MRI Posttreatment Surveillance for Head and Neck Squamous Cell Carcinoma: Proposed MR NI-RADS Criteria

The Role of Neck Imaging Reporting and Data System (NI-RADS) in the Management of Head and Neck Cancers

This review evaluates the current evidence on the use of the Neck Imaging Reporting and Data System (NI-RADS) for the surveillance and early detection of recurrent head and neck cancers. NI-RADS offers a standardized, structured framework specifically tailored for post-treatment imaging, aiding radiologists in differentiating between residual tumors, scar tissue, and post-surgical changes. NI-RADS demonstrated a strong diagnostic performance across multiple studies, with high sensitivity and specificity reported in detecting recurrent tumors at primary and neck sites. Despite these strengths, limitations persist, including a high frequency of indeterminate results and variability in di-agnostic concordance across imaging modalities (computed tomography, magnetic resonance imaging (MRI), positron emission tomography(PET)). The review also highlights the NI-RADS's reproducibility, showing high inter- and intra-reader agreements across different imaging techniques, although some modality-specific differences were observed. While it demonstrates strong diagnostic performance and good reproducibility across imaging modalities, attention is required to address indeterminate imaging findings and the limitations of modality-specific variations. Future studies should focus on integrating advanced imaging characteristics, such as diffusion-weighted imaging and PET/MRI fusion techniques, to further enhance NI-RADS's diagnostic accuracy. Continuous efforts to refine NI-RADS protocols and imaging interpretations will ensure more consistent detection of recurrences, ultimately improving clinical outcomes in head and neck cancer management.

An international survey of diffusion and perfusion magnetic resonance imaging implementation in the head and neck

OBJECTIVE

The goal of this international survey was to understand how diffusion (DWI) and perfusion imaging (PWI) are being applied to clinical head and neck imaging.

METHODS AND MATERIALS

An online questionnaire focusing on acquisition, clinical indications, analysis, and reporting of qualitative DWI (QlDWI), quantitative DWI (QnDWI) and dynamic contrast-enhanced PWI (DCE-PWI) in the head and neck was circulated to members of the American Society of Head and Neck Radiology (ASHNR) and European Society of Head and Neck Radiology (ESHNR) over a 3-month period. Descriptive statistics and group comparisons were calculated with SPSS® v27.

RESULTS

There were 294 unique respondents (17.6% response rate) from 256 institutions (182 ESHNR, 74 ASHNR). DWI was routinely acquired for some head and neck indications at 95.7% of the respondents' institutions, with 92.5% of radiologists interpreting QlDWI but only 36.7% analysing QnDWI. QlDWI was most frequently applied to primary mucosal masses or the middle ear, whilst QnDWI was routinely used to distinguish tumour histologies, and primary or recurrent carcinoma. DCE-PWI was routinely acquired at 53.6% of institutions and used by 40.8% of respondents, however, there was no clinical scenario in which it was routinely applied by most users. DCE-PWI analysis methods varied, with time-intensity curve classifications being the most frequently reported. Lack of standardisation was identified as a key reason for not implementing QnDWI, whilst numerous factors prevented the adoption of DCE-PWI.

CONCLUSION

There is widespread routine interpretation of QlDWI by head and neck radiologists, but there is considerable variation in the application and analysis of head and neck QnDWI and DCE-PWI.

KEY POINTS

Question How are diffusion (DWI) and dynamic contrast-enhanced perfusion imaging (DCE-PWI) being utilised by head and neck radiologists across a wide range of practices? Findings An international survey demonstrated widespread routine interpretation of qualitative DWI but variable application and analysis of quantitative DWI and DCE-PWI with numerous barriers to implementation. Clinical relevance The survey results will aid discussion on how to standardise and optimally disseminate these MRI techniques in day-to-day practice. More focused education and resource allocation may be required to accelerate the adoption of quantitative DWI and DCE-PWI.

Current Applications of PET/MR: Part I: Technical Basics and Preclinical/Clinical Applications

