Diffusion weighted imaging in differentiating malignant and benign neuroblastic tumors

Jpn J Radiol. 2016 Sep;34(9):620-4. doi: 10.1007/s11604-016-0565-z. Epub 2016 Jul 14.

Abstract

Purpose: Our aim was to assess diffusion weighted imaging (DWI) of neuroblastic tumors and whether apparent diffusion coefficient (ADC) value may have a role in discrimination among neuroblastoma, ganglioneuroblastoma and ganglioneuroma.

Material and methods: The DWIs (b = 0-800 s/mm(2)) of 24 children (13 girls, 11 boys) who were diagnosed neuroblastic tumors on histopathological examination (neuroblastoma = 15, ganglioneuroblastoma = 5, ganglioneuroma = 4) were evaluated retrospectively. The ADC maps were performed by drawing freehand ROI on PACS (Sectra Workstation IDS7, Linköping, Sweden).

Results: We observed a significant decrease in ADC value of neuroblastomas 0.869 ± 0.179 × 10(-3) mm(2)/s compared to ganglioneuroblastomas 0.97 ± 0.203 × 10(-3) mm(2)/s and ganglioneuromas 1.147 ± 0.299 × 10(-3) mm(2)/s (p = 0.026). There was no significant difference in between ganglioneuroblastoma and ganglioneuroma (p = 0.16). In detecting neuroblastomas; the sensitivity, specificity, negative and positive predictive values of ADC were 74, 67, 78.6, 66 % respectively with a cut-off value of 0.93 × 10(-3) mm(2)/s.

Conclusion: Our study stands out as the most comprehensive study with larger sample size on this topic. Moreover, we are able to suggest a cut-off value which can discriminate neuroblastoma from ganglioneuroblastoma and ganglioneuroma. We believe that ADC will evolve to an objective, quantitative measurement in discrimination among malignant and benign neuroblastic tumors.

Keywords: ADC; DWI; Ganglioneuroblastoma; Ganglioneuroma; Neuroblastoma.

MeSH terms

  • Adolescent
  • Child
  • Child, Preschool
  • Diagnosis, Differential
  • Diffusion Magnetic Resonance Imaging / methods*
  • Female
  • Ganglioneuroma / diagnostic imaging*
  • Humans
  • Infant
  • Infant, Newborn
  • Male
  • Neuroblastoma / diagnostic imaging*
  • ROC Curve
  • Reproducibility of Results
  • Retrospective Studies
  • Sensitivity and Specificity