Digital Twin of Nonpregnant Human Uterus

Digital Twin of Nonpregnant Human Uterus | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Digital Twin of Nonpregnant Human Uterus Yiqi Lin, Jazmin Aguado-Sierra, Yuan Nan, Sicheng Wang, Constantine Butakoff, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6505611/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Uterine peristalsis involves spontaneous, mild contractions of the sub-endometrial layer in the nonpregnant uterus, playing a crucial role in menstruation and fertility. Disruptions in peristaltic patterns have been linked to conditions like subfertility, abnormal uterine bleeding, and endometriosis. Uterine Peristalsis Imaging (UPI) was developed to noninvasively image 3D uterine electrical activation patterns with high spatial and temporal resolution. However, UPI cannot capture the mechanical deformation or intrauterine fluid dynamics following electrical activation. To address this, we developed Alya Purple, a digital twin of the human nonpregnant uterus that integrates patient-specific anatomical and electrophysiological data from UPI to simulate electrical, mechanical, and fluid-dynamic processes across multiple biological scales. Alya Purple reproduces uterine peristalsis patterns while offering detailed insights into human nonpregnant uterine function. In the future, it could enable personalized treatment evaluations, bridging clinical and computational models to advance gynecological care and improve patient outcomes through precision medicine. Biological sciences/Physiology Biological sciences/Physiology/Reproductive biology Health sciences/Diseases Health sciences/Diseases/Reproductive disorders Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Uterine peristalsis, characterized by spontaneous mild contractions in the inner layer of the nonpregnant uterus, demonstrates distinct 3D peristalsis patterns during different menstrual phases and plays a central role in maintaining physiological functions such as menstrual blood expulsion and sperm transport 1 , 2 . Disruptions in these patterns are believed to be associated with various gynecological conditions, including infertility, endometriosis, and abnormal uterine bleeding 3 , 4 . For example, during the menses phase of women with normal menstrual cycle, 65% of waves traveled from the fundus toward the cervix, which may facilitate the vaginal expulsion of the menstrual blood. Frequent or strong cervix-to-fundus peristalsis waves during the menses phase could potentially cause retrograde menstruation and increase the risk of developing endometriosis 5 – 7 . In contrast, 75.8% of waves traveled in the opposite direction during normal ovulation, which may promote sperm transport 8 – 11 . The cervix-to-fundus waves could help move sperm toward the fallopian tubes to promote fertilization in patients with normal menstrual cycles 1 , 2 , and insufficient cervix-to-fundus peristalsis could contribute to infertility. Recent development of Uterine Peristalsis Imaging (UPI) has enabled noninvasive imaging of human uterine peristalsis by integrating patient-specific uterine anatomy measured by magnetic resonance imaging (MRI) and multi-channel abdominal electrical activities 8 , 9 . UPI can map the electrical activity driving uterine peristalsis across the entire 3-dimensional (3D) uterine surface, allowing precise quantification of peristalsis patterns with high spatial and temporal resolution. However, UPI lacks the ability to provide critical information on mechanical deformation and intrauterine fluid dynamics following electrical activation—key components for understanding the functional outcomes of human uterine peristalsis. A similar challenge has been well addressed by a multi-physics, multi-scale whole-heart model in Cardiology 12 . Additionally, in the past decade, electrical-mechanical simulation models for pregnant uteruses have been developed to explore the coupling between electrical activation and mechanical contractions during labor. These models have provided valuable insights into human labor physiology and its management 13 – 16 . However, they often rely on simplified spherical geometries and lack the ability to simulate intrauterine fluid dynamics, limiting their applicability to the nonpregnant uterus. Given the significant differences in geometry and functional behavior between the pregnant and nonpregnant uterus, these models cannot be directly adapted for studying uterine peristalsis in nonpregnant individuals. To address the unmet need, we developed Alya Purple , a multi-scale, multi-physics digital twin of the non-pregnant human uterus, to simulate the electrical, mechanical, and fluid dynamics of uterine peristalsis (Fig. 1 ). Herein, a digital twin refers to a virtual replica of a physical object or system that uses real-world data to emulate its behavior. As a patient-specific, high-performance computational platform based on the Alya simulation system 17 – 21 , Alya Purple integrates anatomical and microstructural information of human nonpregnant uterus obtained through UPI. Alya Purple simulates the peristalsis initiation potentially driven by interstitial Cajal-like cells (ICLCs) 22 – 26 , electrical propagation, mechanical deformation, and intrauterine fluid dynamics across cellular, tissue, and uterine levels 17 – 21 . Alya Purple can dynamically simulate both physiological and pathological behaviors of the human nonpregnant uterus across different menstrual phases. By integrating patient-specific data and modeling complex interactions between electrical, mechanical, and fluid-dynamic processes, Alya Purple holds great potential to address critical knowledge gaps in uterine physiology and serve as a transformative platform for personalized gynecological care, enabling improved diagnosis, treatment planning, and management of various uterine conditions. Results Simulation of uterine peristalsis during menses in participants with normal menstrual cycles To simulate uterine peristalsis waves in patients with a normal menstrual cycle using Alya Purple, the uterine geometry was segmented from the patient’s MRI data, and the myometrium fiber structure was refined based on DTI (Fig. 2 ). The patient’s uterine peristalsis patterns imaged by UPI during the menses phase 8 were replicated in Alya Purple’s electro-mechanical-fluid simulation by identifying the earliest activation site observed in the UPI data. This site was selected as the initiation point for slow peristaltic wave propagation in the nonpregnant uterine digital twin, enabling accurate reproduction of patient-specific uterine peristalsis dynamics. UPI found that the dominant uterine peristalsis during menses in normal menstrual cycles is fundus-to-cervix peristalsis 8 , 9 . Figure 3 A shows a representative fundus-to-cervix uterine peristalsis during the menses phase, as imaged by UPI, alongside the corresponding Alya Purple simulation. The peristalsis wave originates near the fundus and left fallopian tube, propagating toward the cervix. Alya Purple accurately reproduced the electrical activation pattern (red band) observed in the UPI data. More importantly, Alya Purple simulated the resulting mechanical deformation driven by 3D electrical activation through its electro-mechanical coupling mechanism ( Section Electrical-Mechanical coupling model ). The subsequent intrauterine menstrual blood flow was computed using fluid dynamics simulation ( Section Computational fluid and particle dynamics and fluid-structure interaction ). Multiple groups of red particles representing menstrual blood were placed in the uterine cavity's left, right, and fundus areas for visualization. The simulation demonstrated that the uterine peristalsis waves effectively propelled menstrual blood toward the cervix, facilitating its expulsion from the uterus through the vaginal canal. UPI also imaged a small percentage of mild cervix-to-fundus uterine peristalsis during the menses phase in patients with normal menstrual cycles 8 , 9 . Digital twin simulations were conducted to explore how a mild cervix-to-fundus peristalsis wave affects menstrual blood movement during the menses phase. Figure 3 B presents the simulation results of two consecutive mild cervix-to-fundus peristaltic waves in a patient with a normal menstrual cycle. In the Alya Purple simulation, the first electrical wave initiates near the cervix, triggering corresponding mechanical deformation propagating toward the uterine fundus. During the first peristaltic wave (1.00 seconds to 6.00 seconds in Fig. 3 B), a small amount of menstrual blood is transported toward the upper uterine cavity near the fallopian tube. Following the subsequent peristaltic wave, a small fraction of this menstrual blood near the upper uterine cavity is further propelled into the fallopian tube at 12.00 seconds. These findings suggest that consecutive cervix-to-fundus uterine peristalsis waves can cause mild retrograde menstruation, even in patients with normal menstrual cycles, potentially contributing to menstrual blood movement toward the fallopian tubes. Simulation of uterine peristalsis during the ovulatory phase in patients with normal menstrual cycles UPI found that the dominant uterine peristalsis during the ovulatory phase in normal menstrual cycles is cervix-to-fundus peristalsis 8 , 9 . Alya Purple was used to replicate cervix-to-fundus uterine peristalsis. Figure 4 A shows a representative cervix-to-fundus peristalsis wave imaged by UPI. In the digital twin simulation, the uterine peristaltic wave traveled with a speed and pattern consistent with UPI findings. To evaluate the effect of cervix-to-fundus peristalsis on sperm movement, white particles representing sperm were placed near the lower segment of the uterus around the cervix, simulating uterine insemination during intercourse. The Alya Purple simulation demonstrated how sperm were transported from the cervix area toward the left fallopian tube during the peristaltic wave. Quantitative analysis revealed that after three consecutive cervix-to-fundus peristaltic waves, 77.46% of the sperm particles successfully reached the fallopian tube (Fig. 4 C, Left ), highlighting the critical role of coordinated uterine peristalsis in facilitating sperm transport during the ovulatory phase. Alya Purple is further employed to simulate irregular uterine peristalsis waves during the ovulatory phase 9 , 10 . Consecutive right-to-left peristalsis waves are simulated using Alya Purple (Fig. 4 B). This irregular uterine peristalsis significantly impaired the uterus’s ability to transport sperm to the fallopian tubes during the ovulatory phase, potentially reducing the likelihood of successful fertilization. After three right-to-left peristalsis waves, 41.93% of the sperm reached the fallopian tubes nearest the uterus (Fig. 4 C, Right ). Simulation of uterine peristalsis in the menses phase of patients with endometriosis Compared to women with normal menstrual cycles, UPI found that the dominant uterine peristalsis during the menses phase in patients with endometriosis is frequent, strong cervix-to-fundus peristalsis 8 , 9 . Alya Purple simulation was conducted for a patient with surgically confirmed endometriosis during the menses phase. The patient-specific uterine geometry and myometrium fiber structure were derived from an MRI scan. UPI identified typical cervix-to-fundus peristalsis in this endometriosis patient (Fig. 5 A). Based on UPI findings, an electrical stimulus was applied to the cervical area of the uterus digital twin. The simulated electrical activation pattern accurately reproduced the peristalsis wave observed in UPI imaging. Following the electrical activation, Alya Purple simulated the resulting mechanical deformation and intrauterine fluid dynamics. The simulation showed that menstrual blood within the uterine cavity, represented by red particles in Fig. 5 A, was propelled into both fallopian tubes due to the cervix-to-fundus uterine peristalsis. This finding highlights the potential role of abnormal cervix-to-fundus uterine peristalsis during the menses phase in retrograde menstruation and the subsequent development of endometriosis lesions outside the uterus. The simulated retrograde menstrual blood flow during menses was quantified and compared between mild cervix-to-fundus peristalsis waves in women with normal menstrual cycles and strong, frequent cervix-to-fundus peristalsis waves in patients with endometriosis (Fig. 5 B). In the simulation, 1000 particles representing menstrual blood were placed in distinct areas of the uterine cavity. After two mild cervix-to-fundus peristalsis waves, 33.34% of the particles reached the fallopian tubes in the patient with a normal menstrual cycle. In contrast, following consecutive, strong cervix-to-fundus peristalsis waves, 70.72% of the particles were propelled into the fallopian tubes in the patient with endometriosis (Fig. 5 B). These results demonstrate a significantly increased retrograde blood flow in endometriosis patients. Modeling the effects of electrical pacing to neutralize the cervix-to-fundus peristalsis wave direction in the menses phases of patients with endometriosis Finally, Alya Purple was employed as a virtual platform to examine the feasibility and efficiency of a nonpharmaceutical intervention to neutralize retrograde menstruation in patients with endometriosis. Similar to the cardiac and gastric pacemakers, a pacing stimulation was delivered to the uterus fundus in a representative endometriosis patient when a strong cervix-to-fundus