This research was supported by the National Center of Competence in Research (NCCR) "SYNAPSY - The Synaptic Bases of Mental Diseases" financed by the Swiss National Science Foundation (n&deg; 51AU40_125759). Development of the local Gyrification Index was supported by grants from the Swiss National Research Fund to Dr. Marie Schaer (323500-111165) and to Dr. Stephan Eliez (3200-063135.00/1, 3232-063134.00/1, PP0033-102864 and 32473B-121996) and by the Center for Biomedical Imaging (CIBM) of the Geneva-Lausanne Universities and the EPFL, as well as the foundations Leenaards and Louis-Jeantet. Support for the development of FreeSurfer software was provided in part by the National Center for Research Resources (P41-RR14075, and the NCRR BIRN Morphometric Project BIRN002, U24 RR021382), the National Institute for Biomedical Imaging and Bioengineering (R01 EB001550, R01EB006758), the National Institute for Neurological Disorders and Stroke (R01 NS052585-01) as well as the Mental Illness and Neuroscience Discovery (MIND) Institute, and is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149. Additional support was provided by The Autism &amp; Dyslexia Project funded by the Ellison Medical Foundation.

1. Reconstruct the 3D cortical surfaces
This first part of the protocol uses the standard FreeSurfer pipeline as described in the Wiki (<a href="http://surfer.nmr.mgh.harvard.edu/fswiki">http://surfer.nmr.mgh.harvard.edu/fswiki</a>). Note that the commands detailed here describe one way of achieving the cortical surface reconstructions, but equivalent commands may also be used.
<ol class="lalpha">
 <li>Import the raw MRI DICOM into FreeSurfer and verify the quality of the image (e.g. that the orientation is correct, the contrast sufficient and the images not moved). This process uses the following commands (replace the text between &lt;...&gt; (inclusive) with values appropriate to a specific instance, and "#" denotes comments): 
 
 mksubjdirs <subj_id> # create the folder architecture used by FreeSurfer 
 cd <subj_id>/mri # go to the mri folder of your subject 
 mri_convert -cm <path_to_your_dicom> 001.mgz # convert the raw MRI in the # FreeSurfer format 
 tkmedit <subj_id> 001.mgz # visualize the converted volume 
 
 </subj_id></path_to_your_dicom></subj_id></subj_id></li>
 <li>Create the three-dimensional cortical mesh models8,9. In order to cope with the problem of buried sulci, FreeSurfer first creates a unitary white matter volume, which is used as a starting point for the initial gray-white surface. This surface is then optimized according to the local gradient of intensity and further expanded to the gray-CSF interface. 
 
 recon-all -s <subj_id> # launch the cortical surface reconstruction</subj_id> 
 
 At the end of the reconstruction process, you will get two mesh models composed of about 150,000 points for each hemisphere: a white (gray-white interface) and a pial (gray-CSF interface) surface. It is important to note that all the surfaces and volumes remain in the native space, allowing measurement such as volume, surface area, thickness or gyrification index to be measured without deformation. 
 </li>
 <li>Check for the accuracy of these reconstructed surfaces: 
 
 tkmedit <subj_id> T1.mgz ?h.pial # the white surface is overlaid in green and the pial surface in red</subj_id> 
 
 where ?h denotes the hemisphere: lh.pial for the left hemisphere and rh.pial for the right hemisphere. The Figure 2 (in 2 versions: an animated gif image to be included in the movie and a static one for the website) shows an example of correct white and pial surfaces reconstructions for the "bert" subject distributed along with the FreeSurfer package. If you have to manually correct the result of the reconstruction process, you will find a tutorial on the FreeSurfer Wiki (<a href="http://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/WhiteMatterEdits">http://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/WhiteMatterEdits</a> , <a href="http://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/PialEdits">http://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/PialEdits</a>).</li>
</ol>
2. Compute the local Gyrification Index
When you are satisfied with your surfaces, compute the local Gyrification Index (lGI) using the command: 
 
