Associations between Histogram Analysis Parameters Derived from DCE-MRI and Histopathological Features including Expression of EGFR, p16, VEGF, Hif1-alpha, and p53 in HNSCC

Abstract

Background Our purpose was to elucidate possible correlations between histogram parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) with several histopathological features in head and neck squamous cell carcinomas (HNSCC). Methods Thirty patients with primary HNSCC were prospectively acquired. Histogram analysis was derived from the DCE-MRI parameters: Ktrans, Kep, and Ve. Additionally, in all cases, expression of human papilloma virus (p16) hypoxia-inducible factor-1-alpha (Hif1-alpha), vascular endothelial growth factor (VEGF), epidermal growth factor receptor (EGFR), and tumor suppressor protein p53 were estimated. Results K ep kurtosis was significantly higher in p16 tumors, and Ve min was significantly lower in p16 tumors compared to the p16 negative tumors. In the overall sample, Kep entropy correlated well with EGFR expression (p=0.38, P=0.04). In p16 positive carcinomas, Ktrans max correlated with VEGF expression (p=0.46, P=0.04), Ktrans kurtosis correlated with Hif1-alpha expression (p=0.46, P=0.04), and Ktrans entropy correlated with EGFR expression (p=0.50, P=0.03). Regarding Kep parameters, mode correlated with VEGF expression (p=0.51, P=0.02), and entropy correlated with Hif1-alpha expression (p=0.47, P=0.04). In p16 negative carcinomas, Kep mode correlated with Her2 expression (p=−0.72, P=0.03), Ve max correlated with p53 expression (p=−0.80, P=0.009), and Ve p10 correlated with EGFR expression (p=0.68, P=0.04). Conclusion DCE-MRI can reflect several histopathological features in HNSCC. Associations between DCE-MRI and histopathology in HNSCC depend on p16 status. Kep kurtosis and Ve min can differentiate p16 positive and p16 negative carcinomas.

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

“…Recent studies reported that diffusion-weighted imaging (DWI) may help predict HPV status in patients with OPSCC, as HPV-positive OPSCC reveals a low mean apparent diffusion coefficient (ADC) compared with HPV-negative OPSCC 9 – 11 . Furthermore, a histogram analysis based on dynamic contrast-enhanced MR image showed significantly higher K ep kurtosis values and lower V e min values in patients with p16-positive OPSCC 12 . Recently, several published studies had addressed the prediction of HPV status employing a CT-based radiomics approach; however, their diagnostic performance was moderate (area under the curve; AUC, 0.75–0.80) 13 – 15 .…”

Correlation between histogram-based DCE-MRI parameters and 18F-FDG PET values in oropharyngeal squamous cell carcinoma: Evaluation in primary tumors and metastatic nodes

“…Considering the volume of data that can be derived from both histology and functional imaging, radiologists and clinicians should be aware of the different potential roles of several biomarkers with respect to specific clinical end points. To this purpose, a number of reports have recently evaluated the complementarity and/or associations between imaging and histopathological features in HNSCC [10][11][12][13][14][15], as well as in different malignancies, i.e. breast cancer, lung adenocarcinoma and glioma [16][17][18].…”

Correlation Between Quantitative Perfusion Histogram Parameters of DCE-MRI and PTEN, P-Akt and m-TOR in Different Pathological Types of Lung Cancer

“…The disadvantage of these methods is that they need invasive methods to obtain tissue samples, local samples often can't re ect the whole tumor situation, and samples in vitro can't really re ect the metabolism situation in vivo. DCE-MRI quantitative perfusion histogram can detect the metabolic activity inside the tumor from the molecular level based on the gray-scale intensity information of the lesion site and describe the heterogeneity of the lesion [8][9][10]. Therefore, the purpose of this study is to investigate the correlation between the DCE-MRI histogram parameters and PTEN, P-Akt, and m-TOR of lung cancer, so as to provide a basis for non-invasive prediction of P13K / Akt / mTOR signal pathway gene activation in lung cancer tissue by DCE-MRI histogram parameters.…”