Head and neck squamous cell carcinoma: differentiation of histologic grade with standard- and high-b-value diffusion-weighted MRI

Whole-tumor histogram analysis of apparent diffusion coefficient maps with machine learning algorithms for predicting histologic grade of sinonasal squamous cell carcinoma: a preliminary study

PURPOSE

Accurate histologic grade assessment is helpful for clinical decision making and prognostic assessment of sinonasal squamous cell carcinoma (SNSCC). This research aimed to explore whether whole-tumor histogram analysis of apparent diffusion coefficient (ADC) maps with machine learning algorithms can predict histologic grade of SNSCC.

METHODS

One hundred and forty-seven patients with pathologically diagnosed SNSCC formed this retrospective study. Sixty-six patients were low-grade (grade I/II) and eighty-one patients were high-grade (grade III). Eighteen histogram features were obtained from quantitative ADC maps. Additionally, the mean ADC value and clinical features were analyzed for comparison with histogram features. Machine learning algorithms were applied to build the best diagnostic model for predicting histological grade. The receiver operating characteristic (ROC) curve was used to evaluate the performance of each model prediction, and the area under the ROC curve (AUC) were analyzed.

RESULTS

The histogram model based on three features (10th Percentile, Mean, and 90th Percentile) with support vector machine (SVM) classifier demonstrated excellent diagnostic performance, with an AUC of 0.947 on the testing dataset. The AUC of the histogram model was similar to that of the mean ADC value model (0.947 vs 0.957; P = 0.7029). The poor diagnostic performance of the clinical model (AUC = 0.692) was improved by the combined model incorporating histogram features or mean ADC value (P < 0.05).

CONCLUSION

ADC histogram analysis improved the projection of SNSCC histologic grade, compared with clinical model. The complex histogram model had comparable but not better performance than mean ADC value model.

A Randomized Study to Evaluate Efficacy and Toxicity Profile of Paclitaxel-carboplatin as Neo-adjuvant Chemotherapy in Locally Advanced Supraglottic and Hypopharyngeal Primaries

This study was conducted in locally advanced supraglottic and hypopharyngeal squamous cell carcinoma patients to ascertain the efficacy and toxicity profile of a two drug combination neo adjuvant chemotherapy (NACT) schedule containing Taxane and Platinum; prior to definitive concurrent chemo-radiotherapy (Def CCRT); sixty patients with stage III, IVA and IVB locally advanced squamous cell cancers of larynx and hypopharynx were randomised to two arms. Thirty patients in study group were treated with NACT with Paclitaxel (175 mg/m2) and Carboplatin (AUC 5-7) for 3, 3 weekly cycles; followed by CCRT in the patients who showed at-least a partial response (PR). These patients were compared with the 30 patients of control group who received upfront CCRT. More patients in Study arm developed grade 3 dysphagia (p = 0.001) and mucositis (p = 0.003). Renal, hematogenous and skin toxicities were identical in two arms. At 3 months post treatment complete response (CR) at primary site was 83.3% and 66.6% (p = 0.245) in study and control arms respectively. At 6 months post treatment; 20 patients (66.6%) in the study group and 17 patients (56.6%) in the control group continued to be in clinic-radiological CR (p = 0.20). NACT with Paclitaxel and Carboplatin is tolerated with manageable toxicities in patients with LAHNSCC (Locally advanced head and neck squamous cell carcinoma), with increased Grade 3 dysphagia and mucositis as compared to patients getting upfront CCRT. A longer follow-up period with a larger sample size is required to further evaluate any statistically significant benefit of adding NACT prior to CCRT.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

The 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.

Correlation between 18F-FDG PET/CT and diffusion-weighted MRI parameters in head and neck squamous cell carcinoma at baseline and after chemo-radiotherapy. A retrospective single institutional study

OBJECTIVES

The relationship between glucose metabolism and tumor cellularity before chemo-radiotherapy in patients with head and neck squamous cell carcinoma (SCC) has never been compared with that of patients evaluated after treatment. This retrospective study analyzed the correlation between glucose metabolism parameters expressed by standardized uptake value (SUV) derived from 18F-fluorodeoxyglucose (18F-FDG) PET/CT and cellularity tumor parameters expressed by apparent diffusion coefficients (ADC) derived from diffusion-weighted (DW) MRI in untreated and treated patients with head and neck SCC.

