Dynamic contrast-enhanced magnetic resonance imaging biomarkers in head and neck cancer: Potential to guide treatment? A systematic review

Dynamic contrast-enhanced magnetic resonance imaging in cervical cancer: correlation between quantitative parameters and molecular markers hypoxia-inducible factors-1-alpha, vascular endothelial growth factor, and Ki-67

AIM

To investigate whether dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has the potential to non-invasively detect microenvironmental condition by quantitatively measuring blood perfusion, vessel wall permeability, and vascularity, and to elucidate the possible correlations between DCE-MRI quantitative parameters and the expression level of hypoxia, vascularity, and cell proliferation related molecular biomarkers.

MATERIALS AND METHODS

In this prospective single center clinical study, 58 patients diagnosed with cervical cancer underwent DCE-MRI before anticancer treatment were enrolled. Ktrans, Kep, Ve, and Vp were generated from Extended Toft's model. Then patients conducted colposcopy biopsy within 1 week after DCE-MRI. Pretreatment expression levels of HIF-1α, VEGF and Ki-67 were assessed and scored by immunohistochemistry on colposcopy obtained tumor specimens.

RESULTS

In HIF-1α low-expression group, Ktrans (p=0.031) and Kep (p=0.012) values were significantly higher than the high-expression group. In VEGF high-expression group, Ktrans (p=0.044) and Ve values (p=0.021) were significantly higher than the low-expression group. In Ki-67 high-expression group, Ktrans (p=0.026) and Kep (p=0.033) were significantly higher than the low-expression group. Multiple linear regression analyses and Pearson correlation revealed that Ktrans independently negatively correlated with HIF-1α expression, Ve independently positively correlated with VEGF, and Kep independently positively correlated with Ki-67. The area under the ROC curves of Ktrans for HIF-1α, Ve for VEGF, and Kep for Ki-67 were 0.728, 0.743, 0.730, respectively.

CONCLUSION

Our results suggest that DCE-MRI quantitative parameters could be potentially used as imaging markers for non-invasively detecting microenvironmental hypoxia, vascularity and proliferation in cervical cancer patients.

PDZK1 is correlated with DCE-MRI perfusion parameters in high-grade glioma

OBJECTIVE

This study investigated the relationship between PDZK1 expression and Dynamic Contrast-Enhanced MRI (DCE-MRI) perfusion parameters in High-Grade Glioma (HGG).

METHODS

Preoperative DCE-MRI scanning was performed on 80 patients with HGG to obtain DCE perfusion transfer coefficient (Ktrans), vascular plasma volume fraction (vp), extracellular volume fraction (ve), and reverse transfer constant (kep). PDZK1 in HGG patients was detected, and its correlation with DCE-MRI perfusion parameters was assessed by the Pearson method. An analysis of Cox regression was performed to determine the risk factors affecting survival, while Kaplan-Meier and log-rank tests to evaluate PDZK1's prognostic significance, and ROC curve analysis to assess its diagnostic value.

RESULTS

PDZK1 was upregulated in HGG patients and predicted poor overall survival and progression-free survival. Moreover, PDZK1 expression distinguished grade III from grade IV HGG. PDZK1 expression was positively correlated with Ktrans 90, and ve_90, and negatively correlated with kep_max, and kep_90.

CONCLUSION

PDZK1 is upregulated in HGG, predicts poor survival, and differentiates tumor grading in HGG patients. PDZK1 expression is correlated with DCE-MRI perfusion parameters.

The Use of MR-Guided Radiation Therapy for Head and Neck Cancer and Recommended Reporting Guidance

Although magnetic resonance imaging (MRI) has become standard diagnostic workup for head and neck malignancies and is currently recommended by most radiological societies for pharyngeal and oral carcinomas, its utilization in radiotherapy has been heterogeneous during the last decades. However, few would argue that implementing MRI for annotation of target volumes and organs at risk provides several advantages, so that implementation of the modality for this purpose is widely accepted. Today, the term MR-guidance has received a much broader meaning, including MRI for adaptive treatments, MR-gating and tracking during radiotherapy application, MR-features as biomarkers and finally MR-only workflows. First studies on treatment of head and neck cancer on commercially available dedicated hybrid-platforms (MR-linacs), with distinct common features but also differences amongst them, have also been recently reported, as well as "biological adaptation" based on evaluation of early treatment response via functional MRI-sequences such as diffusion weighted ones. Yet, all of these approaches towards head and neck treatment remain at their infancy, especially when compared to other radiotherapy indications. Moreover, the lack of standardization for reporting MR-guided radiotherapy is a major obstacle both to further progress in the field and to conduct and compare clinical trials. Goals of this article is to present and explain all different aspects of MR-guidance for radiotherapy of head and neck cancer, summarize evidence, as well as possible advantages and challenges of the method and finally provide a comprehensive reporting guidance for use in clinical routine and trials.

Quantitative dynamic contrast-enhanced magnetic resonance imaging in head and neck cancer: A systematic comparison of different modelling approaches

Background and purpose

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) describes tissue microvasculature and has prognostic and predictive potential in radiotherapy for head and neck cancer (HNC). However, lack in standardization of DCE-MRI hinders comparison of studies and clinical implementation. This study investigated the accuracy and robustness of the population arterial input function (AIF), correlations between pharmacokinetic parameters and their association to T stage and human papillomavirus (HPV) status for HNC.

Materials and methods

DCE-MRI was acquired for 44 HNC patients. Population AIFs were calculated with six different approaches. DCE-MRI was analysed in primary and lymph node tumours using Tofts model (TM) with population AIFs and individual AIFs, extended TM (ETM) with individual AIFs, Brix model (BM), and areas under the curve (AUCs). Intraclass correlation, concordance correlation, Pearson correlation and Whitney Mann U test helped examining the robustness and accuracy of population AIF, correlations between DCE-MRI parameters and their association to T stage and HPV status, respectively.

Results

The population AIF was robust but differed from individual AIFs. There was significant correlation between KtransTM/ETM and ve, TM/ETM, and KtransTM/ETM and Kep, TM/ETM. ABrix and AUCs correlated for lymph nodes. Kep, Brix correlated with ABrix, KtransTM/ETM and Kep, TM/ETM for primary tumours. Kep, TM significantly decreased with increasing T stage. Both the correlations and the parameters' association to T stage were stronger for HPV negative lesions.

Conclusions

Individual AIF was preferred for accurate pharmacokinetic modelling of DCE-MRI. DCE-MRI parameters and their correlations were affected by the lesion type, HPV status and T staging.

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.

Clinical indications and acquisition protocol for the use of dynamic contrast-enhanced MRI in head and neck cancer squamous cell carcinoma: recommendations from an expert panel

BACKGROUND

The clinical role of perfusion-weighted MRI (PWI) in head and neck squamous cell carcinoma (HNSCC) remains to be defined. The aim of this study was to provide evidence-based recommendations for the use of PWI sequence in HNSCC with regard to clinical indications and acquisition parameters.

METHODS

Public databases were searched, and selected papers evaluated applying the Oxford criteria 2011. A questionnaire was prepared including statements on clinical indications of PWI as well as its acquisition technique and submitted to selected panelists who worked in anonymity using a modified Delphi approach. Each panelist was asked to rate each statement using a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree). Statements with scores equal or inferior to 5 assigned by at least two panelists were revised and re-submitted for the subsequent Delphi round to reach a final consensus.

RESULTS

Two Delphi rounds were conducted. The final questionnaire consisted of 6 statements on clinical indications of PWI and 9 statements on the acquisition technique of PWI. Four of 19 (21%) statements obtained scores equal or inferior to 5 by two panelists, all dealing with clinical indications. The Delphi process was considered concluded as reasons entered by panelists for lower scores were mainly related to the lack of robust evidence, so that no further modifications were suggested.

CONCLUSIONS

Evidence-based recommendations on the use of PWI have been provided by an independent panel of experts worldwide, encouraging a standardized use of PWI across university and research centers to produce more robust evidence.

