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	<title>personalized computational blood flow models &#8211; Science</title>
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	<title>personalized computational blood flow models &#8211; Science</title>
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		<title>Blood Flow Digital Twins Aim to Catch Hidden Fetal Heart Defects Before Birth</title>
		<link>https://scienmag.com/blood-flow-digital-twins-aim-to-catch-hidden-fetal-heart-defects-before-birth/</link>
		
		<dc:creator><![CDATA[Denise Maddox]]></dc:creator>
		<pubDate>Mon, 05 Oct 2026 05:50:40 +0000</pubDate>
				<category><![CDATA[Technology and Engineering]]></category>
		<category><![CDATA[3D printing]]></category>
		<category><![CDATA[biomedical engineering]]></category>
		<category><![CDATA[biomedical engineering fetal heart]]></category>
		<category><![CDATA[blood flow modeling]]></category>
		<category><![CDATA[blood flow physics in fetal health]]></category>
		<category><![CDATA[coarctation of the aorta]]></category>
		<category><![CDATA[coarctation of the aorta diagnosis]]></category>
		<category><![CDATA[computational fluid dynamics]]></category>
		<category><![CDATA[congenital heart defect detection]]></category>
		<category><![CDATA[congenital heart disease]]></category>
		<category><![CDATA[digital twin]]></category>
		<category><![CDATA[digital twin technology in obstetrics]]></category>
		<category><![CDATA[early detection of fetal heart obstructions]]></category>
		<category><![CDATA[echocardiography]]></category>
		<category><![CDATA[fetal blood flow digital twins]]></category>
		<category><![CDATA[fetal cardiovascular health monitoring]]></category>
		<category><![CDATA[fetal heart defects]]></category>
		<category><![CDATA[National Institutes of Health]]></category>
		<category><![CDATA[NIH-funded fetal heart research]]></category>
		<category><![CDATA[noninvasive fetal cardiac testing]]></category>
		<category><![CDATA[personalized computational blood flow models]]></category>
		<category><![CDATA[prenatal blood flow analysis]]></category>
		<category><![CDATA[prenatal diagnosis]]></category>
		<category><![CDATA[Worcester Polytechnic Institute]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=237004</guid>

					<description><![CDATA[A WPI researcher is leading a $2.9 million NIH-funded project to build a digital twin model that uses fetal blood flow data to detect coarctation of the aorta before birth.]]></description>
										<content:encoded><![CDATA[<p>Every year, thousands of babies are born with hearts that were quietly struggling long before anyone noticed. Among congenital heart defects, the most common category of birth defect worldwide, one condition in particular has proven stubbornly difficult to spot before delivery: a narrowing of the aorta known as coarctation. Now, a biomedical engineer at Worcester Polytechnic Institute is betting that the key to finding these hidden problems lies not in the shape of the fetal heart, but in the physics of the blood moving through it. Zhenglun &#8220;Alan&#8221; Wei, an assistant professor in WPI&#8217;s Department of Biomedical Engineering, is leading a four-year research project funded with $2,915,519 from the National Institutes of Health to build a personalized computational model that uses detailed blood flow information from noninvasive tests to detect obstructions of the aorta in fetuses.</p>
<p>The clinical stakes are considerable. The aorta is the body&#8217;s largest blood vessel, the highway that carries oxygen-rich blood from the heart to every organ and limb. When this vessel is pinched or narrowed as it exits the heart, a hallmark of coarctation of the aorta, blood flow to the lower body is restricted and the fetal heart must pump harder to push blood through the constriction. The condition accounts for an estimated 6% to 8% of all cardiac birth defects, making it one of the more frequently encountered diagnoses a fetal cardiologist must consider. Yet despite its prevalence, coarctation remains one of the most challenging defects to identify prenatally.</p>
<p>The reason for that difficulty lies in the limitations of current screening tools. Standard prenatal testing relies primarily on anatomic information, essentially static pictures of the heart&#8217;s structure, rather than on dynamic blood-flow data, to assess fetal heart health. Standard ultrasound and even specialized echocardiograms, noninvasive tests that use sound waves to create images and generate data about a fetus, often fail to detect anatomical and blood flow abnormalities in a developing heart. Worse, ultrasound-based tests sometimes produce false positives, suggesting that an abnormality is present when no such defect actually exists. &#8220;Standard prenatal testing and even specialized imaging often fail to detect anatomical problems in the fetal aorta,&#8221; Wei says. &#8220;By integrating detailed blood flow parameters, we will give doctors a more precise tool to use when diagnosing congenital heart defects.&#8221;</p>
<p>The consequences of a missed diagnosis can follow a child for a lifetime. If coarctation of the aorta is not diagnosed early and repaired with surgery, infants can suffer long-term health problems such as high blood pressure, or in severe cases, die. Early detection changes the entire trajectory of care. When clinicians and families know before birth that a defect is present, they can plan for delivery at a center equipped for immediate intervention, schedule surgical repair, and monitor the newborn closely from the first hours of life. &#8220;Surgeons can repair many heart problems in babies, but the first, and most important, step is detecting problems,&#8221; Wei said. &#8220;The earlier we can identify a condition, the more time clinicians and families have to plan for the baby&#8217;s care.&#8221;</p>
