MRI for Differentiation between HPV-Positive and HPV-Negative Oropharyngeal Squamous Cell Carcinoma: A Systematic Review

Human papillomavirus (HPV) is an important risk factor for oropharyngeal squamous cell carcinoma (OPSCC). HPV-positive (HPV+) cases are associated with a different pathophysiology, microstructure, and prognosis compared to HPV-negative (HPV-) cases. This review aimed to investigate the potential of magnetic resonance imaging (MRI) to discriminate between HPV+ and HPV- tumours and predict HPV status in OPSCC patients. A systematic literature search was performed on 15 December 2022 on EMBASE, MEDLINE ALL, Web of Science, and Cochrane according to PRISMA guidelines. Twenty-eight studies (n = 2634 patients) were included. Five, nineteen, and seven studies investigated structural MRI (e.g., T1, T2-weighted), diffusion-weighted MRI, and other sequences, respectively. Three out of four studies found that HPV+ tumours were significantly smaller in size, and their lymph node metastases were more cystic in structure than HPV- ones. Eleven out of thirteen studies found that the mean apparent diffusion coefficient was significantly higher in HPV- than HPV+ primary tumours. Other sequences need further investigation. Fourteen studies used MRI to predict HPV status using clinical, radiological, and radiomics features. The reported areas under the curve (AUC) values ranged between 0.697 and 0.944. MRI can potentially be used to find differences between HPV+ and HPV- OPSCC patients and predict HPV status with reasonable accuracy. Larger studies with external model validation using independent datasets are needed before clinical implementation.

Multiparametric MRI-based radiomics model for predicting human papillomavirus status in oropharyngeal squamous cell carcinoma: optimization using oversampling and machine learning techniques

OBJECTIVES

To develop and validate a multiparametric MRI-based radiomics model with optimal oversampling and machine learning techniques for predicting human papillomavirus (HPV) status in oropharyngeal squamous cell carcinoma (OPSCC).

METHODS

This retrospective, multicenter study included consecutive patients with newly diagnosed and pathologically confirmed OPSCC between January 2017 and December 2020 (110 patients in the training set, 44 patients in the external validation set). A total of 293 radiomics features were extracted from three sequences (T2-weighted images [T2WI], contrast-enhanced T1-weighted images [CE-T1WI], and ADC). Combinations of three feature selection, five oversampling, and 12 machine learning techniques were evaluated to optimize its diagnostic performance. The area under the receiver operating characteristic curve (AUC) of the top five models was validated in the external validation set.

RESULTS

A total of 154 patients (59.2 ± 9.1 years; 132 men [85.7%]) were included, and oversampling was employed to account for data imbalance between HPV-positive and HPV-negative OPSCC (86.4% [133/154] vs. 13.6% [21/154]). For the ADC radiomics model, the combination of random oversampling and ridge showed the highest diagnostic performance in the external validation set (AUC, 0.791; 95% CI, 0.775-0.808). The ADC radiomics model showed a higher trend in diagnostic performance compared to the radiomics model using CE-T1WI (AUC, 0.604; 95% CI, 0.590-0.618), T2WI (AUC, 0.695; 95% CI, 0.673-0.717), and a combination of both (AUC, 0.642; 95% CI, 0.626-0.657).

CONCLUSIONS

The ADC radiomics model using random oversampling and ridge showed the highest diagnostic performance in predicting the HPV status of OPSCC in the external validation set.

CLINICAL RELEVANCE STATEMENT

Among multiple sequences, the ADC radiomics model has a potential for generalizability and applicability in clinical practice. Exploring multiple oversampling and machine learning techniques was a valuable strategy for optimizing radiomics model performance.

KEY POINTS

• Previous radiomics studies using multiparametric MRI were conducted at single centers without external validation and had unresolved data imbalances. • Among the ADC, CE-T1WI, and T2WI radiomics models and the ADC histogram models, the ADC radiomics model was the best-performing model for predicting human papillomavirus status in oropharyngeal squamous cell carcinoma. • The ADC radiomics model with the combination of random oversampling and ridge showed the highest diagnostic performance.

Relating pre-treatment non-Gaussian intravoxel incoherent motion diffusion-weighted imaging to human papillomavirus status and response in oropharyngeal carcinoma

Background and purpose

Diffusion-weighted imaging (DWI) is a promising technique for response assessment in head-and-neck cancer. Recently, we optimized Non-Gaussian Intravoxel Incoherent Motion Imaging (NG-IVIM), an extension of the conventional apparent diffusion coefficient (ADC) model, for the head and neck. In the current study, we describe the first application in a group of patients with human papillomavirus (HPV)-positive and HPV-negative oropharyngeal squamous cell carcinoma. The aim of this study was to relate ADC and NG-IVIM DWI parameters to HPV status and clinical treatment response.

