AI and the post-COVID imaging surge – Part 2

In our recent blog on the post-COVID imaging surge, we spoke about how radiology can leverage AI to deal with the backlog of routine follow-up imaging, scr

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In our recent blog on the post-COVID imaging surge, we spoke about how radiology can leverage AI to deal with the backlog of routine follow-up imaging, screening studies and interventional procedures secondary to the COVID-19 pandemic.

Today, we thought we would share some examples of the applications available to support specific clinical requirements in the post-COVID world. Neuroimaging studies The backlog of MS follow-up studies as well as routine dementia and epilepsy imaging can be addressed through improved radiologist reporting efficiency. AI solutions from CorTechs Labs and icometrix enable radiologists to provide detailed reporting of neurological conditions within time constraints. CorTechs Labs supports radiologists by providing accurate and reliable brain structure volumes along with normative percentiles to aid in the diagnosis and monitoring of patients with neurodegenerative disorders. icometrix provides easy and reliable access to MRI and CT quantification for conditions such as MS, dementia, epilepsy, and traumatic brain injury. Lung cancer screening Blackford Smart Localizer can assist with the backlog of lung cancer screening studies as well as follow-up CT imaging studies by increasing reporting efficiency. Blackford Smart Localizer allows radiologists to quickly locate and compare an increased number of findings and model new measurements based on prior exams. Automated image registration increases radiologist efficiency by 10-20%, and up to 50% for more challenging exams, such as lung nodule comparisons. CT chest studies There is the potential for an increased demand for follow up CT Chest studies of patients infected with COVID-19, in addition to a backlog of routine CT Chest follow-ups. Applications that improve reporting efficiency, such as LungPrint Discovery, can help. Vida LungPrint Discovery has been shown to reduce chest CT reading time of the lung stack by 35% – a significant time saving for radiologists overwhelmed by the caseload. Interventional procedures Finally, how can AI help overcome a backlog of interventional procedures, an area in which efficiency gains are difficult to come by? The answer is in offering alternative workflows, such as those provided by FerriSmart. FerriSmart provides accurate and validated MRI-based measurements of liver iron concentration, allowing patients with confirmed or suspected systemic iron overload to be diverted from invasive liver biopsy to a non-invasive MRI workflow This not only provides a more pleasant procedure for the patient but also eases the workload on the interventional suite. Want to know even more? Check out our SIIM 2020 presentation where Blackford CEO Ben Panter and our partners from CorTechs Labs, Icometrix, Subtle Medical, and VIDA discuss how to best deal with the post-COVID-19 imaging surge: Watch now