Criteria for the diagnosis of extranodal extension detected on radiological imaging in head and neck cancer: Head and Neck Cancer International Group consensus recommendations.

Extranodal extension of tumour on histopathology is known to be a negative prognostic factor in head and neck cancer. Compelling evidence suggests that extranodal extension detected on radiological imaging is also a negative prognostic factor. Furthermore, if imaging detected extranodal extension could be identified reliably before the start of treatment, it could be used to guide treatment selection, as patients might be better managed with non-surgical approaches to avoid the toxicity and cost of trimodality therapy (surgery, chemotherapy, and radiotherapy together). There are many aspects of imaging detected extranodal extension that remain unresolved or are without consensus, such as the criteria to best diagnose them and the associated terminology. The Head and Neck Cancer International Group conducted a five-round modified Delphi process with a group of 18 international radiology experts, representing 14 national clinical research groups. We generated consensus recommendations on the terminology and diagnostic criteria for imaging detected extranodal extension to harmonise clinical practice and research. These recommendations have been endorsed by 19 national and international organisations, representing 34 countries. We propose a new classification system to aid diagnosis, which was supported by most of the participating experts over existing systems, and which will require validation in the future. Additionally, we have created an online educational resource for grading imaging detected extranodal extensions.

Deep learning for the automatic detection and segmentation of parotid gland tumors on MRI.

OBJECTIVES: Parotid gland tumors (PGTs) often occur as incidental findings on magnetic resonance images (MRI) that may be overlooked. This study aimed to construct and validate a deep learning model to automatically identify parotid glands (PGs) with a PGT from normal PGs, and in those with a PGT to segment the tumor. MATERIALS AND METHODS: The nnUNet combined with a PG-specific post-processing procedure was used to develop the deep learning model trained on T1-weighed images (T1WI) in 311 patients (180 PGs with tumors and 442 normal PGs) and fat-suppressed (FS)-T2WI in 257 patients (125 PGs with tumors and 389 normal PGs), for detecting and segmenting PGTs with five-fold cross-validation. Additional validation set separated by time, comprising T1WI in 34 and FS-T2WI in 41 patients, was used to validate the model performance. RESULTS AND CONCLUSION: To identify PGs with tumors from normal PGs, using combined T1WI and FS-T2WI, the deep learning model achieved an accuracy, sensitivity and specificity of 98.2% (497/506), 100% (119/119) and 97.7% (378/387), respectively, in the cross-validation set and 98.5% (67/68), 100% (20/20) and 97.9% (47/48), respectively, in the validation set. For patients with PGTs, automatic segmentation of PGTs on T1WI and FS-T2WI achieved mean dice coefficients of 86.1% and 84.2%, respectively, in the cross-validation set, and of 85.9% and 81.0%, respectively, in the validation set. The proposed deep learning model may assist the detection and segmentation of PGTs and, by acting as a second pair of eyes, ensure that incidentally detected PGTs on MRI are not missed.

Early detection of nasopharyngeal carcinoma: performance of a short contrast-free screening magnetic resonance imaging.

BACKGROUND: Although contrast-enhanced magnetic resonance imaging (MRI) detects early-stage nasopharyngeal carcinoma (NPC) not detected by endoscopic-guided biopsy (EGB), a short contrast-free screening MRI would be desirable for NPC screening programs. This study evaluated a screening MRI in a plasma Epstein-Barr virus (EBV)-DNA NPC screening program. METHODS: EBV-DNA-screen-positive patients underwent endoscopy, and endoscopy-positive patients underwent EGB. EGB was negative if the biopsy was negative or was not performed. Patients also underwent a screening MRI. Diagnostic performance was based on histologic confirmation of NPC in the initial study or during a follow-up period of at least 2 years. RESULTS: The study prospectively recruited 354 patients for MRI and endoscopy; 40/354 (11.3%) endoscopy-positive patients underwent EGB. Eighteen had NPC (5.1%), and 336 without NPC (94.9%) were followed up for a median of 44.8 months. MRI detected additional NPCs in 3/18 (16.7%) endoscopy-negative and 2/18 (11.1%) EGB-negative patients (stage I/II, n = 4; stage III, n = 1). None of the 24 EGB-negative patients who were MRI-negative had NPC. MRI missed NPC in 2/18 (11.1%), one of which was also endoscopy-negative. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of MRI, endoscopy, and EGB were 88.9%, 91.1%, 34.8%, 99.4%, and 91.0%; 77.8%, 92.3%, 35.0%, 98.7%, and 91.5%; and 66.7%, 92.3%, 31.6%, 98.1%, and 91.0%, respectively. CONCLUSION: A quick contrast-free screening MRI complements endoscopy in NPC screening programs. In EBV-screen-positive patients, MRI enables early detection of NPC that is endoscopically occult or negative on EGB and increases confidence that NPC has not been missed.