peristalsis was detected during the menses phase. Specifically, at 2.00 seconds, one second after a peristalsis wave started at the cervix region (Fig. 6 ), electrical pacing was applied at the fundus region. Following the fundus stimulus, a slow peristalsis wave was initiated and traveled from the fundus toward the cervix, which collided and neutralized with the cervix-to-fundus peristalsis wave. As a result, the menstrual blood (represented by red particles) remained within the uterus. Following the second fundus pacing signal at 11.00 seconds, another fundus-to-cervix peristalsis wave is initiated by the fundus pacing and moved downwards toward the cervix, which expels the menstrual blood vaginally through the cervix beginning at 13.00 seconds. Discussion In this paper, we developed and presented, Alya Purple, a digital twin of the human nonpregnant uterus, which can conduct an efficient, multi-scale, multi-physical simulation of human uterine peristalsis across the menstrual cycle for women with normal menstrual cycles and patients with endometriosis. Alya Purple can not only precisely reproduce the electrical activation patterns of the uterine peristalsis, but also provide detailed information on resulting mechanical deformation and intrauterine fluid dynamics following uterine peristalsis. This capability enables precise quantification of menstrual blood movement during the menses phase and sperm transport during the ovulatory phase, offering a comprehensive framework for studying uterine physiology and associated gynecological conditions. Alya Purple revealed that fundus-to-cervix peristalsis, which dominates the menses phase in women with normal menstrual cycles, generates downward uterine mechanical deformation, effectively expelling menstrual blood vaginally. In comparison, weak and infrequent cervix-to-fundus peristalsis during normal menses induces only mild retrograde menstruation, displacing a small fraction of menstrual blood toward the fallopian tubes. In contrast, in patients with surgically confirmed endometriosis, Alya Purple simulations showed strong and frequent cervix-to-fundus peristalsis, generating significant retrograde blood flow toward the fallopian tubes. This mechanism likely contributes to the implantation of endometriosis lesions outside the uterus. These findings suggest that while mild retrograde menstruation occurs in healthy women, its phenotype and clinical outcomes differ significantly from the strong, frequent cervix-to-fundus peristalsis observed in patients with endometriosis. By accurately reproducing the electrical patterns of cervix-to-fundus peristalsis detected by UPI and simulating its mechanical and fluid consequences, Alya Purple can precisely quantify the severity of retrograde blood flow toward the fallopian tubes. This ability enables the phenotyping of retrograde peristalsis and offers a quantitative framework for risk stratification in developing endometriosis. In the long term, Alya Purple holds significant potential for noninvasive, early detection of endometriosis, particularly in adolescent patients. Alya Purple is also capable of simulating the effect of uterine peristalsis on sperm transport during the ovulatory phase. Simulations revealed that frequent cervix-to-fundus peristalsis observed during ovulation in individuals with normal menstrual cycles effectively facilitates sperm movement toward the fallopian tubes, enhancing fertility potential. In contrast, irregular uterine peristalsis, commonly seen during ovulation in patients with gynecological conditions such as endometriosis and fibroids, significantly reduces the percentage of sperm reaching the fallopian tubes. This disruption in sperm transport could partially explain the increased incidence of subfertility or infertility among patients with such conditions. By modeling sperm fluid dynamics during the ovulatory phase, Alya Purple offers a novel approach for assessing uterine peristalsis patterns associated with infertility. Its ability to simulate patient-specific scenarios may support more accurate diagnoses and personalized fertility treatment planning. A promising future application of Alya Purple is assessing the effectiveness of pharmaceutical interventions. By adjusting the electrical behavior of membrane ionic channels, Alya Purple can simulate the effects of various drugs on uterine peristalsis, offering a powerful platform for preclinical testing and treatment optimization. Excitingly, Alya Purple demonstrates potential for developing novel, personalized, non-pharmaceutical therapies. Notably, simulations showed that electrical pacing could normalize retrograde cervix-to-fundus peristalsis during the menses phase in patients with endometriosis. Similar to cardiac and gastric pacemakers, a uterine pacemaker could be designed to restore normal uterine peristalsis and improve gynecological function without relying on pharmaceutical treatments. Moreover, a uterine pacemaker could also potentially prevent sperm transportation toward the fallopian tubes, leading to a novel, non-hormonal contraception strategy based on controlled uterine peristalsis. These potential applications highlight Alya Purple’s potential to advance personalized reproductive health management through both therapeutic and contraceptive innovations. Future research on Alya Purple will focus on incorporating a more anatomically accurate, patient-specific model of the uterus, cervix, and fallopian tubes to enhance simulation accuracy. Future studies will utilize MRE to measure patient-specific mechanical properties of the myometrium and endometrium in both healthy individuals and patients with gynecological conditions such as endometriosis. Integrating these biomechanical properties into Alya Purple’s digital twin framework will enable more realistic simulations and deeper insights into how pathological changes affect electrical, mechanical, and fluid dynamics within the uterus. Additionally, incorporating hormone receptor dynamics and mechanosensitive channels into Alya Purple’s cellular models will significantly expand its simulation capabilities and clinical relevance. Future work will also focus on replicating complex uterine peristalsis patterns imaged by UPI and designing optimized electrical pacing strategies for therapeutic interventions. The digital twin of the nonpregnant human uterus offers a powerful platform to explore the consequences of uterine abnormalities and investigate mechanisms underlying gynecological conditions such as endometriosis. In the long term, Alya Purple could facilitate the development of patient-specific treatment options, advancing personalized care and improving clinical outcomes in reproductive health. Methods The digital twin of the human uterus, Alya Purple, is a patient-specific computation framework for creating a multi-scale (cellular level, tissue level, and organ level), multi-physics (electro-mechanical-fluid coupled) whole uterus simulation of uterine peristalsis using the data collected by the uterine peristalsis imaging (UPI) (Fig. 1 ). A detailed summary of the entire computational solver can be found in the Supplemental Methods section. Briefly, a simplified cellular-level ion channel model is employed for uterine myocytes in Alya purple. The electrical action potential propagation on the 2D tissue and 3D organ (uterus) level is modeled using a modified FitzHugh-Nagumo model. The myometrium fiber orientation derived by diffusion MRI scans included in the UPI process will provide patient-specific 3D architecture. Mechanical deformation and stress are also computed across cellular, tissue, and organ levels in a coupled fashion. The excitation-contraction coupling was modeled across multiple scales in Alya Purple. Following the coupled electrical and mechanical simulation on the organ level, the intra-uterine fluid dynamics was simulated using computational fluid dynamics (CFD), which employs the Navier-Stokes equations for an incompressible flow of a Newtonian fluid on a deformable mesh. The intrauterine fluid dynamics provides insight into the behavior and movement of menstrual blood or sperms following the electrical activation and mechanical deformation during uterine peristalsis. The simulation methodology has been adapted from simulation schemes developed to model the electro-mechanic-fluid behavior of the heart 17–21,27−30 . The Alya Purple software program operates on a Linux system and runs on a hardware platform equipped with dual AMD EPYC 74F3 24-core processors, providing 96 virtual CPUs (vCPUs). The system is configured with 1 TB of memory. Running 1,000 simulation steps requires approximately 24 hours. The inclusion and exclusion criteria for each human subject cohort (normal and endometriosis), the consent process, and demographic, obstetric, and gynecologic history information for enrolled participants are described in detail in Wang et al. 8 , 9 , which was approved by the Washington University Institutional Review Board, and all participants signed informed consent documents. Detailed descriptions of each component of Alya Purple are included in the following sections. Electrophysiology model The electrophysiology model simulates the electrical propagation observed during uterine peristalsis. This model includes two coupled sub-components: the ionic current model on the cellular level and the diffusion of the electrical wave at the tissue level. No established ionic channel model has been described to represent the electromyographic activities generated by ICLCs in the non-pregnant uterus 24 , 25 , 31 . The modified Fitzhugh-Nagumo 32 model includes a fast variable representing the action potential upstroke and a slow variable expressing the recovery rate. Thus, we parameterized this simplified model 32 , 33 to mirror the slow wave observed in the gastrointestinal system 23 . The diffusion at the tissue level was modeled using a monodomain approximation as described previously 27 , 29 , 34 , 35 . The diffusion was defined to reproduce the electrical propagation times observed in the UPI. The initial depolarization locations were the regions observed in the UPI. The diffusion tensor reflects the muscle fiber orientation (discussed in section Geometry and microstructure) in the myometrium and can be derived from diffusion tensor MRI that can be obtained in the clinical setting. The electro-mechanics mesh comprises 1,291,399 tetrahedral elements with a regular side length of approximately 0.6 mm. Electrophysiology and mechanics are tightly coupled and solved in the same mesh at the same resolution. Mechanical model The employed constitutive law for the passive mechanical behavior of ventricular tissue is a nearly, or quasi-, incompressible version of Holzapfel and Ogden 36 using similar material properties of the human myocardium. The material model used in this study has an anisotropic hyperelastic strain energy density function, governed by the fiber structure of the tissue 37 – 41 . This model has been widely used in biomechanical simulations and accurately captures the mechanical behavior of soft tissues 27 – 29 , 34 , 35 , 37 , 39 , 41 , 42 . The endometrium, myometrium, and fallopian tubes were modeled using the same passive material properties 42 – 46 . Only the endometrium was considered capable of producing active tension. Dirichlet boundary conditions were applied to the outlets of the fallopian tubes and the cervix to fix the anatomy in space. The parameters of the Holzapfel and Ogden 36 model were carefully chosen after a sensitivity analysis 28 . Electrical-Mechanical coupling model The electrical excitation-mechanical contraction coupling model developed by Hunter and McCulloch 47 was adopted in this study to define the active stress model in the endometrium. Following a waveform triggered by the electrical activation, active stress is assumed to be produced only in the direction of the muscle fibers and is dependent on the calcium transient in myometrial cells. As calcium plays a crucial role in mechanical force generation, the active tension is triggered by an approximate representation of the intracellular calcium twitch transient waveform as previously published 47 . The zero-crossing of the action potential's upstroke triggers the calcium transient twitch initiation throughout the endometrial tissue. The calcium triggers the active stress via a force-calcium relationship defined as proposed by Hunter 47 , where the peak twitch tension was set as 160 kP to approximate the contractility observed clinically in normal uteri. Computational fluid and particle dynamics and fluid-structure interaction Alya Purple uses computational fluid dynamics (CFD) to simulate the fluid domain inside the uterus. The CFD approach employs the Navier-Stokes equations for an incompressible flow of a Newtonian fluid on a deformable mesh using an arbitrary Lagrangian-Eulerian (ALE) scheme. The electro-mechanic-fluid implementation has been described previously in detail 29 , 48 . The fluid's viscosity was set as 0.0799 (Poise), and the fluid density was set as 1.2599 (g/cm3). The mesh comprises 276,433 regular tetrahedral elements of approximately 0.06 cm in side-length with open outlets at the fallopian tubes and cervix. The fluid domain outlets have a 5-element layer of 10x the fluid's viscosity to smooth out the outflow and prevent numerical instabilities. The ALE approach is essential for modeling the deformation of the mesh 29 , 48 . By applying an ALE scheme, the mesh can deform based on the electro-mechanic activity of the uterus and