MR Imaging Criteria for the Detection of Nasopharyngeal Carcinoma: Discrimination of Early-Stage Primary Tumors from Benign Hyperplasia

Magnetic resonance imaging based on radiomics for differentiating T1-category nasopharyngeal carcinoma from nasopharyngeal lymphoid hyperplasia: a multicenter study

PURPOSE

To investigate the role of magnetic resonance imaging (MRI) based on radiomics using T2-weighted imaging fat suppression (T2WI-FS) and contrast enhanced T1-weighted imaging (CE-T1WI) sequences in differentiating T1-category nasopharyngeal carcinoma (NPC) from nasopharyngeal lymphoid hyperplasia (NPH).

MATERIALS AND METHODS

This study enrolled 614 patients (training dataset: n = 390, internal validation dataset: n = 98, and external validation dataset: n = 126) of T1-category NPC and NPH. Three feature selection methods were used, including analysis of variance, recursive feature elimination, and relief. The logistic regression classifier was performed to construct the radiomics signatures of T2WI-FS, CE-T1WI, and T2WI-FS + CE-T1WI to differentiate T1-category NPC from NPH. The performance of the optimal radiomics signature (T2WI-FS + CE-T1WI) was compared with those of three radiologists in the internal and external validation datasets.

RESULTS

Twelve, 15, and 15 radiomics features were selected from T2WI-FS, CE-T1WI, and T2WI-FS + CE-T1WI to develop the three radiomics signatures, respectively. The area under the curve (AUC) values for radiomics signatures of T2WI-FS + CE-T1WI and CE-T1WI were significantly higher than that of T2WI-FS (AUCs = 0.940, 0.935, and 0.905, respectively) for distinguishing T1-category NPC and NPH in the training dataset (Ps all < 0.05). In the internal and external validation datasets, the radiomics signatures based on T2WI-FS + CE-T1WI and CE-T1WI outperformed T2WI-FS with no significant difference (AUCs = 0.938, 0.925, and 0.874 for internal validation dataset and 0.932, 0.918, and 0.882 for external validation dataset; Ps > 0.05). The radiomics signature of T2WI-FS + CE-T1WI significantly performed better than three radiologists in the internal and external validation datasets.

CONCLUSION

The MRI-based radiomics signature is meaningful in differentiating T1-category NPC from NPH and potentially helps clinicians select suitable therapy strategies.

Artificial intelligence for diagnosis and prognosis prediction of natural killer/T cell lymphoma using magnetic resonance imaging

Accurate diagnosis and prognosis prediction are conducive to early intervention and improvement of medical care for natural killer/T cell lymphoma (NKTCL). Artificial intelligence (AI)-based systems are developed based on nasopharynx magnetic resonance imaging. The diagnostic systems achieve areas under the curve of 0.905-0.960 in detecting malignant nasopharyngeal lesions and distinguishing NKTCL from nasopharyngeal carcinoma in independent validation datasets. In comparison to human radiologists, the diagnostic systems show higher accuracies than resident radiologists and comparable ones to senior radiologists. The prognostic system shows promising performance in predicting survival outcomes of NKTCL and outperforms several clinical models. For patients with early-stage NKTCL, only the high-risk group benefits from early radiotherapy (hazard ratio = 0.414 vs. late radiotherapy; 95% confidence interval, 0.190-0.900, p = 0.022), while progression-free survival does not differ in the low-risk group. In conclusion, AI-based systems show potential in assisting accurate diagnosis and prognosis prediction and may contribute to therapeutic optimization for NKTCL.

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.

Cross-site prognosis prediction for nasopharyngeal carcinoma from incomplete multi-modal data

Accurate prognosis prediction for nasopharyngeal carcinoma based on magnetic resonance (MR) images assists in the guidance of treatment intensity, thus reducing the risk of recurrence and death. To reduce repeated labor and sufficiently explore domain knowledge, aggregating labeled/annotated data from external sites enables us to train an intelligent model for a clinical site with unlabeled data. However, this task suffers from the challenges of incomplete multi-modal examination data fusion and image data heterogeneity among sites. This paper proposes a cross-site survival analysis method for prognosis prediction of nasopharyngeal carcinoma from domain adaptation viewpoint. Utilizing a Cox model as the basic framework, our method equips it with a cross-attention based multi-modal fusion regularization. This regularization model effectively fuses the multi-modal information from multi-parametric MR images and clinical features onto a domain-adaptive space, despite the absence of some modalities. To enhance the feature discrimination, we also extend the contrastive learning technique to censored data cases. Compared with the conventional approaches which directly deploy a trained survival model in a new site, our method achieves superior prognosis prediction performance in cross-site validation experiments. These results highlight the key role of cross-site adaptability of our method and support its value in clinical practice.

Incidental findings of cervical magnetic resonance imaging: A retrospective reinterpretation of a large adult population

Background

Magnetic resonance imaging (MRI) of the cervical spine is one of the routine MRI scans of the cervical region in investigating spinal disc pathologies, spinal stenosis, and the detection of spinal lesions, which are the major parameters to be evaluated in this examination.

