Evaluation of Head and Neck Tumors with Functional MR Imaging

Risk Stratification for Oropharyngeal Squamous Cell Carcinoma Using Texture Analysis on CT - A Step Beyond HPV Status

Background and Purpose: Human papillomavirus-associated oropharyngeal squamous cell carcinoma (OPSCC) is increasingly prevalent. Despite the overall more favorable outcome, the observed heterogeneous treatment response within this patient group highlights the need for additional means to prognosticate and guide clinical decision-making. Promising prediction models using radiomics from primary OPSCC have been derived. However, no model/s using metastatic lymphadenopathy exist to allow prognostication in those instances when the primary tumor is not seen. The aim of our study was to evaluate whether radiomics using metastatic lymphadenopathy allows for the development of a useful risk assessment model comparable to the primary tumor and whether additional knowledge of the HPV status further improves its prognostic efficacy. Materials and Methods: 80 consecutive patients diagnosed with stage III-IV OPSCC between February 2009 and October 2015, known human papillomavirus status, and pre-treatment CT images were retrospectively identified. Manual segmentation of primary tumor and metastatic lymphadenopathy was performed and the extracted texture features were used to develop multivariate assessment models to prognosticate treatment response. Results: Texture analysis of either the primary or metastatic lymphadenopathy from pre-treatment enhanced CT images can be used to develop models for the stratification of treatment outcomes in OPSCC patients. AUCs range from .78 to .85 for the various OPSCC groups tested, indicating high predictive capability of the models. Conclusions: This preliminary study can form the basis multi-centre trial that may help optimize treatment and improve quality of life in patients with OPSCC in the era of personalized medicine.

Geometric and dosimetric analysis of CT- and MR-based automatic contouring for the EPTN contouring atlas in neuro-oncology

PURPOSE

Atlas-based and deep-learning contouring (DLC) are methods for automatic segmentation of organs-at-risk (OARs). The European Particle Therapy Network (EPTN) published a consensus-based atlas for delineation of OARs in neuro-oncology. In this study, geometric and dosimetric evaluation of automatically-segmented neuro-oncological OARs was performed using CT- and MR-models following the EPTN-contouring atlas.

METHODS

Image and contouring data from 76 neuro-oncological patients were included. Two atlas-based models (CT-atlas and MR-atlas) and one DLC-model (MR-DLC) were created. Manual contours on registered CT-MR-images were used as ground-truth. Results were analyzed in terms of geometrical (volumetric Dice similarity coefficient (vDSC), surface DSC (sDSC), added path length (APL), and mean slice-wise Hausdorff distance (MSHD)) and dosimetrical accuracy. Distance-to-tumor analysis was performed to analyze to which extent the location of the OAR relative to planning target volume (PTV) has dosimetric impact, using Wilcoxon rank-sum tests.

RESULTS

CT-atlas outperformed MR-atlas for 22/26 OARs. MR-DLC outperformed MR-atlas for all OARs. Highest median (95 %CI) vDSC and sDSC were found for the brainstem in MR-DLC: 0.92 (0.88-0.95) and 0.84 (0.77-0.89) respectively, as well as lowest MSHD: 0.27 (0.22-0.39)cm. Median dose differences (ΔD) were within ± 1 Gy for 24/26(92 %) OARs for all three models. Distance-to-tumor showed a significant correlation for ΔDmax,0.03cc-parameters when splitting the data in ≤ 4 cm and > 4 cm OAR-distance (p < 0.001).

CONCLUSION

MR-based DLC and CT-based atlas-contouring enable high-quality segmentation. It was shown that a combination of both CT- and MR-autocontouring models results in the best quality.

Contemporary Imaging and Reporting Strategies for Head and Neck Cancer: MRI, FDG PET/MRI, NI-RADS, and Carcinoma of Unknown Primary-AJR Expert Panel Narrative Review

CT, MRI, and FDG PET/CT play major roles in the diagnosis, staging, treatment planning, and surveillance of head and neck cancers. Nonetheless, an evolving understanding of head and neck cancer pathogenesis, advances in imaging techniques, changing treatment regimens, and a lack of standardized guidelines have led to areas of uncertainty in the imaging of head and neck cancer. This narrative review aims to address four issues in the contemporary imaging of head and neck cancer. The first issue relates to the standard and advanced sequences that should be included in MRI protocols for head and neck cancer imaging. The second issue relates to approaches to surveillance imaging after treatment of head and neck cancer, including the choice of imaging modality, the frequency of surveillance imaging, and the role of standardized reporting through the Neck Imaging Reporting and Data System. The third issue relates to the role of imaging in the setting of neck carcinoma of unknown primary. The fourth issue relates to the role of simultaneous PET/MRI in head and neck cancer evaluation. The authors of this review provide consensus opinions for each issue.

Quantitative parameters derived from 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging can accurately estimate the histologic grade of hypopharyngeal squamous cell carcinoma preoperatively

PURPOSE

Among head and neck cancers, hypopharyngeal squamous cell carcinoma (HSCC) shows the highest malignancy, which is associated with histologic grading. This study was designed to investigate whether quantitative parameters derived from ¹⁸F-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (¹⁸F-FDG PET/MRI) can preoperatively estimate the histologic grade of HSCC.

METHODS

¹⁸F-FDG PET/MRI of neck was successfully performed in 21 patients with histologically proven HSCC including poorly differentiated group (ten patients) and well-moderately differentiated group (eleven patients). Quantitative parameters derived from FDG-PET, diffusion-weighted imaging (DWI), and dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) were calculated based on volume of interest drawn on the tumor and compared between two groups. The efficacy of quantitative parameters for the estimation of histologic grades of HSCC was evaluated.

RESULTS

There were statistically significant differences in mean value of standard uptake value (SUV), apparent diffusion coefficient (ADC), and K^trans derived from ¹⁸F-FDG PET/MRI of HSCC between two groups (p < 0.05). There was no statistically significant difference in other quantitative parameters derived from ¹⁸F-FDG PET/MRI of HSCC between two groups. The area under the curve (AUC) of the combination of SUV_mean, ADC_mean, and K^trans in the estimation of histologic grade of HSCC was 0.936 with sensitivity of 90.0% and specificity of 81.8%.

