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• Clinical Article •
Development of a nomogram based on diffusion weighted imaging of peritumoral liver tissue to predict local progression of recurrent hepatocellular carcinoma after hepatectomy
WANG Jing  ZENG Chaoqiang  TANG Mengyue  XU Min  ZHANG Xiaoming  CHEN Tianwu 

Cite this article as: WANG J, ZENG C Q, TANG M Y, et al. Development of a nomogram based on diffusion weighted imaging of peritumoral liver tissue to predict local progression of recurrent hepatocellular carcinoma after hepatectomy[J]. Chin J Magn Reson Imaging, 2024, 15(2): 63-70. DOI:10.12015/issn.1674-8034.2024.02.009.


[Abstract] Objective To investigate feasibility of a nomogram model developed with apparent diffusion coefficient (ADC) of peritumoral liver tissue to predict local progression of recurrent hepatocellular carcinoma (rHCC) after hepatectomy.Materials and Methods A retrospective cohort study was conducted by collecting MRI and clinical data of patients with diagnosed rHCC after hepatectomy at the Affiliated Hospital of North Sichuan Medical College from January 2021 to December 2022. Using Firevoxel software, the peritumor mean ADC (pADCmean), minimum ADC (pADCmin), and maximum ADC (pADCmax) values, as well as the tumor mean ADC (tADCmean), minimum ADC (tADCmin), and maximum (tADCmax) values were measured. The background liver tissue mean ADC (bADCmean), minimum ADC (bADCmin), and maximum ADC (bADCmax) values were also obtained. The ratios of pADCmean to bADCmean (RPB-ADCmean), ADCmin (RPB-ADCmin), and ADCmax (RPB-ADCmax) along with the ratios of tADCmean to bADCmean (RTB-ADCmean), ADCmin (RTB-ADCmin), and ADCmax (RTB-ADCmax) were calculated. Cox regression analysis was used to identify independent risk factors, and then a nomogram model was constructed to predict local progression of rHCC after hepatectomy. Receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were employed to evaluate the predictive value of the model for prediction of local progression of rHCC.Results A total of 70 patients with rHCC after hepatectomy were enrolled, and the local progression rate of rHCC was 65.7% (46/70) confirmed by follow-up. Multivariate Cox regression analysis revealed that RPB-ADCmean, pADCmin and vitamin K absence antagonist-Ⅱ were independent risk factors for local progression of rHCC after hepatectomy (all P<0.05). The area under the ROC curve of the nomogram model to predict local progression of rHCC within 3 months and within 6 months after hepatectomy was 0.834 and 0.841, respectively. DCA demonstrated a favorable clinical net benefit of the model.Conclusions The pADCmin, RPB-ADCmean and vitamin K absence antagonist-Ⅱ can be independent risk factors associated with local progression of rHCC after hepatectomy, and the developed nomogram model can intuitively predict local progression of rHCC with good performance and net clinical benefit.
[Keywords] hepatocellular carcinoma；recurrence；peritumoral tissue；magnetic resonance imaging；diffusion weighted imaging；nomogram

WANG Jing1, 2   ZENG Chaoqiang2   TANG Mengyue1   XU Min1   ZHANG Xiaoming1   CHEN Tianwu3*  

1 Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Sichuan Key Laboratory of Medical Imaging, Nanchong 637000, China

2 Department of Imaging, the Second Clinical School of North Sichuan Medical College/Nanchong Central Hospital, Nanchong 637000, China

3 Department of Radiology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China

Corresponding author: CHEN T W, E-mail: tianwuchen_nsmc@163.com

Conflicts of interest   None.

Received  2023-10-22
Accepted  2024-01-05
DOI: 10.12015/issn.1674-8034.2024.02.009
Cite this article as: WANG J, ZENG C Q, TANG M Y, et al. Development of a nomogram based on diffusion weighted imaging of peritumoral liver tissue to predict local progression of recurrent hepatocellular carcinoma after hepatectomy[J]. Chin J Magn Reson Imaging, 2024, 15(2): 63-70. DOI:10.12015/issn.1674-8034.2024.02.009.

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