EIDORS: Electrical Impedance Tomography and Diffuse Optical Tomography Reconstruction Software

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PEEP trial after lung injury (pig)

Methods and Data

Methods and Data

Data were published in Frerichs, I., Dargavillle, P.A., Dudykevych, T., Rimensberger, P.M. (2003) Electrical Impedance Tomography − a method for monitoring regional lung aeration and tidal volume distribution? Intensive Care Med. 29:2312-2316, 2003.

Results

EIDORS Analysis

1. Download the data and save it to your working directory.
2. Create a FEM model of the pig

   % Create Model $Id: if_peep_trial01.m 1535 2008-07-26 15:36:27Z aadler $
   
   imdl= mk_common_model('c2c2',16);
   % Use normalized difference imaging
   imdl.fwd_model.normalize_measurements=1;
   
   subplot(211);
   show_fem(imdl.fwd_model, [0,1,0]);
   axis equal; axis off
   
   hh=text(-1.1,0,'Right');
   set(hh,'Rotation',90,'HorizontalAlignment','Center');
   hh=text(0,+1.1,'Ventral');
   set(hh,'HorizontalAlignment','Center');
   
   print -r150 -dpng if_peep_trial01.png
   
   

   
   Figure: 2D FEM of pig thorax
3. Reconstruct images

   % Reconstruct Images $Id: if_peep_trial02.m 1535 2008-07-26 15:36:27Z aadler $
   
   v_injury = eidors_readdata('p1130107.get');
   r_injury = mean(v_injury(:,1:10),2); % reference meas
   v_treat  = eidors_readdata('p1130122.get');
   r_treat  = mean(v_treat(:,1:10),2); % reference meas
   
   i_injury = inv_solve(imdl, r_injury, v_injury);
   i_treat  = inv_solve(imdl, r_treat , v_treat );
   
   

4. Select Regions of interest to plot

   % Select ROI's
   
   img = i_injury; img.elem_data = img.elem_data(:,630);
   rimg = calc_colours( calc_slices( img ), img);
   
   np= calc_colours('npoints');
   xlocn= 0.25 * np;
   ylocn= [2:5]/8 * np; 
   for yl = 1:4;
      rimg(ylocn(yl) + (-2:2), xlocn + (-2:2) ) = 1;
   end
   image(rimg); axis square
   
   for yl = 1:4;
      text(xlocn-1, ylocn(yl), num2str(yl));
   end
   
   axis off
   print -r100 -dpng if_peep_trial03.png
   
   

   
   Figure: Image of ventilation and 4 identified points to analyse regional ventilation
5. Normalized Impedance Change (ΔZ) at each ROI

   % Display Times courses $Id: if_peep_trial04.m 1535 2008-07-26 15:36:27Z aadler $
   
   for loop = 1:2;
      if loop == 1; img = i_injury;
      else          img = i_treat;
      end
   
      subplot(2,2,loop);
      time = (0:size(img.elem_data,2)-1)/13; % Frame rate = 13/s
   
      raster= calc_slices( img );
      ROIs  = raster(ylocn, xlocn, :);
      ROIs  = permute(ROIs, [3,1,2]);
   
      %Normalize to its maximum
      for i=1:length(ylocn)
         ROIs(:,i) = - ROIs(:,i) / max(abs(ROIs(:,i)));
      end
      plot(time, ROIs);
      axis([0, max(time), -0.1, 1]);
      legend('1','2','3','4',2)
      xlabel('time (s)')
      ylabel('normalized \Delta Z')
   end
   
   print -dpng -r150 if_peep_trial04.png
   
   

   
   Figure: Normalized ΔZ time course for different lung ROIs. Left Lung Injury Right Treated
6. Animate Output for each condition This function creates a video of the sample sequences.

   % Display Times courses $Id: if_peep_trial04.m 1535 2008-07-26 15:36:27Z aadler $
   
   for loop = 1:2;
      if loop == 1; img = i_injury;
      else          img = i_treat;
      end
   
      subplot(2,2,loop);
      time = (0:size(img.elem_data,2)-1)/13; % Frame rate = 13/s
   
      raster= calc_slices( img );
      ROIs  = raster(ylocn, xlocn, :);
      ROIs  = permute(ROIs, [3,1,2]);
   
      %Normalize to its maximum
      for i=1:length(ylocn)
         ROIs(:,i) = - ROIs(:,i) / max(abs(ROIs(:,i)));
      end
      plot(time, ROIs);
      axis([0, max(time), -0.1, 1]);
      legend('1','2','3','4',2)
      xlabel('time (s)')
      ylabel('normalized \Delta Z')
   end
   
   print -dpng -r150 if_peep_trial04.png
   
   

   
   Figure: Video of sample sequences Left Lung Injury Right Treated