CONCLUSION

The combination of SUV_mean, ADC_mean, and K^trans derived from ¹⁸F-FDG PET/MRI can accurately predict the histologic grade of HSCC preoperatively.

The Diagnostic Value of MRI-Based Radiomic Analysis of Lacrimal Glands in Patients with Sjögren's Syndrome

This study aimed to assess the effectiveness of MRI-based texture features of the lacrimal glands (LG) in augmenting the imaging differentiation between primary Sjögren’s Syndrome (pSS) affected LG and healthy LG, as well as to emphasize the possible importance of radiomics in pSS early-imaging diagnosis. The MRI examinations of 23 patients diagnosed with pSS and 23 healthy controls were retrospectively included. Texture features of both LG were extracted from a coronal post-contrast T1-weighted sequence, using a dedicated software. The ability of texture features to discriminate between healthy and pSS lacrimal glands was performed through univariate, multivariate, and receiver operating characteristics analysis. Two quantitative textural analysis features, RunLengthNonUniformityNormalized (RLNonUN) and Maximum2DDiameterColumn (Max2DDC), were independent predictors of pSS-affected glands (p < 0.001). Their combined ability was able to identify pSS LG with 91.67% sensitivity and 83.33% specificity. MRI-based texture features have the potential to function as quantitative additional criteria that could increase the diagnostic accuracy of pSS-affected LG.

Multifactorial Model Based on DWI-Radiomics to Determine HPV Status in Oropharyngeal Squamous Cell Carcinoma

Background: Oropharyngeal squamous cell carcinoma (OPSCC) associated with human papillomavirus (HPV) has higher rates of locoregional control and a better prognosis than HPV-negative OPSCC. These differences are due to some unique biological characteristics that are also visible through advanced imaging modalities. We investigated the ability of a multifactorial model based on both clinical factors and diffusion-weighted imaging (DWI) to determine the HPV status in OPSCC. Methods: The apparent diffusion coefficient (ADC) and the perfusion-free tissue diffusion coefficient D were derived from DWI, both in the primary tumor (PT) and lymph node (LN). First- and second-order radiomic features were extracted from ADC and D maps. Different families of machine learning (ML) algorithms were trained on our dataset using five-fold cross-validation. Results: A cohort of 144 patients was evaluated retrospectively, which was divided into a training set (n = 95) and a validation set (n = 49). The 50th percentile of DPT, the inverse difference moment of ADCLN, smoke habits, and tumor subsite (tonsil versus base of the tongue) were the most relevant predictors. Conclusions: DWI-based radiomics, together with patient-related parameters, allowed us to obtain good diagnostic accuracies in differentiating HPV-positive from HPV-negative patients. A substantial decrease in predictive power was observed in the validation cohort, underscoring the need for further analyses on a larger sample size.

Predictors of Outcome after (Chemo)Radiotherapy for Node-Positive Oropharyngeal Cancer: The Role of Functional MRI

The prognosis of a subset of patients with locally advanced oropharyngeal cancer (LA-OPC) is still poor despite improvements in patient selection and treatment. Identifying specific patient- and tumor-related factors can help to select those patients who need intensified treatment. We aimed to assess the role of historical risk factors and novel magnetic resonance imaging (MRI) biomarkers in predicting outcomes in these patients. Patients diagnosed with LA-OPC were studied with diffusion-weighted imaging (DWI) and dynamic-contrast enhanced MRI at baseline and at the 10th radiotherapy (RT) fraction. Clinical information was collected as well. The endpoint of the study was the development of disease progression, locally or distantly. Of the 97 patients enrolled, 68 were eligible for analysis. Disease progression was recorded in 21 patients (11 had loco-regional progression, 10 developed distant metastases). We found a correlation between N diameter and disease control (p = 0.02); features such as p16 status and extranodal extension only showed a trend towards statistical significance. Among perfusion MRI features, higher median values of K_ep both in primary tumor (T, p = 0.016) and lymph node (N, p = 0.003) and lower median values of v_e (p = 0.018 in T, p = 0.004 in N) correlated with better disease control. K_ep P90 and N diameter were identified by MRMR algorithm as the best predictors of outcome. In conclusion, the association of non-invasive MRI biomarkers and patients and tumor characteristics may help in predicting disease behavior and patient outcomes in order to ensure a more customized treatment.

Dynamic contrast-enhanced magnetic resonance imaging in correlation with tongue cancer stages

BACKGROUND

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) plays a significant role in tumor stage as it can be used to measure tissue perfusion and permeability of tumors.

PURPOSE

To investigate the relationships between both quantitative and semi-quantitative variables obtained from DCE-MRI and tongue cancer stages.

MATERIAL AND METHODS

Mean values of K^trans, enhancement ratio (ER), wash-in slope (slope), and the 95th percentile (95%) values of the distribution for K^trans, ER, and slope values (K^trans (95%), ER (95%), and slope (95%), respectively) were calculated for 53 patients with tongue cancers (American Joint Committee on Cancer 8th Edition stage group: 10 in stages I and II, 14 in stage III, 21 in stage IVa, and eight in stage IVb as determined by histopathologic assessment). The relationship between tumor staging and each of the six DCE-MRI parameters was assessed separately using ordinal logistic regression.

RESULTS

The logistic regression analysis revealed that both mean and 95th percentile values of K^trans were significantly and positively correlated with tongue cancer stage (P < 0.01). More aggressive tumor stages had larger kinetic parameter. Moreover, the semi-quantitative parameters, such as ER (95%) and slope (95%), may be more significant predictors for evaluating tongue cancer stages than the mean ER and mean slope.

CONCLUSION

Both quantitative and semi-quantitative imaging biomarkers are useful for evaluating the stages of tongue cancer, and the indices obtained from DCE-MRI were positively correlated with the tumor stages. These parameters have the potential to non-invasively evaluate the stages of tongue cancer in the clinical setting.