Purpose

The authors of this study are focused on a different aspect of cervical MRI, revealing the incidences and reporting rates of extraspinal incidental findings.

Methods

A total of 1000 patients (324 males, 676 females, mean age 47 ± 14) who had undergone an MRI of the cervical spine were enrolled in this study. The magnetic resonance (MR) images of these patients were re-interpreted with respect to the incidental extraspinal imaging findings. The incidence and reporting rate of each incidental finding encountered during the evaluation were presented in percentages.

Results

726 patients in this study had at least one incidental lesion. The results of this study revealed that the most common incidental lesions encountered during the reinterpretation of cervical MRI were nasopharyngeal mucosal thickening (n = 442) and thyroid hypertrophy (n = 231). The total reporting rate of incidental findings was 5.29%.

Conclusion

There are many data to be reported and evaluated by MR imaging of the cervical spine, not only the main parameters of MRI scanning in the routine daily practice of radiologists. All our colleagues should be aware and careful of these incidental findings, which may be the initial medical data of the patients' diagnoses, or to avoid undesirable medicolegal problems.

Radiological features of thyroid-like low-grade nasopharyngeal papillary adenocarcinoma: case series and systematic review

PURPOSE

To comprehensively summarize the clinical data and CT/MRI characteristics of thyroid-like low-grade nasopharyngeal papillary adenocarcinoma (TL-LGNPPA).

METHODS

Twenty-seven lesions from 25 study articles identified through a systematic review and three lesions from our institution associated with TL-LGNPPA were evaluated.

RESULTS

The mean age of the patients at diagnosis was 35.7 years, and the male-to-female ratio was nearly half. The chief complaint was nasal obstruction, followed by epistaxis. All patients underwent excision. None of the patients had neck nodes or distant metastases. All patients survived with no locoregional/distant recurrence during 3-93 months of follow-up. All lesions were located at the posterior edge of the nasal septum, attached to the nasopharyngeal parietal wall, and showed no laterality. The mean lesion diameter was 1.7 cm. The margins of lesions were well-defined and lobulated, followed by well-defined smooth margins. None of lesions were associated with parapharyngeal space or skull base destruction. All lesions were iso- and low-density on non-contrast CT. Adjacent skull base sclerosis was detected in 63.6% of lesions. High signal intensity on T2-weighted imaging and mostly iso-signal intensity on T1-weighted imaging compared to muscle tissue. Most lesions were heterogeneous and exhibited moderate contrast enhancement. Relatively large lesions (≥1.4 cm) tended to be more lobulated than smooth margins compared to relatively small lesions (<1.4 cm) (p = 0.016).

CONCLUSION

We summarized the clinical and radiological features of TL-LGNPPA to facilitate accurate diagnosis and appropriate management.

Synthetic MRI quantitative parameters in discriminating stage T1 nasopharyngeal carcinoma and benign hyperplasia: Combination with morphological features

PURPOSE

To investigate the feasibility of synthetic MRI (syMRI) quantitative parameters and its combination with morphological features in discriminating stage T1 nasopharyngeal carcinoma (T1-NPC) and benign hyperplasia (BH).

MATERIAL AND METHODS

Eighty-eight patients with nasopharyngeal lesions (T1-NPC, n = 54; BH, n = 34) were retrospectively enrolled between October 2020 and May 2022. The syMRI quantitative parameters of nasopharyngeal lesions (T1, T2, PD, T1SD, T2SD, PDSD) and longus capitis (T1, T2, PD) were measured, and T1ratio, T2ratio and PDratio were calculated (lesion/longus capitis). The morphological features (lesion pattern, retention cyst, serrated protrusion, middle ear effusion, tumor volume, and retropharyngeal lymph node) were compared. Statistical analyses were performed using the independent sample t test, Chi-square test, logistic regression analysis, receiver operating characteristic curve (ROC), and DeLong test.

RESULTS

The T1, T2, PD, T1SD, T1ratio, and T2ratio values of T1-NPC were significantly lower than those of BH. The morphological features (lesion pattern, retention cyst, retropharyngeal lymph node) were significant difference between these two entities. T2 value has the highest AUC in all syMRI quantitative parameters, followed by T1, T1ratio, PD, T2ratio and T1SD. Combined syMRI quantitative parameters (T2, PD, T1ratio) can further improve the diagnosis efficiency. Combined syMRI parameters and morphological feature (T2, PD, lesion pattern, retropharyngeal lymph node) has the excellent diagnostic efficiency, with AUC, sensitivity, specificity, and accuracy of 0.979, 96.30%, 97.06%, 96.77%.

CONCLUSIONS

Synthetic MRI was helpful in distinguishing T1-NPC from BH, and combined syMRI quantitative parameters and morphological features has the optimal diagnostic performance.

