When you see “Nicolaides” on a prenatal ultrasound report, you’re seeing a reference to Professor Kypros Nicolaides, a fetal medicine specialist whose research group developed the screening algorithms your clinic used to calculate your pregnancy risk scores. His team, working through an organization called the Fetal Medicine Foundation (FMF), created standardized methods for measuring specific features on ultrasound and combining them with blood tests to estimate the chance of chromosomal conditions, preeclampsia, and other complications. The name appears on reports because the software running those calculations was built on his published formulas.
The Fetal Medicine Foundation and Why Its Name Appears on Reports
The Fetal Medicine Foundation is a UK-based research and education charity that Nicolaides established to standardize prenatal screening worldwide. Over several decades, his group published the foundational research on first-trimester risk assessment, creating the mathematical models that combine a pregnant person’s age, ultrasound measurements, and blood-test results into a single risk estimate for conditions like Down syndrome (trisomy 21).1Wiley Online Library (Ultrasound in Obstetrics & Gynecology). Screening for chromosomal defects Most clinics around the world that offer first-trimester combined screening are using either the FMF’s own software or a locally developed system built around the same published algorithms. That’s why “Nicolaides,” “FMF,” or “Fetal Medicine Foundation” may show up somewhere on your printed results, in the software header, or in the references section of the report.
Seeing this name doesn’t mean Professor Nicolaides personally reviewed your scan. It simply identifies whose research methods were used to generate your risk numbers, much the way a lab report might reference the manufacturer of the testing equipment.
What First-Trimester Combined Screening Actually Measures
The screening that carries the FMF label typically happens between about 11 and 14 weeks of pregnancy. It combines three inputs. The first is an ultrasound measurement of the fluid-filled space at the back of the baby’s neck, called the nuchal translucency (NT). A larger-than-expected measurement can be associated with chromosomal abnormalities and certain heart defects. The second and third inputs come from a blood draw: levels of a hormone fragment called free beta-hCG and a protein called PAPP-A. When these three values are plugged into the FMF algorithm along with your age and the exact gestational age of the pregnancy, the software produces a risk ratio for trisomy 21 and other major chromosomal conditions.
This combined approach can identify roughly 90 percent of pregnancies affected by trisomy 21, with a false-positive rate of about 5 percent.2PubMed. Screening for fetal aneuploidies at 11 to 13 weeks That means the vast majority of affected pregnancies are flagged, but around 1 in 20 unaffected pregnancies will also receive a higher-risk result and be offered further testing. The algorithm was validated in a large prospective study confirming that this combination of maternal age, NT, free beta-hCG, and PAPP-A performs well as a screening tool.3PubMed. Prospective validation of first-trimester combined screening for trisomy 21
Additional Ultrasound Markers That Improve Detection
The FMF’s research didn’t stop at nuchal translucency. Over time, Nicolaides’s group identified several additional features visible on first-trimester ultrasound that, when assessed alongside NT, can push detection rates higher or reduce false positives. The three main additions are the nasal bone (whether it is visible or absent at the time of the scan), blood flow through the tricuspid valve of the fetal heart, and flow through a vessel called the ductus venosus.
Adding all three of these markers to the standard NT measurement and maternal age can raise the detection rate for trisomy 21 to about 94 percent while lowering the false-positive rate to around 3 percent.4PubMed. First trimester ultrasound screening for Down syndrome based on maternal age, fetal nuchal translucency and different combinations of the additional markers nasal bone, tricuspid and ductus venosus flow Not every clinic assesses all three, because doing so requires a more experienced sonographer and a longer appointment. If your report mentions any of these markers, the scan was a more comprehensive version of the standard first-trimester screen.
Second-Trimester Soft Markers Are a Separate Category
If you had a later anatomy scan, typically around 18 to 22 weeks, the report may also list what are called “soft markers.” These are a different set of ultrasound findings from the first-trimester markers described above. Common soft markers include a thickened nuchal fold (distinct from the first-trimester NT measurement), slightly shortened limb bones, mild kidney dilation, echogenic (bright-appearing) bowel, a bright spot in the heart, and choroid plexus cysts in the brain.5PubMed Central. Ultrasonographic Soft Markers of Aneuploidy in Second Trimester: Are We Lost?
