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

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

Background and purpose

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

Materials and methods

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

Results

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

Conclusions

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

The therapeutic utility of combining dynamic contrast-enhanced magnetic resonance imaging with arterial spin labeling in the staging of nasopharyngeal carcinoma

BACKGROUND

To research the pathological and clinical staging uses of arterial spin labeling (ASL) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

MATERIALS AND METHODS

64 newly diagnosed nasopharyngeal carcinoma (NPC) patients were enrolled from December 2020 to January 2022, and 3.0 T MRI (Discovery 750W, GE Healthcare, USA) were used for ASL and DCE-MRI scans. The DCE-MRI and ASL raw data were processed post-acquisition on the GE image processing workstation (GE Healthcare, ADW 4.7, USA). The volume transfer constant (Ktrans), blood flow (BF), and accompanying pseudo-color images were generated automatically. Draw the region of interest (ROIs), and the Ktrans and BF values for each ROI were recorded separately. Based on pathological information and the most recent AJCC staging criteria, patients were divided into low T stage groups = T_1-2 and high T stage groups = T_3-4, low N stage groups = N_0-1 and high N stage groups = N_2-3, and low AJCC stage group = stage I-II and high AJCC stage group = stage III-IV. The association between the Ktrans_t and BF parameters and the T, N, and AJCC stages was compared using an independent sample t-test. Using a receiver operating characteristic (ROC) curve, the sensitivity, specificity, and AUC of Ktrans_t, BF_t, and their combined use in T and AJCC staging of NPC were investigated and assessed.

RESULT

The tumor-BF (BF_t) (t = - 4.905, P < 0.001) and tumor-Ktrans (Ktrans_t) (t = - 3.113, P = 0.003) in the high T stage group were significantly higher than those in the low T stage group. The Ktrans_t in the high N stage group was significantly higher than that in the low N stage group (t = - 2.071, P = 0.042). The BF_t (t = - 3.949, P < 0.001) and Ktrans_t (t = - 4.467, P < 0.001) in the high AJCC stage group were significantly higher than those in the low AJCC stage group. BF_t was moderately positively correlated with the T stage (r = 0.529, P < 0.001) and AJCC stage (r = 0.445, P < 0.001). Ktrans_t was moderately positively correlated with T staging (r = 0.368), N staging (r = 0.254), and AJCC staging (r = 0.411). There was also a positive correlation between BF and Ktrans in gross tumor volume (GTV) (r = 0.540, P < 0.001), parotid (r = 0.323, P < 0.009) and lateral pterygoid muscle (r = 0.445, P < 0.001). The sensitivity of the combined application of Ktrans_t and BF_t for AJCC staging increased from 76.5 and 78.4 to 86.3%, and the AUC value increased from 0.795 and 0.819 to 0.843, respectively.

CONCLUSION

Combining Ktrans and BF measures may make it possible to identify the clinical stages in NPC patients.

Evaluation of Proton MR Spectroscopy for the Study of the Tongue Tissue in Healthy Subjects and Patients With Tongue Squamous Cell Carcinoma: Preliminary Findings

Purpose

To noninvasively assess spectroscopic and metabolic profiles of healthy tongue tissue and in an exploratory objective in nontreated and treated patients with tongue squamous cell carcinoma (SCC).

Methods

Fourteen healthy subjects (HSs), one patient with nontreated tongue SCC (NT-SCC), and two patients with treated tongue SCC (T-SCC) underwent MRI and single-voxel proton magnetic resonance spectroscopy (1H-MRS) evaluations (3 and 1.5T). Multi-echo-times 1H-MRS was performed at the medial superior part (MSP) and the anterior inferior part (AIP) of the tongue in HS, while 1H-MRS voxel was placed at the most aggressive part of the tumor for patients with tongue SCC. 1H-MRS data analysis yielded spectroscopic metabolite ratios quantified to total creatine.

Results

In HS, compared to MSP and AIP, 1H-MRS spectra revealed higher levels of creatine, a more prominent and well-identified trimethylamine-choline (TMA-Cho) peak. However, larger prominent lipid peaks were better differentiated in the tongue MSP. Compared to HS, patients with NT-SCC exhibited very high levels of lipids and relatively higher values of TMA-Cho peak. Interestingly, patients with T-SCC showed almost nonproliferation activity. However, high lipids levels were measured, although they were relatively lower than lipids levels measured in patients with NT-SCC.