Advanced CT and MR Imaging of the Posttreatment Head and Neck

Advances in MR and computed tomography (CT) techniques have resulted in greater fidelity in the assessment of treatment response and residual tumor on one hand and the assessment of recurrent head and neck malignancies on the other hand. The advances in MR techniques primarily are related to diffusion and perfusion imaging which rely on the intrinsic architecture of the tissues and organ systems. The techniques exploit the density of the cellular architecture; and the vascularity of benign and malignant lesions which in turn affect the changes in the passage of contrast through the vascular bed. Dual-energy CT and CT perfusion are the major advances in CT techniques that have found significant applications in the assessment of treatment response and tumor recurrence.

Update on MR Imaging of Soft Tissue Tumors of Head and Neck

This article reviews soft tissue tumors of the head and neck following the 2020 revision of WHO Classification of Soft Tissue and Bone Tumours. Common soft tissue tumors in the head and neck and tumors are discussed, along with newly added entities to the classification system. Salient clinical and imaging features that may allow for improved diagnostic accuracy or to narrow the imaging differential diagnosis are covered. Advanced imaging techniques are discussed, with a focus on diffusion-weighted and dynamic contrast imaging and their potential to help characterize soft tissue tumors and aid in distinguishing malignant from benign tumors.

MR imaging of Oral Cavity and Oropharyngeal Cancer

MR imaging is the modality of choice in the evaluation of oral cavity and oropharyngeal cancer. Routine postcontrast MR imaging is important for the accurate localization and characterization of the locoregional extension of oral cavity and oropharyngeal cancers. The anatomy of the oral cavity and oropharynx is complex; accurate interpretation is vital for description of the extension of the masses. Understanding the new changes in the eighth edition of the American Joint Committee on Cancer staging system. MR imaging is the imaging modality of choice for detection of perineural spread.

Arterial spin labeling for head and neck lesion assessment: technical adjustments and clinical applications

PURPOSE

Despite, currently, "state-of-the-art" magnetic resonance imaging (MRI) protocols for head and neck (H&N) lesion assessment incorporate perfusion sequences, these acquisitions require the intravenous injection of exogenous gadolinium-based contrast agents (GBCAs), which may have potential risks. Alternative techniques such as arterial spin labeling (ASL) can provide quantitative microvascular information similar to conventional perfusion sequences for H&N lesions evaluation, as a potential alternative without GBCA administration.

METHODS

We review the existing literature and analyze the latest evidence regarding ASL in H&N area highlighting the technical adjustments needed for a proper ASL acquisition in this challenging region for lesion characterization, treatment monitoring, and tumor recurrence detection.

RESULTS

ASL techniques, widely used for central nervous system lesions evaluation, can be also applied to the H&N region. Technical adjustments, especially regarding post-labeling delay, are mandatory to obtain robust and reproducible results. Several studies have demonstrated the feasibility of ASL in the H&N area including the orbits, skull base, paranasal sinuses, upper airway, salivary glands, and thyroid.

CONCLUSION

ASL is a feasible technique for the assessment of H&N lesions without the need of GBCAs. This manuscript reviews ASL's physical basis, emphasizing the technical adjustments necessary for proper ASL acquisition in this unique and challenging anatomical region, and the main applications in evaluating H&N lesions.

Multi-parametric MRI (mpMRI) for treatment response assessment of radiation therapy

Magnetic resonance imaging (MRI) plays an important role in the modern radiation therapy (RT) workflow. In comparison with computed tomography (CT) imaging, which is the dominant imaging modality in RT, MRI possesses excellent soft-tissue contrast for radiographic evaluation. Based on quantitative models, MRI can be used to assess tissue functional and physiological information. With the developments of scanner design, acquisition strategy, advanced data analysis, and modeling, multiparametric MRI (mpMRI), a combination of morphologic and functional imaging modalities, has been increasingly adopted for disease detection, localization, and characterization. Integration of mpMRI techniques into RT enriches the opportunities to individualize RT. In particular, RT response assessment using mpMRI allows for accurate characterization of both tissue anatomical and biochemical changes to support decision-making in monotherapy of radiation treatment and/or systematic cancer management. In recent years, accumulating evidence have, indeed, demonstrated the potentials of mpMRI in RT response assessment regarding patient stratification, trial benchmarking, early treatment intervention, and outcome modeling. Clinical application of mpMRI for treatment response assessment in routine radiation oncology workflow, however, is more complex than implementing an additional imaging protocol; mpMRI requires additional focus on optimal study design, practice standardization, and unified statistical reporting strategy to realize its full potential in the context of RT. In this article, the mpMRI theories, including image mechanism, protocol design, and data analysis, will be reviewed with a focus on the radiation oncology field. Representative works will be discussed to demonstrate how mpMRI can be used for RT response assessment. Additionally, issues and limits of current works, as well as challenges and potential future research directions, will also be discussed.

MRI Dynamic Contrast Imaging of Oral Cavity and Oropharyngeal Tumors

ABSTRACT

In the past decade, dynamic contrast-enhanced magnetic resonance imaging has had an increasing role in assessing the microvascular characteristics of various tumors, including head and neck cancer. Dynamic contrast-enhanced magnetic resonance imaging allows noninvasive assessment of permeability and blood flow, both important parametric features of tumor hypoxia, which is in turn a marker for treatment resistance for head and neck cancer.In this article we will provide a comprehensive review technique in evaluating tumor proliferation and application of its parameters in differentiating between various tumor types of the oral cavity and how its parameters can correlate between epidermal growth factor receptor and human papillomavirus which can have an implication in patient's overall survival rates.We will also review how the parameters of this method can predict local tumor control after treatment and compare its efficacy with other imaging modalities. Lastly, we will review how its parameters can be used prospectively to identify early complications from treatment.

