Functional MRI for the prediction of treatment response in head and neck squamous cell carcinoma: potential and limitations

Utility of Echo Planar Imaging With Compressed Sensing-Sensitivity Encoding (EPICS) for the Evaluation of the Head and Neck Region

Purpose This study aimed to compare the image quality between echo planar imaging (EPI) with compressed sensing-sensitivity encoding (EPICS)-based diffusion-weighted imaging (DWI) and conventional parallel imaging (PI)-based DWI of the head and neck. Materials and methods Ten healthy volunteers participated in this study. EPICS-DWI was acquired based on an axial spin-echo EPI sequence with EPICS acceleration factors of 2, 3, and 4, respectively. Conventional PI-DWI was acquired using the same acceleration factors (i.e., 2, 3, and 4). Quantitative assessment was performed by measuring the signal-to-noise ratio (SNR) and apparent diffusion coefficient (ADC) in a circular region of interest (ROI) on the parotid and submandibular glands. For qualitative evaluation, a three-point visual grading system was used to assess the (1) overall image quality and (2) degree of image distortion. Results In the quantitative assessment, the SNR of the parotid gland in EPICS-DWI was significantly higher than that of PI-DWI in acceleration factors of 3 and 4 (p<0.05). In a comparison of ADC values, significant differences were not observed between EPICS-DWI and PI-DWI. In the qualitative assessment, the overall image quality of EPICS-DWI was significantly higher than that of PI-DWI for acceleration factors 3 and 4 (p<0.05). The degree of image distortion was significantly larger in EPICS-DWI with an acceleration factor of 2 than that of 3 or 4 (p<0.01, respectively). Conclusion Under the appropriate parameter setting, EPICS-DWI demonstrated higher SNR and better overall image quality for head and neck imaging than PI-DWI, without increasing image distortion.

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.

Improvement of image quality in diffusion-weighted imaging with model-based deep learning reconstruction for evaluations of the head and neck

OBJECTIVES

To investigate the utility of deep learning (DL)-based image reconstruction using a model-based approach in head and neck diffusion-weighted imaging (DWI).

MATERIALS AND METHODS

We retrospectively analyzed the cases of 41 patients who underwent head/neck DWI. The DWI in 25 patients demonstrated an untreated lesion. We performed qualitative and quantitative assessments in the DWI analyses with both deep learning (DL)- and conventional parallel imaging (PI)-based reconstructions. For the qualitative assessment, we visually evaluated the overall image quality, soft tissue conspicuity, degree of artifact(s), and lesion conspicuity based on a five-point system. In the quantitative assessment, we measured the signal-to-noise ratio (SNR) of the bilateral parotid glands, submandibular gland, the posterior muscle, and the lesion. We then calculated the contrast-to-noise ratio (CNR) between the lesion and the adjacent muscle.

RESULTS

Significant differences were observed in the qualitative analysis between the DWI with PI-based and DL-based reconstructions for all of the evaluation items (p < 0.001). In the quantitative analysis, significant differences in the SNR and CNR between the DWI with PI-based and DL-based reconstructions were observed for all of the evaluation items (p = 0.002 ~ p < 0.001).

DISCUSSION

DL-based image reconstruction with the model-based technique effectively provided sufficient image quality in head/neck DWI.

Current State of Artificial Intelligence in Clinical Applications for Head and Neck MR Imaging

Due primarily to the excellent soft tissue contrast depictions provided by MRI, the widespread application of head and neck MRI in clinical practice serves to assess various diseases. Artificial intelligence (AI)-based methodologies, particularly deep learning analyses using convolutional neural networks, have recently gained global recognition and have been extensively investigated in clinical research for their applicability across a range of categories within medical imaging, including head and neck MRI. Analytical approaches using AI have shown potential for addressing the clinical limitations associated with head and neck MRI. In this review, we focus primarily on the technical advancements in deep-learning-based methodologies and their clinical utility within the field of head and neck MRI, encompassing aspects such as image acquisition and reconstruction, lesion segmentation, disease classification and diagnosis, and prognostic prediction for patients presenting with head and neck diseases. We then discuss the limitations of current deep-learning-based approaches and offer insights regarding future challenges in this field.

Prospective validation of diffusion-weighted MRI as a biomarker of tumor response and oncologic outcomes in head and neck cancer: Results from an observational biomarker pre-qualification study

PURPOSE

To determine DWI parameters associated with tumor response and oncologic outcomes in head and neck (HNC) patients treated with radiotherapy (RT).

METHODS

HNC patients in a prospective study were included. Patients had MRIs pre-, mid-, and post-RT completion. We used T2-weighted sequences for tumor segmentation which were co-registered to respective DWIs for extraction of apparent diffusion coefficient (ADC) measurements. Treatment response was assessed at mid- and post-RT and was defined as: complete response (CR) vs. non-complete response (non-CR). The Mann-Whitney U test was used to compare ADC between CR and non-CR. Recursive partitioning analysis (RPA) was performed to identify ADC threshold associated with relapse. Cox proportional hazards models were done for clinical vs. clinical and imaging parameters and internal validation was done using bootstrapping technique.

RESULTS

Eighty-one patients were included. Median follow-up was 31 months. For patients with post-RT CR, there was a significant increase in mean ADC at mid-RT compared to baseline ((1.8 ± 0.29) × 10-3 mm2/s vs. (1.37 ± 0.22) × 10-3 mm2/s, p < 0.0001), while patients with non-CR had no significant increase (p > 0.05). RPA identified GTV-P delta (Δ)ADCmean < 7% at mid-RT as the most significant parameter associated with worse LC and RFS (p = 0.01). Uni- and multi-variable analysis showed that GTV-P ΔADCmean at mid-RT ≥ 7% was significantly associated with better LC and RFS. The addition of ΔADCmean significantly improved the c-indices of LC and RFS models compared with standard clinical variables (0.85 vs. 0.77 and 0.74 vs. 0.68 for LC and RFS, respectively, p < 0.0001 for both).

CONCLUSION

ΔADCmean at mid-RT is a strong predictor of oncologic outcomes in HNC. Patients with no significant increase of primary tumor ADC at mid-RT are at high risk of disease relapse.

Artificial intelligence to predict outcomes of head and neck radiotherapy

Head and neck radiotherapy induces important toxicity, and its efficacy and tolerance vary widely across patients. Advancements in radiotherapy delivery techniques, along with the increased quality and frequency of image guidance, offer a unique opportunity to individualize radiotherapy based on imaging biomarkers, with the aim of improving radiation efficacy while reducing its toxicity. Various artificial intelligence models integrating clinical data and radiomics have shown encouraging results for toxicity and cancer control outcomes prediction in head and neck cancer radiotherapy. Clinical implementation of these models could lead to individualized risk-based therapeutic decision making, but the reliability of the current studies is limited. Understanding, validating and expanding these models to larger multi-institutional data sets and testing them in the context of clinical trials is needed to ensure safe clinical implementation. This review summarizes the current state of the art of machine learning models for prediction of head and neck cancer radiotherapy outcomes.