recon-all -lgi -s <subj_id></subj_id>
This command usually runs for about 3 hours for the two hemispheres of one study participant, depending on the power of your workstation. The different steps of lGI process are overviewed in Fig. 1. The computing begins with the creation of an outer surface using morphological closing operation. This outer surface, denoted ?h.pial_outer_smoothed, is further illustrated in Fig. 3. Then, about 800 overlapping circular regions of interest are created on the outer surface. For each one of these regions, a corresponding region of interest is defined on the pial surface. The whole computation ends up with the creation of an individual map containing one lGI value for each point of the cortical surface (i.e. ~150,000 values per hemisphere).
3. Check the result of the lGI calculation for each hemisphere
tksurfer <subj_id> ?h pial -overlay <subj_id>/surf/?h.pial_lgi -fthresh 1</subj_id></subj_id>
The lGI values are overlaid over the cortical surface. As correct lGI values are typically comprised between 1 and 5, setting the minimum threshold at 1 (with the option fthresh) allows a rapid check: you should not see any gray cortical area. An example of correct individual result is shown in Fig. 4.
4. Statistical group comparisons
The purpose is to quantify the effect of group at each vertex over the cortical surface while controlling for the effect of gender and age. You will need to follow the same process as if you would like to compare cortical thickness at each vertex, but giving ?h.pial_lgi instead of ?h.thickness. Two options are possible to compute the statistical group comparisons: the classical commands are listed first, and the graphical interface (Qdec) is briefly mentioned thereafter.
<ol>
 <li>The first option to compare lGI results between groups use the commands listed below; further details can be obtained at <a href="https://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/GroupAnalysis">https://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/GroupAnalysis</a>.
 <ol class="lalpha">
 <li>First you will need to create a study specific template giving all your subjects in input: 
 
 make_average_subject --subjects <subj_1> <subj_2> <subj_3> ...</subj_3></subj_2></subj_1> 
 
 The command above will create a subject named "average". Alternatively, you can use the subject "fsaverage" distributed as a part of the FreeSurfer distribution.</li>
 <li>Then, create the text file containing the description of the subjects involved in your study (the "FreeSurfer Group Descriptor File"). Your FSGD.txt should look like this: 
 
 GroupDescriptorFile 1 
 Group Control_Male 
 Group Control_Female 
 Group Patient_Male 
 Group Patient_Female 
 Variables Age 
 Input <subj_1> Patient_Male 20 
 Input <subj_2> Control_Female 23 
 &lt;&hellip;&gt;</subj_2></subj_1></li>
 <li>Resample the lGI data in the space of the average subject using the following command for each hemisphere: 
 
 mris_preproc --fsgd FSGD.txt --target average --hemi ?h --meas pial_lgi --out ?h.lgi.mgh 
 </li>
 <li>Smooth the data on the cortical surface to reduce the signal to noise: 
 
 mri_surf2surf --hemi ?h --s average --sval ?h.lgi.mgh --fwhm 10 --tval ?h.10.lgi.mgh 
 </li>
 <li>Compute the group comparison at the level of each vertex. For that you will need to create a contrast text file (e.g. in the case of the FSGD.txt described above, the "contrast.txt" will contain the values "1 1 -1 -1 0" to compute the difference between controls and patients while controlling for age and gender). Finally run the comparison: 
 
 mri_glmfit --y ?h.10.lgi.mgh --fsgd FSGD.txt doss --glmdir ?h.lgi.glmdir --surf average ?h --C contrast.txt 
 </li>
 <li>Visualize the results on your average subject using tksurfer: 
 
 tksurfer average ?h inflated 
 
 Then load as overlay the sig.mgh file located in the folder ?h.lgi.glmdir/contrast.txt/sig.mgh. Using the option "configure overlay" you can further modify the p threshold as well as correct for multiple comparisons using false discovery rate10. 
 </li>
 </ol>
 </li>
 <li>The alternative option for group comparison is to use Qdec, a graphical user interface implemented in FreeSurfer. The use of Qdec with local Gyrification Index implies to pre-smooth the lGI data: 
 
 recon-all -qcache -measure pial_lgi -average <your_average_subj> -s <subj_id></subj_id></your_average_subj> 
 
 With Qdec, the FreeSurfer Group Descriptor File is replaced by a slightly different version, the Data Table (qdec.table.dat) that includes the description of the different groups and other confounding variables such as age. A detailed description of the utilization of Qdec is provided at <a href="http://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/QdecGroupAnalysis">http://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/QdecGroupAnalysis</a>. 
 Of note, if the lGI is not available in the list of dependent variables in Qdec, you must add the following line to the .Qdecrc file located in your home directory: 
 