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.

Recommendations for Epstein-Barr virus-based screening for nasopharyngeal cancer in high- and intermediate-risk regions.

A meeting of experts was held in November 2021 to review and discuss available data on performance of Epstein-Barr virus (EBV)-based approaches to screen for early stage nasopharyngeal carcinoma (NPC) and methods for the investigation and management of screen-positive individuals. Serum EBV antibody and plasma EBV DNA testing methods were considered. Both approaches were found to have favorable performance characteristics and to be cost-effective in high-risk populations. In addition to endoscopy, use of magnetic resonance imaging (MRI) to investigate screen-positive individuals was found to increase the sensitivity of NPC detection with minimal impact on cost-effectiveness of the screening program.

Discriminating between benign and malignant salivary gland tumors using diffusion-weighted imaging and intravoxel incoherent motion at 3 Tesla.

PURPOSE: The purpose of this study was to retrospectively evaluate the diagnostic performances of diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) for discriminating between benign and malignant salivary gland tumors (SGTs). MATERIALS AND METHODS: Sixty-seven patients with 71 SGTs who underwent MRI examination at 3 Tesla were included. There were 34 men and 37 women with a mean age of 57 ± 17 (SD) years (age range: 20-90 years). SGTs included 21 malignant tumors (MTs) and 50 benign SGTs (33 pleomorphic adenomas [PAs] and 17 Warthin's tumors [WTs]). For each SGT, DWI and IVIM parameters, mean, skewness, and kurtosis of apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*) and perfusion volume fraction (f) were calculated and further compared between SGTs using univariable analysis. Areas under the curves (AUC) of receiver operating characteristic of significant parameters were compared using the Delong test. RESULTS: Significant differences in ADCmean, Dmean and D*mean were found between SGTs (P < 0.001). The highest AUC values were obtained for ADCmean (0.949) for identifying PAs and D*mean (0.985) for identifying WTs and skewness and kurtosis did not outperform mean. To discriminate benign from malignant SGTs with thresholds set to maximize Youden index, IVIM and DWI produced accuracies of 85.9% (61/71; 95% CI: 75.6-93.0) and 77.5% (55/71; 95% CI: 66.0-86.5) but misdiagnosed MTs as benign in 28.6% (6/21) and 61.9% (13/21) of SGTs, respectively. After maximizing specificity to 100% for benign SGTs, the accuracies of IVIM and DWI decreased to 76.1% (54/71; 95% CI: 64.5-85.4) and 64.8% (46/71; 95% CI: 52.5-75.8) but no MTs were misdiagnosed as benign. IVIM and DWI correctly diagnosed 66.0% (33/50) and 50.0% (25/50) of benign SGTs and 46.5% (33/71) and 35.2% (25/71) of all SGTs, respectively. CONCLUSION: IVIM is more accurate than DWI for discriminating between benign and malignant SGTs because of its advantage in detecting WTs. Thresholds set by maximizing specificity for benign SGTs may be advantageous in a clinical setting.

Normal size of benign upper neck nodes on MRI: parotid, submandibular, occipital, facial, retroauricular and level IIb nodal groups.

