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A proposal for a useful algorithm to diagnose small hepatocellular carcinoma on MRI
Jean-Baptiste Coty1, Anita Paisant2, Maxime Esvan3,4
1Radiology Department, Cochin Hospital, Paris-Centre University Hospitals, APHP.
European Journal of Gastroenterology & Hepatology
|June 19, 2019
Summary
Magnetic resonance imaging (MRI) hallmarks are key for diagnosing small hepatocellular carcinomas (HCCs). A new algorithm incorporating diffusion-weighted (DW) imaging and capsule presence improves noninvasive HCC diagnosis when typical hallmarks are absent.
Area of Science:
- Radiology
- Hepatology
- Oncology
Background:
- Small hepatocellular carcinomas (HCCs) pose diagnostic challenges.
- Accurate noninvasive diagnosis is crucial for timely treatment of HCC.
Purpose of the Study:
- To evaluate magnetic resonance imaging (MRI) features for diagnosing small HCCs (10-30 mm).
- To assess MRI features as diagnostic substitutions for typical hallmarks in HCC nodules.
- To develop an improved diagnostic algorithm for small HCCs.
Main Methods:
- Liver MRI was performed on 364 cirrhotic patients with 10-30 mm nodules.
- Diagnostic performance of various MRI features (T1, T2, DW imaging, enhancement, capsule, fat content) was tested.
- A multifactorial algorithm with high specificity was used as the diagnostic reference.
Main Results:
- No single alternative MRI feature outperformed typical hallmarks for HCC diagnosis.
- For nodules lacking one hallmark, diffusion-weighted (DW) hyperintensity was the most accurate substitute.
- A new algorithm combining typical hallmarks with DW hyperintensity or capsule presence correctly classified 77.7% of nodules.
Conclusions:
- Typical MRI hallmarks remain the primary criteria for diagnosing small HCCs.
- An algorithm incorporating additional MRI features can enable noninvasive diagnosis of HCCs with one or no typical hallmarks.
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