{"id":36834,"date":"2022-05-17T18:14:00","date_gmt":"2022-05-17T16:14:00","guid":{"rendered":"https:\/\/supazena.ovh\/c\/etap\/?post_type=ressource&p=36680"},"modified":"2026-04-15T22:20:21","modified_gmt":"2026-04-15T20:20:21","slug":"preclinical-models-of-cerebral-haemorrhage","status":"publish","type":"ressource","link":"https:\/\/www.etap-lab.com\/en\/ressource\/preclinical-models-of-cerebral-haemorrhage\/","title":{"rendered":"Preclinical models of cerebral haemorrhage"},"content":{"rendered":"\n

Haemorrhagic strokes account for 10-15% of all strokes. In 40% of patients<\/strong>, haemorrhagic strokes are fatal within one month, rising to<\/strong> 54% after 1 year<\/strong>. Haemorrhagic strokes have a devastating effect on the quality of life of <\/strong>surviving patients, <\/em>with only 12 to 39% able to get back to long-term independence.<\/em><\/p>\n\n\n\n

Rapid diagnosis, stopping the haemorrhage and draining the haematoma, initiating treatment against blood poisoning, limiting vasospasms, neuroprotection<\/em><\/strong> and finally stimulating functional recovery <\/strong>are all possible strategies<\/strong> for reducing the number of deaths, promoting long term recovery and improving patients\u2019 quality of life. Unfortunately, few pharmacological solutions are available.<\/strong><\/em><\/p>\n\n\n\n

The entire medicines R&D sector, from bench to bedside, is rising to the challenge of developing new, effective therapies<\/strong>. From initial proof of concept, <\/strong>through preclinical development<\/strong>, the use of appropriate tools maximises the chances of a successful translation. <\/strong><\/em>Whether the target is subarachnoid haemorrhage (SAH), intercranial haemorrhages (ICH)<\/strong> or evaluating the risks of haemorrhagic<\/strong> transformation <\/strong>following the administration of thrombolytic therapy, the choice of animal model and experimental design are key.<\/p>\n\n\n\n

Our R&D team, in partnership with that of Professor Denis Vivien <\/strong>(U1237, INSERM\/UNICEAN, Caen) has developed several haemorrhagic stroke models <\/strong>using our insight into the issues involved. They are suitable for use in rodents and designed to respond to a wide range of questions surrounding the preclinical development of new therapies linked to cerebral haemorrhage. <\/strong>As in the clinical setting, we assess both the impact of haemorrhage on the brain tissue using functional magnetic resonance imaging (MRI) and functional recovery via measurement of behavioural parameters. We also offer tools which allow more precise investigation of the process of neuroinflammation, such as molecular imaging using MRI, flow cytometry, and various other immunohistochemistry markers (Neutrophiles and NETS, activated microglia, etc.).<\/p>\n\n\n\n

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Let\u2019s take a more detailed look at each model<\/strong>!<\/p>\n\n\n\n

ICH\u00a0models<\/h2>\n\n\n\n

These models, which are well documented in the literature (see Goulay et al., 2017<\/a>), have been enhanced by the STROK@LLIANCE R&D team.
The models are induced in rats and mice using intraparenchymal injections of collagenase (collagenase model), or of autologous blood (blood injection model) directly into the striatum. Collagenase model: following damage to the vascular wall collagen, the surrounding brain tissue becomes flooded with blood. In this model the extent of the haemorrhage is well controlled; the site of the injection determines whether or not the blood leak affects the lateral ventricles. Blood injection model: a fixed volume of autologous blood is injected. The main difference between the two models is that there is a real bleed in the collagenase model, whereas an artificial haematoma is created in the blood injection model. The collagenase model is more physiological, but the volume of bleeding can be influenced by the administration of the compound, which is not necessarily the aim of the study. Tools: in both models, we monitor development of the haemorrhage in rats and mice using MRI (T2 & T2* imaging), using molecular imaging of the inflammation (endothelial activation of VCAM-1), behavioural assessment and immunohistochemistry.<\/p>\n\n\n\n

>> More information about ICH models<\/a><\/p>\n\n\n\n

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SAH models<\/h2>\n\n\n\n

SAH models unfortunately remain unsatisfactory at the moment in terms of their similarity to real clinical situations. Professor Vivien\u2019s team published a literature review in November 2021 in Frontiers in cardiovascular disease<\/em>, taking stock of the current situation and pointing out the models\u2019 shortcomings:
>> link to article : Delayed Cerebral Ischaemia After Subarachnoid Haemorrhage: Is There a Relevant Experimental Model? A Systematic Review of Preclinical Literature<\/a><\/em> (Goursaud et al., 2021). In this review the SAH model which uses the autologous blood injection in the cisterna magna, although not perfect, is described as the best alternative available for testing molecule effectiveness.<\/p>\n\n\n\n

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Haemorrhagic transformation or over bleeding model<\/h2>\n\n\n\n