<p>Wei&#8217;s answer to this diagnostic gap is a digital twin: a viewable digital replica of an individual patient&#8217;s cardiovascular system that can be interrogated on a computer the way a clinician might examine a patient at the bedside. The model will integrate multidimensional, patient-specific data to support clinical decision-making, including assessment of whether a fetal heart defect is present. Rather than relying on a single snapshot of anatomy, the digital twin will simulate how blood actually behaves inside a particular fetus&#8217;s aorta, capturing the hemodynamic signatures that a narrowing leaves on pressure, velocity, and wall stress even when the structural change is too subtle for imaging to resolve.</p>
<p>The raw material for this model comes from an unusually rich data source. Wei&#8217;s team will draw on fetal heart data collected at more than 15 cardiology programs across North America that are part of the Fetal Heart Society. The database includes information gathered during two-dimensional and three-dimensional ultrasound tests performed on hundreds of racially and ethnically diverse pregnant women, including some whose babies were confirmed after birth to have heart defects. That breadth matters both scientifically and clinically: a model trained on diverse populations is more likely to perform reliably across the full spectrum of patients a prenatal clinic will see, and the inclusion of confirmed postnatal diagnoses gives the researchers ground truth against which their predictions can be checked.</p>
<p>Wei and his team have already used information in the database to create a model representing blood flow in healthy fetal hearts, establishing a baseline of normal hemodynamics. Going forward, the new model will focus on a set of physically meaningful measurements that reflect how the cardiovascular system responds to obstruction. These include the forces exerted on the walls of fetal blood vessels, the pressure and flow characteristics through a narrowed fetal artery, and the resistance that arises when freshly pumped blood collides with blood already moving through the vessel. Each of these parameters encodes information about the geometry and elasticity of the aorta in ways that a static image cannot, which is precisely why the researchers believe flow-based metrics will outperform anatomy-only assessment.</p>
<p>Building a model is only half the challenge; proving that it is trustworthy is the other half. To validate their computational predictions, the researchers will conduct laboratory experiments using 3D-printed silicone models of fetal aortas, paired with fluid and pumping mechanisms that recreate the mechanical conditions of the fetal circulation. These physical phantoms allow the team to compare what the digital twin predicts against what actually happens in a controlled, measurable system with known geometry. Finally, data from the Geisinger healthcare system&#8217;s database will be used to evaluate blood flow metrics for better diagnosis of aorta narrowing in the future, closing the loop between computation, experiment, and real clinical outcomes.</p>
<p>The project is a deliberately interdisciplinary effort. Wei is working with Professor Zhongqiang Zhang and Associate Professor Fangfang Wang, both of WPI&#8217;s Department of Mathematical Sciences, whose expertise in computational mathematics underpins the numerical machinery of the digital twin, and with Dr. Shuping Ge, a pediatric cardiologist and researcher with the Geisinger healthcare system in Pennsylvania, who brings the clinical perspective needed to ensure the model answers questions doctors actually face. The work also builds on Wei&#8217;s broader research program in computational and experimental models of blood flow mechanics. His fetus-related research has been supported by the American Heart Association&#8217;s Second Century Faculty Independence Award and a National Institute of Biomedical Imaging and Bioengineering Trailblazer Award, honors recognizing the innovation and potential clinical impact of his work, and he has previously collaborated on pediatric medical devices and 3D-printed blood vessels for heart bypass surgery.</p>
<p>For Wei, the ultimate measure of success is not a publication or a patent but a change in how early and how confidently fetal heart defects are caught. He says that development of a validated digital twin model for coarctation of the fetal aorta will lay a solid foundation for future human studies that could lead to more accurate screening tools and better health outcomes for children with the birth defect. &#8220;The goal of my lab is to improve the detection and treatment of cardiovascular disease and, ultimately, to help ensure that patients receive the right care at the right time,&#8221; Wei said. If the project succeeds, the faint hemodynamic whispers of a narrowed aorta, invisible to today&#8217;s ultrasound screens, may become impossible for medicine to miss.</p>
<p><strong>Subject of Research:</strong> Development of a blood flow-based digital twin model for prenatal detection of fetal aortic coarctation</p>
<p><strong>Article Title:</strong> Worcester Polytechnic Institute researcher is seeking clues to problems in tiny hearts</p>
<p><strong>Article References:</strong> Worcester Polytechnic Institute researcher is seeking clues to problems in tiny hearts. (n.d.). <a href="https://www.eurekalert.org/news-releases/1146094" rel="noopener noreferrer">Original publication</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> Not provided</p>
<p><strong>Keywords:</strong> fetal heart defects, coarctation of the aorta, digital twin, blood flow modeling, prenatal diagnosis, echocardiography, computational fluid dynamics, 3D printing, National Institutes of Health, Worcester Polytechnic Institute, congenital heart disease, biomedical engineering</p>
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