Reliability of NI-RADS criteria in the interpretation of contrast-enhanced magnetic resonance imaging considering the potential role of diffusion-weighted imaging

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.

Interrater reliability of MRI Neck Imaging Reporting and Data System (NI-RADS) in the follow-up of nasopharyngeal carcinoma after radiation therapy

PURPOSE

Evidence supporting the reliability of magnetic resonance imaging (MRI) Neck Imaging Reporting and Data System (NI-RADS) is currently limited. This study aims to evaluate the interrater agreement of MRI NI-RADS among radiologists with varying levels of expertise in nasopharyngeal carcinoma (NPC) patients.

MATERIAL AND METHODS

We designed an observational retrospective study to identify follow-up MRIs in patients who had undergone radiation therapy. Five radiologists (2 head and neck experts, 1 general radiologist, and 2 residents in radiology) scored each MRI using NI-RADS. Kappa (κ) and percentage of agreement (POA) were calculated for the ultimate score and for each individual feature of the NI-RADS (primary tumor size, signal on T2-weighted images, contrast enhancement, diffusion restriction, and lymph node size). Agreement was analyzed also separately for the first follow-up MRI and subsequent scans.

RESULTS

Thirty patients were included (a total of 97 MRIs per rater). Interreader agreement between all readers was moderate for NI-RADS (κ = 0.41; POA = 81%). The first follow-up showed a low reliability between the head and neck expert radiologist and the two radiology residents for both primary tumor contrast enhancement and size assessment (κ = 0.02; POA = 31% and κ = 0.17; POA = 38%, respectively), while there was a high level of agreement in the analysis of diffusion-weighted imaging (DWI) (κ = 0.79; POA = 96%).

CONCLUSION

MRI NI-RADS has a moderate interrater agreement in NPC patients after radiation therapy. Educational effort should focus on the assessment and interpretation of primary tumor contrast enhancement and size in the first examination performed after treatment, by also considering information derived from DWI.

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.

Multiparametric MRI: From Simultaneous Rapid Acquisition Methods and Analysis Techniques Using Scoring, Machine Learning, Radiomics, and Deep Learning to the Generation of Novel Metrics

ABSTRACT

With the recent advancements in rapid imaging methods, higher numbers of contrasts and quantitative parameters can be acquired in less and less time. Some acquisition models simultaneously obtain multiparametric images and quantitative maps to reduce scan times and avoid potential issues associated with the registration of different images. Multiparametric magnetic resonance imaging (MRI) has the potential to provide complementary information on a target lesion and thus overcome the limitations of individual techniques. In this review, we introduce methods to acquire multiparametric MRI data in a clinically feasible scan time with a particular focus on simultaneous acquisition techniques, and we discuss how multiparametric MRI data can be analyzed as a whole rather than each parameter separately. Such data analysis approaches include clinical scoring systems, machine learning, radiomics, and deep learning. Other techniques combine multiple images to create new quantitative maps associated with meaningful aspects of human biology. They include the magnetic resonance g-ratio, the inner to the outer diameter of a nerve fiber, and the aerobic glycolytic index, which captures the metabolic status of tumor tissues.

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.

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.