Pretreatment Dynamic Contrast-Enhanced MRI Improves Prediction of Early Distant Metastases in Patients With Nasopharyngeal Carcinoma

Prognostic and therapeutic evaluation of nasopharyngeal carcinoma by dynamic contrast-enhanced (DCE), diffusion-weighted (DW) magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS)

Nasopharyngeal carcinoma (NPC) is an aggressive head and neck malignancy, and radiotherapy (with or without chemotherapy) is the primary treatment modality. Reliable tumour assessment during the treatment phase, which can portend the efficacy of radiotherapy and early identification of potential treatment failure in radioresistant disease, has been implicit for better cancer management. Technological advancement in the last decade has fostered the development of functional magnetic resonance imaging (fMRI) techniques into a promising tool for diagnostic and therapeutic assessments in head and neck cancer. Apart from conventional morphological assessment, early detection of the physiological environment by fMRI allows a more thorough investigation in monitoring tumour response. This article discusses the relevant fMRI utilities in NPC as an early prognostic and monitoring tool for treatment. Challenges and future developments of fMRI in radiation oncology are also discussed.

Combing MRI Perfusion and 18F-FDG PET/CT Metabolic Biomarkers Helps Predict Survival in Advanced Nasopharyngeal Carcinoma: A Prospective Multimodal Imaging Study

We prospectively investigated the prognostic value of imaging parameters for nasopharyngeal carcinoma (NPC) using dynamic contrast-enhanced MRI (DCE-MRI), diffusion-weighted imaging (DWI), and 2-deoxy-2-[fluorine-18]fluoro-D-glucose positron emission tomography (¹⁸F-FDG PET)/computed tomography (CT). Patients with stage III-IVb NPC underwent F-FDG PET/CT, DCE-MRI, and DWI before treatment. Kaplan-Meier and Cox-regression analyses were used to assess associations of PET and MRI imaging biomarkers with overall survival (OS) and recurrence-free survival (RFS). We used independent prognosticators to establish prognostic models; model performance was examined using Harrell's concordance index (c-index). Sixty-one patients were available for analysis, as 13 patients died and 20 experienced recurrence. Total lesion glycolysis (TLG) (p = 0.002) from PET/CT and the initial area under the curve (iAUC) (p = 0.036) from DCE-MRI were identified as independent prognosticators of OS; Epstein-Barr virus (EBV) DNA (p = 0.027), the extracellular volume fraction (V_e) (p = 0.027) from DCE-MRI, and TLG/iAUC (p = 0.025) were significant predictors of RFS. The c-indices of the prognostic models incorporating TLG + iAUC in predicting OS and incorporating EBV DNA + V_e + TLG/iAUC in predicting RFS were 0.79 and 0.76, respectively. These were significantly higher than the corresponding c-indices of the TNM staging system (p = 0.047 and 0.025, respectively); they were also higher than those of models with only MRI or PET biomarkers. In conclusion, the combination of pretreatment DCE-MRI and ¹⁸F-FDG PET/CT imaging biomarkers helps survival prediction in advanced NPC. Integrating MRI perfusion with PET metabolism and plasma EBV information may aid clinicians in planning the optimal personalized management strategy.

Perfusion-based functional magnetic resonance imaging for differentiating serous borderline ovarian tumors from early serous ovarian cancers in a rat model

BACKGROUND

Differentiation of borderline tumors from early ovarian cancer has recently received increasing attention, since borderline tumors often affect young women of childbearing age who desire to preserve fertility. However, previous studies have demonstrated that non-enhanced magnetic resonance imaging (MRI) sequences cannot sufficiently differentiate these tumors.

PURPOSE

To investigate the value of dynamic contrast-enhanced MRI (DCE-MRI) and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in differentiating serous borderline ovarian tumors (SBOT) from early serous ovarian cancers (eSOCA).