the motion of the fluid. The incompressible flow assumption is valid for low-speed flow, which is typically the case in physiological processes. The particle transport was simulated in a Lagrangian frame of reference, following each individual particle as previously published in detail 30 , 49 – 51 . The characteristics of the particles simulated were: 1) Particles were sufficiently small, and the suspension was dilute to neglect their effect on flow: i.e. one-way coupling; 2) Particles were spherical and did not interact with each other; 3) The forces considered were dragged on each of the particles; 4) Particles have a zero velocity at t = 0 and the same density of the fluid; 5) At least 1000 particles were injected in each selected location. Geometry and microstructure The uterus geometry used in this study was generated from patient-specific MRI data obtained from a Siemens Vida 3T MRI Scanner. Anatomical MR images performed detailed segmentations of the uterus surface, cervix, uterine cavity, and other components (Fig. 2 A). To address the large pixel size of the segmented MR images and interpolate the gap between each layer, manual smoothing of the uterus anatomy was performed to create a more realistic geometry without sharp edges from discretization aliasing. Subsequently, a tetrahedral mesh (Fig. 2 B) was created on the myometrium of the uterus from the segmented images using ANSA (Beta Cae), with at least four transmural elements to apply boundary conditions onto the exterior muscles. We refined and interpolated diffusion tensor imaging (DTI)-derived data to the meshed uterus geometry to accurately model the myometrium fiber orientation. In this case, DTI was used to determine the general orientation of myometrium fibers in the uterus. We conducted uterus boundary segmentation on the DTI images to reduce errors caused by patient movement during the imaging. Then, we aligned each frame of the MR image by the uterus boundary segmentations and refined the fiber orientations. According to previous studies 52 , we further refined and smoothed the DTI-derived data according to the main direction of each area of the myometrium to model the fiber orientation (Fig. 2 C). Declarations Code availability: The underlying code for this study is not publicly available but may be made available to qualified researchers at a reasonable request from the corresponding authors. Competing interests: The authors declare no competing interests in the work described in this paper. A patent disclosure of the digital twin of nonpregnant human uterus was submitted to Washington University in St. Louis by YW for consideration of patent applications. Funding acquisition: YW, MV Project administration: YW, MV Supervision: YW, MV Writing – original draft: YL, JAS, YN Writing – review & editing: YL, JAS, YN, CB, GH, QW, YW, MV Author Contribution Conceptualization: YW, MVMethodology: YL, JAS, GH, YW, MVInvestigation: YN, SW, CB, ZW, WU, HG, YL, PKW, GH, QW, MV, YWVisualization: YL, JAS, YN, CB, GHFunding acquisition: YW, MVProject administration: YW, MVSupervision: YW, MVWriting – original draft: YL, JAS, YNWriting – review & editing: YL, JAS, YN, CB, GH, QW, YW, MV Acknowledgement We thank Deborah Frank and James Ballard for editing the manuscript. We thank Qiuchang Sun for helping with the manuscript revision. This study was funded by Washington University in St. Louis Startup Fund (to PI Y. Wang). The funder played no role in study design, data collection, analysis and interpretation of data, or the writing of this manuscript. Data Availability The datasets used and analyzed during the current study are available from the corresponding authors on reasonable request. References Georg Kunz and Gerhard Leyendecker. Uterine peristaltic activity during the menstrual cycle: characterization, regulation, function and dysfunction. Reproductive biomedicine online , 4:5–9, 2002. Nienke Petronella Maria Kuijsters, Willem Gerardus Methorst, Madeleine Susanne Quirine Kortenhorst, Chiara Rabotti, Massimo Mischi, and Benedictus Christiaan Schoot. Uterine peristalsis and fertility: current knowledge and future perspectives: a review and meta-analysis. Reproductive biomedicine online , 35(1):50–71, 2017. Ying Zhang, Jingjing Qian, Oren Zaltzhendler, Mustafa Bshara, Ariel J Jaffa, Dan Grisaru, Enkui Duan, and David Elad. Analysis of in vivo uterine peristalsis in the non-pregnant female mouse. Interface Focus , 9(4):20180082, 2019. Carlo Bulletti and Dominique De Ziegler. Uterine contractility and embryo implantation. Current Opinion in Obstetrics and Gynecology , 17(3):265–276, 2005. Carlo Bulletti, Dominique De Ziegler, Valeria Polli, Elena Del Ferro, Simone Palini, and Carlo Flamigni. Characteristics of uterine contractility during menses in women with mild to moderate endometriosis. Fertility and sterility , 77(6):1156–1161, 2002. Carlo Bulletti, Dominique De Ziegker, Stefania Rossi, Valeria Polli, Marc Massoneau, Elisa Rossi, Alessia Albonetti, Valeria Negrini, and Carlo Flamigni. Abnormal uterine contractility in nonpregnant women. Annals of the New York Academy of Sciences , 828(1):223–229, 1997. Alberto Salamanca and Estanislao Beltrán. Subendometrial contractility in menstrual phase visualized by transvaginal sonography in patients with endometriosis. Fertility and sterility , 1(64):193–195, 1995. Sicheng Wang, Kelsey Anderson, Stephanie Pizzella, Haonan Xu, Zichao Wen, Yiqi Lin, Yuan Nan, Josephine Lau, Qing Wang, Valerie Ratts, et al. Noninvasive electrophysiolog- ical imaging identifies 4d uterine peristalsis patterns in subjects with normal menstrual cycles and patients with endometriosis. Research Square , 2023. Sicheng Wang, Kelsey Anderson, Stephanie Pizzella, Haonan Xu, Wenshang Wang, Zichao Wen, Yuan Nan, Josephine Lau, Qing Wang, Valerie Ratts, et al. Noninvasive imaging of 4d electrical activation patterns of uterine peristalsis during normal menstrual cycles. npj Women’s Health , 2(1):1, 2024. Kelsey L Anderson, Sicheng Wang, Stephanie Pizzella, Yong Wang, and Valerie Ratts. Direction and laterality of uterine peristalsis waves during the peri-ovulatory phase. Fertility and Sterility , 120(4):e302, 2023. Kelsey L Anderson, Sicheng Wang, Stephanie Pizzella, Valerie Ratts, and Yong Wang. 3d non-invasive electrophysiology imaging of human uterine peristalsis. Fertility and Sterility , 116(3):e328, 2021. M V´azquez, R Ar´ıs, J Aguado-Sierra, G Houzeaux, A Santiago, M L´opez, P C´ordoba, M Rivero, and JC Cajas. Alya red ccm: Hpc-based cardiac computational modelling. Selected topics of computational and experimental fluid mechanics , pages 189–207. Springer, 2015. Patricio S La Rosa, Hari Eswaran, Hubert Preissl, and Arye Nehorai. Multiscale forward electromagnetic model of uterine contractions during pregnancy. BMC medical physics , 12(1):1–16, 2012. Mengxue Zhang, Vanessa Tidwell, Patricio S La Rosa, James D Wilson, Hari Eswaran, and Arye Nehorai. Modeling magnetomyograms of uterine contractions during pregnancy using a multiscale forward electromagnetic approach. PloS one , 11(3):e0152421, 2016. Yiqi Lin, Mengxue Zhang, Patricio S La Rosa, James D Wilson, and Arye Nehorai. Electro-mechanical ionic channel modeling for uterine contractions and oxytocin effect during pregnancy. Sensors , 19(22):4898, 2019. Maxime Yochum, J´er´emy Laforˆet, and Catherine Marque. Multi-scale and multi-physics model of the uterine smooth muscle with mechanotransduction. Computers in Biology and Medicine , 93:17–30, 2018. Guillaume Houzeaux, Mariano Va´zquez, Romain Aubry, and Jos´e Mar´ıa Cela. A massively parallel fractional step solver for incompressible flows. Journal of Computational Physics , 228(17):6316–6332, 2009. Guillaume Houzeaux, R Aubry, and Mariano V´azquez. Extension of fractional step techniques for incompressible flows: The preconditioned orthomin (1) for the pressure schur complement. Computers & Fluids , 44(1):297–313, 2011. Eva Casoni, Antoine J´erusalem, Crist´obal Samaniego, Beatriz Eguzkitza, Pierre Lafortune, DD Tjahjanto, Xavier S´aez, Guillaume Houzeaux, and Mariano Va´zquez. Alya: computational solid mechanics for supercomputers. Archives of Computational Methods in Engineering , 22:557–576, 2015. Mariano Va´zquez, Ruth Ar´ıs, Guillaume Houzeaux, R Aubry, P Villar, J Garcia-Barn´es, D Gil, and F Carreras. A massively parallel computational electrophysiology model of the heart. International journal for numerical methods in biomedical engineering , 27(12):1911–1929, 2011. M V´azquez, G Houzeaux, S Koric, A Artigues, J Aguado-Sierra, R Aris, D Mira, H Calmet, F Cucchietti, H Owen, et al. Alya: Towards exascale for engineering simulation codes. arxiv. org (2014). Kenton M Sanders. A case for interstitial cells of cajal as pacemakers and mediators of neurotransmission in the gastrointestinal tract. Gastroenterology , 111(2):492–515, 1996. Md Ashfaq Ahmed and Ranu Jung. Modeling of slow waves in the stomach. Encyclopedia of Computational Neuroscience , pages 2064–2072. Springer, 2022. Malgorzata Domino, Bartosz Pawlinski, Magdalena Gajewska, Tomasz Jasinski, Maria Sady, and Zdzislaw Gajewski. Uterine emg activity in the non-pregnant sow during estrous cycle. BMC veterinary research , 14:1–9, 2018. Graham Hutchings, Olivia Williams, D Cretoiu, and Sanda M Ciontea. Myometrial interstitial cells and the coordination of myometrial contractility. Journal of cellular and molecular medicine , 13(10):4268–4282, 2009. Yiqi Lin. Patient-specific multi-scale, multi-physics simulations of human uterine con- tractions and peristalsis during pregnancy and the menstrual cycle. ProQuest Dissertations and Theses , page 99, 2023. Lafortune, Ruth Ar´ıs, Mariano Va´zquez, and Guillaume Houzeaux. Coupled electromechanical model of the heart: parallel finite element formulation. International journal for numerical methods in biomedical engineering , 28(1):72–86, 2012. F Levrero-Florencio, F Margara, E Zacur, A Bueno-Orovio, ZJ Wang, A Santiago, J Aguado-Sierra, G Houzeaux, V Grau, D Kay, et al. Sensitivity analysis of a strongly-coupled human-based electromechanical cardiac model: Effect of mechanical parameters on physiologically relevant biomarkers. Computer methods in applied mechanics and engineering , 361:112762, 2020. Alfonso Santiago, Jazm´ın Aguado-Sierra, Miguel Zavala-Ak´e, Ruben Doste-Beltran, Samuel G´omez, Ruth Ar´ıs, Juan C Cajas, Eva Casoni, and Mariano V´azquez. Fully coupled fluid-electro-mechanical model of the human heart for supercomputers. International journal for numerical methods in biomedical engineering , 34(12):e3140, 2018. Garcia-Gasulla, Marta, Filippo Mantovani, Marc Josep-Fabrego, Beatriz Eguzkitza, and Guillaume Houzeaux. Runtime mechanisms to survive new HPC architectures: a use case in human respiratory simulations. The International Journal of High Performance Computing Applications , 34(1):42-56, 2020. Amy S Garrett, Shawn A Means, Mathias W Roesler, Kiara JW Miller, Leo K Cheng, and Alys R Clark. Modeling and experimental approaches for elucidating multi-scale uterine smooth muscle electro-and mechano-physiology: A review. Frontiers in Physiology , 13, 2022. Jack M Rogers and Andrew D McCulloch. A collocation-galerkin finite element model of cardiac action potential propagation. IEEE Transactions on Biomedical Engineering , 41(8):743–757, 1994. Richard FitzHugh. Impulses and physiological states in theoretical models of nerve membrane. Biophysical journal , 1(6):445–466, 1961. Margara, Francesca, Zhinuo J. Wang, Francesc Levrero-Florencio, Alfonso Santiago, Mariano Vázquez, Alfonso Bueno-Orovio, and Blanca Rodriguez. In-silico human electro-mechanical ventricular modelling and simulation for drug-induced pro-arrhythmia and inotropic risk assessment. Progress in Biophysics and Molecular Biology, 159:58-74, 2021. Wang, Zhinuo J., Alfonso Santiago, Xin Zhou, Lei Wang, Francesca Margara, Francesc Levrero-Florencio, Arka Das et al. Human biventricular electromechanical simulations on the progression of electrocardiographic and mechanical abnormalities in post-myocardial infarction. EP Europace , (Supplement_1):i143-52, 2021. Gerhard A Holzapfel and Ray W Ogden. Constitutive modelling of passive my- ocardium: a structurally based framework for material characterization. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences , 367(1902):3445–3475, 2009. Jay D Humphrey. Continuum biomechanics of soft biological tissues. Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences , 459(2029):3–46, 2003. Humphrey, J. D. Vascular adaptation and mechanical homeostasis at tissue, cellular, and sub-cellular levels. Cell biochemistry and biophysics , 50: 53-78, 2008. Humphrey, J. D. Need for a continuum biochemomechanical theory of soft tissue and cellular growth and remodeling. Biomechanical modelling at the molecular, cellular and tissue levels, pp. 1-82. Vienna: Springer Vienna, 2009. Humphrey, Jay D and Sherry L O’Rourke. An Introduction to Biomechanics. Epilogue, pp. 667-673. Springer, 2015. Cyron, Christian J., John S. Wilson, and Jay D. Humphrey. Constitutive formulations for soft tissue growth and remodeling. Biomechanics of Living Organs , pp. 79-100. Academic Press, 2017. Humphrey, Jay D. Constrained mixture models of soft tissue growth and remodeling–twenty years after. Journal of Elasticity , 145 no. 1: 49-75, 2021. Baek, S., and J. D. Humphrey. Computational modeling of growth and remodeling in biological soft tissues: application to arterial mechanics. Computational modeling in biomechanics , 253-274, 2010. Ateshian, G. A., and J. D. Humphrey. Continuum mixture models of biological growth and remodeling: past successes and future opportunities. Annual review of biomedical engineering , 14 no. 1: 97-111, 2012. Cyron, Christian J., and Jay D. Humphrey. Growth and remodeling of load-bearing biological soft tissues. Meccanica, 52: 645-664, 2017. Rolf-Pissarczyk, Malte, Richard Schussnig, Thomas-Peter Fries, Dominik Fleischmann, John A. Elefteriades, Jay D. Humphrey, and Gerhard A. Holzapfel. Mechanisms of aortic dissection: from pathological changes to experimental and in silico models. Progress in Materials Science , 101363, 2024. Peter J Hunter, Andrew D McCulloch, and HEDJ Ter Keurs. Modelling the mechanical properties of cardiac muscle. Progress in biophysics and molecular biology , 69(2-3):289– 331, 1998. Santiago, Alfonso, Constantine Butakoff, Beatriz Eguzkitza, Richard A. Gray, Karen May-Newman, Pras Pathmanathan, Vi Vu, and Mariano Vázquez. Design and execution of a verification, validation, and uncertainty quantification plan for a numerical model of left ventricular flow after LVAD implantation. PLoS computational biology, 18 no. 6: e1010141, 2022. Prisco, Anthony R., Jazmin Aguado-Sierra, Constantine Butakoff, Mariano Vazquez, Guillaume Houzeaux, Beatriz Eguzkitza, Jason A. Bartos et al. Concomitant respiratory failure can impair myocardial oxygenation in patients with acute cardiogenic shock supported by VA-ECMO. Journal of cardiovascular translational research , 1-10, 2022. Calmet, Hadrien, Kiao Inthavong, Beatriz Eguzkitza, Oriol Lehmkuhl, Guillaume Houzeaux, and Mariano Vázquez. Nasal sprayed particle deposition in a human nasal cavity under different inhalation conditions. PloS one, 14 no. 9: e0221330, 2019. Calmet, Hadrien, Alberto M. Gambaruto, Alister J. Bates, Mariano Vázquez, Guillaume Houzeaux, and Denis J. Doorly. Large-scale CFD simulations of the transitional and turbulent regime for the large human airways during rapid inhalation. Computers in biology and medicine, 69: 166-180, 2016. Stephan Weiss, Thomas Jaermann, Peter Schmid, Philipp Staempfli, Peter Boesiger, Peter Niederer, Rosmarie Caduff, and Michael Bajka. Three-dimensional fiber archi- tecture of the nonpregnant human uterus determined ex vivo using magnetic resonance diffusion tensor imaging. The Anatomical Record Part A: Discoveries in Molecular, Cel- lular, and Evolutionary Biology: An Official Publication of the American Association of Anatomists , 288(1):84–90, 2006. Additional Declarations No competing interests reported. Supplementary Files SupplementaryMethodology04152025.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6505611","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":448931468,"identity":"f5848cfd-538c-41ac-afa3-cec2f55c33bf","order_by":0,"name":"Yiqi Lin","email":"","orcid":"","institution":"Washington University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yiqi","middleName":"","lastName":"Lin","suffix":""},{"id":448931471,"identity":"2b755458-0ba4-4c83-903e-9f2908ea9a06","order_by":1,"name":"Jazmin Aguado-Sierra","email":"","orcid":"","institution":"Barcelona Supercomputing Center","correspondingAuthor":false,"prefix":"","firstName":"Jazmin","middleName":"","lastName":"Aguado-Sierra","suffix":""},{"id":448931472,"identity":"ec2e88d3-27c2-41dc-8c03-b8076d68c16d","order_by":2,"name":"Yuan Nan","email":"","orcid":"","institution":"Washington University in St. Louis","correspondingAuthor":false,"prefix":"","firstName":"Yuan","middleName":"","lastName":"Nan","suffix":""},{"id":448931473,"identity":"3d8483b5-f1fa-4913-9f31-d2c72782593a","order_by":3,"name":"Sicheng Wang","email":"","orcid":"","institution":"Washington University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Sicheng","middleName":"","lastName":"Wang","suffix":""},{"id":448931474,"identity":"e80a3123-e783-4452-ae4e-d55166c7bbbf","order_by":4,"name":"Constantine Butakoff","email":"","orcid":"","institution":"Elem Biotech S.L.","correspondingAuthor":false,"prefix":"","firstName":"Constantine","middleName":"","lastName":"Butakoff","suffix":""},{"id":448931475,"identity":"9b09d21e-ec14-444b-a6d9-ef645e5b7668","order_by":5,"name":"Zichao Wen","email":"","orcid":"","institution":"Washington University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Zichao","middleName":"","lastName":"Wen","suffix":""},{"id":448931476,"identity":"b5ec5204-800b-432b-8f4b-3af93002b8f2","order_by":6,"name":"Wenjie Wu","email":"","orcid":"","institution":"Washington University in St. Louis","correspondingAuthor":false,"prefix":"","firstName":"Wenjie","middleName":"","lastName":"Wu","suffix":""},{"id":448931477,"identity":"46c115de-7a35-43df-9fd0-b4677941d02b","order_by":7,"name":"Hansong Gao","email":"","orcid":"","institution":"Washington University in St. Louis","correspondingAuthor":false,"prefix":"","firstName":"Hansong","middleName":"","lastName":"Gao","suffix":""},{"id":448931478,"identity":"b04f2ce8-14bd-4c05-9098-9a5874fb3f7f","order_by":8,"name":"Josephine Lau","email":"","orcid":"","institution":"Washington University in St. Louis","correspondingAuthor":false,"prefix":"","firstName":"Josephine","middleName":"","lastName":"Lau","suffix":""},{"id":448931479,"identity":"b9c274e6-0782-47cd-8a0f-7cb1a5642a33","order_by":9,"name":"Yuelin Li","email":"","orcid":"","institution":"Washington University in St. Louis","correspondingAuthor":false,"prefix":"","firstName":"Yuelin","middleName":"","lastName":"Li","suffix":""},{"id":448931480,"identity":"47ee8e16-1631-426a-a87c-e42f1a159eff","order_by":10,"name":"Pamela K. Woodard","email":"","orcid":"","institution":"Washington University in St. Louis","correspondingAuthor":false,"prefix":"","firstName":"Pamela","middleName":"K.","lastName":"Woodard","suffix":""},{"id":448931481,"identity":"2b962406-f857-40d6-b19e-a6557af5d892","order_by":11,"name":"Guillaume Houzeaux","email":"","orcid":"","institution":"Barcelona Supercomputing Center","correspondingAuthor":false,"prefix":"","firstName":"Guillaume","middleName":"","lastName":"Houzeaux","suffix":""},{"id":448931482,"identity":"41cb1b6b-170b-4506-a070-9345214365d2","order_by":12,"name":"Qing Wang","email":"","orcid":"","institution":"Washington University in St. Louis","correspondingAuthor":false,"prefix":"","firstName":"Qing","middleName":"","lastName":"Wang","suffix":""},{"id":448931483,"identity":"7ef47627-db27-44fd-9d16-615660958f96","order_by":13,"name":"Mariano Vazquez","email":"","orcid":"","institution":"Barcelona Supercomputing Center","correspondingAuthor":false,"prefix":"","firstName":"Mariano","middleName":"","lastName":"Vazquez","suffix":""},{"id":448931484,"identity":"ce79c917-744f-4c7b-9114-a39dd318337d","order_by":14,"name":"Yong Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIiWNgGAWjYDADfjBZAMQHiNUi2QBSbUCKFoMDxGoxOH728Gueijt2m2/kGH/+YMAgx3cjgYCWM3lp1jxnniVvu5FjJgG0xViSkBazAzlmxrxth5PNbueYgRyWuIGglvNvIFqMZ+cYfwBqqSesBeiFx0AtdgbSOQYghyUYENJif+ONGeOcM4cTJO4/K5M4YyBhOPPMA/xaJPuB7nlTcdiev+fw5g8VFTbyfMcJ2AIEbFI8DAyJDRCOBEHlIMD88QfQgUQpHQWjYBSMgpEJAFfhS/xRinABAAAAAElFTkSuQmCC","orcid":"","institution":"Washington University School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Yong","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2025-04-22 15:08:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6505611/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6505611/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82141920,"identity":"506d1f21-f58e-4f7b-9c57-5883a34069ad","added_by":"auto","created_at":"2025-05-07 06:36:11","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1592414,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSchematic for\u003c/strong\u003e \u003cstrong\u003eDigital Twin of the Human Nonpregnant Uterus: Alya Purple. \u0026nbsp;\u003c/strong\u003eAlya Purple leverages patient-specific uterine anatomy, microstructures, and functional data to construct a virtual digital model of the human nonpregnant uterus through multi-physics and multi-scale simulation. This innovative platform integrates anatomical and physiological details, enabling dynamic simulations of uterine electrical activity, mechanical deformation, and intrauterine fluid dynamics across various menstrual phases.\u003c/p\u003e","description":"","filename":"Figure1New.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6505611/v1/4fdcc95423b52cee04e85fe0.jpg"},{"id":82143956,"identity":"ddc3905a-101f-4ff9-98bb-0ec7575ed8c0","added_by":"auto","created_at":"2025-05-07 06:44:12","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3019251,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNonpregnant\u003c/strong\u003e \u003cstrong\u003euterus geometry and microstructure\u003c/strong\u003e. Nonpregnant uterus geometry and microstructure were displayed in different views. a) Whole uterus segmentation, including the uterine surface, cervix, and myometrium, extracted from Diffusion Tensor Imaging (DTI) data. b) 3D uterus mesh generated from the segmented uterus structure. c) Refined muscle fiber structure visualization: circular fibers in the inner layer (white) and longitudinal fibers in the outer layer (orange). Scale bar added. \u0026nbsp;\u003cem\u003eDTI = Diffusion Tensor Imaging\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure2New.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6505611/v1/a1573acad6c7f3d8d54f6bbc.jpg"},{"id":82141935,"identity":"64d69baa-104d-4985-abb1-0920bca58b57","added_by":"auto","created_at":"2025-05-07 06:36:12","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3925620,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eUPI and Alya Purple simulation of uterine peristalsis during normal menses.\u003c/strong\u003e UPI and Alya Purple simulation of uterine peristalsis and menstrual blood transport during menses in participants with normal menstrual cycles\u003cstrong\u003e. \u003c/strong\u003ea) Comparison between Uterine Peristalsis Imaging (UPI) and Alya Purple simulation of fundus-to-cervix peristalsis. b) Alya Purple simulation of mild retrograde cervix-to-fundus peristalsis. The red band indicates the activation wavefront during uterine peristalsis, while the blue area represents the resting myometrium. The electromechanical simulation results from Alya Purple illustrate six frames of electro-mechanical wave propagation during uterine peristalsis, compared with UPI imaging data. In the fluid dynamics simulation results from Alya Purple, red particles represent menstrual blood originating from the endometrial regions of the uterus. \u003cem\u003eUPI = Uterine Peristalsis Imaging; EM = Electrical-Mechanical;\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure3New.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6505611/v1/2915a58581cdcc3509ee1f41.jpg"},{"id":82139733,"identity":"496f3ad9-fc00-4866-9aaa-0d1b6daab33e","added_by":"auto","created_at":"2025-05-07 06:28:12","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":5131517,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eUPI and Alya Purple simulation of uterine peristalsis during normal ovulation. \u003c/strong\u003eUPI and Alya Purple simulation of uterine peristalsis and sperm transport during the ovulation in patients with normal menstrual cycles.\u003cstrong\u003e \u003c/strong\u003ea) Comparison between Uterine Peristalsis Imaging (UPI) and Alya Purple simulation of cervix-to-fundus peristalsis. b) Alya Purple simulation of irregular peristalses patterns. c) d) Number of sperm reaching the fallopian tubes during representative regular cervix-to-fundus peristalses (left) and irregular lateral peristalses (right). The red band indicates the activation wavefront during uterine peristalsis, while the blue area represents the resting myometrium. Alya Purple's electromechanical results show six frames of electro-mechanical wave propagation during uterine peristalsis, compared to UPI imaging data. In the fluid dynamics simulation, white particles representing sperm are transported from the cervix toward the fallopian tubes. \u003cem\u003eUPI = Uterine Peristalsis Imaging; EM = Electrical-Mechanical;\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure4New.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6505611/v1/54b5310472d2a9be612814d8.jpg"},{"id":82141928,"identity":"e17c024c-8ddc-4eb3-a0d7-9b49f6157470","added_by":"auto","created_at":"2025-05-07 06:36:12","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":3133054,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eUPI and Alya Purple simulation of uterine peristalsis during menses in endometriosis.\u003c/strong\u003e UPI and Alya Purple simulation of uterine peristalsis in the menses phase of patients with endometriosis.\u003cstrong\u003e \u003c/strong\u003ea) Cervix-to-fundus uterine peristalsis recorded by UPI. b) similar peristalsis simulated by Alya Purple. c) Amount of menstrual blood expelled via the fallopian tubes during mild retrograde menstruation in patients with normal menstrual cycles (left) versus strong retrograde menstruation in patients with endometriosis (right). The red band indicates the activation wavefront during uterine peristalsis, while the blue area represents the resting myometrium. Red particles represent menstrual blood, illustrating fluid dynamics during uterine peristalsis. \u003cem\u003eUPI = Uterine Peristalsis Imaging; EM = Electrical-Mechanical;\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure5New.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6505611/v1/d82aa904ba5db87af24ffc38.jpg"},{"id":82141930,"identity":"ee1644ef-459e-4543-9595-d85a1a9ff68e","added_by":"auto","created_at":"2025-05-07 06:36:12","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":2415210,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRetrograde peristalsis normalization by uterine pacing.