# Histogram analysis of continuous-time random walk and restrictive spectrum imaging for identifying hepatocellular carcinoma and intrahepatic cholangiocarcinoma

## TL;DR

This study compares advanced imaging techniques to distinguish between two types of liver cancer, finding that combining methods improves accuracy.

## Contribution

The study introduces the combined use of CTRW and RSI histogram parameters for improved liver cancer subtype differentiation.

## Key findings

- RSI's f1 40th percentile showed the highest accuracy in distinguishing cancer types.
- Combining CTRW and RSI improved diagnostic performance with higher sensitivity and specificity.
- Whole-lesion histogram parameters provided better insights than mean values alone.

## Abstract

To compare the ability and potential additional value of various diffusion models, including continuous-time random walk (CTRW), restrictive spectrum imaging (RSI), and diffusion-weighted imaging (DWI), as well as their associated histograms, in distinguishing the pathological subtypes of liver cancer.

40 patients with liver cancer were included in this study. Histogram metrics were derived from CTRW (D, α, β), RSI (f1, f2, f3), and DWI (ADC) parameters across the entire tumor volume. Statistical analyses included the Chi-square test, independent samples t-test, Mann-Whitney U test, ROC, logistic regression, and Spearman correlation.

Patients with hepatocellular carcinoma exhibited higher values in f1 median, f1 20th, f1 40th, and f1 60th compared to patients with intrahepatic cholangiocarcinoma, whereas Dmean, Dmedian, D40th, D60th, and D80th percentiles were lower (P<0.05). Among the individual histogram parameters, f1 40th percentile demonstrated the highest accuracy (AUC = 0.717). Regarding the combined and single models, the total combined model exhibited the best diagnostic performance (AUC = 0.792). Although RSI showed higher diagnostic efficacy than CTRW (AUC = 0.731, 0.717), the combination of CTRW and RSI further improved diagnostic performance (AUC = 0.787), achieving superior sensitivity and specificity (sensitivity = 0.72, specificity = 0.80).

CTRW, RSI, and their corresponding histogram parameters demonstrated the ability to distinguish between pathological subtypes of liver cancer. Moreover, whole-lesion histogram parameters provided more comprehensive statistical insights compared to mean values alone.