Imaging of pharyngeal pathology

The pharynx plays a significant role in swallowing and speech, and this is reflected in both its complex anatomy and degree of physiological motility. Patients who present with pharynx-related symptoms such as sore throat, globus, dysphagia or dysphonia will usually undergo visual and nasal endoscopic examination in the first instance. Imaging is frequently required to supplement clinical assessment and this typically involves MRI and CT. However, fluoroscopy, ultrasound and radionuclide imaging are valuable in certain clinical situations. The aforementioned complexity of the pharynx and the myriad of pathologies which may arise within it often make radiological evaluation challenging. In this pictorial review, we aim to provide a brief overview of cross-sectional pharyngeal anatomy and present the radiological features of a variety of pharyngeal pathologies, both benign and malignant.

Imaging Approach for Cervical Lymph Node Metastases from Unknown Primary Tumor

Neck swelling due to lymph node (LN) metastasis is one of the initial symptoms of head and neck cancer, and in some cases, the primary tumor is not clinically evident. The purpose of imaging for LN metastasis from an unknown primary site is to identify the primary tumor or detect its absence, which leads to the correct diagnosis and optimal treatment. The authors discuss diagnostic imaging approaches for identifying the primary tumor in cases of unknown primary cervical LN metastases. The distribution and characteristics of LN metastases may help locate the primary site. Unknown primary LN metastasis often occurs at nodal levels II and III, and in recent reports, these were mostly related to human papillomavirus (HPV)-positive squamous cell carcinoma of the oropharynx. Another characteristic imaging finding suggestive of metastasis from HPV-associated oropharyngeal cancer is a cystic change in LN metastases. Other characteristic imaging findings such as calcification may help predict the histologic type and locate the primary site. In cases of LN metastases at nodal levels IV and VB, a primary lesion located outside the head and neck region must also be considered. One clue for detecting the primary lesion at imaging is the disruption of anatomic structures, which can help in identifying small mucosal lesions or submucosal tumors at each subsite. Additionally, fluorine 18 fluorodeoxyglucose PET/CT may help identify a primary tumor. These imaging approaches for identifying primary tumors enable prompt identification of the primary site and assist clinicians in making the correct diagnosis. ^© RSNA, 2023 Quiz questions for this article are available through the Online Learning Center.

The utility of texture analysis based on quantitative synthetic magnetic resonance imaging in nasopharyngeal carcinoma: a preliminary study

BACKGROUND

Magnetic resonance imaging (MRI) is commonly used for the diagnosis of nasopharyngeal carcinoma (NPC) and occipital clivus (OC) invasion, but a proportion of lesions may be missed using non-enhanced MRI. The purpose of this study is to investigate the diagnostic performance of synthetic magnetic resonance imaging (SyMRI) in differentiating NPC from nasopharyngeal hyperplasia (NPH), as well as evaluating OC invasion.

METHODS

Fifty-nine patients with NPC and 48 volunteers who underwent SyMRI examination were prospectively enrolled. Eighteen first-order features were extracted from VOIs (primary tumours, benign mucosa, and OC). Statistical comparisons were conducted between groups using the independent-samples t-test and the Mann-Whitney U test to select significant parameters. Multiple diagnostic models were then constructed using multivariate logistic analysis. The diagnostic performance of the models was calculated by receiver operating characteristics (ROC) curve analysis and compared using the DeLong test. Bootstrap and 5-folds cross-validation were applied to avoid overfitting.

RESULTS

The T1, T2 and PD map-derived models had excellent diagnostic performance in the discrimination between NPC and NPH in volunteers, with area under the curves (AUCs) of 0.975, 0.972 and 0.986, respectively. Besides, SyMRI models also showed excellent performance in distinguishing OC invasion from non-invasion (AUC: 0.913-0.997). Notably, the T1 map-derived model showed the highest diagnostic performance with an AUC, sensitivity, specificity, and accuracy of 0.997, 96.9%, 97.9% and 97.5%, respectively. By using 5-folds cross-validation, the bias-corrected AUCs were 0.965-0.984 in discriminating NPC from NPH and 0.889-0.975 in discriminating OC invasion from OC non-invasion.

CONCLUSIONS

SyMRI combined with first-order parameters showed excellent performance in differentiating NPC from NPH, as well as discriminating OC invasion from non-invasion.

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).

MRI detection of suspected nasopharyngeal carcinoma: a systematic review and meta-analysis

Purpose

Endoscopic biopsy is recommended for diagnosis of nasopharyngeal carcinoma (NPC). A proportion of lesions are hidden from endoscopic view but detected with magnetic resonance imaging (MRI). This systematic review and meta-analysis investigated the diagnostic performance of MRI for detection of NPC.

Methods

An electronic search of twelve databases and registries was performed. Studies were included if they compared the diagnostic accuracy of MRI to a reference standard (histopathology) in patients suspected of having NPC. The primary outcome was accuracy for detection of NPC. Random-effects models were used to pool outcomes for sensitivity, specificity, and positive and negative likelihood ratio (LR). Bias and applicability were assessed using the modified QUADAS-2 tool.

