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Keywords:
Liver, Interventional non-vascular, Oncology, MR, MR-Diffusion/Perfusion, Biopsy, Statistics, Neoplasia, Tissue characterisation
Authors:
K. Drevelegas1, K. Nikiforaki2, G. C. Manikis2, K. Marias2, M. Constantinides1, I. Stoikou1, L. Papalavrentios1, P. Bangeas1, A. Drevelegas1; 1Thessaloniki/GR, 2Heraklion/GR
DOI:
10.1594/ecr2017/C-2993
Methods and materials
Patient population comprised of 94 patients with focal liver lesion who underwent respiratory triggered DW-MRI at a 3T GE scanner (HDXt) and consecutively core needle biopsy prior to therapeutic management.
DW-MRI (b: 0,
1000) was post processed on in-house platform for 3D lesion delineation and pixel-based ADC calculations.
Correlation with biopsy histological diagnosis consequently made.
An exploratory histogram analysis,
using the derived ADC parametric maps from the ROIs,
was performed yielding several metrics including: minimum,
maximum,
mean,
standard deviation,
median,
skewness,
kurtosis,
variance,
histogram peak,
5%,
30%,
70% and 95% percentiles for each parameter.
A Kruskal-Wallis test was applied to a total of 12 histogram metrics calculated from the ADC values to investigate the differences between the primary - metastatic-neuroendocrine lesion group as well as for the different subgroups (primary site of metastatic group,
HCC vs colangioCa,
degree of cell differentiation).
The estimated p-values were declared statistically significant only at the 1% significance level.
Receiver Operator Characteristics (ROC) curves were then computed and corresponding area under the receiving operating curves (AUCs) were calculated to assess the performance of each histogram metric in differentiating the studied groups.
Sensitivity,
specificity,
negative and positive predictive values,
accuracy,
the confusion matrix and the optimal cutoff value of all ROC curves were calculated.
The confusion matrix reports the number of True Positive (TP),
True Negative (TN),
False Positive (FP) and False Negative (FN).