Comparative study of 3D MR elastography and intravoxel incoherent motion for the evaluation of hepatocellular carcinoma grade

Abstract

Background and aims: Noninvasive preoperative radiologic prediction of histologic grade-a key prognostic factor-is invaluable. We aim to compare the diagnostic values of 3D magnetic resonance elastography (MRE), intravoxel incoherent motion (IVIM), and conventional contrast-enhanced magnetic resonance imaging (cMRI) in predicting the histologic grade of hepatocellular carcinoma (HCC).

Methods: This institutional review board-approved retrospective study included patients who underwent MRI between December 2014 and October 2021. Sixty-eight patients with pathologically confirmed HCCs who underwent MRE, IVIM, and cMRI imaging were included in the analysis. Two radiologists measured HCC stiffness volumetrically and over a single slice, and also measured apparent diffusion coefficient (ADC), IVIM-derived parameters, and enhancement ratio (ER) on arterial phase images via cMRI. Student’s t-test or the Mann-Whitney U test was used for group comparisons. Receiver operating characteristic (ROC) curve analyses were performed to evaluate the diagnostic performance.

Results: Histologically, fifty-three (78%) patients had well-differentiated or moderately differentiated HCCs, and fifteen (22%) patients had poorly differentiated HCCs. Both the volumetric stiffness and single-ROI tumor stiffness were significantly elevated in the poorly differentiated HCC group (P < 0.001, P = 0.001), and the volumetric stiffness was a better measurement of stiffness because it had a higher ROC curve value (0.816). However, the ADC, the true diffusion coefficient (D), the pseudodiffusion coefficient (D^*), the pseudodiffusion fraction (f), and ER during the arterial phases on cMRI were not significantly different between the two groups (P = 0.309, 0.187, 0.440, 0.350, and 0.714, respectively).

Conclusions: Stiffness measured with 3D MRE may be useful for noninvasively predicting HCC histologic grade, and the volumetric measuring method achieved the highest ROC curve value, outperforming single-ROI HCC stiffness, IVIM parameters, and arterial-phase ER on cMRI.

Keywords

Magnetic resonance elastography (MRE) / Hepatocellular carcinoma (HCC) / Diagnostic imaging / Neoplasm grading / Elasticity imaging techniques

Authors' contributions

Weimin Liu: Writing - original draft, Methodology, Formal analysis, Data curation. Sidong Xie: Methodology, Data curation. Wenjie Tang: Writing - review & editing. Ka Zhang: Writing -review & editing, Visualization, Supervision.

Data availability statement

The data that support the findings of this study are available on request from the corresponding author.

Declaration of competing interest

The authors declare that there are no conflicts of interest.

Acknowledgements

This work was supported by grants from the National Natural Science Foundation of China (NO. 82370626) to Ka Zhang.

References

[1] Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA Cancer J Clin. 2023; 73:17-48. https://doi.org/10.3322/caac.21763.

[2] Sankar K, Gong J, Osipov A, et al. Recent advances in the management of hepatocellular carcinoma. Clin Mol Hepatol. 2024; 30:1-15. https://doi.org/10.3350/cmh.2023.0125.

[3] Singal AG, Kanwal F, Llovet JM. Global trends in hepatocellular carcinoma epidemiology: implications for screening, prevention and therapy. Nat Rev Clin Oncol. 2023; 20:864-884. https://doi.org/10.1038/s41571-023-00825-3.

[4] Oishi K, Itamoto T, Amano H, et al. Clinicopathologic features of poorly differentiated hepatocellular carcinoma. J Surg Oncol. 2007; 95:311-316. https://doi.org/10.1002/jso.20661.

[5] Moctezuma-Velázquez C, Lewis S, Lee K, et al. Non-invasive imaging criteria for the diagnosis of hepatocellular carcinoma in non-cirrhotic patients with chronic hepatitis B. JHEP Rep. 2021; 3:100364. https://doi.org/10.1016/j.jhepr.2021.100364.

[6] Yang T, Wei H, Wu Y, et al. Predicting histologic differentiation of solitary hepatocellular carcinoma up to 5 cm on gadoxetate disodium-enhanced MRI. Insights Imaging. 2023; 14:3. https://doi.org/10.1186/s13244-022-01354-w.

[7] Rong D, Liu W, Kuang S, et al. Preoperative prediction of pathologic grade of HCC on gadobenate dimeglumine-enhanced dynamic MRI. Eur Radiol. 2021; 31:7584-7593. https://doi.org/10.1007/s00330-021-07891-0.

[8] Tahir B, Sandrasegaran K, Ramaswamy R, et al. Does the hepatocellular phase of gadobenate dimeglumine help to differentiate hepatocellular carcinoma in cirrhotic patients according to histological grade? Clin Radiol. 2011; 66: 845-852. https://doi.org/10.1016/j.crad.2011.03.021.

[9] Moura Cunha G, Fan B, Navin PJ, et al. Interpretation, reporting, and clinical applications of liver MR elastography. Radiology. 2024; 310:e231220. https://doi.org/10.1148/radiol.231220.

[10] Thompson SM, Wang J, Chandan VS, et al. MR elastography of hepatocellular carcinoma: correlation of tumor stiffness with histopathology features-preliminary findings. Magn Reson Imaging. 2017; 37:41-45. https://doi.org/10.1016/j.mri.2016.11.005.

[11] Liu W, Rong D, Zhu J, et al.Diagnostic accuracy of 3D magnetic resonance elastography for assessing histologic grade of hepatocellular carcinoma:comparison of three methods for positioning region of interest. Abdom Radiol (NY). 2021; 46:4601-4609. https://doi.org/10.1007/s00261-021-03150-4.