In the development of molecules for the treatment of thromboembolic\/ischemic stroke, the question of safe utilisation \u2013 particularly in relation to bleeding \u2013 is central for neurologists and assessment agencies. One key issue is to determine whether the risk of haemorrhagic transformation is increased with the use of the candidate drug. Another is whether the product increases the volume of bleeding (over bleeding) when haemorrhagic transformation occurs (the risk of transformation being present in all patients). The risk of over bleeding can be assessed using the collagenase model described above, to measure the effect a molecule of interest has on bleeding. >> More information about ICH models<\/p>\n\n\n\n

Our R&D team is currently developing a new model in diabetic mice to meet the need for a reliable model for assessing the risk of haemorrhagic transformation. Watch this space in September 2022<\/strong>, to see the presentation of validation data.<\/p>\n\n\n\n

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ICH models: our results<\/h2>\n\n\n\n

The aim of the collagenase model is to mimic the effects of an intraparenchymal brain haemorrhage<\/strong><\/p>\n\n\n\n

This model is induced by the direct, unilateral injection of collagenase in the striatum. It results in damage to the adventitia (external layer of the vascular wall), which causes haemorrhaging around the injection site. By choosing the structure, concentration and volume of collagenase it is possible to obtain a reproducible haemorrhage associated with a brain lesion and well-defined motor defects.<\/p>\n\n\n\n

MRI & molecular imaging<\/h3>\n\n\n\n

Changes in the volume of both the lesion (T2) and the haematoma (T2*) can be located, measured and tracked with MRI brain imaging. (Illustration: Figure 1: rat on day 1 , Figure 2: mouse on day 1).<\/strong><\/p>\n\n\n\n

\"Rat
Figure 1<\/strong>\u2013 Lesion volume: MRI-T2 of a rat, 24 hours post stroke<\/figcaption><\/figure>\n\n\n\n
\"MRI
Figure 2<\/strong>\u2013 Assessment volume of brain lesion and haemorrhage: MRI T2 and T2* of a mouse, 24 hours post stroke<\/figcaption><\/figure>\n\n\n\n

This type of measurement can answer questions relating to the efficacy of a treatment on haem toxicity, oxidative stress linked to the release of iron oxide, increase in intracranial pressure and the capacity of a treatment to reduce brain lesions through different processes.<\/p>\n\n\n\n

Long term monitoring enables researchers to highlight the impact of a treatment over the longer term and to observe the animal\u2019s functional recovery phase (Figure 3). It also makes it possible to track the reduction in post-induction oedema and tissue remodelling in the damaged area. The activation of those processes results in a reduction in the size of the lesion (phagocytosis of cellular debris, glial colonisation, etc.).<\/p>\n\n\n\n

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Figure 3: The development of the visible volume of the lesion and bleeding in a mouse over 14 days following induction (n=8; ANOVA; p<0.001; Post Hoc test (Student-Newman-Keuls) *: p<0.05 VS day 1; #:p<0.05 VS day 5 ; Mean +\/- SEM)<\/figcaption><\/figure>\n\n\n\n

It is also possible to use this model to acquire data relating to inflammation. A protein of interest can be visualised in vivo via molecular imaging, using microparticles of iron oxide (MPIO) coupled with an antibody. By targeting markers such as VCAM-1 or P-Selectine it is possible to track and quantify the level of brain inflammation (Figure 4).<\/p>\n\n\n\n

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Figure 4 <\/strong>\u2013 Molecular imaging<\/strong> \u2013 Measurement of the effects of Exonaparin on the monitoring of brain haemorrhage (T2*) and the extent of the lesion (T2) at day 1 and day 3 post-stroke, as well as VCAM-1 labelling in molecular imagery at day 3.<\/figcaption><\/figure>\n\n\n\n

In the study of our ICH model, we assessed the impact of an anticoagulant agent (such as Enoxaparin). We observed that Enoxaparin produced an increase in the volume of the haemorrhage at day 1 (Figure 4) as well as an increase in the size of the lesion at day 3 (Figure 5). With this model it is possible to assess a susceptible molecule\u2019s risk of bleeding to provoke over bleeding<\/strong>.<\/p>\n\n\n\n

By using MPIOs coupled with a V-CAM1 antibody, we have been able to quantify in vivo <\/em>the impact of Enoxaparin pre-treatment on the expression of this cell adhesion molecule and thus demonstrate the level of post-haemorrhage inflammation (Figures 4 and 5).<\/p>\n\n\n\n

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Figure 5<\/strong>\u2013 Lesion and Hemorrhage volume at D1 and D3<\/strong> (on the left), n=6 Effect of Enoxaparin VS PBS (ANOVA; *p<0.05; Mean +\/- SEM)
and VCAM quantification at D3 (on the right)<\/strong>, hemispheres comparaison (ANOVA; *p<0.05; Mean +\/- SEM); Effect of Enoxaparin VS PBS (ANOVA; *p<0.05) H= hemisphere<\/figcaption><\/figure>\n\n\n\n

Immunohistochemistry labeling<\/h3>\n\n\n\n

This molecular imaging data can be supplemented by immunohistochemistry studies. Following tissue sampling, we can, for example, quantify:<\/p>\n\n\n\n