Abstract

BackgroundTo evaluate the usefulness of differentiation of histological grade in hepatocellular carcinoma (HCC) using three-dimensional (3D) analysis of apparent diffusion coefficient (ADC) histograms retrospectively.MethodsThe subjects consisted of 53 patients with 56 HCCs. The subjects included 12 well-differentiated, 35 moderately differentiated, and nine poorly differentiated HCCs. Diffusion-weighted imaging (b-values of 100 and 800 s/mm2) were obtained within 3 months before surgery. Regions of interest (ROIs) covered the entire tumor. The data acquired from each slice were summated to derive voxel-by-voxel ADCs for the entire tumor. The following parameters were derived from the ADC histogram: mean, standard deviation, minimum, maximum, mode, percentiles (5th, 10th, 25th, 50th, 75th, and 90th), skew, and kurtosis. These parameters were analyzed according to histological grade. After eliminating steatosis lesions, these parameters were re-analyzed.ResultsA weak correlation was observed in minimum ADC and 5th percentile for each histological grade (r = –0.340 and r = –0.268, respectively). The minimum ADCs of well, moderately, and poorly differentiated HCC were 585 ± 388, 411 ± 278, and 235 ± 102 × 10−6 mm2/s, respectively. Minimum ADC showed significant differences among tumor histological grades (P = 0.009). The minimum ADC of poorly differentiated HCC and that of combined well and moderately differentiated HCC were 236 ± 102 and 437 ± 299 × 10−6 mm2/s. The minimum ADC of poorly differentiated HCC was significantly lower than that of combined well and moderately differentiated HCC (P = 0.001). The sensitivity and specificity, when a minimum ADC of 400 × 10−6 mm2/s or lower was considered to be poorly differentiated HCC, were 100 and 54%, respectively. After exclusion of the effect of steatosis, the sensitivity and specificity did not change, although the statistical differences became strong (P < 0.0001).ConclusionMinimum ADC was most useful to differentiate poorly differentiated HCC in 3D analysis of ADC histograms.

Highlights

  • To evaluate the usefulness of differentiation of histological grade in hepatocellular carcinoma (HCC) using three-dimensional (3D) analysis of apparent diffusion coefficient (ADC) histograms retrospectively

  • Some different histological grade components are often included in an HCC nodule; the region of interest (ROI) set through the entire lesion three-dimensionally may lead to a more accurate diagnosis

  • We evaluated the usefulness of differentiating the histological grade of HCC using 3D analysis of ADC histograms derived from the ROI set at the entire tumor

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Summary

Introduction

To evaluate the usefulness of differentiation of histological grade in hepatocellular carcinoma (HCC) using three-dimensional (3D) analysis of apparent diffusion coefficient (ADC) histograms retrospectively. When the ROI is set at the entire tumor on a slice, the measured ADC is represented only on the selected slice. Some different histological grade components are often included in an HCC nodule; the ROI set through the entire lesion three-dimensionally may lead to a more accurate diagnosis. The usefulness of differentiation of brain glioma grade using ADC histogram analysis in which ROI is set to the entire lesion threedimensionally has already been reported [10]. We evaluated the usefulness of differentiating the histological grade of HCC using 3D analysis of ADC histograms derived from the ROI set at the entire tumor

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