PURPOSE: Nodal size is an important imaging criterion for differentiating benign from malignant nodes in the head and neck cancer staging. This study evaluated the size of normal nodes in less well-documented nodal groups in the upper head and neck on magnetic resonance imaging (MRI). METHODS: Analysis was performed on 289 upper head and neck MRIs of patients without head and neck cancer. The short axial diameters (SAD) of the largest node in the parotid, submandibular, occipital, facial, retroauricular and Level IIb of the upper internal jugular nodal groups were documented and compared to the commonly used threshold of ≥ 10 mm for diagnosis of a malignant node. RESULTS: Normal nodes in the parotid, occipital, retroauricular and Level IIb groups were small with a mean SAD ranging from 3.8 to 4.4 mm, nodes in the submandibular group were larger with a mean SAD of 5.5 mm and facial nodes were not identified. A size ≥ 10 mm was found in 0.8% of submandibular nodes. Less than 10% of the other nodal group had a SAD of ≥ 6 mm and none of them had a SAD ≥ 8 mm. CONCLUSION: To identify malignant neck nodes in these groups there is scope to reduce the size threshold of ≥ 10 mm to improve sensitivity without substantial loss of specificity.

Radiomics for Discriminating Benign and Malignant Salivary Gland Tumors; Which Radiomic Feature Categories and MRI Sequences Should Be Used?

The lack of a consistent MRI radiomic signature, partly due to the multitude of initial feature analyses, limits the widespread clinical application of radiomics for the discrimination of salivary gland tumors (SGTs). This study aimed to identify the optimal radiomics feature category and MRI sequence for characterizing SGTs, which could serve as a step towards obtaining a consensus on a radiomics signature. Preliminary radiomics models were built to discriminate malignant SGTs (n = 34) from benign SGTs (n = 57) on T1-weighted (T1WI), fat-suppressed (FS)-T2WI and contrast-enhanced (CE)-T1WI images using six feature categories. The discrimination performances of these preliminary models were evaluated using 5-fold-cross-validation with 100 repetitions and the area under the receiver operating characteristic curve (AUC). The differences between models' performances were identified using one-way ANOVA. Results show that the best feature categories were logarithm for T1WI and CE-T1WI and exponential for FS-T2WI, with AUCs of 0.828, 0.754 and 0.819, respectively. These AUCs were higher than the AUCs obtained using all feature categories combined, which were 0.750, 0.707 and 0.774, respectively (p < 0.001). The highest AUC (0.846) was obtained using a combination of T1WI + logarithm and FS-T2WI + exponential features, which reduced the initial features by 94.0% (from 1015 × 3 to 91 × 2). CE-T1WI did not improve performance. Using one feature category rather than all feature categories combined reduced the number of initial features without compromising radiomic performance.

Radiomics for Discrimination between Early-Stage Nasopharyngeal Carcinoma and Benign Hyperplasia with Stable Feature Selection on MRI.

Discriminating early-stage nasopharyngeal carcinoma (NPC) from benign hyperplasia (BH) on MRI is a challenging but important task for the early detection of NPC in screening programs. Radiomics models have the potential to meet this challenge, but instability in the feature selection step may reduce their reliability. Therefore, in this study, we aim to discriminate between early-stage T1 NPC and BH on MRI using radiomics and propose a method to improve the stability of the feature selection step in the radiomics pipeline. A radiomics model was trained using data from 442 patients (221 early-stage T1 NPC and 221 with BH) scanned at 3T and tested on 213 patients (99 early-stage T1 NPC and 114 BH) scanned at 1.5T. To verify the improvement in feature selection stability, we compared our proposed ensemble technique, which uses a combination of bagging and boosting (BB-RENT), with the well-established elastic net. The proposed radiomics model achieved an area under the curve of 0.85 (95% confidence interval (CI): 0.82−0.89) and 0.80 (95% CI: 0.74−0.86) in discriminating NPC and BH in the 3T training and 1.5T testing cohort, respectively, using 17 features selected from a pool of 422 features by the proposed feature selection technique. BB-RENT showed a better feature selection stability compared to the elastic net (Jaccard index = 0.39 ± 0.14 and 0.24 ± 0.06, respectively; p < 0.001).

