Effectiveness of 18F-FDG PET/CT in the diagnosis and staging of osteosarcoma: a meta-analysis of 26 studies

Liu, Fanxiao; Zhou, Dongsheng; Dong, Jinlei

doi:10.1186/s12885-019-5488-5

Cited by 51 publications

(28 citation statements)

References 48 publications

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“…SUVmax, MTV, and TLG have been previously demonstrated as strong predictors of sarcoma cell proliferation and disease progression [ 17 , 18 ]. Several studies have claimed that SUVmax and its retention index could both be used to differentiate between benign and malignant soft tissue or bone lesions [ 19 , 20 ]. Nonetheless, SUVmax is not a precise indicator of the global metabolic activity of tumors.…”

Section: Discussionmentioning

confidence: 99%

Differentiation of soft tissue and bone sarcomas from benign lesions utilizing 18F-FDG PET/CT-derived parameters

et al. 2020

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Background Accurate differentiation between malignant and benign changes in soft tissue and bone lesions is essential for the prevention of unnecessary biopsies and surgical resection. Nevertheless, it remains a challenge and a standard diagnosis modality is urgently needed. The objective of this study was to evaluate the usefulness of 18 F-fluorodeoxyglucose ( 18 F-FDG) PET/CT-derived parameters to differentiate soft tissue sarcoma (STS) and bone sarcoma (BS) from benign lesions. Methods Patients who had undergone pre-treatment 18 F-FDG PET/CT imaging and subsequent pathological diagnoses to confirm malignant (STS and BS, n = 37) and benign ( n = 33) soft tissue and bone lesions were retrospectively reviewed. The tumor size, PET and low-dose CT visual characteristics, maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and heterogeneous factor (HF) of each lesion were measured. Univariate and multivariate logistic regression analyses were conducted to determine the significant risk factors to distinguish sarcoma from benign lesions. To establish a regression model based on independent risk factors, and the receiver operating characteristic curves (ROCs) of individual parameters and their combination were plotted and compared. Conventional imaging scans were re-analyzed, and the diagnostic performance compared with the regression model. Results Univariate analysis results revealed that tumor size, SUVmax, MTV, TLG, and HF of 18 F-FDG PET/CT imaging in the STS and BS group were all higher than in the benign lesions group (all P values were < 0.01). The differences in the visual characteristics between the two groups were also all statistically significant ( P < 0.05). However, the multivariate regression model only included SUVmax and HF as independent risk factors, for which the odds ratios were 1.135 (95%CI: 1.026 ~ 1.256, P = 0.014) and 7.869 (95%CI: 2.119 ~ 29.230, P = 0.002), respectively. The regression model was constructed using the following expression: Logit ( P ) = − 2.461 + 0.127SUVmax + 2.063HF. The area under the ROC was 0.860, which was higher than SUVmax (0.744) and HF (0.790). The diagnostic performance of the regression model was superior to those of individual parameters and conventional imaging. Conclusion The regression model including SUVmax and HF based on 18 F-FDG PET/CT imaging may be useful for differentiating STS and BS from benign lesions.

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Section: Discussionmentioning

confidence: 99%

Differentiation of soft tissue and bone sarcomas from benign lesions utilizing 18F-FDG PET/CT-derived parameters

et al. 2020

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“…24 Recently, 18 F-fluorodeoxy-D-glucose positron emission tomography ( 18 F-FDG PET) and positron emission tomography with computed tomography (PET CT) has emerged as a useful investigation to identify skeletal lesions. 24 A meta-analysis by Liu et al demonstrated a sensitivity of 93% and specificity of 97% for 18 F-FDG PET and PET CT. 25 While these findings are interesting, there are numerous shortcomings to this study which need to be considered. First, the small sample size makes any definitive recommendation in this regard impossible.…”

Section: Discussionmentioning

confidence: 89%

Tumour volume as a predictor of metastases in patients presenting with high-grade conventional osteosarcoma of the extremities