Materials and methods

Thirty-six patients (18 HPV-positive, 18 HPV-negative) were prospectively included. Presence of progressive disease was scored within one year. The mean pre-treatment ADC and NG-IVIM parameters in the gross tumor volume were compared between HPV-positive and HPV-negative patients. In HPV-negative patients, ADC and NG-IVIM parameters were compared between patients with and without progressive disease.

Results

ADC, the NG-IVIM diffusion coefficient D, and perfusion fraction f were significantly higher, while pseudo-diffusion coefficient D* and kurtosis K were significantly lower in the HPV-negative compared to HPV-positive patients. In the HPV-negative group, a significantly lower D was found for patients with progressive disease compared to complete responders. No relation with ADC was observed.

Conclusion

The results of our single-center study suggest that ADC is related to HPV status, but not an independent response predictor. The NG-IVIM parameter D, however, was independently associated to response in the HPV-negative group. Noteworthy in the opposite direction as previously thought based on ADC.

The Prediction of Biological Features Using Magnetic Resonance Imaging in Head and Neck Squamous Cell Carcinoma: A Systematic Review and Meta-Analysis

Magnetic resonance imaging (MRI) is an indispensable, routine technique that provides morphological and functional imaging sequences. MRI can potentially capture tumor biology and allow for longitudinal evaluation of head and neck squamous cell carcinoma (HNSCC). This systematic review and meta-analysis evaluates the ability of MRI to predict tumor biology in primary HNSCC. Studies were screened, selected, and assessed for quality using appropriate tools according to the PRISMA criteria. Fifty-eight articles were analyzed, examining the relationship between (functional) MRI parameters and biological features and genetics. Most studies focused on HPV status associations, revealing that HPV-positive tumors consistently exhibited lower ADCmean (SMD: 0.82; p < 0.001) and ADCminimum (SMD: 0.56; p < 0.001) values. On average, lower ADCmean values are associated with high Ki-67 levels, linking this diffusion restriction to high cellularity. Several perfusion parameters of the vascular compartment were significantly associated with HIF-1α. Analysis of other biological factors (VEGF, EGFR, tumor cell count, p53, and MVD) yielded inconclusive results. Larger datasets with homogenous acquisition are required to develop and test radiomic-based prediction models capable of capturing different aspects of the underlying tumor biology. Overall, our study shows that rapid and non-invasive characterization of tumor biology via MRI is feasible and could enhance clinical outcome predictions and personalized patient management for HNSCC.

Imaging of human papilloma virus associated oropharyngeal squamous cell carcinoma and its impact on diagnosis, prognostication, and response assessment

The clinical behaviour and outcomes of patients with oropharyngeal cancer (OPC) may be dichotomised according to their association with human papilloma virus (HPV) infection. Patients with HPV-associated disease (HPV+OPC) have a distinct demographic profile, clinical phenotype and demonstrate considerably better responses to chemoradiotherapy. This has led to a reappraisal of staging and treatment strategies for HPV+OPC, which are underpinned by radiological data. Structural modalities, such as CT and MRI can provide accurate staging information. These can be combined with ultrasound-guided tissue sampling and functional techniques (such as diffusion-weighted MRI and 18F-fludeoxyglucose positron emission tomography-CT) to monitor response to treatment, derive prognostic information, and to identify individuals who might benefit from intensification or deintensification strategies. Furthermore, advanced MRI techniques, such as intravoxel incoherent motion and perfusion MRI as well as application of artificial intelligence and radiomic techniques, have shown promise in treatment response monitoring and prognostication. The following review will consider the contemporary role and knowledge on imaging in HPV+OPC.

