55 research outputs found

    Quantitative birefringence microscopy for imaging the structural integrity of CNS myelin following circumscribed cortical injury in the rhesus monkey

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    Significance: Myelin breakdown is likely a key factor in the loss of cognitive and motor function associated with many neurodegenerative diseases. Aim: New methods for imaging myelin structure are needed to characterize and quantify the degradation of myelin in standard whole-brain sections of nonhuman primates and in human brain. Approach: Quantitative birefringence microscopy (qBRM) is a label-free technique for rapid histopathological assessment of myelin structural breakdown following cortical injury in rhesus monkeys. Results: We validate birefringence microscopy for structural imaging of myelin in rhesus monkey brain sections, and we demonstrate the power of qBRM by characterizing the breakdown of myelin following cortical injury, as a model of stroke, in the motor cortex. Conclusions: Birefringence microscopy is a valuable tool for histopathology of myelin and for quantitative assessment of myelin structure. Compared to conventional methods, this label-free technique is sensitive to subtle changes in myelin structure, is fast, and enables more quantitative assessment, without the variability inherent in labeling procedures such as immunohistochemistry.Published versio

    Diagnosis of breast cancer using elastic-scattering spectroscopy: preliminary clinical results

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    We report on the first stages of a clinical study designed to test elastic-scattering spectroscopy, mediated by fiberoptic probes, for three specific clinical applications in breast-tissue diagnosis: (1) a transdermal-needle (interstitial) measurement for instant diagnosis with minimal invasiveness similar to fine-needle aspiration but with sensitivity to a larger tissue volume, (2) a hand-held diagnostic probe for use in assessing tumor/resection margins during open surgery, and (3) use of the same probe for real-time assessment of the `sentinel' node during surgery to determine the presence or absence of tumor (metastatic). Preliminary results from in vivo measurements on 31 women are encouraging. Optical spectra were measured on 72 histology sites in breast tissue, and 54 histology sites in sentinel nodes. Two different artificial intelligence methods of spectral classification were studied. Artificial neural networks yielded sensitivities of 69% and 58%, and specificities of 85% and 93%, for breast tissue and sentinel nodes, respectively. Hierarchical cluster analysis yielded sensitivities of 67% and 91%, and specificities of 79% and 77%, for breast tissue and sentinel nodes, respectively. These values are expected to improve as the data sets continue to grow and more sophisticated data preprocessing is employed. The study will enroll up to 400 patients over the next two years

    A Partially Supervised Bayesian Image Classification Model with Applications in Diagnosis of Sentinel Lymph Node Metastases in Breast Cancer

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    A method has been developed for the analysis of images of sentinel lymph nodes generated by a spectral scanning device. The aim is to classify the nodes, excised during surgery for breast cancer, as normal or metastatic. The data from one node constitute spectra at 86 wavelengths for each pixel of a 20*20 grid. For the analysis, the spectra are reduced to scores on two factors, one derived externally from a linear discriminant analysis using spectra taken manually from known normal and metastatic tissue, and one derived from the node under investigation to capture variability orthogonal to the external factor. Then a three-group mixture model (normal, metastatic, non-nodal background) using multivariate t distributions is fitted to the scores, with external data being used to specify informative prior distributions for the parameters of the three distributions. A Markov random field prior imposes smoothness on the image generated by the model. Finally, the node is classified as metastatic if any one pixel in this smoothed image is classified as metastatic. The model parameters were tuned on a training set of nodes, and then the tuned model was tested on a separate validation set of nodes, achieving satisfactory sensitivity and specificity. The aim in developing the analysis was to allow flexibility in the way each node is modelled whilst still using external information. The Bayesian framework employed is ideal for this.Comment: 31 pages, 7 figure

    Towards minimally-invasive, quantitative assessment of chronic kidney disease using optical spectroscopy

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    The universal pathologic features implicated in the progression of chronic kidney disease (CKD) are interstitial fibrosis and tubular atrophy (IFTA). Current methods of estimating IFTA are slow, labor-intensive and fraught with variability and sampling error, and are not quantitative. As such, there is pressing clinical need for a less-invasive and faster method that can quantitatively assess the degree of IFTA. We propose a minimally-invasive optical method to assess the macro-architecture of kidney tissue, as an objective, quantitative assessment of IFTA, as an indicator of the degree of kidney disease. The method of elastic-scattering spectroscopy (ESS) measures backscattered light over the spectral range 320-900 nm and is highly sensitive to micromorphological changes in tissues. Using two discrete mouse models of CKD, we observed spectral trends of increased scattering intensity in the near-UV to short-visible region (350-450 nm), relative to longer wavelengths, for fibrotic kidneys compared to normal kidney, with a quasi-linear correlation between the ESS changes and the histopathology-determined degree of IFTA. These results suggest the potential of ESS as an objective, quantitative and faster assessment of IFTA for the management of CKD patients and in the allocation of organs for kidney transplantation.T32 HL007224 - NHLBI NIH HHS; R01 CA175382 - NCI NIH HHS; T32 GM086308 - NIGMS NIH HHS; R01 HL132325 - NHLBI NIH HHS; UL1 TR001430 - NCATS NIH HHSAccepted manuscriptPublished versio

