Optical scanning for rapid intraoperative diagnosis of sentinel node metastases in breast cancer

Keshtgar, Mohammed; Chicken, Dennis W.; Austwick, Martin Zaltz; Somasundaram, Santosh K.; Mosse, Charles A.; Zhu, Ying; Bigio, Irving J.; Bown, Stephen G.

doi:10.1002/bjs.7095

Cited by 26 publications

(17 citation statements)

References 19 publications

(29 reference statements)

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“…These techniques include fluorescence molecular imaging [7], elastic scattering spectroscopy [8,9] and optical coherence tomography (OCT) [10–13]. In previous studies, metastatic deposits in lymph nodes imaged with OCT were observed as regions of higher scattering relative to surrounding normal tissue, confirmed by comparison to histological sections [10,11].…”

Section: Introductionmentioning

confidence: 99%

Parametric imaging of the local attenuation coefficient in human axillary lymph nodes assessed using optical coherence tomography

Scolaro¹,

McLaughlin²,

Klyen³

et al. 2012

Biomed. Opt. Express

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We report the use of optical coherence tomography (OCT) to determine spatially localized optical attenuation coefficients of human axillary lymph nodes and their use to generate parametric images of lymphoid tissue. 3D-OCT images were obtained from excised lymph nodes and optical attenuation coefficients were extracted assuming a single scattering model of OCT. We present the measured attenuation coefficients for several tissue regions in benign and reactive lymph nodes, as identified by histopathology. We show parametric images of the measured attenuation coefficients as well as segmented images of tissue type based on thresholding of the attenuation coefficient values. Comparison to histology demonstrates the enhancement of contrast in parametric images relative to OCT images. This enhancement is a step towards the use of OCT for in situ assessment of lymph nodes.

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Section: Introductionmentioning

confidence: 99%

Parametric imaging of the local attenuation coefficient in human axillary lymph nodes assessed using optical coherence tomography

Scolaro¹,

McLaughlin²,

Klyen³

et al. 2012

Biomed. Opt. Express

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show abstract

“…Probing depths range from 0.5–2mm, depending on the tissue optical properties and source-to-detector distance in the array[27]. Initial efforts here and by others have employed stepper motors to raster scan the tissue sample across a more localized beam (100–200μm spot size), but significant limitations were imposed upon data acquisition time and field size [30, 31]. The Raman molecular fingerprint has also been used for point-based diagnostic sensing in the tumor resection cavity, first by Haka et al [26] and later by Keller et al [32], who demonstrated detection of breast cancers up to 2mm below a normal tissue layer with a spatially offset source-detector pair.…”

Section: Introductionmentioning

confidence: 99%

Scatter Spectroscopic Imaging Distinguishes between Breast Pathologies in Tissues Relevant to Surgical Margin Assessment

Laughney

Krishnaswamy

Rizzo

et al. 2012

Clinical Cancer Research

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Purpose A new approach to spectroscopic imaging was developed to detect and discriminate microscopic pathologies in resected breast tissues; diagnostic performance of the prototype system was tested in 27 tissues procured during breast conservative surgery. Experimental Design A custom-built, scanning in situ spectroscopy platform sampled broadband reflectance from a 150μm diameter spot over a 1×1cm2 field using a dark field geometry and telecentric lens; the system was designed to balance sensitivity to cellular morphology and imaging the inherent diversity within tissue subtypes. Nearly 300,000 broadband spectra were parameterized using light scattering models and spatially dependent spectral signatures were interpreted using a co-occurrence matrix representation of image texture. Results Local scattering changes distinguished benign from malignant pathologies with 94% accuracy, 93% sensitivity, 95% specificity, and 93% positive & 95% negative predictive values using a threshold-based classifier. Texture and shape features were important to optimally discriminate benign from malignant tissues, including pixel-to-pixel correlation, contrast and homogeneity, and the shape features of fractal dimension and Euler number. Analysis of the region-based diagnostic performance showed that spectroscopic image features from 1×1mm2 areas were diagnostically discriminant and enabled quantification of within-class tissue heterogeneities. Conclusions Localized scatter-imaging signatures detected by the scanning spectroscopy platform readily distinguished benign from malignant pathologies in surgical tissues and demonstrated new spectral-spatial signatures of clinical breast pathologies.

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“…Due to its ability to translate tissue morphology into spectral features at the cellular and sub‐cellular levels, ESS relates directly to the observed tissue architecture and structure of histopathologic features . Different tissue types and histopathological status exhibit specific optical signatures, and ESS has been demonstrated clinically to assess malignancy in multiple tissue types . Spectral correlation with histopathologic diagnosis using variations of ESS has also been reported by other groups .…”

Section: Introductionmentioning

confidence: 87%

Optical Spectroscopy as a Method for Skin Cancer Risk Assessment

Rodriguez‐Diaz

Manolakos

Christman

et al. 2019

Photochem & Photobiology

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Skin cancer is the most prevalent cancer, and its assessment remains a challenge for physicians. This study reports the application of an optical sensing method, elastic scattering spectroscopy (ESS), coupled with a classifier that was developed with machine learning, to assist in the discrimination of skin lesions that are concerning for malignancy. The method requires no special skin preparation, is non‐invasive, easy to administer with minimal training, and allows rapid lesion classification. This novel approach was tested for all common forms of skin cancer. ESS spectra from a total of 1307 lesions were analyzed in a multi‐center, non‐randomized clinical trial. The classification algorithm was developed on a 950‐lesion training dataset, and its diagnostic performance was evaluated against a 357‐lesion testing dataset that was independent of the training dataset. The observed sensitivity was 100% (14/14) for melanoma and 94% (105/112) for non‐melanoma skin cancer. The overall observed specificity was 36% (84/231). ESS has potential, as an adjunctive assessment tool, to assist physicians to differentiate between common benign and malignant skin lesions.

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Optical scanning for rapid intraoperative diagnosis of sentinel node metastases in breast cancer

Abstract: In this proof-of-principle study, the ESS results were comparable with current intraoperative diagnostic techniques of lymph node assessment.

Cited by 26 publications

References 19 publications

Parametric imaging of the local attenuation coefficient in human axillary lymph nodes assessed using optical coherence tomography

Parametric imaging of the local attenuation coefficient in human axillary lymph nodes assessed using optical coherence tomography

Scatter Spectroscopic Imaging Distinguishes between Breast Pathologies in Tissues Relevant to Surgical Margin Assessment

Optical Spectroscopy as a Method for Skin Cancer Risk Assessment

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