Biomedical subjects

A Mahadevan-Jansen

Publications and source records attributed to A Mahadevan-Jansen.

6 recordsLinked to original sources

PubMed2006

In vitro determination of normal and neoplastic human brain tissue optical properties using inverse adding-doubling.

To complement a project towards the development of real-time optical biopsy for brain tissue discrimination and surgical resection guidance, the optical properties of various brain tissues were measured in vitro and correlated to features within clinical diffuse reflectance tissue spectra measured in vivo. Reflectance and transmission spectra of in vitro brain tissue samples were measured with a single-integrating-sphere spectrometer for wavelengths 400-1300 nm and converted to absorption and reduced scattering spectra using an inverse adding-doubling technique. Optical property spectra were classified as deriving from white matter, grey matter or glioma tissue according to histopathologic diagnosis, and mean absorption and reduced scattering spectra were calculated for the three tissue categories. Absolute reduced scattering and absorption values and their relative differences between histopathological groups agreed with previously reported results with the exception that absorption coefficients were often overestimated, most likely due to biologic variability or unaccounted light loss during reflectance/transmission measurement. Absorption spectra for the three tissue classes were dominated by haemoglobin absorption below 600 nm and water absorption above 900 nm and generally determined the shape of corresponding clinical diffuse reflectance spectra. Reduced scattering spectral shapes followed the power curve predicted by the Rayleigh limit of Mie scattering theory. While tissue absorption governed the shape of clinical diffuse reflectance spectra, reduced scattering determined their relative emission intensities between the three tissue categories.

Algorithms↗

PubMed2001

In vivo brain tumor demarcation using optical spectroscopy.

The applicability of optical spectroscopy for intraoperative detection of brain tumors/tumor margins was investigated in a pilot clinical trial consisting of 26 brain tumor patients. The results of this clinical trial suggest that brain tumors and infiltrating tumor margins (ITM) can be effectively separated from normal brain tissues in vivo using combined autofluorescence and diffuse-reflectance spectroscopy. A two-step empirical discrimination algorithm based on autofluorescence and diffuse reflectance at 460 and 625 nm was developed. This algorithm yields a sensitivity and specificity of 100 and 76%, respectively, in differentiating ITM from normal brain tissues. Blood contamination was found to be a major obstacle that attenuates the accuracy of brain tumor demarcation using optical spectroscopy. Overall, this study indicates that optical spectroscopy has the potential to guide brain tumor resection intraoperatively with high sensitivity.

Adult↗

PubMed2000

Brain tumor demarcation using optical spectroscopy; an in vitro study.

Optical spectroscopy for brain tumor demarcation was investigated in this study. Fluorescence and diffuse reflectance spectra were measured from normal and tumorous human brain tissues in vitro. A fluorescence peak was consistently observed around 460 nm (+/- 10 nm) emission from both normal and tumorous brain tissues using 337 nm excitation. Intensity of this fluorescence peak (F460) from normal brain tissues was greater than that from primary brain tumorous tissues. In addition, diffuse reflectance (Rd) between 650 and 800 nm from white matter was significantly stronger than that from primary and secondary brain tumors. A good separation between gray matter and brain tumors was found using the ratio of F460 and Rd at 460 nm (Rd460). Two empirical discrimination algorithms based on F460, Rd625, and F460/Rd460 were developed. These algorithms yielded an average sensitivity and specificity of 96% and 93%, respectively.

Algorithms↗

PubMed1998

Near-infrared Raman spectroscopy for in vitro detection of cervical precancers.