\u003c/strong\u003e Uterine fundus electrical pacing neutralizes the retrograde cervix-to-fundus peristalsis in patients with endometriosis.\u003cstrong\u003e \u003c/strong\u003eTwo instances of uterine fundus electrical pacing were applied at 2.00 seconds and 11.00 seconds, respectively. The first pacing successfully canceled the retrograde cervix-to-fundus uterine peristalsis, which is associated with retrograde menstruation in patients with endometriosis. The second pacing induced a normal fundus-to-cervix peristalsis, restoring the downward uterine contraction needed to expel menstrual blood vaginally. The red band indicates the activation wavefront during uterine peristalsis, while the blue area represents the resting myometrium. Red particles represent menstrual blood, illustrating fluid dynamics during uterine contraction. \u003cem\u003eUPI = Uterine Peristalsis Imaging; EM = Electrical-Mechanical;\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure6New.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6505611/v1/c0c915b3e0b2349b19c33efb.jpg"},{"id":83312987,"identity":"9dd4f742-70b2-47b1-8a49-9e2723528b90","added_by":"auto","created_at":"2025-05-22 20:46:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":20186051,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6505611/v1/e9390850-9724-4298-a15b-1f84bbc741b3.pdf"},{"id":82139723,"identity":"44b37af0-b01c-4d31-b9d8-df4e3a5f968a","added_by":"auto","created_at":"2025-05-07 06:28:11","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":271440,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMethodology04152025.docx","url":"https://assets-eu.researchsquare.com/files/rs-6505611/v1/dbde7e187d512cdaa4457da8.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Digital Twin of Nonpregnant Human Uterus","fulltext":[{"header":"Introduction","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eUterine peristalsis, characterized by spontaneous mild contractions in the inner layer of the nonpregnant uterus, demonstrates distinct 3D peristalsis patterns during different menstrual phases and plays a central role in maintaining physiological functions such as menstrual blood expulsion and sperm transport\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Disruptions in these patterns are believed to be associated with various gynecological conditions, including infertility, endometriosis, and abnormal uterine bleeding\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. For example, during the menses phase of women with normal menstrual cycle, 65% of waves traveled from the fundus toward the cervix, which may facilitate the vaginal expulsion of the menstrual blood. Frequent or strong cervix-to-fundus peristalsis waves during the menses phase could potentially cause retrograde menstruation and increase the risk of developing endometriosis\u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. In contrast, 75.8% of waves traveled in the opposite direction during normal ovulation, which may promote sperm transport\u003csup\u003e\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. The cervix-to-fundus waves could help move sperm toward the fallopian tubes to promote fertilization in patients with normal menstrual cycles\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, and insufficient cervix-to-fundus peristalsis could contribute to infertility.\u003c/p\u003e \u003cp\u003eRecent development of Uterine Peristalsis Imaging (UPI) has enabled noninvasive imaging of human uterine peristalsis by integrating patient-specific uterine anatomy measured by magnetic resonance imaging (MRI) and multi-channel abdominal electrical activities\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. UPI can map the electrical activity driving uterine peristalsis across the entire 3-dimensional (3D) uterine surface, allowing precise quantification of peristalsis patterns with high spatial and temporal resolution. However, UPI lacks the ability to provide critical information on mechanical deformation and intrauterine fluid dynamics following electrical activation\u0026mdash;key components for understanding the functional outcomes of human uterine peristalsis.\u003c/p\u003e \u003cp\u003eA similar challenge has been well addressed by a multi-physics, multi-scale whole-heart model in Cardiology\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Additionally, in the past decade, electrical-mechanical simulation models for pregnant uteruses have been developed to explore the coupling between electrical activation and mechanical contractions during labor. These models have provided valuable insights into human labor physiology and its management\u003csup\u003e\u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. However, they often rely on simplified spherical geometries and lack the ability to simulate intrauterine fluid dynamics, limiting their applicability to the nonpregnant uterus. Given the significant differences in geometry and functional behavior between the pregnant and nonpregnant uterus, these models cannot be directly adapted for studying uterine peristalsis in nonpregnant individuals.\u003c/p\u003e \u003cp\u003eTo address the unmet need, we developed \u003cem\u003eAlya Purple\u003c/em\u003e, a multi-scale, multi-physics digital twin of the non-pregnant human uterus, to simulate the electrical, mechanical, and fluid dynamics of uterine peristalsis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Herein, a digital twin refers to a virtual replica of a physical object or system that uses real-world data to emulate its behavior. As a patient-specific, high-performance computational platform based on the Alya simulation system\u003csup\u003e\u003cspan additionalcitationids=\"CR18 CR19 CR20\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, Alya Purple integrates anatomical and microstructural information of human nonpregnant uterus obtained through UPI. Alya Purple simulates the peristalsis initiation potentially driven by interstitial Cajal-like cells (ICLCs)\u003csup\u003e\u003cspan additionalcitationids=\"CR23 CR24 CR25\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, electrical propagation, mechanical deformation, and intrauterine fluid dynamics across cellular, tissue, and uterine levels\u003csup\u003e\u003cspan additionalcitationids=\"CR18 CR19 CR20\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Alya Purple can dynamically simulate both physiological and pathological behaviors of the human nonpregnant uterus across different menstrual phases. By integrating patient-specific data and modeling complex interactions between electrical, mechanical, and fluid-dynamic processes, Alya Purple holds great potential to address critical knowledge gaps in uterine physiology and serve as a transformative platform for personalized gynecological care, enabling improved diagnosis, treatment planning, and management of various uterine conditions.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSimulation of uterine peristalsis during menses in participants with normal menstrual cycles\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTo simulate uterine peristalsis waves in patients with a normal menstrual cycle using Alya Purple, the uterine geometry was segmented from the patient\u0026rsquo;s MRI data, and the myometrium fiber structure was refined based on DTI (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The patient\u0026rsquo;s uterine peristalsis patterns imaged by UPI during the menses phase\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e were replicated in Alya Purple\u0026rsquo;s electro-mechanical-fluid simulation by identifying the earliest activation site observed in the UPI data. This site was selected as the initiation point for slow peristaltic wave propagation in the nonpregnant uterine digital twin, enabling accurate reproduction of patient-specific uterine peristalsis dynamics.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eUPI found that the dominant uterine peristalsis during menses in normal menstrual cycles is fundus-to-cervix peristalsis\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA shows a representative fundus-to-cervix uterine peristalsis during the menses phase, as imaged by UPI, alongside the corresponding Alya Purple simulation. The peristalsis wave originates near the fundus and left fallopian tube, propagating toward the cervix. Alya Purple accurately reproduced the electrical activation pattern (red band) observed in the UPI data. More importantly, Alya Purple simulated the resulting mechanical deformation driven by 3D electrical activation through its electro-mechanical coupling mechanism (\u003cb\u003eSection Electrical-Mechanical coupling model\u003c/b\u003e). The subsequent intrauterine menstrual blood flow was computed using fluid dynamics simulation (\u003cb\u003eSection Computational fluid and particle dynamics and fluid-structure interaction\u003c/b\u003e). Multiple groups of red particles representing menstrual blood were placed in the uterine cavity's left, right, and fundus areas for visualization. The simulation demonstrated that the uterine peristalsis waves effectively propelled menstrual blood toward the cervix, facilitating its expulsion from the uterus through the vaginal canal.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eUPI also imaged a small percentage of mild cervix-to-fundus uterine peristalsis during the menses phase in patients with normal menstrual cycles\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Digital twin simulations were conducted to explore how a mild cervix-to-fundus peristalsis wave affects menstrual blood movement during the menses phase. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB presents the simulation results of two consecutive mild cervix-to-fundus peristaltic waves in a patient with a normal menstrual cycle. In the Alya Purple simulation, the first electrical wave initiates near the cervix, triggering corresponding mechanical deformation propagating toward the uterine fundus. During the first peristaltic wave (1.00 seconds to 6.00 seconds in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB), a small amount of menstrual blood is transported toward the upper uterine cavity near the fallopian tube. Following the subsequent peristaltic wave, a small fraction of this menstrual blood near the upper uterine cavity is further propelled into the fallopian tube at 12.00 seconds. These findings suggest that consecutive cervix-to-fundus uterine peristalsis waves can cause mild retrograde menstruation, even in patients with normal menstrual cycles, potentially contributing to menstrual blood movement toward the fallopian tubes.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSimulation of uterine peristalsis during the ovulatory phase in patients with normal menstrual cycles\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eUPI found that the dominant uterine peristalsis during the ovulatory phase in normal menstrual cycles is cervix-to-fundus peristalsis\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Alya Purple was used to replicate cervix-to-fundus uterine peristalsis. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA shows a representative cervix-to-fundus peristalsis wave imaged by UPI. In the digital twin simulation, the uterine peristaltic wave traveled with a speed and pattern consistent with UPI findings. To evaluate the effect of cervix-to-fundus peristalsis on sperm movement, white particles representing sperm were placed near the lower segment of the uterus around the cervix, simulating uterine insemination during intercourse. The Alya Purple simulation demonstrated how sperm were transported from the cervix area toward the left fallopian tube during the peristaltic wave. Quantitative analysis revealed that after three consecutive cervix-to-fundus peristaltic waves, 77.46% of the sperm particles successfully reached the fallopian tube (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC, \u003cb\u003eLeft\u003c/b\u003e), highlighting the critical role of coordinated uterine peristalsis in facilitating sperm transport during the ovulatory phase.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAlya Purple is further employed to simulate irregular uterine peristalsis waves during the ovulatory phase\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Consecutive right-to-left peristalsis waves are simulated using Alya Purple (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). This irregular uterine peristalsis significantly impaired the uterus\u0026rsquo;s ability to transport sperm to the fallopian tubes during the ovulatory phase, potentially reducing the likelihood of successful fertilization. After three right-to-left peristalsis waves, 41.93% of the sperm reached the fallopian tubes nearest the uterus (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC, \u003cb\u003eRight\u003c/b\u003e).