Machine learning (ML) models are becoming increasingly valuable for cardiovascular prediction and simulation, offering critical support for medical decision-making. These models are particularly useful for predicting disease progression and evaluating potential treatments. A major challenge in these models is to preserve the geometric fidelity of meshes while optimizing parameter efficiency to reduce memory usage, computational resources and execution time. In this paper, we present innovative approaches to abdominal aortic aneurysm (AAA) mesh compression, utilizing both statistical and deep learning models, with a focus on unsupervised learning techniques. We explore principal component analysis (PCA) as a statistical method and compare it with several deep learning models, including a simple autoencoder, an enhanced autoencoder based on PCA, a convolutional neural network (CNN), and a graph neural network (GNN). Human aortas are compressed using different statistical and deep learning methods to get the most relevant features. The mesh is reconstructed using the computed features and the error of the reconstructed meshes is compared. Our results indicate that PCA, using 64 principal components, outperforms deep learning models with a comparable latent space of 64, achieving the best overall performance. Among the deep learning approaches, the PCA-based autoencoder demonstrates the highest effectiveness.

Endoluminal reconstruction using flow diverters represents a novel paradigm for the minimally invasive treatment of intracranial aneurysms. The configuration assumed by these very dense braided stents once deployed within the parent vessel is not easily predictable and medical volumetric images alone may be insufficient to plan the treatment satisfactorily. Therefore, here we propose a fast and accurate machine learning and reduced order modelling framework, based on finite element simulations, to assist practitioners in the planning and interventional stages. It consists of a first classification step to determine a priori whether a simulation will be successful (good conformity between stent and vessel) or not from a clinical perspective, followed by a regression step that provides an approximated solution of the deployed stent configuration. The latter is achieved using a non-intrusive reduced order modelling scheme that combines the proper orthogonal decomposition algorithm and Gaussian process regression. The workflow was validated on an idealized intracranial artery with a saccular aneurysm and the effect of six geometrical and surgical parameters on the outcome of stent deployment was studied. We trained six machine learning models on a dataset of varying size and obtained classifiers with up to 95% accuracy in predicting the deployment outcome. The support vector machine model outperformed the others when considering a small dataset of 50 training cases, with an accuracy of 93% and a specificity of 97%. On the other hand, real-time predictions of the stent deployed configuration were achieved with an average validation error between predicted and high-fidelity results never greater than the spatial resolution of 3D rotational angiography, the imaging technique with the best spatial resolution (0.15 mm). Such accurate predictions can be reached even with a small database of 47 simulations: by increasing the training simulations to 147, the average prediction error is reduced to 0.07 mm. These results are promising as they demonstrate the ability of these techniques to achieve simulations within a few milliseconds while retaining the mechanical realism and predictability of the stent deployed configuration.

Background and Objective: Endovascular aortic aneurysm repair (EVAR) has become the standard treatment for abdominal aortic aneurysms in most centers. However, proximal sealing complications leading to endoleaks and migrations sometimes occur, particularly in unfavorable aortic anatomies and are strongly dependent on biomechanical interactions between the aortic wall and the endograft. The objective of the present work is to develop and validate a computational patient-specific model that can accurately predict these complications.Methods: Based on pre-operative CT-scans, we developed finite element models of the aorta of 10 patients who underwent endovascular aortic aneurysm repair, 7 with standard morphologies and 3 with unfavorable anatomies. We simulated the deployment of stent grafts in each aorta by solving mechanical equilibrium with a virtual shell method. Eventually we compared the actual stent ring positions from post-operative computed-tomography-scans with the predicted simulated positions. Results: A successful deployment simulation could be performed for each patient. Relative radial, transverse and longitudinal deviations were 6.3 +/- 4.4%, 2.5 +/- 0.9 mm and 1.4 +/- 1.1 mm, respectively.Conclusions: The numerical model predicted accurately stent-graft positions in the aortic neck of 10 patients, even in complex anatomies. This shows the potential of computer simulation to anticipate possible proximal endoleak complications before EVAR interventions.

