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Review
. 2021 Mar 1;50(3):251-279.
doi: 10.1097/MPA.0000000000001762.

Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review

Barbara Kenner  1 , Suresh T Chari  2 , David Kelsen  3 , David S Klimstra  4 , Stephen J Pandol  5 , Michael Rosenthal  6 , Anil K Rustgi  7 , James A Taylor  8 , Adam Yala, Noura Abul-Husn  9 , Dana K Andersen  10 , David Bernstein  11 , Søren Brunak  12 , Marcia Irene Canto  13 , Yonina C Eldar  14 , Elliot K Fishman  15 , Julie Fleshman  16 , Vay Liang W Go  17 , Jane M Holt  18 , Bruce Field  1 , Ann Goldberg  1 , William Hoos  19 , Christine Iacobuzio-Donahue  20 , Debiao Li  21 , Graham Lidgard  22 , Anirban Maitra  23 , Lynn M Matrisian  16 , Sung Poblete  24 , Laura Rothschild  1 , Chris Sander  25 , Lawrence H Schwartz  26 , Uri Shalit  27 , Sudhir Srivastava  28 , Brian Wolpin  29
Affiliations
Review

Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review

Barbara Kenner et al. Pancreas. .

Abstract

Despite considerable research efforts, pancreatic cancer is associated with a dire prognosis and a 5-year survival rate of only 10%. Early symptoms of the disease are mostly nonspecific. The premise of improved survival through early detection is that more individuals will benefit from potentially curative treatment. Artificial intelligence (AI) methodology has emerged as a successful tool for risk stratification and identification in general health care. In response to the maturity of AI, Kenner Family Research Fund conducted the 2020 AI and Early Detection of Pancreatic Cancer Virtual Summit (www.pdac-virtualsummit.org) in conjunction with the American Pancreatic Association, with a focus on the potential of AI to advance early detection efforts in this disease. This comprehensive presummit article was prepared based on information provided by each of the interdisciplinary participants on one of the 5 following topics: Progress, Problems, and Prospects for Early Detection; AI and Machine Learning; AI and Pancreatic Cancer-Current Efforts; Collaborative Opportunities; and Moving Forward-Reflections from Government, Industry, and Advocacy. The outcome from the robust Summit conversations, to be presented in a future white paper, indicate that significant progress must be the result of strategic collaboration among investigators and institutions from multidisciplinary backgrounds, supported by committed funders.

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Conflict of interest statement

The authors declare no conflict of interest. S.T.C., B. F., V.L.W.G., W.H., and D.S.K. are Kenner Family Research Fund scientific advisors. A.G., B.K., and L.R. are Kenner Family Research Fund board members.

Figures

FIGURE 1
FIGURE 1
Strategic map for innovation (© Kenner Family Research Fund, 2015).
FIGURE 2
FIGURE 2
Survival rates by stage.
FIGURE 3
FIGURE 3
Probability of overall survival following surgery.
FIGURE 4
FIGURE 4
Phases of biomarker discovery and validation.
FIGURE 5
FIGURE 5
Risk versus prevalence of PDAC. Courtesy of Suresh Chari.
FIGURE 6
FIGURE 6
Vision for an early detection protocol. Modified from Kenner et al.
FIGURE 7
FIGURE 7
Timeline of changes on CT scan in prediagnostic PDAC.
FIGURE 8
FIGURE 8
Learning to classify images of dogs versus cats. A, Initial model guess. B, The refined estimate after measuring its performance on the reference set. Courtesy of Adam Yala.
FIGURE 9
FIGURE 9
Disease progression over the life course. The figure illustrates how diseases follow each other and how different patients develop different complications to the same disease over time. Events in early disease-free periods will in many cases influence disease risks and disease severity later in life. Big data disease analytics aim at finding such early events and symptoms with predictive value in relation to early diagnosis of for example pancreatic cancer. Courtesy of Jessica Xin Hjaltelin, University of Copenhagen.
FIGURE 10
FIGURE 10
Early detection strategy. Courtesy of participants from Collaborative Opportunities and Kenner Family Research Fund.
See this image and copyright information in PMC

References

    1. Cancer Stat Facts: Pancreatic Cancer. Available at: https://seer.cancer.gov/statfacts/html/pancreas.html. Accessed October 10, 2020.
    1. Gheorghe G Bungau S Ilie M, et al. Early diagnosis of pancreatic cancer: the key for survival. Diagnostics. 2020;10:869. - PMC - PubMed
    1. Chari ST Kelly K Hollingsworth MA, et al. Early detection of sporadic pancreatic cancer: summative review. Pancreas. 2015;44:693–712. - PMC - PubMed
    1. Canto M, Brentnall TA. Screening familial pancreatic cancer (FPC). Supplemental Digital Content 1. In: Chari ST, Kelly K, Hollingsworth MA, et al. Early detection of sporadic pancreatic cancer: summative review. Pancreas. 2015;44:693–712. Available at: http://links.lww.com/MPA/A372. Accessed August 14, 2020. - PMC - PubMed
    1. Kenner BJ Chari ST Cleeter DF, et al. Early detection of sporadic pancreatic cancer: strategic map for innovation—a white paper. Pancreas. 2015;44:686–692. - PMC - PubMed

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