Magnetic resonance imaging (MRI) texture analysis is increasingly recognised as a valuable tool for evaluating liver lesions and predicting post-biopsy complications. MRI-guided liver biopsies play a critical role in confirming diagnoses, particularly in cases where conventional imaging does not provide definitive results. However, the risk of complications, including post-procedural haemorrhage and unsuccessful biopsy outcomes, remains a concern. A recent study published in the Journal of Imaging Informatics in Medicine explores the association between MRI-derived texture features and these complications, with the aim of improving risk stratification for patients undergoing percutaneous MRI-guided liver biopsy.
MRI-guided liver biopsy offers superior lesion visualisation, particularly for small or poorly defined lesions that are difficult to target using ultrasound or computed tomography (CT). Despite its advantages, the procedure is associated with risks, and complications can impact both patient safety and diagnostic efficiency. By incorporating MRI texture analysis into pre-procedural assessments, clinicians may be able to better identify patients at risk and adjust biopsy techniques accordingly.
MRI Texture Analysis and Post-Biopsy Haemorrhage
Post-interventional haemorrhage is one of the primary concerns following MRI-guided liver biopsy. In this study, 13.9% of patients experienced post-procedural bleeding, underlining the importance of improved predictive models. Conventional clinical parameters, such as coagulation status and liver pathology, were not found to be significantly correlated with haemorrhage risk. However, several MRI texture features demonstrated notable differences between patients with and without bleeding complications.
Notably, texture features such as GrVariance and GrSkewness showed significant associations with haemorrhage occurrence. The study’s multivariate prediction model, incorporating multiple texture parameters, achieved a diagnostic accuracy of 77%. These findings suggest that MRI texture analysis could serve as an additional tool to identify at-risk patients before the procedure, potentially leading to modified biopsy strategies and improved patient safety.
Incorporating MRI texture analysis into pre-procedural evaluations could help reduce the incidence of haemorrhagic complications. If clinicians can identify patients who are more likely to experience bleeding, additional precautions could be taken, such as adjusting the biopsy approach, selecting an alternative imaging modality or monitoring patients more closely post-procedure. This could be particularly relevant for patients with complex liver pathology or those undergoing repeated biopsies.
Impact on Biopsy Success Rates
In addition to post-procedural complications, MRI texture analysis was also found to influence biopsy success rates. In 11.4% of cases, the biopsy failed to provide a diagnostic result, necessitating further interventions. This can prolong the diagnostic process and increase the burden on both patients and healthcare resources. The study identified specific texture features, particularly those related to the co-occurrence matrix, as being significantly different between successful and unsuccessful biopsies.
Among the most relevant features were S(1,1)DifEntrp and S(0,4)DifEntrp, which demonstrated notable associations with negative biopsy outcomes. The presence of such patterns suggests that MRI texture analysis could be used pre-emptively to identify lesions that are more likely to yield non-diagnostic results. This could allow clinicians to refine their approach, either by reconsidering biopsy necessity, modifying the puncture strategy or opting for alternative diagnostic methods when appropriate.
The integration of MRI texture analysis into routine workflows could improve biopsy accuracy by ensuring that only those lesions with a high likelihood of yielding diagnostic results are selected for intervention. Reducing the rate of non-diagnostic biopsies would enhance overall efficiency in liver disease diagnosis and management, ultimately improving patient outcomes while minimising unnecessary procedures.
Clinical Implications and Future Prospects
The integration of MRI texture analysis into routine clinical workflows has the potential to enhance patient outcomes by enabling more precise risk assessments prior to biopsy. MRI-guided biopsies provide high-resolution visualisation of liver lesions, but they also come with increased costs and longer procedural durations compared to ultrasound- or CT-guided techniques. Therefore, accurate patient selection is crucial to ensuring that the benefits of MRI guidance outweigh its limitations.
By using texture analysis to stratify risk, clinicians can make more informed decisions about whether MRI-guided biopsy is the most appropriate approach for a given patient. This could lead to better procedural planning, reduced rates of complications and improved efficiency in diagnosing liver conditions. Future research should focus on refining predictive models and validating these findings in larger patient cohorts to ensure their reliability across diverse clinical settings.
Furthermore, while the current study highlights the potential of MRI texture analysis, further exploration is needed to understand how different liver pathologies influence texture parameters. Investigating the correlation between specific tumour characteristics and texture patterns may provide deeper insights into lesion behaviour, further improving biopsy targeting and procedural safety. Additionally, advancements in artificial intelligence and machine learning could enhance the accuracy and applicability of MRI texture-based risk assessment models.
MRI-derived texture features provide valuable insights into the likelihood of post-biopsy complications and biopsy success rates in MRI-guided liver biopsies. By identifying patients at higher risk for haemorrhage or non-diagnostic biopsies, MRI texture analysis can assist in refining patient selection and procedural planning. Although further validation is necessary, this approach represents a promising advancement in personalised medicine, enhancing both safety and diagnostic accuracy in liver biopsies. The integration of texture-based risk assessments into routine practice has the potential to optimise clinical workflows and improve overall patient outcomes in hepatology.
Source: Journal of Imaging Informatics in Medicine
Image Credit: iStock