Prognostic value of cervical nodal necrosis on staging imaging of nasopharyngeal carcinoma in era of intensity-modulated radiotherapy: a systematic review and meta-analysis.

PURPOSES: To systematically review and perform meta-analysis to evaluate the prognostic value of cervical nodal necrosis (CNN) on the staging computed tomography/magnetic resonance imaging (MRI) of nasopharyngeal carcinoma (NPC) in era of intensity-modulated radiotherapy. METHODS: Literature search through PubMed, EMBASE, and Cochrane Library was conducted. The hazard ratios (HRs) with 95% confidence intervals (CIs) of CNN for distant metastasis-free survival (DMFS), disease free survival (DFS) and overall survival (OS) were extracted from the eligible studies and meta-analysis was performed to evaluate the pooled HRs with 95%CI. RESULTS: Nine studies, which investigated the prognostic values of 6 CNN patterns on MRI were included. Six/9 studies were eligible for meta-analysis, which investigated the CNN presence/absence in any nodal group among 4359 patients. The pooled unadjusted HRs showed that the CNN presence predicted poor DMFS (HR =1.89, 95%CI =1.72-2.08), DFS (HR =1.57, 95%CI =1.08-2.26), and OS (HR =1.87, 95%CI =1.69-2.06). The pooled adjusted HRs also showed the consistent results for DMFS (HR =1.34, 95%CI =1.17-1.54), DFS (HR =1.30, 95%CI =1.08-1.56), and OS (HR =1.61, 95%CI =1.27-2.04). Results shown in the other studies analysing different CNN patterns indicated the high grade of CNN predicted poor outcome, but meta-analysis was unable to perform because of the heterogeneity of the analysed CNN patterns. CONCLUSION: The CNN observed on the staging MRI is a negative factor for NPC outcome, suggesting that the inclusion of CNN is important in the future survival analysis. However, whether and how should CNN be included in the staging system warrant further evaluation.

Utility of Epstein-Barr Virus DNA in Nasopharynx Swabs as a Reflex Test to Triage Seropositive Individuals in Nasopharyngeal Carcinoma Screening Programs.

BACKGROUND: Epstein-Barr virus (EBV) DNA detection in the nasopharynx is considered a biomarker for nasopharyngeal carcinoma (NPC). We evaluated its performance as a reflex test to triage EBV seropositives within an NPC screening program in China. METHODS: The study population was embedded within an ongoing NPC screening trial and included 1111 participants who screened positive for anti-EBV VCA (antibodies against EBV capsid antigens)/EBNA1 (EBV nuclear antigen1)-IgA antibodies (of 18 237 screened). Nasopharynx swabs were collected/tested for EBNA1 gene EBV DNA load. We evaluated performance of EBV DNA in the nasopharynx swab as a reflex test to triage EBV serological high-risk (those referred to endoscopy/MRI) and medium-risk (those referred to accelerated screening) individuals. RESULTS: By the end of 2019, we detected 20 NPC cases from 317 serological high-risk individuals and 4 NPC cases from 794 medium-risk individuals. When used to triage serological high-risk individuals, nasopharynx swab EBV DNA was detected in 19/20 cases (positivity rate among cases: 95.0%; 95% CI, 75.1%-99.9%), with a referral rate of 63.4% (201/317, 95% CI, 57.8%-68.7%) and NPC detection rate among positives of 9.5% (19/201, 95% CI, 5.8%-14.4%). The performance of an algorithm that combined serology with triage of serology high-risk individuals using EBV DNA testing yielded a sensitivity of 72.4% (95% CI, 3.0%-81.4%) and specificity of 97.6% (95% CI, 97.2%-97.9%). When used to triage EBV serological medium-risk individuals, the positivity rate among cases was 75.0% (95% CI, 19.4%-99.4%), with a referral rate of 61.8% (95% CI, 58.4%-65.2%) and NPC detection rate among positives of 0.6% (95% CI, 0.1%-1.8%). CONCLUSIONS: Nasopharynx swab EBV DNA showed promise as a reflex test to triage serology high-risk individuals, reducing referral by ca. 40% with little reduction in sensitivity compared to a serology-only screening program.