The correlations between dynamic contrast enhanced magnetic resonance imaging and immunohistochemical data in head and neck squamous cell carcinomas

BACKGROUND

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) can in vivo characterize tumor microvascular environment. The aim of the present study was to reveal the DCE-MRI findings and to determine the correlation between these findings and immunohistochemical data in head and neck squamous cell carcinoma (HNSCC).

METHODS

Thirty-three patients diagnosed with primary HNSCC were evaluated retrospectively. DCE-MRI was conducted in all cases. CD34, CD105, and ki-67 expressions were analyzed with immunohistochemistry in tissue sections to determine micro-vessel density and proliferative activity.

RESULTS

The DCE-MRI is a successful technique in distinguishing tumor tissue from normal tissue. It was determined that Ve, Ktrans, and ki-67 values were significantly higher in high-stage tumors and there were positive correlations between the Ktrans value (by standard ROI) and CD34 MVDmax and CD34 MVDmean values. No statistically significant correlation was determined between other parameters in DCE-MRI and immunohistochemical data, and T stage.

DISCUSSION

DCE-MRI could successfully differentiate tumor tissue in HNSCC. Furthermore, it was observed that DCE-MRI had the potential to reveal certain immunohistochemical information in vivo.

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.

MR-Guided Adaptive Radiotherapy for OAR Sparing in Head and Neck Cancers

Simple Summary

Normal tissue toxicities in head and neck cancer persist as a cause of decreased quality of life and are associated with poorer treatment outcomes. The aim of this article is to review organ at risk (OAR) sparing approaches available in MR-guided adaptive radiotherapy and present future developments which hope to improve treatment outcomes. Increasing the spatial conformity of dose distributions in radiotherapy is an important first step in reducing normal tissue toxicities, and MR-guided treatment devices presents a new opportunity to use biological information to drive treatment decisions on a personalized basis.

Abstract

MR-linac devices offer the potential for advancements in radiotherapy (RT) treatment of head and neck cancer (HNC) by using daily MR imaging performed at the time and setup of treatment delivery. This article aims to present a review of current adaptive RT (ART) methods on MR-Linac devices directed towards the sparing of organs at risk (OAR) and a view of future adaptive techniques seeking to improve the therapeutic ratio. This ratio expresses the relationship between the probability of tumor control and the probability of normal tissue damage and is thus an important conceptual metric of success in the sparing of OARs. Increasing spatial conformity of dose distributions to target volume and OARs is an initial step in achieving therapeutic improvements, followed by the use of imaging and clinical biomarkers to inform the clinical decision-making process in an ART paradigm. Pre-clinical and clinical findings support the incorporation of biomarkers into ART protocols and investment into further research to explore imaging biomarkers by taking advantage of the daily MR imaging workflow. A coherent understanding of this road map for RT in HNC is critical for directing future research efforts related to sparing OARs using image-guided radiotherapy (IGRT).

Histogram analysis of dynamic contrast-enhanced magnetic resonance imaging in the differential diagnosis of parotid tumors

Objective

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) histograms were used to investigate whether their parameters can distinguish between benign and malignant parotid gland tumors and further differentiate tumor subgroups.

Materials and methods

A total of 117 patients (32 malignant and 85 benign) who had undergone DCE-MRI for pretreatment evaluation were retrospectively included. Histogram parameters including mean, median, entropy, skewness, kurtosis and 10th, 90th percentiles were calculated from time to peak (TTP) (s), wash in rate (WIR) (l/s), wash out rate (WOR) (l/s), and maximum relative enhancement (MRE) (%) mono-exponential models. The Mann–Whitney U test was used to compare the differences between the benign and malignant groups. The diagnostic value of each significant parameter was determined on Receiver operating characteristic (ROC) analysis. Multivariate stepwise logistic regression analysis was used to identify the independent predictors of the different tumor groups.

Results

For both the benign and malignant groups and the comparisons among the subgroups, the parameters of TTP and MRE showed better performance among the various parameters. WOR can be used as an indicator to distinguish Warthin’s tumors from other tumors. Warthin’s tumors showed significantly lower values on 10th MRE and significantly higher values on skewness TTP and 10th WOR, and the combination of 10th MRE, skewness TTP and 10th WOR showed optimal diagnostic performance (AUC, 0.971) and provided 93.12% sensitivity and 96.70% specificity. After Warthin’s tumors were removed from among the benign tumors, malignant parotid tumors showed significantly lower values on the 10th TTP (AUC, 0.847; sensitivity 90.62%; specificity 69.09%; P < 0.05) and higher values on skewness MRE (AUC, 0.777; sensitivity 71.87%; specificity 76.36%; P < 0.05).

Conclusion

DCE-MRI histogram parameters, especially TTP and MRE parameters, show promise as effective indicators for identifying and classifying parotid tumors. Entropy TTP and kurtosis MRE were found to be independent differentiating variables for malignant parotid gland tumors. The 10th WOR can be used as an indicator to distinguish Warthin’s tumors from other tumors.

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.

Associations between dynamic-contrast enhanced MRI and tumor infiltrating lymphocytes and tumor-stroma ratio in head and neck squamous cell cancer

Objectives

The present study used dynamic-contrast enhanced MRI (DCE-MRI) to elucidate possible associations with tumor-infiltrating lymphocytes (TIL), stroma ratio and vimentin expression in head and neck squamous cell cancer (HNSCC).

Methods

Overall, 26 patients with primary HNSCC of different localizations were involved in the study. DCE-MRI was obtained on a 3 T MRI and analyzed with a whole lesion measurement using a histogram approach. TIL- and vimentin-expression was calculated on bioptic samples before any form of treatment. P16 staining was used to define HPV-status.

Results

Tumor-stroma ratio correlated with entropy derived from K^trans (r = − 0.52, p = 0.0071) and with kurtosis derived from V_e (r = − 0.53, p = 0.0058).

Several V_e derived parameters correlated with expression of TIL within the stroma compartment. TIL within the tumor compartment correlated with entropy derived from K^trans (r = 0.39, p = 0.047), p90 derived from V_e (r = 0.41, p = 0.036) and skewness derived from V_e (r = 0.41, p = 0.037). Furthermore, these associations were different between HPV positive and negative tumors.

Conclusions

DCE-MRI might be able to reflect tumor compartments and TIL expression in HNSCC. The most promising parameters were values derived from K^trans and V_e.

Comparison of the pre-treatment functional MRI metrics' efficacy in predicting Locoregionally advanced nasopharyngeal carcinoma response to induction chemotherapy

Background

Functional MRI (fMRI) parameters analysis has been proven to be a promising tool of predicting therapeutic response to induction chemotherapy (IC) in nasopharyngeal carcinoma (NPC). The study was designed to identify and compare the value of fMRI parameters in predicting early response to IC in patients with NPC.

Methods

This prospective study enrolled fifty-six consecutively NPC patients treated with IC from January 2021 to May 2021. Conventional diffusion weighted imaging (DWI), diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) protocols were performed before and after IC. Parameters maps (ADC, MD, MK, D_slow, D_fast, PF, K^trans, V_e and K_ep) of the primary tumor were calculated by the Functool post-processing software. The participants were classified as responding group (RG) and non-responding group (NRG) according to Response Evaluation Criteria in Solid Tumors 1.1. The fMRI parameters were compared before and after IC and between RG with NRG. Logistic regression analysis and ROC were performed to further identify and compare the efficacy of the parameters.

Results

After IC, the mean values of ADC(p < 0.001), MD(p < 0.001), D_slow(p = 0.001), PF(p = 0.030) and V_e(p = 0.003) significantly increased, while MK(p < 0.001), D_fast(p = 0.009) and K_ep(p = 0.003) values decreased dramatically, while no significant difference was detected in K^trans(p = 0.130). Compared with NRG, ADC-pre(p < 0.001), MD-pre(p < 0.001) and D_slow-pre(p = 0.002) values in RG were lower, while MK-pre(p = 0.017) values were higher. The areas under the ROC curves for the ADC-pre, MD-pre, MK-pre, D_slow-pre and PRE were 0.885, 0.855, 0.809, 0.742 and 0.912, with the optimal cutoff value of 1210 × 10^− 6 mm²/s, 1010 × 10^− 6 mm²/s, 832 × 10^− 6, 835 × 10^− 6 mm²/s and 0.799 respectively.

