• Clinics · Jan 2024

    Development of HepatIA: A computed tomography annotation platform and database for artificial intelligence training in hepatocellular carcinoma detection at a Brazilian tertiary teaching hospital.

    • Bruno Aragão Rocha, Lorena Carneiro Ferreira, Luis Gustavo Rocha Vianna, Ana Claudia Martins Ciconelle, João Martins Cortez Filho, Lucas Salume Lima Nogueira, Maurício Ricardo Moreira da Silva Filho, LeiteClaudia da CostaCDCInstituto de Radiologia (InRad) da Universidade de São Paulo (USP), São Paulo, SP, Brasil., Cesar Higar Nomura, Giovanni Guido Cerri, Flair José Carrilho, and Suzane Kioko Ono.
    • Instituto de Radiologia (InRad) da Universidade de São Paulo (USP), São Paulo, SP, Brasil; Machiron, Guarulhos, SP, Brasil. Electronic address: brunoaragao92@gmail.com.
    • Clinics (Sao Paulo). 2024 Jan 1; 79: 100512100512.

    BackgroundHepatocellular carcinoma (HCC) is a prevalent tumor with high mortality rates. Computed tomography (CT) is crucial in the non-invasive diagnosis of HCC. Recent advancements in artificial intelligence (AI) have shown significant potential in medical imaging analysis. However, developing these AI algorithms is hindered by the scarcity of comprehensive, publicly available liver imaging datasets.ObjectivesThis study aims to detail the tools, data organization, and database structuring used in creating HepatIA, a medical imaging annotation platform and database at a Brazilian tertiary teaching hospital. HepatIA supports liver disease AI research at the institution.Material And MethodsThe authors collected baseline characteristics and CT scans of 656 patients from 2008 to 2021. The database, designed using PostgreSQL and implemented with Django and Vue.js, includes 692 CT volumes from a four-phase abdominal CT protocol. Radiologists made segmentation annotations using the OHIF medical image viewer, incorporating MONAI Label for pre-annotation segmentation models. The annotation process included detailed descriptions of liver morphology and nodule characteristics.ResultsThe HepatIA database currently includes healthy individuals and those with liver diseases such as HCC and cirrhosis. The database dashboard facilitates user interaction with intuitive plots and histograms. Key patient demographics include 64% males and an average age of 56.89 years. The database supports various filters for detailed searches, enhancing research capabilities.ConclusionA comprehensive data structure was successfully created and integrated with the IT systems of a teaching hospital, enabling research on deep learning algorithms applied to abdominal CT scans for investigating hepatic lesions such as HCC.Copyright © 2024 HCFMUSP. Published by Elsevier España, S.L.U. All rights reserved.

      Pubmed     Copy Citation     Plaintext  

      Add institutional full text...

    Notes

     
    Knowledge, pearl, summary or comment to share?
    300 characters remaining
    help        
    You can also include formatting, links, images and footnotes in your notes
    • Simple formatting can be added to notes, such as *italics*, _underline_ or **bold**.
    • Superscript can be denoted by <sup>text</sup> and subscript <sub>text</sub>.
    • Numbered or bulleted lists can be created using either numbered lines 1. 2. 3., hyphens - or asterisks *.
    • Links can be included with: [my link to pubmed](http://pubmed.com)
    • Images can be included with: ![alt text](https://bestmedicaljournal.com/study_graph.jpg "Image Title Text")
    • For footnotes use [^1](This is a footnote.) inline.
    • Or use an inline reference [^1] to refer to a longer footnote elseweher in the document [^1]: This is a long footnote..

    hide…