Utility of mono-exponential, bi-exponential, and stretched exponential signal models of intravoxel incoherent motion (IVIM) to predict prognosis and survival risk in laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC) patients after chemoradiotherapy

PURPOSE

To investigate the predictive power of mono-exponential, bi-exponential, and stretched exponential signal models of intravoxel incoherent motion (IVIM) in prognosis and survival risk of laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC) patients after chemoradiotherapy.

MATERIALS AND METHODS

Forty-five patients with laryngeal or hypopharyngeal squamous cell carcinoma were retrospectively enrolled. All patients had undergone pretreatment IVIM examination, subsequently, mean apparent diffusion coefficient (ADCmean), maximum ADC (ADCmax), minimum ADC (ADCmin) and ADCrange (ADCmax - ADCmean) by mono-exponential model, true diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f) by bi-exponential model, distributed diffusion coefficient (DDC), and diffusion heterogeneity index (α) by stretched exponential model were measured. Survival data were collected for 5 years.

RESULTS

Thirty-one cases were in the treatment failure group and fourteen cases were in the local control group. Significantly lower ADCmean, ADCmax, ADCmin, D, f, and higher D* values were observed in the treatment failure group than in the local control group (p < 0.05). D* had the greatest AUC of 0.802, with sensitivity and specificity of 77.4 and 85.7% when D* was 38.85 × 10^-3 mm²/s. Kaplan-Meier survival analysis showed that the curves of N stage, ADCmean, ADCmax, ADCmin, D, D*, f, DDC, and α values were significant. Multivariate Cox regression analysis showed ADCmean and D* were independently correlated with progression-free survival (PFS) (hazard ratio [HR] = 0.125, p = 0.001; HR = 1.008, p = 0.002, respectively).

CONCLUSION

The pretreatment parameters of mono-exponential and bi-exponential models were significantly correlated with prognosis of LHSCC, ADCmean and D* values were independent factors for survival risk prediction.

Clinical utility of combined assessments of 4D volumetric perfusion CT, diffusion-weighted MRI and 18F-FDG PET-CT for the prediction of outcomes of head and neck squamous cell carcinoma treated with chemoradiotherapy

BACKGROUND

Multiparametric imaging has been seen as a route to improved prediction of chemoradiotherapy treatment outcomes. Four-dimensional volumetric perfusion CT (4D PCT) is useful for whole-organ perfusion measurement, as it reflects the heterogeneity of the tumor and its perfusion parameters. However, there has been no study using multiparametric imaging including 4D PCT for the prognostic prediction of chemoradiotherapy. The purpose of this study was to determine whether combining assessments of 4D PCT with diffusion-weighted MRI (DWI) and ¹⁸F-fluorodeoxyglucose PET-CT could enhance prognostic accuracy in head and neck squamous cell carcinoma (HNSCC) patients treated with chemoradiotherapy.

METHODS

We examined 53 patients with HNSCC who underwent 4D PCT, DWI and PET-CT before chemoradiotherapy. The imaging and clinical parameters were assessed the relations to locoregional control (LRC) and progression-free survival (PFS) by logistic regression analyses. A receiver operating characteristic (ROC) analysis was performed to assess the accuracy of the significant parameters identified by the multivariate analysis for the prediction of LRC and PFS. We additionally assessed using the scoring system whether these independent parameters could have a complementary role for the prognostic prediction.

RESULTS

The median follow-up was 30 months. In multivariate analysis, blood flow (BF; p = 0.02) and blood volume (BV; p = 0.04) were significant prognostic factors for LRC, and BF (p = 0.03) and skewness of the ADC histogram (p = 0.02) were significant prognostic factors for PFS. A significant positive correlation was found between BF and BV (ρ = 0.6, p < 0.001) and between BF and skewness (ρ = 0.46, p < 0.01). The ROC analysis showed that prognostic accuracy for LRC of BF, BV, and combination of BF and BV were 77.8%, 70%, and 92.9%, and that for PFS of BF, skewness, and combination of BF and skewness were 55.6%, 63.2%, and 77.5%, respectively. The scoring system demonstrated that the combination of higher BF and higher BV was significantly associated with better LRC (p = 0.04), and the combination of lower BF and lower skewness was significantly associated with worse PFS (p = 0.004).

CONCLUSION

A combination of parameters derived from 4DPCT and ADC histograms may enhance prognostic accuracy in HNSCC patients treated with chemoradiotherapy.

Microenvironmental Factors in Oral Cavity Squamous Cell Carcinoma Undergoing Surgery: Correlation with Diffusion Kurtosis Imaging and Dynamic Contrast-Enhanced MRI

BACKGROUND

In this prospective study, we hypothesized that magnetic resonance imaging (MRI) may represent not only the tumor but also the microenvironment, reflecting the heterogeneity and microstructural complexity of neoplasms. We investigated the correlation between both diffusion kurtosis imaging (DKI) and dynamic contrast-enhanced (DCE)-MRI with the pathological factors in oral cavity squamous cell carcinomas (OSCCs).

METHODS

A total of 37 patients with newly diagnosed OSCCs underwent an MR examination on a 3T system. The diffusion coefficient (D), the kurtosis parameter (K), the transfer constants K^trans and K_ep and the volume of extravascular extracellular space v_e were quantified. A histogram-based approach was proposed to investigate the associations between the imaging and the pathological factors based on the histology and immunochemistry.

RESULTS

Significant differences in the DCE-MRI and DKI parameters were found in relation to the inflammatory infiltrate, tumor grading, keratinization and desmoplastic reaction. Relevant relationships emerged between tumor-infiltrating lymphocytes (TILs) and DKI, with lower D and higher K values being associated with increased TILs.

CONCLUSION

Although a further investigation is needed, these findings provide a more comprehensive biological characterization of OSCCs and may contribute to a better understanding of DKI-derived parameters, whose biophysical meaning is still not well-defined.

Prospective Investigation of 18FDG-PET/MRI with Intravoxel Incoherent Motion Diffusion-Weighted Imaging to Assess Survival in Patients with Oropharyngeal or Hypopharyngeal Carcinoma

To prospectively investigate the prognostic value of 18F-FDG PET/MRI in patients with oropharyngeal or hypopharyngeal squamous cell carcinomas (OHSCC) treated by chemoradiotherapy. The study cohort consisted of patients with OHSCC who had undergone integrated PET/MRI prior to chemoradiotherapy or radiotherapy. Imaging parameters derived from intravoxel incoherent motion (IVIM), dynamic contrast-enhanced MRI (DCE-MRI), and 18F-FDG PET were analyzed in relation to overall survival (OS) and recurrence-free survival (RFS). In multivariable analysis, T classification (p < 0.001), metabolic tumor volume (p = 0.013), and pseudo-diffusion coefficient (p = 0.008) were identified as independent risk factors for OS. The volume transfer rate constant (p = 0.015), initial area under the curve (p = 0.043), T classification (p = 0.018), and N classification (p = 0.018) were significant predictors for RFS. The Harrell’s c-indices of OS and RFS obtained from prognostic models incorporating clinical and PET/MRI predictors were significantly higher than those derived from the traditional TNM staging system (p = 0.001). The combination of clinical risk factors with functional parameters derived from IVIM and DCE-MRI plus metabolic PET parameters derived from 18F-FDG PET in integrated PET/MRI outperformed the information provided by traditional TNM staging in predicting the survival of patients with OHSCC.

