PURPOSE: We evaluated the feasibility of using optical coherence tomography and optical coherence microscopy technology to assess human kidney morphology. MATERIALS AND 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.
PURPOSE: We evaluated the feasibility of using optical coherence tomography and optical coherence microscopy technology to assess human kidney morphology. MATERIALS AND 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: Osman O Ahsen; Yuankai K Tao; Benjamin M Potsaid; Yuri Sheikine; James Jiang; Ireneusz Grulkowski; Tsung-Han Tsai; Vijaysekhar Jayaraman; Martin F Kraus; James L Connolly; Joachim Hornegger; Alex Cable; James G Fujimoto Journal: Opt Express Date: 2013-07-29 Impact factor: 3.894
Authors: Hsiang-Chieh Lee; Jonathan J Liu; Yuri Sheikine; Aaron D Aguirre; James L Connolly; James G Fujimoto Journal: Biomed Opt Express Date: 2013-07-01 Impact factor: 3.732
Authors: Mei Wang; David B Tulman; Andrew B Sholl; Sree H Mandava; Michael M Maddox; Benjamin R Lee; J Quincy Brown Journal: J Biophotonics Date: 2017-10-05 Impact factor: 3.207