The increasing use of mini-invasive and endovascular surgical techniques is at the origin of the pressing need for computational models to support planning and training. Several implantable devices have a wire-like structure, which can be modelled using beam elements. Our objective is to create an efficient Finite Element (FE) modelling framework for such devices. For that, we developed the EndoBeams.jl package, written exclusively in Julia, for the numerical simulation of contact interactions between wire-like structures and rigid surfaces. The package is based on a 3D FE corotational formulation for frictional contact dynamics of beams. The rigid target surface is described implicitly using a signed distance field, predefined in a volumetric grid. Since the main objective behind this package is to find the best compromise between computational speed and code readability, the algorithm, originally in Matlab, was translated and optimised in Julia, a programming language designed to combine the performance of low-level languages with the productivity of high-level ones. To evaluate the robustness, a set of tests were conducted to compare the simulation results and computational time of EndoBeams.jl against literature data, the original Matlab code and the commercial software Abaqus. The tests proved the accuracy of the underlying beam-to-surface formulation and showed the drastic performance improvement of the Julia code with respect to the original one. EndoBeams.jl is also slightly faster than Abaqus. Finally, as a proof of concept in cardiovascular medicine, a further example is shown where the deployment of a braided stent is simulated within an idealised artery.

HomeCirculation: Cardiovascular ImagingVol. 15, No. 4Computer Simulation Model May Prevent Thoracic Stent-Graft Collapse Complication Free AccessCase ReportPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessCase ReportPDF/EPUBComputer Simulation Model May Prevent Thoracic Stent-Graft Collapse Complication Lucie Derycke, Stephane Avril, David Perrin, Jean-Noël Albertini and Frederic Cochennec Lucie DeryckeLucie Derycke Correspondence to: Lucie Derycke, MD, 51 Avenue du Maréchal de Lattre de Tassigny, 94010 Créteil, France. Email E-mail Address: [email protected] https://orcid.org/0000-0001-7172-1858 Mines Saint-Etienne, Univ Lyon, Univ Jean Monnet, INSERM, U 1059 Sainbiose, Centre CIS, France (L.D., S.A.). Department of Vascular Surgery, Henri Mondor Hospital, University of Paris XII, Créteil, France (L.D., F.C.). , Stephane AvrilStephane Avril Mines Saint-Etienne, Univ Lyon, Univ Jean Monnet, INSERM, U 1059 Sainbiose, Centre CIS, France (L.D., S.A.). , David PerrinDavid Perrin https://orcid.org/0000-0001-7258-2191 PrediSurge, 3, place Roannelle, France (D.P., J.-N.A.). , Jean-Noël AlbertiniJean-Noël Albertini PrediSurge, 3, place Roannelle, France (D.P., J.-N.A.). Service de Chirurgie vasculaire, Centre Hospitalier Régional Universitaire de Saint-Etienne, avenue Albert Raimond, France (J.-N.A.). and Frederic CochennecFrederic Cochennec Department of Vascular Surgery, Henri Mondor Hospital, University of Paris XII, Créteil, France (L.D., F.C.). Originally published29 Mar 2022https://doi.org/10.1161/CIRCIMAGING.121.013764Circulation: Cardiovascular Imaging. 2022;15Other version(s) of this articleYou are viewing the most recent version of this article. Previous versions: March 29, 2022: Ahead of Print A 71-year-old man with a history of hypertension, hypercholesterolemia, and arteriopathy was referred for a 60 mm aortic arch aneurysm. No adequate sealing zone in zone 1 or 2 could be identified on the preoperative aortic computed tomography angiography (slice thickness=0.6 mm; pixel size=0.9×0.9 mm). Since this patient was deemed to be at risk for open repair, we decided to treat him using a custom-made double branch Relay device (Terumo Aortic, Sunrise). A left common carotid artery to left subclavian artery prosthetic bypass was performed during a first step procedure. The double branch stent-graft was deployed one month after. No technical problem was noticed during the procedure. During the early postoperative course, the patient presented with severe acute limb ischemia related to an iliac occlusion, a cardiogenic shock, a renal failure requiring dialysis and a complete paraplegia. Despite emergent iliac thrombectomy, a major amputation was required 15 days after TEVAR. He died 5 months after surgery.The postoperative aortic computed tomography angiography (slice thickness=3 mm, pixel size=0.7×0.7 mm) revealed a collapse of the device located at the level of the distal end of the valley dedicated to incorporate branches to the innominate artery and left common carotid artery. This collapse was deemed to be the main cause of postoperative complications.Anatomic data extracted from the preop CT-scan as well as mechanical and geometric characteristics of the double branch device were used to simulate stent-graft deployment using finite element technology (Figure 1). This work was based on proprietary algorithms (PrediSurge, Saint-Etienne, France) developed to simulate deployment of endovascular devices in patient-specific aortic aneurysms models and previously described for the aortic arch.1 Algorithms used for analysis were those from commercially available finite element solver Abaqus/Explicit v6.14 (Dassault