The utility of diffusion-weighted T2 mapping for the prediction of histological tumor grade in patients with head and neck squamous cell carcinoma

Background

In head and neck cancers, histopathological information is important for the determination of the tumor characteristics and for predicting the prognosis. The aim of this study was to assess the utility of diffusion-weighted T2 (DW-T2) mapping for the evaluation of tumor histological grade in patients with head and neck squamous cell carcinoma (SCC).

Methods

The cases of 41 patients with head and neck SCC (21 well/moderately and 17 poorly differentiated SCC) were retrospectively analyzed. All patients received MR scanning using a 3-Tesla MR unit. The conventional T2 value, DW-T2 value, ratio of DW-T2 value to conventional T2 value, and apparent diffusion coefficient (ADC) were calculated using signal information from the DW-T2 mapping sequence with a manually placed region of interest (ROI).

Results

ADC values in the poorly differentiated SCC group were significantly lower than those in the moderately/well differentiated SCC group (P<0.05). The ratio of DW-T2 value to conventional T2 value was also significantly different between poorly and moderately/well differentiated SCC groups (P<0.01). Receiver operating characteristic (ROC) curve analysis of ADC values showed a sensitivity of 0.76, specificity of 0.67, positive predictive value (PPV) of 0.62, negative predictive value (NPV) of 0.8, accuracy of 0.71 and area under the curve (AUC) of 0.73, whereas the ROC curve analysis of the ratio of DW-T2 value to conventional T2 value showed a sensitivity of 0.76, specificity of 0.83, PPV of 0.76, NPV of 0.83, accuracy of 0.8 and AUC of 0.82.

Conclusions

DW-T2 mapping might be useful as supportive information for the determination of tumor histological grade in patients with head and neck SCC.

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.

The COMPLETE trial: HolistiC early respOnse assessMent for oroPharyngeaL cancEr paTiEnts; Protocol for an observational study

INTRODUCTION

The locoregional failure (LRF) rate in human papilloma virus (HPV)-negative oropharyngeal squamous cell carcinoma (OPSCC) remains disappointingly high and toxicity is substantial. Response prediction prior to or early during treatment would provide opportunities for personalised treatment. Currently, there are no accurate predictive models available for correct OPSCC patient selection. Apparently, the pivotal driving forces that determine how a OPSCC responds to treatment, have yet to be elucidated. Therefore, the holistiC early respOnse assessMent for oroPharyngeaL cancer paTiEnts study focuses on a holistic approach to gain insight in novel potential prognostic biomarkers, acquired before and early during treatment, to predict response to treatment in HPV-negative patients with OPSCC.

METHODS AND ANALYSIS

This single-centre prospective observational study investigates 60 HPV-negative patients with OPSCC scheduled for primary radiotherapy (RT) with cisplatin or cetuximab, according to current clinical practice. A holistic approach will be used that aims to map the macroscopic (with Intra Voxel Incoherent Motion Diffusion Kurtosis Imaging (IVIM-DKI); before, during, and 3 months after RT), microscopic (with biopsies of the primary tumour acquired before treatment and irradiated ex vivo to assess radiosensitivity), and molecular landscape (with circulating tumour DNA (ctDNA) analysed before, during and 3 months after treatment). The main end point is locoregional control (LRC) 2 years after treatment. The primary objective is to determine whether a relative change in the mean of the diffusion coefficient D (an IVIM-DKI parameter) in the primary tumour early during treatment, improves the performance of a predictive model consisting of tumour volume only, for 2 years LRC after treatment. The secondary objectives investigate the potential of other IVIM-DKI parameters, ex vivo sensitivity characteristics, ctDNA, and combinations thereof as potential novel prognostic markers.

ETHICS AND DISSEMINATION

The study was approved by the Medical Ethical Committee of Erasmus Medical Center. The main results of the trial will be presented in international meetings and medical journals.

TRIAL REGISTRATION NUMBER

NL8458.

The impact of radiomics for human papillomavirus status prediction in oropharyngeal cancer: systematic review and radiomics quality score assessment

Purpose

Human papillomavirus (HPV) status assessment is crucial for decision making in oropharyngeal cancer patients. In last years, several articles have been published investigating the possible role of radiomics in distinguishing HPV-positive from HPV-negative neoplasms. Aim of this review was to perform a systematic quality assessment of radiomic studies published on this topic.

Methods

Radiomics studies on HPV status prediction in oropharyngeal cancer patients were selected. The Radiomic Quality Score (RQS) was assessed by three readers to evaluate their methodological quality. In addition, possible correlations between RQS% and journal type, year of publication, impact factor, and journal rank were investigated.

Results

After the literature search, 19 articles were selected whose RQS median was 33% (range 0–42%). Overall, 16/19 studies included a well-documented imaging protocol, 13/19 demonstrated phenotypic differences, and all were compared with the current gold standard. No study included a public protocol, phantom study, or imaging at multiple time points. More than half (13/19) included feature selection and only 2 were comprehensive of non-radiomic features. Mean RQS was significantly higher in clinical journals.

Conclusion

Radiomics has been proposed for oropharyngeal cancer HPV status assessment, with promising results. However, these are supported by low methodological quality investigations. Further studies with higher methodological quality, appropriate standardization, and greater attention to validation are necessary prior to clinical adoption.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00234-022-02959-0.

Techniques, Tricks, and Stratagems of Oral Cavity Computed Tomography and Magnetic Resonance Imaging

The oral cavity constitutes a complex anatomical area that can be affected by many developmental, inflammatory, and tumoural diseases. MultiSlice Computed Tomography (MSCT) and Magnetic Resonance Imaging (MRI) currently represent the essential and complementary imaging techniques for detecting oral cavity abnormalities. Advanced MRI with diffusion-weighted imaging (DWI) and dynamic contrast-enhanced perfusion-weighted imaging (DCE-PWI) has recently increased the ability to characterise oral lesions and distinguish disease recurrences from post therapy changes. The analysis of the oral cavity area via imaging techniques is also complicated both by mutual close appositions of different mucosal surfaces and metal artifacts from dental materials. Nevertheless, an exact identification of oral lesions is made possible thanks to dynamic manoeuvres and specific stratagems applicable on MSCT and MRI acquisitions. This study summarises the currently available imaging techniques for oral diseases, with particular attention to the role of DWI, DCE-PWI, and dynamic manoeuvres. We also propose MSCT and MRI acquisition protocols for an accurate study of the oral cavity area.

