Prevalence and practices of immunofluorescent cell image processing: a systematic review

Area of Science:

• Neuroscience
• Biomedical Imaging
• Computational Biology

Background:

• Systematic review of 9,000+ PubMed papers featuring immunofluorescent images of central nervous system (CNS) cells.
• Identified a significant gap in the reporting of image processing techniques within CNS research literature.
• Highlighted the underrepresentation of image analysis methods compared to image acquisition and staining protocols.

Approach:

• Conducted a comprehensive literature search on PubMed using specific keywords for CNS cells and fluorescent microscopy.
• Manually tagged publication metadata, including animal/cell models, quantified features, and image processing techniques (thresholding, segmentation).
• Analyzed image processing methods commonly published alongside CNS cell studies and microscopy techniques.

Key Points:

• Only 856 of nearly 9,000 papers explicitly included image processing details.
• Hundreds of these papers lacked crucial thresholding and segmentation details for reproducibility.
• Identified underreporting and underutilization of image processing methods for quantifying CNS cell research.

Conclusions:

• Less than 10% of CNS immunofluorescent imaging papers adequately describe image processing.
• Advanced image analysis methods offer quantitative insights but require rigorous reporting.
• Enhanced documentation of image processing is essential for advancing CNS research rigor and reproducibility.