Results

Nine studies were included involving 1736 patients of whom 337 were diagnosed with NPC. MRI demonstrated a pooled sensitivity of 98.1% (95% CI 95.2–99.3%), specificity of 91.7% (95% CI 88.3–94.2%), negative LR of 0.02 (95% CI 0.01–0.05), and positive LR of 11.9 (95% CI 8.35–16.81) for detection of NPC. Most studies were performed in regions where NPC is endemic, and there was a risk of selection bias due to inclusion of retrospective studies and one case–control study. There was limited reporting of study randomization strategy.

Conclusion

This study demonstrates that MRI has a high pooled sensitivity, specificity, and negative predictive value for detection of NPC. MRI may be useful for lesion detection prior to endoscopic biopsy and aid the decision to avoid biopsy in patients with a low post-test probability of disease.

The contrast-enhanced MRI can be substituted by unenhanced MRI in identifying and automatically segmenting primary nasopharyngeal carcinoma with the aid of deep learning models: An exploratory study in large-scale population of endemic area

BACKGROUND AND OBJECTIVES

Administration of contrast is not desirable for all cases in clinical setting, and no consensus in sequence selection for deep learning model development has been achieved, thus we aim to explore whether contrast-enhanced magnetic resonance imaging (ceMRI) can be substituted in the identification and segmentation of nasopharyngeal carcinoma (NPC) with the aid of deep learning models in a large-scale cohort.

METHODS

A total of 4478 eligible individuals were randomly split into training, validation and test sets, and self-constrained 3D DenseNet and V-Net models were developed using axial T1-weighted imaging (T1WI), T2WI or enhanced T1WI (T1WIC) images separately. The differential diagnostic performance between NPC and benign hyperplasia were compared among models using chi-square test. Segmentation evaluation metrics, including dice similarity coefficient (DSC) and average surface distance (ASD), were compared using paired student's t-test between T1WIC and T1WI or T2WI models or M_T1/T2, a merged output of malignant region derived from T1WI and T2WI models.

RESULTS

All models exhibited similar satisfactory diagnostic performance in discriminating NPC from benign hyperplasia, all attaining overall accuracy over 99.00% in all T stages of NPC. And T1WIC model exhibited similar average DSC and ASD with those of M_T1/T2 (DSC, 0.768±0.070 vs 0.764±0.070; ASD, 1.573±10.954 mm vs 1.626±10.975 mm 1.626±0.975 mm vs 1.573±0.954 mm, all p > 0.0167) in primary NPC using DenseNet, but yielded a significantly higher DSC and lower ASD than either T1WI model or T2WI model (DSC, 0.759±0.065 or 0.755±0.071; ASD, 1.661±0.898 mm or 1.722±1.133 mm, respectively, all p < 0.01) in the entire test set of NPC cohort. Moreover, the average DSCs and ASDs were not statistically significant between T1WIC model and M_T1/T2 in both.

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.

Multiparametric dual-energy CT to differentiate stage T1 nasopharyngeal carcinoma from benign hyperplasia

Background

Stage T1 nasopharyngeal carcinoma (NPC_T1) and benign hyperplasia (BH) are 2 common causes of nasopharyngeal mucosa/submucosa thickening without specific clinical symptoms. The treatment management of these 2 entities is significantly different. Reliable differentiation between the 2 entities is critical for the treatment decision and prognosis of patients. Therefore, our study aims to explore the optimal energy level of noise-optimized virtual monoenergetic images [VMI (+)] derived from dual-energy computed tomography (DECT) to display NPC_T1 and BH and to explore the clinical value of DECT for differentiating these 2 diseases.

Methods

A total of 91 patients (44 NPC_T1, 47 BH) were enrolled. The demarcation of the lesion margins and overall image quality, noise, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) were evaluated for 40-80 kiloelectron volts (keV) VMIs (+) and polyenergetic images in the contrast-enhanced phase. Image features were assessed in the contrast-enhanced images with optimal visualization of NPC_T1 and BH. The demarcation of NPC_T1 and BH in iodine-water maps was also assessed. The contrast-enhanced images were used to calculate the slope of the spectral Hounsfield unit curve (λ_HU) and normalized iodine concentration (NIC). The nonenhanced phase images were used to calculate the normalized effective atomic number (NZ_eff). The attenuation values on 40-80 keV VMIs (+) in the contrast-enhanced phase were recorded. The diagnostic performance was assessed using receiver operating characteristic (ROC) curve analysis.

Results

The 40 keV VMI (+) in the enhanced phase yielded higher demarcation of the lesion margins scores, overall image quality scores, noise, SNR, and CNR values than 50-80 keV VMIs (+) and polyenergetic images. NPC_T1 yielded higher attenuation values on VMI (+) at 40 keV (A₄₀), NIC, λ_HU, and NZ_eff values than BH. The multivariate logistic regression model combining image features (tumor symmetry) with quantitative parameters (A₄₀, NIC, λ_HU, and NZ_eff) yielded the best performance for differentiating the 2 diseases (AUC: 0.963, sensitivity: 89.4%, specificity: 93.2%).

Conclusions

The combination of DECT-derived image features and quantitative parameters contributed to the differentiation between NPC_T1 and BH.