 MEASURE1 = pial_lgi</li>
</ol>
5. Analysis
Alternatively, the statistical analyses could eventually be computed at the level of the cortical parcellation integrated in FreeSurfer11. For that purpose, average lGI values can be extracted for the 34 gyral regions of interest for each hemisphere, and these measurements can be further compared between the different groups. This parcel-wise analysis (as opposed to the vertex-wise analysis described above) could be attractive as it limits the amount of statistical comparisons. However, the lGI at each point quantifies the gyrification in the surrounding circular area, so that the average lGI in a gyral region of interest also reflects to some extent the gyrification in the neighboring regions of interest.
Finally, although the most important issues were described in this protocol, a solution to the other problems that may be encountered during the FreeSurfer or the lGI processing can be found in the archives of the FreeSurfer mailing list (<a href="http://surfer.nmr.mgh.harvard.edu/fswiki/FreeSurferSupport">http://surfer.nmr.mgh.harvard.edu/fswiki/FreeSurferSupport</a>).
6. Representative Results
As described in section 1c of the protocol, you should always carefully check the accuracy of the reconstruction of the cortical surfaces prior to lGI computation. While scrolling between the frontal and the occipital lobe, pay particular attention that vessels and membrane are not included in the pial surface. Check also that the white surface accurately follows the gray-white interface. An example of correct reconstruction is provided in Figure 2 (see the animated gif figure for the whole volume).
At the end of the lGI computation, you will also have to check the result for both hemispheres of each subject. There shouldn't be any cortical area with a lGI result smaller than 1. The section 3 of the protocol and the figure 4 show how to check correct if the output of the lGI computation is correct.
<img alt="Figure 1" src="/files/ftp_upload/3417/3417fig1.jpg" /> 
Figure 1. Overview of the lGI computation. First, three-dimensional cortical mesh models are reconstructed from the raw images using the standard FreeSurfer pipeline. These reconstruction algorithms use a binary white matter volume as starting point to overcome the issue of buried sulci. The cortical mesh models typically comprises about 150,000 vertices and are classically used to compute cortical thickness at each point. Similarly, local Gyrification Index (lGI) will be computed at each vertex. For that purpose, an outer surface is created. Then corresponding circular regions of interest are identified on the outer and cortical surface using matching algorithm. After about 800 of generating overlapping regions of interest, the process results in the creation of individual maps of lGI. These maps can be easily interpreted: an index of 5 means that there is 5 time more cortical surface invaginated within the sulci in the surrounding area that the amount of visible cortical surface; an index of 1 means that the cortex is flat in the surrounding area. Finally, statistical group comparisons are computed at the level of each vertex, similarly to cortical thickness comparisons.
Figure 1B. Individual cortical map of lGI. This small movie shows a 360-degrees rotation of an individual cortical lGI map as shown in Fig. 1. It is striking to note that the cortical regions with higher lGI values correspond to the first fold to be created during the in utero life: the sylvian fissure, the superior temporal sulcus and the intraparietal sulcus on the lateral view of the brain, and the parieto-occipital sulcus on the medial view of the brain. <a href="https://www.jove.com/files/ftp_upload/3417/3417fig1B.avi">View movie </a>
<img alt="Figure 2" src="/files/ftp_upload/3417/3417fig2.jpg" /> 
 Figure 2. Example of adequate cortical surface reconstruction (one coronal section). After the end of the reconstruction process, the cortical surfaces should be accurately verified across the entire cerebral volume. The inner cortical surface (denoted white surface, in green on the image) should precisely follow the gray-white interface. The outer cortical surface (i.e. gray-CSF interface, denoted pial surface, here in red) should not include any piece of vessel or membrane. Of note, the example presented here uses the "bert" subject distributed along with the FreeSurfer package.
Figure 2B. Example of adequate cortical surface reconstruction (full volume). This animated gif image shows the cortical surface of the left hemisphere of the "bert" subject on each coronal section, as seen by scrolling from the most frontal to the most occipital coronal sections with FreeSurfer. <a href="https://www.jove.com/files/ftp_upload/3417/3417fig2B.gif"> View movie </a>
<img alt="Figure 3" src="/files/ftp_upload/3417/3417fig3.jpg" /> 
Figure 3. Example of outer surface computed as a part of the lGI process (one coronal section). The first step in the lGI computation is the creation of an outer surface enveloping the hemisphere. This surface (denoted ?h.pial_outer_smoothed in FreeSurfer) can be checked using tkmedit. Here, the "bert" subject distributed with FreeSurfer is used as an example.
Figure 3B. Example of outer surface computed as a part of the lGI process (full volume). This animated gif image shows the outer surface of the left hemisphere on each coronal section, as seen by scrolling from the most frontal to the most occipital coronal sections with tkmedit in FreeSurfer. <a href="https://www.jove.com/files/ftp_upload/3417/3417fig3B.gif">View movie</a>







<img alt="Figure 4" src="/files/ftp_upload/3417/3417fig4.jpg" /> 
Figure 4. Example of correct lGI output as viewed with FreeSurfer. Different orientations of the cortical surface of the "bert" subject with lGI values overlaid. The color-code is the default "heat" overlay as seen with tksurfer in FreeSurfer. Using a minimum threshold of 1, all the vertices must be colored and no cortical area should appear in gray. Of note, the color overlay can be modified using the option "Configure Overlay" in tksurfer, where the minimum and maximum values, as well as the histogram of the overall distribution of the lGI can also be checked.

