A globally available COVID-19 – Template for clinical imaging studies

  1. G.A. Salg
  2. M.K. Ganten
  3. M. Baumhauer
  4. C.P. Heußel
  5. J. Kleesiek

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Abstract

Background

The pandemic spread of COVID-19 has caused worldwide implications on societies and economies. Chest computed tomography (CT) has been found to support both, current diagnostic and disease monitoring. A joint approach to collect, analyze and share clinical and imaging information about COVID-19 in the highest quality possible is urgently needed.

Methods

An evidence-based reporting template was developed for assessing COVID-19 pneumonia using an FDA-approved medical software. The annotation of qualitative and quantitative findings including radiomics features is performed directly on primary imaging data. For data collection, secondary information from the patient history and clinical data such as symptoms and comorbidities are queried.

Results

License-royalty free, cloud-based web platform and on-premise deployments are offered. Hospitals can upload, assess, report and if pseudonymized share their COVID-19 cases. The aggregation of radiomics in correlation with rt-PCR, patient history, clinical and radiological findings, systematically documented in a single database, will lead to optimized diagnosis, risk stratification and response evaluation. A customizable analytics dashboard allows the explorative real-time data analysis of imaging features and clinical information.

Conclusions

The COVID-19-Template is based on a systematic, computer-assisted and context-guided approach to collect, analyze and share data. Epidemiological and clinical studies for therapies and vaccine candidates can be implemented in compliance with high data quality, integrity and traceability.

An additional explanation video of the COVID-19-Template video is provided via: http://cloud1.mint-medical.de/downloads/player/index.html?v=Covid19StandardizedAssessmentWeb

Highlights

  • Dynamic evidence-based electronic case report form (eCRF) for COVID-19 including documentation of primary imaging data, secondary clinical data and patient history including radiomics features

  • Computer-assisted, context-guided reporting approach based on FDA approved medical product software package available free of charge

  • Data quality, traceability, integrity in open-access web platform

  • Customizable analytics dashboard for explorative real-time data analysis of imaging features and clinical information

  • Human and machine-readable data export for clinical trials

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.04.02.20048793: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Our approach has limitations. Data acquisition and handling of an eCRF is more time consuming than a reading in clinical routine. Further, integral data acquisition of imaging and clinical parameters requires an interdisciplinary input, which might not be available for every case. Currently, the template is designed for CT imaging only, but providing an eCRF for Chest-X-rays can be realized easily and is the scope for future work. Lastly, it might also appear controversial, that an increased research effort is encouraged even though manpower is limited during the current pandemic. The primary goal is to provide a tool for future clinical studies which are urgently needed. We do not want to present a predefined global standard for the assessment and reporting for patients with COVID-19 infection, instead the intention is to initiate an evidence-based approach to define a joint global standard that can be adapted to the dynamic situations and discoveries yet to come. This might also discover regional difference in the disease leading to a personalized patient management. The eCRF can be adapted and refined according to evidence generated in ongoing and future clinical trials but also through the crowd-intelligence approach itself. Any addition or changes in template parameters will not put previously collected data in danger. Data integrity is permanently ensured, and even retrospective acquisition of certain parameters will be possible if applicable. Chest CT as a supporting t...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. ScreenIT

    SciScore for 10.1101/2020.04.02.20048793: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.Randomizationnot detected.Blindingnot detected.Power Analysisnot detected.Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Introduction The infection with SARS-CoV-2 has become pandemic since the first cases have been reported from the Hubei province to the WHO on Dec. 31st, 2019.
    SARS-CoV-2
    suggested: (Sino Biological Cat# 40143-R019, AB_2827973)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, please follow this link.

  3. Version published to 10.1101/2020.04.02.20048793v1 on medRxiv