[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"sperm-selection\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:sperm-selection":31},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,3,0,[8,52,81],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":13,"acronym":14,"eligibilityCriteria":15,"healthyVolunteers":11,"sex":16,"minAge":17,"maxAge":18,"enrollmentInfo":19,"targetDuration":4,"studyType":22,"phases":23,"briefSummary":25,"conditions":26,"keywords":32,"overallStatus":39,"whyStopped":4,"lastUpdateSubmitDate":40,"lastUpdatePostDateStruct":41,"startDateStruct":44,"completionDateStruct":46,"leadSponsor":48,"locationsCount":51},"100564483","the-epic-study-exploring-paternal-age-and-the-influence-on-blastocyst-culture-100564483",false,"NCT06629766","The EPIC Study: Exploring Paternal Age and the Influence on Blastocyst Culture","EPIC","Inclusion Criteria:\n\n* Undergoing first IVF cycle\n* Electing single embryo transfer\n* Electing PGT-A of their embryos\n* Female partners age \\\u003C42 years old at start of VOR cycle, but \\>18 years old.\n* AMH ≥ 1.2 ng\u002FmL\n* AFC ≥ 8\n* FSH ≤ 12IU\u002FL\n* At least 4 mature oocytes (M2s) retrieved at the VOR procedure in order to randomize\n* Intention to transfer the morphological best quality, euploid, embryo at the frozen embryo transfer procedure\n\nExclusion Criteria:\n\n* Contraindication to IVF\n* Clinical indication for preimplantation genetic testing (i.e., screening for single gene disorder, chromosomal translocation, or any other disorders requiring a more detailed embryo genetic analysis)\n* Male partner with azoospermia or oligozoospermia (\\\u003C500,000 total motile spermatozoa on the most recent semen analysis within one year of enrollment)\n* Planned for previously cryopreserved sperm to be used for ICSI\n* Donor sperm\n* Male partner with Y-chromosome microdeletion\n* Male partner with any Karyotype other than 46,XY\n* Male partner requiring surgically obtained sperm either via testicular or epididymal retrieval procedures\n* Uncorrected hydrosalpinges that communicate with the endometrial cavity\n* Endometrial Insufficiency, as defined by a prior cycle with maximal endometrial thickness \\\u003C6mm,), or persistent endometrial fluid\n* Donor oocyte or embryo cycles\n* Gestational carriers","FEMALE","18 Years","41 Years",{"count":20,"type":21},100,"ESTIMATED","INTERVENTIONAL",[24],"NA","This study aims to assess the effect of age of the male partner and the reproductive ability of sperm prepared via sperm selection devices (Zymot) compared to routine embryologist selected sperm after density gradient centrifugation (DGC) preparation for intracytoplasmic sperm injection (ICSI) in patients undergoing in vitro fertilization treatment (IVF) of their infertility.",[27,28,29,30,31],"Infertility (IVF Patients)","Oocyte Competence","Sperm DNA Fragmentation","Paternal Age","Sperm Selection",[33,34,35,36,37,38],"microfluidic","density grade centrifugation","sperm selection","paternal age","sperm DNA fragmentation","Zymot","RECRUITING","2026-06-01",{"date":42,"type":43},"2026-06-03","ACTUAL",{"date":45,"type":43},"2025-04-09",{"date":47,"type":21},"2028-12",{"name":49,"class":50},"Reproductive Medicine Associates of New Jersey","OTHER",1,{"id":53,"slug":54,"hasResults":11,"nctId":55,"briefTitle":56,"officialTitle":56,"acronym":4,"eligibilityCriteria":57,"healthyVolunteers":11,"sex":58,"minAge":17,"maxAge":59,"enrollmentInfo":60,"targetDuration":4,"studyType":62,"phases":4,"briefSummary":63,"conditions":64,"keywords":66,"overallStatus":71,"whyStopped":4,"lastUpdateSubmitDate":72,"lastUpdatePostDateStruct":73,"startDateStruct":75,"completionDateStruct":77,"leadSponsor":79,"locationsCount":51},"100607240","functional-development-and-clinical-validation-of-a-diagnostic-tool-based-on-artificial-intelligence-for-the-assessment-of-sperm-quality-and-the-selection-of-the-optimal-in-vitro-fertilisation-ivf-treatment-100607240","NCT07185984","Functional Development and Clinical Validation of a Diagnostic Tool Based on Artificial Intelligence for the Assessment of Sperm Quality and the Selection of the Optimal In Vitro Fertilisation (IVF) Treatment","* Inclusion criteria:\n\n  * Men between the ages of 18 and 50 who come to the clinic to undergo an ICSI cycle.\n  * Men between the ages of 18 and 50 who come to the clinic to undergo an artificial insemination cycle.\n  * All embryos will be placed in a time-lapse incubator.\n  * All women over 18 years of age who have obtained a MII number greater than or equal to 2 in oocyte retrieval, without excluding couples from the oocyte donation programme.\n  * All men and women with a previously known normal karyotype.\n  * Informed consent (IC) provided and signed by patients.\n* Exclusion criteria:\n\n  * All women diagnosed with recurrent pregnancy loss.\n  * All semen samples obtained by testicular biopsy.\n  * All donor semen samples.","MALE","50 Years",{"count":61,"type":21},200,"OBSERVATIONAL","Infertility is a growing global health problem affecting millions of couples worldwide, with male infertility accounting for approximately half of all cases. In the physiological environment, sperm go through an exhaustive selection process in the female reproductive tract before reaching the oocyte. During this journey, progressive mobility and morphology are key parameters for achieving fertilisation. Therefore, before starting an assisted reproduction treatment, it is essential to analyse and process the semen sample to assess the fertile potential, select the most optimal sperm and determine the most appropriate treatment.