Anna-Marie Bort MLT (ASCP)CM

President

Understanding Borderline Normal forms in Sperm Morphology

*Historical Data Referenced* Sperm morphology is an important predictor of male fertility and is often the parameter used to determine fertility treatment. Ironically, sperm morphology is often the most difficult part of a semen profile to interpret due to poor standardization of morphologic variant classification, coupled with high subjectivity and variability in performance of the analysis.

Reviewing our Competency Challenge data and published Proficiency Test results revealed several serious problems in morphology analysis:

    Many labs do not know what classification system is used in their facility.
    Technologists often use the wrong reference atlas for the classification system they are reporting.
    Many laboratories are confused by the difference between the two major systems currently used for the diagnosis of infertility:
    Traditional:  WHO laboratory manual 3rd Edition (1992)Strict:  WHO laboratory manual 4th Edition (1999) / 5th Edition (2010) / 6th Edition (2021)

Traditional vs. Strict

The primary difference between these two classification systems is in how borderline normal sperm are classified. WHO 3rd Edition classifies borderline sperm as normal, while the Strict system classifies them as abnormal. To easily compare systems, examine at least 200 sperm with a 100X oil objective and classify them as normal, borderline, or abnormal according to the criteria below. Only intact recognizable sperm should be counted in the differential. Do NOT count tailless heads or headless tails.

Borderline Normal Forms

Round head shape with a normal acrosome.
V-Shape - straight sides to a point at the base
Curly Bracket - a pinched projection or tip at the neck
Irregular roughness, waviness, or indentation in the contour of the head shape

In all cases, the variation does not dramatically change the shape of the head from oval.

Calculations

Traditional

    % Normal = [(# Normal + # Borderline) / # Analyzed] * 100

Strict

    % Normal = [#Normal / #Analyzed] * 100

On The Borderline

Understanding Borderline Normal forms in Sperm Morphology

*Historical Data Referenced* Sperm morphology is an important predictor of male fertility and is often the parameter used to determine fertility treatment. Ironically, sperm morphology is often the most difficult part of a semen profile to interpret due to poor standardization of morphologic variant classification, coupled with high subjectivity and variability in performance of the analysis.

Reviewing our Competency Challenge data and published Proficiency Test results revealed several serious problems in morphology analysis:

    Many labs do not know what classification system is used in their facility.
    Technologists often use the wrong reference atlas for the classification system they are reporting.
    Many laboratories are confused by the difference between the two major systems currently used for the diagnosis of infertility:
    Traditional:  WHO laboratory manual 3rd Edition (1992)Strict:  WHO laboratory manual 4th Edition (1999) / 5th Edition (2010) / 6th Edition (2021)

Traditional vs. Strict

The primary difference between these two classification systems is in how borderline normal sperm are classified. WHO 3rd Edition classifies borderline sperm as normal, while the Strict system classifies them as abnormal. To easily compare systems, examine at least 200 sperm with a 100X oil objective and classify them as normal, borderline, or abnormal according to the criteria below. Only intact recognizable sperm should be counted in the differential. Do NOT count tailless heads or headless tails.

Borderline Normal Forms

Round head shape with a normal acrosome.
V-Shape - straight sides to a point at the base
Curly Bracket - a pinched projection or tip at the neck
Irregular roughness, waviness, or indentation in the contour of the head shape

In all cases, the variation does not dramatically change the shape of the head from oval.

Calculations

Traditional

    % Normal = [(# Normal + # Borderline) / # Analyzed] * 100

Strict

    % Normal = [#Normal / #Analyzed] * 100