METHODS

In 19 patients with no previous exposure to any treatment and 17 different chemo-radiotreated patients with head and neck SCC, we correlated the semi-quantitative uptake values (SUVmax, SUVpeak, and SUVmean) with the ADC functional parameters (ADCmin, ADCmean) including the standard deviation of ADC values (ADCsd).

RESULTS

No significant correlation was found between glucose metabolism parameters and ADCmin or ADCmean in untreated and treated patient groups. However, in untreated patients, significant inverse correlations were found between ADCsd and SUVmax (P = 0.039, r = -0.476), SUVpeak (P = 0.003, r = -0.652) and SUVmean (P = 0.039, r = -0.477). Analyses after chemo-radiotherapy in 17 patients showed no significant correlation between glucose metabolism parameters and DW MRI values, excluding a persistent significant (but lower intensity) inverse correlation between SUVpeak and ADCsd (P = 0.033, r = -0.519).

CONCLUSIONS

The demonstrated relationships suggest complex interactions especially between metabolic activity and heterogeneity of tumoral tissue, which might play a complementary role in the assessment of head and neck SCC.

TRIAL DATE OF REGISTRATION AND REGISTRATION NUMBER

Our retrospective study was registered on April 9th, 2020 by the Ethics Committee of the Coordinating Center "Area Vasta Nord Ovest" (CEAVNO) with Registration Number CEAVNO09042020.

Radiomics of apparent diffusion coefficient maps to predict histologic grade in squamous cell carcinoma of the oral tongue and floor of mouth: a preliminary study

BACKGROUND

Histologic grade assessment plays an important part in the clinical decision making and prognostic evaluation of squamous cell carcinoma (SCC) of the oral tongue and floor of mouth (FOM).

PURPOSE

To assess the value of apparent diffusion coefficient (ADC)-based radiomics in discriminating between low- and high-grade SCC of the oral tongue and FOM.

MATERIAL AND METHODS

We included data from 88 patients (training cohort: n = 59; testing cohort: n = 29) who underwent diffusion-weighted imaging with a 3.0-T magnetic resonance imaging scanner before treatment. A total of 526 radiomics features were extracted from ADC maps to construct a radiomics signature with least absolute shrinkage and selection operator logistic regression. Receiver operating characteristic curves and areas under the curve (AUCs) were used to evaluate the performance of radiomic signature.

RESULTS

Five features were selected to construct the radiomics signature for predicting histologic grade. The ADC-based radiomics signature performed well for discriminating between low- and high-grade tumors, with AUCs of 0.83 in both cohorts. Based on the cut-off value of the training cohort, the radiomics signature achieved accuracies of 0.78 and 0.79, sensitivities of 0.65 and 0.71, and specificities of 0.85 and 0.82 in the training and testing cohorts, respectively.

CONCLUSION

ADC-based radiomics can be a useful and promising non-invasive method for predicting histologic grade of SCC of the oral tongue and FOM.

Diffusion tensor imaging of oral carcinoma: Clinical evaluation and comparison with histopathological findings

PURPOSE

This study aims to assess the usefulness of diffusion tensor imaging (DTI) as a noninvasive method for the evaluation of histological grade and lymph node metastasis in patients with oral carcinoma (OC).

MATERIALS AND METHODS

Thirty-six consecutive patients with histologically confirmed OC underwent examination by 3-T MRI. DTI was performed using a single-shot echo-planar imaging sequence with b values of 0 and 1000 s/mm² and motion-probing gradients in 12 noncollinear directions. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) maps were compared with histopathological findings. The DTI parameters were correlated with the histological grade of the OCs based on the World Health Organization grading criteria and the presence or absence of lymph node metastasis.

RESULTS

The FA values (0.275 ± 0.058) of OC were significantly lower than those of normal tongue, muscle, and parotid glands (P < 0.001 for all), and the MD, AD, and RD values (1.220 ± 0.149, 1.434 ± 0.172, and 1.019 ± 0.165 × 10^-3 mm²/s, respectively) were significantly higher than their respective normal values (P < 0.001 for all). Significant inverse correlations with histological grades were shown for FA, MD, AD, and RD values in OC patients (r = -0.862, r = -0.797, r = -0.747, and r = -0.844, respectively; P < 0.001 for all). In addition, there was a significant difference in the FA values of metastatic and nonmetastatic lymph nodes (0.186 vs. 0.276), MD (0.923 vs. 1.242 × 10^-3 mm²/s), AD (1.246 vs. 1.621 × 10^-3 mm²/s), and RD (0.792 vs. 1.100 × 10^-3 mm²/s; P < 0.001 for all).

