MRI-Based Metastatic Nodal Number and Associated Nomogram Improve Stratification of Nasopharyngeal Carcinoma Patients: Potential Indications for Individual Induction Chemotherapy

A novel fully automatic segmentation and counting system for metastatic lymph nodes on multimodal magnetic resonance imaging: Evaluation and prognostic implications in nasopharyngeal carcinoma

BACKGROUND

The number of metastatic lymph nodes (MLNs) is crucial for the survival of nasopharyngeal carcinoma (NPC), but manual counting is laborious. This study aims to explore the feasibility and prognostic value of automatic MLNs segmentation and counting.

METHODS

We retrospectively enrolled 980 newly diagnosed patients in the primary cohort and 224 patients from two external cohorts. We utilized the nnUnet model for automatic MLNs segmentation on multimodal magnetic resonance imaging. MLNs counting methods, including manual delineation-assisted counting (MDAC) and fully automatic lymph node counting system (AMLNC), were compared with manual evaluation (Gold standard).

RESULTS

In the internal validation group, the MLNs segmentation results showed acceptable agreement with manual delineation, with a mean Dice coefficient of 0.771. The consistency among three counting methods was as follows 0.778 (Gold vs. AMLNC), 0.638 (Gold vs. MDAC), and 0.739 (AMLNC vs. MDAC). MLNs numbers were categorized into three-category variable (1-4, 5-9, > 9) and two-category variable (<4, ≥ 4) based on the gold standard and AMLNC. These categorical variables demonstrated acceptable discriminating abilities for 5-year overall survival (OS), progression-free, and distant metastasis-free survival. Compared with base prediction model, the model incorporating two-category AMLNC-counting numbers showed improved C-indexes for 5-year OS prediction (0.658 vs. 0.675, P = 0.045). All results have been successfully validated in the external cohort.

CONCLUSIONS

The AMLNC system offers a time- and labor-saving approach for fully automatic MLNs segmentation and counting in NPC. MLNs counting using AMLNC demonstrated non-inferior performance in survival discrimination compared to manual detection.

Prognostic value of pre-treatment [18F] FDG PET/CT in recurrent nasopharyngeal carcinoma without distant metastasis

BACKGROUND

[18 F]-Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) has the ability to detect local and/or regional recurrence as well as distant metastasis. We aimed to evaluate the prognosis value of PET/CT in locoregional recurrent nasopharyngeal (lrNPC).

METHODS

A total of 451 eligible patients diagnosed with recurrent I-IVA (rI-IVA) NPC between April 2009 and December 2015 were retrospectively included in this study. The differences in overall survival (OS) of lrNPC patients with and without PET/CT were compared in the I-II, III-IVA, r0-II, and rIII-IVA cohorts, which were grouped by initial staging and recurrent staging (according to MRI).

RESULTS

In the III-IVA and rIII-IVA NPC patients, with PET/CT exhibited significantly higher OS rates in the univariate analysis (P = 0.045; P = 0.009; respectively). Multivariate analysis revealed that with PET/CT was an independent predictor of OS in the rIII-IVA cohort (hazard ratio [HR] = 0.476; 95% confidence interval [CI]: 0.267 to 0.847; P = 0.012). In the rIII-IVA NPC, patients receiving PET/CT sacns before salvage surgery had a better prognosis compared with MRI alone (P = 0.036). The recurrent stage (based on PET/CT) was an independent predictor of OS. (r0-II versus [vs]. rIII-IVA; HR = 0.376; 95% CI: 0.150 to 0.938; P = 0.036).

CONCLUSION

The present study showed that with PET/CT could improve overall survival for rIII-IVA NPC patients. PET/CT appears to be an effective method for assessing rTNM staging.

Radiologic extranodal extension for nodal staging in nasopharyngeal carcinoma

PURPOSE

Extranodal extension (ENE) has the potential to add value to the current nodal staging system (N8th) for predicting outcome in nasopharyngeal carcinoma (NPC). This study aimed to incorporate ENE, as well as cervical nodal necrosis (CNN) to the current stage N3 and evaluated their impact on outcome prediction. The findings were validated on an external cohort.

