Dynamic snapshot gradient-echo imaging of head and neck malignancies: time dependency and quality of contrast-to-noise ratio

Quantitative parameters correlated well with differentiation of squamous cell carcinoma at head and neck: a study of dynamic contrast-enhanced MRI

Background

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is widely used for the diagnosis and prognostic assessment of head and neck squamous cell carcinoma (HNSCC). However, no research on grading HNSCC using DCE-MRI has been found. We hypothesize that DCE-MRI can grade the HNSCC non-invasively.

Purpose

To verify the hypothesis that DCE-MRI can grade the HNSCC non-invasively.

Material and Methods

Forty-two patients with histopathologically proved HNSCC from September 2013 to February 2016 were retrospectively analyzed. Chi-square test was used to compare patterns of time intensity curves (TICs) between well and poorly differentiated HNSCC. Two-sample t-test was performed to calculate the difference of volume transfer constant (Ktrans), extravascular extracellular volume fraction (Ve), and initial area under the curve (iAUC) between groups. The diagnostic ability and cut-off value were assessed by receiver operator characteristic analysis.

Results

Most TICs of HNSCC are type III; no difference between well and poorly differentiated HNSCC has been found ( P > 0.05). The value of Ktrans, Ve, and iAUC for well and poorly differentiated HNSCC are (0.218 ± 0.048; 0.383 ± 0.074) min−1, (0.605 ± 0.108; 0.712 ± 0.150), and (27.552 ± 6.238; 43.157 ± 9.148), respectively. Ktrans, Ve, and iAUC are higher in poorly differentiated HNSCC, compared with well differentiated HNSCC ( P < 0.001, 0.013, and < 0.001, respectively). Ktrans has the greatest diagnostic significance with Youden’s index being 0.859 by cut-off value 0.270 min−1. The diagnostic sensitivity and specificity were 95.0% and 90.9%, respectively.

Conclusion

The Ktrans, Ve, and iAUC of HNSCC can be reliable quantitative parameters for evaluating well and poorly differentiated HNSCC where Ktrans has the highest value.

The Role of Dynamic Contrast-Enhanced Magnetic Resonance Imaging Parameters in Head-Neck Tumors

We evaluated dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in various head-neck masses, some of which are very rare tumors whose DCE-MRI have not been published to date. The purpose of this study was to investigate DCE-MRI in the differentiation of benign versus malignant lesions and to evaluate the DCE-MRI parameters most predictive for malignancy. Forty-one head-neck tumors including parotid gland tumors in 41 patients were examined at gadolinium-enhanced dynamic MR imaging. There were 26 malignant and 15 benign tumors. DCE-MR images were obtained between four and six minutes. Time-signal intensity curves (TICs) of the tumors on dynamic MR images were plotted, and then time of peak enhancement ( Tpeak), and enhancement ratios (ER) with different times (such as ER30, ER60, ER90, ER120, ERmax) were also calculated. Data of the benign and malignant group with head-neck masses were compared by Mann-Whitney U-test. The mean values of time to peak ( Tpeak) were found to be significantly shorter for the malignant group than the benign tumors ( P<0.05). The mean enhancement rates of malignant lesions were ER30: 60.62±52.62, ER60: 105.65±56.26, ER90: 113.17±45.83, ER120: 116.59±46.75 and ERmax: 128.56±56.51 whereas the mean enhancement rate of benign lesions were ER30: 67.35±60.78, ER60: 79.79±63.33, ER90: 84.53±64.92, ER120: 88.41±67.07 and ERmax: 112.06±66.48. The mean signal intensity values of the 60th second (ER60) and 90th second (ER90) were significantly different from other values for predicting malignancy ( P<.05). The parameters obtained from the time-signal intensity curve are important in differentiating benign and malignant enhancing lesions in dynamic head-neck MR imaging. DCE-MRI cannot replace standard MR imaging sequences for evaluating head-neck masses, but in addition to routine MR imaging it will improve differentiation between benign and malignant lesions.

Dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) for differential diagnosis in head and neck cancers

PURPOSE

To examine the potential of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) for differential diagnosis of head and neck cancer.

METHODS AND MATERIALS

DCE-MRI was performed in 26 patients with untreated squamous cell carcinoma (SCC), 28 undifferentiated carcinoma (UD) and 8 lymphoma. DCE-MRI was analyzed with the pharmacokinetic model proposed by Tofts and Kermode to produce the three DCE parameters: k(trans), v(e) and v(p). Areas under the curve (AUC) at the initial 60 and 90s (AUC60 and AUC90) were also recorded. Histogram analysis was conducted to obtain the mean, 25%, 50%, 75% and 95% percentile values and the Kruskal-Wallis test was used to compare the DCE parameters between the three groups of cancer.

RESULTS

k(trans), AUC60 and AUC90 showed significant differences (p<0.01) between UD/SCC and UD/lymphoma, but not between SCC/lymphoma. The mean AUC90 demonstrated the highest accuracy of 78% (sensitivity of 68% and specificity of 88%) for distinguishing UD and SCC, and the 75% percentile AUC90 provided the highest accuracy of 97% (sensitivity of 100% and specificity of 88.5%) for distinguishing UD and lymphoma.

CONCLUSIONS

There are significant differences in the DCE parameters which show the potential for distinguishing UD from SCC or lymphoma.

An exploratory pilot study into the association between microcirculatory parameters derived by MRI-based pharmacokinetic analysis and glucose utilization estimated by PET-CT imaging in head and neck cancer

OBJECTIVES

To examine the feasibility of deriving quantitative microcirculatory parameters and to investigate the relationship between vascular and metabolic characteristics of head and neck tumours in vivo, using dynamic contrast-enhanced (DCE) MRI and fluorodeoxyglucose (FDG) PET imaging.