CONCLUSIONS

DTI may be clinically useful for the noninvasive evaluation of histological grade and lymph node metastasis in OC patients.

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.

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-weighted MRI: impact of the size of the ROI in detecting metastases in subcentimeter lymph nodes in head and neck squamous cell carcinoma

PURPOSE

Our aim is to determine the impact of the size of ROI in detecting subcentimeter metastatic lymph nodes in patients with head and neck squamous cell carcinoma (HNSCC). Secondary aim is to determine the impact of the histopathologic grade of the primary cancer on the ADC value of the metastatic nodes.

METHODS

The prospective study included 51 patients with histopathologically proven HNSCC at the primary site. Primary site includes oral cavity, oropharynx, larynx, and hypopharynx. ADC values of the lymph nodes were measured on ADC maps by placing two ROIs in the lymph nodes (0.2 cm² in the center of the node and the whole node). Lymph nodes were dissected by levels, marked by the surgeon, and sent to the pathologist.

RESULTS

By applying a smaller ROI, ADC values have greater sensitivity, specificity, NPV, PPV, and AUC in detecting metastasis compared to the ADC value of the entire node (88.0%, 80.73%, 90.7%, 75.9%, 0.912% versus 80.0%, 77.98%, 85% ,71.4%, and 0.819%, respectively) p < 0.001. Statistically significant negative correlation was established between the tumor grade and the ADC of lymph node at ROI 0.2 cm²and ROI of the whole lymph node (rho = - 0.425; p = 0.002, and rho = - 0.298; p = 0.038, respectively).

CONCLUSION

ROI size affects the ADC value of the nodes. The higher histopathological grade of the primary tumor is inversely correlated with the ADC value of the lymph nodes.

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.

Application of diffusion-weighted MR imaging with ADC measurement for distinguishing between the histopathological types of sinonasal neoplasms

PURPOSE

To evaluate the potential contribution of quantitative DWI parameters including ADC_mean and ADC_ratio values to help in distinguishing the histopathological types of sinonasal neoplasms.

METHODS

This retrospective study included 83 patients (50 males, 33 females; mean age 61 years) with pathologically proven untreated sinonasal neoplasms who have undergone diffusion-weighted MRI imaging from February 2010 to August 2017. Diffusion-weighted MRI was performed on a 3 T unit with b factors of 0 and 1000 s/mm², and ADC maps were generated. Mean ADC values of sinonasal tumors and ADC ratios (ADC_mean of the tumor to ADC_mean of pterygoid muscles) were compared with the histopathological diagnosis by utilizing the Kruskal-Wallis non-parametric test.

RESULTS

Mean ADC_mean and ADC_ratio were 0.8 (SD, ±0.4) × (10^-3 mm²/s) and 1.2 (SD, ±0.5), respectively, and each parameter was significantly different between histopathological types (p < 0.05). Mean ADC_mean and ADC_ratio were higher in adenoid cystic carcinoma (ACC) than in SCC, lymphoma, neuroendocrine carcinoma and sinonasal undifferentiated carcinoma (SNUC) (p < 0.05). Optimized ADC_mean thresholds of 0.79, 0.81, 0.74 and 0.78 (10^-3 mm²/s) achieved maximal discriminatory accuracies of 100%, 79%, 100% and 89% for ACC/SNUC, ACC/SCC, ACC/neuroendocrine carcinoma, and ACC/lymphoma, respectively.

CONCLUSIONS

The optimized ADC_mean threshold of 0.80 (10^-3 mm²/s) could be used to differentiate ACC from non-ACC sinonasal neoplasms with maximal discriminatory accuracy (82%) and sensitivity of 100%. However, there is considerable overlapping of the ADC_mean and ADC_ratio values among non-ACC sinonasal neoplasms hence surgical biopsy is still needed.

The utility of MRI histogram and texture analysis for the prediction of histological diagnosis in head and neck malignancies

BACKGROUND

To assess the utility of histogram and texture analysis of magnetic resonance (MR) fat-suppressed T2-weighted imaging (Fs-T2WI) for the prediction of histological diagnosis of head and neck squamous cell carcinoma (SCC) and malignant lymphoma (ML).