Dynamic contrast-enhanced (DCE) imaging: state of the art and applications in whole-body imaging

Dynamic contrast-enhanced (DCE) imaging is a non-invasive technique used for the evaluation of tissue vascularity features through imaging series acquisition after contrast medium administration. Over the years, the study technique and protocols have evolved, seeing a growing application of this method across different imaging modalities for the study of almost all body districts. The main and most consolidated current applications concern MRI imaging for the study of tumors, but an increasing number of studies are evaluating the use of this technique also for inflammatory pathologies and functional studies. Furthermore, the recent advent of artificial intelligence techniques is opening up a vast scenario for the analysis of quantitative information deriving from DCE. The purpose of this article is to provide a comprehensive update on the techniques, protocols, and clinical applications - both established and emerging - of DCE in whole-body imaging.

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.

Analysis of quantitative and semi-quantitative parameters of DCE-MRI in differential diagnosis of benign and malignant cervical tumors

OBJECTIVE

To explore and analyze the value of quantitative and semi-quantitative parameters of dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) in the differential diagnosis of benign and malignant cervical tumors.

METHODS

A total of 51 patients with cervical tumor who were treated in our hospital from April 2017 to October 2019 were recruited as the research subjects. All patients underwent conventional MRI plain scan and DCE-MRI examination. With histopathological results as the gold standard, the participants were classified into a malignant tumor group (n = 36) and a benign tumor group (n = 15) on the basis of the nature of the cervical tumor. The difference of quantitative and semi-quantitative parameters of DCE-MRI between the two groups was compared, and the specificity, sensitivity, negative and positive predictive values of quantitative and semi-quantitative parameters in differentiating benign from malignant cervical tumors were analyzed to evaluate the value of quantitative and semi-quantitative parameters of DCE-MRI in the differential diagnosis of benign and malignant cervical tumors.

RESULTS

The quantitative parameters Kep, Ktrans and Ve of DCE-MRI in the malignant-tumor-group were critically higher than that in the benign tumor group (P<0.05). When distinguishing between the benign and malignant cervical tumors, the specificity and sensitivity of kep, Ktrans and Ve were higher in the differential diagnosis of malignant cervical tumors than in the benign cervical tumors. The peak of the malignant tumor group was remarkably earlier than that of the benign tumor group, and SI60% of the malignant tumor group was dramatically higher than that of benign tumor group (P<0.05). In addition, compared with benign cervical tumors, the semi-quantitative parameters of DCE-MR TTP and SI60% were more sensitive to malignant cervical tumors.

CONCLUSION

The quantitative and semi-quantitative parameters of DCE-MRI have high value in differentiating benign and malignant cervical tumors. When adopting conventional MRI to diagnose oncologic cervical tumors, the differential diagnosis of quantitative and semi-quantitative parameters of DCE-MRI has demonstrated a high clinical value by avoiding unnecessary radical surgeries.

Multiparametric Analysis of Tumor Morphological and Functional MR Parameters Potentially Predicts Local Failure in Pharynx Squamous Cell Carcinoma Patients

Purpose : To predict local control / failure by a multiparametric approach using magnetic resonance (MR)-derived tumor morphological and functional parameters in pharynx squamous cell carcinoma (SCC) patients. Materials and Methods : Twenty-eight patients with oropharyngeal and hypopharyngeal SCCs were included in this study. Quantitative morphological parameters and intratumoral characteristics on T2-weighted images, tumor blood flow from pseudo-continuous arterial spin labeling, and tumor diffusion parameters of three diffusion models from multi-b-value diffusion-weighted imaging as well as patients' characteristics were analyzed. The patients were divided into local control / failure groups. Univariate and multiparametric analysis were performed for the patient group division. Results : The value of morphological parameter of 'sphericity' and intratumoral characteristic of 'homogeneity' was revealed respectively significant for the prediction of the local control status in univariate analysis. Higher diagnostic performance was obtained with the sensitivity of 0.8, specificity of 0.75, positive predictive value of 0.89, negative predictive value of 0.6 and accuracy of 0.79 by multiparametric diagnostic model compared to results in the univariate analysis. Conclusion : A multiparametric analysis with MR-derived quantitative parameters may be useful to predict local control in pharynx SCC patients. J. Med. Invest. 68 : 354-361, August, 2021.

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.

Lack of predictive tools for conventional and targeted cancer therapy: Barriers to biomarker development and clinical translation

Predictive tools, utilising biomarkers, aim to objectively assessthe potentialresponse toa particular clinical intervention in order to direct treatment.Conventional cancer therapy remains poorly served by predictive biomarkers, despite being the mainstay of treatment for most patients. In contrast, targeted therapy benefits from a clearly defined protein target for potential biomarker assessment. We discuss potential data sources of predictive biomarkers for conventional and targeted therapy, including patient clinical data andmulti-omicbiomarkers (genomic, transcriptomic and protein expression).Key examples, either clinically adopted or demonstrating promise for clinical translation, are highlighted. Following this, we provide an outline of potential barriers to predictive biomarker development; broadly discussing themes of approaches to translational research and study/trial design, and the impact of cellular and molecular tumor heterogeneity. Future avenues of research are also highlighted.

The Role of Dynamic Contrast-Enhanced Magnetic Resonance Imaging in Predicting Treatment Response for Cervical Cancer Treated with Concurrent Chemoradiotherapy

Purpose

To evaluate the role of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting early treatment response.

Materials and Methods

Patients with locally advanced cervical cancer (LACC) treated with concurrent chemoradiotherapy (CCRT) were enrolled. Pelvic DCE-MRI scans were performed before RT (pre-RT), in the middle of RT (mid-RT), and at the end of RT (post-RT), separately. Parameters (ie, K^trans, K_ep, and V_e) were measured. Pre-, mid-, and post-RT K^trans were denoted as K^trans-preTx, K^trans-midTx, and K^trans-postTx, respectively. And the same denoting rule also went for K_ep and V_e. Difference for the same parameter such as K^trans measured between two consecutive time points was calculated as second K^trans value minus first K^trans value. The differences in K^trans between pre-RT and post-RT, between pre-RT and mid-RT, and between mid-RT and post-RT were denoted as ΔK^trans-post-preTx, ΔK^trans-mid-preTx, and ΔK^trans-post-midTx, respectively, and the same denoting rule was also applied to K_ep and V_e.

Results

A total of 57 patients were enrolled. After the treatment, 31 patients had complete response (CR group). The remaining 26 patients had partial response (NCR group). Significant differences were found in K^trans-postTx, K_ep-postTx, V_e-midTx, ΔK^trans-post-preTx, ΔK^trans-post-midTx, ΔK_ep-post-preTx, ΔK_ep-mid-preTx and ΔK_ep-post-midTx between the two groups. Receiver operating characteristic (ROC) analysis for their performances in predicting treatment response showed an area under curve (AUC) of 0.656-0.849, sensitivity of 61.3-93.5%, specificity of 46.1-73.1%, and maximal Youden Index of 36.5-66.6. Among those parameters, K_ep-postTx was the best, and its AUC, sensitivity, specificity, maximal Youden Index, and cutoff value were 0.849, 87.1%, 73.1%, 60.2, and 0.341, respectively. These combined parameters showed an AUC of 0.952, with sensitivity of 87.1%, specificity of 96.1%, and maximal Youden Index of 83.2.

Conclusion

DCE-MRI parameters can predict early treatment outcome. Among those parameters, K_ep-postTx is the best predictor. The combination of multi-parameters can increase the predictive potency.

