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

Meyer, Hans Jonas; Leifels, Leonard; Schob, Stefan; Garnov, Nikita; Surov, Alexey

doi:10.1016/j.mri.2017.09.015

Cited by 21 publications

(17 citation statements)

References 15 publications

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“…The following parameters were calculated ( Fig 1D ): mean ADC (ADC mean ), maximum ADC (ADC max ), minimum ADC (ADC min ), median ADC (ADC median ), mode ADC (ADC mode ). Furthermore, ADC percentiles: 10 th (P10 ADC), 25 th (P25 ADC), 75 th (P75 ADC), and 90 th (P90 ADC), as well histogram-based characteristics of the ROIs—kurtosis, skewness, and entropy–were estimated [ 16 ].…”

Section: Methodsmentioning

confidence: 99%

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

Meyer¹,

Purz²,

Sabri³

2018

PLoS ONE

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PurposeHistogram analysis is an emergent imaging technique to further analyze radiological images and to obtain imaging biomarker. In head and neck cancer, MRI and PET are routinely used in clinical practice. The aim of this study was to analyze associations between histogram based ADC parameters and complex FDG-PET derived parameters in head and neck squamous cell carcinoma (HNSCC).Methods34 patients (26% female, mean age, 56.7 ± 10.2 years) with primary HNSCC were prospectively included into the study. ADC histogram parameters were calculated by inhouse made matlab software using a whole lesion measurement. For each tumor, maximum and mean standardized uptake values (SUVmax, SUVmean), Total Lesion Glycolysis (TLG) and Metabolic Tumor Volume (MTV) were determined on PET-images. Spearman's correlation coefficient (ρ) was used to analyze associations between investigated parameters. Benjamini-Hochberg correction was used to adjust for multiple testing. Mann-Whitney test was used for group discrimination. P-values < 0.05 were taken to indicate statistical significance.ResultsThe correlation analysis in the whole tumor group revealed a statistically significant correlation between entropy and MTV as well as TLG (ρ = 0.67, P<0.0001 and ρ = 0.61, P = 0.0002 respectively).There were statistically significant differences between T1/2 and T3/4 tumors in the following parameters: entropy (2.07 ± 0.36 vs 2.61 ± 0.43, P = 0.007), SUVmax (10.79 ± 4.13 vs 17.93 ± 5.89, P = 0.007), SUVmean (6.39 ± 2.48 vs 9.81 ± 4.49, P = 0.01), SUVmin (4.09 ± 1.57 vs 6.34 ± 2.59, P = 0.03), MTV (9.50 ± 7.92 vs 20.36 ± 13.30, P = 0.02), TGU (55.97 ± 39.09 vs 212.3 ± 186.3, P = 0.002).ConclusionThis study showed that entropy derived from ADC maps is strongly associated with MTV and TLG in HNSCC. Entropy, SUVmax, SUVmean, TLG and MTV were statistically significant higher in T3/4 tumors in comparison to T1/2 carcinomas.

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Section: Methodsmentioning

confidence: 99%

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

Meyer¹,

Purz²,

Sabri³

2018

PLoS ONE

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“…However, conflicting results were published here. In a recent study investigating head and neck cancer, a moderate correlation coefficient was identified between V e and ADC using histogram-based analysis [11] . In glioblastoma and in breast cancer, however, no correlation was identified between these parameters, and therefore, they might reflect different tumor aspects [18] , [19] .…”

Section: Discussionmentioning

confidence: 99%

“…Interestingly, V e as a parameter reflecting the extracellular volume fraction might also be linked to cell count [9] , [10] . In fact, previously, it has been shown that V e correlated with ADC in head and neck cancer [11] . Furthermore, some studies indicated that V e correlated with cellularity [9] , [10] .…”