[12] Wang J, Shan Q, Liu Y, et al. 3D MR elastography of hepatocellular carcinomas as a potential biomarker for predicting tumor recurrence. J Magn Reson Im-aging. 2019; 49:719-730. https://doi.org/10.1002/jmri.26250.

[13] Wang Q, Yu G, Qiu J, Lu W. Application of intravoxel incoherent motion in clinical liver imaging: a literature review. J Magn Reson Imaging. 2024; 60: 417-440. https://doi.org/10.1002/jmri.29086.

[14] Zhou Y, Yang G, Gong XQ, et al. A study of the correlations between IVIM-DWI parameters and the histologic differentiation of hepatocellular carcinoma. Sci Rep. 2021; 11:10392. https://doi.org/10.1038/s41598-021-89784-2.

[15] Woo S, Lee JM, Yoon JH, Joo I, Han JK, Choi BI. Intravoxel incoherent motion diffusion-weighted MR imaging of hepatocellular carcinoma: correlation with enhancement degree and histologic grade. Radiology. 2014; 270:758-767. https://doi.org/10.1148/radiol.13130444.

[16] Le Bihan D, Breton E, Lallemand D, Aubin ML, Vignaud J, Laval-Jeantet M. Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. Radiology. 1988; 168:497-505. https://doi.org/10.1148/radiology.168.2.3393671.

[17] Bruix J, Sherman M, American Association for the Study of Liver Diseases. Management of hepatocellular carcinoma: an update. Hepatology. 2011; 53: 1020-1022. https://doi.org/10.1002/hep.24199.

[18] 18. Wurnig MC, Donati OF, Ulbrich E, et al. Systematic analysis of the intravoxel incoherent motion threshold separating perfusion and diffusion effects: pro-posal of a standardized algorithm. Magn Reson Med. 2015; 74:1414-1422. https://doi.org/10.1002/mrm.25506.

[19] Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin. 2015; 65:87-108. https://doi.org/10.3322/caac.21262.

[20] Kleihues P, Sobin LH. World health organization classification of tumors. Cancer. 2000; 88:2887. https://doi.org/10.1002/1097-0142(20000615)88:12<2887::aid-cncr32>3.0.co;2-f.

[21] Park SJ, Yoon JH, Lee DH, Lim WH, Lee JM. Tumor stiffness measurements on MR elastography for single nodular hepatocellular carcinomas can predict tumor recurrence after hepatic resection. J Magn Reson Imag. 2021; 53: 587-596. https://doi.org/10.1002/jmri.27359.

[22] Serai SD, Dillman JR, Trout AT. Spin-echo Echo-planar imaging MR elastog-raphy versus Gradient-echo MR elastography for assessment of liver stiffness in children and young adults suspected of having liver disease. Radiology. 2017; 282:761-770. https://doi.org/10.1148/radiol.2016160589.

[23] Zhu SC, Liu YH, Wei Y, et al. Intravoxel incoherent motion diffusion-weighted magnetic resonance imaging for predicting histological grade of hepatocellu-lar carcinoma: comparison with conventional diffusion-weighted imaging. World J Gastroenterol. 2018; 24:929-940. https://doi.org/10.3748/wjg.v24.i8.929.

[24] Le Bihan D. Apparent diffusion coefficient and beyond: what diffusion MR imaging can tell us about tissue structure. Radiology. 2013; 268:318-322. https://doi.org/10.1148/radiol.13130420.

[25] Xu H, Li X, Xie JX, Yang ZH, Wang B. Diffusion-weighted magnetic resonance imaging of focal hepatic nodules in an experimental hepatocellular carcinoma rat model. Acad Radiol. 2007; 14:279-286. https://doi.org/10.1016/j.acra.2006.12.005.

[26] Nasu K, Kuroki Y, Tsukamoto T, Nakajima H, Mori K, Minami M. Diffusion-weighted imaging of surgically resected hepatocellular carcinoma: imaging characteristics and relationship among signal intensity, apparent diffusion coefficient, and histopathologic grade. AJR Am J Roentgenol. 2009; 193: 438-444. https://doi.org/10.2214/AJR.08.1424.

[27] Shan Q, Chen J, Zhang T, et al.Evaluating histologic differentiation of hepatitis B virus-related hepatocellular carcinoma using intravoxel incoherent motion and AFP levels alone and in combination. Abdom Radiol (NY). 2017; 42: 2079-2088. https://doi.org/10.1007/s00261-017-1107-6.

[28] Chiaradia M, Baranes L, Van Nhieu JT, et al. Intravoxel incoherent motion (IVIM) MR imaging of colorectal liver metastases: are we only looking at tu-mor necrosis? J Magn Reson Imaging. 2014; 39:317-325. https://doi.org/10.1002/jmri.24172.

[29] Wei Y, Gao F, Wang M, et al. Intravoxel incoherent motion diffusion-weighted imaging for assessment of histologic grade of hepatocellular carcinoma: comparison of three methods for positioning region of interest. Eur Radiol. 2019; 29:535-544. https://doi.org/10.1007/s00330-018-5638-1.

[30] Cohen AD, Schieke MC, Hohenwalter MD, Schmainda KM. The effect of low b-values on the intravoxel incoherent motion derived pseudodiffusion param-eter in liver. Magn Reson Med. 2015; 73:306-311. https://doi.org/10.1002/mrm.25109.