\n\nConventional methods of semen processing, such as density gradient centrifugation (DGC) and Swim-up washing of motile sperm, have significant limitations. These include interobserver and interlaboratory subjectivity, as well as damage to sperm DNA caused by centrifugation. Alternatively, microfluidics, which simulates natural selection, allows higher counts of morphologically normal, progressive motile sperm to be obtained. On the other hand, the CASA (computer-assisted sperm analysis) system has improved the standardisation and quality of semen analysis. Furthermore, the incorporation of Artificial Intelligence (AI) into semen quality analysis represents a promising opportunity, as it improves efficiency, accuracy and standardisation, and has the potential to increase success rates in assisted reproduction treatments.\n\nThis project aims to develop an innovative AI-based diagnostic tool to address male infertility. The tool will integrate microfluidic technology and the CASA system to analyse semen quality, calculate fertilisation potential and recommend personalised treatments with an estimate of success. Trained with large volumes of biological and clinical data, it will provide a comprehensive and patient-specific diagnosis by identifying complex relationships between multiple variables. Finally, a comparative study will be conducted to evaluate laboratory indicators and clinical outcomes of cycles using this tool versus those using conventional methods.",[27,65,31],"Male Fertility",[67,68,69,70],"Male infertility","Microfluidics","Artificial intelligence","Sperm quality","NOT_YET_RECRUITING","2025-09-19",{"date":74,"type":43},"2025-09-22",{"date":76,"type":21},"2025-11",{"date":78,"type":21},"2027-11",{"name":80,"class":50},"Instituto Valenciano de Infertilidad, IVI VALENCIA",{"id":82,"slug":83,"hasResults":11,"nctId":84,"briefTitle":85,"officialTitle":86,"acronym":87,"eligibilityCriteria":88,"healthyVolunteers":11,"sex":89,"minAge":17,"maxAge":4,"enrollmentInfo":90,"targetDuration":4,"studyType":22,"phases":91,"briefSummary":92,"conditions":93,"keywords":96,"overallStatus":71,"whyStopped":4,"lastUpdateSubmitDate":102,"lastUpdatePostDateStruct":103,"startDateStruct":105,"completionDateStruct":107,"leadSponsor":109,"locationsCount":4},"100605533","use-of-the-sidtm-v20-algorithm-to-assist-embiyologists-in-sperm-selection-during-icsi-procedures-100605533","NCT07163754","Use of the SiDTM v2.0 Algorithm to Assist Embiyologists in Sperm Selection During ICSI Procedures","Use of the SiDTM v2.0 Algorithm to Assist Embryologists in Sperm Selection During ICSI Procedures: Impact in Biological and Clinical Outcomes","SID_3","Inclusion Criteria:\n\n* Patients with indication for ICSI.\n* Women of advanced maternal age (\\>35 years) in whom at least 4 oocytes in metaphase II stages are obtained in the follicular puncture, without excluding patients from the oocyte donation program.\n* Sperm obtained by masturbation with a concentration above 1 million spermatozoa\u002FmL after sperm capacitation.\n* Normal karyotype of both partners.\n* Informed Consent (IC).\n\nExclusion Criteria:\n\n* Patients diagnosed with recurrent gestational loss.\n* Semen extracted by testicular biopsy.\n* Semen samples with globozoospermia (sperm defect due to lack of acrosome) or azoospermia (absence of spermatozoa in the ejaculate).\n* Semen samples treated with pentoxifylline.\n* ICSI cycles with application of calcium ionophore. o ICSI cycles with application of calcium ionophore.","ALL",{"count":20,"type":21},[24],"Infertility is defined as a failure of a couple to achieve a pregnancy after 12 or more months of unprotected intercourse. Males are found to be solely responsible for 20-30% of infertility cases but contribute to 50% of cases overall. The selection of sperm to microinject is completely subjective and there is high intra- and inter- observer variability. SiDTM v2.0 is an algorithm which analyses real-time seminal samples located at ICSI dishes. Particularly, it assesses morphology and several motility parameters of each sperm, and it assigns a categorical and numerical score to each one. Categorical scores are represented by colours: green colour for optimal sperm, yellow for good sperm, orange for medium-quality sperm and red for low-quality sperm. Numerical scores ranged from 0 to 100, with higher scores for those best-quality sperm. SiDTM v2.0 can reduce subjectivity of the sperm selection process to the maximum, selecting the optimal sperm in real time. In addition, it could help junior embryologists to perform this complex and tedious procedure, which is the sperm selection for ICSI. To carry out the study, we will conduct a prospective cohort study in a total of 100 couples. Therefore, the aim of this study is to validate SiDTM v2.0 as an useful Artificial Intelligence-tool for sperm selection; that means achieving , at least, same clinical results as sperm selection performed by the embryologist.",[65,94,95,31],"Testicular","Sperm Parameters in Fertile and Infertile Men",[97,98,99,100,101],"Intracytoplasmatic Sperm injection","automated sperm selection","artificial intelligence","fertilization","embryo quality","2025-09-02",{"date":104,"type":43},"2025-09-09",{"date":106,"type":21},"2025-10",{"date":108,"type":21},"2027-10",{"name":80,"class":50}]