An evaluation of MR based deep learning auto-contouring for planning head and neck radiotherapy

INTRODUCTION

Auto contouring models help consistently define volumes and reduce clinical workload. This study aimed to evaluate the cross acquisition of a Magnetic Resonance (MR) deep learning auto contouring model for organ at risk (OAR) delineation in head and neck radiotherapy.

METHODS

Two auto contouring models were evaluated using deep learning contouring expert (DLCExpert) for OAR delineation: a CT model (modelCT) and an MR model (modelMRI). Models were trained to generate auto contours for the bilateral parotid glands and submandibular glands. Auto-contours for modelMRI were trained on diagnostic images and tested on 10 diagnostic, 10 MR radiotherapy planning (RTP), eight MR-Linac (MRL) scans and, by modelCT, on 10 CT planning scans. Goodness of fit scores, dice similarity coefficient (DSC) and distance to agreement (DTA) were calculated for comparison.

RESULTS

ModelMRI contours improved the mean DSC and DTA compared with manual contours for the bilateral parotid glands and submandibular glands on the diagnostic and RTP MRs compared with the MRL sequence. There were statistically significant differences seen for modelMRI compared to modelCT for the left parotid (mean DTA 2.3 v 2.8 mm), right parotid (mean DTA 1.9 v 2.7 mm), left submandibular gland (mean DTA 2.2 v 2.4 mm) and right submandibular gland (mean DTA 1.6 v 3.2 mm).

CONCLUSION

A deep learning MR auto-contouring model shows promise for OAR auto-contouring with statistically improved performance vs a CT based model. Performance is affected by the method of MR acquisition and further work is needed to improve its use with MRL images.

Advanced Magnetic Resonance Imaging of the Skull Base

Magnetic resonance (MR) imaging is a crucial tool for evaluation of the skull base, enabling characterization of complex anatomy by utilizing multiple image contrasts. Recent technical MR advances have greatly enhanced radiologists' capability to diagnose skull base pathology and help direct management. In this paper, we will summarize cutting-edge clinical and emerging research MR techniques for the skull base, including high-resolution, phase-contrast, diffusion, perfusion, vascular, zero echo-time, elastography, spectroscopy, chemical exchange saturation transfer, PET/MR, ultra-high-field, and 3D visualization. For each imaging technique, we provide a high-level summary of underlying technical principles accompanied by relevant literature review and clinical imaging examples.

Diffusion-weighted imaging with histogram analysis of the apparent diffusion coefficient maps in the diagnosis of parotid tumours

The aim of this study was to investigate the role of diffusion-weighted imaging (DWI) with histogram analysis of apparent diffusion coefficient (ADC) maps in the characterization of parotid tumours. This prospective study included 39 patients with parotid tumours. All patients underwent magnetic resonance imaging with DWI, and ADC maps were generated. The whole lesion was selected to obtain histogram-related parameters, including the mean (ADC_mean), minimum (ADC_min), maximum (ADC_max), skewness, and kurtosis of the ADC. The final diagnosis included pleomorphic adenoma (PA; n=18), Warthin tumour (WT; n=12), and salivary gland malignancy (SGM; n=9). ADC_mean (×10^-3mm²/s) was 1.93±0.34 for PA, 1.01±0.11 for WT, and 1.26±0.54 for SGM. There was a significant difference in whole lesion ADC_mean among the three study groups. Skewness had the best diagnostic performance in differentiating PA from WT (P=0.001; best detected cut-off 0.41, area under the curve (AUC) 0.990) and in discriminating WT from SGM (P=0.03; best detected cut-off 0.74, AUC 0.806). The whole lesion ADC_mean value had best diagnostic performance in differentiating PA from SGM (P=0.007; best detected cut-off 1.16×10^-3mm²/s, AUC 0.948). In conclusion, histogram analysis of ADC maps may offer added value in the differentiation of parotid tumours.

Diffusion-weighted magnetic resonance imaging (DWMRI) of head and neck squamous cell carcinoma: could it be an imaging biomarker for prediction of response to chemoradiation therapy

Background

Chemoradiation therapy (CRT) has become a primary definitive treatment modality for head and neck squamous cell carcinoma (HNSCC); however, not all patients respond completely to treatment. Ability to identify those patients, who would not achieve complete response, before or early during the course of CRT will allow treatment modifications to improve outcome and overall survival. The aim of this prospective study was to assess the usefulness of diffusion-weighted imaging (DWI) in prediction of early therapeutic response of HNSCC after CRT.

Results

Local control was achieved in 22 patients out of 46 patients with pathologically proven HNSCC treated by chemoradiation therapy and local failure was detected in 24 patients out of 46 patients. Pretreatment mean apparent diffusion coefficient (ADCpre) was significantly higher in local failure group (1.1 ± 0.2 × 10−3 mm2/s) than local control group (0.89 ± 0.1 × 10−3 mm2/s). An optimal cut-off value of more than 0.94 × 10−3 mm2/s was predictive of local failure with sensitivity 83.33%, specificity 59.9%, PPV 69%, NPV 76.5%. Early intra-treatment percentage change of ADC (ΔADC) was significantly lower in local failure group (21.8% ± 21.3) than in local control group (45.2% ± 27.8). An optimal cut-off value of ≤ 33% was predictive of local failure after CRT with sensitivity of 71.34%, specificity of 60%, PPV of 62.5%, and NPV of 69.2%.

Conclusions

Diffusion-weighted MRI could be a potential predictive biomarker for therapeutic response of HNSCC to CRT. Primary tumors with higher pretreatment mean ADC, and a smaller early intratreatment percentage increase of mean ADC would be more likely to fail treatment.

The utility of multiparametric MRI to characterize hypoxic tumor subvolumes in comparison to FMISO PET/CT. Consequences for diagnosis and chemoradiation treatment planning in head and neck cancer

BACKGROUND AND PURPOSE

Hypoxia is an essential metabolic marker that determines chemo- and radiation resistance in head-and-neck squamous cell carcinoma (HNSCC) patients. Our exploratory analysis aimed to identify multiparametric MRI (mpMRI) parameters linked to hypoxia that might be used as surrogate for [¹⁸F]FMISO-PET in diagnosis and chemoradiation treatment (CRT) of HNSCC.