Automatic detection and segmentation of morphological changes of the maxillary sinus mucosa on cone-beam computed tomography images using a three-dimensional convolutional neural network.

OBJECTIVES: To propose and evaluate a convolutional neural network (CNN) algorithm for automatic detection and segmentation of mucosal thickening (MT) and mucosal retention cysts (MRCs) in the maxillary sinus on low-dose and full-dose cone-beam computed tomography (CBCT). MATERIALS AND METHODS: A total of 890 maxillary sinuses on 445 CBCT scans were analyzed. The air space, MT, and MRCs in each sinus were manually segmented. Low-dose CBCTs were divided into training, training-monitoring, and testing datasets at a 7:1:2 ratio. Full-dose CBCTs were used as a testing dataset. A three-step CNN algorithm built based on V-Net and support vector regression was trained on low-dose CBCTs and tested on the low-dose and full-dose datasets. Performance for detection of MT and MRCs using area under the curves (AUCs) and for segmentation using Dice similarity coefficient (DSC) was evaluated. RESULTS: For the detection of MT and MRCs, the algorithm achieved AUCs of 0.91 and 0.84 on low-dose scans and of 0.89 and 0.93 on full-dose scans, respectively. The median DSCs for segmenting the air space, MT, and MRCs were 0.972, 0.729, and 0.678 on low-dose scans and 0.968, 0.663, and 0.787 on full-dose scans, respectively. There were no significant differences in the algorithm performance between low-dose and full-dose CBCTs. CONCLUSIONS: The proposed CNN algorithm has the potential to accurately detect and segment MT and MRCs in maxillary sinus on CBCT scans with low-dose and full-dose protocols. CLINICAL RELEVANCE: An implementation of this artificial intelligence application in daily practice as an automated diagnostic and reporting system seems possible.

MR Imaging of Nasopharyngeal Carcinoma.

Nasopharyngeal carcinoma is endemic in parts of the world such as southern China and Southeast Asia. It is predominantly an undifferentiated carcinoma with a strong genetic basis and a close association with the Epstein-Barr virus. The ability of MR imaging to depict the boundaries of the primary tumor and its relationship with the complex structures of the skull base makes it the technique of choice for imaging of this disease in the head and neck. This article describes the MR imaging findings pertinent to staging and management and a new role of MR imaging in early cancer detection, in addition to a brief discussion of differential diagnoses.

A convolutional neural network combined with positional and textural attention for the fully automatic delineation of primary nasopharyngeal carcinoma on non-contrast-enhanced MRI.