These findings are called “soft” because they are nonspecific and often temporary. Many of them resolve on their own and are found in pregnancies with perfectly normal chromosomes. Their significance depends heavily on context: if your first-trimester screening already showed low risk, a single isolated soft marker usually doesn’t change the overall picture very much. If several are found together, or if earlier screening was borderline, your provider may recommend additional testing. The FMF algorithms are primarily designed for first-trimester use, so second-trimester soft markers are generally interpreted using different frameworks, though some clinics incorporate them into the same software platform.
How to Read the Risk Number on Your Report
The output you’ll see on a report using FMF methodology is typically expressed as a ratio, like 1:1,500 or 1:150. The first number means that out of a group of pregnancies with the same measurements and blood results as yours, roughly one would be expected to have the condition in question. A result of 1:1,500 is lower risk than 1:150. Many people find this counterintuitive because the bigger number looks “more,” but it means the opposite: the larger the second number, the lower the estimated chance.
Clinics set a threshold, often somewhere around 1:150 or 1:100, to divide results into “higher risk” and “lower risk” categories. If your number falls on the higher-risk side of that threshold, you’ll typically be offered follow-up testing. That might be a non-invasive prenatal test (NIPT), which analyzes fragments of fetal DNA circulating in your blood, or a diagnostic procedure like chorionic villus sampling or amniocentesis. The screening result is not a diagnosis. A “high risk” result means additional investigation is warranted, not that your baby definitely has a chromosomal condition.
The specific cut-off a clinic uses matters quite a bit. Research on preeclampsia screening algorithms, for instance, has shown that shifting the threshold and including or excluding certain blood markers can meaningfully change which patients are flagged and which are missed.6PubMed Central. Effectiveness of Different Algorithms and Cut-off Value in Preeclampsia First Trimester Screening The same principle applies to chromosomal screening: the detection rate and false-positive rate quoted in any study depend on where the line is drawn. Your clinic’s chosen threshold should be explained to you before the test, and your report may list it.
Preeclampsia Screening Using the FMF Algorithm
Chromosomal screening is the most well-known application of the FMF’s work, but the one that’s grown fastest in recent years is preeclampsia prediction. Preeclampsia is a dangerous blood-pressure disorder that can develop in the second half of pregnancy, and the FMF algorithm estimates the risk of it during the same first-trimester visit used for chromosomal screening. The model combines information about the pregnant person’s medical history and characteristics with measurements of blood pressure, blood flow in the uterine arteries (assessed by ultrasound), and blood levels of PAPP-A and a protein called PlGF.7PubMed. Prospective Validation of First-Trimester Screening for Preterm Preeclampsia in Nulliparous Women (PREDICTION Study)
The reason this matters practically is that identifying high-risk individuals early enough allows them to start low-dose aspirin before 16 weeks of gestation, which has been shown to reduce the risk of preterm preeclampsia. A health technology assessment of the FMF-based screening program found that it likely reduces the risk of preeclampsia requiring delivery before 37 weeks, with risk reductions in the range of 30 to 36 percent compared with standard care.8PubMed Central. First-Trimester Screening Program for the Risk of Pre-eclampsia Using a Multiple-Marker Algorithm: A Health Technology Assessment If your report includes a preeclampsia risk score alongside the chromosomal risk score, the same FMF software calculated both during the same appointment.
Fetal Growth Charts and Later Pregnancy Monitoring
The FMF’s influence extends beyond the first trimester. Later in pregnancy, your ultrasound reports may reference FMF growth charts when estimating your baby’s weight. The FMF published population-based reference ranges for estimated fetal weight (EFW) that allow clinicians to plot where a baby falls on the growth curve, expressed as a percentile.9PubMed. Fetal Medicine Foundation fetal and neonatal population weight charts If a baby’s estimated weight is below the 10th percentile for gestational age, for example, the pregnancy may be monitored more closely for signs of growth restriction.
Different growth charts exist, and not every clinic uses the FMF’s version. Some use charts from the World Health Organization or from the INTERGROWTH-21st project, and the percentile cutoffs can differ slightly depending on which reference is chosen. If your report says something like “EFW at the 8th percentile (FMF),” that tells you both the finding and which standard was used for comparison. Knowing the reference source matters because a baby labeled “small for gestational age” on one chart might fall within normal range on another.
Why Sonographer Training and Accreditation Matter
One reason the FMF’s name appears so prominently in prenatal medicine is that the organization doesn’t just publish algorithms; it also certifies individual sonographers. To use the FMF’s NT-based screening, a sonographer must demonstrate competence through an accreditation process that includes submitting ultrasound images for review. This standardization step is important because the accuracy of the entire screening depends on how precisely that NT measurement is taken. A millimeter off in either direction can shift the risk calculation substantially.
