Original Research

Liver Imaging Reporting and Data System in Patients at High Risk for Hepatocellular Carcinoma in the Memphis Veterans Affairs Population

Fed Pract. 2019 May;36(suppl 3):S47-S52

References

1. El–Serag HB, Rudolph KL. Hepatocellular carcinoma: epidemiology and molecular carcinogenesis. Gastroenterology. 2007;132(7):2557-2576.

2. El-Serag HB. Hepatocellular carcinoma. N Engl J Med. 2011;365(12):1118-1127.

3. Bruix J, Sherman M; American Association for the Study of Liver Diseases. Management of hepatocellular carcinoma: an update. Hepatology. 2011;53(3):1020-1022.

4. Selvapatt N, House H, Brown A. Hepatocellular carcinoma surveillance: are we utilizing it? J Clin Gastroenterol. 2016;50(1):e8-e12.

5. Lee JM, Yoon JH, Joo I, Woo HS. Recent advances in CT and MR imaging for evaluation of hepatocellular carcinoma. Liver Cancer. 2012;1(1):22-40.

6. Chou R, Cuevas C, Fu R, et al. Imaging techniques for the diagnosis of hepatocellular carcinoma: a systemic review and meta-analysis. Ann Intern Med. 2015;162(10):697-711.

7. Ariff B, Lloyd CR, Khan S, et al. Imaging of liver cancer. World J Gastroenterol. 2009;15(11):1289-1300.

8. Yuen MF, Cheng CC, Lauder IJ, Lam SK, Ooi CG, Lai CL. Early detection of hepatocellular carcinoma increases the chance of treatment: Hong Kong experience. Hepatology. 2000;31(2):330-335.

9. Singal AG, Pillai A, Tiro J. Early detection, curative treatment, and survival rates for hepatocellular carcinoma surveillance in patients with cirrhosis: a meta-analysis. PLoS Med. 2014;11(4):e1001624.

10. Nusbaum, JD, Smirniotopoulos J, Wright HC, et al. The effect of hepatocellular carcinoma surveillance in an urban population with liver cirrhosis. J Clin Gastroenterol. 2015;49(10):e91-e95.

11. Kansagara D, Papak J, Pasha AS, et al. Screening for hepatocellular carcinoma in chronic liver disease: a systemic review. Ann Intern Med. 2014;161(4):261-269.

12. Shah S, Shukla A, Paunipagar B. Radiological features of hepatocellular carcinoma. J Clin Exp Hepatol. 2014;4(suppl 3):S63-S66.

13. You MW, Kim SY, Kim KW, et al. Recent advances in the imaging of hepatocellular carcinoma. Clin Mol Hepatol. 2015;21(1):95-103.

14. American College of Radiology. Liver reporting and data system (LI-RADS). https://www.acr.org/Clinical-Resources/Reporting-and-Data-Systems/LI-RADS. Accessed April 10, 2018.

15. Anis M. Imaging of hepatocellular carcinoma: new approaches to diagnosis. Clin Liver Dis. 2015;19(2):325-340.

16. Mitchell D, Bruix J, Sherman M, Sirlin CB. LI-RADS (Liver Imaging Reporting and Data System): summary, discussion, and consensus of the LI-RADS Management Working Group and future directions. Hepatology. 2015;61(3):1056-1065.

17. Darnell A, Forner A, Rimola J, et al. Liver imaging reporting and data system with MR imaging: evaluation in nodules 20 mm or smaller detected in cirrhosis at screening US. Radiology. 2015; 275(3):698-707.

18. Davenport MS, Khalatbari S, Liu PS, et al. Repeatability of diagnostic features and scoring systems for hepatocellular carcinoma by using MR imaging. Radiology. 2014;272(1):132-142.

19. An C, Rakhmonova G, Choi JY, Kim MJ. Liver imaging reporting and data system (LI-RADS) version 2014: understanding and application of the diagnostic algorithm. Clin Mol Hepatol. 2016;22(2):296-307.

