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This study introduces an innovative approach using holotomography (HT), a 3D label-free quantitative phase imaging technique, to detect\n                    <jats:italic>NPM1<\/jats:italic>\n                    mutations. We analyzed a dataset of 2073 HT myeloblast images from 48 individuals, including both\n                    <jats:italic>NPM1<\/jats:italic>\n                    wild-type and mutated samples, to distinguish subcellular morphological changes associated with\n                    <jats:italic>NPM1<\/jats:italic>\n                    mutations. Employing a convolutional neural network, we analyzed 3D cell morphology, focusing on refractive index distributions. The machine learning model showed high accuracy, with an area under the receiver operating characteristic curve of 0.9375 and a validation accuracy of 76.0%. Our findings reveal distinct morphological differences between the\n                    <jats:italic>NPM1<\/jats:italic>\n                    wild-type and mutation at the subcellular level. This study demonstrates the potential of HT combined with deep learning for early, efficient, and cost-effective diagnosis of AML, offering a promising alternative to traditional stepwise genetic testing methods and providing additional assistance in morphological myeloblast discrimination. This approach may revolutionize the diagnostic process in leukemia, facilitating early detection and potentially reducing the reliance on extensive genetic testing.\n                  <\/jats:p>","DOI":"10.1038\/s41598-024-75168-9","type":"journal-article","created":{"date-parts":[[2024,10,10]],"date-time":"2024-10-10T14:02:02Z","timestamp":1728568922000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Integrating holotomography and deep learning for rapid detection of NPM1 mutations in AML"],"prefix":"10.1038","volume":"14","author":[{"given":"Hyunji","family":"Kim","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Geon","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"HeyJung","family":"Park","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mahn Jae","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2402-7633","authenticated-orcid":false,"given":"YongKeun","family":"Park","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0045-1747","authenticated-orcid":false,"given":"Seongsoo","family":"Jang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,10,10]]},"reference":[{"key":"75168_CR1","volume-title":"WHO classification of tumours of haematopoietic and lymphoid tissues","author":"SH Swerdlow","year":"2008","unstructured":"Swerdlow, S. 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The other authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"The study protocol was approved by the Institutional Review Board of Asan Medical Center (no. S2020-2538-0001) and Seoul National University Bundang Hospital (no. X-2309-853-901). This study was conducted using residual samples, and therefore, confirming that the need for informed consent was waived by Asan Medical Center. All methods of this study were conducted in accordance with the guidelines and regulations approved by the IRB.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}],"article-number":"23780"}}