Systèmes, Paris, France). When compared with post op CT-scan images, the 3-dimensional simulation model extracted from the numerical analysis reproduced the collapse of the stent-graft, at the same location of the fabric and predicted the collapse of the exact same three stent rings seen on the postoperative CT-scan located distally to the fenestration zone. Major deformations of the 3 stent rings distal to the valley were well predicted (Figure 2).Download figureDownload PowerPointFigure 1. Results of numerical stent-graft deployment simulation. A, Arterial geometry extracted from the preoperative computed tomography (CT)-scan. B, Prestressed models of the main stent-graft and the bridging stents. C, Sagittal view of the qualitative comparison between simulation (in red) and postoperative CT-scan (in gray). D, Simulation result. E, Transversal view of the qualitative comparison between simulation (in red) and postoperative CT-scan (in gray).Download figureDownload PowerPointFigure 2. Prediction of the collapse complication by the numerical simulation model. A, Sagittal view of the stent rings extracted from the postoperative computed tomography-scan and cross-sectional view of the stent rings with failed deployment. B, Postoperative transversal and coronal images showing the failed deployment of the 3 stent rings located just after the fenestration zone with a collapse. C, Sagittal view and cross-sectional views of the simulation result at the same location showing the same collapse. The arterial surface and the bridging stents were omitted from the overview to facilitate visualization. D, Shapes of the 3 deformed stent rings after simulation.Personalized medicine has a potential to improve endovascular treatment of patients with aortic arch disease. Despite design improvements and increased surgeon technical skills, accurate prediction of device behavior in complex anatomies remains a challenge. Procedure planning is currently limited to CT-scan imaging reconstruction softwares. One of the main limitations is the inability to provide realistic information on the interaction between the aortic wall and stent-grafts. The Finite-element analysis is a numerical method for solving mechanical problems and finite element simulation studies performed on aortic valves and aortic stent-graft have highlight the potential of this technology for predicting patient-specific behavior of aortic devices.2–4 This technique offers several potential advantages over currently used methods of preoperative planning with direct assessment of a stent-graft deployed in a personalized aortic anatomy.Such personalization during preoperative planning may be helpful to improve patient selection, type of stent-graft choice, allowing testing different stent-graft designs, and intervention strategies. This may result in a reduction of intraoperative technical issues and postoperative complications, one of which is illustrated by this case.Article InformationSources of FundingNone.Disclosures Drs Perrin, Albertini, and Avril are cofounders of the company Predisurge SAS. Dr Cochennec is proctor for Cook Medical. The other author reports no conflicts.FootnotesFor Sources of Funding and Disclosures, see page 291.Correspondence to: Lucie Derycke, MD, 51 Avenue du Maréchal de Lattre de Tassigny, 94010 Créteil, France. Email lucie.[email protected]frReferences1. Derycke L, Perrin D, Cochennec F, Albertini JN, Avril S. Predictive numerical simulations of double branch stent-graft deployment in an aortic arch aneurysm.Ann Biomed Eng. 2019; 47:1051–1062. doi: 10.1007/s10439-019-02215-2CrossrefMedlineGoogle Scholar2. de Jaegere P, De Santis G, Rodriguez-Olivares R, Bosmans J, Bruining N, Dezutter T, Rahhab Z, El Faquir N, Collas V, Bosmans B, et al. Patient-specific computer modeling to predict aortic regurgitation after transcatheter aortic valve replacement.JACC Cardiovasc Interv. 2016; 9:508–512. doi: 10.1016/j.jcin.2016.01.003CrossrefMedlineGoogle Scholar3. Rocatello G, El Faquir N, De Santis G, Iannaccone F, Bosmans J, De Backer O, Sondergaard L, Segers P, De Beule M, de Jaegere P, et al. Patient-specific computer simulation to elucidate the role of contact pressure in the development of new conduction abnormalities after catheter-based implantation of a self-expanding aortic valve.Circ Cardiovasc Interv. 2018; 11:e005344. doi: 10.1161/CIRCINTERVENTIONS.117.005344LinkGoogle Scholar4. Dupont C, Kaladji A, Rochette M, Saudreau B, Lucas A, Haigron P. Numerical simulation of fenestrated graft deployment: Anticipation of stent graft and vascular structure adequacy.Int J Numer Method Biomed Eng. 2021; 37:e03409. doi: 10.1002/cnm.3409CrossrefMedlineGoogle Scholar Previous Back to top Next FiguresReferencesRelatedDetailsCited By Derycke L, Avril S and Millon A (2023) Patient-Specific Numerical Simulations of Endovascular Procedures in Complex Aortic Pathologies: Review and Clinical Perspectives, Journal of Clinical Medicine, 10.3390/jcm12030766, 12:3, (766) April 2022Vol 15, Issue 4 Advertisement Article InformationMetrics © 2022 American Heart Association, Inc.https://doi.org/10.1161/CIRCIMAGING.121.013764PMID: 35439041 Originally publishedMarch 29, 2022 Keywordsaortic aneurysmendovascular proceduresfinite element analysisintraoperative complicationsPDF download Advertisement SubjectsCardiovascular SurgeryImaging