Amide proton transfer imaging for the determination of human papillomavirus status in patients with oropharyngeal squamous cell carcinoma

The aim of this study was to investigate the utility of amide proton transfer (APT) imaging for the determination of human papillomavirus (HPV) status in patients with oropharyngeal squamous cell carcinoma (SCC). Thirty-one patients with oropharyngeal SCC were retrospectively evaluated. All patients underwent amide proton transfer imaging using a 3T magnetic resonance (MR) unit. Patients were divided into HPV-positive and -negative groups depending on the pathological findings in their primary tumor. In APT imaging, the primary tumor was delineated with a polygonal region of interest (ROI). Signal information in the ROI was used to calculate the mean, standard deviation (SD) and coefficient of variant (CV) of the APT signals (APT mean, APT SD, and APT CV, respectively). The value of APT CV in the HPV-positive group (0.43 ± 0.04) was significantly lower than that in the HPV-negative group (0.48 ± 0.04) (P = .01). There was no significant difference in APT mean (P = .82) or APT SD (P = .13) between the HPV-positive and -negative groups. Receiver operating characteristic (ROC) curve analysis of APT CV had a sensitivity of 0.75, specificity of 0.8, positive predictive value of 0.75, negative predictive value of 0.8, accuracy of 0.77 and area under the curve (AUC) of 0.8. The APT signal in the HPV-negative group was considered heterogeneous compared to the HPV-positive group. This information might be useful for the determination of HPV status in patients with oropharyngeal SCC.

18F-FDG PET cannot predict expression of clinically relevant histopathological biomarkers in head and neck squamous cell carcinoma: a meta-analysis

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is a common cancer. Positron emission tomography (PET) with 18F-fluorodeoxyglucose (18F-FDG) is a widely used imaging modality in HNSCC.

PURPOSE

To provide evident data about associations between 18F-FDG PET and histopathology in HNSCC.

MATERIAL AND METHODS

The MEDLINE database was screened for associations between maximum standard uptake values (SUV_max) derived from 18F-FDG PET and histopathological features in HNSCC up to May 2020. Only papers containing correlation coefficients between SUV_max and histopathology were acquired. Overall, 23 publications were collected.

RESULTS

The following correlations were calculated: KI 67: 12 studies (345 patients), pooled correlation coefficient (PCC): 0.23 (95% confidence interval [CI] 0.06-0.40); hypoxia-inducible factor-1α: eight studies (240 patients), PCC: 0.24 (95% CI 0.06-0.42); microvessel density: three studies (64 patients), PCC: 0.33 (95% CI 0.02-0.65); vascular endothelial growth factor: two studies (59 cases), PCC: 0.27 (95% CI 0.02-0.51); tumor suppressor protein p53: four studies (159 patients), PCC: 0.05 (95% CI -0.41 to 0.51); epidermal growth factor receptor: two studies (124 patients), PCC: 0.21 (95% CI 0.05-0.37); tumor cell count: three studies (67 patients), PCC: 0.18 (95% CI -0.06 to 0.42); tumor cell apoptosis: two studies (40 patients), PCC: 0.07 (95% CI = -0.85 to 0.99); B-cell lymphoma-2 protein: two studies (118 patients); PCC: 0.04 (95% CI -0.65 to 0.74); glucose-transporter 1: 10 studies (317 patients), PCC: 0.20 (95% CI 0.10-0.30).

CONCLUSION

SUV_max derived from 18F-FDG PET cannot reflect relevant histopathological features in HNSCC.

Multiparametric MRI Evaluation of Oropharyngeal Squamous Cell Carcinoma. A Mono-Institutional Study

The aim of this paper is to define the pre-treatment radiological characteristics of oropharyngeal squamous cell carcinoma (OPSCC) using morphological and non-morphological magnetic resonance imaging (MRI), based on HPV status, in a single-institution cohort. In total, 100 patients affected by OPSCC were prospectively enrolled in the present study. All patients underwent 1.5T MR with standard sequences, including diffusion-weighted imaging with and intravoxel incoherent motion (IVIM-DWI) technique and a dynamic contrast-enhanced (DCE) MRI. For all patients, human papillomavirus (HPV) status was available. No statistically significant differences in the volume of primary tumors (PTs) and lymph nodes (LNs) were observed based on HPV status. When comparing the two patient groups, no significant differences were found for the PT radiologic characteristics (presence of well-defined borders, exophytic growth, ulceration, and necrosis) and LN morphology (solid/cystic/necrotic). Tumor subsite, smoking status, and alcohol intake significantly differed based on HPV status, as well as ADC and D_t values of both PTs and LNs. We detected no significant difference in DCE-MRI parameters by HPV status. Based on a multivariate logistic regression model, the combination of clinical factors, such as tumor subsite and alcohol habits, with the perfusion-free diffusion coefficient D_t of LNs, may help to accurately discriminate OPSCC by HPV status.

