Search

Your search keyword '"Saha, Anushree"' showing total 25 results
Start Over Author "Saha, Anushree"
25 results on '"Saha, Anushree"'

16. Raman spectroscopic sensing of carbonate intercalation in breast microcalcifications at stereotactic biopsy

Author

Massachusetts Institute of Technology. Department of Chemistry, Massachusetts Institute of Technology. Laser Biomedical Research Center, Massachusetts Institute of Technology. Spectroscopy Laboratory, Spegazzini, Nicolas, Dasari, Ramachandra Rao, Sathyavathi, R., Saha, Anushree, Soares, Jaqueline S., McGee, Sasha, Fitzmaurice, Maryann, Barman, Ishan, Massachusetts Institute of Technology. Department of Chemistry, Massachusetts Institute of Technology. Laser Biomedical Research Center, Massachusetts Institute of Technology. Spectroscopy Laboratory, Spegazzini, Nicolas, Dasari, Ramachandra Rao, Sathyavathi, R., Saha, Anushree, Soares, Jaqueline S., McGee, Sasha, Fitzmaurice, Maryann, and Barman, Ishan

Abstract

Microcalcifications are an early mammographic sign of breast cancer and frequent target for stereotactic biopsy. Despite their indisputable value, microcalcifications, particularly of the type II variety that are comprised of calcium hydroxyapatite deposits, remain one of the least understood disease markers. Here we employed Raman spectroscopy to elucidate the relationship between pathogenicity of breast lesions in fresh biopsy cores and composition of type II microcalcifications. Using a chemometric model of chemical-morphological constituents, acquired Raman spectra were translated to characterize chemical makeup of the lesions. We find that increase in carbonate intercalation in the hydroxyapatite lattice can be reliably employed to differentiate benign from malignant lesions, with algorithms based only on carbonate and cytoplasmic protein content exhibiting excellent negative predictive value (93–98%). Our findings highlight the importance of calcium carbonate, an underrated constituent of microcalcifications, as a spectroscopic marker in breast pathology evaluation and pave the way for improved biopsy guidance., National Institute for Biomedical Imaging and Bioengineering (U.S.) (9P41EB015871-27A1), Johns Hopkins University. Whiting School of Engineering, National Cancer Institute (U.S.) (R01-CA140288)

Published
2015

19. Development and comparative assessment of Raman spectroscopic classification algorithms for lesion discrimination in stereotactic breast biopsies with microcalcifications

Author

Dingari, Narahara Chari, primary, Barman, Ishan, additional, Saha, Anushree, additional, McGee, Sasha, additional, Galindo, Luis H., additional, Liu, Wendy, additional, Plecha, Donna, additional, Klein, Nina, additional, Dasari, Ramachandra Rao, additional, and Fitzmaurice, Maryann, additional

Published
2012
Full Text
View/download PDF

25. Development and comparative assessment of Raman spectroscopic classification algorithms for lesion discrimination in stereotactic breast biopsies with microcalcifications.

Author

Dingari, Narahara Chari, Barman, Ishan, Saha, Anushree, McGee, Sasha, Galindo, Luis H., Liu, Wendy, Plecha, Donna, Klein, Nina, Dasari, Ramachandra Rao, and Fitzmaurice, Maryann

Abstract

Microcalcifications are an early mammographic sign of breast cancer and a target for stereotactic breast needle biopsy. Here, we develop and compare different approaches for developing Raman classification algorithms to diagnose invasive and in situ breast cancer, fibrocystic change and fibroadenoma that can be associated with microcalcifications. In this study, Raman spectra were acquired from tissue cores obtained from fresh breast biopsies and analyzed using a constituent-based breast model. Diagnostic algorithms based on the breast model fit coefficients were devised using logistic regression, C4.5 decision tree classification, k-nearest neighbor ( k -NN) and support vector machine (SVM) analysis, and subjected to leave-one-out cross validation. The best performing algorithm was based on SVM analysis (with radial basis function), which yielded a positive predictive value of 100% and negative predictive value of 96% for cancer diagnosis. Importantly, these results demonstrate that Raman spectroscopy provides adequate diagnostic information for lesion discrimination even in the presence of microcalcifications, which to the best of our knowledge has not been previously reported. (© 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [ABSTRACT FROM AUTHOR]

Published
2013
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results