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Stulpinas R, Morkunas M, Rasmusson A, Drachneris J, Augulis R, Gulla A, Strupas K, Laurinavicius A. Improving HCC Prognostic Models after Liver Resection by AI-Extracted Tissue Fiber Framework Analytics. Cancers (Basel) 2023; 16:106. [PMID: 38201532 PMCID: PMC10778366 DOI: 10.3390/cancers16010106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 12/11/2023] [Accepted: 12/21/2023] [Indexed: 01/12/2024] Open
Abstract
Despite advances in diagnostic and treatment technologies, predicting outcomes of patients with hepatocellular carcinoma (HCC) remains a challenge. Prognostic models are further obscured by the variable impact of the tumor properties and the remaining liver parenchyma, often affected by cirrhosis or non-alcoholic fatty liver disease that tend to precede HCC. This study investigated the prognostic value of reticulin and collagen microarchitecture in liver resection samples. We analyzed 105 scanned tissue sections that were stained using a Gordon and Sweet's silver impregnation protocol combined with Picric Acid-Sirius Red. A convolutional neural network was utilized to segment the red-staining collagen and black linear reticulin strands, generating a detailed map of the fiber structure within the HCC and adjacent liver tissue. Subsequent hexagonal grid subsampling coupled with automated epithelial edge detection and computational fiber morphometry provided the foundation for region-specific tissue analysis. Two penalized Cox regression models using LASSO achieved a concordance index (C-index) greater than 0.7. These models incorporated variables such as patient age, tumor multifocality, and fiber-derived features from the epithelial edge in both the tumor and liver compartments. The prognostic value at the tumor edge was derived from the reticulin structure, while collagen characteristics were significant at the epithelial edge of peritumoral liver. The prognostic performance of these models was superior to models solely reliant on conventional clinicopathologic parameters, highlighting the utility of AI-extracted microarchitectural features for the management of HCC.
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Affiliation(s)
- Rokas Stulpinas
- Faculty of Medicine, Institute of Biomedical Sciences, Department of Pathology and Forensic Medicine, Vilnius University, 03101 Vilnius, Lithuania (A.L.)
- National Center of Pathology, Affiliate of Vilnius University Hospital Santaros Klinikos, 08406 Vilnius, Lithuania;
| | - Mindaugas Morkunas
- National Center of Pathology, Affiliate of Vilnius University Hospital Santaros Klinikos, 08406 Vilnius, Lithuania;
- Vilnius Santaros Klinikos Biobank, Vilnius University Hospital Santaros Klinikos, 08661 Vilnius, Lithuania
| | - Allan Rasmusson
- Faculty of Medicine, Institute of Biomedical Sciences, Department of Pathology and Forensic Medicine, Vilnius University, 03101 Vilnius, Lithuania (A.L.)
- National Center of Pathology, Affiliate of Vilnius University Hospital Santaros Klinikos, 08406 Vilnius, Lithuania;
| | - Julius Drachneris
- Faculty of Medicine, Institute of Biomedical Sciences, Department of Pathology and Forensic Medicine, Vilnius University, 03101 Vilnius, Lithuania (A.L.)
- National Center of Pathology, Affiliate of Vilnius University Hospital Santaros Klinikos, 08406 Vilnius, Lithuania;
| | - Renaldas Augulis
- Faculty of Medicine, Institute of Biomedical Sciences, Department of Pathology and Forensic Medicine, Vilnius University, 03101 Vilnius, Lithuania (A.L.)
- National Center of Pathology, Affiliate of Vilnius University Hospital Santaros Klinikos, 08406 Vilnius, Lithuania;
| | - Aiste Gulla
- Faculty of Medicine, Institute of Clinical Medicine, Vilnius University, 03101 Vilnius, Lithuania
- Faculty of Medicine, Centre for Visceral Medicine and Translational Research, Vilnius University, 03101 Vilnius, Lithuania
- Center of Abdominal Surgery, Vilnius University Hospital Santaros Klinikos, 08410 Vilnius, Lithuania
| | - Kestutis Strupas
- Faculty of Medicine, Institute of Clinical Medicine, Vilnius University, 03101 Vilnius, Lithuania
- Faculty of Medicine, Centre for Visceral Medicine and Translational Research, Vilnius University, 03101 Vilnius, Lithuania
- Center of Abdominal Surgery, Vilnius University Hospital Santaros Klinikos, 08410 Vilnius, Lithuania
| | - Arvydas Laurinavicius
- Faculty of Medicine, Institute of Biomedical Sciences, Department of Pathology and Forensic Medicine, Vilnius University, 03101 Vilnius, Lithuania (A.L.)
- National Center of Pathology, Affiliate of Vilnius University Hospital Santaros Klinikos, 08406 Vilnius, Lithuania;
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McPherson S, Shearer J. Moving forward with the detection of chronic liver disease. Frontline Gastroenterol 2023; 14:449-450. [PMID: 37854777 PMCID: PMC10579543 DOI: 10.1136/flgastro-2023-102470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 08/29/2023] [Indexed: 10/20/2023] Open
Affiliation(s)
- Stuart McPherson
- Liver Unit and NIHR Biomedical Research Centre, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Jessica Shearer
- Liver Unit, Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne, UK
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