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The authors have nothing to disclose.

The protocol above describes how to measure local Gyrification Index based on cerebral T1-weighted MRI and conduct statistical group comparisons. Our method has been specifically designed to localize early disruption in the cortical expansion process and as such is of particular interest in many neurodevelopmental or psychiatric conditions. Examples of group comparisons in clinical samples can be found in publications by our group1,12 or by others13-16. The process is fully automated and requ...

Material: a Unix or Mac workstation with a processor of 2GHz or faster and a minimum of 4GB of RAM, with FreeSurfer installed (<a href="http://surfer.nmr.mgh.harvard.edu/fswiki">http://surfer.nmr.mgh.harvard.edu/fswiki</a>, preferably the latest version, but no older than version 4.0.3). In order to compute the local Gyrification Index, MATLAB is also required (<a href="http://www.mathworks.ch/">http://www.mathworks.com/</a>) along with the Image Processing Toolbox. 
Data: A sample of good quality (high-resolution, high contrast) cerebral MRI T1-weighted dataset. Your group of subjects must be preferably matched for age and gender. Given the normal inter-individual variability in cerebral morphology, the number of subjects in each group should be sufficient to identify an existing group difference (the more - the better). A reasonable minimum sample size would be around 20 subjects per group (although you can probably go for less if the intensity of changes is large and if your groups are tightly matched for gender and age).
<table border="1">
<tbody>
 <tr>
 <td>Name of the equipment</td>
 <td>Company</td>
 <td>Catalogue number</td>
 <td>Comments</td>
 </tr>
 <tr>
 <td>FreeSurfer </td>
 <td>Martinos Center for Biomedical Imaging, MGH</td>
 <td>&nbsp;</td>
 <td>Version newer than 4.0.3</td>
 </tr>
 <tr>
 <td>Matlab</td>
 <td>Mathworks</td>
 <td>&nbsp;</td>
 <td>Image Processing Toolbox</td>
 </tr>
 </tbody>
</table>

how to measure cortical folding from mr images: a step-by-step tutorial to compute local gyrification index

Cortical folding (gyrification) is determined during the first months of life, so that adverse events occurring during this period leave traces that will be identifiable at any age. As recently reviewed by Mangin and colleagues2, several methods exist to quantify different characteristics of gyrification. For instance, sulcal morphometry can be used to measure shape descriptors such as the depth, length or indices of inter-hemispheric asymmetry3. These geometrical properties have the advantage of being easy to interpret. However, sulcal morphometry tightly relies on the accurate identification of a given set of sulci and hence provides a fragmented description of gyrification. A more fine-grained quantification of gyrification can be achieved with curvature-based measurements, where smoothed absolute mean curvature is typically computed at thousands of points over the cortical surface4. The curvature is however not straightforward to comprehend, as it remains unclear if there is any direct relationship between the curvedness and a biologically meaningful correlate such as cortical volume or surface. To address the diverse issues raised by the measurement of cortical folding, we previously developed an algorithm to quantify local gyrification with an exquisite spatial resolution and of simple interpretation. Our method is inspired of the Gyrification Index5, a method originally used in comparative neuroanatomy to evaluate the cortical folding differences across species. In our implementation, which we name local Gyrification Index (lGI1), we measure the amount of cortex buried within the sulcal folds as compared with the amount of visible cortex in circular regions of interest. Given that the cortex grows primarily through radial expansion6, our method was specifically designed to identify early defects of cortical development.
In this article, we detail the computation of local Gyrification Index, which is now freely distributed as a part of the FreeSurfer Software (<a href="http://surfer.nmr.mgh.harvard.edu/">http://surfer.nmr.mgh.harvard.edu/</a>, Martinos Center for Biomedical Imaging, Massachusetts General Hospital). FreeSurfer provides a set of automated reconstruction tools of the brain's cortical surface from structural MRI data. The cortical surface extracted in the native space of the images with sub-millimeter accuracy is then further used for the creation of an outer surface, which will serve as a basis for the lGI calculation. A circular region of interest is then delineated on the outer surface, and its corresponding region of interest on the cortical surface is identified using a matching algorithm as described in our validation study1. This process is repeatedly iterated with largely overlapping regions of interest, resulting in cortical maps of gyrification for subsequent statistical comparisons (Fig. 1). Of note, another measurement of local gyrification with a similar inspiration was proposed by Toro and colleagues7, where the folding index at each point is computed as the ratio of the cortical area contained in a sphere divided by the area of a disc with the same radius. The two implementations differ in that the one by Toro et al. is based on Euclidian distances and thus considers discontinuous patches of cortical area, whereas ours uses a strict geodesic algorithm and include only the continuous patch of cortical area opening at the brain surface in a circular region of interest.