\u003c/p\u003e\n\u003ch3\u003eSimulation of uterine peristalsis in the menses phase of patients with endometriosis\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eCompared to women with normal menstrual cycles, UPI found that the dominant uterine peristalsis during the menses phase in patients with endometriosis is frequent, strong cervix-to-fundus peristalsis\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Alya Purple simulation was conducted for a patient with surgically confirmed endometriosis during the menses phase. The patient-specific uterine geometry and myometrium fiber structure were derived from an MRI scan. UPI identified typical cervix-to-fundus peristalsis in this endometriosis patient (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Based on UPI findings, an electrical stimulus was applied to the cervical area of the uterus digital twin. The simulated electrical activation pattern accurately reproduced the peristalsis wave observed in UPI imaging. Following the electrical activation, Alya Purple simulated the resulting mechanical deformation and intrauterine fluid dynamics. The simulation showed that menstrual blood within the uterine cavity, represented by red particles in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, was propelled into both fallopian tubes due to the cervix-to-fundus uterine peristalsis. This finding highlights the potential role of abnormal cervix-to-fundus uterine peristalsis during the menses phase in retrograde menstruation and the subsequent development of endometriosis lesions outside the uterus.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe simulated retrograde menstrual blood flow during menses was quantified and compared between mild cervix-to-fundus peristalsis waves in women with normal menstrual cycles and strong, frequent cervix-to-fundus peristalsis waves in patients with endometriosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). In the simulation, 1000 particles representing menstrual blood were placed in distinct areas of the uterine cavity. After two mild cervix-to-fundus peristalsis waves, 33.34% of the particles reached the fallopian tubes in the patient with a normal menstrual cycle. In contrast, following consecutive, strong cervix-to-fundus peristalsis waves, 70.72% of the particles were propelled into the fallopian tubes in the patient with endometriosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). These results demonstrate a significantly increased retrograde blood flow in endometriosis patients.\u003c/p\u003e \u003cp\u003e \u003cb\u003eModeling the effects of electrical pacing to neutralize the cervix-to-fundus peristalsis wave direction in the menses phases of patients with endometriosis\u003c/b\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eFinally, Alya Purple was employed as a virtual platform to examine the feasibility and efficiency of a nonpharmaceutical intervention to neutralize retrograde menstruation in patients with endometriosis. Similar to the cardiac and gastric pacemakers, a pacing stimulation was delivered to the uterus fundus in a representative endometriosis patient when a strong cervix-to-fundus peristalsis was detected during the menses phase. Specifically, at 2.00 seconds, one second after a peristalsis wave started at the cervix region (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), electrical pacing was applied at the fundus region. Following the fundus stimulus, a slow peristalsis wave was initiated and traveled from the fundus toward the cervix, which collided and neutralized with the cervix-to-fundus peristalsis wave. As a result, the menstrual blood (represented by red particles) remained within the uterus. Following the second fundus pacing signal at 11.00 seconds, another fundus-to-cervix peristalsis wave is initiated by the fundus pacing and moved downwards toward the cervix, which expels the menstrual blood vaginally through the cervix beginning at 13.00 seconds.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn this paper, we developed and presented, Alya Purple, a digital twin of the human nonpregnant uterus, which can conduct an efficient, multi-scale, multi-physical simulation of human uterine peristalsis across the menstrual cycle for women with normal menstrual cycles and patients with endometriosis. Alya Purple can not only precisely reproduce the electrical activation patterns of the uterine peristalsis, but also provide detailed information on resulting mechanical deformation and intrauterine fluid dynamics following uterine peristalsis. This capability enables precise quantification of menstrual blood movement during the menses phase and sperm transport during the ovulatory phase, offering a comprehensive framework for studying uterine physiology and associated gynecological conditions.\u003c/p\u003e \u003cp\u003eAlya Purple revealed that fundus-to-cervix peristalsis, which dominates the menses phase in women with normal menstrual cycles, generates downward uterine mechanical deformation, effectively expelling menstrual blood vaginally. In comparison, weak and infrequent cervix-to-fundus peristalsis during normal menses induces only mild retrograde menstruation, displacing a small fraction of menstrual blood toward the fallopian tubes. In contrast, in patients with surgically confirmed endometriosis, Alya Purple simulations showed strong and frequent cervix-to-fundus peristalsis, generating significant retrograde blood flow toward the fallopian tubes. This mechanism likely contributes to the implantation of endometriosis lesions outside the uterus. These findings suggest that while mild retrograde menstruation occurs in healthy women, its phenotype and clinical outcomes differ significantly from the strong, frequent cervix-to-fundus peristalsis observed in patients with endometriosis. By accurately reproducing the electrical patterns of cervix-to-fundus peristalsis detected by UPI and simulating its mechanical and fluid consequences, Alya Purple can precisely quantify the severity of retrograde blood flow toward the fallopian tubes. This ability enables the phenotyping of retrograde peristalsis and offers a quantitative framework for risk stratification in developing endometriosis. In the long term, Alya Purple holds significant potential for noninvasive, early detection of endometriosis, particularly in adolescent patients.\u003c/p\u003e \u003cp\u003eAlya Purple is also capable of simulating the effect of uterine peristalsis on sperm transport during the ovulatory phase. Simulations revealed that frequent cervix-to-fundus peristalsis observed during ovulation in individuals with normal menstrual cycles effectively facilitates sperm movement toward the fallopian tubes, enhancing fertility potential. In contrast, irregular uterine peristalsis, commonly seen during ovulation in patients with gynecological conditions such as endometriosis and fibroids, significantly reduces the percentage of sperm reaching the fallopian tubes. This disruption in sperm transport could partially explain the increased incidence of subfertility or infertility among patients with such conditions. By modeling sperm fluid dynamics during the ovulatory phase, Alya Purple offers a novel approach for assessing uterine peristalsis patterns associated with infertility. Its ability to simulate patient-specific scenarios may support more accurate diagnoses and personalized fertility treatment planning.\u003c/p\u003e \u003cp\u003eA promising future application of Alya Purple is assessing the effectiveness of pharmaceutical interventions. By adjusting the electrical behavior of membrane ionic channels, Alya Purple can simulate the effects of various drugs on uterine peristalsis, offering a powerful platform for preclinical testing and treatment optimization. Excitingly, Alya Purple demonstrates potential for developing novel, personalized, non-pharmaceutical therapies. Notably, simulations showed that electrical pacing could normalize retrograde cervix-to-fundus peristalsis during the menses phase in patients with endometriosis. Similar to cardiac and gastric pacemakers, a uterine pacemaker could be designed to restore normal uterine peristalsis and improve gynecological function without relying on pharmaceutical treatments. Moreover, a uterine pacemaker could also potentially prevent sperm transportation toward the fallopian tubes, leading to a novel, non-hormonal contraception strategy based on controlled uterine peristalsis. These potential applications highlight Alya Purple\u0026rsquo;s potential to advance personalized reproductive health management through both therapeutic and contraceptive innovations.\u003c/p\u003e \u003cp\u003eFuture research on Alya Purple will focus on incorporating a more anatomically accurate, patient-specific model of the uterus, cervix, and fallopian tubes to enhance simulation accuracy. Future studies will utilize MRE to measure patient-specific mechanical properties of the myometrium and endometrium in both healthy individuals and patients with gynecological conditions such as endometriosis. Integrating these biomechanical properties into Alya Purple\u0026rsquo;s digital twin framework will enable more realistic simulations and deeper insights into how pathological changes affect electrical, mechanical, and fluid dynamics within the uterus. Additionally, incorporating hormone receptor dynamics and mechanosensitive channels into Alya Purple\u0026rsquo;s cellular models will significantly expand its simulation capabilities and clinical relevance. Future work will also focus on replicating complex uterine peristalsis patterns imaged by UPI and designing optimized electrical pacing strategies for therapeutic interventions. The digital twin of the nonpregnant human uterus offers a powerful platform to explore the consequences of uterine abnormalities and investigate mechanisms underlying gynecological conditions such as endometriosis. In the long term, Alya Purple could facilitate the development of patient-specific treatment options, advancing personalized care and improving clinical outcomes in reproductive health.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe digital twin of the human uterus, Alya Purple, is a patient-specific computation framework for creating a multi-scale (cellular level, tissue level, and organ level), multi-physics (electro-mechanical-fluid coupled) whole uterus simulation of uterine peristalsis using the data collected by the uterine peristalsis imaging (UPI) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). A detailed summary of the entire computational solver can be found in the Supplemental Methods section. Briefly, a simplified cellular-level ion channel model is employed for uterine myocytes in Alya purple. The electrical action potential propagation on the 2D tissue and 3D organ (uterus) level is modeled using a modified FitzHugh-Nagumo model. The myometrium fiber orientation derived by diffusion MRI scans included in the UPI process will provide patient-specific 3D architecture. Mechanical deformation and stress are also computed across cellular, tissue, and organ levels in a coupled fashion. The excitation-contraction coupling was modeled across multiple scales in Alya Purple. Following the coupled electrical and mechanical simulation on the organ level, the intra-uterine fluid dynamics was simulated using computational fluid dynamics (CFD), which employs the Navier-Stokes equations for an incompressible flow of a Newtonian fluid on a deformable mesh. The intrauterine fluid dynamics provides insight into the behavior and movement of menstrual blood or sperms following the electrical activation and mechanical deformation during uterine peristalsis. The simulation methodology has been adapted from simulation schemes developed to model the electro-mechanic-fluid behavior of the heart\u003csup\u003e17\u0026ndash;21,27\u0026minus;30\u003c/sup\u003e. The Alya Purple software program operates on a Linux system and runs on a hardware platform equipped with dual AMD EPYC 74F3 24-core processors, providing 96 virtual CPUs (vCPUs). The system is configured with 1 TB of memory. Running 1,000 simulation steps requires approximately 24 hours.\u003c/p\u003e\u003cp\u003eThe inclusion and exclusion criteria for each human subject cohort (normal and endometriosis), the consent process, and demographic, obstetric, and gynecologic history information for enrolled participants are described in detail in Wang et al.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, which was approved by the Washington University Institutional Review Board, and all participants signed informed consent documents. Detailed descriptions of each component of Alya Purple are included in the following sections.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eElectrophysiology model\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe electrophysiology model simulates the electrical propagation observed during uterine peristalsis. This model includes two coupled sub-components: the ionic current model on the cellular level and the diffusion of the electrical wave at the tissue level.\u003c/p\u003e \u003cp\u003eNo established ionic channel model has been described to represent the electromyographic activities generated by ICLCs in the non-pregnant uterus\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. The modified Fitzhugh-Nagumo\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e model includes a fast variable representing the action potential upstroke and a slow variable expressing the recovery rate. Thus, we parameterized this simplified model\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e to mirror the slow wave observed in the gastrointestinal system\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. The diffusion at the tissue level was modeled using a monodomain approximation as described previously\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. The diffusion was defined to reproduce the electrical propagation times observed in the UPI. The initial depolarization locations were the regions observed in the UPI. The diffusion tensor reflects the muscle fiber orientation (discussed in section Geometry and microstructure) in the myometrium and can be derived from diffusion tensor MRI that can be obtained in the clinical setting. The electro-mechanics mesh comprises 1,291,399 tetrahedral elements with a regular side length of approximately 0.6 mm. Electrophysiology and mechanics are tightly coupled and solved in the same mesh at the same resolution.