MATERIALS AND METHODS

21 patients undergoing definitive CRT for HNSCC were prospectively imaged with serial [¹⁸F]FMISO-PET and 3 Tesla mpMRI for T1- and T2-weighted and dynamic contrast-enhanced perfusion and diffusion-weighted measurements (k^trans, v_e, k_ep, ADC) in weeks 0, 2 and 5 and FDG-PET in week 0. [¹⁸F]FMISO-PET-derived hypoxic subvolumes (HSV) and complementary non-hypoxic subvolumes (nonHSV) were created for tumor and lymph nodes and projected on the mpMRI scans after PET/MRI co-registration. MpMRI and [¹⁸F]FMISO-PET parameters within HSVs and nonHSVs were statistically compared.

RESULTS

FMISO-PET-based HSVs of the primary tumors on MRI were characterized by lower ADC at all time points (p = 0.012 at baseline; p = 0.015 in week 2) and reduced interstitial space volume fraction v_e and perfusion k^trans at baseline (p = 0.006, p = 0.047) compared to nonHSVs. Hypoxic lymph nodes were characterized by significantly lower ADC values at baseline (p = 0.039), but not at later time points and a reduction in k^trans-based perfusion at week 2 (p = 0.018).

CONCLUSION

MpMRI parameters differ significantly between hypoxic and non-hypoxic tumor regions, defined on FMISO-PET/CT as gold standard and might represent surrogate markers for tumor hypoxia. These findings suggest that mpMRI may be useful in the future as a surrogate modality for hypoxia imaging in order to personalize CRT.

Diffusion kurtosis imaging in head and neck cancer: A correlation study with dynamic contrast enhanced MRI

PURPOSE

To investigate the biophysical meaning of Diffusion Kurtosis Imaging (DKI) parameters via correlations with the perfusion parameters obtained from a long Dynamic Contrast Enhanced MRI scan, in head and neck (HN) cancer.

METHODS

Twenty two patients with newly diagnosed HN tumor were included in the present retrospective study. Some patients had multiple lesions, therefore a total of 26 lesions were analyzed. DKI was acquired using 5b values at 0, 500, 1000,1500 and 2000 s/mm². DCE-MRI was obtained with 130 dynamic volumes, with a temporal resolution of 5 s, to achieve a long scan time (>10 min). The apparent diffusion coefficient D_app and apparent diffusional kurtosis K_app were calculated voxel-by-voxel, removing the point at b value = 0 to eliminate possible perfusion effects on the parameter estimations. The transfer constants K^trans and K_ep, v_e, and the histogram-based entropy (En) and interquartile range (IQR) of each DCE-MRI parameter were quantified. Correlations between all variables were investigated by the Spearman's Rho correlation test.

RESULTS

Moderate relationships emerged between D_app and K_ep (Rho =  - 0.510, p = 0.009), and between D_app and v_e (Rho = 0.418, p = 0.038). En(K_ep) was significantly related to K_app (Rho = 0.407, p = 0.043), while IQR(K_ep) showed an inverse association with D_app (Rho = -0.422, p = 0.035).

CONCLUSIONS

A weak to intermediate correlation was found between DKI parameters and both K_ep and v_e. The kurtosis was associated to the intratumoral heterogeneity and complexity of the capillary permeability, expressed by En(K_ep).

Application of integrated positron emission tomography/magnetic resonance imaging in evaluating the prognostic factors of head and neck squamous cell carcinoma with positron emission tomography, diffusion-weighted imaging, dynamic contrast enhancement and combined model

OBJECTIVES

This study was designed to investigate the distribution of the independent parameters of PET and MR in tumour differentiation and staging and to evaluate the diagnostic efficiency of the independent parameters and combined model of PET/MR in the tumour differentiation of head and neck squamous cell carcinoma (HNSCC).

METHODS

The patients with the preliminary diagnosis of HNSCC were included and underwent the integrated PET/MR The parameters included the diffusion-weighted imaging, dynamic contrast enhancement and PET. The correlations between different parameters and the distribution in groups of tumour differentiation and staging were analysed. The combined model was established with complementary PET/MR parameters. The diagnostic efficiency of the independent parameters and combined model in the tumour differentiation were analysed by receiver operating characteristic curve.

RESULTS

The correlations between the parameters of dynamic contrast enhancement and PET were most significant. There were significant differences between the well-differentiated group and the moderately/poorly differentiated group in terms of the mean values of apparent diffusion coefficient (ADC) and standardised uptake value (SUV) (p < 0.05). The distributions among different tumour stage groups were not statistically different in all the parameters. The diagnostic efficiency of tumour differentiation increased in the order of K_epmean, SUVmean, ADCmean, and the combined model.

CONCLUSIONS

Compared with the independent parameter, the combination of multiple parameters with PET/MR can further improve the diagnostic performance of tumour differentiation in HNSCC.

Correlation between histogram-based DCE-MRI parameters and 18F-FDG PET values in oropharyngeal squamous cell carcinoma: Evaluation in primary tumors and metastatic nodes

OBJECTIVES

To investigate the correlation between histogram-based Dynamic Contrast-Enhanced magnetic resonance imaging (DCE-MRI) parameters and positron emission tomography with 18F-fluorodeoxyglucose (18F-FDG-PET) values in oropharyngeal squamous cell carcinoma (OPSCC), both in primary tumors (PTs) and in metastatic lymph nodes (LNs).