METHODS & MATERIALS

Pre-treatment MRI of 750 patients from the internal cohort were retrospectively reviewed. Predictive values of six modified nodal staging systems that incorporated four patterns of ENE and two patterns of CNN to the current stage N3 for disease-free survival (DFS) were compared with that of N8th using multivariate cox-regression and concordance statistics in the internal cohort. Performance of stage N3 for predicting disease recurrence was calculated. An external cohort of 179 patients was used to validate the findings.

RESULTS

Incorporation of advanced ENE, which infiltrates into adjacent muscle/skin/salivary glands outperformed the other five modifications for predicting outcomes (p < 0.01) and achieved a significantly higher c-index for 5-year DFS (0.69 vs 0.72) (p < 0.01) when compared with that of N8th staging system. By adding advanced ENE to the current N3 increased the sensitivity for predicting disease recurrence from 22.4 % to 47.1 %. The finding was validated in the external cohort (5-year DFS 0.65 vs. 0.72, p < 0.01; sensitivity of stage N3 increased from 14.0 % to 41.9 % for disease recurrence).

CONCLUSION

Results from two centre cohorts confirmed that the radiological advanced ENE should be considered as a criterion for stage N3 disease in NPC.

Optimal Size Threshold for MRI-Detected Retropharyngeal Lymph Nodes to Predict Outcomes in Nasopharyngeal Carcinoma: A Two-Center Study

BACKGROUND. Retropharyngeal lymph node (RLN) metastases have profound prognostic implications in patients with nasopharyngeal carcinoma (NPC). However, the AJCC staging system does not specify a size threshold for determining RLN involvement, resulting in inconsistent thresholds in practice. OBJECTIVE. The purpose of this article was to determine the optimal size threshold for determining the presence of metastatic RLNs on MRI in patients with NPC, in terms of outcome predictions. METHODS. This retrospective study included 1752 patients (median age, 46 years; 1297 men, 455 women) with NPC treated by intensity-modulated radiotherapy (RT) from January 2010 to March 2014 from two hospitals; 438 patients underwent MRI 3-4 months after treatment. Two radiologists measured the minimal axial diameter (MAD) of the largest RLN for each patient using a consensus process. A third radiologist measured MAD in 260 randomly selected patients to assess interobserver agreement. Initial ROC and restricted cubic spline (RCS) analyses were used to derive an optimal MAD threshold for predicting progression-free survival (PFS). The threshold's predictive utility was assessed in multivariable Cox regression analyses, controlling for standard clinical predictors. The threshold's utility for predicting PFS and overall survival (OS) was compared with a 5-mm threshold using Kaplan-Meier curves and log-rank tests. RESULTS. The intraclass correlation coefficient for MAD was 0.943. ROC and RCS analyses yielded an optimal threshold of 6 mm. In multivariable analyses, MAD of 6 mm and greater independently predicted PFS in all patients (HR = 1.35, p = .02), patients with N0 or N1 disease (HR = 1.80, p = .008), and patients who underwent posttreatment MRI (HR = 1.68, p = .04). In patients with N1 disease without cervical lymph node involvement, 5-year PFS was worse for MAD greater than or equal to 6 mm than for MAD that was greater than or equal to 5 mm but less than 6 mm (77.2% vs 89.7%, p = .03). OS was significantly different in patients with stage I and stage II disease defined using a 6-mm threshold (p = .04), but not using a 5-mm threshold (p = .09). The 5-year PFS rate was associated with a post-RT MAD of 6 mm and greater (HR = 1.68, p = .04) but not a post-RT MAD greater than or equal to 5 mm (HR = 1.09, p = .71). CONCLUSION. The findings support a threshold MAD of 6 mm for determining RLN involvement in patients with NPC. CLINICAL IMPACT. Future AJCC staging updates should consider incorporation of the 6-mm threshold for N-category and tumor-stage determinations.

