{"doi":"10.64898/2025.12.16.694634","title":"BEADS: An Interactive Semi-Automated Workflow for 3D Fibrin Angiogenesis Assays Enabling Co-Culture and Directionality Analysis","abstract":", yet current analytical approaches are either time-consuming or poorly adaptable to complex imaging conditions, limiting quantitative assessment of co-cultures, spatial interactions, and nearest-neighbor-dependent angiogenic behavior. In this study, we developed a semiautomated user-interactive image analysis pipeline, Bead-based Endothelial Angiogenesis Data Suite (BEADS), to provide standardized quantitative bead-centric metrics of sprouting, migration, and spatial orientation in 3D fibrin angiogenesis assays. BEADS integrates automated bead detection with manual correction, followed by guided sprout and migratory-cell annotation across multi-channel image z-stacks. Novel analytical capabilities include co-culture designation, nearest-neighbor pairing, and circular statistics for sprout-directionality quantification. Performance was evaluated in assays using co-cultured male and female human pulmonary microvascular endothelial cell (HPMEC)-coated beads. BEADS reduced hands-on analysis time approximately sevenfold compared with manual tracing while preserving sprout-length accuracy against manual ground truth. BEADS provides a standardized, extensible platform for microvascular image analysis, supporting co-culture experimentation, spatial endothelial-interaction metrics, migratory-cell quantification, and high-throughput adaptation. This semiautomated workflow enables quantitative microvascular research by integrating computational precision with endothelial behavior and is broadly applicable to angiogenesis assays that incorporate co-cultures, perturbations, or multi-label experimental designs.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2025,"id":586700,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9434,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":511386,"name":"Brielle Hayward-Piatkovskyi","orcid":"0000-0003-4610-975X","position":1,"is_corresponding":false},{"id":301790,"name":"Jason P. Gleghorn","orcid":"0000-0003-1283-2966","position":2,"is_corresponding":false},{"id":1248067,"name":"Cailin R. Gonyea","orcid":"0000-0002-3566-7898","position":0,"is_corresponding":true}],"reference_count":36,"raw_metadata":null,"created_at":"2026-07-19T02:59:32.191237Z","pmid":"41446114","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}