BACKGROUND: Convolutional neural networks (CNNs) have the potential to automatically delineate primary nasopharyngeal carcinoma (NPC) on magnetic resonance imaging (MRI), but currently, the literature lacks a module to introduce valuable pre-computed features into a CNN. In addition, most CNNs for primary NPC delineation have focused on contrast-enhanced MRI. To enable the use of CNNs in clinical applications where it would be desirable to avoid contrast agents, such as cancer screening or intra-treatment monitoring, we aim to develop a CNN algorithm with a positional-textural fully-connected attention (FCA) module that can automatically delineate primary NPCs on contrast-free MRI. METHODS: This retrospective study was performed in 404 patients with NPC who had undergone staging MRI. A proposed CNN algorithm incorporated with our positional-textural FCA module (Aproposed ) was trained on manually delineated tumours (M1st ) to automatically delineate primary NPCs on non-contrast-enhanced T2-weighted fat-suppressed (NE-T2W-FS) images. The performance of Aproposed , three well-established CNNs, Unet (Aunet ), Attention-Unet (Aatt ) and Dense-Unet (Adense ), and a second manual delineation repeated to evaluate human variability (M 2 nd ) were measured by comparing to the reference standard M 1 st to obtain the Dice similarity coefficient (DSC) and average surface distance (ASD). The Wilcoxon rank test was used to compare the performance of Aproposed against Aunet , Aatt , Adense and M 2 nd . RESULTS: Aproposed showed a median DSC of 0.79 (0.10) and ASD of 0.66 (0.84) mm. It performed better than the well-established networks Aunet [DSC =0.75 (0.12) and ASD =1.22 (1.73) mm], Aatt [DSC =0.75 (0.10) and ASD =0.96 (1.16) mm] and Adense [DSC =0.71 (0.14) and ASD =1.67 (1.92) mm] (all P<0.01), but slightly worse when compared to M 2 nd [DSC =0.81 (0.07) and ASD =0.56 (0.80) mm] (P<0.001). CONCLUSIONS: The proposed CNN algorithm has potential to accurately delineate primary NPCs on non-contrast-enhanced MRI.

Nasopharyngeal carcinoma: an evolving paradigm.

The past three decades have borne witness to many advances in the understanding of the molecular biology and treatment of nasopharyngeal carcinoma (NPC), an Epstein-Barr virus (EBV)-associated cancer endemic to southern China, southeast Asia and north Africa. In this Review, we provide a comprehensive, interdisciplinary overview of key research findings regarding NPC pathogenesis, treatment, screening and biomarker development. We describe how technological advances have led to the advent of proton therapy and other contemporary radiotherapy approaches, and emphasize the relentless efforts to identify the optimal sequencing of chemotherapy with radiotherapy through decades of clinical trials. Basic research into the pathogenic role of EBV and the genomic, epigenomic and immune landscape of NPC has laid the foundations of translational research. The latter, in turn, has led to the development of new biomarkers and therapeutic targets and of improved approaches for individualizing immunotherapy and targeted therapies for patients with NPC. We provide historical context to illustrate the effect of these advances on treatment outcomes at present. We describe current preclinical and clinical challenges and controversies in the hope of providing insights for future investigation.

Comparison of new magnetic resonance imaging grading system with conventional endoscopy for the early detection of nasopharyngeal carcinoma.

BACKGROUND: Although stratifying individuals with respect to nasopharyngeal carcinoma (NPC) risk with Epstein-Barr virus-based markers is possible, the performance of diagnostic methods for detecting lesions among screen-positive individuals is poorly understood. METHODS: The authors prospectively evaluated 882 participants aged 30 to 70 years who were enrolled between October 2014 and November 2018 in an ongoing, population-based NPC screening program and had an elevated NPC risk. Participants were offered endoscopy and magnetic resonance imaging (MRI), and lesions were identified either by biopsy at a follow-up endoscopy or further contact and linkage to the local cancer registry through December 31, 2019. The diagnostic performance characteristics of endoscopy and MRI for NPC detection were investigated. RESULTS: Eighteen of 28 identified NPC cases were detected by both methods, 1 was detected by endoscopy alone, and 9 were detected by MRI alone. MRI had significantly higher sensitivity than endoscopy for NPC detection overall (96.4% vs 67.9%; Pdifference = .021) and for early-stage NPC (95.2% vs 57.1%; P = .021). The sensitivity of endoscopy was suggestively lower among participants who had previously been screened in comparison with those undergoing an initial screening (50.0% vs 81.2%; P = .11). The authors observed a higher overall referral rate by MRI versus endoscopy (17.3% vs 9.1%; P < .001). Cases missed by endoscopy had early-stage disease and were more commonly observed for tumors originating from the pharyngeal recess. CONCLUSIONS: MRI was more sensitive than endoscopy for NPC detection in the context of population screening but required the referral of a higher proportion of screen-positive individuals. The sensitivity of endoscopy was particularly low for individuals who had previously been screened.