    Temporal Variations of Skin Pigmentation in C57Bl/6 Mice Affect Optical Bioluminescence Quantitation

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    ABSTRACT PURPOSE: Depilation-induced skin pigmentation in C57Bl/6 mice is a known occurrence, and presents a unique problem for quantitative optical imaging of small animals, especially for bioluminescence. The work reported here quantitatively investigated the optical attenuation of bioluminescent light due to melanin pigmentation in the skin of transgenic C57B1/6 mice, modified such that luciferase expression is under the transcription control of a physiologically and pharmacologically inducible gene. PROCEDURE: Both in vivo and ex vivo experiments were performed to track bioluminescence signal attenuation through different stages of the mouse hair growth cycle. Simultaneous reflectance measurements were collected in vivo to estimate melanin levels. RESULTS: Biological variability of skin pigmentation was found to dramatically affect collected bioluminescent signal emerging through the skin of the mice. When compared to signal through skin with no pigmentation, the signal through highly-pigmented skin was attenuated an average of 90%. Correlation of reflectance signals to bioluminescence signal loss forms the basis of the proposed correction method. We observed, however, that variability in tissue composition, which results in inconsistent reflectance spectra, limits the accuracy of the correction method but can be improved by incorporating more complex analysis. CONCLUSION: Skin pigmentation is a significant variable in bioluminescent imaging, and should be considered in experimental design and implementation for longitudinal studies, and especially when sensitivity to small signal changes, or differences among animals, is required

    The color of cancer: margin guidance for oral cancer resection using elastic scattering spectroscopy

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    Published in final edited form as: Laryngoscope. 2017 September ; 127(Suppl 4): S1–S9. doi:10.1002/lary.26763.OBJECTIVES/HYPOTHESIS: To evaluate the usefulness of elastic scattering spectroscopy (ESS) as a diagnostic adjunct to frozen section analysis in patients with diagnosed squamous cell carcinoma of the oral cavity. STUDY DESIGN: Prospective analytic study. METHODS: Subjects for this single institution, institutional review board-approved study were recruited from among patients undergoing surgical resection for squamous cell cancer of the oral cavity. A portable ESS device with a contact fiberoptic probe was used to obtain spectral signals. Four to 10 spectral readings were obtained on each subject from various sites including gross tumor and normal-appearing mucosa in the surgical margin. Each reading was correlated with the histopathologic findings of biopsies taken from the exact location of the spectral readings. A diagnostic algorithm based on multidimensional pattern recognition/machine learning was developed. Sensitivity and specificity, error rate, and area under the curve were used as performance metrics for tests involving classification between disease and nondisease classes. RESULTS: Thirty-four (34) subjects were enrolled in the study. One hundred seventy-six spectral data point/biopsy specimen pairs were available for analysis. ESS distinguished normal from abnormal tissue, with a sensitivity ranging from 84% to 100% and specificity ranging from 71% to 89%, depending on how the cutoff between normal and abnormal tissue was defined (i.e., mild, moderate, or severe dysplasia). There were statistically significant differences in malignancy scores between histologically normal tissue and invasive cancer and between noninflamed tissue and inflamed tissue. CONCLUSIONS: This is the first study to evaluate the effectiveness of ESS in guiding mucosal resection margins in oral cavity cancer. ESS provides fast, real-time assessment of tissue without the need for pathology expertise. ESS appears to be effective in distinguishing between normal mucosa and invasive cancer and between "normal" tissue (histologically normal and mild dysplasia) and "abnormal" tissue (severe dysplasia and carcinoma in situ) that might require further margin resection. Further studies, however, are needed with a larger sample size to validate these findings and to determine the effectiveness of ESS in distinguishing visibly and histologically normal tissue from visibly normal but histologically abnormal tissue. LEVEL OF EVIDENCE: NA Laryngoscope, 127:S1-S9, 2017.R21 DE023192 - NIDCR NIH HHSAccepted manuscrip

    At the frontiers of surgery: review

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    The complete surgical removal of disease is a desirable outcome particularly in oncology. Unfortunately much disease is microscopic and difficult to detect causing a liability to recurrence and worsened overall prognosis with attendant costs in terms of morbidity and mortality. It is hoped that by advances in optical diagnostic technology we could better define our surgical margin and so increase the rate of truly negative margins on the one hand and on the other hand to take out only the necessary amount of tissue and leave more unaffected non-diseased areas so preserving function of vital structures. The task has not been easy but progress is being made as exemplified by the presentations at the 2nd Scientific Meeting of the Head and Neck Optical Diagnostics Society (HNODS) in San Francisco in January 2010. We review the salient advances in the field and propose further directions of investigation
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