RedTell: an AI tool for interpretable analysis of red blood cell morphology, 2023, Ario Sadafi et al

Introduction: Hematologists analyze microscopic images of red blood cells to study their morphology and functionality, detect disorders and search for drugs. However, accurate analysis of a large number of red blood cells needs automated computational approaches that rely on annotated datasets, expensive computational resources, and computer science expertise. We introduce RedTell, an AI tool for the interpretable analysis of red blood cell morphology comprising four single-cell modules: segmentation, feature extraction, assistance in data annotation, and classification.

Methods: Cell segmentation is performed by a trained Mask R-CNN working robustly on a wide range of datasets requiring no or minimum fine-tuning. Over 130 features that are regularly used in research are extracted for every detected red blood cell. If required, users can train task-specific, highly accurate decision tree-based classifiers to categorize cells, requiring a minimal number of annotations and providing interpretable feature importance.

Results: We demonstrate RedTell’s applicability and power in three case studies. In the first case study we analyze the difference of the extracted features between the cells coming from patients suffering from different diseases, in the second study we use RedTell to analyze the control samples and use the extracted features to classify cells into echinocytes, discocytes and stomatocytes and finally in the last use case we distinguish sickle cells in sickle cell disease patients.

The feature extraction and classification modules of RedTell can be applied to a broad variety of RBC research questions. In the future, we will apply RedTell to high throughput analyses, e.g., evaluating drug efficacy and assessing SCD progression by detecting and extracting features of sickle cells in blood samples of different patients at different timepoints, and hope that other researchers will follow. We also expect to include a graphical user interface for easier interaction with the user and extend RedTell functionality by providing automated analysis reports and data visualizations for the most common use cases as defined in consultation with RBC researchers.

https://www.frontiersin.org/articles/10.3389/fphys.2023.1058720/full

 

Testing different timepoints of blood samples before, during and after PEM onset would be interesting.