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMechanical model\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe employed constitutive law for the passive mechanical behavior of ventricular tissue is a nearly, or quasi-, incompressible version of Holzapfel and Ogden\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e using similar material properties of the human myocardium. The material model used in this study has an anisotropic hyperelastic strain energy density function, governed by the fiber structure of the tissue\u003csup\u003e\u003cspan additionalcitationids=\"CR38 CR39 CR40\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. This model has been widely used in biomechanical simulations and accurately captures the mechanical behavior of soft tissues\u003csup\u003e\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e,\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. The endometrium, myometrium, and fallopian tubes were modeled using the same passive material properties\u003csup\u003e\u003cspan additionalcitationids=\"CR43 CR44 CR45\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. Only the endometrium was considered capable of producing active tension. Dirichlet boundary conditions were applied to the outlets of the fallopian tubes and the cervix to fix the anatomy in space. The parameters of the Holzapfel and Ogden\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e model were carefully chosen after a sensitivity analysis\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eElectrical-Mechanical coupling model\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe electrical excitation-mechanical contraction coupling model developed by Hunter and McCulloch\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e was adopted in this study to define the active stress model in the endometrium. Following a waveform triggered by the electrical activation, active stress is assumed to be produced only in the direction of the muscle fibers and is dependent on the calcium transient in myometrial cells. As calcium plays a crucial role in mechanical force generation, the active tension is triggered by an approximate representation of the intracellular calcium twitch transient waveform as previously published\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. The zero-crossing of the action potential's upstroke triggers the calcium transient twitch initiation throughout the endometrial tissue. The calcium triggers the active stress via a force-calcium relationship defined as proposed by Hunter\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e, where the peak twitch tension was set as 160 kP to approximate the contractility observed clinically in normal uteri.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eComputational fluid and particle dynamics and fluid-structure interaction\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAlya Purple uses computational fluid dynamics (CFD) to simulate the fluid domain inside the uterus. The CFD approach employs the Navier-Stokes equations for an incompressible flow of a Newtonian fluid on a deformable mesh using an arbitrary Lagrangian-Eulerian (ALE) scheme. The electro-mechanic-fluid implementation has been described previously in detail\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. The fluid's viscosity was set as 0.0799 (Poise), and the fluid density was set as 1.2599 (g/cm3). The mesh comprises 276,433 regular tetrahedral elements of approximately 0.06 cm in side-length with open outlets at the fallopian tubes and cervix. The fluid domain outlets have a 5-element layer of 10x the fluid's viscosity to smooth out the outflow and prevent numerical instabilities.\u003c/p\u003e \u003cp\u003eThe ALE approach is essential for modeling the deformation of the mesh\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. By applying an ALE scheme, the mesh can deform based on the electro-mechanic activity of the uterus and the motion of the fluid. The incompressible flow assumption is valid for low-speed flow, which is typically the case in physiological processes.\u003c/p\u003e \u003cp\u003eThe particle transport was simulated in a Lagrangian frame of reference, following each individual particle as previously published in detail\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan additionalcitationids=\"CR50\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. The characteristics of the particles simulated were: 1) Particles were sufficiently small, and the suspension was dilute to neglect their effect on flow: i.e. one-way coupling; 2) Particles were spherical and did not interact with each other; 3) The forces considered were dragged on each of the particles; 4) Particles have a zero velocity at t\u0026thinsp;=\u0026thinsp;0 and the same density of the fluid; 5) At least 1000 particles were injected in each selected location.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eGeometry and microstructure\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe uterus geometry used in this study was generated from patient-specific MRI data obtained from a Siemens Vida 3T MRI Scanner. Anatomical MR images performed detailed segmentations of the uterus surface, cervix, uterine cavity, and other components (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). To address the large pixel size of the segmented MR images and interpolate the gap between each layer, manual smoothing of the uterus anatomy was performed to create a more realistic geometry without sharp edges from discretization aliasing. Subsequently, a tetrahedral mesh (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB) was created on the myometrium of the uterus from the segmented images using ANSA (Beta Cae), with at least four transmural elements to apply boundary conditions onto the exterior muscles.\u003c/p\u003e \u003cp\u003eWe refined and interpolated diffusion tensor imaging (DTI)-derived data to the meshed uterus geometry to accurately model the myometrium fiber orientation. In this case, DTI was used to determine the general orientation of myometrium fibers in the uterus. We conducted uterus boundary segmentation on the DTI images to reduce errors caused by patient movement during the imaging. Then, we aligned each frame of the MR image by the uterus boundary segmentations and refined the fiber orientations. According to previous studies\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e, we further refined and smoothed the DTI-derived data according to the main direction of each area of the myometrium to model the fiber orientation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCode availability:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe underlying code for this study is not publicly available but may be made available to qualified researchers at a reasonable request from the corresponding authors.\u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests:\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests in the work described in this paper. A patent disclosure of the digital twin of nonpregnant human uterus was submitted to Washington University in St. Louis by YW for consideration of patent applications.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eacquisition: YW, MV\u003c/p\u003e \u003cp\u003eProject administration: YW, MV\u003c/p\u003e \u003cp\u003eSupervision: YW, MV\u003c/p\u003e \u003cp\u003eWriting \u0026ndash; original draft: YL, JAS, YN\u003c/p\u003e \u003cp\u003eWriting \u0026ndash; review \u0026amp; editing: YL, JAS, YN, CB, GH, QW, YW, MV\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization: YW, MVMethodology: YL, JAS, GH, YW, MVInvestigation: YN, SW, CB, ZW, WU, HG, YL, PKW, GH, QW, MV, YWVisualization: YL, JAS, YN, CB, GHFunding acquisition: YW, MVProject administration: YW, MVSupervision: YW, MVWriting \u0026ndash; original draft: YL, JAS, YNWriting \u0026ndash; review \u0026amp; editing: YL, JAS, YN, CB, GH, QW, YW, MV\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe thank Deborah Frank and James Ballard for editing the manuscript. We thank Qiuchang Sun for helping with the manuscript revision. This study was funded by Washington University in St. Louis Startup Fund (to PI Y. Wang). The funder played no role in study design, data collection, analysis and interpretation of data, or the writing of this manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and analyzed during the current study are available from the corresponding authors on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGeorg Kunz and Gerhard Leyendecker. Uterine peristaltic activity during the menstrual cycle: characterization, regulation, function and dysfunction. \u003cem\u003eReproductive biomedicine online\u003c/em\u003e, 4:5\u0026ndash;9, 2002.\u003c/li\u003e\n\u003cli\u003eNienke Petronella Maria Kuijsters, Willem Gerardus Methorst, Madeleine Susanne Quirine Kortenhorst, Chiara Rabotti, Massimo Mischi, and Benedictus Christiaan Schoot. Uterine peristalsis and fertility: current knowledge and future perspectives: a review and meta-analysis. \u003cem\u003eReproductive biomedicine online\u003c/em\u003e, 35(1):50\u0026ndash;71, 2017.\u003c/li\u003e\n\u003cli\u003eYing Zhang, Jingjing Qian, Oren Zaltzhendler, Mustafa Bshara, Ariel J Jaffa, Dan Grisaru, Enkui Duan, and David Elad. Analysis of in vivo uterine peristalsis in the non-pregnant female mouse. \u003cem\u003eInterface Focus\u003c/em\u003e, 9(4):20180082, 2019.\u003c/li\u003e\n\u003cli\u003eCarlo Bulletti and Dominique De Ziegler. Uterine contractility and embryo implantation. \u003cem\u003eCurrent Opinion in Obstetrics and Gynecology\u003c/em\u003e, 17(3):265\u0026ndash;276, 2005. \u003c/li\u003e\n\u003cli\u003eCarlo Bulletti, Dominique De Ziegler, Valeria Polli, Elena Del Ferro, Simone Palini, and Carlo Flamigni. Characteristics of uterine contractility during menses in women with mild to moderate endometriosis. \u003cem\u003eFertility and sterility\u003c/em\u003e, 77(6):1156\u0026ndash;1161, 2002.\u003c/li\u003e\n\u003cli\u003eCarlo Bulletti, Dominique De Ziegker, Stefania Rossi, Valeria Polli, Marc Massoneau, Elisa Rossi, Alessia Albonetti, Valeria Negrini, and Carlo Flamigni. Abnormal uterine contractility in nonpregnant women. \u003cem\u003eAnnals of the New York Academy of Sciences\u003c/em\u003e, 828(1):223\u0026ndash;229, 1997.\u003c/li\u003e\n\u003cli\u003eAlberto Salamanca and Estanislao Beltr\u0026aacute;n. Subendometrial contractility in menstrual phase visualized by transvaginal sonography in patients with endometriosis. \u003cem\u003eFertility and sterility\u003c/em\u003e, 1(64):193\u0026ndash;195, 1995.\u003c/li\u003e\n\u003cli\u003eSicheng Wang, Kelsey Anderson, Stephanie Pizzella, Haonan Xu, Zichao Wen, Yiqi Lin, Yuan Nan, Josephine Lau, Qing Wang, Valerie Ratts, et al. Noninvasive electrophysiolog- ical imaging identifies 4d uterine peristalsis patterns in subjects with normal menstrual cycles and patients with endometriosis. \u003cem\u003eResearch Square\u003c/em\u003e, 2023.\u003c/li\u003e\n\u003cli\u003eSicheng Wang, Kelsey Anderson, Stephanie Pizzella, Haonan Xu, Wenshang Wang, Zichao Wen, Yuan Nan, Josephine Lau, Qing Wang, Valerie Ratts, et al. Noninvasive imaging of 4d electrical activation patterns of uterine peristalsis during normal menstrual cycles. \u003cem\u003enpj Women\u0026rsquo;s Health\u003c/em\u003e, 2(1):1, 2024.\u003c/li\u003e\n\u003cli\u003eKelsey L Anderson, Sicheng Wang, Stephanie Pizzella, Yong Wang, and Valerie Ratts. Direction and laterality of uterine peristalsis waves during the peri-ovulatory phase. \u003cem\u003eFertility and Sterility\u003c/em\u003e, 120(4):e302, 2023.\u003c/li\u003e\n\u003cli\u003eKelsey L Anderson, Sicheng Wang, Stephanie Pizzella, Valerie Ratts, and Yong Wang. 3d non-invasive electrophysiology imaging of human uterine peristalsis. \u003cem\u003eFertility and Sterility\u003c/em\u003e, 116(3):e328, 2021.\u003c/li\u003e\n\u003cli\u003eM V\u0026acute;azquez, R Ar\u0026acute;ıs, J Aguado-Sierra, G Houzeaux, A Santiago, M L\u0026acute;opez, P C\u0026acute;ordoba, M Rivero, and JC Cajas. Alya red ccm: Hpc-based cardiac computational modelling. \u003cem\u003eSelected topics of computational and experimental fluid mechanics\u003c/em\u003e, pages 189\u0026ndash;207. Springer, 2015.\u003c/li\u003e\n\u003cli\u003ePatricio S La Rosa, Hari Eswaran, Hubert Preissl, and Arye Nehorai. Multiscale forward electromagnetic model of uterine contractions during pregnancy. \u003cem\u003eBMC medical physics\u003c/em\u003e, 12(1):1\u0026ndash;16, 2012.\u003c/li\u003e\n\u003cli\u003eMengxue Zhang, Vanessa Tidwell, Patricio S La Rosa, James D Wilson, Hari Eswaran, and Arye Nehorai. Modeling magnetomyograms of uterine contractions during pregnancy using a multiscale forward electromagnetic approach. \u003cem\u003ePloS one\u003c/em\u003e, 11(3):e0152421, 2016.\u003c/li\u003e\n\u003cli\u003eYiqi Lin, Mengxue Zhang, Patricio S La Rosa, James D Wilson, and Arye Nehorai. Electro-mechanical ionic channel modeling for uterine contractions and oxytocin effect during pregnancy. \u003cem\u003eSensors\u003c/em\u003e, 19(22):4898, 2019.