METHODS

Twenty-seven patients with primary squamous cell carcinoma (SCCA) underwent DCE-MRI and combined PET/CT imaging. DCE-MRI data were post-processed by using commercially available software. Transfer constant (K (trans)), extravascular extracellular blood volume (v (e)), transfer constant from the extracellular extravascular space to plasma (k (ep)) and iAUC (initial area under the signal intensity-time curve) were calculated. 3D static PET data were acquired and standardised uptake values (SUV) calculated.

RESULTS

All microcirculatory parameters in tumours were higher than in normal muscle tissue (P ≤ 0.0019). Significant correlations were shown between k (ep) and K (trans) (ρ = 0.77), v (e) and k (ep) (ρ = -0.7), and iAUC and v (e) (ρ = 0.53). Significant correlations were observed for SUV(mean) and v (e) as well as iAUC (ρ = 0.42 and ρ = 0.66, respectively). SUV(max) was significantly correlated with iAUC (ρ = 0.69).

CONCLUSIONS

The demonstrated relationships between vascular and metabolic characteristics of primary SCCA imply a complex interaction between vascular delivery characteristics and tumour metabolism. The lack of correlation between SUV and K (trans)/k (ep) suggests that both diagnostic techniques may provide complementary information.

New directions in head and neck imaging

Computerized tomography (CT) and magnetic resonance imaging (MRI), positron emission tomography (PET) and the hybrid modality of PET/CT are sensitive and reliable tools for detection and staging of head and neck cancers. This article describes the role of PET/CT in initial staging of head and neck squamous cell carcinoma, the utility of CT/MR perfusion imaging in qualitative analysis of tumor tissue, and the usefulness of diffusion weighted MR and dynamic contrast-enhanced MR imaging in head and neck oncological imaging.

Oral cavity cancer

The oral cavity is anterioly located and unique in the variety of tissues contained in this area. Although oral cancer screening may be done on clinical examination, imaging plays a critical role in staging and determination of deep margins for either tumor resectability or radiation planning. This article discusses the relevant anatomy on magnetic resonance imaging (MRI), including the lips and gingiva, floor of mouth, and oral tongue. This is followed by a discussion of standard MRI techniques, American Joint Committee on Cancer (AJCC) classification, and relevant MRI findings with discussion and imaging examples of carcinoma in major sites, including floor of mouth, oral tongue, buccal mucosa, bony upper alveolus, hard palate, and retromolar trigone. A brief summary of newer imaging techniques for evaluation of oral cancer is also presented.

Dynamic contrast-enhanced MR imaging

Dynamic contrast-enhanced magnetic resonance imaging is a useful clinical tool in evaluation of soft tissue neoplasm and lymph nodes in head and neck. It is thought to be a useful predictor of response to radiotherapy for head and neck carcinoma and used to monitor the treatment and distinguish post-therapeutic changes from recurrent mass with greater confidence. It can be used to distinguish between normal and malignant tissue and to differentiate a malignant lymphoma from other lymph nodal enlargements. The technique utilizes relative differences in microvasculature and microcirculation between malignant and non-malignant tissue to achieve greater contrast in signal imaging following bolus contrast administration. This article explains the underlying principles and imaging techniques for this new diagnostic tool. The clinical applications and technical challenges are discussed. The future challenges and some contradictions in results are also outlined.

Newer MR imaging techniques for head and neck

Dynamic and functional imaging techniques are being developed to improve the evaluation of various pathologic processes of the head and neck region. These techniques include dynamic contrast-enhanced MR imaging for evaluating soft tissue masses and cervical lymph nodes, the use of ultrasmall superparamagnetic iron oxide contrast agent, and functional techniques such as in vivo and in vitro MR spectroscopy of head and neck cancer and lymph nodes and apparent diffusion coefficient mapping of parotid glands. These techniques can help to differentiate nonmalignant tissue from malignant tumors and lymph nodes and can aid in differentiating residual malignancies from postradiation changes. From methodological development, they are making the critical transition to preclinical and clinical validating methods and eventually to widespread clinical tools.

Challenges in dynamic contrast-enhanced MRI imaging of cervical lymph nodes to detect metastatic disease

PURPOSE

To identify and overcome challenges in using dynamic contrast-enhanced magnetic resonance imaging (MRI) to distinguish tumor from nontumor in the cervical lymph nodes of patients with squamous cell carcinoma of the head and neck.

MATERIALS AND METHODS

Signal-to-noise ratio (S/N), motion, node heterogeneity, and tissue normalizations were examined. Twenty-one patients with squamous cell carcinoma of the head and neck were scanned before a neck dissection (two-dimensional fast spoiled gradient-echo: 10 locations/13 seconds). Peak time, peak enhancement, maximum upslope, and washout slope were measured in pathologically confirmed tumor and nontumor nodes and in the submandibular gland and the sternocleidomastoid muscle.

RESULTS

Surface coil arrays provided high coverage and high S/N. Motion averaged 1.1 pixels and was corrected. Large tumor nodes were heterogeneous in their contrast enhancement, while the nontumor nodes were homogeneous. The contrast enhancement parameters were significantly different for all regions except for the submandibular gland compared to the nontumor nodes.

CONCLUSION

Challenges of dynamic imaging of cervical lymph nodes were overcome and significant differences were found between the tumor and nontumor nodes, indicating that dynamic imaging is feasible and may aid this patient population.