METHODS

The cases of 57 patients with SCC (45 well/moderately and 12 poorly differentiated SCC) and 10 patients with ML were retrospectively analyzed. Quantitative parameters with histogram features (relative mean signal, coefficient of variation, kurtosis and skewness) and gray-level co-occurrence matrix (GLCM) features (contrast, correlation, energy and homogeneity) were calculated using Fs-T2WI data with a manual tumor region of interest (ROI).

RESULTS

The following significantly different values were obtained for the total SCC versus ML groups: relative mean signal (3.65 ± 0.86 vs. 2.61 ± 0.49), contrast (72.9 ± 16.2 vs. 49.3 ± 8.7) and homogeneity (2.22 ± 0.25 × 10^- 1 vs. 2.53 ± 0.12 × 10^- 1). In the comparison of the SCC histological grades, the relative mean signal and contrast were significantly lower in the poorly differentiated SCC (2.89 ± 0.63, 56.2 ± 12.9) compared to the well/moderately SCC (3.85 ± 0.81, 77.5 ± 13.9). The homogeneity in poorly differentiated SCC (2.56 ± 0.15 × 10^- 1) was higher than that of the well/moderately SCC (2.1 ± 0.18 × 10^- 1).

CONCLUSIONS

Parameters obtained by histogram and texture analysis of Fs-T2WI may be useful for noninvasive prediction of histological type and grade in head and neck malignancy.

Adaptive Boost Target Definition in High-Risk Head and Neck Cancer Based on Multi-imaging Risk Biomarkers

PURPOSE

Positron emission tomography with ¹⁸F-deoxyglucose (FDG), dynamic contrast-enhanced magnetic resonance imaging (MRI), and diffusion-weighted MRI each identify unique risk factors for treatment outcomes in head and neck cancer (HNC). Clinical trials in HNC largely rely on a single imaging modality to define targets for boosting. This study aimed to investigate the spatial correspondence of FDG uptake, perfusion, and the apparent diffusion coefficient (ADC) in HNC and their response to chemoradiation therapy (CRT) and to determine the implications of this overlap or lack thereof for adaptive boosting.

METHODS AND MATERIALS

Forty patients with HNC enrolled in a clinical trial underwent FDG positron emission tomography-computed tomography before CRT and underwent dynamic contrast-enhanced and diffusion-weighted MRI scans before and during CRT. The gross tumor volume (GTV) of the primary tumor was contoured on post-gadolinium T1-weighted images. Tumor subvolumes with high FDG uptake, low blood volume (BV), and low ADC were created by using previously established thresholds. Spatial correspondences between subvolumes were analyzed using the Dice coefficient, and those between each pair of image parameters at voxel level were analyzed by Spearman rank correlation coefficients.

RESULTS

Prior to CRT, the median subvolumes of high FDG, low BV, and low ADC relative to the primary GTV were 20%, 21%, and 45%, respectively. Spearman correlation coefficients between BV and ADC varied from -0.47 to 0.22; between BV and FDG, from -0.08 to 0.59; and between ADC and FDG, from -0.68 to 0.25. Dice coefficients between subvolumes of FDG and BV, FDG and ADC, and BV and ADC were 10%, 46%, and 15%, respectively. The union of the 3 parameters was 64% of the GTV. The union of the subvolumes of BV and ADC was 56% of the GTV before CRT but was reduced significantly by 57% after 10 fractions of radiation therapy.

CONCLUSIONS

High FDG uptake, low BV, and low ADC as imaging risk biomarkers of HNC identify largely distinct tumor characteristics. A single imaging modality may not define the boosting target adequately.

Multiparametric magnetic resonance imaging in mucosal primary head and neck cancer: a prospective imaging biomarker study

BACKGROUND

Radical radiotherapy, with or without concomitant chemotherapy forms the mainstay of organ preservation approaches in mucosal primary head and neck cancer. Despite technical advances in cancer imaging and radiotherapy administration, a significant proportion of patients fail to achieve a complete response to treatment. For those patients who do achieve a complete response, acute and late toxicities remain a cause of morbidity. A critical need therefore exists for imaging biomarkers which are capable of informing patient selection for both treatment intensification and de-escalation strategies.

