Establishment and Validation of a Nomogram with Intratumoral Heterogeneity Derived from 18F-FDG PET/CT for Predicting Individual Conditional Risk of 5-Year Recurrence before Initial Treatment of Nasopharyngeal Carcinoma

Gu, Bingxin; Ma, Guoying; Song, Shaoli; Shi, Liqun; Zhang, Yingjian; Zhang, Jianping; Yang, Zhongyi

doi:10.21203/rs.2.15721/v3

Cited by 4 publications

(5 citation statements)

References 41 publications

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“…Radiomic features from [ 18 F]FDG-PET/CT images can quantify the spatial heterogeneity of tumors and have become potential prognostic predictors of many diseases [28][29][30][31]. However, as [ 18 F]FDG PET/CT radiomics has not been widely applied to predict the clinical prognosis of cancer cases, there is no consensus on the screening of texture features [28].…”

Section: Discussionmentioning

confidence: 99%

Development and validation of a [18F]FDG PET/CT-based radiomics nomogram to predict the prognostic risk of pretreatment diffuse large B cell lymphoma patients

Yao

Zhang

et al. 2022

Eur Radiol

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Objective In this study, based on PET/CT radiomics features, we developed and validated a nomogram to predict progression-free survival (PFS) for cases with diffuse large B cell lymphoma (DLBCL) treated with immunochemotherapy. Methods This study retrospectively recruited 129 cases with DLBCL. Among them, PET/CT scans were conducted and baseline images were collected for radiomics features along with their clinicopathological features. Radiomics features related to recurrence were screened for survival analysis using univariate Cox regression analysis with p < 0.05. Next, a weighted Radiomics-score (Rad-score) was generated and independent risk factors were obtained from univariate and multivariate Cox regressions to build the nomogram. Furthermore, the nomogram was tested for their ability to predict PFS using time-dependent receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results Blood platelet, Rad-score, and gender were included in the nomogram as independent DLBCL risk factors for PFS. We found that the training cohort areas under the curve (AUCs) were 0.79, 0.84, and 0.88, and validation cohort AUCs were 0.67, 0.83, and 0.72, respectively. Further, the DCA and calibration curves confirmed the predictive nomogram’s clinical relevance. Conclusion Using Rad-score, blood platelet, and gender of the DLBCL patients, a PET/CT radiomics-based nomogram was developed to guide cases’ recurrence risk assessment prior to treatment. The developed nomogram can help provide more appropriate treatment plans to the cases. Key Points • DLBCL cases can be classified into low- and high-risk groups using PET/CT radiomics based Rad-score. • When combined with other clinical characteristics (gender and blood platelet count), Rad-score can be used to predict the outcome of the pretreatment of DLBCL cases with a certain degree of accuracy. • A prognostic nomogram was established in this study in order to aid in assessing prognostic risk and providing more accurate treatment plans for DLBCL cases.

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Section: Discussionmentioning

confidence: 99%

Development and validation of a [18F]FDG PET/CT-based radiomics nomogram to predict the prognostic risk of pretreatment diffuse large B cell lymphoma patients

Yao

Zhang

et al. 2022

Eur Radiol

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“…Although it provided a better predictive efficacy, there is still a long way to go before clinical application because of constraints in the instability of MRI-based radiomics. Compared with previous prognostic models [26,27], a major strength of our model is that prognostic factors were easy to obtain, and the nomogram yielded a satisfactory C-index as well.…”

Section: Consistent With the Conclusion N Category Has Comparable Prmentioning

confidence: 95%

Development and Validation of Web-Based Nomograms to Precisely Predict Survival Outcomes of Non-metastatic Nasopharyngeal Carcinoma in an Endemic Area