Objective: The aim was to validate a computational patient specific model of Zenith (R) fenestrated device deployment in abdominal aortic aneurysms to predict fenestration positions. Methods: This was a retrospective analysis of the accuracy of numerical simulation for fenestrated stent graft sizing. Finite element computational simulation was performed in 51 consecutive patients that underwent successful endovascular repair with Zenith (R) fenestrated stent grafts in two vascular surgery units with a high volume of aortic procedures. Longitudinal and rotational clock positions of fenestrations were measured on the simulated models. These measurements were compared with those obtained by (i) an independent observer on the post-operative computed tomography (CT) scan and (ii) by the stent graft manufacturer planning team on the pre-operative CT scan. (iii) Pre- and post-operative positions were also compared. Longitudinal distance and clock face discrepancies >3 mm and 15 degrees, respectively, were considered significant. Reproducibility was assessed using Bland-Altman and linear regression analysis. Results: A total of 195 target arteries were analysed. Both Bland-Altman and linear regression showed good reproducibility between the three measurement techniques performed. The median absolute difference between the simulation and post-operative CT scan was 1.0 +/- 1.1 mm for longitudinal distance measurements and 6.9 +/- 6.1 degrees for clock positions. The median absolute difference between the planning centre and post-operative CT scan was 0.8 +/- 0.8 mm for longitudinal distance measurements and 5.1 +/- 5.0 degrees for clock positions. Finally, the median absolute difference between the simulation and the planning centre was 0.96 +/- 0.97 mm for longitudinal distance measurements and 4.8 +/- 3.6 degrees for clock positions. Conclusion: The numerical model of deployed fenestrated stent grafts is accurate for planning position of fenestrations. It has been validated in 51 patients, for whom fenestration locations were similar to the sizing performed by physicians and the planning centre.

Total endovascular repair of the aortic arch represents a promising option for patients ineligible to open surgery. Custom-made design of stent-grafts (SG), such as the Terumo Aortic® RelayBranch device (DB), requires complex preoperative measures. Accurate SG deployment is required to avoid intraoperative or postoperative complications, which is extremely challenging in the aortic arch. In that context, our aim is to develop a computational tool able to predict SG deployment in such highly complex situations. A patient-specific case is performed with complete deployment of the DB and its bridging stents in an aneurysmal aortic arch. Deviations of our simulation predictions from actual stent positions are estimated based on post-operative scan and a sensitivity analysis is performed to assess the effects of material parameters. Results show a very good agreement between simulations and post-operative scan, with especially a torsion effect, which is successfully reproduced by our simulation. Relative diameter, transverse and longitudinal deviations are of 3.2 ± 4.0%, 2.6 ± 2.9 mm and 5.2 ± 3.5 mm respectively. Our numerical simulations show their ability to successfully predict the DB deployment in complex anatomy. The results emphasize the potential of computational simulations to assist practitioners in planning and performing complex and secure interventions.