Positron emission tomography/magnetic resonance (PET/MR) imaging has gone through major hardware improvements in recent years, making it a reliable state-of-the-art hybrid modality in clinical practice. At the same time, image reconstruction, attenuation correction, and motion correction algorithms have significantly evolved to provide high-quality images. Part I of the current review discusses technical basics, pre-clinical applications, and clinical applications of PET/MR in radiation oncology and head and neck imaging. PET/MR offers a broad range of advantages in preclinical and clinical imaging. In the preclinic, small and large animal-dedicated devices were developed, making PET/MR capable of delivering new insight into animal models in diseases and facilitating the development of methods that inform clinical PET/MR. Regarding PET/MR's clinical applications in radiation medicine, PET and MR already play crucial roles in the radiotherapy process. Their combination is particularly significant as it can provide molecular and morphological characteristics that are not achievable with other modalities. In addition, the integration of PET/MR information for therapy planning with linear accelerators is expected to provide potentially unique biomarkers for treatment guidance. Furthermore, in clinical applications in the head and neck region, it has been shown that PET/MR can be an accurate modality in head and neck malignancies for staging and resectability assessment. Also, it can play a crucial role in diagnosing residual or recurrent diseases, reliably distinguishing from oedema and fibrosis. PET/MR can furthermore help with tumour characterization and patient prognostication. Lastly, in head and neck carcinoma of unknown origin, PET/MR, with its diagnostic potential, may obviate multiple imaging sessions in the near future.

Radiographic Response Assessments and Standardized Imaging Interpretation Criteria in Head and Neck Cancer on FDG PET/CT: A Narrative Review

INTRODUCTION

There is growing interest in the development and application of standardized imaging criteria (SIC), to minimize variability and improve the reproducibility of image interpretation in head and neck squamous cell carcinoma (HNSCC).

METHODS

"Squamous cell carcinoma" AND "standardized interpretation criteria" OR "radiographic response assessment" were searched using PubMed and Google Scholar for articles published between 2009 and 2024, returning 56 publications. After abstract review, 18 were selected for further evaluation, and 6 different SICs (i.e., PERCIST, Porceddu, Hopkins, NI-RADS, modified Deauville, and Cuneo) were included in this review. Each SIC is evaluated in the context of 8 desired traits of a standardized reporting system.

RESULTS

Two SICs have societal endorsements (i.e., PERCIST, NI-RADS); four can be used in the evaluation of locoregional and systemic disease (i.e., PERCIST, Hopkins, NI-RADS, Cuneo), and four have specific categories for equivocal imaging results (i.e., Porceddu, NI-RADS, modified Deauville, and Cuneo). All demonstrated areas for future improvement in the context of the 8 desired traits.

CONCLUSION

Multiple SICs have been developed for and demonstrated value in HNSCC post-treatment imaging; however, these systems remain underutilized. Selecting an SIC with features that best match the needs of one's practice is expected to maximize the likelihood of successful implementation.

Diagnostic accuracy of NI-RADS for prediction of head and neck squamous cell carcinoma: a systematic review and meta-analysis

OBJECTIVES

This study aimed to assess the diagnostic performance of NI-RADS for the prediction of recurrence in patients treated for Head and Neck Squamous Cell Carcinoma (HNSCC).

METHODS

A literature search was conducted using various databases to identify relevant articles published from June 2016 onwards. We included studies reporting the diagnostic accuracy of NI-RADS in distinguishing recurrence in patients undergoing imaging surveillance, with pathologic results and/or follow-up as the reference standard. Summary estimates of diagnostic accuracy in terms of sensitivity, specificity, positive likelihood ratio (LR +), negative likelihood ratio (LR -), and diagnostic odds ratio (DOR) were calculated with the hierarchical summary receiver operating characteristic (HSROC) model. Meta-regression and subgroup analyses were conducted to investigate different clinical settings. Study quality was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 tool.

RESULTS

A total of 12 studies were included in the current meta-analysis. The pooled sensitivity and specificity were 0.69 (95% CI 0.59-0.79) and 0.94 (95% CI 0.89-0.97), respectively. For the primary site, the pooled summary estimates were 0.67 (95% CI 0.53-0.78) and 0.95 (95% CI 0.90-0.97), for the nodal sites were 0.64 (95% CI 0.44-0.80) and 0.99 (95% CI 0.98-0.99), respectively. The recurrence rate for NI-RADS categories 1-3 was 0.03 (95% CI 0.02-0.05), 0.13 (95% CI 0.10-0.15), and 0.77 (95% CI 0.73-0.81). Meta-regression revealed that the type of analysis (per person vs. per site) and number of sites (≤ 200 vs. > 200) were significant factors associated with heterogeneity.

CONCLUSIONS

NI-RADS demonstrated high specificity but moderate sensitivity in patients after treatment for HNSCC. Summary estimates showed a significantly higher malignancy rate for NI-RADS category 3 compared to category 2.

PET/MR Imaging in Head and Neck Cancer

Head and neck squamous cell carcinoma (HNSCC) can either be examined with hybrid PET/MR imaging systems or sequentially, using PET/CT and MR imaging. Regardless of the acquisition technique, the superiority of MR imaging compared to CT lies in its potential to interrogate tumor and surrounding tissues with different sequences, including perfusion and diffusion. For this reason, PET/MR imaging is preferable for the detection and assessment of locoregional residual/recurrent HNSCC after therapy. In addition, MR imaging interpretation is facilitated when combined with PET. Nevertheless, distant metastases and distant second primary tumors are detected equally well with PET/MR imaging and PET/CT.

