# Deep-UV Microscopy for Real-Time Adequacy Analysis of Bone Marrow Aspirates

> **NIH NIH R41** · CELLIA SCIENCE, INC. · 2023 · $275,766

## Abstract

Project Summary/Abstract
Bone marrow aspirates are critical to the diagnosis, staging, and monitoring of hematologic conditions and
cancers (e.g., leukemia, aplastic anemia, sickle cell disease, and metastasis of solid tumors), but 8-50% of
aspirations are unsuccessful due to operator technique, hemodilution, or underlying pathology. Because this
process is manual and error-prone, there is an opportunity to improve patient outcomes by providing real-time
and automated feedback on the sample quality. Cellia Science will enable improved quality and reliability of
bone marrow aspiration procedures by developing a point-of-care screening instrument. Our approach is
based on a recently developed label-free, deep-ultraviolet (UV) technique for cell imaging and analysis.
Preliminary data has shown that the spicules present in a bone marrow aspirate are easily identifiable by their
characteristic deep blue hue in the unstained pseudocolorized UV image—a result of strong light attenuation at
255nm by bone spicules. The resulting deep-UV images can be generated in under 3 minutes, making the
technique suitable for real-time use during aspiration procedures, and are nearly identical to the Giemsa-
stained slides, which take over 45 min to process. Label-free deep-UV imaging can be combined with machine
learning techniques for feature extraction and classification, which will enable automated quality assessment of
aspirate smears without a pathology technician. We will leverage this technology to develop a bone marrow
aspirate quality screening device for use during aspiration procedures. Towards this goal, we propose quantify
sensitivity and specificity of spicule detection by deep-UV microscopy and evaluate concordance of deep-UV
aspirate assessment with visual assessment by trained technician, with Giemsa-stained samples serving as
the ground truth. We will also develop prototype instrument for automated spicule adequacy assessment to
enable adoption of this technique without a specially trained pathology technician. To automate the adequacy
assessment, we will use machine learning techniques for feature extraction and classification, detect the
presence of one or more spicules in the sample. Successful implementation of this device is expected to
increase the fraction of successful procedures, which will drastically improve the quality of care for the patient.

## Key facts

- **NIH application ID:** 10761397
- **Project number:** 1R41EB035057-01
- **Recipient organization:** CELLIA SCIENCE, INC.
- **Principal Investigator:** Francisco E Robles
- **Activity code:** R41 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $275,766
- **Award type:** 1
- **Project period:** 2023-08-01 → 2024-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10761397

## Citation

> US National Institutes of Health, RePORTER application 10761397, Deep-UV Microscopy for Real-Time Adequacy Analysis of Bone Marrow Aspirates (1R41EB035057-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10761397. Licensed CC0.

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