Publications
Below are some publications in various media sources from and about the PIcc Alliance, its members, and its projects.
A unifying force for the realization of medical AI
Source: npj Digital Medicine
Abstract: Artificial Intelligence (AI) in medicine has grown rapidly, yet few algorithms have been deployed. It is not the problem with the AI itself but with the way functions and results are communicated. Regulatory science provides the appropriate language and solutions to this problem for three reasons: First, there is value in the intentionally interdisciplinary regulatory language. Second, regulatory concepts are important for AI researchers because these concepts enable tackling of risk and safety concerns as well as understanding of recently proposed regulations in the US and Europe. Third, regulatory science is a scientific discipline that evaluates and challenges current regulation—aiming for evidence-based improvements. Knowledge of the regulatory language, concepts, and science should be regarded a core competency for communicating medical innovation. Regulatory grade communication will be the key to bringing medical AI from hype to standard of care. Foregoing the possible benefits of regulatory science as a unifying force for the realization of medical AI is a missed opportunity.
Temporary Regulatory Deviations and the Coronavirus Disease 2019 PCR Labeling Update Study Indicate What LDT Regulation by the US FDA Could Look Like
Source: The Journal of Molecular Diagnostics (October 2021)
Snippet: The coronavirus disease 2019 (COVID-19) response necessitated innovations and a series of regulatory deviations that also affected laboratory-developed tests (LDTs). To examine real-world consequences and specify regulatory paradigm shifts, legislative proposals were aligned on a common timeline with Emergency Use Authorization (EUA) of LDTs and the US Food and Drug Administration (FDA)-orchestrated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) labeling update study. The initial EUA adoption by LDT developers shows that the FDA can have oversight over LDTs. We used efficiency-corrected microcosting of our EUA PCR assay to estimate the national cost of the labeling update study to $0.3 to $1.4 million US dollars. Labeling update study performance data showed lower average detection limits in commercial in vitro diagnostic (IVD) assays versus LDTs (32,000 ± 75,000 versus 71,000 ± 147,000 nucleic acid amplification tests/mL; P = 0.04); however, comparison also shows that FDA review of IVD assays and LDTs did not prevent differences between initial and labeling update performance (IVD assay, P < 0.0001; LDT, P = 0.003). The regulatory shifts re-emphasized that both commercial tests and LDTs rely heavily on laboratory competence and procedures; however, lack of performance data on authorized tests, when clinically implemented, precludes assessment of the benefit related to regulatory review. Temporary regulatory deviations during the pandemic and regulatory science tools (ie, reference material) have generated valuable real-world evidence to inform pending legislation regarding LDT regulation.
Feature: Pathology Innovation Collaborative Community
Source: MDIC Annual Report 2020
Snippet: The MDIC 2020 Annual Report shares the impact of MDIC’s work during the 2020 year. This report quantifies and demonstrates the organization’s impact and identifies opportunities for growth and improvement.
Do not sell regulatory science short
Source: Nature Medicine (April 2021)
Snippet: To the Editor—A recent federal notice1 proposes to permanently remove oversight by the US Food and Drug Administration (FDA) over 91 medical devices, including several devices that apply artificial intelligence and those under temporary COVID-19 waiver. Public needs during a response to an unprecedented public-health emergency aside, the federal notice sends an alarming message—that regulatory science and applying its principles during regulatory review are unnecessary.
Aligning Reimbursement for Digital Pathology with its Value
Source: The Journal of Precision Medicine (December 2020)
Snippet: Over the last couple of months the Payor working group of the Alliance for Digital Pathology has been active in developing a paper about reimbursement and its landscape in Digital Pathology. We are happy and proud to share that the paper has been published in the Journal of Precision Medicine before the end of the year 2020. The paper discusses the introduction of new technologies such as Artificial Intelligence in Pathology and the adoption thereof, and how they might impact clinical innovation, payment reform, value-based care, and coverage and reimbursement decisions.
A regulatory science initiative to harmonize and standardize digital pathology and machine learning processes to speed up clinical innovation to patients
Source: Journal of Pathology Informatics (August 2020)
Snippet: Unlocking the full potential of pathology data by gaining computational access to histological pixel data and metadata (digital pathology) is one of the key promises of computational pathology. Despite scientific progress and several regulatory approvals for primary diagnosis using whole-slide imaging, true clinical adoption at scale is slower than anticipated. In the U.S., advances in digital pathology are often siloed pursuits by individual stakeholders, and to our knowledge, there has not been a systematic approach to advance the field through a regulatory science initiative. The Alliance for Digital Pathology ( the Alliance) is a recently established, volunteer, collaborative, regulatory science initiative to standardize digital pathology processes to speed up innovation to patients. The purpose is: (1) to account for the patient perspective by including patient advocacy; (2) to investigate and develop methods and tools for the evaluation of effectiveness, safety, and quality to specify risks and benefits in the precompetitive phase; (3) to help strategize the sequence of clinically meaningful deliverables; (4) to encourage and streamline the development of ground-truth data sets for machine learning model development and validation; and (5) to clarify regulatory pathways by investigating relevant regulatory science questions. The Alliance accepts participation from all stakeholders, and we solicit clinically relevant proposals that will benefit the field at large. The initiative will dissolve once a clinical, interoperable, modularized, integrated solution (from tissue acquisition to diagnostic algorithm) has been implemented. In times of rapidly evolving discoveries, scientific input from subject-matter experts is one essential element to inform regulatory guidance and decision-making. The Alliance aims to establish and promote synergistic regulatory science efforts that will leverage diverse inputs to move digital pathology forward and ultimately improve patient care.
