DataVXACS NanoPaper
journal article·2018-09-25Open access

Computational Optics Enables Breast Cancer Profiling in Point-of-Care Settings

Jouha Min, Hyungsoon Im, Matthew Allen, Phillip J. McFarland, Ismail Degani, Hojeong Yu, Erica Normandin, Divya Pathania, Jaymin M. Patel, Cesar M. Castro, Ralph Weissleder, Hakho Lee

ACS Nano· Volume 12· Issue 9
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Source abstract

Abstract

The global burden of cancer, severe diagnostic bottlenecks in underserved regions, and underfunded health care systems are fueling the need for inexpensive, rapid, and treatment-informative diagnostics. On the basis of advances in computational optics and deep learning, we have developed a low-cost digital system, termed AIDA (artificial intelligence diffraction analysis), for breast cancer diagnosis of fine needle aspirates. Here, we show high accuracy (>90%) in (i) recognizing cells directly from diffraction patterns and (ii) classifying breast cancer types using deep-learning-based analysis of sample aspirates. The image algorithm is fast, enabling cellular analyses at high throughput (∼3 s per 1000 cells), and the unsupervised processing allows use by lower skill health care workers. AIDA can perform quantitative molecular profiling on individual cells, revealing intratumor molecular heterogeneity, and has the potential to improve cancer diagnosis and treatment. The system could be further developed for other cancers and thus find widespread use in global health.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: AI in cancer detection · Cell Image Analysis Techniques · Bacterial Identification and Susceptibility Testing

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Center for Systems Biology, Massachusetts General Hospital, Boston, Massachusetts 02114, United States

Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts 02114, United States

Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States

Department of Systems Biology, Harvard Medical School, Boston, Massachusetts 02115, United States

BreastCare Center, Division of Hematology Oncology, Beth Israel Deaconess Medical Center, Boston, Massachusetts 02115, United States

Massachusetts General Hospital Cancer Center, Boston, Massachusetts 02114, United States

Funding

National Cancer Institute · National Research Foundation of Korea · National Heart, Lung, and Blood Institute · Massachusetts General Hospital · V Foundation for Cancer Research

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