METHODS/DESIGN

A prospective imaging study has been initiated, aiming to recruit patients undergoing radical radiotherapy (RT) or chemoradiotherapy (CRT) for mucosal primary head and neck cancer (MPHNC). Eligible patients are imaged using FDG-PET/CT before treatment, at the end of week 3 of treatment and 12 weeks after treatment completion according to local imaging policy. Functional MRI using diffusion weighted (DWI), blood oxygen level-dependent (BOLD) and dynamic contrast enhanced (DCE) sequences is carried out prior to, during and following treatment. Information regarding treatment outcomes will be collected, as well as physician-scored and patient-reported toxicity.

DISCUSSION

The primary objective is to determine the correlation of functional MRI sequences with tumour response as determined by FDG-PET/CT and clinical findings at 12 weeks post-treatment and with local control at 12 months post-treatment. Secondary objectives include prospective correlation of functional MRI and PET imaging with disease-free survival and overall survival, defining the optimal time points for functional MRI assessment of treatment response, and determining the sensitivity and specificity of functional MRI sequences for assessment of potential residual disease following treatment. If the study is able to successfully characterise tumours based on their functional MRI scan characteristics, this would pave the way for further studies refining treatment approaches based on prognostic and predictive imaging data.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12616000534482 (26 April 2016).

State of the art MRI in head and neck cancer

Head and neck cancer affects more than 11,000 new patients per year in the UK¹ and imaging has an important role in the diagnosis, treatment planning, and assessment, and post-treatment surveillance of these patients. The anatomical detail produced by magnetic resonance imaging (MRI) is ideally suited to staging and follow-up of primary tumours and cervical nodal metastases in the head and neck; however, anatomical images have limitations in cancer imaging and so increasingly functional-based MRI techniques, which provide molecular, metabolic, and physiological information, are being incorporated into MRI protocols. This article reviews the state of the art of these functional MRI techniques with emphasis on those that are most relevant to the current management of patients with head and neck cancer.

Utility of a Hybrid IVIM-DKI Model to Predict the Development of Distant Metastasis in Head and Neck Squamous Cell Carcinoma Patients

Purpose:

To evaluate the diagnostic power of hybrid intravoxel incoherent motion (IVIM)-diffusion kurtosis imaging (DKI) model parameters in pretreatment for the prediction of future distant metastasis in head and neck squamous cell carcinoma (HNSCC) patients.

Materials and Methods:

We retrospectively evaluated 49 HNSCC patients who underwent curative chemoradiation therapy. Diffusion-weighted image (DWI) acquired by single-shot spin-echo echo-planar imaging with 12 b-values (0–2000) was performed in all patients before any treatment. We calculated the IVIM-DKI parameters and the conventional apparent diffusion coefficient (ADC) in the ROI placed on the primary lesion. The presence of future distant metastasis was determined by histological findings or clinical follow-up.

Results:

A univariate analysis revealed significant differences between the patients with distant metastasis and those without in slow diffusion coefficient (D) and kurtosis value (K). Highest diagnostic accuracy was obtained by the D value. In addition, a multivariate analysis revealed that the D value was an independent predictor of future distant metastasis.

Conclusion:

The D and K values obtained by this hybrid IVIM-DKI model can be one of the diagnostic tools for the prediction of future distant metastasis in HNSCC patients.

Apparent diffusion coefficient for discriminating metastatic lymph nodes in patients with squamous cell carcinoma of the head and neck

PURPOSE

We aimed to evaluate the apparent diffusion coefficient (ADC) values of metastatic lymph nodes in patients with squamous cell carcinoma (SCC) of the head and neck.

METHODS

Patients with metastatic lymph nodes underwent 1.5 Tesla diffusion-weighted magnetic resonance imaging (MRI). The ADC values of the histologically proven metastases were evaluated retrospectively and mean ADC values were compared using one-way analysis of variance test. Receiver operating characteristic analysis was performed to identify ADC threshold values.

RESULTS

We included 33 patients (27 males, 6 females; mean age, 60.7 years) with 53 metastatic lymph nodes in the study. Mean ADC values for nodal metastases of nasopharyngeal carcinoma (NPC) (n=7), oropharyngeal (n=12), laryngeal (n=27), and hypopharyngeal (n=7) carcinoma were (0.810±0.158)×10-3 mm2/s, (0.985±0.099)×10-3 mm2/s, (1.037±0.150)×10-3 mm2/s, and (0.948±0.081)×10-3 mm2/s, respectively. The mean ADC values of nodal metastases of NPC were significantly lower than ADC values of laryngeal carcinoma (LSCC) (P = 0.002). An ADC value less than 0.890×10-3 mm2/s was found to facilitate differentiation of NPC from LSCC with a sensitivity of 71% and specificity of 85% (area under the curve, 0.852).