METHODS

52 patients with a new pathologically-confirmed OPSCC were included in the present retrospective cohort study. Imaging including DCE-MRI and 18F-FDG PET/CT scans were acquired in all patients. Both PTs and the largest LN, if present, were volumetrically contoured. Quantitative parameters, including the transfer constants, Ktrans and Kep, and the volume of extravascular extracellular space, ve, were calculated from DCE-MRI. The percentiles (P), P10, P25, P50, P75, P90, and skewness, kurtosis and entropy were obtained from the histogram-based analysis of each perfusion parameter. Standardized uptake values (SUV), SUVmax, SUVpeak, SUVmean, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were calculated applying a SUV threshold of 40%. The correlations between all variables were investigated with the Spearman-rank correlation test. To exclude false positive results under multiple testing, the Benjamini-Hockberg procedure was applied.

RESULTS

No significant correlations were found between any parameters in PTs, while significant associations emerged between Ktrans and 18F-FDG PET parameters in LNs.

CONCLUSIONS

Evident relationships emerged between DCE-MRI and 18F-FDG PET parameters in OPSCC LNs, while no association was found in PTs. The complex relationships between perfusion and metabolic biomarkers should be interpreted separately for primary tumors and lymph-nodes. A multiparametric approach to analyze PTs and LNs before treatment is advisable in head and neck squamous cell carcinoma (HNSCC).

Recent advances in MRI of the head and neck, skull base and cranial nerves: new and evolving sequences, analyses and clinical applications

MRI is an invaluable diagnostic tool in the investigation and management of patients with pathology of the head and neck. However, numerous technical challenges exist, owing to a combination of fine anatomical detail, complex geometry (that is subject to frequent motion) and susceptibility effects from both endogenous structures and exogenous implants. Over recent years, there have been rapid developments in several aspects of head and neck imaging including higher resolution, isotropic 3D sequences, diffusion-weighted and diffusion-tensor imaging as well as permeability and perfusion imaging. These have led to improvements in anatomic, dynamic and functional imaging. Further developments using contrast-enhanced 3D FLAIR for the delineation of endolymphatic structures and black bone imaging for osseous structures are opening new diagnostic avenues. Furthermore, technical advances in compressed sensing and metal artefact reduction have the capacity to improve imaging speed and quality, respectively. This review explores novel and evolving MRI sequences that can be employed to evaluate diseases of the head and neck, including the skull base.

Differentiation of Malignant and Benign Head and Neck Tumors with Amide Proton Transfer-Weighted MR Imaging

PURPOSE

To prospectively evaluate the feasibility and capability of amide proton transfer-weighted (APTw) imaging for the characterization of head and neck tumors.

PROCEDURES

Twenty-nine consecutive patients with suspected head and neck tumors were enrolled in this study and underwent APTw magnetic resonance imaging (MRI) on a 3.0-T MRI scanner. The patients were divided into malignant (n = 16) and benign (n = 13) groups, based on pathological results. A map of magnetization transfer ratio asymmetry at 3.5 ppm [MTR_asym (3.5 ppm)] was generated for each patient. Interobserver agreement was evaluated and comparisons of MTR_asym (3.5 ppm) were made between the malignant and benign groups. Receiver operating characteristic analysis was used to determine the appropriate threshold value of MTR_asym (3.5 ppm) for the differentiation of malignant from benign tumors.

RESULTS

The intraclass correlation coefficients of the malignant and benign groups were 0.96 and 0.90, respectively, which indicated a good interobserver agreement. MTR_asym (3.5 ppm) was significantly higher for the malignant group (3.66 ± 1.15 %) than for the benign group (1.94 ± 0.93 %, P < 0.001). APTw MRI revealed an area under the curve of 0.904 in discriminating these two groups, with a sensitivity of 81.3 %, a specificity of 92.3 %, and an accuracy of 86.2 %, at the threshold of 2.62 % of MTR_asym (3.5 ppm).

CONCLUSIONS

APTw MRI is feasible for use in the head and neck tumors and is a valuable imaging biomarker for distinguishing malignant from benign lesions.

Imaging biomarkers in upper gastrointestinal cancers

In parallel with the increasingly widespread availability of high performance imaging platforms and recent progresses in pathobiological characterisation and treatment of gastrointestinal malignancies, imaging biomarkers have become a major research topic due to their potential to provide additional quantitative information to conventional imaging modalities that can improve accuracy at staging and follow-up, predict outcome, and guide treatment planning in an individualised manner. The aim of this review is to briefly examine the status of current knowledge about imaging biomarkers in the field of upper gastrointestinal cancers, highlighting their potential applications and future perspectives in patient management from diagnosis onwards.

Differential diagnostic value of diffusion-weighted and dynamic contrast-enhanced MR imaging in non-cystic lesions in floor of the mouth

METHODS:

A total of 82 patients were included in this study. The apparent diffusion coefficient (ADC) values and time-signal intensity curves (TICs) were measured. Clinical characteristics, ADC value, and TIC pattern were compared between benign and malignant FOM lesions. Receiver operating characteristic curve and logistic regression analyses were performed to evaluate respective and combined value of ADC value and TIC pattern for differential diagnosis. The retrospective study was approved by our institutional review board, and the need for informed consent was waived.

RESULTS:

The area under the curve ADC value and TIC pattern were 0.71 and 0.73, respectively. The combined use of ADC value and TIC pattern increased the area under the curve value to 0.81 [95% confidence interval (CI), (0.66-0.97)]. ADC < 1.23 × 10^-3 mm² s^-1 (odds ratio, 45.8; 95% CI, 2.8-737.9) and both the plateau and washout TIC patterns (OR, 6.8; 95% CI, 1.8-24.8) were significantly associated with malignancy of FOM lesions.

CONCLUSIONS:

Our results suggest that both diffusion-weighted imaging and DCE-MRI could contribute to the differential diagnosis of non-cystic FOM lesions, especially when used in combination.

Treatment Response Prediction of Nasopharyngeal Carcinoma Based on Histogram Analysis of Diffusional Kurtosis Imaging

BACKGROUND AND PURPOSE

The prediction of treatment response is important in planning and modifying the chemoradiation therapy regimen. This study aimed to explore the quantitative histogram indices for treatment-response prediction of nasopharyngeal carcinoma based on diffusional kurtosis imaging compared with a standard ADC value (ADC_standard).

