The Nucleophosmin 1 (NPM1) mutation rapidly progresses to acute myeloid leukemia, emphasizing the need for early diagnosis, especially in cases with low blast counts. Some low blast count instances may not undergo next-generation sequencing, causing delays and necessitating swift NPM1 mutation screening. This study utilizes cutting-edge label-free three-dimensional imaging with holotomography (HT) to identify NPM1 mutation in blasts. Machine learning and deep learning algorithms achieve precise single-cell and patient-specific predictions. HT's accurate detection of protein movement associated with NPM1 mutation holds great promise as a reliable and efficient tool for early detection in hematologic malignancy patients with low blast counts.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.