2020

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BACKGROUND: The aim of this study was to compare the initial tumour volume in patients with and without pulmonary and/or skeletal metastases at time of presentation. The secondary aim was to compare the value of tumour volume in the prediction of metastases at time of presentation with known predictive factors, namely serum alkaline phosphatase (ALP) and lactate dehydrogenase (LDH). MATERIALS AND METHODS: A retrospective cross-sectional analysis was performed comparing the primary tumour volume in patients with and without metastases. All patients with histologically confirmed high-grade conventional osteosarcoma over a five-year period were included. RESULTS: The study comprised 61 patients. The mean age was 21 years (SD: 11.9, range 5-56) with an equal distribution of males and females (51% vs 49%). There was no correlation between tumour volume and age at presentation (p=0.31). There was no evidence of metastases in only 20% (n=12) of patients. Skeletal metastases were present in 28% (n=16) of the patients and pulmonary metastases were present in 44 cases (72%). There was no significant difference in the tumour volume at presentation between patients with and without pulmonary metastases (p=0.11). However, tumour volume did appear to predict the presence of skeletal metastases (p=0.02). A tumour volume of 1 383 cm3 had a negative predictive value (NPV) of 92% and positive predictive value (PPV) of 55% for the presence of skeletal metastases (area under curve [AUC]=0.76; sensitivity 66%; specificity 87%). A tumour volume of 480 cm3 had a 100% NPV for the presence of skeletal metastases (AUC=0.74). A tumour volume > 1 380 cm3 had an odds ratio (OR) of 13.6 (p<0.01; 95% CI 2.6-72.5) as an independent variable in relation to skeletal metastases. Multivariate analysis (with ALP and LDH) of tumour volume >1 380 cm3 yielded an OR of 8.6 (p=0.04; 95% CI 1.1-67) for presence of skeletal metastases. CONCLUSION: In this series of conventional high-grade osteosarcoma of the extremities, we found a very high rate of metastases at time of diagnosis. While there was no association with pulmonary metastases, increased tumour volume was associated with an increased risk for the presence of skeletal metastases. More studies in the developing world clinical setting are required to investigate this further; the high rate of metastases seen at time of diagnosis also requires further investigation Level of evidence: Level 4. Keywords: osteosarcoma, metastases, tumour volume, prognosis, staging

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“…In the present study, we assessed the usefulness of 18 [17,19]. Several studies have claimed that SUVmax and its retention index could both be used to differentiate between benign and malignant soft tissue or bone lesions [20,21]. Nonetheless, SUVmax is not a precise indicator of the global metabolic activity of tumors.…”

Section: Discussionmentioning

confidence: 99%

Differentiation of soft tissue and bone sarcomas from benign lesions utilizing 18F- FDG PET/CT-derived parameters

Chen

Feng

Xie

et al. 2020

Preprint

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Background: Accurate differentiation between malignant and benign changes in soft tissue and bone lesions is essential for the prevention of unnecessary biopsies and surgical resection. Nevertheless, it remains a challenge and a standard diagnosis modality is urgently needed. The objective of this study was to evaluate the usefulness of 18F-fluorodeoxyglucose (18F-FDG) PET/CT-derived parameters to differentiate soft tissue sarcoma (STS) and bone sarcoma (BS) from benign lesions. Methods: Patients who had undergone pre-treatment 18F-FDG PET/CT imaging and subsequent pathological diagnoses to confirm malignant (STS and BS, n = 37) and benign (n = 33) soft tissue and bone lesions were retrospectively reviewed. The tumor size, PET and low-dose CT visual characteristics, maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and heterogeneous factor (HF) of each lesion were measured. Univariate and multivariate logistic regression analyses were conducted to determine the significant risk factors to distinguish sarcoma from benign lesions. To establish a regression model based on independent risk factors, and the receiver operating characteristic curves (ROCs)of individual parameters and their combination were plotted and compared. Conventional imaging scans were re-analyzed, and the diagnostic performance compared with the regression model.Results: Univariate analysis results revealed that tumor size, SUVmax, MTV, TLG, and HF of 18F-FDG PET/CT imaging in the STS and BS group were all higher than in the benign lesions group (all P values were <0.01). The differences in the visual characteristics between the two groups were also all statistically significant (P <0.05). However, the multivariate regression model only included SUVmax and HF as independent risk factors, for which the odds ratios were 1.135 (95%CI: 1.026~1.256, P = 0.014) and 7.869 (95%CI: 2.119~29.230, P = 0.002), respectively. The regression model was constructed using the following expression: Logit (P) = -2.461+0.127SUVmax+2.063HF. The area under the ROC was 0.860, which was higher than SUVmax (0.744) and HF (0.790). The diagnostic performance of the regression model was superior to those of individual parameters and conventional imaging.Conclusion: The regression model including SUVmax and HF based on 18F-FDG PET/CT imaging may be useful for differentiating STS and BS from benign lesions.

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Effectiveness of 18F-FDG PET/CT in the diagnosis and staging of osteosarcoma: a meta-analysis of 26 studies

Cited by 51 publications

References 48 publications

Differentiation of soft tissue and bone sarcomas from benign lesions utilizing 18F-FDG PET/CT-derived parameters

Differentiation of soft tissue and bone sarcomas from benign lesions utilizing 18F-FDG PET/CT-derived parameters

Tumour volume as a predictor of metastases in patients presenting with high-grade conventional osteosarcoma of the extremities

Differentiation of soft tissue and bone sarcomas from benign lesions utilizing 18F- FDG PET/CT-derived parameters

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