Dataset Information

Automated video-mosaicking approach for confocal microscopic imaging in vivo: an approach to address challenges in imaging living tissue and extend field of view.

ABSTRACT: We describe a computer vision-based mosaicking method for in vivo videos of reflectance confocal microscopy (RCM). RCM is a microscopic imaging technique, which enables the users to rapidly examine tissue in vivo. Providing resolution at cellular-level morphology, RCM imaging combined with mosaicking has shown to be highly sensitive and specific for non-invasively guiding skin cancer diagnosis. However, current RCM mosaicking techniques with existing microscopes have been limited to two-dimensional sequences of individual still images, acquired in a highly controlled manner, and along a specific predefined raster path, covering a limited area. The recent advent of smaller handheld microscopes is enabling acquisition of videos, acquired in a relatively uncontrolled manner and along an ad-hoc arbitrarily free-form, non-rastered path. Mosaicking of video-images (video-mosaicking) is necessary to display large areas of tissue. Our video-mosaicking methods addresses this need. The method can handle unique challenges encountered during video capture such as motion blur artifacts due to rapid motion of the microscope over the imaged area, warping in frames due to changes in contact angle and varying resolution with depth. We present test examples of video-mosaics of melanoma and non-melanoma skin cancers, to demonstrate potential clinical utility.

SUBMITTER: Kose K

PROVIDER: S-EPMC5589933 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Publications

Automated video-mosaicking approach for confocal microscopic imaging in vivo: an approach to address challenges in imaging living tissue and extend field of view.

Kose Kivanc K Gou Mengran M Yélamos Oriol O Cordova Miguel M Rossi Anthony M AM Nehal Kishwer S KS Flores Eileen S ES Camps Octavia O Dy Jennifer G JG Brooks Dana H DH Rajadhyaksha Milind M

Scientific reports 20170907 1

We describe a computer vision-based mosaicking method for in vivo videos of reflectance confocal microscopy (RCM). RCM is a microscopic imaging technique, which enables the users to rapidly examine tissue in vivo. Providing resolution at cellular-level morphology, RCM imaging combined with mosaicking has shown to be highly sensitive and specific for non-invasively guiding skin cancer diagnosis. However, current RCM mosaicking techniques with existing microscopes have been limited to two-dimensi ...[more]

PMID: 28883434

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Project description:BACKGROUND:The surgical removal of non-melanoma skin cancers (NMSCs) is guided by the pathologic examination of margins. However, the preparation of histopathology is time consuming, labour-intensive and requires separate laboratory infrastructure. Furthermore, when histopathology indicates positive margins, patients must return for re-excisions. Reflectance confocal microscopy (RCM) with a new video-mosaicking approach can noninvasively delineate margins directly on patients and potentially guide surgery in real-time, augmenting the traditional approaches of histopathology. OBJECTIVE:To assess a new peri-operative RCM video-mosaicking approach for comprehensive delineation of NMSC margins on patients in vivo. METHODS:Thirty-five patients undergoing Mohs micrographic surgery (MMS) in the Mohs surgery unit at Memorial Sloan Kettering Cancer Center, New York, NY were included in the study. RCM imaging was performed before and after the first staged excision by acquiring videos along the surgical margins (epidermal, peripheral and deep dermal) of each wound, which were subsequently processed into video-mosaics. Two RCM evaluators read and assessed video-mosaics, and subsequently compared to the corresponding Mohs frozen histopathology. RESULTS:Reflectance confocal microscopy videos and video-mosaics displayed acceptable imaging quality (resolution and contrast), pre-operatively in 32/35 (91%) NMSC lesions and intra-operatively in 29/35 lesions (83%). Pre-operative delineation of margins correlated with the histopathology in 32/35 (91%) lesions. Intra-operative delineation correlated in 10/14 (71%) lesions for the presence of residual tumour and in 18/21 (86%) lesions for absence. Sensitivity/specificity were 71%/86% and 86%/81% for two RCM video-mosaic evaluators, and overall agreement was 80% and 83% with histopathology, with moderate inter-evaluator agreement (k = 0.59, P ≤ 0.0002). CONCLUSIONS:Peri-operative RCM video-mosaicking of NMSC margins directly on patients may potentially guide surgery in real-time, serve as an adjunct to histopathology, reduce time spent in clinic and reduce the need for re-excisions. Further testing in larger studies is needed.

Dataset Information

Automated video-mosaicking approach for confocal microscopic imaging in vivo: an approach to address challenges in imaging living tissue and extend field of view.

Publications

Automated video-mosaicking approach for confocal microscopic imaging in vivo: an approach to address challenges in imaging living tissue and extend field of view.

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