Accuracy of fluorodeoxyglucose-positron emission tomography for diagnosis of single bone metastasis: Comparison with bone scintigraphy

Jin Hur, Choon Sik Yoon, Young Hoon Ryu, Mi Jin Yun, Jin Suck Suh

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

PURPOSE: The aim of this study was to compare the accuracy of fluorodeoxyglucose-positron emission tomography (FDG-PET) with bone scan for diagnosis of single bone metastasis using a semiquantitative method. MATERIAL AND METHODS: Seventy-six patients with suspected single bone metastasis, who underwent both FDG-PET and a bone scan, were selected. The number and location of lesions detected upon both FDG-PET and bone scan were recorded, and the lesions were compared using the McNemar test. For semiquantitative analysis, a maximum (max) standard uptake value (SUV) of 2.5 was used as the positive cutoff value for metastasis. The difference in max SUV value among 3 groups (osteolytic, osteoblastic, and benign lesions) was assessed using the Student-Newman-Keuls method. Biopsy results, other imaging findings (multirow detector computed tomography, magnetic resonance imaging), and the patient's clinical course were used as references. RESULTS: There were 47 single bone metastases and 29 benign lesions. The sensitivity, specificity, and accuracy of bone scans for diagnosing bone metastases were 89%, 41%, and 71%, respectively, and those of FDG-PET were 85%, 52%, and 72%, respectively. These data were not significantly different (P > 0.05). Using a max SUV of 2.5 as the positive cutoff value for metastasis, the specificity and accuracy of FDG-PET, 83% for each, improved. When classifying bone metastasis as osteoblastic or osteolytic, the max SUV was significantly higher in osteolytic metastasis than in osteoblastic and benign lesions (P = 0.001). CONCLUSIONS: Fluorodeoxyglucose- positron emission tomography (FDG-PET) using the semiquantitative parameter SUV improves the diagnostic ability to differentiate between single bone metastases and benign lesions.

Original languageEnglish
Pages (from-to)812-819
Number of pages8
JournalJournal of Computer Assisted Tomography
Volume31
Issue number5
DOIs
Publication statusPublished - 2007 Sep 1

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging

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