Imaging in head and neck cancers: Update for non-radiologist

Head and neck cancer (HNC) is the fifth most frequent cancer worldwide and associated with significant morbidity. Along with clinical examination and endoscopic evaluation, imaging plays an important role in pre- and posttherapeutic evaluation of patients with HNC. Cross-sectional Imaging techniques such as computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography / computed tomography (PET/CT) are routinely used in the assessment of these patients. This review provides an overview of the various cross-sectional imaging modalities used in the evaluation of HNC and will give a short summary of the latest imaging technologies regarding head and neck cancer diagnosis.

Prognostic imaging variables for recurrent laryngeal and hypopharyngeal carcinoma treated with primary chemoradiotherapy: A systematic review and meta-analysis

Background

In this systematic review, we aim to identify prognostic imaging variables of recurrent laryngeal or hypopharyngeal carcinoma after chemoradiotherapy.

Methods

A systematic search was performed in PubMed and EMBASE (1990–2020). The crude data and effect estimates were extracted for each imaging variable. The level of evidence of each variable was assessed and pooled risk ratios (RRs) were calculated.

Results

Twenty‐two articles were included in this review, 17 on computed tomography (CT) and 5 on magnetic resonance imaging (MRI) variables. We found strong evidence for the prognostic value of tumor volume at various cut‐off points (pooled RRs ranging from 2.09 to 3.03). Anterior commissure involvement (pooled RR 2.19), posterior commissure involvement (pooled RR 2.44), subglottic extension (pooled RR 2.25), and arytenoid cartilage extension (pooled RR 2.10) were also strong prognostic factors.

Conclusion

Pretreatment tumor volume and involvement of several subsites are prognostic factors for recurrent laryngeal or hypopharyngeal carcinoma after chemoradiotherapy.

MR-Guided Radiotherapy for Head and Neck Cancer: Current Developments, Perspectives, and Challenges

Based on the development of new hybrid machines consisting of an MRI and a linear accelerator, magnetic resonance image guided radiotherapy (MRgRT) has revolutionized the field of adaptive treatment in recent years. Although an increasing number of studies have been published, investigating technical and clinical aspects of this technique for various indications, utilizations of MRgRT for adaptive treatment of head and neck cancer (HNC) remains in its infancy. Yet, the possible benefits of this novel technology for HNC patients, allowing for better soft-tissue delineation, intra- and interfractional treatment monitoring and more frequent plan adaptations appear more than obvious. At the same time, new technical, clinical, and logistic challenges emerge. The purpose of this article is to summarize and discuss the rationale, recent developments, and future perspectives of this promising radiotherapy modality for treating HNC.

Intravoxel Incoherent Motion Magnetic Resonance Imaging for Prediction of Induction Chemotherapy Response in Locally Advanced Hypopharyngeal Carcinoma: Comparison With Model-Free Dynamic Contrast-Enhanced Magnetic Resonance Imaging

BACKGROUND

Multiparametric intravoxel incoherent motion (IVIM) provides diffusion and perfusion information for the treatment prediction of cancer. However, the superiority of IVIM over dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in locally advanced hypopharyngeal carcinoma (LAHC) remains unclear.

PURPOSE

To compare the diagnostic performance of IVIM and model-free DCE in assessing induction chemotherapy (IC) response in patients with LAHC.

STUDY TYPE

Prospective.

POPULATION

Forty-two patients with LAHC.

FIELD STRENGTH/SEQUENCE

3.0 T MRI, including IVIM (12 b values, 0-800 seconds/mm² ) with a single-shot echo planar imaging sequence and DCE-MRI with a volumetric interpolated breath-hold examination sequence. IVIM MRI is a commercially available sequence and software for calculation and analysis from vendor.

ASSESSMENT

The IVIM-derived parameters (diffusion coefficient [D], pseudodiffusion coefficient [D*], and perfusion fraction [f]) and DCE-derived model-free parameters (Wash-in, time to maximum enhancement [Tmax], maximum enhancement [Emax], area under enhancement curve [AUC] over 60 seconds [AUC₆₀ ], and whole area under enhancement curve [AUC_w ]) were measured. At the end of IC, patients with complete or partial response were classified as responders according to the Response Evaluation Criteria in Solid Tumors.

STATISTICAL TESTS

The differences of parameters between responders and nonresponders were assessed using Mann-Whitney U tests. The performance of parameters for predicting IC response was evaluated by the receiver operating characteristic curves.

RESULTS

Twenty-three (54.8%) patients were classified as responders. Compared with nonresponders, the perfusion parameters D*, f, f × D*, and AUC_w were significantly higher whereas Wash-in was lower in responders (all P-values <0.05). The f × D* outperformed other parameters, with an AUC of 0.84 (95% confidence interval [CI]: 0.69-0.93), sensitivity of 79.0% (95% CI: 54.4-93.9), and specificity of 82.6% (95% CI: 61.2-95.0).

DATA CONCLUSION

The IVIM MRI technique may noninvasively help predict the IC response before treatment in patients with LAHC.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 2.

Magnetic resonance image biomarkers improve differentiation of benign and malignant parotid tumors through diagnostic model analysis

OBJECTIVES

To explore the effectiveness of magnetic resonance image (MRI)-based biomarkers for identifying benign and malignant parotid tumors via diagnostic model analysis.

METHODS

This retrospective study included 109 patients (development cohort and validation cohort) who underwent MRI preoperatively, including T1- and T2-weighted images. Parameters based on 2D or 3D texture analysis were extracted from tumor lesions by MaZda software, fisher discriminant and bootstrap method were used to perform parameter reduction, diagnostic models with the selected biomarkers were established along with clinical data, model performance (discrimination and calibration) was furtherly evaluated by internal and external validation, decision curve analysis was applied to measure the improvement of clinical benefits.

RESULTS

S(5,5) Entrop, S(0,1) ASM, WavEnHH (s-4), S(1,1,0) Entropy and Perc.10% were significantly associated with the pathological diagnosis of parotid tumor (benign versus malignancy), when adding these biomarkers to the regression analysis, model performance significantly improved in the development cohort (likelihood-ratio-test; p < 0.05, with an increase of AUC from 0.72 (reference model) to 0.85), and these results were maintained in a small external validation cohort. Decision curve analysis indicated that clinical benefit was greater with the application of MRI-based biomarkers.

CONCLUSIONS

MRI-based texture analysis is proven to be an effective tool in differentiating benign and malignant parotid tumors, preoperative diagnosis was improved with the selected biomarkers compared to the reference model.

A Nomogram for Pretreatment Prediction of Response to Induction Chemotherapy in Locally Advanced Hypopharyngeal Carcinoma

Background

Induction chemotherapy (IC) significantly improves the rate of larynx preservation; however, some patients could not benefit from it. Hence, it is of clinical importance to predict the response to IC to determine the necessity of IC. We aimed to develop a clinical nomogram for predicting the treatment response to IC in locally advanced hypopharyngeal carcinoma.