MATERIALS AND METHODS

Thirty-six patients with an initial diagnosis of locoregionally advanced nasopharyngeal carcinoma and diffusional kurtosis imaging acquisitions before and after neoadjuvant chemotherapy were enrolled. Patients were divided into respond-versus-nonrespond groups after neoadjuvant chemotherapy and residual-versus-nonresidual groups after radiation therapy. Histogram parameters of diffusional kurtosis imaging-derived parameters (ADC, ADC coefficient corrected by the non-Gaussain model [D], apparent kurtosis coefficient without a unit [K]) were calculated. The ADC_standard was calculated on the basis of intravoxel incoherent movement data. The intraclass correlation coefficient, Kolmogorov-Smirnov test, Student t test or Mann-Whitney U test, and receiver operating characteristic analysis were performed.

RESULTS

Most of the parameters had good-to-excellent consistency (intraclass correlation coefficient = 0.675-0.998). The pre-ADC_standard, pre-ADC (10th, 25th, 50th percentiles), pre-D (10th, 25th, 50th percentiles), and pre-K_50th were significantly different between the respond and nonrespond groups, while the pre-ADC_10th, pre-K_90th, post-ADC_50th, post-K_75th, post-K_90th, and the percentage change of parameters before and after neoadjuvant chemotherapy (▵ADC_50th%) were significantly different between the residual and nonresidual groups (all P < .05). Receiver operating characteristic analysis indicated that setting pre-D_50th = 0.875 × 10^-3mm²/s as the cutoff value could result in optimal diagnostic performance for neoadjuvant chemotherapy response prediction (area under the curve = 0.814, sensitivity = 0.70, specificity = 0.92), while the post-K_90th = 1.035 (area under the curve = 0.829, sensitivity = 0.78, specificity = 0.72), and▵ADC_50th% = 0.253 (area under the curve = 0.833, sensitivity = 0.94, specificity = 0.72) were optimal for radiation therapy response prediction.

CONCLUSIONS

Histogram analysis of diffusional kurtosis imaging may potentially predict the neoadjuvant chemotherapy and short-term radiation therapy response in locoregionally advanced nasopharyngeal carcinoma, therefore providing evidence for modification of the treatment regimen.

Functional imaging early during (chemo)radiotherapy for response prediction in head and neck squamous cell carcinoma; a systematic review

This systematic review gives an extensive overview of the current state of functional imaging during (chemo)radiotherapy to predict locoregional control (LRC) and overall survival (OS) for head and neck squamous cell carcinoma. MEDLINE and EMBASE were searched for literature until April 2018 assessing the predictive performance of functional imaging (computed tomography perfusion (CTp), MRI and positron-emission tomography (PET)) within 4 weeks after (chemo)radiotherapy initiation. Fifty-two studies (CTp: n = 4, MRI: n = 19, PET: n = 26, MRI/PET: n = 3) were included involving 1623 patients. Prognostic information was extracted according the PRISMA protocol. Pooled estimation and subgroup analyses were performed for comparable parameters and outcome. However, the heterogeneity of included studies limited the possibility for comparison. Early tumoral changes from (chemo)radiotherapy can be captured by functional MRI and ¹⁸F-FDG-PET and could allow for personalized treatment adaptation. Lesions showed potentially prognostic intratreatment changes in perfusion, diffusion and metabolic activity. Intratreatment ADC_mean increase (decrease of diffusion restriction) and low SUV_max (persistent low or decrease of ¹⁸F-FDG uptake) were most predictive of LRC. Intratreatment persistent high or increase of perfusion on CT/MRI (i.e. blood flow, volume, permeability) also predicted LRC. Low SUV_max and total lesion glycolysis (TLG) predicted favorable OS. The optimal timing to perform functional imaging to predict LRC or OS was 2-3 weeks after treatment initiation.

Quantitative imaging biomarkers alliance (QIBA) recommendations for improved precision of DWI and DCE-MRI derived biomarkers in multicenter oncology trials

Physiological properties of tumors can be measured both in vivo and noninvasively by diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging. Although these techniques have been used for more than two decades to study tumor diffusion, perfusion, and/or permeability, the methods and studies on how to reduce measurement error and bias in the derived imaging metrics is still lacking in the literature. This is of paramount importance because the objective is to translate these quantitative imaging biomarkers (QIBs) into clinical trials, and ultimately in clinical practice. Standardization of the image acquisition using appropriate phantoms is the first step from a technical performance standpoint. The next step is to assess whether the imaging metrics have clinical value and meet the requirements for being a QIB as defined by the Radiological Society of North America's Quantitative Imaging Biomarkers Alliance (QIBA). The goal and mission of QIBA and the National Cancer Institute Quantitative Imaging Network (QIN) initiatives are to provide technical performance standards (QIBA profiles) and QIN tools for producing reliable QIBs for use in the clinical imaging community. Some of QIBA's development of quantitative diffusion-weighted imaging and dynamic contrast-enhanced QIB profiles has been hampered by the lack of literature for repeatability and reproducibility of the derived QIBs. The available research on this topic is scant and is not in sync with improvements or upgrades in MRI technology over the years. This review focuses on the need for QIBs in oncology applications and emphasizes the importance of the assessment of their reproducibility and repeatability. Level of Evidence: 5 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;49:e101-e121.

Quantitative diffusion magnetic resonance imaging in head and neck tumors

In patients with head and neck cancer, conventional anatomical magnetic resonance imaging (MRI) scans are commonly used for identification of primary lesion, assessment of structural distortion, and presence of metastatic lymph nodes. However, quantitative analysis of diffusion MRI can provide added value to structural and anatomical evaluation of head and neck tumors (HNT), by differentiation of primary malignant process, prognostic prediction, and treatment monitoring. In this article, we will review the applications of quantitative diffusion MRI in identification of primary malignant tissue, differentiation of tumor pathology, prediction of molecular phenotype, monitoring of treatment response, and evaluation of posttreatment changes in patient with HNT.