Effect of high-quality nursing intervention on psychological emotion, life quality and nursing satisfaction of patients with nasopharyngeal carcinoma undergoing radiotherapy

OBJECTIVE

This study was designed to investigate the effect of high-quality nursing (HQN) intervention on psychological emotion, quality of life (QOL) and nursing satisfaction of patients with nasopharyngeal carcinoma (NPC) undergoing radiotherapy.

METHODS

Fifty-eight NPC patients receiving radiotherapy in our hospital between August 2017 and February 2019 were selected and divided into two groups according to different nursing intervention models. Among them, the control group (CG; 28 cases) was given routine nursing intervention, while the research group (RG; 30 cases) was treated with HQN intervention. The efficacy and the incidence of adverse reactions of the two groups were evaluated. Health knowledge awareness rate, psychological mood, QOL, sleep quality and nursing satisfaction were compared between CG and RG.

RESULTS

RG presented significantly higher efficacy and notably lower incidence of adverse reactions than CG after 3 months of nursing intervention. Patients in RG acquired evidently higher knowledge awareness rate regarding radiotherapy, dietary, adverse reaction prevention, self-care and functional exercise than those in RG (P < 0.05). In comparison with CG, the scores of Self-rating Anxiety Scale (SAS) and Self-rating Depression Scale (SDS) as well as Pittsburgh Sleep Quality Index (PSQI) in RG were evidently lower, while the Short-Form 36 Item Health Survey (SF-36) scores and nursing satisfaction were statistically higher.

CONCLUSIONS

HQN intervention is high-performing in NPC patients undergoing radiotherapy, which can effectively improve the curative effect, reduce the incidence of adverse reactions, enhance patients' health knowledge awareness rate while relieving their bad emotions and improving their QOL, sleep quality and nursing satisfaction.

Using arterial spin labeling blood flow and its histogram analysis to distinguish early-stage nasopharyngeal carcinoma from lymphoid hyperplasia

To investigate the feasibility of arterial spin labeling (ASL) blood flow (BF) and its histogram analysis to distinguish early-stage nasopharyngeal carcinoma (NPC) from nasopharyngeal lymphoid hyperplasia (NPLH).Sixty-three stage T1 NPC patients and benign NPLH patients underwent ASL on a 3.0-T magnetic resonance imaging system. BF histogram parameters were derived automatically, including the mean, median, maximum, minimum, kurtosis, skewness, and variance. Absolute values were obtained for skewness and kurtosis (absolute value of skewness [AVS] and absolute value of kurtosis [AVK], respectively). The Mann-Whitney U test, receiver operating characteristic curve, and multiple logistic regression models were used for statistical analysis.The mean, maximum, and variance of ASL BF values were significantly higher in early-stage NPC than in NPLH (all P < 0.0001), while the median and AVK values of early-stage NPC were also significantly higher than those of NPLH (all P < 0.001). No significant difference was found between the minimum and AVS values in early-stage NPC compared with NPLH (P = 0.125 and P = 0.084, respectively). The area under the curve (AUC) of the maximum was significantly higher than those of the mean and median (P < 0.05). The AUC of variance was significantly higher than those of the other parameters (all P < 0.05). Multivariate analysis showed that variance was the only independent predictor of outcome (P < 0.05).ASL BF and its histogram analysis could distinguish early-stage NPC from NPLH, and the variance value was a unique independent predictor.

Convolutional neural network for discriminating nasopharyngeal carcinoma and benign hyperplasia on MRI

OBJECTIVES

A convolutional neural network (CNN) was adapted to automatically detect early-stage nasopharyngeal carcinoma (NPC) and discriminate it from benign hyperplasia on a non-contrast-enhanced MRI sequence for potential use in NPC screening programs.

METHODS

We retrospectively analyzed 412 patients who underwent T2-weighted MRI, 203 of whom had biopsy-proven primary NPC confined to the nasopharynx (stage T1) and 209 had benign hyperplasia without NPC. Thirteen patients were sampled randomly to monitor the training process. We applied the Residual Attention Network architecture, adapted for three-dimensional MR images, and incorporated a slice-attention mechanism, to produce a CNN score of 0-1 for NPC probability. Threefold cross-validation was performed in 399 patients. CNN scores between the NPC and benign hyperplasia groups were compared using Student's t test. Receiver operating characteristic with the area under the curve (AUC) was performed to identify the optimal CNN score threshold.

RESULTS

In each fold, significant differences were observed in the CNN scores between the NPC and benign hyperplasia groups (p < .01). The AUCs ranged from 0.95 to 0.97 with no significant differences between the folds (p = .35 to .92). The combined AUC from all three folds (n = 399) was 0.96, with an optimal CNN score threshold of > 0.71, producing a sensitivity, specificity, and accuracy of 92.4%, 90.6%, and 91.5%, respectively, for NPC detection.

CONCLUSION

Our CNN method applied to T2-weighted MRI could discriminate between malignant and benign tissues in the nasopharynx, suggesting that it as a promising approach for the automated detection of early-stage NPC.