et al. 2021

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Purpose This study aimed to develop web-based nomograms to precisely predict survival outcomes in patients with non-metastatic nasopharyngeal carcinoma (NPC) in an endemic area.Materials and Methods A total of 10,126 patients who underwent radical intensity-modulated radiotherapy at Sun Yat-sen University Cancer Center (SYSUCC) from 2009 to 2015 were analyzed. We assigned patients into a training cohort (SYSUCC-A, n=6,751) and an internal validation cohort (SYSUCC-B, n=3,375) based on computer-generated random numbers. Patients collected from Wuzhou Red Cross Hospital (WZRCH) between 2012 and 2015 were used as the independent external validation cohort (WZRCH, n=450). Concordance index (C-index) was used to determine predictive accuracy and discriminative ability for the nomogram. The web-based clinicopathologic prediction models for predicting survival were based on Cox regression. Results The C-indexes for SYSUCC-A, SYSUCC-B, and WZRCH cohorts for the established nomograms to predict 3-year overall survival (OS) was 0.736, 0.715, and 0.691. Additionally, C-indexes to predict 3-year distant metastasis-free survival (DMFS) was 0.717, 0.706, and 0.686, disease-free survival (DFS) was 0.713, 0.697, and 0.656, local relapse-free survival was 0.695, 0.684, and 0.652, and regional relapse-free survival was 0.672, 0.650, and 0.616. The calibration plots showed great agreement between nomogram-predicted 3-year survival outcomes and actual 3-year survival outcomes. Moreover, C-indexes of the nomograms for OS, DMFS, and DFS were significantly superior than TNM stage (p< 0.001 for all).Conclusion These user-friendly nomograms can precisely predict survival endpoints in patients with non-metastatic NPC. They may serve as a useful tool for providing patient counseling and help physicians to make individual follow-up plans.

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“…PET-computed tomography (PET/CT) using fluorine-18 fludeoxyglucose ( 18 F-FDG) provides high spatial resolution and semiquantitative parameters. It is a widely used technique for NPC staging assessment and prediction of clinical outcomes [4][5][6]. Gu et al [6] analyzed the clinicopathologic parameters and some PET parameters from pretreatment 18 F-FDG PET/CT images of 171 patients with NPC and constructed a prognostic nomogram.…”

Section: Introductionmentioning

confidence: 99%

“…It is a widely used technique for NPC staging assessment and prediction of clinical outcomes [4][5][6]. Gu et al [6] analyzed the clinicopathologic parameters and some PET parameters from pretreatment 18 F-FDG PET/CT images of 171 patients with NPC and constructed a prognostic nomogram. It has shown that intratumor heterogeneity can predict the long-term prognosis of patients with NPC.…”

Section: Introductionmentioning

confidence: 99%

A diagnosis model in nasopharyngeal carcinoma based on PET/MRI radiomics and semiquantitative parameters

Feng

Liang²,

Wang

et al. 2022

BMC Med Imaging

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Background The staging of nasopharyngeal carcinoma (NPC) is of great value in treatment and prognosis. We explored whether a positron emission tomography/ magnetic resonance imaging (PET/MRI) based comprehensive model of radiomics features and semiquantitative parameters was useful for clinical evaluation of NPC staging. Materials and methods A total of 100 NPC patients diagnosed with non-keratinized undifferentiated carcinoma were divided into early-stage group (I—II) and advanced-stage group (III—IV) and divided into the training set (n = 70) and the testing set (n = 30). Radiomics features (n = 396 × 2) of the primary site of NPC were extracted from MRI and PET images, respectively. Three major semiquantitative parameters of primary sites including maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) in all NPC patients were measured. After feature selection, three diagnostic models including the radiomics model, the metabolic parameter model, and the combined model were established using logistic regression model. Finally, internal validation was performed, and a nomogram for NPC comprehensive diagnosis has been made. Results The radiomics model and metabolic parameter model showed an area under the curve (AUC) of 0.83 and 0.80 in the testing set, respectively. The combined model based on radiomics and semiquantitative parameters showed an AUC of 0.90 in the testing set, with the best performance among the three models. Conclusion The combined model based on PET/MRI radiomics and semiquantitative parameters is of great value in the evaluation of clinical stage (early-stage group and advanced-stage group) of NPC.

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Establishment and Validation of a Nomogram with Intratumoral Heterogeneity Derived from 18F-FDG PET/CT for Predicting Individual Conditional Risk of 5-Year Recurrence before Initial Treatment of Nasopharyngeal Carcinoma

Cited by 4 publications

References 41 publications

Development and validation of a [18F]FDG PET/CT-based radiomics nomogram to predict the prognostic risk of pretreatment diffuse large B cell lymphoma patients

Development and validation of a [18F]FDG PET/CT-based radiomics nomogram to predict the prognostic risk of pretreatment diffuse large B cell lymphoma patients

Development and Validation of Web-Based Nomograms to Precisely Predict Survival Outcomes of Non-metastatic Nasopharyngeal Carcinoma in an Endemic Area

A diagnosis model in nasopharyngeal carcinoma based on PET/MRI radiomics and semiquantitative parameters

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