Literature DB >> 28963049

Histogram analysis parameters identify multiple associations between DWI and DCE MRI in head and neck squamous cell carcinoma.

Hans Jonas Meyer1, Leonard Leifels1, Stefan Schob2, Nikita Garnov1, Alexey Surov3.   

Abstract

OBJECTIVE: Nowadays, multiparametric investigations of head and neck squamous cell carcinoma (HNSCC) are established. These approaches can better characterize tumor biology and behavior. Diffusion weighted imaging (DWI) can by means of apparent diffusion coefficient (ADC) quantitatively characterize different tissue compartments. Dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) reflects perfusion and vascularization of tissues. Recently, a novel approach of data acquisition, namely histogram analysis of different images is a novel diagnostic approach, which can provide more information of tissue heterogeneity. The purpose of this study was to analyze possible associations between DWI, and DCE parameters derived from histogram analysis in patients with HNSCC.
MATERIALS AND METHODS: Overall, 34 patients, 9 women and 25 men, mean age, 56.7±10.2years, with different HNSCC were involved in the study. DWI was obtained by using of an axial echo planar imaging sequence with b-values of 0 and 800s/mm2. Dynamic T1w DCE sequence after intravenous application of contrast medium was performed for estimation of the following perfusion parameters: volume transfer constant (Ktrans), volume of the extravascular extracellular leakage space (Ve), and diffusion of contrast medium from the extravascular extracellular leakage space back to the plasma (Kep). Both ADC and perfusion parameters maps were processed offline in DICOM format with custom-made Matlab-based application. Thereafter, polygonal ROIs were manually drawn on the transferred maps on each slice. For every parameter, mean, maximal, minimal, and median values, as well percentiles 10th, 25th, 75th, 90th, kurtosis, skewness, and entropy were estimated.
RESULTS: Сorrelation analysis identified multiple statistically significant correlations between the investigated parameters. Ve related parameters correlated well with different ADC values. Especially, percentiles 10 and 75, mode, and median values showed stronger correlations in comparison to other parameters. Thereby, the calculated correlation coefficients ranged from 0.62 to 0.69. Furthermore, Ktrans related parameters showed multiple slightly to moderate significant correlations with different ADC values. Strongest correlations were identified between ADC P75 and Ktrans min (p=0.58, P=0.0007), and ADC P75 and Ktrans P10 (p=0.56, P=0.001). Only four Kep related parameters correlated statistically significant with ADC fractions. Strongest correlation was found between Kep max and ADC mode (p=-0.47, P=0.008).
CONCLUSION: Multiple statistically significant correlations between, DWI and DCE MRI parameters derived from histogram analysis were identified in HNSCC.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  ADC; DCE MRI; DWI; Head and neck cancer; Histogram analysis

Mesh:

Substances:

Year:  2017        PMID: 28963049     DOI: 10.1016/j.mri.2017.09.015

Source DB:  PubMed          Journal:  Magn Reson Imaging        ISSN: 0730-725X            Impact factor:   2.546


  10 in total

1.  Histogram analysis derived from apparent diffusion coefficient (ADC) is more sensitive to reflect serological parameters in myositis than conventional ADC analysis.

Authors:  Hans Jonas Meyer; Alexander Emmer; Malte Kornhuber; Alexey Surov
Journal:  Br J Radiol       Date:  2018-02-20       Impact factor: 3.039

Review 2.  Metabolic and physiologic magnetic resonance imaging in distinguishing true progression from pseudoprogression in patients with glioblastoma.

Authors:  Sanjeev Chawla; Sultan Bukhari; Omar M Afridi; Sumei Wang; Santosh K Yadav; Hamed Akbari; Gaurav Verma; Kavindra Nath; Mohammad Haris; Stephen Bagley; Christos Davatzikos; Laurie A Loevner; Suyash Mohan
Journal:  NMR Biomed       Date:  2022-03-15       Impact factor: 4.478

3.  Histogram Analysis Parameters Derived from Conventional T1- and T2-Weighted Images Can Predict Different Histopathological Features Including Expression of Ki67, EGFR, VEGF, HIF-1α, and p53 and Cell Count in Head and Neck Squamous Cell Carcinoma.

Authors:  Hans Jonas Meyer; Leonard Leifels; Gordian Hamerla; Anne Kathrin Höhn; Alexey Surov
Journal:  Mol Imaging Biol       Date:  2019-08       Impact factor: 3.488

4.  Histogram analysis parameters of apparent diffusion coefficient reflect tumor cellularity and proliferation activity in head and neck squamous cell carcinoma.

Authors:  Alexey Surov; Hans Jonas Meyer; Karsten Winter; Cindy Richter; Anna-Kathrin Hoehn
Journal:  Oncotarget       Date:  2018-05-04

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

Authors:  Hans Jonas Meyer; Leonard Leifels; Gordian Hamerla; Anne Kathrin Höhn; Alexey Surov
Journal:  Contrast Media Mol Imaging       Date:  2019-01-02       Impact factor: 3.161

6.  Comparison of Two Mathematical Models of Cellularity Calculation.

Authors:  Hans Jonas Meyer; Nikita Garnov; Alexey Surov
Journal:  Transl Oncol       Date:  2018-02-03       Impact factor: 4.243

7.  Histogram analysis parameters of dynamic contrast-enhanced magnetic resonance imaging can predict histopathological findings including proliferation potential, cellularity, and nucleic areas in head and neck squamous cell carcinoma.

Authors:  Alexey Surov; Hans Jonas Meyer; Leonard Leifels; Anne-Kathrin Höhn; Cindy Richter; Karsten Winter
Journal:  Oncotarget       Date:  2018-04-20

8.  Relationships between histogram analysis of ADC values and complex 18F-FDG-PET parameters in head and neck squamous cell carcinoma.

Authors:  Hans-Jonas Meyer; Sandra Purz; Osama Sabri; Alexey Surov
Journal:  PLoS One       Date:  2018-09-06       Impact factor: 3.240

9.  Histogram Analysis Parameters Apparent Diffusion Coefficient for Distinguishing High and Low-Grade Meningiomas: A Multicenter Study.

Authors:  Alexey Surov; Daniel T Ginat; Tchoyoson Lim; Teresa Cabada; Ozdil Baskan; Stefan Schob; Hans Jonas Meyer; Georg Alexander Gihr; Diana Horvath-Rizea; Gordian Hamerla; Karl Titus Hoffmann; Andreas Wienke
Journal:  Transl Oncol       Date:  2018-07-11       Impact factor: 4.243

10.  Relationship between histogram metrics of pharmacokinetic parameters of DCE-MRI and histological phenotype in breast cancer.

Authors:  Guocai Yang; Jing Yang; Hui Xu; Qingxin Zhang; Yonghong Qi; Aiju Zhang
Journal:  Transl Cancer Res       Date:  2020-01       Impact factor: 1.241

  10 in total

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