CONCLUSION

The mean ADC values showed significant differences between nodal metastases of NPC and LSCC. Considering SCCs as a single group may affect the accuracy of ADC-based differentiation. Location of the primary tumor should be taken into account and cutoff values should be determined separately for each anatomical location.

Squamous cell carcinoma of the oral cavity and oropharynx: what does the apparent diffusion coefficient tell us about its histology?

Background Diffusion-weighted imaging obtained with magnetic resonance (DW-MRI) is a non-invasive imaging tool potentially able to provide information about microstructural tumor characteristics. Purpose To prospectively analyze the correlation between the apparent diffusion coefficient (ADC) and clinical-histologic characteristics of squamous cell carcinoma (SCCA) of the oral cavity and oropharynx. Material and Methods Sixty-seven patients with untreated, histologically proven SCCA of the oral cavity and oropharynx underwent conventional and diffusion-weighted (b-values 0, 50, 250, 500, and 900 s/mm²) MRI. Tumor ADC was calculated from regions of interest drawn manually on the highest b-value images using ImageJ (ImageJ, NIH) and fsl (fsl 4, University of Oxford) image processing packages. ADC was calculated in two ways: standard ADC using all b-values; and ADC^High using only b-values ≥ 250 s/mm². We assessed the correlations between both ADC and ADC^High and the clinical-histological characteristics of SCCA. Results Fifty-two patients (36 men, 16 women; mean age, 55 ± 13 years) were suitable for ADC calculation. Mean ADC was 1136.0 ± 108.5 × 10^-6mm²/s. Mean tumor ADC^High was 991.2 ± 152.1 × 10^-6mm²/s. Mean tumor size was 32.3 ± 13.4 mm (range, 14.0-69.0 mm). We observed no correlation of either ADC or ADC^High values with any of the clinical-histological tumor characteristics. Undifferentiated tumors (G3) showed lower apparent diffusion coefficient values compared to differentiated ones (G1-G2), without reaching statistical significance. Conclusion We did not observe any statistically significant correlation between ADC values and clinical-histological characteristics of SCCA of the oral cavity and oropharynx.

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

Pre-treatment or early intra-treatment prediction of patients with head and neck squamous cell carcinomas (HNSCC) who are likely to have tumours that are resistant to chemoradiotherapy (CRT) would enable treatment regimens to be changed at an early time point, or allow patients at risk of residual disease to be targeted for more intensive post-treatment investigation. Research into the potential advantages of using functional-based magnetic resonance imaging (MRI) sequences before or during cancer treatments to predict treatment response has been ongoing for several years. In regard to HNSCC, the reported results from functional MRI research are promising but they have yet to be transferred to the clinical domain. This article will review the functional MRI literature in HNSCC to determine the current status of the research and try to identify areas that are close to application in clinical practice. This review will focus on diffusion-weighted imaging (DWI) and dynamic contrast-enhanced MRI (DCE–MRI) and briefly include proton magnetic resonance spectroscopy (¹H-MRS)and blood oxygen level dependent (BOLD) MRI.

High b-Value Diffusion MRI to Differentiate Recurrent Tumors from Posttreatment Changes in Head and Neck Squamous Cell Carcinoma: A Single Center Prospective Study

Recently DW-MR Imaging has shown promising results in distinguishing between recurrent tumors and posttreatment changes in Head and Neck Squamous Cell Carcinoma (HNSSC). Aim of this study was to evaluate the diagnostic performances of DWI at high b-value (b = 2000 s/mm²) compared to standard b-value (b = 1000 s/mm²) and ADC_ratio values (ADC_ratio = ADC₂₀₀₀/ADC₁₀₀₀ × 100) to differentiate recurrent tumors from posttreatment changes after treatment of HSNCC. 20 patients (16 M, 4 F) underwent MR Imaging between 2 and 16 months (mean 7) after treatment. Besides morphological sequences, we performed single-shot echo-planar DWI at b = 1000 s/mm² and b = 2000 s/mm², and corresponding ADC maps were generated (ADC₁₀₀₀ and ADC₂₀₀₀, resp.). By considering contrast-enhanced T1-weighted images as references, ROIs were drawn in order to evaluate mean ADC₁₀₀₀, ADC₂₀₀₀, and ADC_ratio. The mean ADC₁₀₀₀ and ADC₂₀₀₀ in recurrent tumors were significantly lower than those in posttreatment changes (P = 0.001 and P = 0.016, resp.). Moreover, the mean ADC_ratio between the two groups showed a statistically significant difference (P = 0.002). Sensitivity, specificity, and accuracy of ADC_ratio were 82.0%, 100%, and 90%, respectively, by considering an optimal cutoff value of 65.5%. ADC_ratio is a promising value to differentiate between recurrent tumors and posttreatment changes in HNSCC and may be more useful than ADC₁₀₀₀ and ADC₂₀₀₀.

