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Quantitative assessment of liver fibrosis by digital image analysis reveals correlation with qualitative clinical fibrosis staging in liver transplant patients

Kun Jiang, Mohammad K. Mohammad, Wasim A. Dar, Jun Kong, Alton B. Farris, Yun-Wen Zheng
2020 PLoS ONE  
We aimed to assess liver fibrosis degree with quantitative morphometric measurements of histopathological sections utilizing digital image analysis (DIA) and to further investigate if a correlation with  ...  Digital quantitative assessment of portal triad size and fibrosis percentage demonstrates a strong correlation with visually assessed histologic stage of liver fibrosis and complements the standard assessment  ...  segmentation and exclusion of extraneous structures.  ... 
doi:10.1371/journal.pone.0239624 pmid:32986732 fatcat:kv636hmlpjdrrkgpejnec3djfy

Accuracy of Estimation of Graft Size for Living-Related Liver Transplantation: First Results of a Semi-Automated Interactive Software for CT-Volumetry

Theresa Mokry, Nadine Bellemann, Dirk Müller, Justo Lorenzo Bermejo, Miriam Klauß, Ulrike Stampfl, Boris Radeleff, Peter Schemmer, Hans-Ulrich Kauczor, Christof-Matthias Sommer, Nupur Gangopadhyay
2014 PLoS ONE  
Results: Liver segments II/III, II-IV and V-VIII served in 6, 3, and 7 donors as transplanted liver segments.  ...  Materials and Methods: Sixteen donors for living-related liver transplantation (11 male; mean age: 38.269.6 years) underwent contrast-enhanced CT prior to graft removal.  ...  Acknowledgments The authors would like to thank the technicians of the Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany, for the performance of  ... 
doi:10.1371/journal.pone.0110201 pmid:25330198 pmcid:PMC4201494 fatcat:xmv67cimabhppnz6yt34o4elki

Applications of Machine Learning and Deep Learning in Ultrasound Imaging

Siddhika Arunachalam
2020 International Journal of Scientific Research in Computer Science Engineering and Information Technology  
In this paper, leading Machine Learning (ML) and Deep Learning (DL) approaches and research directions in US, with an emphasis on recent ML and DL advances is discussed.  ...  As US devices become smaller, due to progressive miniaturization of US devices in the last decade, increased computational capability can contribute significantly to decreasing variability through advanced  ...  The aggregated machine intelligence will have the ability to observe data, orient the end user, assess new information, and assist with decision making.  ... 
doi:10.32628/cseit206429 fatcat:g4uuc5x2cjgrta2bmyag6tf2zq

MRI-guided Biopsy to Correlate Tissue Specimens with MR Elastography Stiffness Readings in Liver Transplants

Ryan B. Perumpail, Josh Levitsky, Yi Wang, Victoria S. Lee, Jennifer Karp, Ning Jin, Guang-Yu Yang, Bradley D. Bolster, Saurabh Shah, Sven Zuehlsdorff, Albert A. Nemcek, Andrew C. Larson (+2 others)
2012 Academic Radiology  
In this study, the ability of real-time MRI to guide biopsies of segments of the liver with different MRE stiffness values in the same post-transplant patient was assessed.  ...  The Wilcoxon signed-rank test was used to compare mean stiffness differences for highest and lower MRE stiffness segments, with α = 0.05.  ...  Richard Ehman (Mayo Clinic, Rochester, MN) who provided access to prototype hardware and software for MRE and assisted with manuscript preparation.  ... 
doi:10.1016/j.acra.2012.05.011 pmid:22877987 pmcid:PMC3432910 fatcat:bygw3sppuncghcgavxca4eb4my

Digital Image Analysis of Picrosirius Red Staining: A Robust Method for Multi-Organ Fibrosis Quantification and Characterization

Guillaume E. Courtoy, Isabelle Leclercq, Antoine Froidure, Guglielmo Schiano, Johann Morelle, Olivier Devuyst, François Huaux, Caroline Bouzin
2020 Biomolecules  
The proposed method involves a novel algorithm for more specific and more sensitive detection of collagen fibers stained by picrosirius red (PSR), a computer-assisted segmentation of histological structures  ...  We applied this new method on established mouse models of liver, lung, and kidney fibrosis and demonstrated its validity by evidencing topological collagen accumulation in relevant histological compartments  ...  We are indebted to Michele de Beuckelaer for her help in histological preparation and to Aurélie Daumerie for her advice with Visiopharm.  ... 
doi:10.3390/biom10111585 pmid:33266431 fatcat:iwacfsl6g5emlh3cbckrqglh6y