Endovascular aneurysm repair (EVAR) is a current alternative treatment for thoracic and abdominal aortic aneurysms, but is still sometimes compromised by possible complications such as device migration or endoleaks. In order to assist clinicians in preventing these complications, finite element analysis (FEA) is a promising tool. However, the strong material and geometrical nonlinearities added to the complex multiple contacts result in costly finite-element models. To reduce this computational cost, we establish here an alternative and systematic methodology to simplify the computational simulations of stent-grafts (SG) based on FEA. The model reduction methodology relies on equivalent shell models with appropriate geometrical and mechanical parameters. It simplifies significantly the contact interactions but still shows very good agreement with a complete reference finite-element model. Finally, the computational time for EVAR simulations is reduced of a factor 6-10. An application is shown for the deployment of a SG during thoracic endovascular repair, showing that the developed methodology is both effective and accurate to determine the final position of the deployed SG inside the aneurysm.

The rate of post-operative complications is the main drawback of endovascular repair, a technique used to treat abdominal aortic aneurysms. Complex anatomies, featuring short aortic necks and high vessel tortuosity for instance, have been proved likely prone to these complications. In this context, practitioners could benefit, at the preoperative planning stage, from a tool able to predict the post-operative position of the stent-graft, to validate their stent-graft sizing and anticipate potential complications. In consequence, the aim of this work is to prove the ability of a numerical simulation methodology to reproduce accurately the shapes of stent-grafts, with a challenging design, deployed inside tortuous aortic aneurysms. Stent-graft module samples were scanned by X-ray microtomography and subjected to mechanical tests to generate finite-element models. Two EVAR clinical cases were numerically reproduced by simulating stent-graft models deployment inside the tortuous arterial model generated from patient pre-operative scan. In the same manner, an in vitro stent-graft deployment in a rigid polymer phantom, generated by extracting the arterial geometry from the preoperative scan of a patient, was simulated to assess the influence of biomechanical environment unknowns in the in vivo case. Results were validated by comparing stent positions on simulations and post-operative scans. In all cases, simulation predicted stents deployed locations and shapes with an accuracy of a few millimetres. The good results obtained in the in vitro case validated the ability of the methodology to simulate stent-graft deployment in very tortuous arteries and led to think proper modelling of biomechanical environment could reduce the few local discrepancies found in the in vivo case. In conclusion, this study proved that our methodology can achieve accurate simulation of stent-graft deployed shape even in tortuous patient specific aortic aneurysms and may be potentially helpful to help practitioners plan their intervention.

Endovascular repair of abdominal aortic aneurysms faces some adverse outcomes, such as kinks or endoleaks related to incomplete stent apposition, which are difficult to predict and which restrain its use although it is less invasive than open surgery. Finite element simulations could help to predict and anticipate possible complications biomechanically induced, thus enhancing practitioners' stent-graft sizing and surgery planning, and giving indications on patient eligibility to endovascular repair. The purpose of this work is therefore to develop a new numerical methodology to predict stent-graft final deployed shapes after surgery. The simulation process was applied on three clinical cases, using preoperative scans to generate patient-specific vessel models. The marketed devices deployed during the surgery, consisting of a main body and one or more iliac limbs or extensions, were modeled and their deployment inside the corresponding patient aneurysm was simulated. The numerical results were compared to the actual deployed geometry of the stent-grafts after surgery that was extracted from postoperative scans. We observed relevant matching between simulated and actual deployed stent-graft geometries, especially for proximal and distal stents outside the aneurysm sac which are particularly important for practitioners. Stent locations along the vessel centerlines in the three simulations were always within a few millimeters to actual stents locations. This good agreement between numerical results and clinical cases makes finite element simulation very promising for preoperative planning of endovascular repair.

In this study, finite element analysis is used to simulate the surgical deployment procedure of a bifurcated stent-graft on a real patient's arterial geometry. The stent-graft is modeled using realistic constitutive properties for both the stent and most importantly for the graft. The arterial geometry is obtained from pre-operative imaging exam. The obtained results are in good agreement with the post-operative imaging data. As the whole computational time was reduced to less than 2 hours, this study constitutes an essential step towards predictive planning simulations of aneurysmal endovascular surgery

The mechanical behavior of aortic stent grafts plays an important role in the success of endovascular surgery for aneurysms. In this study, finite element analysis was carried out to simulate the expansion of five marketed stent graft iliac limbs and to evaluate quantitatively their mechanical performances. The deployment was modeled in a simplified manner according to the following steps: (i) stent graft crimping and insertion in the delivery sheath, (ii) removal of the sheath and stent graft deployment in the aneurysm, and (iii) application of arterial pressure. In the most curved aneurysm and for some devices, a decrease of stent graft cross-sectional area up to 57% was found at the location of some kinks. Apposition defects onto the arterial wall were also clearly evidenced and quantified. Aneurysm inner curve presented significantly more apposition defects than outer curve. The feasibility of finite element analysis to simulate deployment of marketed stent grafts in curved aneurysm models was demonstrated. The study of the influence of aneurysm tortuosity on stent graft mechanical behavior shows that increasing vessel curvature leads to stent graft kinks and inadequate apposition against the arterial wall. Such simulation approach opens a very promising way toward surgical planning tools able to predict intra and/or post-operative short-term stent graft complications.

