Discriminating rectal cancer grades using restriction spectrum imaging

Abdom Radiol (NY). 2022 Jun;47(6):2014-2022. doi: 10.1007/s00261-022-03500-w. Epub 2022 Apr 4.

Abstract

Purpose: Restriction spectrum imaging (RSI) is a novel diffusion MRI model that separates water diffusion into several microscopic compartments. The restricted compartment correlating to the tumor cellularity is expected to be a potential indicator of rectal cancer aggressiveness. Our aim was to assess the ability of RSI model for rectal tumor grading.

Methods: Fifty-eight patients with different rectal cancer grading confirmed by biopsy were involved in this study. DWI acquisitions were performed using single-shot echo-planar imaging (SS-EPI) with multi-b-values at 3 T. We applied a three-compartment RSI model, along with ADC model and diffusion kurtosis imaging (DKI) model, to DWI images of 58 patients. ROC and AUC were used to compare the performance of the three models in differentiating the low grade (G1 + G2) and high grade (G3). Mean ± standard deviation, ANOVA, ROC analysis, and correlation analysis were used in this study.

Results: The volume fraction of restricted compartment C1 from RSI was significantly correlated with grades (r = 0.403, P = 0.002). It showed significant difference between G1 and G3 (P = 0.008) and between G2 and G3 (P = 0.01). As for the low-grade and high-grade discrimination, significant difference was found in C1 (P < 0.001). The AUC of C1 for differentiation between low-grade and high-grade groups was 0.753 with a sensitivity of 72.0% and a specificity of 70.0%.

Conclusion: The three-compartment RSI model was able to discriminate the rectal cancer of low and high grades. The results outperform the traditional ADC model and DKI model in rectal cancer grading.

Keywords: Diffusion MRI; Grading; Rectal cancer; Restriction spectrum imaging.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Diffusion Magnetic Resonance Imaging* / methods
  • Diffusion Tensor Imaging / methods
  • Humans
  • Neoplasm Grading
  • ROC Curve
  • Rectal Neoplasms* / diagnostic imaging
  • Rectal Neoplasms* / pathology
  • Sensitivity and Specificity