Research comparing different credentialing programs found real differences in measurement quality. Sonographers accredited through the FMF’s own program produced more consistent NT measurements than those credentialed through a different system (the NTQR program used in the United States). The NTQR-credentialed group had significantly more variation in their measurements and a higher rate of underestimation.10Wiley Online Library (Ultrasound in Obstetrics & Gynecology). Impact of nuchal translucency credentialing by the FMF, the NTQR or both on screening distributions and performance For you as a patient, this is relevant because it means the quality of your screening result depends partly on the training and certification of the person holding the ultrasound probe. If your clinic participates in the FMF’s credentialing program, you can have some confidence that the measurements feeding into your risk calculation are being taken to a defined standard.
When the Algorithm Doesn’t Fit the Population
One limitation worth understanding is that the FMF’s risk models were developed and initially validated in specific populations, predominantly in the UK and Europe. When those same models are applied in populations with different demographic profiles, the risk estimates can shift in unexpected ways. Research testing the FMF’s preeclampsia algorithm in a Brazilian population, for example, found that the model’s treatment of ethnicity as a risk factor didn’t translate cleanly. The algorithm assigned higher baseline risk to individuals of Afro-Caribbean descent, a weighting that was derived from UK data and wasn’t confirmed in the Brazilian setting.11PubMed Central. Performance of Fetal Medicine Foundation Software for Pre-Eclampsia Prediction Upon Marker Customization
When the researchers recalibrated the model for their local population, the proportion of people classified as high risk for preeclampsia dropped from about 14 percent to about 12 percent. That difference isn’t trivial: it means that in the original version, roughly one in seven patients in that population would have been flagged as high risk and potentially started on preventive aspirin, while the recalibrated version would flag closer to one in eight. No screening tool is perfectly portable across all populations, and this is an active area of research. If you’re being screened in a country or at a clinic that’s distant from the populations used to build the original model, it’s worth asking whether the software has been locally validated.
What Showing “Higher Risk” Actually Means for Next Steps
If your FMF-derived risk result puts you in the higher-risk category for a chromosomal condition, the first thing to understand is that screening is not the same as diagnosis. A screening test estimates probability; a diagnostic test gives a definitive answer. The typical pathway after a higher-risk first-trimester screen is to be offered either cell-free DNA testing (NIPT) as an intermediate step or to proceed directly to an invasive procedure like amniocentesis or chorionic villus sampling. Which option your provider recommends depends on how high the risk estimate is, your gestational age, your personal preferences, and local clinical guidelines.
For preeclampsia, a high-risk result on the FMF algorithm usually leads to a recommendation to start low-dose aspirin (typically 150 mg daily) before 16 weeks. Unlike chromosomal screening, where the follow-up is about gathering more information, preeclampsia screening leads to a concrete preventive intervention. The evidence supporting aspirin in this context is strong enough that national guidelines in multiple countries have adopted FMF-style first-trimester screening as the basis for their aspirin recommendations.
When Nicolaides Isn’t on Your Report
Not every prenatal screening program worldwide uses FMF algorithms. In the United States, for example, many labs use a different risk-calculation engine called the FASTER algorithm or proprietary software from commercial laboratories. In those cases, you won’t see Nicolaides or FMF on your report, but the underlying approach is broadly similar: ultrasound measurements plus blood markers combined with maternal age to produce a risk ratio. The detection rates and false-positive rates may differ slightly between systems, partly because of different statistical models and partly because of different sonographer credentialing requirements.
Some clinics have also shifted toward offering NIPT as a first-line screening test, bypassing the combined first-trimester screen entirely. NIPT has a higher detection rate for trisomy 21 and a lower false-positive rate than the traditional combined screen, but it doesn’t provide the ultrasound assessment that can reveal structural issues, and it doesn’t screen for preeclampsia. Many providers view the two approaches as complementary: even if NIPT is used for chromosomal screening, the first-trimester ultrasound and blood work remain valuable for assessing preeclampsia risk, dating the pregnancy precisely, and evaluating fetal anatomy.
If you’re comparing reports from different pregnancies or different clinics and notice that one mentions Nicolaides or FMF and the other doesn’t, the difference is in which statistical engine processed your data. The raw measurements, the NT thickness, the blood marker levels, are the same biological information regardless of which software interprets them. The algorithms differ in how they weight each variable and where they draw the risk thresholds, which is why the same measurements can occasionally produce slightly different risk numbers depending on the platform used.