Quantitative evaluation of liver function using gadoxetic acid-enhanced MRI
Before liver resection, a reliable and accurate assessment of the liver function is essential to ensure a safe surgery and avoid unfavorable complications such as post-hepatectomy liver failure (PHLF). Gadoxetic acid enhanced magnetic resonance imaging (MRI) is a routinely used imaging modality for tumor detection and characterization. In recent years, research has shown that gadoxetic acid enhanced MRI can be a reliable and promising tool in evaluation of liver function, supplying liver function information at both global and regional levels. Accurate assessment of liver function also makes it possible to predict PHLF preoperatively.
In Study I, the three categories of parameters derived from gadoxetic acid enhanced MRI (signal intensity-based, T1 relaxometry-based and dynamic hepatic contrast enhanced MRI-based) were evaluated for the consistency between them and the correlation with Child-Pugh score and Model for End-stage Liver Disease score. It was shown that the simple signal intensity based parameters had a similar capacity as the complex ones in evaluation of liver function. Among them, liver-to-muscle ratio (LMR) showed a good performance and could be selected for clinical usage.
Study II was a prospective pilot study, which compared the efficacy of gadoxetic acid enhanced MRI with two gold standard tests (indocyanine green retention test at 15 min (ICG-R15) and hepatobiliary scintigraphy) in evaluation of liver function during the perioperative period. It was shown that 1) the consistency between the three modalities was good, 2) LMR and hepatic uptake index were reliable for liver function assessment and predictive for liver growth after liver resection, and 3) liver function and volume changed in parallel within one month after liver resection.
The systematic review of Study III was performed to summarize currently available evidence for the value of preoperative gadoxetic acid enhanced MRI in prediction of PHLF. It included 15 original studies and the results demonstrated that gadoxetic acid enhanced MRI had a high predictive value in estimation of PHLF risk, with an area under the curve ranging from 0.67 to 0.96.
In Study IV, a clinical model using radiomics and machine learning approaches based on hepatobiliary phase of gadoxetic acid enhanced MRI for PHLF prediction in patients with hepatocellular carcinoma was developed and validated. The prediction model yielded an AUC of 0.84 and 0.82 in the training and test cohorts respectively, showing a promising ability to stratify patients into different risk levels for PHLF.
In summary, preoperative gadoxetic acid enhanced MRI seems to be an effective and reliable imaging biomarker for quantitative evaluation of liver function and for prediction of post-hepatectomy liver failure.
List of scientific papers
I. Quantitative evaluation of liver function with gadoxetic acid enhanced MRI: Comparison among signal intensity-, T1-relaxometry-, and dynamic-hepatocyte-specific-contrast-enhanced MRI- derived parameters. Wang Q, Kesen S, Liljeroth M, Nilsson H, Zhao Y, Sparrelid E, Brismar TB. Scandinavian Journal of Gastroenterology. 2022 Feb 2:1-8.
https://doi.org/10.1080/00365521.2022.2032321
II. Multimodal perioperative assessment of liver function and volume in patients undergoing hepatectomy for colorectal liver metastasis: a comparison of the indocyanine green retention test, 99mTc mebrofenin hepatobiliary scintigraphy and gadoxetic acid enhanced MRI. [Submitted]
III. Predictive value of gadoxetic acid-enhanced MRI for posthepatectomy liver failure: a systematic review. Wang Q, Wang A, Sparrelid E, Zhang J, Zhao Y, Ma K, Brismar TB. European Radiology. 2022 Mar;32(3):1792-1803.
https://doi.org/10.1007/s00330-021-08297-8
IV. A radiomics model based on preoperative gadoxetic acid enhanced MRI for predicting posthepatectomy liver failure in patients with hepatocellular carcinoma. [Submitted]
History
Defence date
2022-05-23Department
- Department of Clinical Science, Intervention and Technology
Publisher/Institution
Karolinska InstitutetMain supervisor
Brismar, TorkelCo-supervisors
Sparrelid, Ernesto; Hassan, MoustaphaPublication year
2022Thesis type
- Doctoral thesis
ISBN
978-91-8016-591-4Number of supporting papers
4Language
- eng