Section: Introductionmentioning

confidence: 90%

Comparison of Two Mathematical Models of Cellularity Calculation

Meyer

Garnov

2018

Translational Oncology

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OBJECT: Nowadays, there is increasing evidence that functional magnetic resonance imaging (MRI) modalities, namely, diffusion-weighted imaging (DWI) and dynamic-contrast enhanced MRI (DCE MRI), can characterize tumor architecture like cellularity and vascularity. Previously, two formulas based on a logistic tumor growth model were proposed to predict tumor cellularity with DWI and DCE. The purpose of this study was to proof these formulas. METHODS: 16 patients with head and neck squamous cell carcinomas were included into the study. There were 2 women and 14 men with a mean age of 57.0 ± 7.5 years. In every case, tumor cellularity was calculated using the proposed formulas by Atuegwu et al. In every case, also tumor cell count was estimated on histopathological specimens as an average cell count per 2 to 5 high-power fields. RESULTS: There was no significant correlation between the calculated cellularity and histopathologically estimated cell count by using the formula based on apparent diffusion coefficient (ADC) values. A moderate positive correlation (r=0.515, P=.041) could be identified by using the formula including ADC and Ve values. CONCLUSIONS: The formula including ADC and Ve values is more sensitive to predict tumor cellularity than the formula including ADC values only.

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“…On the next step, the saved DI COM images were processed offline with custom-made Matlab-based application (The Mathworks, Natick, MA, USA). Thereafter, polygonal ROIs were automatically drawn on all of the transferred maps along the contours of the primary tumor on each slice (whole lesion measure) according to the previous description [ 12 ]. For every perfusion parameter (K trans , V e , and K ep ), mean, maximal, minimal, and median values, as well percentiles 10th, 25th, 75th, and 90th were estimated (Figure 1 ) according to our previous description ().…”

Section: Methodsmentioning

confidence: 99%

“…Currently, a new approach of imaging analysis, namely histogram analysis of different radiological parameters is in trend. So some reports indicated that histogram analysis parameters of apparent diffusion coefficient (ADC) can better reflect several morphological features in different malignancies in comparison to established ADC parameters [ 10 – 12 ]. For instance, Liu et al showed that ADC histogram parameters can well differentiate T and N stages in gastic cancer [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2018

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Our purpose was to analyze possible associations between histogram analysis parameters of dynamic contrast-enhanced magnetic resonance imaging DCE MRI and histopathological findings like proliferation index, cell count and nucleic areas in head and neck squamous cell carcinoma (HNSCC).30 patients (mean age 57.0 years) with primary HNSCC were included in the study. In every case, histogram analysis parameters of Ktrans, Ve, and Kep were estimated using a mathlab based software. Tumor proliferation index, cell count, and nucleic areas were estimated on Ki 67 antigen stained specimens. Spearman's non-parametric rank sum correlation coefficients were calculated between DCE and different histopathological parameters.KI 67 correlated with Ktrans min (p = −0.386, P = 0.043) and s Ktrans skewness (p = 0.382, P = 0.045), Ve min (p = −0.473, P = 0.011), Ve entropy (p = 0.424, P = 0.025), and Kep entropy (p = 0.464, P = 0.013). Cell count correlated with Ktrans kurtosis (p = 0.40, P = 0.034), Ve entropy (p = 0.475, P = 0.011). Total nucleic area correlated with Ve max (p = 0.386, P = 0.042) and Ve entropy (p = 0.411, P = 0.030).In G1/2 tumors, only Ktrans entropy correlated well with total (P =0.78, P =0.013) and average nucleic areas (p = 0.655, P = 0.006). In G3 tumors, KI 67 correlated with Ve min (p = −0.552, P = 0.022) and Ve entropy (p = 0.524, P = 0.031). Ve max correlated with total nucleic area (p = 0.483, P = 0.049). Kep max correlated with total area (p = −0.51, P = 0.037), and Kep entropy with KI 67 (p = 0.567, P = 0.018).We concluded that histogram-based parameters skewness, kurtosis and entropy of Ktrans, Ve, and Kep can be used as markers for proliferation activity, cellularity and nucleic content in HNSCC. Tumor grading influences significantly associations between perfusion and histopathological parameters.

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

Cited by 21 publications

References 15 publications

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

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

Comparison of Two Mathematical Models of Cellularity Calculation

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

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