Newsbytes

COVID-19 digital pathology repository picking up steam

September 2021—When Stephen Hewitt, MD, PhD, went down the COVID-19 rabbit hole in early 2020, little did he know about the long-term value of a comprehensive COVID-19 digital pathology repository—and how such a project would come to fill his days and, occasionally, nights.

But fill his time it has. Since the early days of the pandemic, Dr. Hewitt has been working diligently on behalf of the National Institutes of Health to make the repository more than its original offering of a “flat file dump of cases with a little bit of metadata so you could find an individual patient or an individual organ.”

To understand the future of the NIH’s COVID-19 Digital Pathology Repository requires cognizance of its past. “We needed a better understanding of the pathophysiology of SARS-CoV-2 if we were to treat patients effectively,” recalls Dr. Hewitt, head of the Experimental Pathology Laboratory, Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, and captain, U.S. Public Health Service. To that end, he and collaborators from the NIH, in partnership with Indica Labs and Octo, launched the COVID-DPR—a centralized, cloud-based whole slide image library of tissue from those with SARS-CoV-2.

The repository, which went live in April 2020, is hosted by the NIH and underpinned by Indica Labs’ Halo Link platform, a Web-based collaborative slide-management and slide-sharing platform. The overarching goal for the COVID-DPR, says Dr. Hewitt, is to have it serve as a reference data set of COVID-19–related pathology for the greater biomedical community that, among other functions, helps inform immune response to SARS-CoV-2.

As of CAP TODAY press time, the COVID-DPR housed more than 2,300 whole slide images representing over 100 autopsies, as well as surgical specimens, cytology specimens, blood smears, and a comparator case of H1N1 influenza. The site also contains placental images because the placental pathology for pregnant women infected with SARS-CoV-2 is complex, Dr. Hewitt says. The autopsy images are arranged by organ and patient, with all patient information deidentified. But because the Halo platform is highly flexible, it easily could allow for other organizational schemas, Dr. Hewitt says, such as categorization by disease process “if we chose to break it down to patients with diffuse alveolar damage, thromboemboli, or pulmonary edema, with reference to lungs.”

Though many of the autopsy cases in the repository were donated by Dr. Hewitt’s pathologist colleagues at other institutions, the NIH has contributed 44 autopsies from its COVID-19 autopsy consortium, 15 of which had been uploaded by CAP TODAY press time. After uploading the NIH autopsies, which are comprehensive across organ systems, with multiple sections per site, Dr. Hewitt plans to add more autopsies from external collaborators. (Cases can be submitted via the COVID-DPR website, at covid19pathology.nih.gov.)

As they address a number of roadblocks—staffing and remote work issues chief among them, in addition to competing institutional goals—Dr. Hewitt and his colleagues are preparing to substantially expand and overhaul the repository. The project has obtained funding for the next four to five years, he says. “It doesn’t sound earth-shattering, but it’s important.”

Among the efforts underway are curating and annotating the whole slide images already in the repository to add metadata and simple histopathologic interpretations; uploading the remainder of the NIH consortium’s autopsies, along with associated immunohistochemical images, RNA in situ results, and EHR-derived data; and expanding the repository to support other NIH-funded COVID-19 studies.

Dr. Hewitt and his collaborators also hope to expand the site by adding more comparators, such as a nonhuman primate model of SARS-CoV-2 infection. Such comparators would allow investigators to contrast the pathophysiology of the virus among different organisms, thereby obtaining a better understanding of host response, Dr. Hewitt says. “We used to believe the pathophysiology and the spread of virus was more related to virus type than anything else.” But the study of Ebola and Zika precipitated a shift in thought, he says, leading pathologists who study virology to focus more on host response, such as how host response is inadequate or modified between the viral processes, than the virus itself. In addition, Dr. Hewitt and his team are working to obtain cases from the outbreak of SARS in the early 21st century, as well as historical images of the 1918 H1N1 influenza and examples of other strains of influenza, which too cause pulmonary damage.

Also in the works is a plan to host whole slide and associated images from SARS-CoV-2–related manuscripts. The manuscripts’ PubMed unique identifiers, or PMID, will be linked to the COVID-DPR, Dr. Hewitt says, allowing users to read a study and at the same time peruse the related whole slide images. The repository will only host images from NIH manuscripts initially but eventually will also display images from external studies.

The COVID-DPR “is the first instance, of which we’re aware, where authors will be able to host whole slide images on servers unrelated to the publishers, as well as have a direct link to PubMed,” Dr. Hewitt says. In the past, he explains, efforts to host whole side images associated with manuscripts were undertaken by the journal publishers themselves. However, “they found this was a complicated process for which sustainability was problematic,” he adds, noting that most of those attempts have fallen by the wayside. “It’s still not in the mindset of investigators to post their images.”

Perhaps because of its ambitious objectives, the repository project hasn’t been without technical challenges—among them, incorporating into the platform the clinical metadata from the NIH autopsies. This has posed difficulties “both in presenting the data and using it analytically,” Dr. Hewitt says. A potential solution to this problem involves building an interlinked search engine that would allow users to search for specific data and thereby access the related images. An alternative, he says, is to add new data fields and bring the clinical metadata directly into the site. How the data will be incorporated and the timeline are uncertain, he adds.