The ability of post-chemoradiotherapy DWI ADCmean and 18F-FDG SUVmax to predict treatment outcomes in head and neck cancer: impact of human papilloma virus oropharyngeal cancer status

OBJECTIVES

To evaluate the ability of post-chemo-radiotherapy (CRT) diffusion-weighted-MRI apparent diffusion coefficient (ADCmean) and 18F-FDG PET maximum standardized uptake value (SUVmax) to predict disease-free survival (DFS) in head and neck squamous cell carcinoma (HNSCC), and to determine whether this ability is influenced by human papillomavirus oropharyngeal cancer (HPV-OPC) status.

METHODS

This prospective cohort observational study included 65 participants (53 male, mean ± SD age 59.9 ± 7.9 years, 46 HPV-OPC) with stage III or IV HNSCC. Primary tumour and nodal ADCmean (pre-treatment, 6- and 12-weeks post-CRT) and SUVmax (12-weeks post-CRT) were measured. Variables were compared with 2-year DFS (independent t-test/Mann-Whitney test) and overall DFS (Cox regression), before and after accounting for HPV-OPC status. Variables were also compared between HPV-OPC and other HNSCC subgroups after stratifying for DFS.

RESULTS

Absolute post-CRT ADCmean values predicted 2-year DFS and overall DFS for all participants (p = 0.03/0.03, 6-week node; p = 0.02/0.03 12-week primary tumour) but not in the HPV-OPC subgroup. In participants with DFS, percentage interval changes in primary tumour ADCmean at 6- and 12-weeks were higher in HPV-OPC than other HNSCC (p = 0.01, 6 weeks; p = 0.005, 12 weeks). The 12-week post-CRT SUVmax did not predict DFS.

CONCLUSION

Absolute post-CRT ADCmean values predicted DFS in HNSCC but not in the HPV-OPC subgroup. Amongst participants with DFS, post-CRT percentage interval changes in primary tumour ADCmean were significantly higher in HPV-OPC than in other HNSCC. Knowledge of HPV-OPC status is crucial to the clinical utilisation of post-CRT DWI-MRI for the prediction of outcomes.

Correlations between DW-MRI and 18 F-FDG PET/CT parameters in head and neck squamous cell carcinoma following definitive chemo-radiotherapy

BACKGROUND

Posttreatment diffusion-weighted magnetic resonance imaging (DW-MRI) and 18F-fluorodeoxygluocose (18 F-FDG) positron emission tomography (PET) with computed tomography (PET/CT) have potential prognostic value following chemo-radiotherapy (CRT) for head and neck squamous cell carcinoma (HNSCC). Correlations between these PET/CT (standardized uptake value or SUV) and DW-MRI (apparent diffusion coefficient or ADC) parameters have only been previously explored in the pretreatment setting.

AIM

To evaluate stage III and IV HNSCC at 12-weeks post-CRT for the correlation between SUVmax and ADC values and their interval changes from pretreatment imaging.

METHODS

Fifty-six patients (45 male, 11 female, mean age 59.9 + - 7.38) with stage 3 and 4 HNSCC patients underwent 12-week posttreatment DW-MRI and 18 F-FDG PET/CT studies in this prospective study. There were 41/56 patients in the cohort with human papilloma virus-related oropharyngeal cancer (HPV OPC). DW-MRI (ADCmax and ADCmin) and 18 F-FDG PET/CT (SUVmax and SUVmax ratio to liver) parameters were measured at the site of primary tumors (n = 48) and the largest lymph nodes (n = 52). Kendall's tau evaluated the correlation between DW-MRI and 18 F-FDG PET/CT parameters. Mann-Whitney test compared the post-CRT PET/CT and DW-MRI parameters between those participants with and without 2-year disease-free survival (DFS).

RESULTS

There was no correlation between DW-MRI and 18 F-FDG PET/CT parameters on 12-week posttreatment imaging (P = .455-.794; tau = -0.075-0.25) or their interval changes from pretreatment to 12-week posttreatment imaging (P = .1-.946; tau = -0.194-0.044). The primary tumor ADCmean (P = .03) and the interval change in nodal ADCmin (P = .05) predicted 2-year DFS but none of the 18 F-FDG PET/CT parameters were associated with 2-year DFS.

CONCLUSIONS

There is no correlation between the quantitative DWI-MRI and 18 F-FDG PET/CT parameters derived from 12-week post-CRT studies. These parameters may be independent biomarkers however in this HPV OPC dominant cohort, only selected ADC parameters demonstrated prognostic significance. Study was prospectively registered at http://www.controlled-trials.com/ISRCTN58327080.