KEY POINTS

• The convolutional neural network (CNN)-based algorithm could automatically discriminate between malignant and benign diseases using T2-weighted fat-suppressed MR images. • The CNN-based algorithm had an accuracy of 91.5% with an area under the receiver operator characteristic curve of 0.96 for discriminating early-stage T1 nasopharyngeal carcinoma from benign hyperplasia. • The CNN-based algorithm had a sensitivity of 92.4% and specificity of 90.6% for detecting early-stage nasopharyngeal carcinoma.

Quantitative T1ρ MRI of the Head and Neck Discriminates Carcinoma and Benign Hyperplasia in the Nasopharynx

BACKGROUND AND PURPOSE

T1ρ imaging is a new quantitative MR imaging pulse sequence with the potential to discriminate between malignant and benign tissue. In this study, we evaluated the capability of T1ρ imaging to characterize tissue by applying T1ρ imaging to malignant and benign tissue in the nasopharynx and to normal tissue in the head and neck.

MATERIALS AND METHODS

Participants with undifferentiated nasopharyngeal carcinoma and benign hyperplasia of the nasopharynx prospectively underwent T1ρ imaging. T1ρ measurements obtained from the histogram analysis for nasopharyngeal carcinoma in 43 participants were compared with those for benign hyperplasia and for normal tissue (brain, muscle, and parotid glands) in 41 participants using the Mann-Whitney U test. The area under the curve of significant T1ρ measurements was calculated and compared using receiver operating characteristic analysis and the Delong test, respectively. A P < . 05 indicated statistical significance.

RESULTS

There were significant differences in T1ρ measurements between nasopharyngeal carcinoma and benign hyperplasia and between nasopharyngeal carcinoma and normal tissue (all, P < . 05). Compared with benign hyperplasia, nasopharyngeal carcinoma showed a lower T1ρ mean (62.14 versus 65.45 × ms), SD (12.60 versus 17.73 × ms), and skewness (0.61 versus 0.76) (all P < .05), but no difference in kurtosis (P = . 18). The T1ρ SD showed the highest area under the curve of 0.95 compared with the T1ρ mean (area under the curve  = 0.72) and T1ρ skewness (area under the curve  = 0.72) for discriminating nasopharyngeal carcinoma and benign hyperplasia (all, P < .05).

CONCLUSIONS

Quantitative T1ρ imaging has the potential to discriminate malignant from benign and normal tissue in the head and neck.

Early Detection of Cancer: Evaluation of MR Imaging Grading Systems in Patients with Suspected Nasopharyngeal Carcinoma

BACKGROUND AND PURPOSE

We evaluated modifications to our contrast-enhanced MR imaging grading system for symptomatic patients with suspected nasopharyngeal carcinoma, aimed at improving discrimination of early-stage cancer and benign hyperplasia. We evaluated a second non-contrast-enhanced MR imaging grading system for asymptomatic patients from nasopharyngeal carcinoma plasma screening programs.

MATERIALS AND METHODS

Dedicated nasopharyngeal MR imaging before (plain scan system) and after intravenous contrast administration (current and modified systems) was reviewed in patients from a nasopharyngeal carcinoma-endemic region, comprising 383 patients with suspected disease without nasopharyngeal carcinoma and 383 patients with nasopharyngeal carcinoma. The modified and plain scan systems refined primary tumor criteria, added a nodal assessment, and expanded the system from 4 to 5 grades. The overall combined sensitivity and specificity of the 3 systems were compared using the extended McNemar test (a χ² value [Formula: see text]> 5.99 indicates significance).

RESULTS

The current, modified, and plain scan MR imaging systems yielded sensitivities of 99.74%, 97.91%, and 97.65%, respectively, and specificities of 63.45%, 89.56% and 86.42%, respectively. The modified system yielded significantly better performance than the current ([Formula: see text] = 122) and plain scan ([Formula: see text] = 6.1) systems. The percentages of patients with nasopharyngeal carcinoma in grades 1-2, grade 3, and grades 4-5 for the modified and plain scan MR imaging systems were 0.42% and 0.44%; 6.31% and 6.96%; and 90.36% and 87.79%, respectively. No additional cancers were detected after contrast administration in cases of a plain scan graded 1-2.

CONCLUSIONS

We propose a modified MR imaging grading system that improves diagnostic performance for nasopharyngeal carcinoma detection. Contrast was not valuable for low MR imaging grades, and the plain scan shows potential for use in screening programs.

Investigating the value of arterial spin labeling and intravoxel incoherent motion imaging on diagnosing nasopharyngeal carcinoma in T1 stage

BACKGROUND

To investigate the diagnostic value of arterial spin labeling (ASL) and intravoxel incoherent motion (IVIM) imaging in distinguishing nasopharyngeal carcinoma (NPC) in T1 stage from healthy controls (HC).

METHODS

Forty-five newly diagnosed NPC patients in the T1 stage and thirty-one healthy volunteers who underwent MR examinations for both 3D pseudo-continuous ASL (pCASL) and IVIM were enrolled in this study. The Mann-Whitney test was used to compare the mean values of blood flow (BF) derived from pCASL and IVIM derived parameters, including apparent diffusion coefficient (ADC), pure molecular diffusion (D), pseudo-diffusion coefficient (D*) and perfusion fraction (f) between NPC tumor and benign nasopharyngeal mucosa of HC. Receiver Operating Characteristic (ROC) was performed to determine diagnostic cutoff and efficiency. The correlation coefficients among parameters were investigated using Spearman's test.