\u003c/li\u003e\n\u003cli\u003eMaxime Yochum, J\u0026acute;er\u0026acute;emy Lafor\u0026circ;et, and Catherine Marque. Multi-scale and multi-physics model of the uterine smooth muscle with mechanotransduction. \u003cem\u003eComputers in Biology and Medicine\u003c/em\u003e, 93:17\u0026ndash;30, 2018.\u003c/li\u003e\n\u003cli\u003eGuillaume Houzeaux, Mariano Va\u0026acute;zquez, Romain Aubry, and Jos\u0026acute;e Mar\u0026acute;ıa Cela. A massively parallel fractional step solver for incompressible flows. \u003cem\u003eJournal of Computational Physics\u003c/em\u003e, 228(17):6316\u0026ndash;6332, 2009.\u003c/li\u003e\n\u003cli\u003eGuillaume Houzeaux, R Aubry, and Mariano V\u0026acute;azquez. Extension of fractional step techniques for incompressible flows: The preconditioned orthomin (1) for the pressure schur complement. \u003cem\u003eComputers \u0026amp; Fluids\u003c/em\u003e, 44(1):297\u0026ndash;313, 2011.\u003c/li\u003e\n\u003cli\u003eEva Casoni, Antoine J\u0026acute;erusalem, Crist\u0026acute;obal Samaniego, Beatriz Eguzkitza, Pierre Lafortune, DD Tjahjanto, Xavier S\u0026acute;aez, Guillaume Houzeaux, and Mariano Va\u0026acute;zquez. Alya: computational solid mechanics for supercomputers. \u003cem\u003eArchives of Computational Methods in Engineering\u003c/em\u003e, 22:557\u0026ndash;576, 2015.\u003c/li\u003e\n\u003cli\u003eMariano Va\u0026acute;zquez, Ruth Ar\u0026acute;ıs, Guillaume Houzeaux, R Aubry, P Villar, J Garcia-Barn\u0026acute;es, D Gil, and F Carreras. A massively parallel computational electrophysiology model of the heart. \u003cem\u003eInternational journal for numerical methods in biomedical engineering\u003c/em\u003e, 27(12):1911\u0026ndash;1929, 2011.\u003c/li\u003e\n\u003cli\u003eM V\u0026acute;azquez, G Houzeaux, S Koric, A Artigues, J Aguado-Sierra, R Aris, D Mira, H Calmet, F Cucchietti, H Owen, et al. Alya: Towards exascale for engineering simulation codes. \u003cem\u003earxiv. org\u003c/em\u003e (2014).\u003c/li\u003e\n\u003cli\u003eKenton M Sanders. A case for interstitial cells of cajal as pacemakers and mediators of neurotransmission in the gastrointestinal tract. \u003cem\u003eGastroenterology\u003c/em\u003e, 111(2):492\u0026ndash;515, 1996.\u003c/li\u003e\n\u003cli\u003eMd Ashfaq Ahmed and Ranu Jung. Modeling of slow waves in the stomach. \u003cem\u003eEncyclopedia of Computational Neuroscience\u003c/em\u003e, pages 2064\u0026ndash;2072. Springer, 2022.\u003c/li\u003e\n\u003cli\u003eMalgorzata Domino, Bartosz Pawlinski, Magdalena Gajewska, Tomasz Jasinski, Maria Sady, and Zdzislaw Gajewski. Uterine emg activity in the non-pregnant sow during estrous cycle. \u003cem\u003eBMC veterinary research\u003c/em\u003e, 14:1\u0026ndash;9, 2018.\u003c/li\u003e\n\u003cli\u003eGraham Hutchings, Olivia Williams, D Cretoiu, and Sanda M Ciontea. Myometrial interstitial cells and the coordination of myometrial contractility. \u003cem\u003eJournal of cellular and molecular medicine\u003c/em\u003e, 13(10):4268\u0026ndash;4282, 2009.\u003c/li\u003e\n\u003cli\u003eYiqi Lin. Patient-specific multi-scale, multi-physics simulations of human uterine con- tractions and peristalsis during pregnancy and the menstrual cycle. \u003cem\u003eProQuest Dissertations and Theses\u003c/em\u003e, page 99, 2023.\u003c/li\u003e\n\u003cli\u003eLafortune, Ruth Ar\u0026acute;ıs, Mariano Va\u0026acute;zquez, and Guillaume Houzeaux. Coupled electromechanical model of the heart: parallel finite element formulation. \u003cem\u003eInternational journal for numerical methods in biomedical engineering\u003c/em\u003e, 28(1):72\u0026ndash;86, 2012.\u003c/li\u003e\n\u003cli\u003eF Levrero-Florencio, F Margara, E Zacur, A Bueno-Orovio, ZJ Wang, A Santiago, J Aguado-Sierra, G Houzeaux, V Grau, D Kay, et al. Sensitivity analysis of a strongly-coupled human-based electromechanical cardiac model: Effect of mechanical parameters on physiologically relevant biomarkers. \u003cem\u003eComputer methods in applied mechanics and engineering\u003c/em\u003e, 361:112762, 2020.\u003c/li\u003e\n\u003cli\u003eAlfonso Santiago, Jazm\u0026acute;ın Aguado-Sierra, Miguel Zavala-Ak\u0026acute;e, Ruben Doste-Beltran, Samuel G\u0026acute;omez, Ruth Ar\u0026acute;ıs, Juan C Cajas, Eva Casoni, and Mariano V\u0026acute;azquez. Fully coupled fluid-electro-mechanical model of the human heart for supercomputers. \u003cem\u003eInternational journal for numerical methods in biomedical engineering\u003c/em\u003e, 34(12):e3140, 2018.\u003c/li\u003e\n\u003cli\u003eGarcia-Gasulla, Marta, Filippo Mantovani, Marc Josep-Fabrego, Beatriz Eguzkitza, and Guillaume Houzeaux. Runtime mechanisms to survive new HPC architectures: a use case in human respiratory simulations. \u003cem\u003eThe International Journal of High Performance Computing Applications\u003c/em\u003e, 34(1):42-56, 2020.\u003c/li\u003e\n\u003cli\u003eAmy S Garrett, Shawn A Means, Mathias W Roesler, Kiara JW Miller, Leo K Cheng, and Alys R Clark. Modeling and experimental approaches for elucidating multi-scale uterine smooth muscle electro-and mechano-physiology: A review. \u003cem\u003eFrontiers in Physiology\u003c/em\u003e, 13, 2022.\u003c/li\u003e\n\u003cli\u003eJack M Rogers and Andrew D McCulloch. A collocation-galerkin finite element model of cardiac action potential propagation. \u003cem\u003eIEEE Transactions on Biomedical Engineering\u003c/em\u003e, 41(8):743\u0026ndash;757, 1994.\u003c/li\u003e\n\u003cli\u003eRichard FitzHugh. Impulses and physiological states in theoretical models of nerve membrane. \u003cem\u003eBiophysical journal\u003c/em\u003e, 1(6):445\u0026ndash;466, 1961.\u003c/li\u003e\n\u003cli\u003eMargara, Francesca, Zhinuo J. Wang, Francesc Levrero-Florencio, Alfonso Santiago, Mariano V\u0026aacute;zquez, Alfonso Bueno-Orovio, and Blanca Rodriguez. In-silico human electro-mechanical ventricular modelling and simulation for drug-induced pro-arrhythmia and inotropic risk assessment. \u003cem\u003eProgress in Biophysics and Molecular Biology, \u003c/em\u003e159:58-74, 2021.\u003c/li\u003e\n\u003cli\u003eWang, Zhinuo J., Alfonso Santiago, Xin Zhou, Lei Wang, Francesca Margara, Francesc Levrero-Florencio, Arka Das et al. Human biventricular electromechanical simulations on the progression of electrocardiographic and mechanical abnormalities in post-myocardial infarction. \u003cem\u003eEP Europace\u003c/em\u003e, (Supplement_1):i143-52, 2021.\u003c/li\u003e\n\u003cli\u003eGerhard A Holzapfel and Ray W Ogden. Constitutive modelling of passive my- ocardium: a structurally based framework for material characterization. \u003cem\u003ePhilosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences\u003c/em\u003e, 367(1902):3445\u0026ndash;3475, 2009.\u003c/li\u003e\n\u003cli\u003eJay D Humphrey. Continuum biomechanics of soft biological tissues. \u003cem\u003eProceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences\u003c/em\u003e, 459(2029):3\u0026ndash;46, 2003.\u003c/li\u003e\n\u003cli\u003eHumphrey, J. D. Vascular adaptation and mechanical homeostasis at tissue, cellular, and sub-cellular levels. \u003cem\u003eCell biochemistry and biophysics\u003c/em\u003e, 50: 53-78, 2008. \u003c/li\u003e\n\u003cli\u003eHumphrey, J. D. Need for a continuum biochemomechanical theory of soft tissue and cellular growth and remodeling. \u003cem\u003eBiomechanical modelling at the molecular, cellular and tissue levels,\u003c/em\u003e pp. 1-82. Vienna: Springer Vienna, 2009. \u003c/li\u003e\n\u003cli\u003eHumphrey, Jay D and Sherry L O\u0026rsquo;Rourke. An Introduction to Biomechanics. \u003cem\u003eEpilogue,\u003c/em\u003e pp. 667-673. Springer, 2015.\u003c/li\u003e\n\u003cli\u003eCyron, Christian J., John S. Wilson, and Jay D. Humphrey. Constitutive formulations for soft tissue growth and remodeling. \u003cem\u003eBiomechanics of Living Organs\u003c/em\u003e, pp. 79-100. Academic Press, 2017. \u003c/li\u003e\n\u003cli\u003eHumphrey, Jay D. Constrained mixture models of soft tissue growth and remodeling\u0026ndash;twenty years after. \u003cem\u003eJournal of Elasticity\u003c/em\u003e, 145 no. 1: 49-75, 2021.\u003c/li\u003e\n\u003cli\u003eBaek, S., and J. D. Humphrey. Computational modeling of growth and remodeling in biological soft tissues: application to arterial mechanics. \u003cem\u003eComputational modeling in biomechanics\u003c/em\u003e, 253-274, 2010.\u003c/li\u003e\n\u003cli\u003eAteshian, G. A., and J. D. Humphrey. Continuum mixture models of biological growth and remodeling: past successes and future opportunities. \u003cem\u003eAnnual review of biomedical engineering\u003c/em\u003e, 14 no. 1: 97-111, 2012.\u003c/li\u003e\n\u003cli\u003eCyron, Christian J., and Jay D. Humphrey. Growth and remodeling of load-bearing biological soft tissues. \u003cem\u003eMeccanica, \u003c/em\u003e52: 645-664, 2017.\u003c/li\u003e\n\u003cli\u003eRolf-Pissarczyk, Malte, Richard Schussnig, Thomas-Peter Fries, Dominik Fleischmann, John A. Elefteriades, Jay D. Humphrey, and Gerhard A. Holzapfel. Mechanisms of aortic dissection: from pathological changes to experimental and in silico models. \u003cem\u003eProgress in Materials Science\u003c/em\u003e, 101363, 2024.\u003c/li\u003e\n\u003cli\u003ePeter J Hunter, Andrew D McCulloch, and HEDJ Ter Keurs. Modelling the mechanical properties of cardiac muscle. \u003cem\u003eProgress in biophysics and molecular biology\u003c/em\u003e, 69(2-3):289\u0026ndash; 331, 1998.\u003c/li\u003e\n\u003cli\u003eSantiago, Alfonso, Constantine Butakoff, Beatriz Eguzkitza, Richard A. Gray, Karen May-Newman, Pras Pathmanathan, Vi Vu, and Mariano V\u0026aacute;zquez. Design and execution of a verification, validation, and uncertainty quantification plan for a numerical model of left ventricular flow after LVAD implantation. \u003cem\u003ePLoS computational biology,\u003c/em\u003e 18 no. 6: e1010141, 2022. \u003c/li\u003e\n\u003cli\u003ePrisco, Anthony R., Jazmin Aguado-Sierra, Constantine Butakoff, Mariano Vazquez, Guillaume Houzeaux, Beatriz Eguzkitza, Jason A. Bartos et al. Concomitant respiratory failure can impair myocardial oxygenation in patients with acute cardiogenic shock supported by VA-ECMO. \u003cem\u003eJournal of cardiovascular translational research\u003c/em\u003e, 1-10, 2022.\u003c/li\u003e\n\u003cli\u003eCalmet, Hadrien, Kiao Inthavong, Beatriz Eguzkitza, Oriol Lehmkuhl, Guillaume Houzeaux, and Mariano V\u0026aacute;zquez. Nasal sprayed particle deposition in a human nasal cavity under different inhalation conditions. \u003cem\u003ePloS one,\u003c/em\u003e 14 no. 9: e0221330, 2019.\u003c/li\u003e\n\u003cli\u003eCalmet, Hadrien, Alberto M. Gambaruto, Alister J. Bates, Mariano V\u0026aacute;zquez, Guillaume Houzeaux, and Denis J. Doorly. Large-scale CFD simulations of the transitional and turbulent regime for the large human airways during rapid inhalation. \u003cem\u003eComputers in biology and medicine,\u003c/em\u003e 69: 166-180, 2016.\u003c/li\u003e\n\u003cli\u003eStephan Weiss, Thomas Jaermann, Peter Schmid, Philipp Staempfli, Peter Boesiger, Peter Niederer, Rosmarie Caduff, and Michael Bajka. Three-dimensional fiber archi- tecture of the nonpregnant human uterus determined ex vivo using magnetic resonance diffusion tensor imaging. \u003cem\u003eThe Anatomical Record Part A: Discoveries in Molecular, Cel- lular, and Evolutionary Biology: An Official Publication of the American Association of Anatomists\u003c/em\u003e, 288(1):84\u0026ndash;90, 2006.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6505611/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6505611/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eUterine peristalsis involves spontaneous, mild contractions of the sub-endometrial layer in the nonpregnant uterus, playing a crucial role in menstruation and fertility. Disruptions in peristaltic patterns have been linked to conditions like subfertility, abnormal uterine bleeding, and endometriosis. Uterine Peristalsis Imaging (UPI) was developed to noninvasively image 3D uterine electrical activation patterns with high spatial and temporal resolution. However, UPI cannot capture the mechanical deformation or intrauterine fluid dynamics following electrical activation. To address this, we developed Alya Purple, a digital twin of the human nonpregnant uterus that integrates patient-specific anatomical and electrophysiological data from UPI to simulate electrical, mechanical, and fluid-dynamic processes across multiple biological scales. Alya Purple reproduces uterine peristalsis patterns while offering detailed insights into human nonpregnant uterine function. In the future, it could enable personalized treatment evaluations, bridging clinical and computational models to advance gynecological care and improve patient outcomes through precision medicine.\u003c/p\u003e","manuscriptTitle":"Digital Twin of Nonpregnant Human Uterus","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-07 06:28:07","doi":"10.21203/rs.3.rs-6505611/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b9342e11-0299-41e6-be74-f39abf6aee74","owner":[],"postedDate":"May 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":47768894,"name":"Biological sciences/Physiology"},{"id":47768895,"name":"Biological sciences/Physiology/Reproductive biology"},{"id":47768896,"name":"Health sciences/Diseases"},{"id":47768897,"name":"Health sciences/Diseases/Reproductive disorders"}],"tags":[],"updatedAt":"2025-05-22T20:38:13+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-07 06:28:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6505611","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6505611","identity":"rs-6505611","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}