Concordance between head and neck MRI and histopathology in detecting laryngeal subsite invasion among patients with laryngeal cancer

BACKGROUND

Accuracy of head and neck MRI (HN-MRI) in predicting tumor invasion of laryngeal site/subsites in patients with laryngeal cancer prior to laryngectomy is poorly evaluated in the literature. Therefore, we aim to evaluate the diagnostic value of HN-MRI in accurate pre-operative estimation of tumor invasion to laryngeal subsites in patients with laryngeal cancer.

METHODS

Patients with laryngeal cancer who underwent HN-MRI for cancer staging and underwent total laryngectomy between 2008 and 2021 were included. Sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy of HN-MRI in predicting tumor invasion of laryngeal subsites were calculated based on concordance between the HN-MRI and histopathological results.

RESULTS

One hundred and thirty-seven patients underwent total laryngectomy [primary: 82/137(60%), salvage 55/137(40%)]. The utilization of HN-MRI resulted in the downstaging of 16/137 (11.6%) patients and the upstaging of 8/137 (5.8%) patients. For the whole cohort, there was a significant discordance between HN-MRI and histopathology for T-category; out of 116 cT4a disease, 102(87.9%) were confirmed to have pT4a disease, and out of 17 cT3 disease, 9(52.9%) were confirmed to have pT3 disease, p < 0.001. The MRI overall diagnostic accuracy of predicting tumor invasion was 91%, 92%, 82%, 87%, 72%, 76%, 65% and 68% for base of tongue, arytenoid, vocal cord, posterior commissure, pre-epiglottic space, cricoid cartilage, inner thyroid cortex, and subglottis, respectively.

CONCLUSIONS

In patients with laryngeal cancer undergoing total laryngectomy, HN-MRI demonstrates promising accuracy in predicting tumor invasion of specific laryngeal subsites (e.g., base of tongue). Our findings showed the potential of HN-MRI as a valuable tool for pre-operative planning and treatment decision-making in this patient population.

Performance of Neck Imaging Reporting and Data System (NI-RADS) for Diagnosis of Recurrence of Head and Neck Squamous Cell Carcinoma: A Systematic Review and Meta-analysis

BACKGROUND

The Neck Imaging Reporting and Data System (NI-RADS) is a reporting template used in head and neck cancer posttreatment follow-up imaging.

PURPOSE

Our aim was to evaluate the pooled detection rates of the recurrence of head and neck squamous cell carcinoma based on each NI-RADS category and to compare the diagnostic accuracy between NI-RADS 2 and 3 cutoffs.

DATA SOURCES

The MEDLINE, Scopus, and EMBASE databases were searched.

STUDY SELECTION

This systematic review identified 7 studies with a total of 694 patients (1233 lesions) that were eligible for the meta-analysis.

DATA ANALYSIS

The meta-analysis of pooled recurrence detection rate estimates for each NI-RADS category and the diagnostic accuracy of recurrence with NI-RADS 3 or 2 as the cutoff was performed.

DATA SYNTHESIS

The estimated recurrence rates in each category for primary lesions were 74.4% for NI-RADS 3, 29.0% for NI-RADS 2, and 4.2% for NI-RADS 1. The estimated recurrence rates in each category for cervical lymph nodes were 73.3% for NI-RADS 3, 14.3% for NI-RADS 2, and 3.5% for NI-RADS 1. The area under the curve of the summary receiver operating characteristic for recurrence detection with NI-RADS 3 as the cutoff was 0.887 and 0.983, respectively, higher than 0.869 and 0.919 for the primary sites and cervical lymph nodes, respectively, with NI-RADS 2 as the cutoff.

LIMITATIONS

Given the heterogeneity of the data of the studies, the conclusions should be interpreted with caution.

CONCLUSIONS

This meta-analysis revealed estimated recurrence rates for each NI-RADS category for primary lesions and cervical lymph nodes and showed that NI-RADS 3 has a high diagnostic performance for detecting recurrence.

Adding MR Diffusion Imaging and T2 Signal Intensity to Neck Imaging Reporting and Data System Categories 2 and 3 in Primary Sites of Postsurgical Oral Cavity Carcinoma Provides Incremental Diagnostic Value

BACKGROUND AND PURPOSE

The NI-RADS lexicon doesn't use ADC parameters and T2 weighted signal for ascribing categories. We explored ADC, DWI, and T2WI to examine the diagnostic accuracy in primary sites of postsurgical oral cavity carcinoma in the Neck Imaging Reporting and Data System (NI-RADS) categories 2 and 3.