RESULTS

The NPC in the T1 stage showed higher mean BF, lower ADC, D, and f compared to benign nasopharyngeal mucosa (P < 0.001) with the area under curve of ROC of 0.742-0.996 (highest by BF). BF cutoff was set at > 36 mL/100 g/min; the corresponding sensitivity, specificity, and accuracy in differentiating NPC stage T1 from benign nasopharyngeal mucosa were 95.56% (43/45), 100% (31/31) and 97.37% (74/76), respectively. BF demonstrated moderate negative correlation with D* on HC (ρ [Spearman correlation coefficients] = - 0.426, P = 0.017).

CONCLUSIONS

ASL and IVIM could reflect the difference in perfusion and diffusion between tumor and benign nasopharyngeal mucosa, indicating a potential for accessing early diagnosis of NPC. Notably, BF, with a specificity of 100%, demonstrated better performance compared to IVIM in distinguishing malignant lesions from healthy tissue.

Complementary roles of MRI and endoscopic examination in the early detection of nasopharyngeal carcinoma

BACKGROUND

Early-stage nasopharyngeal carcinoma (NPC) evades detection when the primary tumor is hidden from view on endoscopic examination. Therefore, in a prospective study of subjects being screened for NPC using plasma Epstein-Barr virus (EBV) DNA, we conducted a study to investigate whether magnetic resonance imaging (MRI) could detect endoscopically occult NPC.

PATIENTS AND METHODS

Participants with persistently positive EBV DNA underwent endoscopic examination and biopsy when suspicious for NPC, followed by MRI blinded to the endoscopic findings. Participants with a negative endoscopic examination and positive MRI were recalled for biopsy or surveillance. Diagnostic performance was assessed by calculating sensitivity, specificity and accuracy, based on the histologic confirmation of NPC in the initial study or in a follow-up period of at least two years.

RESULTS

Endoscopic examination and MRI were performed on 275 participants, 34 had NPC, 2 had other cancers and 239 without cancer were followed-up for a median of 36 months (24-60 months). Sensitivity, specificity and accuracy were 76.5%, 97.5% and 94.9%, respectively, for endoscopic examination and 91.2%, 97.5% and 96.7%, respectively, for MRI. NPC was detected only by endoscopic examination in 1/34 (2.9%) participants (a participant with stage I disease), and only by MRI in 6/34 (17.6%) participants (stage I = 4, II = 1, III = 1), two of whom had stage I disease and follow-up showing slow growth on MRI but no change on endoscopic examination for 36 months.

CONCLUSION

MRI has a complementary role to play in NPC detection and can enable the earlier detection of endoscopically occult NPC.

Development of a self-constrained 3D DenseNet model in automatic detection and segmentation of nasopharyngeal carcinoma using magnetic resonance images

OBJECTIVES

We aimed to develop a dual-task model to detect and segment nasopharyngeal carcinoma (NPC) automatically in magnetic resource images (MRI) based on deep learning method, since the differential diagnosis of NPC and atypical benign hyperplasia was difficult and the radiotherapy target contouring of NPC was labor-intensive.

MATERIALS AND METHODS

A self-constrained 3D DenseNet (SC-DenseNet) architecture was improved using separated training and validation sets. A total of 4100 individuals were finally enrolled and split into the training, validation and test sets at a proximate ratio of 8:1:1 using simple randomization. The diagnostic metrics of the established model against experienced radiologists was compared in the test set. The dice similarity coefficient (DSC) of manual and model-defined tumor region was used to evaluate the efficacy of segmentation.

RESULTS

Totally, 3142 nasopharyngeal carcinoma (NPC) and 958 benign hyperplasia were included. The SC-DenseNet model showed encouraging performance in detecting NPC, attained a higher overall accuracy, sensitivity and specificity than those of the experienced radiologists (97.77% vs 95.87%, 99.68% vs 99.24% and 91.67% vs 85.21%, respectively). Moreover, the model also exhibited promising performance in automatic segmentation of tumor region in NPC, with an average DSC at 0.77 ± 0.07 in the test set.

CONCLUSIONS

The SC-DenseNet model showed competence in automatic detection and segmentation of NPC in MRI, indicating the promising application value as an assistant tool in clinical practice, especially in screening project.

MRI of benign hyperplasia in the nasopharynx: is there an association with Epstein-Barr virus?

AIM

To evaluate whether there is an association between persistently positive plasma Epstein-Barr virus (EBV) DNA and the presence and the change in benign hyperplasia.

MATERIALS AND METHODS

One hundred and seventeen participants with positive-plasma EBV-DNA, but without NPC from previous nasopharyngeal carcinoma (NPC) screening, underwent follow-up magnetic resonance imaging (MRI) and plasma EBV-DNA after 2 years. Logistic regression was used to analyse associations between MRI (benign hyperplasia on the follow-up MRI and change from 2 years earlier), and plasma EBV-DNA, smoking, and age.

