Open AccessNanoparticle surface-enhanced Raman spectroscopy as a noninvasive, label-free tool to monitor hematological malignancy
Author(s) -
Sandra Grieve,
Nagaprasad Puvvada,
Angkoon Phinyomark,
Kevin Russell,
Alli Murugesan,
Elizabeth Zed,
Ansar Hassan,
JeanFrançois Légaré,
Petra C. Kienesberger,
Thomas Pulinilkunnil,
Erik Scheme,
Keith R. Brunt
Publication year - 2021
Publication title -
nanomedicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.947
H-Index - 109
eISSN - 1748-6963
pISSN - 1743-5889
DOI - 10.2217/nnm-2021-0076
Subject(s) - malignancy , surface enhanced raman spectroscopy , medicine , gold standard (test) , raman spectroscopy , machine learning , disease , precision medicine , artificial intelligence , computer science , medical physics , pathology , raman scattering , physics , optics
Aim: Monitoring minimal residual disease remains a challenge to the effective medical management of hematological malignancies; yet surface-enhanced Raman spectroscopy (SERS) has emerged as a potential clinical tool to do so. Materials & methods: We developed a cell-free, label-free SERS approach using gold nanoparticles (nanoSERS) to classify hematological malignancies referenced against two control cohorts: healthy and noncancer cardiovascular disease. A predictive model was built using machine-learning algorithms to incorporate disease burden scores for patients under standard treatment upon. Results: Linear- and quadratic-discriminant analysis distinguished three cohorts with 69.8 and 71.4% accuracies, respectively. A predictive nanoSERS model correlated (MSE = 1.6) with established clinical parameters. Conclusion: This study offers a proof-of-concept for the noninvasive monitoring of disease progression, highlighting the potential to incorporate nanoSERS into translational medicine.