Squamous Cell Carcinoma of the Head and Neck: Comparison of Diffusion-weighted MRI at b-values of 1,000 and 2,000 s/mm(2) to Predict Response to Induction Chemotherapy

PURPOSE

Recent publications have reported contradictory results of pretreatment diffusion-weighted magnetic resonance imaging (DWI) for the prediction of chemoradiotherapeutic response in primary squamous cell carcinomas of the head and neck (HNSCC). Therefore, we evaluated the diagnostic performance of DWI obtained with both standard (b = 0 and 1,000 s/mm²) and high (b = 0 and 2,000 s/mm²) b-values for predicting response to induction chemotherapy in HNSCCs.

METHODS

For 25 patients with primary HNSCC who underwent DWI with both standard and high b-values prior to treatment, we calculated corresponding apparent diffusion coefficient (ADC) maps. Regions of interest containing the tumor were drawn on every section of ADC maps and summated to make volume-based data of the entire tumor. Histogram parameters (mean ADC, kurtosis, and skewness) were correlated with treatment response using unpaired Student t test. Univariate and multivariate analysis of the ADC parameters, patient age, sex, whole tumor volume, and T stage were also performed to predict tumor response to induction chemotherapy.

RESULTS

Response to induction chemotherapy was good in 13 of the 25 patients and poor in 12. The mean ADC values of good responders at standard b-value (ADC1000), 1.23 ± 0.34 (× 10⁻³ mm²/s), and high b-value (ADC2000), 0.62 ± 0.14 (× 10⁻³ mm²/s), were lower than those of poor responders (ADC1000, 1.32 ± 0.28 [× 10⁻³ mm²/s]; ADC2000, 0.76 ± 0.15 [× 10⁻³ mm²/s]), but significant difference was achieved only at the ADC2000 map (P = 0.02). In addition, mean tumor volume prior to treatment of good responders was smaller than that of poor responders. However, at multiple logistic regression analysis, only the mean ADC2000 value remained as a significant predictor of response to induction chemotherapy.

CONCLUSION

DWI with high b-values (b = 0 and 2,000 s/mm²) as an assessment of ADC values may help predict tumor response to neoadjuvant chemotherapy for primary HNSCCs.

Diffusion-weighted MRI of epithelial ovarian cancers: correlation of apparent diffusion coefficient values with histologic grade and surgical stage

OBJECTIVE

The purpose of this article is to correlate the apparent diffusion coefficient (ADC) values of epithelial ovarian cancers with histologic grade and surgical stage.

MATERIALS AND METHODS

We enrolled 43 patients with pathologically proven epithelial ovarian cancers for this retrospective study. All patients underwent preoperative pelvic magnetic resonance imaging (MRI) including diffusion-weighted images with b value of 0 and 1000 s/mm2 at 3.0-T unit. The mean ADC values of the solid portion of the tumor were measured and compared among different histologic grades and surgical stages.

RESULTS

The mean ADC values of epithelial ovarian cancers differed significantly between grade 1 (well-differentiated) and grade 2 (moderately-differentiated) (P=0.013) as well as between grade 1 and grade 3 (poorly-differentiated) (P=0.01); however, no statistically significant difference existed between grade 2 and grade 3 (P=0.737). The receiver-operating characteristic analysis indicated that a cutoff ADC value of less than or equal to 1.09×10(-3)mm2/s was associated with 94.4% sensitivity and 85.7% specificity in distinguishing grade 1 and grade 2/3 cancer. The difference in mean ADC values was statistically significant for early stage (FIGO stage I) and advanced stage (FIGO stage II-IV) cancer (P=0.011). The interobserver agreement for the mean ADC values of epithelial ovarian cancers was excellent.