Conclusions

The pretreatment conventional DWI (ADC), DKI (MD and MK), and IVIM (D_slow) values derived from fMRI showed a promising potential in predicting the response of the primary tumor to IC in NPC patients.

Trial registration

This study was approved by ethics board of the Chinese PLA General Hospital, and registered on January 30, 2021, in Chinese Clinical Trial Registry (ChiCTR2100042863).

Supplementary Information

The online version contains supplementary material available at 10.1186/s40644-021-00428-0.

Relationships Between DCE-MRI, DWI, and 18F-FDG PET/CT Parameters with Tumor Grade and Stage in Patients with Head and Neck Squamous Cell Carcinoma

Objectives

Properties of head and neck squamous cell carcinoma (HNSCC) such as cellularity, vascularity, and glucose metabolism interact with each other. This study aimed to investigate the associations between diffusion-weighted imaging (DWI), dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), and positron emission tomography/computed tomography (PET/CT) in patients with HNSCC.

Methods

Fourteen patients who were diagnosed with HNSCC were investigated using DCE-MRI, DCE, and ¹⁸fluoride-fluorodeoxyglucose PET/CT and evaluated retrospectively. Ktrans, Kep, Ve, and initial area under the curve (iAUC) parameters from DCE-MRI, ADC_max, ADC_mean, and ADCmin parameters from DWI, and maximum standardized uptake value (SUV_max), SUV_mean, metabolic tumor volume (MTV), and total lesion glycolysis (TLG) parameters from PET were obtained. Spearman's correlation coefficient was used to analyze associations between these parameters. In addition, these parameters were grouped according to tumor grade and T and N stages, and the difference between the groups was evaluated using the Mann-Whitney U test.

Results

Correlations at varying degrees were observed in the parameters investigated. ADC_mean moderately correlated with Ve (p=0.035; r=0.566). Ktrans inversely correlated with SUV_max (p=0.017; r=-0.626). iAUC inversely correlated with SUV_max, SUV_mean, TLG, and MTV (p<0.05, r≤-0.700). MTV (40% threshold) was significantly higher in T4 tumors than in T1-3 tumors (p=0.020). No significant difference was found in the grouping made according to tumor grade and N stage in terms of these parameters.

Conclusion

Tumor cellularity, vascular permeability, and glucose metabolism had significant correlations at different degrees. Furthermore, MTV may be useful in predicting T4 tumors.

Prognostic functional MR imaging parameters in head and neck squamous cell carcinoma: A systematic review

OBJECTIVE

Functional MR imaging has demonstrated potential for predicting treatment response. This systematic review gives an extensive overview of the current level of evidence for pre-treatment MR-based perfusion and diffusion imaging parameters that are prognostic for treatment outcome in head and neck squamous cell carcinoma (HNSCC) (PROSPERO registrationCRD42020210689).

MATERIALS AND METHODS

According to the PRISMA statements, Medline, Embase and Scopus were queried for articles with a maximum date of October 19th, 2020. Studies investigating the predictive performance of pre-treatment MR-based perfusion and/or diffusion imaging parameters in HNSCC treatment response were included. All prognosticators were extracted from the primary tumor. Risk of bias was assessed using the QUIPS tool. Results were summarized in tables and forest plots.

RESULTS

31 unique studies met the inclusion criteria; among them, 11 articles described perfusion (n = 529 patients) and 28 described diffusion (n = 1626 patients) MR-imaging, eight studies were included in both categories. Higher K^trans and K_ep were associated with better treatment response for OS and DFS, respectively. Study findings for V_p and V_e were inconsistent or not significant. High-level controversy was observed between studies examining the MR diffusion parameters mean and median ADC.

CONCLUSION

For HNSCC patients, the accurate and consistent results of pre-treatment MR-based perfusion parameters K^trans and K_ep are potential for clinical applicability predictive of OS and DFS and treatment decision guidance. Significant heterogeneity in study designs might affect high discrepancy in study results for parameters extracted from diffusion imaging. Furthermore, recommendations for future research were summarized.

Tumor Blood Flow Is a Predictor of Radiotherapy Response in Patients With Nasopharyngeal Carcinoma

Purpose

The aim of this study was to evaluate tumor blood flow (TBF) as a predictor of radiotherapy response for nasopharyngeal carcinoma (NPC).

Materials and Method

A total of 134 patients were divided into two groups, the complete response (CR) group and the partial response (PR) group based on RECIST 1.1 recommendations. The statistical difference was evaluated for pre- and mid- or post-treatment TBF and changes of TBF for tumors and metastatic lymph nodes between CR and PR, respectively. The receiver operation characteristic (ROC) curve was utilized to evaluate the accuracy of TBF in predicting the response of radiation therapy. The association between TBF and SUVmax was also investigated.

Results

The reduction of TBF in CR was significantly lower than that in PR for primary tumors (P <0.001) and metastatic lymph nodes (P <0.001). The multivariate logistic regression analysis indicated that the reduction of TBF is an independent predictor of the response of radiation therapy for primary tumors (P <0.001) and metastatic lymph nodes (P <0.001). The accuracy of TBF reduction in predicting the response of radiation therapy was 0.817 in primary tumors and 0.924 in metastatic lymph nodes, respectively. No significant correlation was observed between the TBF values and SUVmax of primary tumors (r = -0.008, P = 0.954) and metastasis lymph nodes (r = -0.061, P = 0.652).

Conclusion

This study suggests that the reduction of TBF is a promising parameter for evaluating the response of radiation therapy.

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.

Assessment of metastatic lymph nodes in head and neck squamous cell carcinomas using simultaneous 18F-FDG-PET and MRI

In this study, we investigate the feasibility of using dynamic contrast enhanced magnetic resonance imaging (DCE-MRI), diffusion weighted imaging (DWI), and dynamic positron emission tomography (PET) for detection of metastatic lymph nodes in head and neck squamous cell carcinoma (HNSCC) cases. Twenty HNSCC patients scheduled for lymph node dissection underwent DCE-MRI, dynamic PET, and DWI using a PET-MR scanner within one week prior to their planned surgery. During surgery, resected nodes were labeled to identify their nodal levels and sent for routine clinical pathology evaluation. Quantitative parameters of metastatic and normal nodes were calculated from DCE-MRI (v_e, v_p, PS, F_p, K^trans), DWI (ADC) and PET (K_i, K₁, k₂, k₃) to assess if an individual or a combination of parameters can classify normal and metastatic lymph nodes accurately. There were 38 normal and 11 metastatic nodes covered by all three imaging methods and confirmed by pathology. 34% of all normal nodes had volumes greater than or equal to the smallest metastatic node while 4 normal nodes had SUV > 4.5. Among the MRI parameters, the median v_p, F_p, PS, and K^trans values of the metastatic lymph nodes were significantly lower (p = <0.05) than those of normal nodes. v_e and ADC did not show any statistical significance. For the dynamic PET parameters, the metastatic nodes had significantly higher k₃ (p value = 8.8 × 10^-8) and K_i (p value = 5.3 × 10^-8) than normal nodes. K₁ and k₂ did not show any statistically significant difference. K_i had the best separation with accuracy = 0.96 (sensitivity = 1, specificity = 0.95) using a cutoff of K_i = 5.3 × 10^-3 mL/cm³/min, while k₃ and volume had accuracy of 0.94 (sensitivity = 0.82, specificity = 0.97) and 0.90 (sensitivity = 0.64, specificity = 0.97) respectively. 100% accuracy can be achieved using a multivariate logistic regression model of MRI parameters after thresholding the data with K_i < 5.3 × 10^-3 mL/cm³/min. The results of this preliminary study suggest that quantitative MRI may provide additional value in distinguishing metastatic nodes, particularly among small nodes, when used together with FDG-PET.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for pretreatment prediction of neoadjuvant chemotherapy response in locally advanced hypopharyngeal cancer

