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The State of Imaging in Clinical Research - 2020 & Beyond

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Manage episode 339116903 series 3388024
Contenu fourni par ERT. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par ERT ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

What trends have you seen in imaging in 2019?

One of the biggest trends has been an increase in demand for imaging over the last year as more and more trials have begun to require imaging as a primary endpoint. This has always been common in oncology studies in particular, but not the industry is starting to use imaging as a primary endpoint in other indications as well.

What do you think the future looks like?

In 2020 and beyond, there will be a push toward siteless trials. In imaging, we may be able to use subjects who live far from a primary site and previously would have had to travel for imaging. They’ll be able to visit a local center for imaging instead, and have those images uploaded remotely to a platform for centralized assessment. In fact, ERT’s platform allows this already: sites and local centers are able to complete uploads.

How has artificial intelligence had an impact on imaging?

We can use artificial intelligence to determine whether or not an image is appropriate. By using the information we’ve gathered over the past 15 years, we’ve trained an AI algorithm to determine the quality of an image. AI can also pre-segment images and so readers don’t define boundaries within the image themselves. This reduces variability and gives sponsors additional information that they may not have gotten from simplified criteria. Artificial intelligence can be used to improve efficiency and cost, and also maximizes the data being collected, which is particularly important when a patient is being exposed to radiation during the imaging process.

  continue reading

30 episodes

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iconPartager
 
Manage episode 339116903 series 3388024
Contenu fourni par ERT. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par ERT ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

What trends have you seen in imaging in 2019?

One of the biggest trends has been an increase in demand for imaging over the last year as more and more trials have begun to require imaging as a primary endpoint. This has always been common in oncology studies in particular, but not the industry is starting to use imaging as a primary endpoint in other indications as well.

What do you think the future looks like?

In 2020 and beyond, there will be a push toward siteless trials. In imaging, we may be able to use subjects who live far from a primary site and previously would have had to travel for imaging. They’ll be able to visit a local center for imaging instead, and have those images uploaded remotely to a platform for centralized assessment. In fact, ERT’s platform allows this already: sites and local centers are able to complete uploads.

How has artificial intelligence had an impact on imaging?

We can use artificial intelligence to determine whether or not an image is appropriate. By using the information we’ve gathered over the past 15 years, we’ve trained an AI algorithm to determine the quality of an image. AI can also pre-segment images and so readers don’t define boundaries within the image themselves. This reduces variability and gives sponsors additional information that they may not have gotten from simplified criteria. Artificial intelligence can be used to improve efficiency and cost, and also maximizes the data being collected, which is particularly important when a patient is being exposed to radiation during the imaging process.

  continue reading

30 episodes

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