Dynamic Changes of Post-Radiotherapy Plasma Epstein-Barr Virus DNA in a Randomized Trial of Adjuvant Chemotherapy Versus Observation in Nasopharyngeal Cancer.

PURPOSE: To study the dynamic changes in plasma Epstein-Barr virus (pEBV) DNA after radiotherapy in nasopharyngeal cancer (NPC). EXPERIMENTAL DESIGN: We conducted a randomized controlled trial of adjuvant chemotherapy versus observation in patients with NPC who had detectable pEBV DNA at 6 weeks post-radiotherapy. Randomized patients had a second pEBV DNA checked at 6 months post-randomization. The primary endpoint was progression-free survival (PFS). RESULTS: We prospectively enrolled 789 patients. Baseline post-radiotherapy pEBV DNA was undetectable in 573 (72.6%) patients, and detectable in 216 (27.4%) patients, of whom 104 (13.2%) patients were eligible for randomization to adjuvant chemotherapy (n = 52) versus observation (n = 52). The first post-radiotherapy pEBV DNA had a sensitivity of 0.48, specificity of 0.81, area under receiver-operator characteristics curve (AUC) of 0.65, false positive (FP) rate of 13.8%, and false negative (FN) rate of 14.4% for disease progression. The second post-radiotherapy pEBV DNA had improved sensitivity of 0.81, specificity of 0.75, AUC of 0.78, FP rate of 14.3%, and FN rate of 8.1%. Patients with complete clearance of post-radiotherapy pEBV DNA (51%) had survival superior to that of patients without post-radiotherapy pEBV DNA clearance (5-year PFS, 85.5% vs. 23.3%; HR, 9.6; P < 0.0001), comparable with patients with initially undetectable post-radiotherapy pEBV DNA (5-year PFS, 77.1%), irrespective of adjuvant chemotherapy or observation. CONCLUSIONS: Patients with NPC with detectable post-radiotherapy pEBV DNA who experienced subsequent pEBV DNA clearance had superior survival comparable with patients with initially undetectable post-radiotherapy pEBV DNA. Post-radiotherapy pEBV DNA clearance may serve as an early surrogate endpoint for long-term survival in NPC.

Convolutional neural network in nasopharyngeal carcinoma: how good is automatic delineation for primary tumor on a non-contrast-enhanced fat-suppressed T2-weighted MRI?

PURPOSE: Convolutional neural networks (CNNs) show potential for delineating cancers on contrast-enhanced MRI (ce-MRI) but there are clinical scenarios in which administration of contrast is not desirable. We investigated performance of the CNN for delineating primary nasopharyngeal carcinoma (NPC) on non-contrast-enhanced images and compared the performance to that on ce-MRI. MATERIALS AND METHODS: We retrospectively analyzed primary NPC in 195 patients using a well-established CNN, U-Net, for tumor delineation on the non-contrast-enhanced fat-suppressed (fs)-T2W, ce-T1W and ce-fs-T1W images. The CNN-derived delineations were compared to manual delineations to obtain Dice similarity coefficient (DSC) and average surface distance (ASD). The DSC and ASD on fs-T2W were compared to those on ce-MRI. Primary tumor volumes (PTVs) of CNN-derived delineations were compared to that of manual delineations. RESULTS: The CNN for NPC delineation on fs-T2W images showed similar DSC (0.71 ± 0.09) and ASD (0.21 ± 0.48 cm) to those on ce-T1W images (0.71 ± 0.09 and 0.17 ± 0.19 cm, respectively) (p > 0.05), and lower DSC but similar ASD to ce-fs-T1W images (0.73 ± 0.09, p < 0.001; and 0.17 ± 0.20 cm, p > 0.05). The CNN overestimated PTVs on all sequences (p < 0.001). CONCLUSION: The CNN showed promise for NPC delineation on fs-T2W images in cases where it is desirable to avoid contrast agent injection. The CNN overestimated PTVs on all sequences.