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Introduction to MobileOCT's Multimodal Imaging
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Introduction to MobileOCT's Multimodal Imaging

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  • 1. 1  David  Levitz,  PhD  –  Ariel  Beery,  MPA/MA   Introduction to multimodal imaging An introduction to MobileOCT’s proprietary method, combining high resolution structural, polarization difference, and spectral imaging modalities :  
  • 2. 2   We believe the only cure is early screening We  can  save  more  lives  in  the  ba1le  against   cancer,  if  only  we  catch  cancer  earlier.     Our  proprietary  technology  can  augment  any   digital  camera  to  provide  clinicians  with   revoluConary  access  to  informaCon  about   Cssue  microstructure  and  composiCon,   including  biomarkers,  so  they  can  beGer   idenCfy  and  characterize  cancers.     2  
  • 3. 3   More is more •  Current  clinical  imaging   techniques  relies  primarily  on   bright-­‐field  imaging   •  Tissue  is  not  uniform  –    it   contains  mulCple  layers  and   components   •  No  single  mode  of  imaging  can   quickly  and  reliably  achieve   high  sensi7vity  and  specificity   •  By  combining  the  strengths  of   mulCple  imaging  modaliCes,  we   can  provide  the  clinician  with  a   more  complete  picture  of  the   Cssue   Freckle,  before  and  aPer  PDI:     Standard  Image   PolarizaCon  Difference  Image   Malignant  Basel  Cell  Carcinoma   Standard  Image   PolarizaCon  Difference  Image  
  • 4. 4   MobileOCT’s Multimodal Technology MobileOCT’s  proprietary  technology  does   this  by  using:     •  High  resolu:on  bright-­‐field  imaging  to   provide  the  ‘standard  view’  that   clinicians  are  used  to  working  with   •  Polariza:on  difference  imaging  (PDI)   to  provide  informaCon  about  the   micro-­‐structural  paGerns  in  the   superficial  layer  of  the  Cssue   •  Spectral  imaging  to  provide  the   clinician  with  informaCon  about  the   composiCon  of  Cssue  (water,  oxy-­‐  and   deoxy-­‐hemoglobin),  including  some   biomarkers   MobileOCT’s  adaptor  in  blue,   on  a  Welch  Allyn  video   colposcope  
  • 5. 5   Why multimodal is so important: 15%  returns  from  the  surface,  mainly  as   glare   •  Image  seen  is  formed  by  light   returning  from  different  layers  of   Cssue,  containing  someCmes   conflicCng  informaCon.   •   To  beGer  analyze  a  sample,   MobileOCT  analyzes  each   element  separately.     4%  returns  from  the  superficial  layer   (where  most  cancers  form)   ~80%  of  the  light  returns  from  the  deeper   dermis  (or  stroma),  where  informaCon  on   certain  biomarkers  is  found  
  • 6. 6   Mode 1: bright-field imaging, the standard MobileOCT’s  technology  can  be   mounted  on  any  digital  camera,   enabling  the  same  high  resoluCon   images  physicians  are  used  to   seeing     Stratum     Corneum  
  • 7. 7   Mode 2: Polarization Difference Imaging(PDI) 1.  Linearly  polarized  light  is  sent  into   the  sample  (            )   2.  Light  returning  from  superficial   layer  maintains  polarizaCon   3.  Light  returning  from  deeper  layer  is   diffuse,  with  its  polarizaCon  evenly   split  between  the  PAR  (          )  and   ORTH  (      )  orientaCons   4.  We  isolate  the  superficial  layer  with   the  following  equaCon:   Camera/Sensor   PDI  =  PAR  –  ORTH    
  • 8. 8   Why PDI works: examples from skin Freckle:   Malignant  basal  cell  carcinoma   Standard   PDI   N.  squamous  cell  carcinoma   The  freckle,  a  surface  feature,  does  not  impact  the   superficial  layer   The  disrupCon  occurring  amongst  the  basal  cells  is   hidden  when  observing  the  sample  under  even   high  resoluCon  imaging     The  faded  area  observed  in  the  high  resoluCon   image  ‘pops  out’  when  PDI  is  applied,  because  one   can  now  observe  the  distrupCon  in  the  superficial   layer   Jacques et al, J Biomed Opt 2002  
  • 9. 9   Mode 3: multi-spectral imaging •  All  the  wavelengths  of  light   are  analyzed  together,  to   quanCfy  biomarker  content   in  dermis  (stroma)   •  Tissue  chromophores  are   known  a  priori  (i.e:  Water,   oxy-­‐  and  deoxy-­‐hemoglobin,   melanin,  bilirubin)   •  The  quanCfied  makeup  of   the  deep  layer  provides  more   details  on  the  structural   changes  visualized  with  PDI   Tsumra et al., internal paper, Chiba University, Liu et al., Applied Optics, 46, 8328-8334 (2007) Jacques et al Biomed Opt Express (2011)  
  • 10. 10   Better Together •  Each  mode  has  its  own   inherent  strengths  and   challenges   •  MobileOCT’s  technology   enables  the  clinician  to  view   each  mode  separately,  and   soon  will  enable  viewing  a   composite  of  all  three  models   •  By  increasing  the  power   available  to  clinicians,   MobileOCT  hopes  to  help  find   cancer,  sooner.    

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