Targeted detection of cancer at the cellular level during biopsy by near-infrared confocal laser endomicroscopy

Gregory T. Kennedy, Feredun S. Azari, Elizabeth Bernstein, Bilal Nadeem, Ashley Chang, Alix Segil, Sean Carlin, Neil T. Sullivan, Emmanuel Encarnado, Charuhas Desphande, Sumith Kularatne, Pravin Gagare, Mini Thomas, John C. Kucharczuk, Gaetan Christien, Francois Lacombe, Kaela Leonard, Philip S. Low, Aline Criton and Sunil Singhal ()
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Gregory T. Kennedy: University of Pennsylvania School of Medicine
Feredun S. Azari: University of Pennsylvania School of Medicine
Elizabeth Bernstein: University of Pennsylvania School of Medicine
Bilal Nadeem: University of Pennsylvania School of Medicine
Ashley Chang: University of Pennsylvania School of Medicine
Alix Segil: University of Pennsylvania School of Medicine
Sean Carlin: University of Pennsylvania School of Medicine
Neil T. Sullivan: University of Pennsylvania School of Medicine
Emmanuel Encarnado: University of Pennsylvania School of Medicine
Charuhas Desphande: University of Pennsylvania School of Medicine
Sumith Kularatne: On Target Laboratories
Pravin Gagare: On Target Laboratories
Mini Thomas: On Target Laboratories
John C. Kucharczuk: University of Pennsylvania School of Medicine
Gaetan Christien: Mauna Kea Technologies
Francois Lacombe: Mauna Kea Technologies
Kaela Leonard: Mauna Kea Technologies
Philip S. Low: Purdue University
Aline Criton: Mauna Kea Technologies
Sunil Singhal: University of Pennsylvania School of Medicine

Nature Communications, 2022, vol. 13, issue 1, 1-9

Abstract: Abstract Suspicious nodules detected by radiography are often investigated by biopsy, but the diagnostic yield of biopsies of small nodules is poor. Here we report a method—NIR-nCLE—to detect cancer at the cellular level in real-time during biopsy. This technology integrates a cancer-targeted near-infrared (NIR) tracer with a needle-based confocal laser endomicroscopy (nCLE) system modified to detect NIR signal. We develop and test NIR-nCLE in preclinical models of pulmonary nodule biopsy including human specimens. We find that the technology has the resolution to identify a single cancer cell among normal fibroblast cells when co-cultured at a ratio of 1:1000, and can detect cancer cells in human tumors less than 2 cm in diameter. The NIR-nCLE technology rapidly delivers images that permit accurate discrimination between tumor and normal tissue by non-experts. This proof-of-concept study analyzes pulmonary nodules as a test case, but the results may be generalizable to other malignancies.

Date: 2022
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DOI: 10.1038/s41467-022-30265-z

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