Objective:The aim of this study was to predict response to neoadjuvant chemotherapy (NAC) in patients with locally advanced hypopharyngeal cancer by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).Methods:A retrospective study enrolled 46 diagnosed locally advanced hypopharyngeal cancer. DCE-MRI were performed prior to and after two cycles of NAC. The volume transfer constant (K^trans), extracellular extravascular volume fraction (V_e), and plasma volume fraction (K_ep) were computed from primary tumors. DCE-MRI parameters were used to measure tumor response according to the Response Evaluation Criteria in Solid Tumors criteria (RECIST).Results：After 2 NAC cycles, 30 out of 46 patients were categorized into the responder group, whereas the other 16 were categorized into non-responder group. Compared with the pretreatment value, the post-treatment K^trans and K_ep was significantly lower (P < 0.05), but no significant change in V_e (P > 0.05). Compared with non-responders, a notably higher pretreatment K^trans, K_ep, lower post-treatment K^trans, higher ΔK^trans and ΔK_ep were observed in responders (all P < 0.05). While the pretreatment V_e, post-treatment V_e, and ΔV_e did not differ significantly (P>0.05) between the two groups. The receiver operating characteristic curve analysis revealed that pretreatment K^trans of 0.202/min is the most optimal cut-off in predicting response to chemotherapy, resulting in an AUC of 0.837 and corresponding sensitivity and specificity of 76.7%, and 81.1%, respectively.Conclusion:DCE-MRI especially pretreatment K^trans can potentially predict the treatment response to neoadjuvant chemotherapy for hypopharyngeal cancer.Advances in knowledge:Few studies of DCE-MRI on hypopharyngeal cancer treated with chemoradiation reported. The results demonstrate that DCE-MRI especially pretreatment K^trans may be more potential value in predicting the treatment response to neoadjuvant chemotherapy for hypopharyngeal cancer.

Quantitative dynamic contrast-enhanced MR imaging can be used to predict the pathologic stages of oral tongue squamous cell carcinoma

Background

To investigate whether quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) pharmacokinetic parameters can be used to predict the pathologic stages of oral tongue squamous cell carcinoma (OTSCC).

Methods

For this prospective study, DCE-MRI was performed in participants with OTSCC from May 2016 to June 2017. The pharmacokinetic parameters, including K^trans, K_ep, V_e, and V_p, were derived from DCE-MRI by utilizing a two-compartment extended Tofts model and a three-dimensional volume of interest. The postoperative pathologic stage was determined in each patient based on the 8th AJCC cancer staging manual. The quantitative DCE-MRI parameters were compared between stage I–II and stage III–IV lesions. Logistic regression analysis was used to determine independent predictors of tumor stages, followed by receiver operating characteristic (ROC) analysis to evaluate the predictive performance.

Results

The mean K^trans, K_ep and V_p values were significantly lower in stage III–IV lesions compared with stage I–II lesions (p = 0.013, 0.005 and 0.011, respectively). K_ep was an independent predictor for the advanced stages as determined by univariate and multivariate logistic analysis. ROC analysis showed that K_ep had the highest predictive capability, with a sensitivity of 64.3%, a specificity of 82.6%, a positive predictive value of 81.8%, a negative predictive value of 65.5%, and an accuracy of 72.5%.

Conclusion

The quantitative DCE-MRI parameter K_ep can be used as a biomarker for predicting pathologic stages of OTSCC.

Squamous Cell Carcinoma and Lymphoma of the Oropharynx: Differentiation Using a Radiomics Approach

The purpose of this study was to evaluate the diagnostic performance of magnetic resonance (MR) radiomics-based machine learning algorithms in differentiating squamous cell carcinoma (SCC) from lymphoma in the oropharynx. MR images from 87 patients with oropharyngeal SCC (n=68) and lymphoma (n=19) were reviewed retrospectively. Tumors were semi-automatically segmented on contrast-enhanced T1-weighted images registered to T2-weighted images, and radiomic features (n=202) were extracted from contrast-enhanced T1- and T2-weighted images. The radiomics classifier was built using elastic-net regularized generalized linear model analyses with nested five-fold cross-validation. The diagnostic abilities of the radiomics classifier and visual assessment by two head and neck radiologists were evaluated using receiver operating characteristic (ROC) analyses for distinguishing SCC from lymphoma. Nineteen radiomics features were selected at least twice during the five-fold cross-validation. The mean area under the ROC curve (AUC) of the radiomics classifier was 0.750 [95% confidence interval (CI), 0.613-0.887], with a sensitivity of 84.2%, specificity of 60.3%, and an accuracy of 65.5%. Two human readers yielded AUCs of 0.613 (95% CI, 0.467-0.759) and 0.663 (95% CI, 0.531-0.795), respectively. The radiomics-based machine learning model can be useful for differentiating SCC from lymphoma of the oropharynx.

Exercise-induced calf muscle hyperemia: Rapid mapping of magnetic resonance imaging using deep learning approach

Exercise-induced hyperemia in calf muscles was recently shown to be quantifiable with high-resolution magnetic resonance imaging (MRI). However, processing of the MRI data to obtain muscle-perfusion maps is time-consuming. This study proposes to substantially accelerate the mapping of muscle perfusion using a deep-learning method called artificial neural network (NN). Forty-eight MRI scans were acquired from 21 healthy subjects and patients with peripheral artery disease (PAD). For optimal training of NN, different training-data sets were compared, investigating the effect of data diversity and reference perfusion accuracy. Reference perfusion was estimated by tracer kinetic model fitting initialized with multiple values (multigrid model fitting). Result: The NN method was much faster than tracer kinetic model fitting. To generate a perfusion map of matrix 128 × 128 on a same computer, multigrid model fitting took about 80 min, single-grid or regular model fitting about 3 min, while the NN method took about 1 s. Compared to the reference values, NN trained with a diverse group gave estimates with mean absolute error (MAE) of 15.9 ml/min/100g and correlation coefficient (R) of 0.949, significantly more accurate than regular model fitting (MAE 22.3 ml/min/100g, R 0.889, p < .001). Conclusion: the NN method enables rapid perfusion mapping, and if properly trained, estimates perfusion with accuracy comparable to multigrid model fitting.

Associations between histogram analysis parameters derived from dynamic-contrast enhanced MRI and PD L1-expression in head and neck squamous cell carcinomas. A preliminary study

PURPOSE

Programmed death 1 ligand (PD-L 1) plays an essential role in oncology. It might be crucial to predict its expression non-invasively by imaging. Dynamic-contrast enhanced MRI (DCE MRI) is one of the important imaging modalities in head and neck squamous cell cancer (HNSCC). The aim of the present study was to analyze possible associations between histogram analysis parameters of DCE MRI and PD-L 1 expression in HNSCC METHODS: Overall, 26 patients with primary HNSCC of different localizations were involved in the study. DCE MRI was obtained on a 3 T MRI and analyzed with a whole lesion measurement using a histogram approach. PD-L 1 expression was estimated on bioptic samples before any form of treatment using 3 scores (Tumor positive score (TPS), Immune cell score (ICS) and Combined positive score (CPS)).

RESULTS

CPS correlated with mode derived from Ktrans (r = 0.40, p = .04). Also CPS correlated with P90 derived from Kep (r = 0.40, p = .04). ICS correlated with the maximum derived from Kep (r = 0.41, p = .03) and entropy derived from Kep (r = 0.43, p = .02). There were no associations between DCE MRI parameters and TPS.

CONCLUSION

Ktrans and Kep related histogram analysis parameters derived from DCE MRI correlated moderately with PD-L 1 expression of immune cells in HNSCC.

Technical Improvements in Head and Neck MR Imaging: At the Cutting Edge

Head and neck MR imaging is technically challenging because of magnetic field inhomogeneity, respiratory and swallowing motion, and necessity of high-resolution imaging to trace key anatomic structures. These challenges have been answered by advances in MR imaging technology, including isovolumetric three-dimensional imaging, robust fat-water separation techniques, and novel deep learning-based reconstruction algorithms. New applications of MR imaging have been advanced and functional imaging has been improved. Improvements in acquisition and reconstruction technique facilitate novel applications of morphologic and functional imaging. This results in opportunities to improve diagnosis, staging, and treatment selection through application of advanced MR imaging techniques.