Cervical lymphadenopathy: can the histogram analysis of apparent diffusion coefficient help to differentiate between lymphoma and squamous cell carcinoma in patients with unknown clinical primary tumor?

PURPOSE

To retrospectively evaluate the value of whole-lesion histogram analysis of apparent diffusion coefficient (ADC) maps in differentiating between lymphoma and metastatic squamous cell carcinoma (SCC) of unknown clinical primary in neck nodes.

METHODS

A total of 39 patients, 20 affected by lymphoma and 19 affected by metastatic non-nasopharyngeal SCC, were included in this retrospective study. All patients underwent MR imaging with a 1.5 T scanner system, including diffusion-weighted imaging (DWI) with three different b values (b = 0, 500 and 800 s/mm²). The entire tumor volume was manually delineated on the ADC maps, using the T2-weighted images and DWIs with b = 800 s/mm² as a guide to the lesion location. The Mann-Whitney rank-sum test for independent samples was performed to compare the histogram parameters of patients with lymphoma and SCC.

RESULTS

The SCCs showed significantly higher median ADC (ADC_median) and mean ADC (ADC_mean) values, compared to lymphomas (p < 0.001), while they exhibited lower kurtosis and skewness without reaching significance (p = 0.066 and 0.148, respectively). The ADC_mean and ADC_median had the best discriminative powers for differentiating lymphoma and SCC, with an area under the curve of 87% and 85%, respectively. The optimal cutoff values for ADC_mean and ADC_median as predictors for lymphoma were ≤ 0.83 × 10^-3 mm²/s and ≤ 0.73 × 10^-3 mm²/s, respectively.

CONCLUSIONS

The whole-lesion ADC histogram analysis of cervical lymphadenopathy may help to discriminate lymphomas from non-nasopharyngeal SCC in patients with unknown clinical primary tumor.

The Promise of Novel Biomarkers for Head and Neck Cancer from an Imaging Perspective

It is an agreed fact that overall survival among head and neck cancer patients has increased over the last decade. Several factors however, are still held responsible for treatment failure requiring more in-depth evaluation. Among these, hypoxia and proliferation-specific parameters are the main culprits, along with the more recently researched cancer stem cells. This paper aims to present the latest developments in the field of biomarkers for hypoxia, stemness and tumour proliferation, from an imaging perspective that includes both Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT) as well as functional magnetic resonance imaging (MRI). Quantitative imaging of biomarkers is a prerequisite for accurate treatment response assessment, bringing us closer to the highly needed personalised therapy.

Functional MRI for Treatment Evaluation in Patients with Head and Neck Squamous Cell Carcinoma: A Review of the Literature from a Radiologist Perspective

PURPOSE OF REVIEW

To show the role of functional MRI in patients treated for head and neck squamous cell carcinoma.

RECENT FINDINGS

MRI is commonly used for treatment evaluation in patients with head and neck tumors. However, anatomical MRI has its limits in differentiating between post-treatment effects and tumor recurrence. Recent studies showed promising results of functional MRI for response evaluation.

SUMMARY

This review analyzes possibilities and limitations of functional MRI sequences separately to obtain insight in the post-therapy setting. Diffusion, perfusion and spectroscopy show promise, especially when utilized complimentary to each other. These functional MRI sequences aid in the early detection which might improve survival by increasing effectiveness of salvage therapy. Future multicenter longitudinal prospective studies are needed to provide standardized guidelines for the use of functional MRI in daily clinical practice.

Head and neck paragangliomas: diffusion weighted and dynamic contrast enhanced magnetic resonance imaging characteristics

Background

To determine the feature values of head and neck paragangliomas on diffusion-weighted imaging (DWI) and dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI).

Methods

Patients with primary head and neck paraganglioma who underwent both DWI and DCE-MRI before treatment between January 2010 and June 2013 were identified. Two radiologists assessed apparent diffusion coefficient (ADC) values on DWI and kinetic characteristics on DCE-MRI. The time intensity curves (TICs) and dynamic parameters, including peak height (PH), maximum enhancement ratio (ER_max), time to peak enhancement (T_peak) and maximum rise slope (Slope_max), were generated and evaluated.

Results

Ten patients with head and neck paraganglioma were retrospectively analyzed. On conventional MRI, the tumors demonstrated as well-circumscribed, strongly enhanced lesions. Mean ADC value of the lesions was 1.12 ± 0.15 × 10⁻³ mm²/s. The TICs demonstrated washout pattern (type-III) in all lesions. The mean PH, ER_max, T_peak and Slope_max value was 121.24 ± 63.99, 193.79 ± 67.18, 8.16 ± 3.29 and 25.42 ± 7.91, respectively.

Conclusions

Head and neck paragangliomas demonstrate distinctive DWI and DCE-MRI results than for other benign tumors which should be taken into account in further evaluation of MRI on head and neck lesions.

Texture analysis on parametric maps derived from dynamic contrast-enhanced magnetic resonance imaging in head and neck cancer

AIM: To investigate the merits of texture analysis on parametric maps derived from pharmacokinetic modeling with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as imaging biomarkers for the prediction of treatment response in patients with head and neck squamous cell carcinoma (HNSCC).

METHODS: In this retrospective study, 19 HNSCC patients underwent pre- and intra-treatment DCE-MRI scans at a 1.5T MRI scanner. All patients had chemo-radiation treatment. Pharmacokinetic modeling was performed on the acquired DCE-MRI images, generating maps of volume transfer rate (K^trans) and volume fraction of the extravascular extracellular space (v_e). Image texture analysis was then employed on maps of K^trans and v_e, generating two texture measures: Energy (E) and homogeneity.

RESULTS: No significant changes were found for the mean and standard deviation for K^trans and v_e between pre- and intra-treatment (P > 0.09). Texture analysis revealed that the imaging biomarker E of v_e was significantly higher in intra-treatment scans, relative to pretreatment scans (P < 0.04).

CONCLUSION: Chemo-radiation treatment in HNSCC significantly reduces the heterogeneity of tumors.