Peyronie’s Disease (PD) occurs when plaque develops in the penis, creating a curve when the penis is erect. PD affects around 15% of adult men, 8% of which seek help from a healthcare provider.
After a thorough history and physical examination, clinicians will typically evaluate the curvature during an erection by injecting medication into the penis. They will then objectively measure the penis to see how severe the curvature is. Some clinicians may use home images of an erect penis to see how severe the curve is. The downside to these methods, though, is that clinicians are human, and humans can measure incorrectly.
That’s what pushed a group of researchers to see if artificial intelligence (AI) could do a better and faster job of assessing penile curvature. To do this, they used a tool they call the PenoMeter. This tool uses images of the top, left, and right sides of an erect penis. The AI algorithm scans these images to calculate the angle at the point of maximal curvature (PMC).
It’s important to note that there are two stages of PD: active, and chronic. In the active phase, the plaque is still developing, with guidelines recommending observation or anti-inflammatory treatment until the scarring process settles down. In the chronic phase, the plaque has stabalized, making it more responsive to more treatment options, such as injections or surgery. Using technology to measure the PMC may make it easier to find the baseline curve and identify the best treatment method.
In the PenoMeter study, researchers used high-quality top, left, and right-side images of 22 PD patients at their clinic. Additionally, they had three practiced clinicians hand-assess the exact same images, to see how accurate the PenoMeter is. This process was completed twice with the same images, with a two-month break between assessments. Researchers used the highest and lowest differences in human assessments as a range of accuracy for the PenoMeter’s results.
PenoMeter May Be a Good Clinical Assistant
After the first round, results showed that the PenoMeter’s PMC measurements were accurate, compared with the clinician’s PMC measurements. The PenoMeter was better-than-expected at finding the PMC, with around 60% of the images being in-line with, or more accurate than, the clinicians'.
After the second round, the clinicians’ PMC measurements had varied from their original of the same images. The PenoMeter showed no difference in measurements. However, due to the change in clinician results, only 52% of the images this time were in-line with, or more accurate than, the clinicians’.
Additionally, researchers used several images from online sources. This provided variety for testing how different types of images affect the PenoMeter’s measurements. The images included different lighting/brightness, skin tones, and both circumcised and uncircumcised penises. The results revealed that the PenoMeter can adapt to different types of images, as well as different patients.
The results show that the PenoMeter can be used as a clinician's assistant (both in the office or at home). Clinicians can use this technology to help assess the curvature of PD in patients. However, the PenoMeter is not the end-all-be-all. A clinician still needs to assess the symptoms of PD to create the best plan for each patient.
Conclusion
The PenoMeter’s assessment is only as accurate as the quality of erection presented to it. So, there is a need for consistency for the PenoMeter to be accurate. With further tests, the PenoMeter may become a useful tool for assessing penile curvatures, which may save time for patients and clinicians, and can provide a comfortable at-home option.
References:
Peyronie’s disease. Cleveland Clinic. (2023, April 11). https://my.clevelandclinic.org/health/diseases/10044-peyronies-disease
Soltani, R., Balapour, A., Witherspoon, L., Alhamam, A., Flannigan, R., & Hach, F. (2025). Penometer: A machine learning and algorithmic tool to advance Peyronie’s Disease Assessment. The Journal of Sexual Medicine, 22(4), 597–604. https://doi.org/10.1093/jsxmed/qdaf016
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