Radiomics and radiogenomics in head and neck squamous cell carcinoma: Potential contribution to patient management and challenges

The application of imaging biomarkers in oncology is still in its infancy, but with the expansion of radiomics and radiogenomics a revolution is expected in this field. This may be of special interest in head and neck cancer, since it can promote precision medicine and personalization of treatment by overcoming several intrinsic obstacles in this pathology. Our goal is to provide the medical oncologist with the basis to approach these disciplines and appreciate their main uses in clinical research and clinical practice in the medium term. Aligned with this objective we analyzed the most relevant studies in the field, also highlighting novel opportunities and current challenges.

The impact of human papilloma virus status on the prediction of head and neck cancer chemoradiotherapy outcomes using the pre-treatment apparent diffusion coefficient

Objective:

To determine the impact of Human Papilloma Virus (HPV) oropharyngeal cancer (OPC) status on the prediction of head and neck squamous cell cancer (HNSCC) chemoradiotherapy (CRT) outcomes with pre-treatment quantitative diffusion-weighted magnetic resonance imaging (DW-MRI).

Methods:

Following ethical approval, 65 participants (53 male, age 59.9 ± 7.86) underwent pre-treatment DW-MRI in this prospective cohort observational study. There were 46 HPV OPC and 19 other HNSCC cases with Stage III/IV HNSCC. Regions of interest (ROIs) (volume, largest area, core) at the primary tumour (n = 57) and largest pathological node (n = 59) were placed to analyse ADC_mean and ADC_min. Unpaired t-test or Mann–Whitney test evaluated the impact of HPV OPC status and clinical parameters on their prediction of post-CRT 2 year locoregional and disease-free survival (LRFS and DFS). Multivariate logistic regression compared significant variables with 2 year outcomes.

Results:

On univariate analysis of all participants, the primary tumour area ADC_mean was predictive of 2 year LRFS (p = 0.04). However, only the HPV OPC diagnosis (LFRS p = 0.03; DFS p = 0.02) predicted outcomes on multivariate analysis. None of the pre-treatment ADC values were predictive of 2 year DFS in the HPV OPC subgroup (p = 0.21–0.68). Amongst participants without 2 year disease-free survival, HPV-OPC was found to have much lower primary tumour ADC_mean values than other HNSCC.

Conclusion:

Knowledge of HPV OPC status is required in order to determine the impact of the pre-treatment ADC values on post-CRT outcomes in HNSCC.

Advances in knowledge:

Pre-treatment ADC_mean and ADC_min values acquired using different ROI methods are not predictive of 2 year survival outcomes in HPV OPC.

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.

Oropharyngeal squamous cell carcinoma: radiomic machine-learning classifiers from multiparametric MR images for determination of HPV infection status

We investigated the ability of machine-learning classifiers on radiomics from pre-treatment multiparametric magnetic resonance imaging (MRI) to accurately predict human papillomavirus (HPV) status in patients with oropharyngeal squamous cell carcinoma (OPSCC). This retrospective study collected data of 60 patients (48 HPV-positive and 12 HPV-negative) with newly diagnosed histopathologically proved OPSCC, who underwent head and neck MRIs consisting of axial T1WI, T2WI, CE-T1WI, and apparent diffusion coefficient (ADC) maps from diffusion-weighted imaging (DWI). The median age was 59 years (the range being 35 to 85 years), and 83.3% of patients were male. The imaging data were randomised into a training set (32 HPV-positive and 8 HPV-negative OPSCC) and a test set (16 HPV-positive and 4 HPV-negative OPSCC) in each fold. 1618 quantitative features were extracted from manually delineated regions-of-interest of primary tumour and one definite lymph node in each sequence. After feature selection by using the least absolute shrinkage and selection operator (LASSO), three different machine-learning classifiers (logistic regression, random forest, and XG boost) were trained and compared in the setting of various combinations between four sequences. The highest diagnostic accuracies were achieved when using all sequences, and the difference was significant only when the combination did not include the ADC map. Using all sequences, logistic regression and the random forest classifier yielded higher accuracy compared with the that of the XG boost classifier, with mean area under curve (AUC) values of 0.77, 0.76, and 0.71, respectively. The machine-learning classifier of non-invasive and quantitative radiomics signature could guide the classification of the HPV status.

Multiparametric functional MRI and 18F-FDG-PET for survival prediction in patients with head and neck squamous cell carcinoma treated with (chemo)radiation

Objectives

To assess (I) correlations between diffusion-weighted (DWI), intravoxel incoherent motion (IVIM), dynamic contrast-enhanced (DCE) MRI, and ¹⁸F-FDG-PET/CT imaging parameters capturing tumor characteristics and (II) their predictive value of locoregional recurrence-free survival (LRFS) and overall survival (OS) in patients with head and neck squamous cell carcinoma (HNSCC) treated with (chemo)radiotherapy.