Nasopharyngeal carcinoma perfusion MRI: Comparison of arterial spin labeling and dynamic contrast-enhanced MRI

To investigate the feasibility of 3D arterial spin labeling (ASL) as an alternative to dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for the qualitative and quantitative evaluation of nasopharyngeal carcinoma (NPC) perfusion.Fifty-two newly diagnosed NPC patients underwent 3D ASL and DCE-MRI scans on a 3.0-T MRI system. The visual qualitative evaluation of the NPC perfusion level was scored from 0 to 3 (0 = no contrast to normal peripheral soft tissue, 3 = pronounced contrast to normal peripheral soft tissue). The visual evaluation of the NPC outline was scored from 0 to 2 (0 = very vague outline, 2 = clear outline). Comparisons of the ASL-derived blood flow (BF) with the DCE-MRI-derived positive enhancement integral, maximum slope of increase, maximum slope of decrease, and time to peak (TTP) were conducted between NPC and non-NPC areas with independent samples t-tests. The diagnostic performance of these parameters was assessed by receiver operating characteristic curve analysis. The correlations between ASL BF and DCE parameters were assessed by Spearman correlation analysis.There was no difference in the visual scores of the NPC perfusion level between the 2 perfusion methods (P= .963). ASL had a lower visual score for describing the outline of NPC than DCE-MRI (P < .001). The ASL and DCE parameters of the NPC areas were significantly different from those of the non-NPC areas (P < .001). The ASL BF showed the largest area under the receiver operating characteristic curve (AUC) of 0.936 for identifying NPC. When all NPC and non-NPC areas were taken into account, significant correlations were observed between the ASL BF and the DCE parameters positive enhancement integral (r = 0.503, P < .001), maximum slope of increase (r = 0.616, P < .001), maximum slope of decrease (r = 0.380, P < .001), and TTP (r = -0.601, P < .001).3D ASL could reveal the hyperperfusion of NPC in a qualitative and quantitative manner without using contrast agent. Additionally, the ASL BF correlated significantly with the semiquantitative DCE-MRI parameters.

Does multiparametric imaging with 18F-FDG-PET/MRI capture spatial variation in immunohistochemical cancer biomarkers in head and neck squamous cell carcinoma?

Background

The purpose of this study is to test if functional multiparametric imaging with ¹⁸F-FDG-PET/MRI correlates spatially with immunohistochemical biomarker status within a lesion of head and neck squamous cell carcinoma (HNSCC), and also whether a biopsy with the highest FDG uptake was more likely to have the highest PD-L1 expression or the highest percentage of vital tumour cells (VTC) compared with a random biopsy.

Methods

Thirty-one patients with HNSCC were scanned on an integrated PET/MRI scanner with FDG prior to surgery in this prospective study. Imaging was quantified with SUV, ADC and K^trans. A 3D-morphometric MRI scan of the specimen was used to co-register the patient and the specimen scans. All specimens were sectioned in consecutive slices, and slices from six different locations were selected randomly from each tumour. Core biopsies were performed to construct TMA blocks for IHC staining with the ten predefined biomarkers. The spatial correlation was assessed with a partial correlation analysis.

Results

Twenty-eight patients with a total of 33 lesions were eligible for further analysis. There were significant correlations between the three imaging biomarkers and some of the IHC biomarkers. Moreover, a biopsy taken from the most FDG-avid part of the tumour did not have a statistically significantly higher probability of higher PD-L1 expression or VTC, compared with a random biopsy.

Conclusion

We found statistically significant correlations between functional imaging parameters and key molecular cancer markers.

Quantification of heterogeneity to classify benign parotid tumors: a feasibility study on most frequent histotypes

Aim: To differentiate Warthin tumors (WTs) and pleomorphic adenomas (PAs) measuring heterogeneity of intravoxel incoherent motion (IVIM) and dynamic-contrast enhanced-magnetic resonance imaging biomarkers. Methods: Volumes of interest were traced on 18 WT and 18 PA in 25 patients. For each IVIM and dynamic-contrast enhanced biomarker, histogram parameters were calculated and then compared using the Wilcoxon-signed-rank test. Receiver operating characteristic curves and multivariate analysis were employed to identify the parameters and their pairs with the best accuracy. Results: Most of the biomarkers exhibited significant difference (p < 0.05) between PA and WT for histogram parameters. Time to peak median and skewness, and D* median and entropy showed the highest area under the curve. No meaningful improvement of accuracy was obtained using two features. Conclusion: IVIM and dynamic-contrast enhanced histogram descriptors may help in the classification of WT and PA.

Patient‑derived orthotopic xenograft glioma models fail to replicate the magnetic resonance imaging features of the original patient tumor

Patient-derived orthotopic glioma xenograft models are important platforms used for pre-clinical research of glioma. In the present study, the diagnostic ability of magnetic resonance imaging (MRI) was examined with regard to the identification of biomarkers obtained from patient-derived glioma xenografts and human tumors. Conventional MRI, diffusion weighted imaging and dynamic contrast-enhanced (DCE)-MRI were used to analyze seven pairs of high grade gliomas with their corresponding xenografts obtained from non-obese diabetic-severe-combined immunodeficiency nude mice. Tumor samples were collected for transcriptome sequencing and histopathological staining, and differentially expressed genes were screened between the original tumors and the corresponding xenografts. Gene Ontology (GO) analysis was performed to predict the functions of these genes. In 6 cases of xenografts with diffuse growth, the degree of enhancement was significantly lower compared with the original tumors. Histopathological staining indicated that the microvascular area and microvascular diameter of the xenografts were significantly lower compared with the original tumors (P=0.009 and P=0.007, respectively). In one case, there was evidence of nodular tumor growth in the mouse. Both MRI and histopathological staining showed a clear demarcation between the transplanted tumors and the normal brain tissues. The relative apparent diffusion coefficient values of the 7 cases examined were significantly higher compared with the corresponding original tumors (P=0.001) and transfer coefficient values derived from DCE-MRI of the tumor area was significantly lower compared with the original tumors (P=0.016). GO analysis indicated that the expression levels of extracellular matrix-associated genes, angiogenesis-associated genes and immune function-associated genes in the original tumors were higher compared with the corresponding xenografts. In conclusion, the data demonstrated that the MRI features of patient-derived xenograft glioma models in mice were different compared with those of the original patient tumors. Differential gene expression may underlie the differences noted in the MRI features between original tumors and corresponding xenografts. The results of the present study highlight the precautions that should be taken when extrapolating data from patient-derived xenograft studies, and their applicability to humans.

Tumor segmentation analysis at different post-contrast time points: A possible source of variability of quantitative DCE-MRI parameters in locally advanced breast cancer

PURPOSE

to assess if tumor segmentation analysis performed at different post-contrast time points (TPs) on dynamic images could influence the extraction of dynamic contrast enhanced (DCE)-MRI parameters in locally advanced breast cancer (LABC), and potentially represent a source of variability.

METHOD

forty patients with forty-two LABC lesions were prospectively enrolled and underwent breast DCE-MRI examination at 3 T. On post-processed dynamic images, enhancing tumor lesions were manually segmented at four different TPs: at the first post-contrast dynamic image in which the lesion was appreciable (TP 1) and at 1, 5 and 10 min after contrast-agent administration (TPs 2, 3 and 4, respectively) and corresponding DCE-MRI parameters were extracted. Friedman's test followed by Bonferroni-adjusted Wilcoxon signed rank test for post-hoc analysis was used to compare DCE-MRI parameters. Intra- and inter-observer reliability of DCE-MRI parameters measurements was assessed using the Intraclass Correlation Coefficient (ICC) analysis.

RESULTS

Ktrans, Kep and iAUC were significantly higher when extracted from ROIs placed at TP1 and progressively decreased from TP 2-4. The intra-observer reliability ranged from good to excellent (ICC's: 0.894 to 0.990). The inter-observer reliability varied from moderate to excellent (0.770 to 0.942). The inter-observer reliability was significantly higher for Ktrans and Kep extracted at TPs1 and 2 as compared to TPs 3 and 4.