Regional lymph node density-based nomogram predicts prognosis in nasopharyngeal carcinoma patients without distant metastases

BACKGROUND

Nasopharyngeal carcinoma (NPC) is a relatively common type of cancer in Southern China, with local recurrence or distant metastases even after radical treatment; consequently, it is critical to identify the patients at higher risk for these events beforehand. This study aimed to assess the prognostic value of regional lymph node density (RLND) associated nomograms in NPC and to evaluate the utility of nomograms in risk stratification.

METHODS

A total of 610 NPC patients without distant metastases (425 in the training and 185 in the validation cohort) were enrolled. The MRI-identified nodal features and clinical characteristics were documented, and the RLND was calculated. Cox analyses were conducted to identify prognostic-associated factors. Nomograms were generated based on the multivariate analysis results. The predictive accuracy and discriminative ability of the nomogram models were determined using the concordance index (C-index), receiver operating characteristic (ROC) curve, and calibration curve; the results were compared with those of the tumor-node-metastasis (TNM) classification. Decision curve analysis (DCA) and C-index were used to assess the prognostic effect and added discriminative ability of RLND. We also estimated the optimal RLND-based nomogram score cut-off values for survival prediction.

RESULTS

RLND was an independent predictor of overall survival (OS) and disease-free survival (DFS), with hazard ratios of 1.36 and 1.30, respectively. RLND was utilized in the construction of nomograms, alongside other independent prognostic factors. The RLND-based nomogram models presented a more effective discriminative ability than the TNM classification for predicting OS (C-index, 0.711 vs. 0.680) and DFS (C-index, 0.681 vs. 0.669), with favorable calibration and consistency. The comparison of C-index values between the nomogram models with and without RLND provided substantiation of the crucial role RLND plays in these models. DCA confirmed the satisfactory clinical practicability of RLND. Moreover, the nomograms were used to categorize the patients into three groups (high-, middle-, and low-risk), and the Kaplan-Meier curves showed significant differences in prognosis between them (p < 0.05). These results were verified in the validation cohort.

CONCLUSION

RLND stands as a robust prognostic factor in NPC. The RLND-based nomograms excel in predicting survival, surpassing the TNM classification.

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.

Integrating pretreatment MRI-detected nodal features and Epstein-Barr virus DNA to identify optimal candidates for intensity-modulated radiotherapy alone in patients with stage II nasopharyngeal carcinoma

OBJECTIVES

To develop and validate a prognostic nomogram based on MRI-detected features of retropharyngeal and cervical lymph nodes and Epstein-Barr virus (EBV) DNA in patients with stage II nasopharyngeal carcinoma (NPC) to distinguish low-risk patients for whom intensity-modulated radiotherapy (IMRT) alone is sufficient.

METHODS

This retrospective study enrolled 894 patients with stage II NPC (596 and 298 in the training and validation cohorts, respectively) with pretreatment MRI between August 2010 and May 2019. All patients received IMRT with or without additional chemotherapy. We identified independent risk factors using univariate and multivariate Cox regression analyses. Survival was compared using Kaplan-Meier curves with the log-rank test.

RESULTS

Independent factors derived from the multivariate analysis include cervical nodal necrosis (CNN), the extracapsular spread (ECS) of cervical and retropharyngeal lymph nodes, and gamma-glutamyl transferase (γ-GGT). Nomograms A, B, and C were established based on the clinical [tumor-node-metastasis (TNM) stage + Epstein-Barr virus (EBV) DNA], the clinical-radiological [all independent predictors] and the combined models [the clinical-radiological model + EBV DNA], respectively. Nomogram C (C-index 0.769 [0.718-0.820]) demonstrated better risk discrimination than nomogram B (0.762 [0.715-0.809]), nomogram A (0.619 [0.564-0.674]), and the TNM stage (0.560 [0.509-0.611]). In the low-risk group divided by nomogram C, no significant survival differences were observed between patients treated with radiotherapy (RT) alone and other regimens including additional chemotherapy.

CONCLUSIONS

The nomogram combining MRI-detected retropharyngeal and cervical lymph node features with pretreatment EBV-DNA improved the prognostic risk stratification for stage II NPC.