Background Conventional semen analysis does not fully capture male reproductive potential. The sperm DNA fragmentation index (DFI) may detect latent infertility, although the sperm chromatin structure assay (SCSA) is costly and technically demanding. Image-based analysis of semen microscopy, including artificial intelligence (AI), may enable lower-cost noninvasive assessment. However, progress is limited by a lack of standardized multimodal datasets linking sperm images with the DFI and relevant covariates. Objective This protocol describes the initial phase of the Nippon Semen and Environmental Exposure Database (N-SEED) initiative. The study aims to (1) establish standardized acquisition and quality control procedures for sperm microscopy/video and DFI measurement; (2) evaluate the feasibility and magnitude of associations between predefined image-/video-derived variables and the DFI; and (3) characterize clinical, environmental, physical, and lifestyle factors that may act as candidate correlates or confounders for subsequent image-based fertility research. Methods This multi-institutional cross-sectional study centralized clinical assessment and specimen collection at a single site in Japan. The prespecified group-specific enrollment targets were 25 for group 1 (a relatively homogeneous low-risk cohort for DFI quality control) and 100 for group 2 (apparently healthy community-based adult volunteers for exploratory association analyses). Microscopic sperm videos, automated semen parameters, and sperm oxidative stress data were obtained at collection. SCSA-based DFI assays are currently being performed sequentially. Group 2 participants additionally provided fasting blood and early-morning urine samples for endocrine, metabolic, environmental chemical, and elemental assays. They also underwent physical measurements and completed structured questionnaires/interviews on lifestyle, nutrition, sleep, psychological status, sexual function, and collection conditions. The primary outcome measure is the continuous DFI assessed with SCSA. Group 1 data will be used to evaluate intraday, interday, and interfacility variability and to fix flow cytometry gating settings. In groups 1 and 2, predefined image-/video-derived summary variables after standardized preprocessing will be analyzed against the continuous DFI using correlation analyses and simple linear regression to assess whether sperm microscopy data contain information relevant to sperm DNA integrity. Exploratory categorical DFI analyses will use simple logistic regression. Secondary exploratory analyses will examine candidate covariates and data completeness, including sensitivity analyses. Results The study was registered in the University Hospital Medical Information Network Clinical Trials Registry on January 18, 2026. Between January 18 and February 21, 2026, 124 unique participants were recruited (group 1: n=25; group 2: n=103; both groups: n=4). Sample and data collection were completed on February 21, 2026. Biospecimen assays and primary association analyses are expected to be completed by March 2028. Conclusions This initial N-SEED phase will deliver a standardized, quality-controlled multimodal resource linking sperm microscopy/video data with the DFI and broader physiological and environmental measures. Its immediate contribution is not to provide an immediately deployable clinical AI tool but rather to support feasibility assessment, confounder identification, and planning for subsequent database expansion and external validation of image-based male fertility assessment methods. Trial Registration UMIN Clinical Trials Registry UMIN000060395; https://tinyurl.com/mryfymw5 International Registered Report Identifier (IRRID) DERR1-10.2196/93803
Oguri et al. (Fri,) studied this question.