Methods

Between 2014 and 2018, patients with histopathologically proven HNSCC, planned for curative (chemo) radiotherapy, were prospectively included. Pretreatment clinical, anatomical, and functional imaging parameters (obtained by DWI/IVIM, DCE-MRI, and ¹⁸F-FDG-PET/CT) were extracted for primary tumors (PT) and lymph node metastases. Correlations and differences between parameters were assessed. The predictive value of LRFS and OS was assessed, performing univariable, multivariable Cox and CoxBoost regression analyses.

Results

In total, 70 patients were included. Significant correlations between ¹⁸F-FDG-PET parameters and DWI-/DCE volume parameters were found (r > 0.442, p < 0.002). The combination of HPV (HR = 0.903), intoxications (HR = 1.065), PT ADC_GTV (HR = 1.252), K^trans (HR = 1.223), and V_e (HR = 1.215) was predictive for LRFS (C-index = 0.546; p = 0.023). N-stage (HR = 1.058), HPV positivity (HR = 0.886), hypopharyngeal tumor location (HR = 1.111), ADC_GTV (HR = 1.102), ADC_mean (HR = 1.137), D* (HR = 0.862), K^trans (HR = 1.106), V_e (HR = 1.195), SUV_max (HR = 1.094), and TLG (HR = 1.433) were predictive for OS (C-index = 0.664; p = 0.046).

Conclusions

Functional imaging parameters, performing DWI/IVIM, DCE-MRI, and ¹⁸F-FDG-PET/CT, yielded complementary value in capturing tumor characteristics. More specific, intoxications, HPV-negative status, large tumor volume-related parameters, high permeability (K^trans), and high extravascular extracellular space (V_e) parameters were predictive for adverse locoregional recurrence-free survival and adverse overall survival. Low cellularity (high ADC) and high metabolism (high SUV) were additionally predictive for decreased overall survival. These different predictive factors added to estimated locoregional and overall survival.

Key Points

• Parameters of DWI/IVIM, DCE-MRI, and 18F-FDG-PET/CT were able to capture complementary tumor characteristics.

• Multivariable analysis revealed that intoxications, HPV negativity, large tumor volume and high vascular permeability (K^trans), and extravascular extracellular space (Ve) were complementary predictive for locoregional recurrence.

• In addition to predictive parameters for locoregional recurrence, also high cellularity (low ADC) and high metabolism (high SUV) were complementary predictive for overall survival.

Electronic supplementary material

The online version of this article (10.1007/s00330-020-07163-3) contains supplementary material, which is available to authorized users.

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.

Machine Learning Based Radiomic HPV Phenotyping of Oropharyngeal SCC: A Feasibility Study Using MRI

OBJECTIVES

To investigate whether a radiomic MRI feature-based prediction model can differentiate oropharyngeal squamous cell carcinoma (SCC) according to the human papillomavirus (HPV) status.

STUDY DESIGN

Retrospective cohort study.

METHODS

Pretreatment MRI data from 62 consecutive patients with oropharyngeal SCC were retrospectively reviewed, and chronologically allocated to training (n = 43) and test sets (n = 19). Enhancing tumors were semi-automatically segmented on each slice of the postcontrast T1WI to span the entire tumor volume, after registration of T2WI to postcontrast T1WI; 170 radiomic features were extracted from the entire tumor volume. Relevant features were selected and radiomics models were trained using least absolute shrinkage and selection operator (LASSO) logistic regression model with 10-fold cross-validation, after subsampling of training sets using synthetic minority over-sampling technique to mitigate data imbalance. The selected features, weighted by their respective coefficients, were combined linearly to yield a radiomics score. The diagnostic performance of the radiomic score was evaluated using the area under the receiver operating characteristic curve (AUC).

RESULTS

Six radiomic features, which revealed strong association with HPV status of oropharyngeal SCC, were selected using LASSO. The radiomics model yielded excellent performance on the training set (AUC, 0.982 [95% CI, 0.942-1.000]) and moderate performance on the test set (AUC, 0.744 [95% CI, 0.496-0.991]) for differentiating oropharyngeal SCC according to HPV status.

CONCLUSIONS

Radiomics-based MRI phenotyping differentiates oropharyngeal SCC according to HPV status, and thus, is a potential imaging biomarker.