CONCLUSION

The mean ADC values of the solid portion of epithelial ovarian cancers negatively correlated to histologic grade and surgical stage. The mean ADC values may be useful imaging biomarkers for assessment of tumor grade of epithelial ovarian cancer.

The role of diffusion-weighted magnetic resonance imaging in the diagnosis, lymph node staging and assessment of treatment response of head and neck cancer

Standard magnetic resonance imaging (MRI) and computed tomography continue to be the imaging modalities of choice in staging and reviewing patients with head and neck cancer. Diffusion-weighted MRI (DW-MRI) is an advanced imaging modality that records the molecular diffusion of protons and thus provides an opportunity to further assess tissue character. Interest in DW-MRI of the head and neck continues to grow, especially its application to the assessment and treatment of head and neck cancer. We highlight the potential role of DW-MRI in the delineation, characterization, and lymph node staging of head and neck tumours. Furthermore, we discuss the ability of DW-MRI to provide a real opportunity to differentiate post-treatment tumour recurrence from chemoradiotherapy-induced local tissue changes. The future impact of these findings upon the clinical practice of the head and neck surgeon is discussed.

Whole body MRI: improved lesion detection and characterization with diffusion weighted techniques

Diffusion-weighted imaging (DWI) is an established functional imaging technique that interrogates the delicate balance of water movement at the cellular level. Technological advances enable this technique to be applied to whole-body MRI. Theory, b-value selection, common artifacts and target to background for optimized viewing will be reviewed for applications in the neck, chest, abdomen, and pelvis. Whole-body imaging with DWI allows novel applications of MRI to aid in evaluation of conditions such as multiple myeloma, lymphoma, and skeletal metastases, while the quantitative nature of this technique permits evaluation of response to therapy. Persisting signal at high b-values from restricted hypercellular tissue and viscous fluid also permits applications of DWI beyond oncologic imaging. DWI, when used in conjunction with routine imaging, can assist in detecting hemorrhagic degradation products, infection/abscess, and inflammation in colitis, while aiding with discrimination of free fluid and empyema, while limiting the need for intravenous contrast. DWI in conjunction with routine anatomic images provides a platform to improve lesion detection and characterization with findings rivaling other combined anatomic and functional imaging techniques, with the added benefit of no ionizing radiation.

Differentiation of recurrent tumor and posttreatment changes in head and neck squamous cell carcinoma: application of high b-value diffusion-weighted imaging

BACKGROUND AND PURPOSE

High b-value DWI has been expected to have an additional diagnostic role and demonstrated some promising results in head and neck cancer. The aim of this study was to evaluate the diagnostic performance of DWI at a high b-value (b=2000 s/mm(2)) compared with a standard b-value (b=1000 s/mm(2)) and the ratio of ADC values of high and standard b-values for their ability to differentiate between recurrent tumor and posttreatment changes after the treatment of head and neck squamous cell carcinoma.

MATERIALS AND METHODS

A total of 33 patients diagnosed with head and neck squamous cell carcinoma were enrolled in the present study; all had contrast-enhancing lesions on follow-up MR imaging. All patients underwent single-shot echo-planar DWI at b=1000 s/mm(2) and b=2000 s/mm(2), and corresponding ADC maps were generated (ADC1000 and ADC2000, respectively). The mean ADC1000, ADC2000, and ADCratio (ADCratio = ADC2000/ADC1000 × 100) values were evaluated within a manually placed ROI with contrast-enhanced T1-weighted images as references. For the statistical analysis, we performed a Student t test and multivariate logistic regression.

RESULTS

The mean ADC1000 in recurrent tumor was significantly lower than that in posttreatment changes (P < .001), whereas the mean ADC2000 resulted in no significant difference (P = .365). The mean ADCratio was significantly higher in recurrent tumor than that in posttreatment changes (73.5 ± 7.2% vs 56.9 ± 8.8%, respectively; P < .001). Multivariate logistic regression analysis revealed that the ADCratio was the only independently differentiating variable (P = .024). The sensitivity, specificity, and accuracy of ADCratio were 95.0%, 69.2%, and 84.8%, respectively, by use of the optimal cutoff value of 62.6%.

CONCLUSIONS

We suggest that the ADCratio calculated from the ADC1000 and ADC2000 is a promising value for the differentiation of recurrent tumor and posttreatment changes in head and neck squamous cell carcinoma.