MATERIAL AND METHODS

Twenty SBOT and 20 eSOCA rat models were performed with DCE-MRI and IVIM-DWI at 3.0-T MR scanner. Qualitative and quantitative parameters of DCE-MRI were acquired and compared between two groups and correlated with the microvessel density (MVD). The receiver operating characteristic (ROC) curve analyses were conducted to determine their differentiating performances.

RESULTS

SBOTs presented significantly lower values of the initial area under the enhancement curve (iAUC), volume transfer constant (K^trans), and extracellular extravascular volume fraction (v_e) (P < 0.05) and a significantly higher value of true diffusion (D) (P = 0.001) compared with eSOCAs. The diagnostic effectiveness of v_e combined with D was significantly better than that of v_e or K^trans alone (P ≤ 0.039).

CONCLUSION

DCE-MRI may represent a promising tool for differentiating SBOTs from eSOCAs and may not be replaced by IVIM-DWI. Combining DCE-MRI with DWI may improve the diagnostic performance of ovarian tumors.

Multiparametric positron emission tomography/magnetic resonance imaging in nasopharyngeal carcinoma: Correlations between magnetic resonance imaging functional parameters and 18F-fluorodeoxyglucose positron emission tomography imaging biomarkers and their predictive value for treatment failure

Objectives:

The clinical significance of positron emission tomography/magnetic resonance imaging (PET/MRI) functional parameters in nasopharyngealcarcinoma (NPC) remains unclear. The purpose of this prospective study was two-fold: (1) to investigate the associations between simultaneously acquired PET/MRI perfusion, diffusion, and glucose metabolism parameters in patients with NPC and (2) to analyze their predictive value with respect to treatment failure.

Materials and Methods:

We enrolled 85 patients with primary NPC who simultaneously underwent¹⁸F-fluorodeoxyglucose PET/CT and PET/MRI before definitive treatment. The following variables were determined: (1) functional parameters from the MRI component, including perfusion values (K^trans,k_ep,v_e, and initial area under the enhancement curve) and apparent diffusion coefficient (ADC) values, and (2) PET parameters, including metabolic tumor volume (MTV). The reciprocal interrelationships between these parameters and their correlations with treatment failure were examined.

Results:

We observed significant negative associations between K^trans and ADC (r = −0.215, P = 0.049) as well as between v_e and ADC (r = −0.22, P = 0.04). Correlations between PET and MRI functional parameters were not statistically significant. Treatment failures were observed in 21.2% of patients without distant metastases. Multivariate analysis identified v_e as a significant independent predictor for treatment failure (P = 0.022), whereas MTV showed a borderline significance (P = 0.095). Patients in whom both v_e and MTV values were increased had a significantly higher rate of treatment failure (62.5%) than those with either one (21.9%) or no (7.7%) increased parameter (P = 0.004).

Conclusion:

Correlation analyses revealed complex interrelationships among PET and MRI indices measured in patients with NPC. These parameters may have a complementary role in predicting treatment failure in this clinical setting.

Magnetic Resonance Imaging Texture Analysis Predicts Recurrence in Patients with Nasopharyngeal Carcinoma

Background

The personalization of oncologic treatment using radiomic signatures is mounting in nasopharyngeal carcinoma (NPC). We ascertain the predictive ability of 3D volumetric magnetic resonance imaging (MRI) texture features on NPC disease recurrence.

Methods

A retrospective study of 58 patients with NPC undergoing primary curative-intent treatment was performed. Forty-two image texture features were extracted from pre-treatment MRI in addition to clinical factors. A multivariate logistic regression was used to model the texture features. A receiver operating characteristic curve on 100 bootstrap samples was used to maximize generalizability to out-of-sample data. A Cox proportional model was used to predict disease recurrence in the final model.

Results

A total of 58 patients were included in the study. MRI texture features predicted disease recurrence with an area under the curve (AUC), sensitivity, and specificity of 0.79, 0.73, and 0.71, respectively. Loco-regional recurrence was predicted with AUC, sensitivity, and specificity of 0.82, 0.73 and 0.74 respectively while prediction for distant metastasis had an AUC, sensitivity, and specificity of 0.92, 0.79 and 0.84, respectively. Texture features on MRI had a hazard ratio of 4.37 (95% confidence interval 1.72–20.2) for disease recurrence when adjusting for age, sex, smoking, and TNM staging.