The endovascular treatment is a very common technique to treat aortic aneurysms. However, in spite of a sometimes long phase of preoperative planning, postoperative complications are not rare and secondary interventions are then necessary. Digital simulations of the delivery of stentgrafts (SG) could provide better tools for the planning of the operation, but they still require too computing time. Consequently, the aim of this study was to develop a methodology of simulation of delivery of SG effective and adapted to the clinical environment.

The endovascular treatment of abdominal aortic aneurysm (EVAR) consists of inserting a delivery system through intravascular pathway and deploying one or several stent-grafts at the aneurysm site in order to exclude it. This procedure has proven to have a high success rate for eligible patient population and benefits in terms of reduced blood loss, intraoperative morbidity and length of hospital stay. As the selection criteria for EVAR extend progressively due to enhancements in the devices and delivery systems, clinicians are confronted with cases becoming increasingly difficult and demanding procedures with steep learning curve (aortic dissection, branched and fenestrated stent-graft, and complex anatomy with high tortuosity or short aortic neck). In this context patient-specific Finite Element Modeling (FEM) could provide a predictive tool to support endovascular device assessment and selection as well as intervention planning. Given the lack of dedicated solutions, the aim of this study was to assess the feasibility of simulating the main steps of EVAR procedure, from guidewire insertion to stent-graft deployment.

D. Perrin*, P. Badel, S. Avril, J-N. Albertini, L. Orgéas, C. Geindreau, A. Dumenil, C. Goksu, A. Gupta 1 Ecole Nationale Supérieure des Mines de Saint-Etienne, CIS-EMSE, CNRS:UMR5307, LGF, F-42023 Saint Etienne, France, {perrin ; badel ; avril}@emse.fr 2 CHU Hôpital Nord Saint-Etienne, Department of CardioVascular Surgery, Saint-Etienne F-42055, France, j.noel.albertini@chu-st-etienne.fr 3 CNRS / Université de Grenoble (Grenoble-INP / UJF), Laboratoire Sols-Solides-StructuresRisques (3SR Lab), BP 53, 38 041 Grenoble cedex 9, France, {laurent.orgeas ; christian.geindreau}@3sr-grenoble.fr 4 Therenva, 35000 Rennes, France, {aurelien.dumenil ; cemil.goksu}@therenva.fr 5 Medtronic Inc., Santa Rosa, CA 95403, USA, atul.gupta@medtronic.com

The chemoreflex pathway undergoes postnatal maturation, and the perinatal environment plays a critical role in shaping respiratory control system. We investigated the role of prenatal hypoxia on the maturation of the chemoreflex neural circuits regulating ventilation in rat. Effects of hypoxia (10% O2) from the 5th to the 20th day of gestation were studied on male offspring at birth and on postnatal days 3, 7, 21 and 68. Maturation of the respiratory control system was assessed by in vivo tyrosine hydroxylase (TH) activity measurement in peripheral chemoreceptors (carotid bodies, petrosal ganglia), and in brainstem catecholaminergic cell groups (A2C2c and A1C1 areas in the medulla, A5 and A6 areas in the pons). Resting ventilation and ventilatory response to hypoxia were evaluated as functional sequelae. In peripheral structures, prenatal hypoxia reduced TH activity within the first postnatal week and enhanced it later. In contrast, in central areas, prenatal hypoxia upregulated TH activity within the first postnatal week and downregulated it later. The in vivo TH activity impairment is therefore tissue specific, with an opposite effect on the peripheral and central neural circuits. A shift of the effect of prenatal hypoxia occurred between 1 and 3 weeks, indicating a postnatal temporal effect of prenatal hypoxia. An important period in the development of the chemoafferent pathway occurred between the first and the third postnatal week. Functionally, prenatal hypoxia impaired resting ventilation and ventilatory response to hypoxia. The alterations of the catecholaminergic components of the chemoafferent pathway resulting from prenatal hypoxia might contribute to impair postnatal respiratory behaviour.