CONCLUSIONS

A significant variability of DCE-MRI quantitative parameters occurs when tumor segmentation is performed at different TPs. We suggest to performing tumor delineation at an established TP, preferably the earliest, in order to extract reliable and comparable DCE-MRI data.

Textural features on 18F-FDG PET/CT and dynamic contrast-enhanced MR imaging for predicting treatment response and survival of patients with hypopharyngeal carcinoma

The utility of multimodality molecular imaging for predicting treatment response and survival of patients with hypopharyngeal carcinoma remains unclear. Here, we sought to investigate whether the combination of different molecular imaging parameters may improve outcome prediction in this patient group.Patients with pathologically proven hypopharyngeal carcinoma scheduled to undergo chemoradiotherapy (CRT) were deemed eligible. Besides clinical data, parameters obtained from pretreatment 2-deoxy-2-[fluorine-18]fluoro-D-glucose positron emission tomography/computed tomography (F-FDG PET/CT), dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), and diffusion-weighted MRI were analyzed in relation to treatment response, recurrence-free survival (RFS), and overall survival (OS).A total of 61 patients with advanced-stage disease were examined. After CRT, 36% of the patients did not achieve a complete response. Total lesion glycolysis (TLG) and texture feature entropy were found to predict treatment response. The transfer constant (K), TLG, and entropy were associated with RFS, whereas K, blood plasma volume (Vp), standardized uptake value (SUV), and entropy were predictors of OS. Different scoring systems based on the sum of PET- or MRI-derived prognosticators enabled patient stratification into distinct prognostic groups (P <.0001). The complete response rate of patients with a score of 2 was significantly lower than those of patients with a score 1 or 0 (14.7% vs 58.9% vs 75.7%, respectively, P = .007, respectively). The combination of PET- and DCE-MRI-derived independent risk factors allowed a better survival stratification than the TNM staging system (P <.0001 vs .691, respectively).Texture features on F-FDG PET/CT and DCE-MRI are clinically useful to predict treatment response and survival in patients with hypopharyngeal carcinoma. Their combined use in prognostic scoring systems may help these patients benefit from tailored treatment and obtain better oncological results.

Magnetic resonance features of sinonasal melanotic mucosal melanoma

A 67-year-old man presented to ear, nose and throat department complaining of nasal congestion and recurrent epistaxis for 5 months. Nasal endoscopy revealed a pigmented polyp obstructing the right nasal cavity. MRI with contrast agent showed a right nasal cavity polypoid mass with hyper signal intensity (SI) both in non-enhanced T1-w and diffusion imaging, marked hypo SI in T2-w sequences and avidly contrast enhancement characterised by rapid wash-in without significant wash-out on dynamic perfusion imaging. Histological specimen showed epithelioid and spindle cells with focal intense pigmentations and immunohistochemical features compatible with primary melanotic sinonasal mucosal melanoma (SNM). As melanotic SNM shows MRI pathognomonic high non-enhanced T1-w SI, this case underlines the crucial role of MRI not only in assessing the local tumour extension/recurrence but also in increasing the diagnostic confidence of detecting melanotic SNM. Thus, MRI should be always performed in case of clinical-endoscopic suspicion of SNM.

Individualized survival prediction for patients with oropharyngeal cancer in the human papillomavirus era

BACKGROUND

Accurate, individualized prognostication in patients with oropharyngeal squamous cell carcinoma (OPSCC) is vital for patient counseling and treatment decision making. With the emergence of human papillomavirus (HPV) as an important biomarker in OPSCC, calculators incorporating this variable have been developed. However, it is critical to characterize their accuracy prior to implementation.

METHODS

Four OPSCC calculators were identified that integrate HPV into their estimation of 5-year overall survival. Treatment outcomes for 856 patients with OPSCC who were evaluated at a single institution from 2003 through 2016 were analyzed. Predicted survival probabilities were generated for each patient using each calculator. Calculator performance was assessed and compared using Kaplan-Meier plots, receiver operating characteristic curves, concordance statistics, and calibration plots.

RESULTS

Correlation between pairs of calculators varied, with coefficients ranging from 0.63 to 0.90. Only 3 of 6 pairs of calculators yielded predictions within 10% of each other for at least 50% of patients. Kaplan-Meier curves of calculator-defined risk groups demonstrated reasonable stratification. Areas under the receiver operating characteristic curve ranged from 0.74 to 0.80, and concordance statistics ranged from 0.71 to 0.78. Each calculator demonstrated superior discriminatory ability compared with clinical staging according to the seventh and eighth editions of the American Joint Committee on Cancer staging manual. Among models, the Denmark calculator was found to be best calibrated to observed outcomes.

CONCLUSIONS

Existing calculators exhibited reasonable estimation of survival in patients with OPSCC, but there was considerable variability in predictions for individual patients, which limits the clinical usefulness of these calculators. Given the increasing role of personalized treatment in patients with OPSCC, further work is needed to improve accuracy and precision, possibly through the identification and incorporation of additional biomarkers.

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.

Histogram analysis parameters of dynamic contrast-enhanced magnetic resonance imaging can predict histopathological findings including proliferation potential, cellularity, and nucleic areas in head and neck squamous cell carcinoma

Our purpose was to analyze possible associations between histogram analysis parameters of dynamic contrast-enhanced magnetic resonance imaging DCE MRI and histopathological findings like proliferation index, cell count and nucleic areas in head and neck squamous cell carcinoma (HNSCC).

30 patients (mean age 57.0 years) with primary HNSCC were included in the study. In every case, histogram analysis parameters of K_trans, V_e, and K_ep were estimated using a mathlab based software. Tumor proliferation index, cell count, and nucleic areas were estimated on Ki 67 antigen stained specimens. Spearman's non-parametric rank sum correlation coefficients were calculated between DCE and different histopathological parameters.

KI 67 correlated with K_trans min (p = −0.386, P = 0.043) and s K_trans skewness (p = 0.382, P = 0.045), V_e min (p = −0.473, P = 0.011), Ve entropy (p = 0.424, P = 0.025), and K_ep entropy (p = 0.464, P = 0.013). Cell count correlated with K_trans kurtosis (p = 0.40, P = 0.034), V_e entropy (p = 0.475, P = 0.011). Total nucleic area correlated with V_e max (p = 0.386, P = 0.042) and V_e entropy (p = 0.411, P = 0.030).

In G1/2 tumors, only K_trans entropy correlated well with total (P =0.78, P =0.013) and average nucleic areas (p = 0.655, P = 0.006). In G3 tumors, KI 67 correlated with Ve min (p = −0.552, P = 0.022) and V_e entropy (p = 0.524, P = 0.031). Ve max correlated with total nucleic area (p = 0.483, P = 0.049). Kep max correlated with total area (p = −0.51, P = 0.037), and K_ep entropy with KI 67 (p = 0.567, P = 0.018).

We concluded that histogram-based parameters skewness, kurtosis and entropy of K_trans, V_e, and K_ep can be used as markers for proliferation activity, cellularity and nucleic content in HNSCC. Tumor grading influences significantly associations between perfusion and histopathological parameters.

Dynamic contrast-enhanced magnetic resonance imaging for head and neck cancers

Dynamic myraidpro contrast-enhanced magnetic resonance imaging (DCE-MRI) has been correlated with prognosis in head and neck squamous cell carcinoma as well as with changes in normal tissues. These studies implement different software, either commercial or in-house, and different scan protocols. Thus, the generalizability of the results is not confirmed. To assist in the standardization of quantitative metrics to confirm the generalizability of these previous studies, this data descriptor delineates in detail the DCE-MRI digital imaging and communications in medicine (DICOM) files with DICOM radiation therapy (RT) structure sets and digital reference objects (DROs), as well as, relevant clinical data that encompass a data set that can be used by all software for comparing quantitative metrics. Variable flip angle (VFA) with six flip angles and DCE-MRI scans with a temporal resolution of 5.5 s were acquired in the axial direction on a 3T MR scanner with a field of view of 25.6 cm, slice thickness of 4 mm, and 256×256 matrix size.