RESULTS

At follow-up, EBV-DNA positivity and smoking were independent parameters for the presence of benign hyperplasia (p=0.027 and 0.023 respectively). Compared with participants in whom EBV-DNA became negative (n=44/117 37.6%), those in whom EBV-DNA remained positive (n=73/117 62.4%) had a greater risk of benign hyperplasia developing (previous MRI normal), being stable or processing (52/73 71.2% versus 18/44 40.9%; p=0.001).

CONCLUSION

These results suggest a potential link between benign hyperplasia on MRI and the EBV. As EBV contributes to NPC oncogenesis, future MRI research is warranted to determine if persistent benign hyperplasia is a risk marker for development of NPC.

Carcinoma of unknown primary detected by whole-body diffusion-weighted imaging: A case report and review of the literature

Carcinoma of unknown primary accounts for 2%-5% of all head and neck tumors. Identification of the primary site is challenging. We present a case report of a 43-year-old man with metastatic cervical lymphadenopathy for 3 year, and the primary tumor was unknown after routine examinations, including positron emission tomography/computed tomography. Whole-body diffusion-weighted imaging was performed to detect small lesions in the nasopharynx, and a biopsy confirmed the lesions as squamous cell carcinoma. Therefore, the primary tumor site was found in a patient with carcinoma of unknown primary, suggesting that whole-body diffusion-weighted imaging can be very helpful in detecting small occult cancer.

Quantitative Analysis of DCE-MRI and RESOLVE-DWI for Differentiating Nasopharyngeal Carcinoma from Nasopharyngeal Lymphoid Hyperplasia

To explore the ability of quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) analysis and readout segmentation of long variable echo-trains diffusion weighted imaging (RESOLVE-DWI) to distinguish nasopharyngeal carcinoma (NPC) from nasopharyngeal lymphoid hyperplasia (NPLH). Twenty-five patients with NPC and 30 patients with NPLH were evaluated. Three quantitative DCE-MRI parameters (Ktrans, Kep and Ve) and the apparent diffusion coeffcient (ADC) of lesions were calculated. The two independent samples t test or Mann-Whitney U test was used to compare the parameters between NPC and NPLH group. Receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic ability for distinguishing NPC from NPLH. A P value less than 0.05 was considered statistically significant. The difference in Ktrans value between the NPC group and the NPLH group was statistically significant, and the value of the NPC group was larger than that of the NPLH group. There was no statistical difference in Kep and Ve between the two groups. The ADC value of NPC group was smaller than that of NPLH group, and the difference was statistically significant. ROC curve analysis showed that both Ktrans and ADC were effective in diagnosing NPC and the area under the curve (AUC) was 0.773 and 0.704, respectively. In addition, the combination of Ktrans and ADC demonstrated the obviously improved AUC of 0.884. DCE-MRI and RESOLVE-DWI are effective in differentiating NPC from NPLH, especially the combination of the two models.

Dual-energy CT in the differentiation of stage T1 nasopharyngeal carcinoma and lymphoid hyperplasia

PURPOSE

To explore the value of dual-energy CT for the differentiation between stage T1 nasopharyngeal carcinoma (NPC_T1) and lymphoid hyperplasia (LH).

METHOD

Patients with histopathological proven nasopharyngeal lesions (stage T1 NPCs, n = 30; LHs, n = 47) who underwent dual-energy CT were enrolled in this retrospective study. Quantitative parameters derived from dual-energy CT were measured. Statistical analyses were performed using the independent sample t-test, Wilcoxon rank sum test, and receiver operating characteristic curve (ROC) analysis.

RESULTS

There was significantly higher iodine concentration (IC), normalized iodine concentration (NIC, to internal jugular vein) in NPC_T1 compared with LH (p < 0.001). The effective atomic number (Z_eff) was significantly higher in NPC_T1 than that in LH (p <  0.001). The virtual monochromatic images (VMIs) at 50 keV-110 keV (20 keV-interval) of NPC_T1 were all significantly higher than those of LH (all p <0.001). The slope (k) value of spectral attenuation curve was also significantly higher in NPC_T1 than LH (p <  0.001). There was no significant difference in virtual noncontrast (VNC) and 130 keV-190 keV (20 keV-interval) between the NPC_T1 and LH. For discriminating NPC_T1 from LH, the area under curve (AUC) using 70 keV was the highest in all single parameter (AUC, 0.92; sensitivity, 80.00 %; specificity, 91.49 %). Combined multiple parameters (IC, NIC, Z_eff, 50 keV, 70 keV, 90 keV, slope (k)) by performing multivariate logistic regression model significantly improve the diagnostic capability in differentiating these two entities, with AUC, sensitivity, and specificity values of 0.99, 93.33 %, 97.87 %, respectively.

CONCLUSIONS

Dual-energy CT can be helpful for the differentiation between NPC_T1 and LH lesions.