Intravoxel Incoherent Motion Magnetic Resonance Imaging for Prediction of Induction Chemotherapy Response in Locally Advanced Hypopharyngeal Carcinoma: Comparison With Model-Free Dynamic Contrast-Enhanced Magnetic Resonance Imaging

Machine Learning-Based MRI Radiogenomics for Evaluation of Response to Induction Chemotherapy in Head and Neck Squamous Cell Carcinoma

RATIONALE AND OBJECTIVES

To develop and validate a radiogenomics model integrating clinical data, radiomics-based machine learning (RBML) classifiers, and transcriptomics data for predicting the response to induction chemotherapy (IC) in patients with head and neck squamous cell carcinoma (HNSCC).

MATERIALS AND METHODS

Radiomics features derived from T2-weighted, pre- and post-contrast-enhanced T1-weighted MRI sequences, clinical data, and RNA sequencing data of 150 patients with HNSCC were included in the study. Analysis of variance or recursive feature elimination was used to reduce radiomics features. Three RBML classifiers were developed to distinguish non-responders from responders. Weighted correlation network analysis (WGCNA) was performed to identify the correlation between clinical data or radiomics features and molecular features; subsequently, protein interaction and functional enrichment analyses were performed. The predictive performance of the radiogenomics model integrating significant clinical variables, RBML classifiers, and molecular features was evaluated using receiver operating characteristic curve analysis.

RESULTS

Five radiomics features and two conventional MRI findings significantly stratified HNSCC patients into responders and non-responders. On WGCNA analysis, 809 genes showed a significant correlation with two radiomics features. Functional enrichment analysis suggested that our proposed radiomics features could reflect the T cell-mediated immune response and immune infiltration of HNSCC. The radiogenomics model showed the highest area under the curve (0.88[95%CI 0.75-0.96]) for predicting IC response, which was better than MRI findings(p = 0.0407) or molecular features(p = 0.004) alone, but showed no significant difference with that of RBML model (p = 0.2254) in test cohort.

CONCLUSION

Merging imaging phenotypes with transcriptomic data improved the prediction of IC response in HNSCC.

Utility of mono-exponential, bi-exponential, and stretched exponential signal models of intravoxel incoherent motion (IVIM) to predict prognosis and survival risk in laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC) patients after chemoradiotherapy

PURPOSE

To investigate the predictive power of mono-exponential, bi-exponential, and stretched exponential signal models of intravoxel incoherent motion (IVIM) in prognosis and survival risk of laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC) patients after chemoradiotherapy.

MATERIALS AND METHODS

Forty-five patients with laryngeal or hypopharyngeal squamous cell carcinoma were retrospectively enrolled. All patients had undergone pretreatment IVIM examination, subsequently, mean apparent diffusion coefficient (ADCmean), maximum ADC (ADCmax), minimum ADC (ADCmin) and ADCrange (ADCmax - ADCmean) by mono-exponential model, true diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f) by bi-exponential model, distributed diffusion coefficient (DDC), and diffusion heterogeneity index (α) by stretched exponential model were measured. Survival data were collected for 5 years.

RESULTS

Thirty-one cases were in the treatment failure group and fourteen cases were in the local control group. Significantly lower ADCmean, ADCmax, ADCmin, D, f, and higher D* values were observed in the treatment failure group than in the local control group (p < 0.05). D* had the greatest AUC of 0.802, with sensitivity and specificity of 77.4 and 85.7% when D* was 38.85 × 10^-3 mm²/s. Kaplan-Meier survival analysis showed that the curves of N stage, ADCmean, ADCmax, ADCmin, D, D*, f, DDC, and α values were significant. Multivariate Cox regression analysis showed ADCmean and D* were independently correlated with progression-free survival (PFS) (hazard ratio [HR] = 0.125, p = 0.001; HR = 1.008, p = 0.002, respectively).

CONCLUSION

The pretreatment parameters of mono-exponential and bi-exponential models were significantly correlated with prognosis of LHSCC, ADCmean and D* values were independent factors for survival risk prediction.

Prospective Investigation of 18FDG-PET/MRI with Intravoxel Incoherent Motion Diffusion-Weighted Imaging to Assess Survival in Patients with Oropharyngeal or Hypopharyngeal Carcinoma

To prospectively investigate the prognostic value of 18F-FDG PET/MRI in patients with oropharyngeal or hypopharyngeal squamous cell carcinomas (OHSCC) treated by chemoradiotherapy. The study cohort consisted of patients with OHSCC who had undergone integrated PET/MRI prior to chemoradiotherapy or radiotherapy. Imaging parameters derived from intravoxel incoherent motion (IVIM), dynamic contrast-enhanced MRI (DCE-MRI), and 18F-FDG PET were analyzed in relation to overall survival (OS) and recurrence-free survival (RFS). In multivariable analysis, T classification (p < 0.001), metabolic tumor volume (p = 0.013), and pseudo-diffusion coefficient (p = 0.008) were identified as independent risk factors for OS. The volume transfer rate constant (p = 0.015), initial area under the curve (p = 0.043), T classification (p = 0.018), and N classification (p = 0.018) were significant predictors for RFS. The Harrell’s c-indices of OS and RFS obtained from prognostic models incorporating clinical and PET/MRI predictors were significantly higher than those derived from the traditional TNM staging system (p = 0.001). The combination of clinical risk factors with functional parameters derived from IVIM and DCE-MRI plus metabolic PET parameters derived from 18F-FDG PET in integrated PET/MRI outperformed the information provided by traditional TNM staging in predicting the survival of patients with OHSCC.

