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Background: Lymph node characteristics markedly affect nasopharyngeal carcinoma (NPC) prognosis. Matted node (MN), an important characteristic for lymph node, lacks explored MRI‐based prognostic implications. Purpose: Investigate MRI‐determined MNs' prognostic value in NPC, including 5‐year overall survival (OS), distant metastasis‐free survival (DMFS), local recurrence‐free survival (LRFS), progression‐free survival (PFS), and its role in induction chemotherapy (IC). Study Type: Retrospective cohort survival study. Population: Seven hundred ninety‐two patients with non‐metastatic NPC (female: 27.3%, >45‐year old: 50.1%) confirmed by biopsy. Field Strength/Sequence: 5‐T/3.0‐T, T1‐, T2‐ and post‐contrast T1‐weighted fast spin echo sequences acquired. Assessment: MNs were defined as ≥3 nodes abutting with intervening fat plane replaced by extracapsular nodal spread (ENS). Patients were observed every 3 months for 2 years and every 6 months for 5 years using MRI. Follow‐up extended from treatment initiation to death or final follow‐up. MNs were evaluated by three radiologists with inter‐reader reliability calculated. A 1:1 matched‐pair method compared survival differences between MN‐positive patients with or without IC. Primary endpoints (OS, DMFS, LRFS, PFS) were calculated from therapy initiation to respective event. Statistical Tests: Kappa values assessed inter‐reader reliability. Correlation between MN, ENS, and LNN was studied through Spearman's correlation coefficient. Clinical characteristics were calculated via Fisher's exact, Chi‐squared, and Student's t‐test. Kaplan–Meier curves and log‐rank tests analyzed all time‐to‐event data. Confounding factors were included in Multivariable Cox proportional hazard models to identify independent prognostic factors. P‐values <0.05 were considered statistically significant. Results: MNs incidence was 24.6%. MNs independently associated with decreased 5‐year OS, DMFS, and PFS; not LRFS (P = 0.252). MN‐positive patients gained significant survival benefit from IC in 5‐year OS (88.4% vs. 66.0%) and PFS (76.4% vs. 53.5%), but not DMFS (83.1% vs. 69.9%, P = 0.145) or LRFS (89.9% vs. 77.8%, P = 0.140). Data Conclusion: MNs may independently stratify NPC risk and offer survival benefit from IC. Evidence Level: 3 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

Purpose: To investigate the prognostic significance of MR-detected mandibular nerve involvement (MNI) and its value for induction chemotherapy (IC) administration in patients with nasopharyngeal carcinoma (NPC) and T4 disease. Methods: This retrospective study enrolled 792 non-metastatic, biopsy-proven NPC patients. Univariate and multivariate analysis were used to evaluate potential prognosticators. The inter-observer agreement was assessed by the kappa values. Results: MR-detected MNI was observed in 141 (72.3%) patients among 195 patients with T4 disease, with excellent agreement between the readers (kappa = 0.926). Patients with MR-detected MNI presented better 5-year overall survival (OS) (hazard ratio [HR], 0.40; P = 0.006) than those with MR-negative MNI. Of these patients, IC treatment was verified as an independent factor (HR: 0.35; P = 0.014) with preferable effect on OS. Conclusion: MR-detected MNI could serve as an independent favorable prognostic predictor for OS in NPC patients with stage T4, which should be considered for stratifying these patients for IC administration. [ABSTRACT FROM AUTHOR]

Purpose: Traditional prognostic studies utilized different cut-off values, without evaluating potential information contained in inflammation-related hematological indicators. Using the interpretable machine-learning algorithm RuleFit, this study aimed to explore valuable inflammatory rules reflecting prognosis in nasopharyngeal carcinoma (NPC) patients. Patients and Methods: In total, 1706 biopsy-proven NPC patients treated in two independent hospitals (1320 and 386) between January 2010 and March 2014 were included. RuleFit was used to develop risk-predictive rules using hematological indicators with no distributive difference between the two centers. Time-event-dependent hematological rules were further selected by stepwise multivariate Cox analysis. Combining high-efficiency hematological rules and clinical predictors, a final model was established. Models based on other algorithms (AutoML, Lasso) and clinical predictors were built for comparison, as well as a reported nomogram. Area under the receiver operating characteristic curve (AUROC) and concordance index (C-index) were used to verify the predictive precision of different models. A site-based app was established for convenience. Results: RuleFit identified 22 combined baseline hematological rules, achieving AUROCs of 0.69 and 0.64 in the training and validation cohorts, respectively. By contrast, the AUROCs of the optimal contrast model based on AutoML were 1.00 and 0.58. For overall survival, the final model had a much higher C-index than the base model using TN staging in two cohorts (0.769 vs 0.717, P< 0.001; 0.752 vs 0.688, P< 0.001), and showing great generalizability in training and validation cohorts. The two models based on RuleFit rules performed best, compared with other models. As for other endpoints, the final model showed a similar trend. Kaplan–Meier curve exhibited 22.9% (390/1706) patients were "misclassified" by AJCC staging, but the final model could assess risk classification accurately. Conclusion: The proposed final models based on inflammation-related rules based on RuleFit showed significantly elevated predictive performance. [ABSTRACT FROM AUTHOR]