Watch this Scientific Journal Video about How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index at JoVE.com

How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index

Measuring gyrification (cortical folding) at any age represents a window into early brain development. Hence, we previously developed an algorithm to measure local gyrification at thousands of points over the hemisphere1. In this paper, we detail the computation of this local gyrification index.

Cortical folding (gyrification) is determined during the first months of life, so that adverse events occurring during this period leave traces that will ...

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Research

JoVE Journal

Medicine

27.8K Görüntüleme.  University of Geneva School of Medicine. Ölçüm gyrification (kortikal katlama) herhangi bir yaşta, erken beyin gelişiminde bir pencere temsil eder. Bu nedenle, daha önce yarımkürede üzerinde puan binlerce yerel gyrification ölçmek için bir algoritma geliştirdi 1. Bu çalışmada, biz detay bu yerel gyrification indeksi hesaplama.

Video: How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index

Intrauterine Telemetry to Measure Mouse Contractile Pressure In Vivo

A complex integration of molecular and electrical signals is needed to transform a quiescent uterus into a contractile organ at the end of pregnancy. Despite the discovery of key regulators of uterine contractility, this process is still not fully understood. Transgenic mice provide an ideal model in which to study parturition. Previously, the only method to study uterine contractility in the mouse was ex vivo isometric tension recordings, which are suboptimal for several reasons. The uterus must be removed from its physiological environment, a limited time course of investigation is possible, and the mice must be sacrificed. The recent development of radiometric telemetry has allowed for longitudinal, real-time measurements of in vivo intrauterine pressure in mice. Here, the implantation of an intrauterine telemeter to measure pressure changes in the mouse uterus from mid-pregnancy until delivery is described. By comparing differences in pressures between wild type and transgenic mice, the physiological impact of a gene of interest can be elucidated. This technique should expedite the development of therapeutics used to treat myometrial disorders during pregnancy, including preterm labor.

Intrauterine Telemetry to Measure Mouse Contractile Pressure In Vivo

This manuscript provides a protocol for implanting telemeters in the mouse for the purpose of measuring intrauterine pressures during pregnancy.

A complex integration of molecular and electrical signals is needed to transform a quiescent uterus into a contractile organ at the end of pregnancy. ...

Step By Step: Microsurgical training method combining two nonliving animal models

The learning of microsurgical techniques and the maintenance of microsurgical skills have been traditionally based on the use of living animals, mainly laboratory rats. This method although extremely valuable can be economically demanding both for the surgeon and the sponsoring institution; it also requires special training facilities that may not always be available or accessible. Furthermore ethical concerns can limit the use of living animals for training purposes. Alternative training methods, such as inert tubes and gloves have not gained popularity among surgeons since they do not offer an experience similar to that of a clinical situation. Non-living animal models include the use of chicken thighs and wings; they offer a practice experience that resembles a clinical situation to a considerable extent. This type of training is relatively cheap and easily available. The microscope and instruments required can be acquired over the internet, and the chicken pieces can be bought at the local supermarket.
This approach allows a motivated trainee to rehearse different types of surgical techniques several times at a reasonable expense, helping to develop or maintain his surgical expertise if more complex facilities are not available. On the current manuscript we describe how to setup a small practice station, how to dissect the specimens, and how to practice both with the chicken thighs and with the chicken wings in a progressive fashion. This approach takes advantage on the versatility of the chicken thigh model and the small size of the chicken wing Brachial artery.

Here we describe how to set up a small microsurgical practice station and a simple and inexpensive method for the training of microsurgery with non-living animal models.

The learning of microsurgical techniques and the maintenance of microsurgical skills have been traditionally based on the use of living animals, mainly ...

