TY - JOUR
T1 - Design and clinical validation of a point-of-care device for the diagnosis of lymphoma via contrast-enhanced microholography and machine learning
AU - Im, Hyungsoon
AU - Pathania, Divya
AU - McFarland, Philip J.
AU - Sohani, Aliyah R.
AU - Degani, Ismail
AU - Allen, Matthew
AU - Coble, Benjamin
AU - Kilcoyne, Aoife
AU - Hong, Seonki
AU - Rohrer, Lucas
AU - Abramson, Jeremy S.
AU - Dryden-Peterson, Scott
AU - Fexon, Lioubov
AU - Pivovarov, Misha
AU - Chabner, Bruce
AU - Lee, Hakho
AU - Castro, Cesar M.
AU - Weissleder, Ralph
N1 - Publisher Copyright:
© 2018, The Author(s).
PY - 2018/9/1
Y1 - 2018/9/1
N2 - The identification of patients with aggressive cancer who require immediate therapy is a health challenge in low- and middle-income countries. Limited pathology resources, high healthcare costs and large caseloads call for the development of advanced stand-alone diagnostics. Here, we report and validate an automated, low-cost point-of-care device for the molecular diagnosis of aggressive lymphomas. The device uses contrast-enhanced microholography and a deep learning algorithm to directly analyse percutaneously obtained fine-needle aspirates. We show the feasibility and high accuracy of the device in cells, as well as the prospective validation of the results in 40 patients clinically referred for image-guided aspiration of nodal mass lesions suspicious of lymphoma. Automated analysis of human samples with the portable device should allow for the accurate classification of patients with benign and malignant adenopathy.
AB - The identification of patients with aggressive cancer who require immediate therapy is a health challenge in low- and middle-income countries. Limited pathology resources, high healthcare costs and large caseloads call for the development of advanced stand-alone diagnostics. Here, we report and validate an automated, low-cost point-of-care device for the molecular diagnosis of aggressive lymphomas. The device uses contrast-enhanced microholography and a deep learning algorithm to directly analyse percutaneously obtained fine-needle aspirates. We show the feasibility and high accuracy of the device in cells, as well as the prospective validation of the results in 40 patients clinically referred for image-guided aspiration of nodal mass lesions suspicious of lymphoma. Automated analysis of human samples with the portable device should allow for the accurate classification of patients with benign and malignant adenopathy.
UR - http://www.scopus.com/inward/record.url?scp=85050530041&partnerID=8YFLogxK
U2 - 10.1038/s41551-018-0265-3
DO - 10.1038/s41551-018-0265-3
M3 - Article
AN - SCOPUS:85050530041
SN - 2157-846X
VL - 2
SP - 666
EP - 674
JO - Nature Biomedical Engineering
JF - Nature Biomedical Engineering
IS - 9
ER -