In this study, we investigate the potential of near-infrared Raman spectroscopy to differentiate cervical precancers from normal tissues, inflammation and metaplasia and to differentially diagnose low-grade and high-grade precancers. Near infrared Raman spectra were measured from 36 biopsies from 18 patients in vitro. Detection algorithms were developed and evaluated relative to histopathologic examination. Algorithms based on empirically selected peak intensities, ratios of peak intensities and a combination of principal component analysis for data reduction and Fisher discriminant analysis for classification were investigated. Spectral peaks were tentatively identified from measured spectra of potential chromophores. Empirically selected normalized intensities can differentiate precancers from other tissues with an average sensitivity and specificity of 88 +/- 4% and 92 +/- 4%. Ratios of unnormalized intensities can differentiate precancers from other tissues with a sensitivity and specificity of 82% and 88% and high-grade from low-grade lesions with a sensitivity and specificity of 100%. Using multivariate methods, intensities at eight frequencies can be used to differentiate precancers from all other tissues with a sensitivity and specificity of 82% and 92% in an unbiased test. Raman algorithms can potentially separate benign abnormalities such as inflammation and metaplasia from precancers. Comparison of tissue spectra to published and measured chromophore spectra indicate that the most likely primary contributors to the tissue spectra are collagen, nucleic acids, phospholipids and glucose 1-phosphate. These results suggest that near-infrared Raman spectroscopy can be used for cervical precancer diagnosis and may be able to accurately separate samples with inflammation and metaplasia from precancer.

Cervix Uteri↗

PubMed1998

Development of a fiber optic probe to measure NIR Raman spectra of cervical tissue in vivo.

The goal of this study was to develop a compact fiber optic probe to measure near infrared Raman spectra of human cervical tissue in vivo for the clinical diagnosis of cervical precancers. A Raman spectrometer and fiber optic probe were designed, constructed and tested. The probe was first tested using standards with known Raman spectra, and then the probe was used to acquire Raman spectra from normal and precancerous cervical tissue in vivo. Raman spectra of cervical tissue could be acquired in vivo in 90 s using incident powers comparable to the threshold limit values for laser exposure of the skin. Although some silica signal obscured tissue Raman bands below 900 cm-1, Raman features from cervical tissue could clearly be discerned with an acceptable signal-to-noise ratio above 900 cm-1. The success of the Raman probe described here indicates that near infrared Raman spectra can be measured in vivo from cervical tissues. Increasing the power of the excitation source could reduce the integration time to below 20 s.

Biopsy↗

PubMed1996

Cervical precancer detection using a multivariate statistical algorithm based on laser-induced fluorescence spectra at multiple excitation wavelengths.

A portable fluorimeter was developed and utilized to acquire fluorescence spectra from 381 cervical sites in 95 patients at 337, 380 and 460 nm excitation immediately prior to colposcopy. A multivariate statistical algorithm was used to extract clinically useful information from tissue spectra acquired in vivo. Two full-parameter algorithms were developed using tissue fluorescence emission spectra at all three excitation wavelengths (161 excitation-emission wavelength pairs) for cervical precancer (squamous intraepithelial lesion [SIL]) detection: a screening algorithm that discriminates between SIL and non-SIL with a sensitivity of 82 +/- 1.4% and specificity of 68 +/- 0.0%, and a diagnostic algorithm that differentiates high-grade SIL from non-high-grade SIL with a sensitivity and specificity of 79 +/- 2% and 78 +/- 6%, respectively. Multivariate statistical analysis was also employed to reduce the number of fluorescence excitation-emission wavelength pairs needed to redevelop algorithms that demonstrate a minimum decrease in classification accuracy. Two reduced-parameter algorithms that employ fluorescence intensities at only 15 excitation-emission wavelength pairs were developed: the screening algorithm differentiates SIL from non-SIL with a sensitivity of 84 +/- 1.5% and specificity of 65 +/- 2% and the diagnostic algorithm discriminates high-grade SIL from non-high-grade SIL with a sensitivity and specificity of 78 +/- 0.7% and 74 +/- 2%, respectively. Both the full-parameter and reduced-parameter screening algorithms discriminate between SIL and non-SIL with a similar specificity (+/-5%) and a substantially improved sensitivity relative to Pap smear screening. A comparison of the full-parameter and reduced-parameter diagnostic algorithms to colposcopy in expert hands indicates that all three have a very similar sensitivity and specificity for differentiating high-grade SIL from non-high-grade SIL.

Algorithms↗