Assessing Cortical Cerebral Microinfarcts on High Resolution MR Images

Cerebral microinfarcts are frequent findings in the post-mortem human brain, and are related to cognitive decline and dementia. Due to their small sizes it is challenging to study them on clinical MRI scans. It was recently demonstrated that cortical microinfarcts can be depicted with MRI scanners using high magnetic field strengths (7T). Based on this experience, a proportion of these lesions is also visible on lower resolution 3T MRI. These findings were corroborated with ex vivo imaging of post-mortem human brain tissue, accompanied by histopathological verification of possible cortical microinfarcts.
Here an ex vivo imaging protocol is presented, for the purpose of validating MR observed cerebral microvascular pathology with histological evaluation. Furthermore, guidelines are provided for the assessment of cortical microinfarcts on both in vivo 7T and 3T MR images. These guidelines provide researchers with a tool to rate cortical microinfarcts on in vivo images of larger patient samples, to further unravel their clinical relevance in cognitive decline and dementia, and establish these lesions as a novel biomarker of cerebral small vessel disease.

A high resolution ex vivo 7T MR imaging protocol is presented, to perform MR-guided histopathological validation of microvascular pathology in post-mortem human brain tissue. Furthermore, guidelines are provided for the assessment of cortical microinfarcts on in vivo 7T as well as 3T MR images.

Cerebral microinfarcts are frequent findings in the post-mortem human brain, and are related to cognitive decline and dementia. Due to their small sizes ...

Heterotopic Renal Autotransplantation in a Porcine Model: A Step-by-Step Protocol

Kidney transplantation is the treatment of choice for patients suffering from end-stage renal disease. It offers better life expectancy and higher quality of life when compared to dialysis. Although the last few decades have seen major improvements in patient outcomes following kidney transplantation, the increasing shortage of available organs represents a severe problem worldwide. To expand the donor pool, marginal kidney grafts recovered from extended criteria donors (ECD) or donated after circulatory death (DCD) are now accepted for transplantation. To further improve the postoperative outcome of these marginal grafts, research must focus on new therapeutic approaches such as alternative preservation techniques, immunomodulation, gene transfer, and stem cell administration.
Experimental studies in animal models are the final step before newly developed techniques can be translated into clinical practice. Porcine kidney transplantation is an excellent model of human transplantation and allows investigation of novel approaches. The major advantage of the porcine model is its anatomical and physiological similarity to the human body, which facilitates the rapid translation of new findings to clinical trials. This article offers a surgical step-by-step protocol for an autotransplantation model and highlights key factors to ensure experimental success. Adequate pre- and postoperative housing, attentive anesthesia, and consistent surgical techniques result in favorable postoperative outcomes. Resection of the contralateral native kidney provides the opportunity to assess post-transplant graft function. The placement of venous and urinary catheters and the use of metabolic cages allow further detailed evaluation. For long-term follow-up studies and investigation of alternative graft preservation techniques, autotransplantation models are superior to allotransplantation models, as they avoid the confounding bias posed by rejection and immunosuppressive medication.

Porcine models of organ transplantation provide an important platform to study mechanisms of organ preservation. This article describes a heterotopic porcine renal autotransplantation model, which allows investigating new approaches to improve the outcome of transplantation using marginal kidney grafts.

Kidney transplantation is the treatment of choice for patients suffering from end-stage renal disease. It offers better life expectancy and higher quality ...

A Step by Step Protocol for Subretinal Surgery in Rabbits

Age related macular degeneration (AMD), retinitis pigmentosa, and other RPE related diseases are the most common causes for irreversible loss of vision in adults in industrially developed countries. RPE transplantation appears to be a promising therapy, as it may replace dysfunctional RPE, restore its function, and thereby vision.
Here we describe a method for transplanting a cultured RPE monolayer on a scaffold into the subretinal space (SRS) of rabbits. After vitrectomy xenotransplants were delivered into the SRS using a custom made shooter consisting of a 20-gauge metallic nozzle with a polytetrafluoroethylene (PTFE) coated plunger. The current technique evolved in over 150 rabbit surgeries over 6 years. Post-operative follow-up can be obtained using non-invasive and repetitive in vivo imaging such as spectral domain optical coherence tomography (SD-OCT) followed by perfusion-fixed histology.
The method has well-defined steps for easy learning and high success rate. Rabbits are considered a large eye animal model useful in preclinical studies for clinical translation. In this context rabbits are a cost-efficient and perhaps convenient alternative to other large eye animal models.

