eISSN: 2449-8238
ISSN: 2392-1099
Clinical and Experimental Hepatology
Current issue Archive Manuscripts accepted About the journal Editorial board Abstracting and indexing Subscription Contact Instructions for authors Ethical standards and procedures
Editorial System
Submit your Manuscript
SCImago Journal & Country Rank
2/2024
vol. 10
 
Share:
Share:
Original paper

Potential diagnostic value of high b-value computed diffusion-weighted imaging in hepatocellular carcinoma

Maxime Ablefoni
1
,
Theresa Richter
1
,
Jakob Leonhardi
1
,
Constantin Ehrengut
1
,
Gordian Prasse
1
,
Matthias Mehdorn
2
,
Daniel Seehofer
2
,
Anne Kathrin Höhn
3
,
Timm Denecke
1
,
Hans-Jonas Meyer
1

  1. Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany
  2. Department of Visceral and Transplantation Surgery, University of Leipzig, Leipzig, Germany
  3. Department of Pathology, University of Leipzig, Leipzig, Germany
Clin Exp HEPATOL 2024; 10, 2: 129-136
Online publish date: 2024/06/11
Article file
- Potential (1).pdf  [0.18 MB]
Get citation
 
PlumX metrics:
 
1. Surov A, Pech M, Omari J, et al. Diffusion-weighted imaging reflects tumor grading and microvascular invasion in hepatocellular carcinoma. Liver Cancer 2021; 10: 10-24.
2. Gomaa AI, Khan SA, Toledano MB, et al. Hepatocellular carcinoma: epidemiology, risk factors and pathogenesis. World J Gastroenterol 2008; 14: 4300-4308.
3. Schraml C, Kaufmann S, Rempp H, et al. Imaging of HCC-Current State of the Art. Diagnostics (Basel) 2015; 5: 513-545.
4. Marrero JA, Kulik LM, Sirlin CB, et al. Diagnosis, staging, and management of hepatocellular carcinoma: 2018 Practice Guidance by the American Association for the Study of Liver Diseases. Hepatology 2018; 68: 723-750.
5. Erstad DJ, Tanabe KK. Prognostic and therapeutic implications of microvascular invasion in hepatocellular carcinoma. Ann Surg Oncol 2019; 26: 1474-1493.
6. Shankar S, Kalra N, Bhatia A, et al. Role of diffusion weighted imaging (DWI) for hepatocellular carcinoma (HCC) detection and its grading on 3T MRI: A prospective study. J Clin Exp Hepatol 2016; 6: 303-310.
7. Granata V, Fusco R, Amato DM, et al. Beyond the vascular profile: conventional DWI, IVIM and kurtosis in the assessment of hepatocellular carcinoma. Eur Rev Med Pharmacol Sci 2020; 24: 7284-7293.
8. Lee S, Kim SH, Hwang JA, et al. Pre-operative ADC predicts early recurrence of HCC after curative resection. Eur Radiol 2019; 29: 1003-1012.
9. Xia Y, Wang L, Wu Z, et al. Comparison of computed and acquired DWI in the assessment of rectal cancer: Image quality and preoperative staging. Front Oncol 2022; 12: 788731.
10. Sato M, Kurita Y, Sakai E, et al. Computed diffusion-weighted magnetic resonance imaging with high b-values in the diagnosis of gallbladder lesions. Abdom Radiol (NY) 2022; 47: 3278-3289.
11. Jendoubi S, Wagner M, Montagne S, et al. MRI for prostate cancer: can computed high b-value DWI replace native acquisitions? Eur Radiol 2019; 29: 5197-5204.
12. Ablefoni M, Ullrich S, Surov A, et al. Diagnostic benefit of high b-value computed diffusion-weighted imaging in acute brainstem infarction. J Neuroradiol 2022; 49: 47-52.
13. Ablefoni M, Surup H, Ehrengut C, et al. Diagnostic benefit of high b-value computed diffusion-weighted imaging in patients with hepatic metastasis. J Clin Med 2021; 10: 5289.
14. Ablefoni M, Leonhardi J, Ehrengut C, et al. Magnetic resonance imaging of peritoneal carcinomatosis: Evaluation of high b-value computed diffusion-weighted imaging. Curr Oncol 2022; 29: 4593-4603.
15. Higaki T, Nakamura Y, Tatsugami F, et al. Introduction to the technical aspects of computed diffusion-weighted imaging for radiologists. Radiographics 2018; 38: 1131-1144.
16. Wang W, Guo Y, Zhong J, et al. The clinical significance of microvascular invasion in the surgical planning and postoperative sequential treatment in hepatocellular carcinoma. Sci Rep 2021; 11: 2415.
