%0 Generic %1 herrmann2024based %A Herrmann, Karl-Heinz %A Zhao, Wan-Ting %A Höpfl, Sebastian %A Reichenbach, Jürgen R. %D 2024 %K darus ubs_10008 ubs_20013 ubs_30126 ubs_40439 unibibliografie %R 10.18419/darus-3878 %T MRI based perfusion of rats with 60% PVL %X The study investigates in vivo liver perfusion in rats. Perfusion of ligated and non-ligated liver lobes of 25 rats was monitored via MRI. Rats were subjected to 60% Portal Vein Ligation (PVL).Experimentally, the left stem of the portal vein (supplying Left Median (LML) and Left Lateral Lobe (LLL)) and the right stem to the Right Lobe (RL) were ligated. *Description of the Method and derived Units*: An ASL MRI technique assessed Tissue perfusion in vivo on anaesthetized animals. This method employs selective inversion of magnetization within the imaging plane or global inversion across the entire animal. MR imaging was conducted using a rapid, single-shot EPI technique following this labelling process.To quantify tissue perfusion, which denotes the influx of water molecules from the bloodstream into the tissue and the subsequent exchange of tissue water, we measured the T1 recovery of the magnetization. This involved repeating selective and global inversions, followed by various delay times to capture the T1 recovery in both selective and global scenarios.Tissue perfusion was then determined by calculating the T1 difference between selective and global inversions and scaling the resultant values to mL/100 g/min, representing millilitres of blood per 100 grams of tissue per minute. This computation was executed on MRI images for each voxel. Subsequently, regions of interest (ROIs) were manually delineated on anatomical images for each liver lobe. The resultant single voxel perfusion values are stored in the *.mat files. *Description of the Dataset*: The dataset consists of perfusion measurements for Regions of Interest (ROI) in each lobe. Perfusion values were obtained by collecting the voxel perfusion value for each ROI. The Dataset contains already curated representative perfusion values for each lobe. It can be used to obtain numeric perfusion values for 5 post operative days.This Dataset consists of: The raw data (zip file), A python script to convert the raw data to a tsv file, The converted tsv file, containing the animal id, observation time, lobe and perfusion value

@misc{herrmann2024based, abstract = {The study investigates in vivo liver perfusion in rats. Perfusion of ligated and non-ligated liver lobes of 25 rats was monitored via MRI. Rats were subjected to 60% Portal Vein Ligation (PVL).Experimentally, the left stem of the portal vein (supplying Left Median (LML) and Left Lateral Lobe (LLL)) and the right stem to the Right Lobe (RL) were ligated. *Description of the Method and derived Units*: An ASL MRI technique assessed Tissue perfusion in vivo on anaesthetized animals. This method employs selective inversion of magnetization within the imaging plane or global inversion across the entire animal. MR imaging was conducted using a rapid, single-shot EPI technique following this labelling process.To quantify tissue perfusion, which denotes the influx of water molecules from the bloodstream into the tissue and the subsequent exchange of tissue water, we measured the T1 recovery of the magnetization. This involved repeating selective and global inversions, followed by various delay times to capture the T1 recovery in both selective and global scenarios.Tissue perfusion was then determined by calculating the T1 difference between selective and global inversions and scaling the resultant values to mL/100 g/min, representing millilitres of blood per 100 grams of tissue per minute. This computation was executed on MRI images for each voxel. Subsequently, regions of interest (ROIs) were manually delineated on anatomical images for each liver lobe. The resultant single voxel perfusion values are stored in the *.mat files. *Description of the Dataset*: The dataset consists of perfusion measurements for Regions of Interest (ROI) in each lobe. Perfusion values were obtained by collecting the voxel perfusion value for each ROI. The Dataset contains already curated representative perfusion values for each lobe. It can be used to obtain numeric perfusion values for 5 post operative days.This Dataset consists of: The raw data (zip file), A python script to convert the raw data to a tsv file, The converted tsv file, containing the animal id, observation time, lobe and perfusion value }, added-at = {2024-04-16T12:00:21.000+0200}, affiliation = {Herrmann, Karl-Heinz/Medical Physics Group, Institute for Diagnostic and Interventional Radiology, University Hospital Jena, Zhao, Wan-Ting/Medical Physics Group, Institute for Diagnostic and Interventional Radiology, University Hospital Jena, Höpfl, Sebastian/Universität Stuttgart, Reichenbach, Jürgen R./Medical Physics Group, Institute for Diagnostic and Interventional Radiology, University Hospital Jena}, author = {Herrmann, Karl-Heinz and Zhao, Wan-Ting and Höpfl, Sebastian and Reichenbach, Jürgen R.}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/26f5982ac06ffae21defa454f803c659d/unibiblio}, doi = {10.18419/darus-3878}, howpublished = {Dataset}, interhash = {0a3538539b1f71c5a1c93a5c16c2df34}, intrahash = {6f5982ac06ffae21defa454f803c659d}, keywords = {darus ubs_10008 ubs_20013 ubs_30126 ubs_40439 unibibliografie}, note = {Related to: Sebastian Höpfl, Mohamed Albadry, Uta Dahmen, Karl-Heinz Herrmann, Eva Marie Kindler, Matthias König, Jürgen Rainer Reichenbach, Hans-Michael Tautenhahn, Weiwei Wei, Wan-Ting Zhao, and Nicole Erika Radde: Bayesian Modelling of Time Series Data (BayModTS) - A FAIR Workflow to Process Sparse and Highly Variable Data}, orcid-numbers = {Herrmann, Karl-Heinz/0000-0003-0757-3525, Zhao, Wan-Ting/0000-0002-1907-2501, Höpfl, Sebastian/0000-0002-5300-0915, Reichenbach, Jürgen R./0000-0002-2640-0630}, timestamp = {2024-04-16T12:00:21.000+0200}, title = {MRI based perfusion of rats with 60% PVL}, year = 2024 }