MATERIALS AND METHODS

We performed a retrospective analysis in clinically asymptomatic post-surgically treated patients with oral cavity squamous cell carcinoma who underwent contrast-enhanced MRI between January 2013 and January 2016. Histopathology and follow-up imaging were used to ascertain the presence or absence of malignancy in subjects with "new enhancing lesions," which were interpreted according to the NI-RADS lexicon by experienced readers, including NI-RADS 2 and 3 lesions in the primary site. NI-RADS that included T2WI and DWI (referred to as NI-RADS A) and ADC (using the best cutoff from receiver operating characteristic curve analysis, NI-RADS B) was documented in an Excel sheet to up- or downgrade existing classic American College of Radiology NI-RADS and calculate diagnostic accuracy.

RESULTS

Sixty-one malignant and 23 benign lesions included in the study were assigned American College of Radiology NI-RADS 2 (n = 33) and NI-RADS 3 (n = 51) categories. The recurrence rate was 90% (46/51) for NI-RADS three, 45% (15/33) for NI-RADS 2, and 73% (61/84) overall. T2WI signal morphology was intermediate in 45 subjects (53.5%) and restricted DWI in 54 (64.2%). Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the American College of Radiology NI-RADS were the following: NI-RADS (75.4%, 78.3%, 90.1%, 54.5%, and 76.1%); NI-RADS A (79.1%, 81.2%, 91.9%, 59.1%, and 79.6%); and NI-RADS B (88.9%, 72.7%, 91.4%, 66.7%, and 85.1%), respectively.

CONCLUSIONS

Adding MR imaging diagnostic characteristics like T2WI, DWI, and ADC to the American College of Radiology NI-RADS improved diagnostic accuracy and sensitivity.

PET/MR Imaging in Evaluating Treatment Failure of Head and Neck Malignancies: A Neck Imaging Reporting and Data System-Based Study

BACKGROUND AND PURPOSE

PET/MR imaging is a relatively new hybrid technology that holds great promise for the evaluation of head and neck cancer. The aim of this study was to assess the performance of simultaneous PET/MR imaging versus MR imaging in the evaluation of posttreatment head and neck malignancies, as determined by its ability to predict locoregional recurrence or progression after imaging.

MATERIALS AND METHODS

The electronic medical records of patients who had posttreatment PET/MR imaging studies were reviewed, and after applying the exclusion criteria, we retrospectively included 46 studies. PET/MR imaging studies were independently reviewed by 2 neuroradiologists, who recorded scores based on the Neck Imaging Reporting and Data System (using CT/PET-CT criteria) for the diagnostic MR imaging sequences alone and the combined PET/MR imaging. Treatment failure was determined with either biopsy pathology or initiation of new treatment. Statistical analyses including univariate association, interobserver agreement, and receiver operating characteristic analysis were performed.

RESULTS

There was substantial interreader agreement among PET/MR imaging scores (κ = 0.634; 95% CI, 0.605-0.663). PET/MR imaging scores showed a strong association with treatment failure by univariate association analysis, with P < .001 for the primary site, neck lymph nodes, and combined sites. Receiver operating characteristic curves of PET/MR imaging scores versus treatment failure indicated statistically significant diagnostic accuracy (area under curve range, 0.864-0.987; P < .001).

CONCLUSIONS

Simultaneous PET/MR imaging has excellent discriminatory performance for treatment outcomes of head and neck malignancy when the Neck Imaging Reporting and Data System is applied. PET/MR imaging could play an important role in surveillance imaging for head and neck cancer.

ADC for Differentiation between Posttreatment Changes and Recurrence in Head and Neck Cancer: A Systematic Review and Meta-analysis

BACKGROUND

Previous studies reported that the ADC values of recurrent head and neck cancer lesions are lower than those of posttreatment changes, however, the utility of ADC to differentiate them has not been definitively summarized and established.

PURPOSE

Our aim was to evaluate the diagnostic benefit of ADC calculated from diffusion-weighted imaging in differentiating recurrent lesions from posttreatment changes in head and neck cancer.

DATA SOURCES

MEDLINE, Scopus, and EMBASE data bases were searched for studies.

STUDY SELECTION

The review identified 6 prospective studies with a total of 365 patients (402 lesions) who were eligible for the meta-analysis.

DATA ANALYSIS

Forest plots were used to assess the mean difference in ADC values. Heterogeneity among the studies was evaluated using the Cochrane Q test and the I² statistic.