The postnatal development of tyrosine hydroxylase activity has been studied in the brainstem catecholaminergic cell groups (A1C1, A2C2, A5, A6, A7), involved in cardiorespiratory control. In rat, at birth and at postnatal days P3, P7, P14, P21 ant P68, we used a microdissection technique followed by in vivo measurement of the tyrosine hydroxylase (TH) activity, the rate-limiting enzyme in catecholamine synthesis. There is two successive marked increases in TH activity: at P3 in every catecholaminergic cell groups (A1C1, +225%; A2C2, +300%; A5, +190%; A6, +205% compared to birth) and during the third postnatal week with a peak of TH activity at P14 (A6, +90% above the P7 level) or at P21 (A1C1, +715%; caudal A2C2, +585%; rostral A2C2, +15%; A5, +445%; A7, +180% compared to P7). The data suggest the existence of two temporal windows during the neurochemical development of the catecholaminergic cell groups, which correspond to two metabolic transitions. The first one could be related to the intra-, extrauterine transition and the second one, to a deep energetic phase of maturation in the rat brain, closely related to the maturation of cardiorespiratory processes.

Several key events in the development of the perinatal rat phrenic nerve and diaphragm have been determined, including the following: i) Fetal inspiratory motor discharge commences within the phrenic motoneuron (PMN) pool on embryonic day (E)17; gestation period is 21 days.ii) Phrenic axons grow to innervate the full extent of diaphragmatic musculature by E17-E18.iii) There is a radical maturation of PMN morphology during the period from E16-E20.We have subsequently gone on to examine functional changes by examining PMN electrophysiological and diaphragm contractile properties prior and subsequent to these pivotal developmental stages (E16-P0).Summary data will be presented demonstrating the following: 1) As PMNs develop from E16 to P0, there are changes in passive membrane properties; resting membrane potential becomes hyperpolarized by ~10 mV, the input resistance decreases ~3-fold, and the mean rheobase increases by a factor of ~2.6.2) There are significant changes in the amplitude, duration and the afterpotentials of action potentials from E16-P0 which places restrictions on the repetitive firing patterns of fetal PMNs.3) The changes in PMN firing properties are primarily due to age-dependent changes in the expression of voltage-sensitive calcium and calcium-activated potassium currents.4) Both dye and electrical coupling have been detected amongst subpopulations of PMNs between ages E16 and P0. 5) There are marked changes in diaphragm muscle contractile properties that develop in concert with PMN repetitive firing properties so that the full-range of diaphragm force recruitment can be utilized at each age and potential problems of diaphragm fatigue are minimized.Data presented will be derived from the following references: commentary review reports meeting abstracts primary research S3 lowed by 21% O 2 -79% N 2 for 5 min, either on 6 consecutive days (recurrent episodic hypoxia), or on the 6th day only, following 5 daily normoxic exposures (single episodic hypoxia).Brains were collected either 5 min or 2 h after the last gaseous exposure.Brainstem sections underwent autoradiography with iodinated substance P for NK-1R or DAMGO for MOR.In nucleus tractus solitarius (NTS) from brains collected 2 h after the last exposure, the binding densities of NK-1R and MOR were unaltered by a single episodic hypoxia, and were greatly increased after recurrent episodic hypoxia, indicating an upregulation of both receptors by the recurrent episodic stimulus.In the NTS from the brains collected 5 min after the last hypoxic exposure, there was an important discrepancy in the binding response between the NK-1R and the MOR: The NK-1R displayed a significant decrease in ligand binding after both single and recurrent episodic hypoxia, implying enhanced receptor internalization.In contrast, the binding of MOR was not changed, implying that the rate of receptor internalization was not altered by the hypoxic exposure.This difference would result in relatively greater availability of functional MOR to opioid peptides during hypoxia.At present, we are carrying out the same experiments in developing piglets, using the same hypoxia protocols.If the findings in piglets' brains (to be presented at the Satellite meeting) are the same as those in the adult rat brain, the greater availability of functional MOR as compared to NK-1R during hypoxia may explain the attenuated ventilatory response to repeated hypoxia during development in piglets.