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Kutaiba N, Chung W, Goodwin M, Testro A, Egan G, Lim R. The impact of hepatic and splenic volumetric assessment in imaging for chronic liver disease: a narrative review. Insights Imaging 2024; 15:146. [PMID: 38886297 PMCID: PMC11183036 DOI: 10.1186/s13244-024-01727-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 05/26/2024] [Indexed: 06/20/2024] Open
Abstract
Chronic liver disease is responsible for significant morbidity and mortality worldwide. Abdominal computed tomography (CT) and magnetic resonance imaging (MRI) can fully visualise the liver and adjacent structures in the upper abdomen providing a reproducible assessment of the liver and biliary system and can detect features of portal hypertension. Subjective interpretation of CT and MRI in the assessment of liver parenchyma for early and advanced stages of fibrosis (pre-cirrhosis), as well as severity of portal hypertension, is limited. Quantitative and reproducible measurements of hepatic and splenic volumes have been shown to correlate with fibrosis staging, clinical outcomes, and mortality. In this review, we will explore the role of volumetric measurements in relation to diagnosis, assessment of severity and prediction of outcomes in chronic liver disease patients. We conclude that volumetric analysis of the liver and spleen can provide important information in such patients, has the potential to stratify patients' stage of hepatic fibrosis and disease severity, and can provide critical prognostic information. CRITICAL RELEVANCE STATEMENT: This review highlights the role of volumetric measurements of the liver and spleen using CT and MRI in relation to diagnosis, assessment of severity, and prediction of outcomes in chronic liver disease patients. KEY POINTS: Volumetry of the liver and spleen using CT and MRI correlates with hepatic fibrosis stages and cirrhosis. Volumetric measurements correlate with chronic liver disease outcomes. Fully automated methods for volumetry are required for implementation into routine clinical practice.
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Affiliation(s)
- Numan Kutaiba
- Department of Radiology, Austin Health, 145 Studley Road, Heidelberg, VIC, 3084, Australia.
- The University of Melbourne, Parkville, Melbourne, VIC, Australia.
| | - William Chung
- The University of Melbourne, Parkville, Melbourne, VIC, Australia
- Department of Gastroenterology, Austin Health, 145 Studley Road, Heidelberg, VIC, 3084, Australia
| | - Mark Goodwin
- Department of Radiology, Austin Health, 145 Studley Road, Heidelberg, VIC, 3084, Australia
- The University of Melbourne, Parkville, Melbourne, VIC, Australia
| | - Adam Testro
- The University of Melbourne, Parkville, Melbourne, VIC, Australia
- Department of Gastroenterology, Austin Health, 145 Studley Road, Heidelberg, VIC, 3084, Australia
| | - Gary Egan
- Monash Biomedical Imaging, Monash University, Clayton, VIC, 3800, Australia
| | - Ruth Lim
- Department of Radiology, Austin Health, 145 Studley Road, Heidelberg, VIC, 3084, Australia
- The University of Melbourne, Parkville, Melbourne, VIC, Australia
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Chen Y, Zeng L, Zhu H, Wu Q, Liu R, Liang Q, Chen B, Dai H, Tang K, Liao C, Huang Y, Yan X, Fan K, Du JZ, Lin R, Wang J. Ferritin Nanocaged Doxorubicin Potentiates Chemo-Immunotherapy against Hepatocellular Carcinoma via Immunogenic Cell Death. SMALL METHODS 2023; 7:e2201086. [PMID: 36446639 DOI: 10.1002/smtd.202201086] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 11/05/2022] [Indexed: 05/17/2023]
Abstract
Although immunotherapy of hepatocellular carcinoma using immune checkpoint inhibitors has achieved certain success, only a subset of patients benefits from this therapeutic strategy. The combination of immunostimulatory chemotherapeutics represents a promising strategy to enhance the effectiveness of immunotherapy. However, it is hampered by the poor delivery of conventional chemotherapeutics. Here, it is shown that H-ferritin nanocages loaded with doxorubicin (DOX@HFn) show potent chemo-immunotherapy in hepatocellular carcinoma tumor models. DOX@HFn is constructed with uniform size, high stability, favorable drug loading, and intracellular acidity-driven drug release. The receptor-mediated targeting of DOX@HFn to liver cancer cells promote cellular uptake and tumor penetration in vitro and in vivo. DOX@HFn triggers immunogenic cell death to tumor cells and promotes the subsequent activation and maturation of dendritic cells. In vivo studies in H22 subcutaneous hepatoma demonstrate that DOX@HFn significantly inhibits the tumor growth with >30% tumors completely eliminated, while alleviating the systemic toxicity of free DOX. DOX@HFn also exhibits robust antitumor immune response and tumoricidal effect in a more aggressive Hepa1-6 orthotopic liver tumor model, which is confirmed by the in situ magnetic resonance imaging and transcriptome sequencing. This study provides a facile and robust strategy to improve therapeutic efficacy of liver cancer.