Conclusion

The present study demonstrated the potential use of in-vivo1H-MRS to noninvasively assess spectroscopic and metabolic profiles of the healthy tongue tissue in a spatial location-dependent manner. Preliminary results revealed differences between HS and patients with tongue NT-SCC as well as tongue T-SCC, which should be confirmed with more patients. 1H-MRS could be included, in the future, in the arsenal of tools for treatment response evaluation and noninvasive monitoring of patients with tongue SCC.

Preoperative Prediction of the Aggressiveness of Oral Tongue Squamous Cell Carcinoma with Quantitative Parameters from Dual-Energy Computed Tomography

Objectives

To determine whether quantitative parameters derived from dual-energy computed tomography (DECT) were predictive of the aggressiveness of oral tongue squamous cell carcinoma (OTSCC) including the pathologic stages, histologic differentiation, lymph node status, and perineural invasion (PNI).

Methods

Between August 2019 and March 2021, 93 patients (mean age, 54.6 ± 13.8 years; 66 men) with pathologically diagnosed OTSCC were enrolled in this prospective study. Preoperative DECT was performed and quantitative parameters (e.g., slope of the spectral Hounsfield unit curve [λ_Hu], normalized iodine concentration [nIC], normalized effective atomic number [nZ_eff], and normalized electron density [nRho]) were measured on arterial phase (AP) and venous phase (VP) DECT imaging. Quantitative parameters from DECT were compared between patients with different pathologic stages, histologic differentiation, lymph node statuses, and perineural invasion statuses. Logistic regression analysis was utilized to assess independent parameters and the diagnostic performance was analyzed by the receiver operating characteristic curves (ROC).

Results

λ_Hu and nIC in AP and λ_Hu, nZ_eff, and nIC in VP were significantly lower in stage III–IV lesions than in stage I–II lesions (p < 0.001 to 0.024). λ_Hu in VP was an independent predictor of tumor stage with an odds ratio (OR) of 0.29, and area under the curve (AUC) of 0.80. λ_Hu and nIC were higher in well-differentiated lesions than in poorly differentiated lesions (p < 0.001 to 0.021). The nIC in VP was an independent predictor of histologic differentiation with OR of 0.31, and AUC of 0.78. λ_Hu and nIC in VP were lower in OTSCCs with lymph node metastasis than those without metastasis (p < 0.001 to 0.005). λ_Hu in VP was the independent predictor of lymph node status with OR of 0.42, and AUC of 0.74. No significant difference was found between OTSCCs without PNI and those with PNI in terms of the quantitative DECT parameters.

Conclusion

DECT can be a complementary means for the preoperative prediction of the aggressiveness of OTSCC.

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

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

Study on the Value of DCE-MRI in Differentiating Glossitis and Tongue Cancer and the Intratumour Heterogeneity

Objective

DCE-MRI is an imaging technique that reflects the blood perfusion status of the tissue’s microcirculation. The purpose of this article is to explore the clinical value of dynamic contrast-enhanced (DCE)-MRI in distinguishing benign and malignant tongue lesions and the internal heterogeneity of a tumour.

Methods

The patients were divided into a tongue cancer group (22 patients) and a glossitis group (7 patients) based on the pathology results. All of the patients underwent DCE-MRI examination.

Results

The results of this study showed that the volume transfer constant (Ktrans), rate constant (Kep), contrast enhancement ratio (CER) and initial area under the gadolinium contrast agent concentration time curve (IAUGG) values of the tongue cancer group were significantly higher than those of the glossitis group, and the difference was statistically significant (P < 0.05). However, the extravascular extracellular volume fraction (Ve), fractional plasma volume (fPV), maximum slope (MaxSlope), and bolus arrival time (BAT) values measured by DCE-MRI in the tongue cancer group were not significantly different from those in the glossitis group (P > 0.05). The results of this study showed that the Ktrans, Kep, and IAUGG values measured by DCE-MRI had a good ability to distinguish tongue inflammation from tumours and Ktrans threshold of 0.484 has the best discriminative ability among them. The mean Ktrans values of stage I–II lesions were significantly higher than that of stage III–IV lesion (p = 0.045).

Conclusion

DCE-MRI is effective in distinguishing between benign and malignant tongue lesions and the internal heterogeneity of the tumour; it is worth following up in a larger study.

Clinical Registration Number

Research registry 6393.