title: Integrated optical coherence tomography and optical coherence microscopy imaging of ex vivo human renal tissues.
abstract: OBJECTIVE
  We evaluated the feasibility of using optical coherence tomography and optical coherence microscopy technology to assess human kidney morphology.
  
  
  METHODS
  A total of 35 renal specimens from 19 patients, consisting of 12 normal tissues and 23 tumors (16 clear cell renal cell carcinomas, 5 papillary renal cell carcinomas and 2 oncocytomas) were imaged ex vivo after surgical resection. Optical coherence tomography and optical coherence microscopy images were compared to corresponding hematoxylin and eosin histology to identify characteristic features of normal and pathological renal tissues. Three pathologists blinded to histology evaluated the sensitivity and specificity of optical coherence microscopy images to differentiate normal from neoplastic renal tissues.
  
  
  RESULTS
  Optical coherence tomography and optical coherence microscopy images of normal kidney revealed architectural features, including glomeruli, convoluted tubules, collecting tubules and loops of Henle. Each method of imaging renal tumors clearly demonstrated morphological changes and decreased imaging depth. Optical coherence tomography and microscopy features matched well with the corresponding histology. Three observers achieved 88%, 100% and 100% sensitivity, and 100%, 88% and 100% specificity, respectively, when evaluating normal vs neoplastic specimens using optical coherence microscopy images with substantial interobserver agreement (κ = 0.82, p <0.01).
  
  
  CONCLUSIONS
  Integrated optical coherence tomography and optical coherence microscopy imaging provides coregistered, multiscale images of renal pathology in real time without exogenous contrast medium or histological processing. High sensitivity and specificity were achieved using optical coherence microscopy to differentiate normal from neoplastic renal tissues, suggesting possible applications for guiding renal mass biopsy or evaluating surgical margins.
authors.affiliation: Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA.
authors.forename: Hsiang-Chieh
authors.initials: HC
authors.lastname: Lee
authors.forename: Chao
authors.initials: C
authors.lastname: Zhou
authors.forename: David W
authors.initials: DW
authors.lastname: Cohen
authors.forename: Amy E
authors.initials: AE
authors.lastname: Mondelblatt
authors.forename: Yihong
authors.initials: Y
authors.lastname: Wang
authors.forename: Aaron D
authors.initials: AD
authors.lastname: Aguirre
authors.forename: Dejun
authors.initials: D
authors.lastname: Shen
authors.forename: Yuri
authors.initials: Y
authors.lastname: Sheikine
authors.forename: James G
authors.initials: JG
authors.lastname: Fujimoto
authors.forename: James L
authors.initials: JL
authors.lastname: Connolly
mesh_terms: D018249:Adenoma, Oxyphilic / Q000473:pathology*; D000328:Adult; D000368:Aged; D002292:Carcinoma, Renal Cell / Q000473:pathology*; D006801:Humans; D007680:Kidney Neoplasms / Q000473:pathology*; D008875:Middle Aged; D041623:Tomography, Optical Coherence / Q000379:methods*