Assessment of histological differentiation in gastric cancers using whole-volume histogram analysis of apparent diffusion coefficient maps

J Magn Reson Imaging. 2017 Feb;45(2):440-449. doi: 10.1002/jmri.25360. Epub 2016 Jul 1.

Abstract

Purpose: To investigate the efficacy of histogram analysis of the entire tumor volume in apparent diffusion coefficient (ADC) maps for differentiating between histological grades in gastric cancer.

Materials and methods: Seventy-eight patients with gastric cancer were enrolled in a retrospective 3.0T magnetic resonance imaging (MRI) study. ADC maps were obtained at two different b values (0 and 1000 sec/mm2 ) for each patient. Tumors were delineated on each slice of the ADC maps, and a histogram for the entire tumor volume was subsequently generated. A series of histogram parameters (eg, skew and kurtosis) were calculated and correlated with the histological grade of the surgical specimen. The diagnostic performance of each parameter for distinguishing poorly from moderately well-differentiated gastric cancers was assessed by using the area under the receiver operating characteristic curve (AUC).

Results: There were significant differences in the 5th , 10th , 25th , and 50th percentiles, skew, and kurtosis between poorly and well-differentiated gastric cancers (P < 0.05). There were correlations between the degrees of differentiation and histogram parameters, including the 10th percentile, skew, kurtosis, and max frequency; the correlation coefficients were 0.273, -0.361, -0.339, and -0.370, respectively. Among all the histogram parameters, the max frequency had the largest AUC value, which was 0.675.

Conclusion: Histogram analysis of the ADC maps on the basis of the entire tumor volume can be useful in differentiating between histological grades for gastric cancer.

Level of evidence: 4 J. Magn. Reson. Imaging 2017;45:440-449.

Keywords: cell differentiation; diffusion magnetic resonance imaging; histogram; magnetic resonance imaging; stomach neoplasm.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Biopsy / methods*
  • Data Interpretation, Statistical*
  • Diagnosis, Differential
  • Diffusion Magnetic Resonance Imaging / methods*
  • Female
  • Humans
  • Image Enhancement / methods
  • Image Interpretation, Computer-Assisted / methods*
  • Imaging, Three-Dimensional / methods
  • Male
  • Middle Aged
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Stomach Neoplasms / diagnostic imaging*
  • Stomach Neoplasms / pathology*
  • Tumor Burden*