Methods

We retrospectively include a total of 127 patients with locally advanced hypopharyngeal carcinoma who underwent MRI scans prior to IC between January 2014 and December 2017. The clinical characteristics were collected, which included age, sex, tumor location, invading sites, histological grades, T-stage, N-stage, overall stage, size of the largest lymph node, neutrophil-to-lymphocyte ratio, hemoglobin concentration, and platelet count. Univariate and multivariate logistic regression was used to select the significant predictors of IC response. A nomogram was built based on the results of stepwise logistic regression analysis. The predictive performance and clinical usefulness of the nomogram were determined based on the area under the curve (AUC), calibration curve, and decision curve.

Results

Age, T-stage, hemoglobin, and platelet were four independent predictors of IC treatment response, which were incorporated into the nomogram. The AUC of the nomogram was 0.860 (95% confidence interval [CI]: 0.780-0.940), which was validated using 3-fold cross-validation (AUC, 0.864; 95% CI: 0.755-0.973). The calibration curve demonstrated good consistency between the prediction by the nomogram and actual observation. Decision curve analysis shows that the nomogram was clinically useful.

Conclusion

The proposed nomogram resulted in an accurate prediction of the efficacy of IC for patients with locally advanced hypopharyngeal carcinoma.

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.

Functional Imaging to Predict Treatment Response in Head and Neck Cancer: How Close are We to Biologically Adaptive Radiotherapy?

It is increasingly recognised that head and neck cancer represents a spectrum of disease with a differential response to standard treatments. Although prognostic factors are well established, they do not reliably predict response. The ability to predict response early during radiotherapy would allow adaptation of treatment: intensifying treatment for those not responding adequately or de-intensifying remaining therapy for those likely to achieve a complete response. Functional imaging offers such an opportunity. Changes in parameters obtained with functional magnetic resonance imaging or positron emission tomography-computed tomography during treatment have been found to be predictive of disease control in head and neck cancer. Although many questions remain unanswered regarding the optimal implementation of these techniques, current, maturing and future studies may provide the much-needed homogeneous cohorts with larger sample sizes and external validation of parameters. With a stepwise and collaborative approach, we may be able to develop imaging biomarkers that allow us to deliver personalised, biologically adaptive radiotherapy for head and neck cancer.

Dynamic contrast-enhanced MRI histogram parameters predict progression-free survival in patients with advanced esophageal squamous carcinoma receiving concurrent chemoradiotherapy

BACKGROUND

There is increased interest in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for predicting the outcomes of patients with advanced esophageal cancer.

PURPOSE

To explore whether DCE-MRI histogram parameters can predict 12-month progression-free survival (PFS) in patients with advanced esophageal squamous carcinoma receiving concurrent chemoradiation therapy (CRT).

MATERIAL AND METHODS

This retrospective study enrolled 134 patients with advanced esophageal squamous carcinoma who were receiving CRT. The pre-CRT DCE-MRI histogram parameters (median, mean, SD, skewness, kurtosis, and 10th and 90th percentiles) of K^trans, K_ep, and V_e were collected. PFS analyses were performed using the Kaplan-Meier method and log-rank tests to compute the survival curves. The significant prognostic predictors among the data characteristics and DCE-MRI parameters were determined using multivariate Cox proportional hazards regression analyses.

RESULTS

There were 65 good responders (PFS ≥ 12 months) and 69 poor responders (PFS < 12 months). The median and mean values of K^trans were higher, and the kurtosis value of K^trans was lower in good responders. The median, mean, and 10th and 90th percentile values of K^trans were higher, and the kurtosis values of K^trans and V_e were lower in good responders. The PFS of patients aged ≥60 years, a CR effect, or a 10th percentile value of K^trans ≥0.13 was increased (P < 0.001, <0.001, and 0.014, respectively).

CONCLUSION

DCE-MRI histogram parameters can be used to evaluate the response to CRT in patients with advanced esophageal squamous carcinoma. The 10th percentile value of K^trans has significant prognostic value for 12-month PFS.

Predictive value of quantitative 18F-FDG-PET radiomics analysis in patients with head and neck squamous cell carcinoma

BACKGROUND

Radiomics is aimed at image-based tumor phenotyping, enabling application within clinical-decision-support-systems to improve diagnostic accuracy and allow for personalized treatment. The purpose was to identify predictive 18-fluor-fluoro-2-deoxyglucose (¹⁸F-FDG) positron-emission tomography (PET) radiomic features to predict recurrence, distant metastasis, and overall survival in patients with head and neck squamous cell carcinoma treated with chemoradiotherapy.

METHODS

Between 2012 and 2018, 103 retrospectively (training cohort) and 71 consecutively included patients (validation cohort) underwent ¹⁸F-FDG-PET/CT imaging. The 434 extracted radiomic features were subjected, after redundancy filtering, to a projection resulting in outcome-independent meta-features (factors). Correlations between clinical, first-order ¹⁸F-FDG-PET parameters (e.g., SUVmean), and factors were assessed. Factors were combined with ¹⁸F-FDG-PET and clinical parameters in a multivariable survival regression and validated. A clinically applicable risk-stratification was constructed for patients' outcome.

RESULTS

Based on 124 retained radiomic features from 103 patients, 8 factors were constructed. Recurrence prediction was significantly most accurate by combining HPV-status, SUVmean, SUVpeak, factor 3 (histogram gradient and long-run-low-grey-level-emphasis), factor 4 (volume-difference, coarseness, and grey-level-non-uniformity), and factor 6 (histogram variation coefficient) (CI = 0.645). Distant metastasis prediction was most accurate assessing metabolic-active tumor volume (MATV)(CI = 0.627). Overall survival prediction was most accurate using HPV-status, SUVmean, SUVmax, factor 1 (least-axis-length, non-uniformity, high-dependence-of-high grey-levels), and factor 5 (aspherity, major-axis-length, inversed-compactness and, inversed-flatness) (CI = 0.764).

CONCLUSIONS

Combining HPV-status, first-order ¹⁸F-FDG-PET parameters, and complementary radiomic factors was most accurate for time-to-event prediction. Predictive phenotype-specific tumor characteristics and interactions might be captured and retained using radiomic factors, which allows for personalized risk stratification and optimizing personalized cancer care.

TRIAL REGISTRATION

Trial NL3946 (NTR4111), local ethics commission reference: Prediction 2013.191 and 2016.498. Registered 7 August 2013, https://www.trialregister.nl/trial/3946.

Pretreatment DWI with Histogram Analysis of the ADC in Predicting the Outcome of Advanced Oropharyngeal Cancer with Known Human Papillomavirus Status Treated with Chemoradiation

BACKGROUND AND PURPOSE

The incidence of oropharyngeal squamous cell carcinoma (OPSCC) has increased in the period from the 1970s to 2004, due to increase of infection with human papilloma virus (HPV). This study aimed to examine the role of histogram analysis of the ADC in treatment response and survival prediction of patients with oropharyngeal squamous cell carcinoma and known human papillomavirus status.

