Prognostic value of intratumoral metabolic heterogeneity on F-18 fluorodeoxyglucose positron emission tomography/computed tomography in locally advanced cervical cancer patients treated with concurrent chemoradiotherapy

Chong, Gun Oh; Lee, Won Kee; Jeong, Shin Young; Park, Shin‐Hyung; Lee, Yoon Hee; Lee, Sang‐Woo; Hong, Dae Gy; Kim, Jae-Chul

doi:10.18632/oncotarget.18769

Cited by 25 publications

(33 citation statements)

References 27 publications

(29 reference statements)

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“…In this study, the quantitative metabolic parameter for regional lymph nodes, i.e., nodal SUVmax, and clinicopathological parameters were used to develop a prognostic risk model using nomograms. With a focus on 2-year DFS, our model found nodal SUVmax to be the highest-weighted negative prognostic factor, which corresponded with the findings of our previous studies [12,13]. With a focus on 5-year OS, young age was the highest-weighted negative prognostic factor.…”

Section: Discussionsupporting

confidence: 87%

“…Previously, we evaluated the 18 F-FDG PET/CT metabolic parameters for predicting tumor recurrence in locally advanced cervical cancer treated with CCRT. Among SUVmax, metabolic tumor volume, total lesion glycolysis of the primary tumor, regional lymph node, and whole body, and tumor heterogeneity, the SUVmax of regional lymph node was the most powerful biomarker for predicting tumor recurrence in locally advanced cervical cancer treated with CCRT [12,13]. Previous 18 F-FDG PET-based prognostic nomograms included lymph node status as a prognostic factor; however, only lymph node level was included [19].…”

Section: Discussionmentioning

confidence: 99%

“…Previously, we have attempted to discover a biomarker for predicting tumor recurrence using pre-treatment 18 F-FDG PET/CT in locally advanced cervical cancers treated with CCRT, and found only nodal maximum standardized uptake value (SUVmax) to be the most powerful biomarker for predicting tumor recurrence [12]. Moreover, we evaluated the prognostic value of intratumoral metabolic heterogeneity on 18 F-FDG PET/CT, but it did not show superiority over traditional metabolic parameters [13].…”

Section: Introductionmentioning

confidence: 97%

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Prognosis-Predicting Model Based on [18F]fluorodeoxyglucose PET Metabolic Parameters in Locally Advanced Cervical Cancer Patients Treated with Concurrent Chemoradiotherapy: Multi-Center Retrospective Study

Lee

Chong

Jeong

et al. 2020

JCM

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This study aimed to develop a prognosis-predicting model based on [18F]fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) and clinicopathologic factors in locally advanced cervical cancer patients treated with concurrent chemoradiotherapy (CCRT). The medical records of 270 locally advanced cervical cancer patients who were treated with CCRT were collected from three institutions and reviewed retrospectively. A nomogram was used for predicting 2-year disease-free survival (DFS) and 5-year overall survival (OS) based on Cox proportional hazards regression. Predictor variables included nodal maximum standardized uptake value (SUVmax), primary tumor SUVmax, age, tumor size, stage, serum squamous cell carcinoma antigen level, and human papillomavirus status. Internal nomogram validation was performed. A nomogram for predicting the 2-year DFS and 5-year OS was constructed using six and seven parameters, respectively. With a focus on 2-year DFS, our model found nodal SUVmax to be the highest weighted negative prognostic factor. With a focus on 5-year OS, young age was the highest weighted negative prognostic factor. The concordance index was 0.75 and 0.78 for the 2-year DFS and 5-year OS, respectively. This nomogram is a predictive tool that can be used to counsel patients for predicting survival outcomes. Moreover, our prognosis-predicting model may make it possible to personalize treatment.

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Section: Discussionsupporting

confidence: 87%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

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Prognosis-Predicting Model Based on [18F]fluorodeoxyglucose PET Metabolic Parameters in Locally Advanced Cervical Cancer Patients Treated with Concurrent Chemoradiotherapy: Multi-Center Retrospective Study

Lee

Chong

Jeong

et al. 2020

JCM

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“…In recent years, a quantitative intratumoral glucose metabolic heterogeneity indicator, namely heterogeneity factor (HF), which can be obtained by calculating metabolic volume-threshold function, has attracted signi cant attention [10]. Although numerous studies show that HF is closely related to the therapeutic response and prognosis of malignant tumors [11][12][13], discrimination between malignant and benign soft tissue and bone tumors utilizing this parameter remains unexplored.…”

Section: Introductionmentioning

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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“…Although numerous studies show that HF is closely related to the therapeutic response and prognosis of malignant tumors [11][12][13], few feasibility of studies have investigated involved HF in discrimination malignant and benign in soft tissue and bone tumors.…”

mentioning

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

View full text Add to dashboard Cite

Background: Accurate differentiation between malignant and benign in soft tissue and bone lesions is essential for the prevention of excessive pathological biopsy and unplanned surgical resection. However, it remains a challenge and a standard diagnosis modality is urgently needed. The purpose of this study is to evaluate the usefulness of 18F- FDG PET/CT-derived parameters to differentiate soft tissue sarcoma (STS) and bone sarcoma (BS) from benign lesions.Methods: Patients who underwent pretreatment 18F-FDG PET/CT imaging and subsequent biopsy to confirm malignant (STS and BS, n=37) and benign (n=33) soft tissue and bone lesions were retrospectively reviewed. The tumor size, maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG) and heterogeneous factor (HF) of each lesion were measured. Univariate analysis and multivariate logistic regression analysis were performed to screen the significant risk factors to distinguish STS and BS from benign lesions. To establish a regression model based on independent risk factors, receiver operating characteristic (ROC) analysis was performed to assess the diagnostic performances.Results: Univariate analysis results showed that tumor size, SUVmax, MTV, TLG and HF of 18F-FDG PET/CT imaging in STS and BS group were all higher than benign lesions group, the difference were statistically significant (all P value were<0.01). However, the multivariate regression model only included SUVmax and HF as independent risk factors, odds radios were 1.135(95%CI: 1.026~1.256, P =0.014), 7.869(95%CI: 2.119~29.230, P =0.002), respectively. The regression model was as follow: Logit (P) = -2.461+0.127SUVmax+2.063HF. The area under the ROC was 0.860 (95%CI: 0.771~0.948, P <0.001) higher than SUVmax 0.744(95%CI: 0.628~0.860, P <0.001) and HF 0.790 (95%CI:0.684~0.896, P <0.001).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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Prognostic value of intratumoral metabolic heterogeneity on F-18 fluorodeoxyglucose positron emission tomography/computed tomography in locally advanced cervical cancer patients treated with concurrent chemoradiotherapy

Cited by 25 publications

References 27 publications

Prognosis-Predicting Model Based on [18F]fluorodeoxyglucose PET Metabolic Parameters in Locally Advanced Cervical Cancer Patients Treated with Concurrent Chemoradiotherapy: Multi-Center Retrospective Study

Prognosis-Predicting Model Based on [18F]fluorodeoxyglucose PET Metabolic Parameters in Locally Advanced Cervical Cancer Patients Treated with Concurrent Chemoradiotherapy: Multi-Center Retrospective Study

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

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