DATA SYNTHESIS

Among included studies, the overall mean of ADC values of recurrent lesions was 1.03 × 10^-3mm²/s and that of the posttreatment changes was 1.51 × 10^-3mm²/s. The ADC value of recurrence was significantly less than that of posttreatment changes in head and neck cancer (pooled mean difference: -0.45; 95% CI, -0.59-0.32, P < .0001) with heterogeneity among studies. The threshold of ADC values between recurrent lesions and posttreatment changes was suggested to be 1.10 × 10^-3mm²/s.

LIMITATIONS

Given the heterogeneity of the data of the study, the conclusions should be interpreted with caution.

CONCLUSIONS

The ADC values in recurrent head and neck cancers are lower than those of posttreatment changes, and the threshold of ADC values between them was suggested.

NI-RADS to Predict Residual or Recurrent Head and Neck Squamous Cell Carcinoma

American College of Radiology NI-RADS is a surveillance imaging template used to predict residual or recurrent tumor in the setting of head and neck cancer. The lexicon and imaging template provides a framework to standardize the interpretations and communications with referring physicians and provides linked management recommendations, which add value in patient care. Studies have shown reasonable interreader agreement and excellent discriminatory power among the different NI-RADS categories. This article reviews the literature associated with NI-RADS and serves as a practical guide for radiologists interested in using the NI-RADS surveillance template at their institution, highlighting frequently encountered pearls and pitfalls.

Glioblastoma Surgery Imaging-Reporting and Data System: Validation and Performance of the Automated Segmentation Task

For patients with presumed glioblastoma, essential tumor characteristics are determined from preoperative MR images to optimize the treatment strategy. This procedure is time-consuming and subjective, if performed by crude eyeballing or manually. The standardized GSI-RADS aims to provide neurosurgeons with automatic tumor segmentations to extract tumor features rapidly and objectively. In this study, we improved automatic tumor segmentation and compared the agreement with manual raters, describe the technical details of the different components of GSI-RADS, and determined their speed. Two recent neural network architectures were considered for the segmentation task: nnU-Net and AGU-Net. Two preprocessing schemes were introduced to investigate the tradeoff between performance and processing speed. A summarized description of the tumor feature extraction and standardized reporting process is included. The trained architectures for automatic segmentation and the code for computing the standardized report are distributed as open-source and as open-access software. Validation studies were performed on a dataset of 1594 gadolinium-enhanced T1-weighted MRI volumes from 13 hospitals and 293 T1-weighted MRI volumes from the BraTS challenge. The glioblastoma tumor core segmentation reached a Dice score slightly below 90%, a patientwise F1-score close to 99%, and a 95th percentile Hausdorff distance slightly below 4.0 mm on average with either architecture and the heavy preprocessing scheme. A patient MRI volume can be segmented in less than one minute, and a standardized report can be generated in up to five minutes. The proposed GSI-RADS software showed robust performance on a large collection of MRI volumes from various hospitals and generated results within a reasonable runtime.

Glioblastoma Surgery Imaging-Reporting and Data System: Standardized Reporting of Tumor Volume, Location, and Resectability Based on Automated Segmentations

Treatment decisions for patients with presumed glioblastoma are based on tumor characteristics available from a preoperative MR scan. Tumor characteristics, including volume, location, and resectability, are often estimated or manually delineated. This process is time consuming and subjective. Hence, comparison across cohorts, trials, or registries are subject to assessment bias. In this study, we propose a standardized Glioblastoma Surgery Imaging Reporting and Data System (GSI-RADS) based on an automated method of tumor segmentation that provides standard reports on tumor features that are potentially relevant for glioblastoma surgery. As clinical validation, we determine the agreement in extracted tumor features between the automated method and the current standard of manual segmentations from routine clinical MR scans before treatment. In an observational consecutive cohort of 1596 adult patients with a first time surgery of a glioblastoma from 13 institutions, we segmented gadolinium-enhanced tumor parts both by a human rater and by an automated algorithm. Tumor features were extracted from segmentations of both methods and compared to assess differences, concordance, and equivalence. The laterality, contralateral infiltration, and the laterality indices were in excellent agreement. The native and normalized tumor volumes had excellent agreement, consistency, and equivalence. Multifocality, but not the number of foci, had good agreement and equivalence. The location profiles of cortical and subcortical structures were in excellent agreement. The expected residual tumor volumes and resectability indices had excellent agreement, consistency, and equivalence. Tumor probability maps were in good agreement. In conclusion, automated segmentations are in excellent agreement with manual segmentations and practically equivalent regarding tumor features that are potentially relevant for neurosurgical purposes. Standard GSI-RADS reports can be generated by open access software.