Using AI and Gd-EOB-DTPA-enhanced MR imaging to assess liver function, comparing the MELIF score with the ALBI score
Abstract Monitoring disease progression is particularly important for determining the optimal treatment strategy in patients with liver disease. Especially for patients with diseases that have a reversible course, there is a lack of suitable tools for monitoring liver function. The development and e...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-08-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-39954-1 |
| _version_ | 1827711005957816320 |
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| author | Carolina Río Bártulos Karin Senk Ragnar Bade Mona Schumacher Nico Kaiser Jan Plath Mathis Planert Christian Stroszczynski Jan Woetzel Philipp Wiggermann |
| author_facet | Carolina Río Bártulos Karin Senk Ragnar Bade Mona Schumacher Nico Kaiser Jan Plath Mathis Planert Christian Stroszczynski Jan Woetzel Philipp Wiggermann |
| author_sort | Carolina Río Bártulos |
| collection | DOAJ |
| description | Abstract Monitoring disease progression is particularly important for determining the optimal treatment strategy in patients with liver disease. Especially for patients with diseases that have a reversible course, there is a lack of suitable tools for monitoring liver function. The development and establishment of such tools is very important, especially in view of the expected increase in such diseases in the future. Image-based liver function parameters, such as the T1 relaxometry-based MELIF score, are ideally suited for this purpose. The determination of this new liver function score is fully automated by software developed with AI technology. In this study, the MELIF score is compared with the widely used ALBI score. The ALBI score was used as a benchmark, as it has been shown to better capture the progression of less severe liver disease than the MELD and Child‒Pugh scores. In this study, we retrospectively determined the ALBI and MELIF scores for 150 patients, compared these scores with the corresponding MELD and Child‒Pugh scores (Pearson correlation), and examined the ability of these scores to discriminate between good and impaired liver function (AUC: MELIF 0.8; ALBI 0.77) and to distinguish between patients with and without cirrhosis (AUC: MELIF 0.83, ALBI 0.79). The MELIF score performed more favourably than the ALBI score and may also be suitable for monitoring mild disease progression. Thus, the MELIF score is promising for closing the gap in the available early-stage liver disease monitoring tools (i.e., identification of liver disease at a potentially reversible stage before chronic liver disease develops). |
| first_indexed | 2024-03-10T17:48:45Z |
| format | Article |
| id | doaj.art-424feccf15bc4417b5572d34e8ec2a16 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-10T17:48:45Z |
| publishDate | 2023-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-424feccf15bc4417b5572d34e8ec2a162023-11-20T09:26:38ZengNature PortfolioScientific Reports2045-23222023-08-011311910.1038/s41598-023-39954-1Using AI and Gd-EOB-DTPA-enhanced MR imaging to assess liver function, comparing the MELIF score with the ALBI scoreCarolina Río Bártulos0Karin Senk1Ragnar Bade2Mona Schumacher3Nico Kaiser4Jan Plath5Mathis Planert6Christian Stroszczynski7Jan Woetzel8Philipp Wiggermann9Institut Für Röntgendiagnostik Und Nuklearmedizin, Städtisches Klinikum Braunschweig gGmbHInstitut Für Röntgendiagnostik, Universitätsklinikum RegensburgMeVis Medical Solutions AGMeVis Medical Solutions AGMeVis Medical Solutions AGMeVis Medical Solutions AGInstitut Für Röntgendiagnostik Und Nuklearmedizin, Städtisches Klinikum Braunschweig gGmbHInstitut Für Röntgendiagnostik, Universitätsklinikum RegensburgMeVis Medical Solutions AGInstitut Für Röntgendiagnostik Und Nuklearmedizin, Städtisches Klinikum Braunschweig gGmbHAbstract Monitoring disease progression is particularly important for determining the optimal treatment strategy in patients with liver disease. Especially for patients with diseases that have a reversible course, there is a lack of suitable tools for monitoring liver function. The development and establishment of such tools is very important, especially in view of the expected increase in such diseases in the future. Image-based liver function parameters, such as the T1 relaxometry-based MELIF score, are ideally suited for this purpose. The determination of this new liver function score is fully automated by software developed with AI technology. In this study, the MELIF score is compared with the widely used ALBI score. The ALBI score was used as a benchmark, as it has been shown to better capture the progression of less severe liver disease than the MELD and Child‒Pugh scores. In this study, we retrospectively determined the ALBI and MELIF scores for 150 patients, compared these scores with the corresponding MELD and Child‒Pugh scores (Pearson correlation), and examined the ability of these scores to discriminate between good and impaired liver function (AUC: MELIF 0.8; ALBI 0.77) and to distinguish between patients with and without cirrhosis (AUC: MELIF 0.83, ALBI 0.79). The MELIF score performed more favourably than the ALBI score and may also be suitable for monitoring mild disease progression. Thus, the MELIF score is promising for closing the gap in the available early-stage liver disease monitoring tools (i.e., identification of liver disease at a potentially reversible stage before chronic liver disease develops).https://doi.org/10.1038/s41598-023-39954-1 |
| spellingShingle | Carolina Río Bártulos Karin Senk Ragnar Bade Mona Schumacher Nico Kaiser Jan Plath Mathis Planert Christian Stroszczynski Jan Woetzel Philipp Wiggermann Using AI and Gd-EOB-DTPA-enhanced MR imaging to assess liver function, comparing the MELIF score with the ALBI score Scientific Reports |
| title | Using AI and Gd-EOB-DTPA-enhanced MR imaging to assess liver function, comparing the MELIF score with the ALBI score |
| title_full | Using AI and Gd-EOB-DTPA-enhanced MR imaging to assess liver function, comparing the MELIF score with the ALBI score |
| title_fullStr | Using AI and Gd-EOB-DTPA-enhanced MR imaging to assess liver function, comparing the MELIF score with the ALBI score |
| title_full_unstemmed | Using AI and Gd-EOB-DTPA-enhanced MR imaging to assess liver function, comparing the MELIF score with the ALBI score |
| title_short | Using AI and Gd-EOB-DTPA-enhanced MR imaging to assess liver function, comparing the MELIF score with the ALBI score |
| title_sort | using ai and gd eob dtpa enhanced mr imaging to assess liver function comparing the melif score with the albi score |
| url | https://doi.org/10.1038/s41598-023-39954-1 |
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