Conclusion

Texture features on MRI are independent predictors of NPC recurrence in patients undergoing curative-intent treatment.

Comparison of different images in gross target volume delineating on VX2 nasopharyngeal transplantation tumor models

Background: To determine the optimum conditions for diagnosis of nasopharyngeal carcinoma, we established VX2 rabbit model to delineate gross target volume (GTV) in different imaging methods. Methods: The orthotopic nasopharyngeal carcinoma (NPC) was established in sixteen New Zealand rabbits. After 7-days inoculation, the rabbits were examined by CT scanning and then sacrificed for pathological examination. To achieve the best delineation, different GTVs of CT, MRI, ¹⁸F-FDG PET/CT, and ¹⁸F-FLT PET/CT images were correlated with pathological GTV (GTVp). Results: We found 45% and 60% of the maximum standardized uptake value (SUV_max) as the optimal SUV threshold for the target volume of NPC in ¹⁸F-FDG PET/CT and ¹⁸F-FLT PET/CT images, respectively (GTV_FDG45% and GTV_FLT60%). Moreover, the GTV_MRI and GTV_CT were significantly higher than the GTVp (P ≤ 0.05), while the GTV_FDG45% and especially GTV_FLT60% were similar to the GTVp (R = 0.892 and R = 0.902, respectively; P ≤ 0.001). Conclusions: Notably, the results suggested that ¹⁸F-FLT PET/CT could reflect the tumor boundaries more accurately than ¹⁸F-FDG PET/CT, MRI and CT, which makes ¹⁸F-FLT PET-CT more advantageous for the clinical delineation of the target volume in NPC.

Intravoxel incoherent motion MR imaging in nasopharyngeal carcinoma: comparison and correlation with dynamic contrast enhanced MR imaging

OBJECTIVES

To compare accuracy and assess agreement between intravoxel incoherent motion (IVIM) magnetic resonance (MR) perfusion-related parameters and quantitative dynamic contrast-enhanced (DCE) MR parameters in nasopharyngeal carcinoma (NPC).

RESULTS

D, f, D*, Ktrans , Kep and Vp were significantly lower in the high stage group while Ve was significantly higher in the high stage group. Optimal cut-off values were: D=0.749 × 10-3 mm2/s; f=0.145; D*=100.401 × 10-3 mm2/s; Ktrans =0.571/min; Kep =0.8196/min; Ve =0.6556 %; Vp =0.0757 %. D* (p=0.001), Ktrans (p<0.001), Ve (p=0.014) were all reliable independent predictors for AJCC staging. IVIM-MR perfusion-related (f, D*) and DCE-MR (Ktrans , Kep , Ve , Vp ) parameters were significantly correlated (p<0.001).

MATERIALS AND METHODS

75 patients with newly diagnosed NPC were prospectively recruited. Diffusion-weighted MR and DCE-MR imaging were performed with respective IVIM (D, f, D*) and DCE (Ktrans , Kep , Ve , Vp ) MR parameters calculated. Patients were stratified into low and high tumor stage groups according to American Joint Committee on Cancer (AJCC) staging for determination of the predictive powers of IVIM-MR and DCE-MR parameters using t-test, ROC curve analyses and multiple logistic regression analysis. Correlation between IVIM-MR perfusion-related and DCE-MR parameters was assessed using Spearman's rank correlation.

CONCLUSION

IVIM-MR perfusion-related and quantitative DCE-MR parameters were significantly correlated in the assessment of NPC and were both reliable independent predictors in the prediction of AJCC staging. IVIM-MR perfusion imaging can be a potential useful non-invasive perfusion imaging tool for clinical use in the assessment of NPC.