[Sci Transl Med] An automated smartphone-based diagnostic assay for point-of-care semen analysis

March 24, 2017

Abstract:

 

Male infertility affects up to 12% of the world’s male population and is linked to various environmental and medical conditions. Manual microscope-based testing and computer-assisted semen analysis (CASA) are the current standard methods to diagnose male infertility; however, these methods are labor-intensive, expensive, and laboratory-based. Cultural and socially dominated stigma against male infertility testing hinders a large number of men from getting tested for infertility, especially in resource-limited African countries. We describe the development and clinical testing of an automated smartphone-based semen analyzer designed for quantitative measurement of sperm concentration and motility for point-of-care male infertility screening. Using a total of 350 clinical semen specimens at a fertility clinic, we have shown that our assay can analyze an unwashed, unprocessed liquefied semen sample with <5-s mean processing time and provide the user a semen quality evaluation based on the World Health Organization (WHO) guidelines with ~98% accuracy. The work suggests that the integration of microfluidics, optical sensing accessories, and advances in consumer electronics, particularly smartphone capabilities, can make remote semen quality testing accessible to people in both developed and developing countries who have access to smartphones.

 

Manoj Kumar Kanakasabapathy1, Magesh Sadasivam1,*, Anupriya Singh1,*, Collin Preston1, Prudhvi Thirumalaraju1, Maanasa Venkataraman1, Charles L. Bormann2, Mohamed Shehata Draz1, John C. Petrozza2 and Hadi Shafiee1,3,†
1Division of Engineering in Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02139, USA.
2Division of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynecology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
3Department of Medicine, Harvard Medical School, Boston, MA 02115, USA.
↵†Corresponding author. Email: hshafiee@bwh.harvard.edu
↵* These authors contributed equally to this work.
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Science Translational Medicine  22 Mar 2017:
Vol. 9, Issue 382, eaai7863
DOI: 10.1126/scitranslmed.aai7863

 

Link: http://stm.sciencemag.org/content/9/382/eaai7863

 

 

 

 

 

 

 

 

 

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