MATERIALS AND METHODS

This was a retrospective single-center study. Following inclusion and exclusion criteria, data for 59 patients affected by T2-T4 (according to the 8th edition of the AJCC Cancer Staging Manual) oropharyngeal squamous cell carcinoma were retrieved. Twenty-eight had human papillomavirus-positive oropharyngeal squamous cell carcinoma, while 31 had human papillomavirus-negative oropharyngeal squamous cell carcinoma. All patients underwent a pretreatment MR imaging. Histogram analysis of ADC maps obtained by DWI (b = 0-1000 mm/s²) was performed on the central section of all of tumors. The minimum follow-up period was 2 years. Histogram ADC parameters were associated with progression-free survival and overall survival. Univariable and multivariable Cox models were applied to the data; P values were corrected using the Benjamini-Hochberg method.

RESULTS

At univariable analysis, both human papillomavirus status and mean ADC were associated with progression-free survival (hazard ratio = 0.267, P < .05, and hazard ratio  = 1.0028, P ≤ .05, respectively), while only human papillomavirus status was associated with overall survival (hazard ratio  = 0.213, P ≤ .05) before correction. At multivariable analysis, no parameter was included (in fact, human papillomavirus status lost significance after correction). If we separated the patients into 2 subgroups according to human papillomavirus status, ADC entropy was associated with overall survival in the human papillomavirus-negative group (hazard ratio  = 4.846, P = .01).

CONCLUSIONS

ADC and human papillomavirus status are related to progression-free survival in patients treated with chemoradiation for advanced oropharyngeal squamous cell carcinoma; however, this association seems to result from the strong association between ADC and human papillomavirus status.

Patient-Centric Head and Neck Cancer Radiation Therapy: Role of Advanced Imaging

The traditional 'one-size-fits-all' approach to H&N cancer therapy is archaic. Advanced imaging can identify radioresistant areas by using biomarkers that detect tumor hypoxia, hypercellularity etc. Highly conformal radiotherapy can target resistant areas with precision. The critical information that can be gleaned about tumor biology from these advanced imaging modalities facilitates individualized radiotherapy. The tumor imaging world is pushing its boundaries. Molecular imaging can now detect protein expression and genotypic variations across tumors that can be exploited for tailoring treatment. The exploding field of radiomics and radiogenomics extracts quantitative, biologic and genetic information and further expands the scope of personalized therapy.

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.

Magnetic resonance-guided radiation therapy: A review

Magnetic resonance-guided radiation therapy (MRgRT) is a promising approach to improving clinical outcomes for patients treated with radiation therapy. The roles of image guidance, adaptive planning and magnetic resonance imaging in radiation therapy have been increasing over the last two decades. Technical advances have led to the feasible combination of magnetic resonance imaging and radiation therapy technologies, leading to improved soft-tissue visualisation, assessment of inter- and intrafraction motion, motion management, online adaptive radiation therapy and the incorporation of functional information into treatment. MRgRT can potentially transform radiation oncology by improving tumour control and quality of life after radiation therapy and increasing convenience of treatment by shortening treatment courses for patients. Multiple groups have developed clinical implementations of MRgRT predominantly in the abdomen and pelvis, with patients having been treated since 2014. While studies of MRgRT have primarily been dosimetric so far, an increasing number of trials are underway examining the potential clinical benefits of MRgRT, with coordinated efforts to rigorously evaluate the benefits of the promising technology. This review discusses the current implementations, studies, potential benefits and challenges of MRgRT.

Diffusion-weighted Magnetic Resonance Imaging for Predicting Response to Chemoradiation Therapy for Head and Neck Squamous Cell Carcinoma: A Systematic Review

OBJECTIVE

To systematically review the evaluation of the diagnostic accuracy of pre-treatment apparent diffusion coefficient (ADC) and change in ADC during the intra- or post-treatment period, for the prediction of locoregional failure in patients with head and neck squamous cell carcinoma (HNSCC).

MATERIALS AND METHODS

Ovid-MEDLINE and Embase databases were searched up to September 8, 2018, for studies on the use of diffusion-weighted magnetic resonance imaging for the prediction of locoregional treatment response in patients with HNSCC treated with chemoradiation or radiation therapy. Risk of bias was assessed by using the Quality Assessment Tool for Diagnostic Accuracy Studies-2.

RESULTS

Twelve studies were included in the systematic review, and diagnostic accuracy assessment was performed using seven studies. High pre-treatment ADC showed inconsistent results with the tendency for locoregional failure, whereas all studies evaluating changes in ADC showed consistent results of a lower rise in ADC in patients with locoregional failure compared to those with locoregional control. The sensitivities and specificities of pre-treatment ADC and change in ADC for predicting locoregional failure were relatively high (range: 50-100% and 79-96%, 75-100% and 69-95%, respectively). Meta-analytic pooling was not performed due to the apparent heterogeneity in these values.

CONCLUSION

High pre-treatment ADC and low rise in early intra-treatment or post-treatment ADC with chemoradiation, could be indicators of locoregional failure in patients with HNSCC. However, as the studies are few, heterogeneous, and at high risk for bias, the sensitivity and specificity of these parameters for predicting the treatment response are yet to be determined.

The Application of Radiomics in Breast MRI: A Review

Breast cancer has been a worldwide burden of women's health. Although concerns have been raised for early diagnosis and timely treatment, the efforts are still needed for precision medicine and individualized treatment. Radiomics is a new technology with immense potential to obtain mineable data to provide rich information about the diagnosis and prognosis of breast cancer. In our study, we introduced the workflow and application of radiomics as well as its outlook and challenges based on published studies. Radiomics has the potential ability to differentiate between malignant and benign breast lesions, predict axillary lymph node status, molecular subtypes of breast cancer, tumor response to chemotherapy, and survival outcomes. Our study aimed to help clinicians and radiologists to know the basic information of radiomics and encourage cooperation with scientists to mine data for better application in clinical practice.

Metabolic Imaging Using Hyperpolarized Pyruvate-Lactate Exchange Assesses Response or Resistance to the EGFR Inhibitor Cetuximab in Patient-Derived HNSCC Xenografts

PURPOSE

Optimal head and neck squamous cell carcinoma (HNSCC) patient selection for anti-EGFR-based therapy remains an unmet need since only a minority of patients derive long-term benefit from cetuximab treatment. We assessed the ability of state-of-the-art noninvasive in vivo metabolic imaging to probe metabolic shift in cetuximab-sensitive and -resistant HNSCC patient-derived tumor xenografts (PDTXs).

EXPERIMENTAL DESIGN

Three models selected based on their known sensitivity to cetuximab in patients (cetuximab-sensitive or acquired-resistant HNC007 PDTXs, cetuximab-naïve UCLHN4 PDTXs, and cetuximab-resistant HNC010 PDTXs) were inoculated in athymic nude mice.