LEVEL OF EVIDENCE

3 Laryngoscope, 131:E851-E856, 2021.

Apparent Diffusion Coefficient for Distinguishing Between Malignant and Benign Lesions in the Head and Neck Region: A Systematic Review and Meta-Analysis

Background: The purpose of the present meta-analysis was to provide evident data about use of apparent diffusion coefficient (ADC) values for distinguishing malignant and benign lesions in the head and neck region.

Material and Methods: MEDLINE and Scopus databases were screened for associations between ADC and malignancy/benignancy of head and neck lesions up to December 2018. Overall, 22 studies met the inclusion criteria. The following data were extracted: authors, year of publication, study design, number of patients/lesions, lesion type, mean value, and standard deviation of ADC. The primary endpoint of the systematic review was the analysis of the association between lesion nature and ADC values. The methodological quality of the involved studies was checked according to the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) instrument. The meta-analysis was undertaken by using RevMan 5.3 software. DerSimonian and Laird random-effects models with inverse-variance weights were used without further correction to account for the heterogeneity between the studies. Mean ADC values including 95% confidence intervals were calculated separately for benign and malignant lesions.

Results: The acquired 22 studies comprised 1,227 lesions. Different malignant lesions were diagnosed in 818 cases (66.7%) and benign lesions in 409 cases (33.3%). The mean ADC value of the malignant lesions was 1.04 × 10⁻³ mm²/s, and the mean value of the benign lesions was 1.46 × 10⁻³ mm²/s. Lymphomas and sarcomas showed the lowest calculated mean ADC values, 0.7 and 0.79 × 10⁻³ mm²/s, respectively. Adenoid cystic carcinomas had the highest ADC values (1.5 × 10⁻³ mm²/s). None of the analyzed malignant tumors had mean ADC values above 1.75 × 10⁻³ mm²/s.

Conclusion: ADC values play a limited role in distinguishing between malignant and benign lesions in the head and neck region. It may be only suggested that lesions with mean ADC values above 1.75 × 10⁻³ mm²/s are probably benign. Further large studies are needed for the analysis of the role of diffusion-weighted imaging (DWI)/ADC in the discrimination of benign and malignant lesions in the head and neck region.

Quantitative diffusion magnetic resonance imaging for prediction of human papillomavirus status in head and neck squamous-cell carcinoma: A systematic review and meta-analysis

PURPOSE

Head and neck squamous-cell carcinoma (HNSCC) related to human papillomavirus (HPV) infection represents a distinct biological and prognostic subtype compared to the HPV-negative form. Prior studies suggest a correlation between the apparent diffusion coefficient (ADC) values on diffusion-weighted imaging (DWI) of primary tumor lesion and HPV status in HNSCC. In this meta-analysis, we compared the average ADC of primary lesion between HPV-positive and HPV-negative HNSCC.

METHODS

A comprehensive literature search of PubMed and Embase was performed. Studies comparing the average ADC on echo-planar DWI of primary tumor lesions between HPV-positive and HPV-negative HNSCC were included. The standardized mean difference was calculated using fixed- and random-effects models. Tau-squared estimates of total heterogeneity and Higgins inconsistency index (I² test) were determined.

RESULTS

A total of five studies, pooling data of 264 patients, were included for meta-analysis. Among these five studies, three had included oral cavity, hypopharyngeal, and/or laryngeal HNSCC in addition to oropharyngeal subsite. Primary lesions were comprised of 185 HPV-negative and 79 HPV-positive HNSCC. The meta-analysis showed lower average ADC values in HPV-positive HNSCC compared to the HPV-negative form, with a standardized mean difference of 0.961 (95% confidence interval 0.644-1.279; p < 0.0001). Since there was no significant heterogeneity in analysis (p = 0.3852), both random- and fixed-effects models resulted in the same estimates of overall effect.

CONCLUSIONS

HPV-positive HNSCC primary lesions have a lower average ADC compared to the HPV-negative form, highlighting the potential application of quantitative diffusion magnetic resonance imaging as a noninvasive imaging biomarker for prediction of HPV status.

Predictive value of quantitative diffusion-weighted imaging and 18-F-FDG-PET in head and neck squamous cell carcinoma treated by (chemo)radiotherapy

BACKGROUND AND PURPOSE

In head and neck squamous cell carcinoma (HNSCC) (chemo)radiotherapy is increasingly used to preserve organ functionality. The purpose of this study was to identify predictive pretreatment DWI- and ¹⁸F-FDG-PET/CT-parameters for treatment failure (TF), locoregional recurrence (LR) and death in HNSCC patients treated by (chemo)radiotherapy.