Retinal pigment epithelium (RPE) replacement strategies and gene-based therapy are considered for several retinal degenerative conditions. For clinical translation, large eye animal models are required to study surgical techniques applicable in patients. Here we present a rabbit model for subretinal surgery geared towards RPE transplantation, which is versatile and cost-efficient.

Age related macular degeneration (AMD), retinitis pigmentosa, and other RPE related diseases are the most common causes for irreversible loss of vision in ...

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition

Limited evidence exists to precisely estimate efficacy and safety differences between parenteral nutrition (PN) prepared using olive-oil-based three-chamber bags (3CBs) and soybean-oil-based compounded bags (CoBs) in hospitalized adult patients. We designed a multicenter, randomized, prospective, open-label, noninferiority protocol to compare the efficacy, safety, and distribution of olive-oil-based 3CBs and soybean-oil-based CoB formulations in adult Chinese patients requiring PN during surgical intervention. Subjects were randomized to receive either one of the study treatments using an interactive voice or web-based recognition system in accordance with the randomization code. Randomization was further stratified based on the study site and surgical category. Both treatment groups received similar amounts of calories and protein. In addition, the two study treatments contained a similar composition of the amino-acid component. The only difference between the two PN formulations was the lipid constitution. The duration of administration of study treatments was a minimum of 5 days up to a maximum of 14 days after the surgical procedure. The primary efficacy endpoint was serum prealbumin levels on day 5 of the study. Noninferiority was proved if the anti-log of the lower bound of the 95% confidence interval (CI) of the treatment difference was at least 0.80. Other efficacy measures included treatment preparation time; duration to achieve tolerability of oral nutrition; associated infectious complications; length of hospitalization; and laboratory assessment of markers of nutrition, inflammation, metabolism, and oxidative stress. A total of 458 patients were enrolled in the study. The results showed that olive-oil-based 3CBs were non-inferior to soybean-based CoBs, besides being well tolerated. The infection rate was found to be significantly lower in the olive-oil-based 3CB group. Thus, this study may be used as a reference for future research on lipid emulsion and 3CBs.

Here, we present a protocol for a study comparing the efficacy, safety, and delivery of olive-oil-based 3CB and soybean-oil-based CoB formulations in adults requiring parenteral nutrition. The results revealed that olive-oil-based 3CBs is non-inferior and well tolerated compared to soybean formulations.

Limited evidence exists to precisely estimate efficacy and safety differences between parenteral nutrition (PN) prepared using olive-oil-based ...

Obtaining Quality Extended Field-of-View Ultrasound Images of Skeletal Muscle to Measure Muscle Fascicle Length

Muscle fascicle length, which is commonly measured in vivo using traditional ultrasound, is an important parameter defining a muscle&#8217;s force generating capacity. However, over 90% of all upper limb muscles and 85% of all lower limb muscles have optimal fascicle lengths longer than the field-of-view of common traditional ultrasound (T-US) probes. A newer, less frequently adopted method called extended field-of-view ultrasound (EFOV-US) can enable direct measurement of fascicles longer than the field-of-view of a single T-US image. This method, which automatically fits together a sequence of T-US images from a dynamic scan, has been demonstrated to be valid and reliable for obtaining muscle fascicle lengths in vivo. Despite the numerous skeletal muscles with long fascicles and the validity of the EFOV-US method for making measurements of such fascicles, few published studies have utilized this method. In this study, we demonstrate both how to implement the EFOV-US method to obtain high quality musculoskeletal images and how to quantify fascicle lengths from those images. We expect that this demonstration will encourage the use of the EFOV-US method to increase the pool of muscles, both in healthy and impaired populations, for which we have in vivo muscle fascicle length data.

This study describes how to obtain high quality musculoskeletal images using the extended field-of-view ultrasound (EFOV-US) method for the purpose of making muscle fascicle length measures. We apply this method to muscles with fascicles that extend past the field-of-view of common traditional ultrasound (T-US) probes.

Muscle fascicle length, which is commonly measured in vivo using traditional ultrasound, is an important parameter defining a muscle&#8217;s force ...