Alliance seeks laboratory contributions to international COVID-19 data repository
Source: CAP Today (May 1, 2020)
Snippet: The Alliance for Digital Pathology, a voluntary and temporary initiative formed by various stakeholder groups, is asking for assistance in developing an international pathology data repository of digital images of tissue specimens from COVID-19 patients. Under the stewardship of the World Health Organization, the alliance is collecting data in a standardized format from pathology institutions worldwide to share with other medical institutions and scientific bodies around the globe. The repository is intended to be a global resource that pathologists and researchers can use to gain an understanding of the pathophysiology of COVID-19 and establish histopathologic diagnostic criteria for the disease….
Autopsy slowdown hinders quest to determine how coronavirus kills
Source: Nature News (May 7, 2020)
Snippet: Strained health-care systems, lockdowns and safety requirements have hampered efforts to collect tissue from patients that is crucial to research. When the coronavirus pandemic slammed into the city of Bergamo, Italy, starting in February, the Papa Giovanni XXIII Hospital there was quickly overwhelmed. Clinicians raced to dedicate the hospital, one of the largest in the region, to the care of people with COVID-19. Soon, however, pathologist Andrea Gianatti and his colleagues began to shift their attention to a less visible priority: autopsies. “The need arose to understand how the disease affects the various organs,” Gianatti says. “And the most effective way was performing autopsy.”…
How current assay approval policies are leading to unintended imprecision medicine
Source: Lancet Oncol (Oct 2020)
Snippet: Insightful comment by Roberto Salgado and colleagues regarding unintentional consequences of regulatory decision regarding PD-L1 assessments.
Key insights in the AIDA community policy on sharing of clinical imaging data for research in Sweden
Source: Scientific Data (Oct 2020)
Authors: Hedlund et al.,
Snippet: Fantastic work by Joel on sound data sharing practices under GDPR. Abstract.: Development of world-class artificial intelligence (AI) for medical imaging requires access to massive amounts of training data from clinical sources, but effective data sharing is often hindered by uncertainty regarding data protection. We describe an initiative to reduce this uncertainty through a policy describing a national community consensus on sound data sharing practices.
Validation of a digital pathology system including remote review during the COVID-19 pandemic
Source: Modern Pathology (May 2020)
Authors: Hanna et al.,
Snippet: Remote digital pathology allows healthcare systems to maintain pathology operations during public health emergencies. Existing Clinical Laboratory Improvement Amendments regulations require pathologists to electronically verify patient reports from a certified facility. During the 2019 pandemic of COVID-19 disease, caused by the SAR-CoV-2 virus, this requirement potentially exposes pathologists, their colleagues, and household members to the risk of becoming infected. Relaxation of government enforcement of this regulation allows pathologists to review and report pathology specimens from
a remote, non-CLIA certified facility. The availability of digital pathology systems can facilitate remote microscopic diagnosis, although formal comprehensive (case-based) validation of remote digital diagnosis has not been reported. All glass slides representing routine clinical signout workload in surgical pathology subspecialties at Memorial Sloan Kettering Cancer Center were scanned on an Aperio GT450 at ×40 equivalent resolution (0.26 μm/pixel). Twelve pathologists from nine surgical pathology subspecialties remotely reviewed and reported complete pathology cases using a digital pathology
system from a non-CLIA certified facility through a secure connection. Whole slide images were integrated to and launched within the laboratory information system to a custom vendor-agnostic, whole slide image viewer. Remote signouts utilized consumer-grade computers and monitors (monitor size, 13.3–42 in.; resolution, 1280 × 800–3840 × 2160 pixels) connecting to an institution clinical workstation via secure virtual private network. Pathologists subsequently reviewed all corresponding glass slides using a light microscope within the CLIA-certified department. Intraobserver concordance metrics included reporting elements of top-line diagnosis, margin status, lymphovascular and/or perineural invasion, pathology stage, and ancillary testing. The median whole slide image file size was 1.3 GB; scan time/slide averaged 90 s; and scanned tissue area averaged 612 mm2. Signout sessions included a total of 108 cases, comprised of 254 individual parts and 1196 slides. Major diagnostic equivalency was 100% between digital and glass slide diagnoses; and overall concordance was 98.8% (251/254). This study reports validation of primary diagnostic review and reporting of complete pathology cases from a remote site during a public health emergency. Our experience shows high (100%) intraobserver digital to glass slide major diagnostic concordance when reporting from a remote site. This randomized, prospective study successfully validated remote use of a digital pathology system including operational feasibility supporting remote review and reporting of pathology specimens, and evaluation of remote access performance and usability for remote signout.