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Affiliation(s)
- Yang Chen
- School of Medicine, South China University of Technology, Guangzhou, Guangdong, 510006, China
- Department of Clinical Laboratory, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, 330006, China
| | - Linyuan Zeng
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China
- Center for Precision Medicine, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China
| | - Hongzhang Zhu
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China
| | - Qifei Wu
- CAS Engineering Laboratory for Nanozyme, Key Laboratory of Protein and Peptide Pharmaceuticals, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
- Department of Thoracic Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, 710061, China
| | - Rong Liu
- School of Medicine, South China University of Technology, Guangzhou, Guangdong, 510006, China
| | - Qian Liang
- CAS Engineering Laboratory for Nanozyme, Key Laboratory of Protein and Peptide Pharmaceuticals, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Bin Chen
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China
| | - Haitao Dai
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China
| | - Keyu Tang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China
| | - Changli Liao
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China
| | - Yonghui Huang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China
| | - Xiyun Yan
- CAS Engineering Laboratory for Nanozyme, Key Laboratory of Protein and Peptide Pharmaceuticals, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Kelong Fan
- CAS Engineering Laboratory for Nanozyme, Key Laboratory of Protein and Peptide Pharmaceuticals, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Jin-Zhi Du
- School of Medicine, South China University of Technology, Guangzhou, Guangdong, 510006, China
| | - Run Lin
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China
- Center for Precision Medicine, Sun Yat-sen University, Guangzhou, Guangdong, 510080, China
| | - Jun Wang
- School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, Guangdong, 511442, China
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Müller L, Kloeckner R, Mähringer-Kunz A, Stoehr F, Düber C, Arnhold G, Gairing SJ, Foerster F, Weinmann A, Galle PR, Mittler J, Pinto Dos Santos D, Hahn F. Fully automated AI-based splenic segmentation for predicting survival and estimating the risk of hepatic decompensation in TACE patients with HCC. Eur Radiol 2022; 32:6302-6313. [PMID: 35394184 PMCID: PMC9381627 DOI: 10.1007/s00330-022-08737-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 01/19/2022] [Accepted: 03/05/2022] [Indexed: 01/19/2023]
Abstract
OBJECTIVES Splenic volume (SV) was proposed as a relevant prognostic factor for patients with hepatocellular carcinoma (HCC). We trained a deep-learning algorithm to fully automatically assess SV based on computed tomography (CT) scans. Then, we investigated SV as a prognostic factor for patients with HCC undergoing transarterial chemoembolization (TACE). METHODS This retrospective study included 327 treatment-naïve patients with HCC undergoing initial TACE at our tertiary care center between 2010 and 2020. A convolutional neural network was trained and validated on the first 100 consecutive cases for spleen segmentation. Then, we used the algorithm to evaluate SV in all 327 patients. Subsequently, we evaluated correlations between SV and survival as well as the risk of hepatic decompensation during TACE. RESULTS The algorithm showed Sørensen Dice Scores of 0.96 during both training and validation. In the remaining 227 patients assessed with the algorithm, spleen segmentation was visually approved in 223 patients (98.2%) and failed in four patients (1.8%), which required manual re-assessments. Mean SV was 551 ml. Survival was significantly lower in patients with high SV (10.9 months), compared to low SV (22.0 months, p = 0.001). In contrast, overall survival was not significantly predicted by axial and craniocaudal spleen diameter. Furthermore, patients with a hepatic decompensation after TACE had significantly higher SV (p < 0.001). CONCLUSION Automated SV assessments showed superior survival predictions in patients with HCC undergoing TACE compared to two-dimensional spleen size estimates and identified patients at risk of hepatic decompensation. Thus, SV could serve as an automatically available, currently underappreciated imaging biomarker. KEY POINTS • Splenic volume is a relevant prognostic factor for prediction of survival in patients with HCC undergoing TACE, and should be preferred over two-dimensional surrogates for splenic size. • Besides overall survival, progression-free survival and hepatic decompensation were significantly associated with splenic volume, making splenic volume a currently underappreciated prognostic factor prior to TACE. • Splenic volume can be fully automatically assessed using deep-learning methods; thus, it is a promising imaging biomarker easily integrable into daily radiological routine.
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Affiliation(s)
- Lukas Müller
- Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckst. 1, 55131, Mainz, Germany
| | - Roman Kloeckner
- Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckst. 1, 55131, Mainz, Germany
| | - Aline Mähringer-Kunz
- Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckst. 1, 55131, Mainz, Germany
| | - Fabian Stoehr
- Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckst. 1, 55131, Mainz, Germany
| | - Christoph Düber
- Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckst. 1, 55131, Mainz, Germany
| | - Gordon Arnhold
- Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckst. 1, 55131, Mainz, Germany
| | - Simon Johannes Gairing
- Department of Internal Medicine I, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Friedrich Foerster
- Department of Internal Medicine I, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Arndt Weinmann
- Department of Internal Medicine I, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Peter Robert Galle
- Department of Internal Medicine I, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Jens Mittler
- Department of General, Visceral and Transplant Surgery, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Daniel Pinto Dos Santos
- Department of Radiology, University Hospital of Cologne, Cologne, Germany
- Institute for Diagnostic and Interventional Radiology, Goethe-University Frankfurt am Main, Frankfurt, Germany
| | - Felix Hahn
- Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckst. 1, 55131, Mainz, Germany.
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