Performance of image guided navigation in laparoscopic liver surgery – A systematic review

C. Schneider, M. Allam, D. Stoyanov, D.J. Hawkes, K. Gurusamy, B.R. Davidson
2021 Surgial oncology  
Surgeon feedback suggests that current state of the art IGS may be useful as a supplementary navigation tool, especially in small liver lesions that are difficult to locate.  ...  Due to the heterogeneity of the retrieved data it was not possible to conduct a meta-analysis. Therefore results are presented in tabulated and narrative format.  ...  Some of the proposed methods to overcome this issue have been the use of deep learning to automatically segment (i.e. distinguish) the liver from surrounding organs [40] and the application of a scoring  ... 
doi:10.1016/j.suronc.2021.101637 pmid:34358880 fatcat:iik25ikn7nhntfngbvdocnpuci

Liver angulometry: a simple method to estimate liver volume and ratios

Reza Kianmanesh, Tullio Piardi, Esther Tamby, Alina Parvanescu, Onorina Bruno, Elisa Palladino, Olivier Bouché, Simon Msika, Daniele Sommacale
2013 HPB  
Objectives: Volumetry is standard method for evaluating the volumes of the right liver (RL), left liver (LL), left lateral segments (LLS), total liver (TL) and future liver remnant (FLR).  ...  Left and right tangent lines passing the liver edges were drawn and joined to the centre of the vertebra defining the TL angle.  ...  in two liver CT [or magnetic resonance imaging (MRI)] slices and can be used to assess the volumes of the total liver (TL), right liver (RL) and left liver (LL).  ... 
doi:10.1111/hpb.12079 pmid:23472855 pmcid:PMC3843616 fatcat:hmqh4k6l2vgnrlbnf4oueepp5m

aPROMISE: A Novel Automated-PROMISE platform to Standardize Evaluation of Tumor Burden in 18F-DCFPyL (PSMA) images of Veterans with Prostate Cancer

Nicholas Nickols, Aseem Anand, Kerstin Johnsson, Johan Brynolfsson, Pablo Borrelli, jesus Juarez, Neil Parikh, Lida Jafari, Matthias Eiber, Matthew B. Rettig
2021 Journal of Nuclear Medicine  
Correlation coefficient and ICC was used to evaluate the inter-reader variability of the quantitative assessment (miPSMA-index) in each stage.  ...  the broader standardization of PSMA imaging assessment and to its clinical utility in management of prostate cancer patients.  ...  to some extent in other organs and blood vessels (4).  ... 
doi:10.2967/jnumed.120.261863 pmid:34049980 fatcat:wq7iz4wjereatbs7gnk7zdsrxe

Automatized Hepatic Tumor Volume Analysis of Neuroendocrine Liver Metastases by Gd-EOB MRI—A Deep-Learning Model to Support Multidisciplinary Cancer Conference Decision-Making

Uli Fehrenbach, Siyi Xin, Alexander Hartenstein, Timo Alexander Auer, Franziska Dräger, Konrad Froböse, Henning Jann, Martina Mogl, Holger Amthauer, Dominik Geisel, Timm Denecke, Bertram Wiedenmann (+1 others)
2021 Cancers  
Methods: Manual 3D-segmentations of NELM and livers (149 patients in 278 Gd-EOB MRI scans) were used to train a neural network (U-Net architecture).  ...  Rapid quantification of liver metastasis for diagnosis and follow-up is an unmet medical need in patients with secondary liver malignancies.  ...  Our study shows that deep-learning models can assist the MCC's decisions by automatized the quantification of HTL.  ... 
doi:10.3390/cancers13112726 pmid:34072865 fatcat:2ggmkgacofawhgvl7cp33boqde

Consensus recommendations of three-dimensional visualization for diagnosis and management of liver diseases

Chihua Fang, Jihyun An, Antonio Bruno, Xiujun Cai, Jia Fan, Jiro Fujimoto, Rita Golfieri, Xishan Hao, Hongchi Jiang, Long R. Jiao, Anand V. Kulkarni, Hauke Lang (+25 others)
2020 Hepatology International  
Over the last decade, it has been proven safe and effective to use 3D simulation software for pre-hepatectomy assessment, virtual hepatectomy, and measurement of liver volumes in blood flow areas of the  ...  Herein, we provide recommendations for the research on diagnosis and management of 3D visualization in liver diseases to meet this urgent need in this research field.  ...  IV, V, and VIII, charac- terized by a wide and deep invasion of the parenchyma, or their proximity to the middle hepatic vein Central bisectionectomy (resection of segments IV, V, and VIII ± I)  ... 
doi:10.1007/s12072-020-10052-y pmid:32638296 fatcat:khpyqbvdjjftto3p4ocl67pk5a

