid: 46
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      pub: Springer Nature
      place: New York, New York
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        136129959
        10.1007/s00259-018-4195-9
        136129959
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        atl: Use of 18F-FDG PET/CT texture analysis to diagnose cardiac sarcoidosis.
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          Manabe, Osamu
          Ohira, Hiroshi
          Hirata, Kenji
          Hayashi, Souichiro
          Naya, Masanao
          Tsujino, Ichizo
          Aikawa, Tadao
          Koyanagawa, Kazuhiro
          Oyama-Manabe, Noriko
          Tomiyama, Yuuki
          Magota, Keiichi
          Yoshinaga, Keiichiro
          Tamaki, Nagara
        affil: Department of Nuclear Medicine, Hokkaido University Graduate School of Medicine, N15 W7, Kita-Ku, 0608638, Sapporo, Hokkaido, Japan
      sug:
      ab: Purpose: 18F-fluorodeoxyglocose positron emission tomography (FDG PET) plays a significant role in the diagnosis of cardiac sarcoidosis (CS). Texture analysis is a group of computational methods for evaluating the inhomogeneity among adjacent pixels or voxels. We investigated whether texture analysis applied to myocardial FDG uptake has diagnostic value in patients with CS. Methods: Thirty-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. Results: Twenty-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). Conclusions: The 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.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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