Cationic antimicrobial peptide NRC-03 induces oral squamous cell carcinoma cell apoptosis via CypD-mPTP axis-mediated mitochondrial oxidative stress

Pleurocidin-family cationic antimicrobial peptide NRC-03 exhibits potent and selective cytotoxicity towards cancer cells. However, the anticancer effect of NRC-03 in oral squamous cell carcinoma (OSCC) and the molecular mechanism of NRC-03 induced cancer cell death is still unclear. This study focused to investigate mitochondrial oxidative stress-mediated altered mitochondrial function involved in NRC-03-induced apoptosis of OSCC cells. NRC-03 entered the OSCC cells more easily than that of normal cells and bound to mitochondria as well as the nucleus, causing cell membrane blebbing, mitochondria swelling, and DNA fragmentation. NRC-03 induced high oxygen consumption, reactive oxygen species (ROS) release, mitochondrial dysfunction, and apoptosis in OSCC cells. Non-specific antioxidant N-acetyl-l-cysteine (NAC), or mitochondria-specific antioxidant mitoquinone (MitoQ) alleviated NRC-03-induced apoptosis and mitochondrial dysfunction indicated that NRC-03 exerts a cytotoxic effect in cancer cells via inducing cellular and mitochondrial oxidative stress. Moreover, the expression of cyclophilin D (CypD), the key component of mitochondrial permeability transition pore (mPTP), was upregulated in NRC-03-treated cancer cells. Blockade of CypD by siRNA-mediated depletion or pharmacological inhibitor cyclosporine A (CsA) significantly suppressed NRC-03-induced mitochondrial oxidative stress, mitochondrial dysfunction, and apoptosis. NRC-03 also activated MAPK/ERK and NF-κB pathways. Importantly, intratumoral administration of NRC-03 inhibited the growth of CAL-27 cells-derived tumors on xenografted animal models. Taken together, our study indicates that NRC-03 induces apoptosis in OSCC cells via the CypD-mPTP axis mediated mitochondrial oxidative stress.

Quantitative Dynamic-Enhanced MRI and Intravoxel Incoherent Motion Diffusion-Weighted Imaging for Prediction of the Pathological Response to Neoadjuvant Chemotherapy and the Prognosis in Locally Advanced Gastric Cancer

Background

This study aimed to explore the predictive value of quantitative dynamic contrast-enhanced MRI (DCE-MRI) and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) quantitative parameters for the response to neoadjuvant chemotherapy (NCT) in locally advanced gastric cancer (LAGC) patients, and the relationship between the prediction results and patients’ prognosis, so as to provide a basis for clinical individualized precision treatment.

Methods

One hundred twenty-nine newly diagnosed LAGC patients who underwent IVIM-DWI and DCE-MRI pretreatment were enrolled in this study. Pathological tumor regression grade (TRG) served as the reference standard of NCT response evaluation. The differences in DCE-MRI and IVIM-DWI parameters between pathological responders (pR) and pathological non-responders (pNR) groups were analyzed. Univariate and multivariate logistic regressions were used to identify independent predictive parameters for NCT response. Prediction models were built with statistically significant quantitative parameters and their combinations. The performance of these quantitative parameters and models was evaluated using receiver operating characteristic (ROC) analysis. Clinicopathological variables, DCE-MRI and IVIM-DWI derived parameters, as well as the prediction model were analyzed in relation to 2-year recurrence-free survival (RFS) by using Cox proportional hazards model. RFS was compared using the Kaplan–Meier method and the log-rank test.

Results

Sixty-nine patients were classified as pR and 60 were pNR. K^trans, k_ep, and v_e values in the pR group were significantly higher, while ADC_standard and D values were significantly lower than those in the pNR group. Multivariate logistic regression analysis demonstrated that K^trans, k_ep, v_e, and D values were independent predictors for NCT response. The combined predictive model, which consisted of DCE-MRI and IVIM-DWI, showed the best prediction performance with an area under the curve (AUC) of 0.922. Multivariate Cox regression analysis showed that ypStage III and NCT response predicted by the IVIM-DWI model were independent predictors of poor RFS. The IVIM-DWI model could significantly stratify median RFS (52 vs. 15 months) and 2-year RFS rate (72.3% vs. 21.8%) of LAGC.

Conclusion

Pretreatment DCE-MRI quantitative parameters K^trans, k_ep, v_e, and IVIM-DWI parameter D value were independent predictors of NCT response for LAGC patients. The regression model based on baseline DCE-MRI, IVIM-DWI, and their combination could help RFS stratification of LAGC patients.