Background: Accurately predicting the risk of death, recurrence, and metastasis of patients with nasopharyngeal carcinoma (NPC) is potentially important for personalized diagnosis and treatment. Survival outcomes of patients vary greatly in distinct stages of NPC. Prognostic models of stratified patients may aid in prognostication. Purpose: To explore the prognostic performance of MRI‐based radiomics signatures in stratified patients with NPC. Study Type: Retrospective. Population: Seven hundred and seventy‐eight patients with NPC (T1‐2 stage: 298, T3‐4 stage: 480; training cohort: 525, validation cohort: 253). Field Strength/Sequence: Fast‐spin echo (FSE) axial T1‐weighted images, FSE axial T2‐weighted images, contrast‐enhanced FSE axial T1‐weighted images at 1.5 T or 3.0 T. Assessment: Radiomics signatures, clinical nomograms, and radiomics nomograms combining the radiomic score (Radscore) and clinical factors for predicting progression‐free survival (PFS) were constructed on T1‐2 stage patient cohort (A), T3‐4 stage patient cohort (B), and the entire dataset (C). Statistical Tests: Least absolute shrinkage and selection operator (LASSO) method was applied for radiomics modeling. Harrell's concordance indices (C‐index) were employed to evaluate the predictive power of each model. Results: Among 4,410 MRI‐extracted features, we selected 16, 16, and 14 radiomics features most relevant to PFS for Models A, B, and C, respectively. Only 0, 1, and 4 features were found overlapped between models A/B, A/C, and B/C, respectively. Radiomics signatures constructed on T1‐2 stage and T3‐4 stage patients yielded C‐indices of 0.820 (95% confidence interval [CI]: 0.763–0.877) and 0.726 (0.687–0.765), respectively, which were larger than those on the entire validation cohort (0.675 [0.637–0.713]). Radiomics nomograms combining Radscore and clinical factors achieved significantly better performance than clinical nomograms (P < 0.05 for all). Data Conclusion: The selected radiomics features and prognostic performance of radiomics signatures differed per the type of NPC patients incorporated into the models. Radiomics models based on pre‐stratified tumor stages had better prognostic performance than those on unstratified dataset. Level of Evidence: 4 Technical Efficacy Stage: 5 [ABSTRACT FROM AUTHOR]

Background: Nodal (N) stage is one of the most important predictors for distant metastasis in nasopharyngeal carcinoma (NPC) patients. It may ignore potentially useful nodal features, such as nodal matting (three or more lymph nodes abutting together with the absence of intervening fat planes). Purpose: To explore the prognostic value of nodal matting in NPC patients and construct a nomogram with nodal matting for predicting distant metastasis‐free survival (DMFS). Study type: Retrospective. Population: In all, 792 NPC patients treated with intensity modulated radiation therapy from 2010 to 2013 were enrolled with 2:1 training (n = 527) and validation (n = 65) cohorts. Field Strength/Sequence: T1‐ and T2‐weighted imaging at 1.5 or 3.0T. Assessment: Nodal matting and other nodal characteristics were assessed with MRI. MR images were evaluated separately by three radiologists. The association between nodal matting and DMFS was analyzed. Statistical Tests: Univariate and multivariate analyses were performed using the Cox proportional hazards regression model. Nomograms were constructed from a multivariate logistic regression model with and without nodal matting. The predictive accuracy and discriminative ability of the nomograms were determined by concordance index (C‐index) and calibration curves. The results were validated using bootstrap resampling and validation cohort. Results: The incidence of nodal matting was 24.6% (195/792) in all patients. In the training cohort, nodal matting was independently associated with DMFS (hazard ratio [HR] = 1.97 [1.05–3.69], P < 0.05). N1 patients with nodal matting had worse DMFS than N1 patients without (P < 0.05). However, no significant difference was observed when comparing N1 patients with nodal matting to N2 patients (P = 0.464). The C‐index of the nomogram with nodal matting was higher than the nomogram without (0.717 vs. 0.699, P = 0.084). Data Conclusion: Nodal matting was an independent prognostic factor for DMFS in NPC patients. It may help to select patients at high risk of distant metastasis. [ABSTRACT FROM AUTHOR]

• The developed MLNs counting model demonstrated acceptable ability in NPC. • LNNs counted by AMLNC showed favorable discriminatory in predicting prognostic. • AMLNC may serve as a reference tool for younger radiologists to evaluate MLNs. 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. 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). 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. 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. [ABSTRACT FROM AUTHOR]

Objectives: The carotid space is an integral part of the parapharyngeal space, with ambiguous prognostic value for patients with nasopharyngeal carcinoma (NPC). This study aimed to investigate the prognostic significance of carotid space involvement (CSI) and propose a treatment strategy.Materials and Methods: This retrospective study enrolled 792 patients with biopsy-confirmed, non-distant metastatic NPC staged by magnetic resonance imaging before treatment. We used multivariable Cox regression models and Kaplan-Meier methods to assess the association between the variables and survival outcomes. A matched-pair method (1:1) was used to compare the survival differences between the patients with CSI treated with induction chemotherapy (ICT)and that of those who were not.Results: The incidence rate of CSI was 21.7 % (172/792). Multivariate analysis revealed that CSI was not an independent prognostic factor for survival outcomes in the 792 patients with NPC; however, the Chi-square test showed a different distribution of treatment strategies with ICT for patients with and without CSI. After stratification by ICT, CSI was an independent prognostic factor for overall survival (OS) (p = 0.049) in patients without ICT, but not for distant metastasis-free, local recurrence-free, or progression-free survival (p˃0.05). Additionally, ICT improved OS in patients with CSI (hazard ratio, 0.42; p = 0.019). Matched pair analysis showed that patients with CSI gained prolonged OS from ICT compared with the non-ICT group (88.4 % vs 69.4 %, p = 0.028).Conclusion: CSI was an independent negative prognostic factor for OS in patients with NPC without ICT and might be an imaging marker for identifying eligible candidates for ICT. [ABSTRACT FROM AUTHOR]