Texture Analysis of Gray-Scale Ultrasound Images for Staging of Hepatic Fibrosis

Eun Joo Park, Seung Ho Kim, Sang Joon Park, Tae Wook Baek
2020 Journal of the Korean Society of Radiology  
Conclusion A significant difference was observed regarding skewness in segment 5 between patients with no fibrosis and patients with mild fibrosis.  ...  Skewness in hepatic segment 5 showed a difference between patients with no fibrosis and mild fibrosis (0.2392 ± 0.3361, 0.4134 ± 0.3004, respectively, p = 0.0109).  ...  Acknowledgments This research received no specific grant from any funding agency in the public, commercial, or notfor-profit sectors.  ... 
doi:10.3348/jksr.2019.0185 fatcat:5zulp5lfxbdnfpimcq6z4sukfm

Quantification of Liver Fibrosis—A Comparative Study

Alexandros Arjmand, Markos G. Tsipouras, Alexandros T. Tzallas, Roberta Forlano, Pinelopi Manousou, Nikolaos Giannakeas
2020 Applied Sciences  
Liver disease has been targeted as the fifth most common cause of death worldwide and tends to steadily rise.  ...  The purpose is to identify the major strengths and "gray-areas" in the landscape of this topic.  ...  In particular, the Ishak HAI was employed to assess NIA and fibrosis, while the performance index rating (PIR) score was used to assess the dynamic changes of liver fibrosis pre-and post-treatment.  ... 
doi:10.3390/app10020447 fatcat:laisu5u5onb65iiwzlfvewtenm

Whole Slide Imaging and Its Applications to Histopathological Studies of Liver Disorders

Rossana C. N. Melo, Maximilian W. D. Raas, Cinthia Palazzi, Vitor H. Neves, Kássia K. Malta, Thiago P. Silva
2020 Frontiers in Medicine  
We address how WSI may improve the assessment and quantification of multiple histological parameters in the liver, and help diagnose several hepatic conditions with important clinical implications.  ...  In this review, we summarize current knowledge on the application of WSI to histopathological analyses of liver disorders as well as to understand liver biology.  ...  All authors contributed in part to writing and editing the manuscript and shaping the figures and approved the final version.  ... 
doi:10.3389/fmed.2019.00310 pmid:31970160 pmcid:PMC6960181 fatcat:j3qxq6ke5fbn3ba2n3ejbc6z3m

Multiphase CT-based prediction of Child-Pugh classification: a machine learning approach

Johannes Thüring, Oliver Rippel, Christoph Haarburger, Dorit Merhof, Philipp Schad, Philipp Bruners, Christiane K. Kuhl, Daniel Truhn
2020 European Radiology Experimental  
The performance of a CNN in assessing Child-Pugh class based on multiphase abdominal CT images is comparable to that of ERs.  ...  Their performances were compared to the prediction of experienced radiologists (ERs). Spearman correlation coefficients and accuracy were assessed for all predictive models.  ...  Acknowledgements The authors would like to thank Dr. Andreas Ritter and Mr. Roman Ivan for maintaining the digital infrastructure.  ... 
doi:10.1186/s41747-020-00148-3 pmid:32249336 fatcat:6ti6sumfrjg2zageoygplbcm4y

Non-Alcoholic Fatty Liver Disease: Implementing Complete Automated Diagnosis and Staging. A Systematic Review

Stefan L. Popa, Abdulrahman Ismaiel, Pop Cristina, Mogosan Cristina, Giuseppe Chiarioni, Liliana David, Dan L. Dumitrascu
2021 Diagnostics  
Methods: PubMed, EMBASE, Cochrane Library, and WILEY databases were screened for relevant publications in relation to AI applications in NAFLD.  ...  The search terms included: (non-alcoholic fatty liver disease OR NAFLD) AND (artificial intelligence OR machine learning OR neural networks OR deep learning OR automated diagnosis OR computer-aided diagnosis  ...  Deep learning can utilize these informationx in order to to assess for the presence of nonalcoholic fatty liver disease (NAFLD).  ... 
doi:10.3390/diagnostics11061078 fatcat:ecqguigdqfan5gdfwi4btapb3i
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