Step-by-Step Stapedotomy through Transcanal Exclusive Endoscopic Approach

In recent years there has been an increasing trend in the use of the endoscope to treat a variety of middle ear pathologies, including otosclerosis. Several studies comparing traditional microscopic and endoscopic stapes surgery have reported similar hearing results and an overall low rate of complications. The endoscope has unraveled its full potential in demanding settings of stapes surgery, such as unfavorable anatomy of the oval window niche or revision cases. Reduced manipulation of the chorda tympani and low rate of post-operative dysgeusia are further benefits to mention for endoscopic stapes surgery.
Being a one-handed technique, management of bleeding, positioning, and crimping of the prosthesis may be challenging for novice endoscopic surgeons, so some training in endoscopic ear surgery is recommended before performing endoscopic stapedotomy. The problem of sharing the surgical field between the endoscope and the operating instruments could be easily overcome if proper instruments positioning is understood. One-handed bleeding control in the narrow space of the ear canal may represent an issue during the elevation of the tympano-meatal flap, possibly discouraging the surgeon since the preliminary steps of surgery. Following appropriate technique to raise the flap and the collaboration with the anesthesiology team in keeping the blood pressure low guarantee an adequate bleeding control in most cases.
The aim of this article is to describe the entire surgical procedure of a transcanal exclusive endoscopic stapedotomy, from operating room set up and patient positioning to post-operative care. A step-by-step description of the surgical maneuvers with technical hints is reported, to guide the surgeon across the procedure and allow any ear surgeon to perform stapes surgery endoscopically.

The aim of this article is to provide a step-by-step method for endoscopic stapes surgery from operating room setting and patient positioning to post-operative care. This work would represent a guide for any otologic surgeon who is willing to treat otosclerosis with endoscopic transcanal technique.

In recent years there has been an increasing trend in the use of the endoscope to treat a variety of middle ear pathologies, including otosclerosis. ...

Improved Renal Denervation Mitigated Hypertension Induced by Angiotensin II Infusion

The benefits of renal sympathetic denervation (RDN) on blood pressure have been proved in a large number of clinical trials in recent years. However, the regulatory mechanism of RDN on hypertension remains elusive. Thus, it&#39;s essential to establish a simpler RDN model in mice. In this study, osmotic mini pumps filled with Angiotensin II were implanted in 14-week-old C57BL/6 mice. One week after the implantation of the mini-osmotic pump, a modified RDN procedure was performed on bilateral renal arteries of the mice using phenol. Age-sex-matched mice were given saline and served as sham group. Blood pressure was measured at baseline and every week subsequently for 21 days. Then, renal artery, abdominal aorta and heart were collected for histological examination using H&#38;E and Masson staining. In this study, we present a simple, practical, repeatable, and standardized RDN model, which can control hypertension and alleviate cardiac hypertrophy. The technique can denervate peripheral renal sympathetic nerves without renal artery damage. Compared to previous models, the modified RDN facilitates the study of the pathobiology and pathophysiology of hypertension.

Here, we present a protocol for renal sympathetic denervation (RDN) in mice with hypertension induced by Angiotensin II infusion. The procedure is repeatable, convenient and allows to study the regulatory mechanisms of RDN on hypertension and cardiac hypertrophy.

The benefits of renal sympathetic denervation (RDN) on blood pressure have been proved in a large number of clinical trials in recent years. However, the ...

An Educational Video Demonstration of How to Prone a Critically Ill Intubated Patient

Early in the coronavirus disease 2019 (COVID-19) pandemic, it was reported that prone position was beneficial for mechanically ventilated COVID-19 patients with acute respiratory distress syndrome (ARDS). However, for staff in some small and large hospitals, experience with this intervention was low. Select hospitals were able to assemble proning teams; but, as facilities began to experience staffing shortages, they found proning teams unsustainable, and less specialized staff needed to learn how to safely prone patients.
Proning is a high-risk procedure-a lack of a standard approach can result in staff confusion and poor patient outcomes, including unintentional endotracheal tube (ET) loss, vascular access dislodgement, and skin breakdown. Given the acuity and high patient volume, translating a complex procedure into written policy may not be entirely effective. Critical care nurses, respiratory therapists, physical therapists, wound nurses, nurse practitioners, physician assistants, and medical doctors need to be prepared to safely perform this procedure for an acutely ill COVID-19 patient.
Communication, teamwork, and multidisciplinary collaboration are critical for complication avoidance. Interventions to prevent tube and vascular access dislodgement, skin breakdown, and brachial plexus and soft tissue injury must be implemented during the procedure. Repositioning the patient in the prone position, as well as returning the patient to supine positioning, should be components of a comprehensive proning plan.

Proning a critically ill patient with severe acute respiratory distress syndrome (ARDS) is a complex but beneficial procedure. Excellent communication skills, team work, and multidisciplinary collaboration are critical for patient and staff safety. A standard procedure should be utilized when proning ventilated patients with tubes, drains, and vascular access devices.