A multiparametric analysis combining DCE-MRI- and IVIM -derived parameters to improve differentiation of parotid tumors: a pilot study

AIM

To evaluate dynamic contrast-enhanced (DCE)-MRI and diffusion weighted (DW)-MRI diagnostic value to differentiate Warthin tumors (WT) by pleomorphic adenomas (PA).

MATERIALS & METHODS

Seven WT and seven PA were examined. DCE- and  DW-MRI parameters were extracted from volumes of interest; volume of interest-based averages and standard deviations were calculated. Statistical analysis included: linear discriminant analysis, receiver operating characteristic curves, sensitivity and specificity.

RESULTS

No single feature was able to differentiate WT by PA (p > 0.05); linear discriminant analysis analysis showed that a combination of all features or combinations of feature pairs (namely: K^trans(std) & f(std), K^trans(std) & D(std), k_ep(std) & D(std), MRE(av) & TTP(av)) might achieve sensitivity (SENS), specificity (SPEC) = 100%, with a slight reduction after cross-validation analysis (SENS = 0.875; SPEC = 1).

CONCLUSION

Although preliminary and not conclusive, our results suggest that differentiation between WT and PA is possible through a multiparametric approach based on combination of DCE- and DW-MRI parameters.

Aberrant glioblastoma neovascularization patterns and their correlation with DCE-MRI-derived parameters following temozolomide and bevacizumab treatment

Glioblastoma (GBM) is a highly angiogenic malignancy, and its abundant, aberrant neovascularization is closely related to the proliferation and invasion of tumor cells. However, anti-angiogenesis combined with standard radio-/chemo-therapy produces little improvement in treatment outcomes. Determining the reason for treatment failure is pivotal for GBM treatment. Here, histopathological analysis and dynamic contrast-enhanced MRI (DCE-MRI) were used to explore the effects of temozolomide (TMZ) and bevacizumab (BEV) on GBM neovascularization patterns in an orthotopic U87MG mouse model at 1, 3 and 6 days after treatment. We found that the amount of vascular mimicry (VM) significantly increased 6 days after BEV treatment. TMZ inhibited neovascularization at an early stage, but the microvessel density (MVD) and transfer coefficient (Ktrans) derived from DCE-MRI increased 6 days after treatment. TMZ and BEV combination therapy slightly prolonged the inhibitory effect on tumor microvessels. Sprouting angiogenesis was positively correlated with Ktrans in all treatment groups. The increase in VM after BEV administration and the increase in MVD and Ktrans after TMZ administration may be responsible for treatment resistance. Ktrans holds great potential as an imaging biomarker for indicating the variation in sprouting angiogenesis during drug treatment for GBM.

A Multi-Institutional Comparison of Dynamic Contrast-Enhanced Magnetic Resonance Imaging Parameter Calculations

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provides quantitative metrics (e.g. K^trans, v_e) via pharmacokinetic models. We tested inter-algorithm variability in these quantitative metrics with 11 published DCE-MRI algorithms, all implementing Tofts-Kermode or extended Tofts pharmacokinetic models. Digital reference objects (DROs) with known K^trans and v_e values were used to assess performance at varying noise levels. Additionally, DCE-MRI data from 15 head and neck squamous cell carcinoma patients over 3 time-points during chemoradiotherapy were used to ascertain K^trans and v_e kinetic trends across algorithms. Algorithms performed well (less than 3% average error) when no noise was present in the DRO. With noise, 87% of K^trans and 84% of v_e algorithm-DRO combinations were generally in the correct order. Low Krippendorff’s alpha values showed that algorithms could not consistently classify patients as above or below the median for a given algorithm at each time point or for differences in values between time points. A majority of the algorithms produced a significant Spearman correlation in v_e of the primary gross tumor volume with time. Algorithmic differences in K^trans and v_e values over time indicate limitations in combining/comparing data from distinct DCE-MRI model implementations. Careful cross-algorithm quality-assurance must be utilized as DCE-MRI results may not be interpretable using differing software.

Accuracy of deformable image registration on magnetic resonance images in digital and physical phantoms

PURPOSE

Accurate deformable image registration is necessary for longitudinal studies. The error associated with commercial systems has been evaluated using computed tomography (CT). Several in-house algorithms have been evaluated for use with magnetic resonance imaging (MRI), but there is still relatively little information about MRI deformable image registration. This work presents an evaluation of two deformable image registration systems, one commercial (Velocity) and one in-house (demons-based algorithm), with MRI using two different metrics to quantify the registration error.

METHODS

The registration error was analyzed with synthetic MR images. These images were generated from interpatient and intrapatient variation models trained on 28 patients. Four synthetic post-treatment images were generated for each of four synthetic pretreatment images, resulting in 16 image registrations for both the T1- and T2-weighted images. The synthetic post-treatment images were registered to their corresponding synthetic pretreatment image. The registration error was calculated between the known deformation vector field and the generated deformation vector field from the image registration system. The registration error was also analyzed using a porcine phantom with ten implanted 0.35-mm diameter gold markers. The markers were visible on CT but not MRI. CT, T1-weighted MR, and T2-weighted MR images were taken in four different positions. The markers were contoured on the CT images and rigidly registered to their corresponding MR images. The MR images were deformably registered and the distance between the projected marker location and true marker location was measured as the registration error.

RESULTS

The synthetic images were evaluated only on Velocity. Root mean square errors (RMSEs) of 0.76 mm in the left-right (LR) direction, 0.76 mm in the anteroposterior (AP) direction, and 0.69 mm in the superior-inferior (SI) direction were observed for the T1-weighted MR images. RMSEs of 1.1 mm in the LR direction, 0.75 mm in the AP direction, and 0.81 mm in the SI direction were observed for the T2-weighted MR images. The porcine phantom MR images, when evaluated with Velocity, had RMSEs of 1.8, 1.5, and 2.7 mm in the LR, AP, and SI directions for the T1-weighted images and 1.3, 1.2, and 1.6 mm in the LR, AP, and SI directions for the T2-weighted images. When the porcine phantom images were evaluated with the in-house demons-based algorithm, RMSEs were 1.2, 1.5, and 2.1 mm in the LR, AP, and SI directions for the T1-weighted images and 0.81, 1.1, and 1.1 mm in the LR, AP, and SI directions for the T2-weighted images.

CONCLUSIONS

The MRI registration error was low for both Velocity and the in-house demons-based algorithm according to both image evaluation methods, with all RMSEs below 3 mm. This implies that both image registration systems can be used for longitudinal studies using MRI.

Meta-analysis of magnetic resonance imaging accuracy for diagnosis of oral cancer

Objective

To establish the diagnostic accuracy of magnetic resonance imaging (MRI) as an auxiliary means for the diagnosis of oral cancer through a systematic review and meta-analysis.

Methods

An exhaustive search of publications from 1986 to 2016 was performed of Medline, Embase and Cochrane (and related databases), including grey literature. Primary diagnostic accuracy studies that assessed oral cancer (target condition) using MRI (index test) were included. Diagnostic threshold, sensitivity and meta-regression analyses were performed. A meta-analysis was performed using Meta-DiSc® v. 1.4 software.

Results

A total of 24 primary studies were assessed, comprising 1,403 oral cancer lesions. Nine studies used diffusion-weighted MRI, with a diagnostic odds ratio (DOR) of 30.7 (95% confidence interval [CI]: 12.7–74.3) and area under the curve (AUC) of 0.917 (95% CI: 0.915–0.918); seven studies used dynamic contrast-enhanced MRI, with a DOR of 48.1 (95%CI: 22.4–103.2) and AUC of 0.936 (95% CI: 0.934–0.937); and 13 studies used traditional MRI, with a DOR of 23.9 (95%CI: 13.2–43.3) and AUC of 0.894 (95% CI: 0.894–0.895). Meta-regression analysis indicated that the magnetic field strength may have influenced the heterogeneity of the results obtained (p = 0.0233) using traditional MRI. Sensitivity analysis revealed a discrete reduction of inconsistency in some subgroups.