17. Taouli B, Beer AJ, Chenevert T, et al. Diffusion-weighted imaging outside the brain: Consensus statement from an ISMRM-sponsored workshop. J Magn Reson Imaging 2016; 44: 521-540.
18. Testa ML, Chojniak R, Sene LS, et al. Is DWI/ADC a useful tool in the characterization of focal hepatic lesions suspected of malignancy? PLoS One 2014; 9: e101944.
19. Nalaini F, Shahbazi F, Mousavinezhad SM, et al. Diagnostic accuracy of apparent diffusion coefficient (ADC) value in differentiating malignant from benign solid liver lesions: a systematic review and meta-analysis. Br J Radiol 2021; 94: 20210059.
20. Harder FN, Jung E, Weiss K, et al. Computed high-b-value high-resolution DWI improves solid lesion detection in IPMN of the pancreas. Eur Radiol 2023; 33: 6892-6901.
21. Tokunaga K, Arizono S, Shimizu H, et al. Optimizing b-values for accurate depiction of pancreatic cancer with tumor-associated pancreatitis on computed diffusion-weighted imaging. Clin Imaging 2020; 61: 20-26.
22. DelPriore MR, Biswas D, Hippe DS, et al. Breast cancer conspicuity on computed versus acquired high b-value diffusion-weighted MRI. Acad Radiol 2021; 28: 1108-1117.
23. Kaya B, Koc Z. Diffusion-weighted MRI and optimal b-value for characterization of liver lesions. Acta Radiol 2014; 55: 532-542.
24. Göya C, Hamidi C, Önder H, et al. Primary and metastatic liver malignancy: Utility low and high b value (1600-2000) in 3 Tesla MRI. Hepatogastroenterology 2015; 62: 962-965.
25. Arita Y, Yoshida S, Waseda Y, et al. Diagnostic value of computed high b-value whole-body diffusion-weighted imaging for primary prostate cancer. Eur J Radiol 2021; 137: 109581.
26. Jendoubi S, Wagner M, Montagne S, et al. MRI for prostate cancer: can computed high b-value DWI replace native acquisitions? Eur Radiol 2019; 29: 5197-5204.
27. Bickel H, Polanec SH, Wengert G, et al. Diffusion-weighted MRI of breast cancer: improved lesion visibility and image quality using synthetic b-values. J Magn Reson Imaging 2019; 50: 1754-1761.
28. Kawahara S, Isoda H, Fujimoto K, et al. Additional benefit of computed diffusion-weighted imaging for detection of hepatic metastases at 1.5T. Clin Imaging 2016; 40: 481-485.
29. Hwang YJ, Bae JS, Lee Y, et al. Classification of microvascular invasion of hepatocellular carcinoma: correlation with prognosis and magnetic resonance imaging. Clin Mol Hepatol 2023; 29: 733-746.
30. Zhang J, Zeng F, Jiang S, et al. Preoperative prediction model of microvascular invasion in patients with hepatocellular carcinoma. HPB (Oxford) 2023; 25: 45-53.
31. Bruix J, Cheng AL, Meinhardt G, et al. Prognostic factors and predictors of sorafenib benefit in patients with hepatocellular carcinoma: Analysis of two phase III studies. J Hepatol 2017; 67: 999-1008.
32. Huang J, Tian W, Zhang L, et al. Preoperative prediction power of imaging methods for microvascular invasion in hepatocellular carcinoma: A systemic review and meta-analysis. Front Oncol 2020; 10: 887.
33. Zhang S, Duan C, Zhou X, et al. Radiomics nomogram for prediction of microvascular invasion in hepatocellular carcinoma based on MR imaging with Gd-EOB-DTPA. Front Oncol 2022; 12: 1034519.
34. Granito A, Galassi M, Piscaglia F, et al. Impact of gadoxetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance on the non-invasive diagnosis of small hepatocellular carcinoma: a prospective study. Aliment Pharmacol Ther 2013; 37: 355-363.
Copyright: © 2024 Clinical and Experimental Hepatology. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) License (http://creativecommons.org/licenses/by-nc-sa/4.0/), allowing third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material, provided the original work is properly cited and states its license.
Quick links
© 2024 Termedia Sp. z o.o.
Developed by Bentus.