RESULTS

Cetuximab induced tumor size stabilization in mice for 4 weeks in cetuximab-sensitive and -naïve models treated with weekly injections (30 mg/kg) of cetuximab. Hyperpolarized ¹³C-pyruvate-¹³C-lactate exchange was significantly decreased in vivo in cetuximab-sensitive xenograft models 8 days after treatment initiation, whereas it was not modified in cetuximab-resistant xenografts. Ex vivo analysis of sensitive tumors resected at day 8 after treatment highlighted specific metabolic changes, likely to participate in the decrease in the lactate to pyruvate ratio in vivo. Diffusion MRI showed a decrease in tumor cellularity in the HNC007-sensitive tumors, but failed to show sensitivity to cetuximab in the UCLHN4 model.

CONCLUSIONS

This study constitutes the first in vivo demonstration of cetuximab-induced metabolic changes in cetuximab-sensitive HNSCC PDTXs that were not present in resistant tumors. Using metabolic imaging, we were able to identify hyperpolarized ¹³C-pyruvate as a potential marker for response and resistance to the EGFR inhibitor in 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.

Histogram analysis of DCE-MRI for chemoradiotherapy response evaluation in locally advanced esophageal squamous cell carcinoma

AIMS

The aim of the study was to predict and assess treatment response by histogram analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to patients with locally advanced esophageal squamous cell carcinoma receiving chemoradiotherapy (CRT).

MATERIALS AND METHODS

Seventy-two patients with locally advanced esophageal squamous cell carcinoma who underwent DCE-MRI before and after chemoradiotherapy were enrolled and divided into the complete response (CR) group and the non-CR group based on RECIST. The histogram parameters (10th percentile, 90th percentile, median, mean, standard deviation, skewness, and kurtosis) of pre-CRT and post-CRT were compared using a paired Student's t test in the CR and non-CR groups, respectively. The histogram parameter differences between the CR and the non-CR groups were compared using an unpaired Student's t test. A receiver operating characteristic (ROC) analysis was performed to evaluate the diagnostic performance.

RESULTS

The histogram parameters of K^trans values were observed to have significantly decreased after chemoradiotherapy in the CR group. The CR responders showed significantly higher median, mean, and 10th and 90th percentile of pre-K^trans values than those of the non-CR group. The histogram analysis indicated the decreased heterogeneity in the CR group after CRT. Esophageal cancer with higher pre-K^trans and lower post-K^trans values indicated a good treatment response to CRT. Pre-K^trans-10th showed the best diagnostic performance in predicting the chemoradiotherapy response.

CONCLUSIONS

The histogram parameters of K^trans are useful in the assessment and prediction of the chemoradiotherapy response in patients with advanced esophageal squamous cell carcinoma. DCE-MRI could serve as an adjunctive imaging technique for treatment planning.

Role of diffusion-weighted imaging in the discrimination of purulent intrasinusal content: A retrospective study

OBJECTIVES

The objective of this study was to analyse MRI with morphological (T1, T2) and diffusion sequences (DWI, b1000) in patients presenting non-aggressive patterns of sinus opacity and operated on by functional endoscopic sinus surgery (FESS).

DESIGN

A retrospective study.

SETTING

Diffusion imaging in paranasal sinus pathology remains little known. To date, no imaging system is capable of determining the purulent content of a non-enhanced sinus filling.

PARTICIPANTS

We included consecutive patients having undergone FESS in whom MRI of the paranasal sinuses was performed. Subjects were allocated to Case (pus) or Control (no pus) groups depending on sinus content found intraoperatively. FESS was performed for bacterial acute rhinosinusitis, acute exacerbations of chronic rhinosinusitis, non-purulent sinusitis, naso-sinusal polyposis, antrochoanal polyp, isolated polyp, angiomatous polyp and eosinophilic fungal sinusitis. Tumours, mucoceles and fungus balls were excluded.

MAIN OUTCOME MEASURES

We analysed T1, T2, b1000 and MRI sequences and ADC map.

RESULTS

On univariate analysis, intermediate signal in T2 and high signal in b1000 were associated with Cases (P < 0.001) as were low ADC values (P < 0.001). The difference in mean ADC values between Cases and Controls was statistically significant (respectively, 0.518 vs 2.041 × 10^-3  mm² /sec, P < 0.01). On multivariate analysis, MRI with ADC < 0.725 × 10^-3  mm² /sec and b1000_SI > brain was significantly associated with the case group. MRI with b1000_SI < brain and ADC > 1.450 × 10^-3  mm² /sec was significantly associated with the control group.

CONCLUSIONS

Diffusion MRI offers extremely promising results regarding content characterisation of infectious sinus diseases.

Machine-Learning-Based Prediction of Treatment Outcomes Using MR Imaging-Derived Quantitative Tumor Information in Patients with Sinonasal Squamous Cell Carcinomas: A Preliminary Study

The purpose of this study was to determine the predictive power for treatment outcome of a machine-learning algorithm combining magnetic resonance imaging (MRI)-derived data in patients with sinonasal squamous cell carcinomas (SCCs). Thirty-six primary lesions in 36 patients were evaluated. Quantitative morphological parameters and intratumoral characteristics from T2-weighted images, tumor perfusion parameters from arterial spin labeling (ASL) and tumor diffusion parameters of five diffusion models from multi-b-value diffusion-weighted imaging (DWI) were obtained. Machine learning by a non-linear support vector machine (SVM) was used to construct the best diagnostic algorithm for the prediction of local control and failure. The diagnostic accuracy was evaluated using a 9-fold cross-validation scheme, dividing patients into training and validation sets. Classification criteria for the division of local control and failure in nine training sets could be constructed with a mean sensitivity of 0.98, specificity of 0.91, positive predictive value (PPV) of 0.94, negative predictive value (NPV) of 0.97, and accuracy of 0.96. The nine validation data sets showed a mean sensitivity of 1.0, specificity of 0.82, PPV of 0.86, NPV of 1.0, and accuracy of 0.92. In conclusion, a machine-learning algorithm using various MR imaging-derived data can be helpful for the prediction of treatment outcomes in patients with sinonasal SCCs.

MR-guidance in clinical reality: current treatment challenges and future perspectives

Magnetic Resonance-guided radiotherapy (MRgRT) marks the beginning of a new era. MR is a versatile and suitable imaging modality for radiotherapy, as it enables direct visualization of the tumor and the surrounding organs at risk. Moreover, MRgRT provides real-time imaging to characterize and eventually track anatomical motion. Nevertheless, the successful translation of new technologies into clinical practice remains challenging. To date, the initial availability of next-generation hybrid MR-linac (MRL) systems is still limited and therefore, the focus of the present preview was on the initial applicability in current clinical practice and on future perspectives of this new technology for different treatment sites.MRgRT can be considered a groundbreaking new technology that is capable of creating new perspectives towards an individualized, patient-oriented planning and treatment approach, especially due to the ability to use daily online adaptation strategies. Furthermore, MRL systems overcome the limitations of conventional image-guided radiotherapy, especially in soft tissue, where target and organs at risk need accurate definition. Nevertheless, some concerns remain regarding the additional time needed to re-optimize dose distributions online, the reliability of the gating and tracking procedures and the interpretation of functional MR imaging markers and their potential changes during the course of treatment. Due to its continuous technological improvement and rapid clinical large-scale application in several anatomical settings, further studies may confirm the potential disruptive role of MRgRT in the evolving oncological environment.