20. Zhao W, Li W, Yi X, et al. [Diagnostic value of liver imaging reporting and data system on primary hepatocellular carcinoma] [in Chinese]. Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2016;41(4):380-387.

21. Choi SH, Byun JH, Kim SY, et al. Liver imaging reporting and data system v2014 with gadoxetate disodium-enhanced magnetic resonance imaging: validation of LIRADS category 4 and 5 criteria. Invest Radiol. 2016;51(8):483-490.

22. Zhang YD, Zhu FP, Xu X, et al. Liver imaging reporting and data system: substantial discordance between CT and MR for imaging classification of hepatic nodules. Acad Radiol. 2016;23(3):344-352.

23. Corwin MT, Fananapazir G, Jin M, Lamba R, Bashir MR. Difference in liver imaging and reporting data system categorization between MRI and CT. Am J Roentgenol. 2016;206(2):307-312.

Methods

Patients at MVAMC with cirrhosis and patients with chronic hepatitis B are routinely screened with ultrasound, CT, or MRI in accordance with the AASLD, EASL, and VA guidelines. Of 303 patients with HCV and cirrhosis under care in 2015, 242 (81%) received imaging to screen for HCC according to the VA National Hepatitis C Registry 2015 (Personal Communication, Population Health Service, Office of Patient Care Services).The LI-RADS scoring system was not applied as a standard screening methodology.

Under an institutional review board-approved protocol, we reviewed the charts of all patients diagnosed with HCC at MVAMC from 2009 to 2014, utilizing ICD-9 code of 155.0 for HCC. We identified within these charts patients who had a surveillance CT image performed within a 6- to 13-month period prior to the CTs that diagnosed HCC (prediagnostic HCC CT). Furthermore, we reviewed the charts of all patients diagnosed with benign liver nodules at MVAMC from 2009 to 2014, utilizing the ICD-9 code of 573.8 for other specified disorders of the liver.

Within these charts, we found patients who had a surveillance CT image performed and who were followed after that image with additional imaging for ≥ 2 years or who had a liver biopsy negative for HCC (benign surveillance CT). We compared these 2 sets of CTs utilizing LI-RADS criteria. Once these patients were identified, a list of the CTs to be examined were given to 2 MVAMC radiologists who specialize in CT.

No identifying information of the patients was included, and a 13-digit number unique to each CT exam identified the CTs to be reviewed. Radiologist 1 and 2 examined the CTs on the MVAMC Picture Archiving and Communication System (PACS). Both radiologists were asked to give each nodule a score according to LI-RADS v2014 diagnostic algorithm (Figure).

We hypothesized that the prediagnostic CT images of patients eventually determined to have HCC would have a LI-RADS score of 4 (LR4) or LR5. Furthermore, we hypothesized that the CT images of the benign liver nodule patients would have a score ≤ LR3. If there was a disagreement between the radiologists in terms of a malignant score (LR4 or LR5) vs a benign score (≤ LR3), then a third radiologist (radiologist 3) provided a score for these nodules. The third, tiebreaker radiologist was given the scores of both prior radiologists and asked to choose which score was correct.

Statistical analysis was then applied to the data to determine the sensitivity, specificity, and diagnostic accuracy in diagnosing eventual HCC, as well as the false-negative and false-positive rates of radiologists 1 and 2. Raw data also were used to determine the agreement between raters by calculating the κ statistic with a 95% CI.

Results

A total of 70 nodules were examined by radiologists 1 and 2 with 42 of the nodules in the prediagnostic HCC CTs and 28 of the nodules in the benign surveillance CTs.

Radiologists 1 and 2 found 27 and 29 patients, respectively, that had HCC that might have been predicted in an earlier scan if LI-RADS had been utilized, while5 patients for radiologist 1 and 7 patients for radiologist 2 were determined to have benign disease that would have been incorrectly identified as likely HCC with LR4 or LR5 (Table 1).