Conclusion

The three types of MRI assessed exhibited satisfactory accuracy compared to biopsy. Considering the relevance of early treatment and screening and that better health care results in improved survival rates and quality of life for oral cancer patients, we suggest the use of MRI as a part of the pre-treatment and monitoring protocol at public health services.

Comparison of DCE-MRI kinetic parameters and FMISO-PET uptake parameters in head and neck cancer patients

Purpose

Tumor hypoxia is a major cause of radiation resistance, often present in various solid tumors. Dynamic [¹⁸F]‐fluoromisonidazole (FMISO) PET imaging is able to reliably assess tumor hypoxia. Comprehensive characterization of tumor microenvironment through FMISO‐PET and dynamic contrast enhanced (DCE) MR multimodality imaging might be a valuable alternative to the dynamic FMISO‐PET acquisition. The aim of this work was to explore the correlation between the FMISO‐PET and DCE‐MRI kinetic parameters.

Methods

This study was done on head and neck cancer patients (N = 6), who were imaged dynamically with FMISO‐PET and DCE‐MRI on the same day. Images were registered and analyzed for kinetics on a voxel basis. FMISO‐PET images were analyzed with the two‐tissue compartment three rate‐constant model. Additionally, tumor‐to‐muscle ratio (TMR) maps were evaluated. DCE‐MRI was analyzed with the extended Tofts model. Voxel‐wise Pearson's coefficients were calculated for each patient to assess pairwise parameter correlations.

Results

Median correlations between FMISO uptake parameters and DCE‐MRI kinetic parameters varied across the parameter pairs in the range from −0.05 to 0.71. The highest median correlation of r = 0.71 was observed for the pair V_b−v_p, while the K₁−K^trans median correlation was r = 0.45. Median correlation coefficients for the K₁−v_p and the K_i−K^trans pairs were r = 0.42 and r = 0.32, respectively. Correlations between FMISO uptake rate parameter K_i and DCE‐MRI kinetic parameters varied substantially across the patients, whereas correlations between the FMISO and DCE‐MRI vascular parameters were consistently high. Median TMR‐K₁ and TMR‐K^trans correlations were r = 0.52 and r = 0.46, respectively, but varied substantially across the patients.

Conclusions

Based on this clinical evidence, we can conclude that the vascular fraction parameters obtained through DCE‐MRI kinetic analysis or FMISO kinetic analysis measure the same biological property, while other kinetic parameters are unrelated. These results might be useful in the design of future clinical trials involving FMISO‐PET/DCE‐MR multimodality imaging for the assessment of tumor microenvironment.

The emerging potential of magnetic resonance imaging in personalizing radiotherapy for head and neck cancer: an oncologist's perspective

Head and neck cancer (HNC) is a challenging tumour site for radiotherapy delivery owing to its complex anatomy and proximity to organs at risk (OARs) such as the spinal cord and optic apparatus. Despite significant advances in radiotherapy planning techniques, radiation-induced morbidities remain substantial. Further improvement would require high-quality imaging and tailored radiotherapy based on intratreatment response. For these reasons, the use of MRI in radiotherapy planning for HNC is rapidly gaining popularity. MRI provides superior soft-tissue contrast in comparison with CT, allowing better definition of the tumour and OARs. The lack of additional radiation exposure is another attractive feature for intratreatment monitoring. In addition, advanced MRI techniques such as diffusion-weighted, dynamic contrast-enhanced and intrinsic susceptibility-weighted MRI techniques are capable of characterizing tumour biology further by providing quantitative functional parameters such as tissue cellularity, vascular permeability/perfusion and hypoxia. These functional parameters are known to have radiobiological relevance, which potentially could guide treatment adaptation based on their changes prior to or during radiotherapy. In this article, we first present an overview of the applications of anatomical MRI sequences in head and neck radiotherapy, followed by the potentials and limitations of functional MRI sequences in personalizing therapy.

Contemporary Diagnostic Imaging of Oral Squamous Cell Carcinoma - A Review of Literature

Oral squamous cell carcinoma (OSCC) is the most common cancer of the oral cavity and constitutes 95% of all cancers of this area. Men are affected twice as commonly as women, primarily if they are over 50 years of age. Forty percent of the lesions are localized in the tongue and 30% in the floor of the oral cavity. OSCC often affects upper and lower gingiva, buccal mucous membrane, the retromolar triangle and the palate. The prognosis is poor and the five-year survival rate ranges from 20% (OSCC in the floor of the mouth) to 60% (OSCC in the alveolar part of the mandible). Treatment is difficult, because of the localization and the invasiveness of the available methods. The diagnosis is made based on a histopathological examination of a biopsy sample.

The low detection rate of early oral SCC is a considerable clinical issue. Although the oral cavity can be easily examined, in the majority of cases oral SCC is diagnosed in its late stages. It is difficult to diagnose metastases in local lymph nodes and distant organs, which is important for planning the scope of resection and further treatment, graft implantation, and differentiation between reactive and metastatic lymph nodes as well as between disease recurrence and scars or adverse reactions after surgery or radiation therapy.

Imaging studies are performed as part of the routine work-up in oral SCC. However, it is difficult to interpret the results at the early stages of the disease. The following imaging methods are used – dental radiographs, panoramic radiographs, magnetic resonance imaging with diffusion-weighted and dynamic sequences, perfusion computed tomography, cone beam computed tomography, single-photon emission computed tomography, hybrid methods (PET/CT, PET/MRI, SPECT/CT) and ultrasound. Some important clinical problems can be resolved with the use of novel modalities such as MRI with ADC sequences and PET.

The aim of this article is to describe oral squamous cell carcinoma as it appears in different imaging methods considering both their advantages and limitations.

Dynamic contrast enhanced MRI detects changes in vascular transport rate constants following treatment with thermally-sensitive liposomal doxorubicin

Temperature-sensitive liposomal formulations of chemotherapeutics, such as doxorubicin, can achieve locally high drug concentrations within a tumor and tumor vasculature while maintaining low systemic toxicity. Further, doxorubicin delivery by temperature-sensitive liposomes can reliably cure local cancer in mouse models. Histological sections of treated tumors have detected red blood cell extravasation within tumors treated with temperature-sensitive doxorubicin and ultrasound hyperthermia. We hypothesize that the local release of drug into the tumor vasculature and resulting high drug concentration can alter vascular transport rate constants along with having direct tumoricidal effects. Dynamic contrast enhanced MRI (DCE-MRI) coupled with a pharmacokinetic model can detect and quantify changes in such vascular transport rate constants. Here, we set out to determine whether changes in rate constants resulting from intravascular drug release were detectable by MRI. We found that the accumulation of gadoteridol was enhanced in tumors treated with temperature-sensitive liposomal doxorubicin and ultrasound hyperthermia. While the initial uptake rate of the small molecule tracer was slower (k₁=0.0478±0.011s^-1 versus 0.116±0.047s^-1) in treated compared to untreated tumors, the tracer was retained after treatment due to a larger reduction in the rate of clearance (k₂=0.291±0.030s^-1 versus 0.747±0.24s^-1). While DCE-MRI assesses a combination of blood flow and permeability, ultrasound imaging of microvascular flow rate is sensitive only to changes in vascular flow rate; based on this technique, blood flow was not significantly altered 30min after treatment. In summary, DCE-MRI provides a means to detect changes that are associated with treatment by thermally-activated particles and such changes can be exploited to enhance local delivery.

Quantitative magnetic resonance imaging biomarkers in oncological clinical trials: Current techniques and standardization challenges

Radiological imaging plays an important role in oncological trials to provide imaging biomarkers for disease staging, stratifying patients, defining dose setting, and evaluating the safety and efficacy of new candidate drugs and innovative treatment. This paper reviews the techniques of most commonly used quantitative magnetic resonance imaging (qMRI) biomarkers (dynamic contrast enhanced, dynamic susceptibility contrast, and diffusion weighted imaging) and their applications in oncological trials. Challenges of incorporating qMRI biomarkers in oncological trials are discussed including understanding biological mechanisms revealed by MRI biomarkers, consideration of rigorous trial design and standardized implementation of qMRI protocols.