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Updated: Aug 4, 2025
Fluorescence In Situ Hybridization on DNA Halo Preparations to Reveal Whole Chromosomes, Telomeres and Gene Loci
Published on: March 4, 2021
Novel sperm chromatin dispersion test with artificial intelligence-aided halo evaluation: A comparison study with
Shinnosuke Kuroda1, Keshab Kumar Karna2, Raneen Sawaid Kaiyal1
1Department of Urology, Glickman Urological & Kidney Institute, Cleveland Clinic Foundation, Cleveland, Ohio, USA.
Background:
Sperm chromatin dispersion test is a common and inexpensive technique to assess sperm DNA fragmentation, but its subjectivity in assessing a small number of spermatozoa is a disadvantage.
Objectives:
To study the efficacy of a new sperm chromatin dispersion test kit (R10) combined with an artificial intelligence-aided halo-evaluation platform (X12) and compare the results to those of existing sperm DNA fragmentation testing methods.
Materials And Methods:
Semen samples from normozoospermic donors (n = 10) and infertile men with abnormal semen parameters (n = 10) were enrolled. DNA fragmentation indices were examined by multiple assays, including R10, Halosperm G2 (G2), sperm chromatin structure assay, and terminal deoxynucleotidyl transferase deoxynucleotidyl transferase nick end labeling. In R10 assay, the DNA fragmentation indices were obtained both manually (manual R10) and by X12 (AI-R10). The obtained DNA fragmentation indices were analyzed by agreement analyses.
Results:
The DNA fragmentation indices obtained by manual R10 and those obtained by AI-R10 showed a strong significant correlation (r = 0.97, p < 0.001) and agreement. The number of spermatozoa evaluated by AI-R10 was 2078 (680-5831). The DNA fragmentation indices obtained by manual R10 and AI-R10 both correlated with those of G2 (r = 0.90, p < 0.001; r = 0.88, p < 0.001). Between the AI-R10 and G2 results, Passing-Bablok regression showed no systematic or proportional difference, and Bland-Altman plots revealed overall agreement and a mean bias of 6.3% with an SD of 6.9% (95% limit of agreement: -7.2% to 19.9%). AI-R10 and sperm chromatin structure assays showed systematic differences with a mean bias of -1.9%, while AI-R10 and terminal deoxynucleotidyl transferase deoxynucleotidyl transferase nick end labeling revealed proportional differences with a mean bias of -10.7%.
Conclusions:
The novel sperm chromatin dispersion kit and artificial intelligence-aided platform demonstrated significant correlation and agreement with existing sperm chromatin dispersion methods by assessing greater number of spermatozoa. This technique has the potential to provide a rapid and accurate assessment of sperm DNA fragmentation without technical expertise or flow cytometry.
