Skip to main content Accessibility help
×
Hostname: page-component-78c5997874-ndw9j Total loading time: 0 Render date: 2024-11-17T18:03:35.296Z Has data issue: false hasContentIssue false

Chapter 2 - Standard Semen Analysis: Computer-Assisted Semen Analysis

Published online by Cambridge University Press:  05 April 2021

Ashok Agarwal
Affiliation:
The Cleveland Clinic Foundation, Cleveland, OH
Ralf Henkel
Affiliation:
University of the Western Cape, South Africa
Ahmad Majzoub
Affiliation:
Hamad Medical Corporation, Doha
Get access

Summary

Computer-assisted semen analysis (CASA) is an automated and objective method to evaluate several sperm parameters, either in conjunction with or instead of routine manual semen analysis. CASA systems have undergone a complete metamorphosis since the initial systems were developed to track sperm motion four decades ago [see 1, 2 for detailed history]. Various innovations in bioengineering, software algorithms and computational power have led to more than 14 CASA systems (Figure 2.1) currently available across the globe for commercial use in evaluating both human and animal spermatozoa [3, 4, 5]. Although CASA was initially introduced as a research tool and not commonly used for semen analysis in the clinical setting [1], more and more fertility clinics are investing in and switching to automated systems.

Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2021

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Mortimer, ST, van der Horst, G, Mortimer, D. The future of computer-aided sperm analysis. Asian J Androl 2015; 17: 545–53.Google Scholar
Amann, RP, Waberski, D. Computer-assisted sperm analysis (CASA): capabilities and potential developments. Theriogenology 2014; 81: 517.Google Scholar
van der Horst, G, Maree, L, du Plessis, SS. Current perspectives of CASA applications in diverse mammalian sperm. Reprod Fertil Dev 2018; 30: 875–88.Google Scholar
Yeste, M, Bonet, S, Rodríguez-Gil, JE, Rivera Del Álamo, MM. Evaluation of sperm motility with CASA-Mot: which factors may influence our measurements? Reprod Fertil Dev 2018; 30: 789–98.Google Scholar
Ýaniz, JL, Silvestre, MA, Santolaria, P, Soler, C. CASA-Mot in mammals: an update. Reprod Fertil Dev 2018; 30: 799809.CrossRefGoogle ScholarPubMed
van der Horst, G, du Plessis, SS. Not just the marriage of Figaro: but the marriage of WHO/ESHRE semen analysis criteria with sperm functionality. Adv Androl Online 2017; 4: 621.Google Scholar
Tomlinson, MJ, Pooley, K, Simpson, T, Newton, T, Hopkisson, J, Jayaprakasan, K, Jayaprakasan, R, Naeem, A, Pridmore, A. Validation of a novel computer-assisted sperm analysis (CASA) system using multitarget-tracking algorithms. Fertil Steril 2010; 93: 1911–20.CrossRefGoogle ScholarPubMed
Dearing, CG, Kilkburn, S, Lindsay, KS. Validation of the sperm class analyser CASA system for sperm counting in a busy diagnostic semen analysis laboratory. Human Fertil 2014; 17: 3744.Google Scholar
World Health Organization. (1999) Laboratory Manual for the Examination of Human Semen and Sperm-Cervical Mucus Interaction, 4th ed. Cambridge: Cambridge University Press.Google Scholar
World Health Organization. (2010) WHO Laboratory Manual for the Examination and Processing of Human Semen, 5th ed. Geneva: The WHO Press.Google Scholar
Talarczyk-Desole, J, Berger, A, Taszarek-Hauke, G, Hauke, J, Pawelczyk, L, Jedrzejczak, P. Manual vs. computer-assisted sperm analysis: can CASA replace manual assessment of human semen in clinical practice? Ginekol Pol 2017; 88: 5660.CrossRefGoogle ScholarPubMed
Dearing, C, Jayasena, C, Lindsay, K. Can the Sperm Class Analyser (SCA) CASA-Mot system for human sperm motility analysis reduce imprecision and operator subjectivity and improve semen analysis? Human Fertil 2019; 6: 11.Google Scholar
Kochman, D, Marchlewska, K, Walczak-Jedrzejowska, R, Słowikowska-Hilczer, J, Kula, K, du Plessis, S, Blignaut, R, van der Horst, G. Comparison of manual and computer aided sperm morphology analysis. Adv Androl Online 2016; 3: 75.Google Scholar
Lammers, J, Splingart, C, Barrière, Jean M, Fréour, T. Double-blind prospective study comparing two automated sperm analyzers versus manual semen assessment. J Assist Reprod Genet 2014; 31: 3543.Google Scholar
European Society for Human Reproduction and Embryology (ESHRE). Guidelines on the application of CASA technology in the analysis of spermatozoa. Hum Reprod 1998; 13: 142–5.Google Scholar
Bompart, D, García-Molina, A, Valverde, A, Caldeira, C, Yániz, J, Núñez de Murga, M, Soler, C. CASA-Mot technology: how results are affected by the frame rate and counting chamber. Reprod Fertil Dev 2018; 30: 810–19.Google Scholar
Gallagher, MT, Smith, DJ, Kirkman-Brown, JC. CASA: tracking the past and plotting the future. Reprod Fertil Dev 2018; 30: 867–74.CrossRefGoogle ScholarPubMed
Tomlinson, MJ, Naeem, A. CASA in the medical laboratory: CASA in diagnostic andrology and assisted conception. Reprod Fertil Dev 2018; 30: 850–9.Google Scholar
Menkveld, R, Wong, WY, Lombard, CJ, Wetzels, AMM, Thomas, CMG, Merkus, HMWM, Steegers-Theunissen, RPM. Semen parameters, including WHO and strict criteria morphology, in a fertile and subfertile population: an effort towards standardization of in-vivo thresholds. Hum Reprod 2001; 16: 1165–71.Google Scholar
Maree, L, Menkveld, R, du Plessis, SS, van der Horst, G. Morphometric dimensions of the human sperm head depend on the staining method used. Hum Reprod 2010; 25: 1369–82.Google Scholar
Mukhopadhyay, D, Varghese, AC, Nandi, P, Banerjee, SK, Bhattacharyya, AK. CASA-based sperm kinematics of environmental risk factor-exposed human semen samples designated as normozoospermic in conventional analysis. Andrologia 2010; 42: 242–6.Google Scholar
Semet, M, Paci, M, Saïas-Magnan, J, Metzler-Guillemain, C, Boissier, R, Lejeune, H, Perrin, J. The impact of drugs on male fertility: a review. Andrology 2017; 5: 640–63.Google Scholar
Ayad, BM, van der Horst, G, du Plessis, SS. Short abstinence: a potential strategy for the improvement of sperm quality. Middle East Fertil Soc J 2018; 23: 3743.CrossRefGoogle Scholar
Alipour, H, van der Horst, G, Christiansen, OB, Dardmeh, F, Jørgensen, N, Nielsen, HI, Hnida, C. Improved sperm kinematics in semen samples collected after 2 h versus 4–7 days of ejaculation abstinence. Hum Reprod 2017; 32: 1364–72.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×