Image-based diagnosis of residual or recurrent nasopharyngeal carcinoma may be a phantom tumor phenomenon

Enhancing Nasopharyngeal Carcinoma Survival Prediction: Integrating Pre- and Post-Treatment MRI Radiomics with Clinical Data

Recurrences are frequent in nasopharyngeal carcinoma (NPC) despite high remission rates with treatment, leading to considerable morbidity. This study aimed to develop a prediction model for NPC survival by harnessing both pre- and post-treatment magnetic resonance imaging (MRI) radiomics in conjunction with clinical data, focusing on 3-year progression-free survival (PFS) as the primary outcome. Our comprehensive approach involved retrospective clinical and MRI data collection of 276 eligible NPC patients from three independent hospitals (180 in the training cohort, 46 in the validation cohort, and 50 in the external cohort) who underwent MRI scans twice, once within 2 months prior to treatment and once within 10 months after treatment. From the contrast-enhanced T1-weighted images before and after treatment, 3404 radiomics features were extracted. These features were not only derived from the primary lesion but also from the adjacent lymph nodes surrounding the tumor. We conducted appropriate feature selection pipelines, followed by Cox proportional hazards models for survival analysis. Model evaluation was performed using receiver operating characteristic (ROC) analysis, the Kaplan-Meier method, and nomogram construction. Our study unveiled several crucial predictors of NPC survival, notably highlighting the synergistic combination of pre- and post-treatment data in both clinical and radiomics assessments. Our prediction model demonstrated robust performance, with an accuracy of AUCs of 0.66 (95% CI: 0.536-0.779) in the training cohort, 0.717 (95% CI: 0.536-0.883) in the testing cohort, and 0.827 (95% CI: 0.684-0.948) in validation cohort in prognosticating patient outcomes. Our study presented a novel and effective prediction model for NPC survival, leveraging both pre- and post-treatment clinical data in conjunction with MRI features. Its constructed nomogram provides potentially significant implications for NPC research, offering clinicians a valuable tool for individualized treatment planning and patient counseling.

Posttreatment Head and Neck Cancer Imaging: Anatomic Considerations Based on Cancer Subsites

Posttreatment imaging surveillance of head and neck cancer is challenging owing to complex anatomic subsites and diverse treatment modalities. Early detection of residual disease or recurrence through surveillance imaging is crucial for devising optimal treatment strategies. Posttreatment imaging surveillance is performed using CT, fluorine 18-fluorodeoxyglucose PET/CT, and MRI. Radiologists should be familiar with postoperative imaging findings that can vary depending on surgical procedures and reconstruction methods that are used, which is dictated by the primary subsite and extent of the tumor. Morphologic changes in normal structures or denervation of muscles within the musculocutaneous flap may mimic recurrent tumors. Recurrence is more likely to occur at the resection margin, margin of the reconstructed flap, and deep sites that are difficult to access surgically. Radiation therapy also has a varying dose distribution depending on the primary site, resulting in various posttreatment changes. Normal tissues are affected by radiation, with edema and inflammation occurring in the early stages and fibrosis in the late stages. Distinguishing scar tissue from residual tumor becomes necessary, as radiation therapy may leave behind residual scar tissue. Local recurrence should be carefully evaluated within areas where these postradiation changes occur. Head and Neck Imaging Reporting and Data System (NI-RADS) is a standardized reporting and risk classification system with guidance for subsequent management. Familiarity with NI-RADS has implications for establishing surveillance protocols, interpreting posttreatment images, and management decisions. Knowledge of posttreatment imaging characteristics of each subsite of head and neck cancers and the areas prone to recurrence empowers radiologists to detect recurrences at early stages. ©RSNA, 2024 Test Your Knowledge questions in the supplemental material and the slide presentation from the RSNA Annual Meeting are available for this article.

Development and validation of an MRI-based radiomic model for predicting overall survival in nasopharyngeal carcinoma patients with local residual tumors after intensity-modulated radiotherapy

BACKGROUND

To investigate the potential value of the pretreatment MRI-based radiomic model in predicting the overall survival (OS) of nasopharyngeal carcinoma (NPC) patients with local residual tumors after intensity-modulated radiotherapy (IMRT).

METHODS

A total of 218 consecutive nonmetastatic NPC patients with local residual tumors after IMRT [training cohort (n = 173) and validation cohort (n = 45)] were retrospectively included in this study. Clinical and MRI data were obtained. Univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) were used to select the radiomic features from pretreatment MRI. The clinical, radiomic, and combined models for predicting OS were constructed. The models' performances were evaluated using Harrell's concordance index (C-index), calibration curve, and decision curve analysis.

RESULTS

The C-index of the radiomic model was higher than that of the clinical model, with the C-index of 0.788 (95% CI 0.724-0.852) versus 0.672 (95% CI 0.599-0.745) in the training cohort and 0.753 (95% CI 0.604-0.902) versus 0.634 (95% CI 0.593-0.675) in the validation cohort. Calibration curves showed good agreement between the radiomic model-predicted probability of 2- and 3-year OS and the actual observed probability in the training and validation groups. Decision curve analysis showed that the radiomic model had higher clinical usefulness than the clinical model. The discrimination of the combined model improved significantly in the training cohort (P < 0.01) but not in the validation cohort, with the C-index of 0.834 and 0.734, respectively. The radiomic model divided patients into high- and low-risk groups with a significant difference in OS in both the training and validation cohorts.

CONCLUSIONS

Pretreatment MRI-based radiomic model may improve OS prediction in NPC patients with local residual tumors after IMRT and may assist in clinical decision-making.

Clinical Characteristics and Predictive Outcomes of Recurrent Nasopharyngeal Carcinoma-A Lingering Pitfall of the Long Latency

Purpose: To investigate the clinical characteristics, risk factors, and clinical outcomes of long-latent recurrence (>five years) of nasopharyngeal carcinoma (NPC). Methods: This retrospective study enrolled newly diagnosed NPC patients from the Chang Gung Research Database between January 2007 and December 2019. We analyzed the patients’ characteristics and survival outcomes after recurrence. Results: A total of 2599 NPC patients were enrolled. The overall recurrence rate was 20.5%, while 8.1% of patients had long-latent recurrence (>five years). These patients had a higher percentage of initial AJCC (The American Joint Committee on Cancer) stage I/II (60.5%, p = 0.001) and local recurrence (46.5%, p < 0.001). Unresectable rT3 and rT4 were found in 60% of patients when recurrence and 30% of local recurrence occurred in the skull base, which could not be detected by the regular endoscopy. The five-year overall survival rate of long-latent recurrence was 19.7%. Alive patients tended to be asymptomatic but have regular follow-ups with the interval less than six months. Multivariate analysis showed age and initial advanced AJCC stages were independent risk factors of death after recurrence. In contrast, patients with recurrence between two and five years, salvage surgeries, and regional recurrence had favorable survival outcomes. Conclusion: Long-latent NPC recurrence is not rare, and the survival outcome is poor. Regular follow-up for early detection of NPC recurrence is necessary even after five years of disease-free period.