MATERIALS AND METHODS

We retrospectively included 134 histologically proven HNSCC patients treated with (chemo)radiotherapy between 2012-2017. In 58 patients pre-treatment DWI and ¹⁸F-FDG-PET/CT were performed, in 31 patients DWI only and in 45 patients ¹⁸F-FDG-PET/CT only. Primary tumor (_PT) and largest lymph node (_LN) metastasis were quantitatively assessed for TF, LR and death. Multivariate analysis was performed for ¹⁸F-FDG-PET/CT and DWI separately and thereafter combined. In patients with both imaging modalities, positive and negative predictive value in TF and differences in LR and death, were assessed.

RESULTS

Mean follow-up was 25.6 months (interquartile-range; 14.0-37.1 months). Predictors of treatment failure, corrected for TNM-stage and HPV-status, were SUV_max-PT, ADC_max-PT, total lesion glycolysis (TLG_-LN), ADCp20_-LN (P = 0.049, P = 0.024, P = 0.031, P = 0.047, respectively). TLG_-PT was predictive for LR (P = 0.003). Metabolic active tumor volume (MATV_-PT) (P = 0.003), ADC_GTV-PT (P < 0.001), ADCSD (P = 0.048) were significant predictors for death. In patients with both imaging modalities SUV_max-PT remained predictive for treatment failure (P = 0.049), TLG-_LN for LR (P = 0.003) and ADC_GTV-PT for death (P < 0.001). Higher predictive value for treatment failure was found for the combination of SUV_max-PT and ADC_max-PT, compared to either one separately.

CONCLUSION

Both DWI- and ¹⁸F-FDG-PET/CT-parameters appear to have predictive value for treatment failure, locoregional recurrence and death. Combining SUV_max-PT and ADC_max-PT resulted in better prediction of treatment failure compared to single parameter assessment.

Quantitative diffusion magnetic resonance imaging in head and neck tumors

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

Correlation between Human Papillomavirus Status and Quantitative MR Imaging Parameters including Diffusion-Weighted Imaging and Texture Features in Oropharyngeal Carcinoma

BACKGROUND AND PURPOSE

The incidence of Oropharyngeal Squampus Cell Carcinoma (OPSCC) cases is increasing especially in the Western countries due to the spreading of human papilloma virus (HPV) infection. Radiological investigations, MRI in particular, are used in the daily clinical practice to stage OPSCC. The aim of this study was to investigate the association of quantitative MR imaging features including diffusion-weighted imaging and human papillomavirus status in oropharyngeal squamous cell carcinoma.

MATERIALS AND METHODS

We retrospectively analyzed 59 patients with untreated histologically proved T2-T4 oropharyngeal squamous cell carcinoma. Human papillomavirus status was determined by viral DNA detection on tissue samples. MR imaging protocol included T2-weighted, contrast-enhanced T1-weighted (volumetric interpolated brain examination), and DWI sequences. Parametric maps of apparent diffusion coefficient were obtained from DWI sequences. Texture analysis was performed on T2 and volumetric-interpolated brain examination sequences and on ADC maps. Differences in quantitative MR imaging features between tumors positive and negative for human papillomavirus and among subgroups of patients stratified by smoking status were tested using the nonparametric Mann-Whitney U test; the false discovery rate was controlled using the Benjamini-Hochberg correction; and a predictive model for human papillomavirus status was built using multivariable logistic regression.

RESULTS

Twenty-eight patients had human papillomavirus-positive oropharyngeal squamous cell carcinoma, while 31 patients had human papillomavirus-negative oropharyngeal squamous cell carcinoma. Tumors positive for human papillomavirus had a significantly lower mean ADC compared with those negative for it (median, 850.87 versus median, 1033.68; P < .001). Texture features had a lower discriminatory power for human papillomavirus status. Skewness on volumetric interpolated brain examination sequences was significantly higher in the subgroup of patients positive for human papillomavirus and smokers (P = .003). A predictive model based on smoking status and mean ADC yielded a sensitivity of 83.3% and specificity 92.6% in classifying human papillomavirus status.

CONCLUSIONS

ADC is significantly lower in oropharyngeal squamous cell carcinoma positive for human papillomavirus compared with oropharyngeal squamous cell carcinoma negative for it. ADC and smoking status allowed noninvasive prediction of human papillomavirus status with a good accuracy. These results should be validated and further investigated on larger prospective studies.