Menstrual Cycle Heat Maps: Visualising menstrual cycle variability using hormone heat map arrays referenced to the ultrasound day of ovulation

Thomas Bouchard; Saman Abdullah; Rene Leiva; Rene Ecochard

doi:10.63264/qk8aw674

Menstrual Cycle · Cycle Biomarkers

Menstrual Cycle Heat Maps: Visualising menstrual cycle variability using hormone heat map arrays referenced to the ultrasound day of ovulation

Bouchard T, Abdullah S, Leiva R, Ecochard R

Published May 2, 2025 Journal of Restorative Reproductive Medicine, 1, 1-9

DOI 10.63264/qk8aw674

RRM Academy Synopsis

Heat maps show hormone patterns vary between cycles in healthy women

This proof-of-concept study made heat maps from two existing datasets of healthy women. One had 107 women with 283 cycles. The other had 21 women with 62 cycles. Heat maps displayed individual and group hormone patterns together in one image. Hormone timing varied between women and between cycles.

Key Findings

The larger dataset had 107 women and 283 cycles, with ovulation dated by serial ultrasound. The smaller had 21 women and 62 cycles, with ovulation estimated from peak LH.
The estrogen signal (E1G) began 3-4 days before ovulation in the larger dataset and 4-5 days before the estimated day of ovulation in the smaller one.
In the larger dataset, the LH signal centered on ovulation day and the 1-3 days after. Some of its women showed an increased or prolonged LH signal in the 3-4 days after.
In the larger dataset, the progesterone signal (PDG) rose on day 3 after ovulation, peaked around day 7 and fell on day 12.
A wider window of days around ovulation still showed no clear FSH pattern, which the authors say suggests greater individual variability between cycles.

Interpretation

The paper is a proof-of-concept study that draws pictures from two existing datasets. It describes patterns and tests no outcome. The larger dataset came from healthy women with regular cycles, recruited in the 1990s at European natural family planning centers. Women with abnormal cycles or fertility problems were excluded. In the smaller dataset, ovulation was estimated from another monitor. The authors did not compare the two datasets statistically and say assay differences may explain some variation between them. In these datasets, the authors found the start of the fertile window hard to mark with a single hormone threshold change.

RRM Context

Restorative reproductive medicine reads each woman's own cycle, a cycle-charting-informed principle. The authors say textbook average curves made day-to-day hormone variation look abnormal. They cite earlier work describing a continuum from normal to abnormal cycles. The heat maps show that spread among healthy ovulating women in one image. The authors list infertility and luteal phase questions as possible later uses.

Our editorial summary of this paper, not the article's abstract.

Abstract

Objective

There is considerable individual day-to-day variation within the menstrual cycle and between cycles in women. Average hormone curves inadequately describe the individual hormone patterns experienced by women. The present study applies a novel application of a statistical array (heat map) to demonstrate both individual and group menstrual cycle hormone variability.

Design

Using pre-existing datasets, two cohorts of women were analysed using a statistical method to visualise quantitative hormonal variation.

Subjects

In one cohort, 107 women contributed a total of 283 menstrual cycles and in the second cohort, 21 women contributed a total of 62 menstrual cycles.

Exposure

Women collected first morning urine samples for analysis of estrone-3-glucuronide (E1G) and luteinizing hormone (LH) in both datasets. In the larger dataset, pregnanediol-3-alpha-glucuronide (PDG) and follicle-stimulating hormone (FSH) were also collected. Serial ultrasounds identified the precise day of ovulation in the larger dataset. In the smaller dataset, peak LH was used to identify the estimated day of ovulation.

Outcome Measures

The main outcome measure was identifying hormonal variability using hormone array heat maps.

Conclusion

Heat maps were able to quickly show clustering of hormone patterns in the fertile window and on the day of ovulation. Individual differences were identified in rows on the heat map relative to the day of ovulation. This new tool to visually represent hormonal changes with heat maps identifies both individual and group variability of menstrual cycle hormones.

Topics

Menstrual Cycle › Cycle Biomarkers › Hormonal Markers · Reproductive Endocrinology › Ovarian Hormones › Estrogen · Research Methods › Measurement and Statistics › Data Visualization and Cycle Analytics

Thomas Bouchard, Saman Abdullah, Rene Leiva, Rene Ecochard

Tom Bouchard, T Bouchard, S Abdullah, R Leiva, R Ecochard

DOI 10.63264/qk8aw674 10.63264/qk8aw674 Bouchard et al. 2025, Bouchard 2025

Menstrual Cycle Heat Maps: Visualising menstrual cycle variability using hormone heat map arrays referenced to the ultrasound day of ovulation

Heat maps show hormone patterns vary between cycles in healthy women

Key Findings

Interpretation

RRM Context

Abstract

Topics

By this author

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