Imaging in breast cancer: Diffuse optics in breast cancer: detecting tumors in pre-menopausal women and monitoring neoadjuvant chemotherapy

Diffuse optical spectroscopy (DOS) and diffuse optical imaging (DOI) are non-invasive diagnostic techniques that employ near-infrared (NIR) light to quantitatively characterize the optical properties of centimeter-thick, multiple-scattering tissues. Although NIR was first applied to breast diaphanography more than 70 years ago, quantitative optical methods employing time- or frequency-domain 'photon migration' technologies have only recently been used for breast imaging. Because their performance is not limited by mammographic density, optical methods can provide new insight regarding tissue functional changes associated with the appearance, progression, and treatment of breast cancer, particularly for younger women and high-risk subjects who may not benefit from conventional imaging methods. This paper reviews the principles of diffuse optics and describes the development of broadband DOS for quantitatively measuring the optical and physiological properties of thick tissues. Clinical results are shown highlighting the sensitivity of diffuse optics to malignant breast tumors in 12 pre-menopausal subjects ranging in age from 30 to 39 years and a patient undergoing neoadjuvant chemotherapy for locally advanced breast cancer. Significant contrast was observed between normal and tumor regions of tissue for deoxy-hemoglobin (p = 0.005), oxy-hemoglobin (p = 0.002), water (p = 0.014), and lipids (p = 0.0003). Tissue hemoglobin saturation was not found to be a reliable parameter for distinguishing between tumor and normal tissues. Optical data were converted into a tissue optical index that decreased 50% within 1 week in response to neoadjuvant chemotherapy. These results suggest a potential role for diffuse optics as a bedside monitoring tool that could aid the development of new strategies for individualized patient care

Predicting Breast Cancer Response to Neoadjuvant Chemotherapy Using Pretreatment Diffuse Optical Spectroscopic-Texture Analysis

Purpose: Diffuse optical spectroscopy (DOS) has been demonstrated capable of monitoring response to neoadjuvant chemotherapy (NAC) in locally advanced breast cancer (LABC) patients. In this study, we evaluate texture features of pre-treatment DOS functional maps for predicting LABC response to NAC. Methods: LABC patients (n = 37) underwent DOS-breast imaging before starting neoadjuvant chemotherapy. Breast-tissue parametric maps were constructed and texture analyses were performed based on grey level co-occurrence matrices (GLCM) for feature extraction. Ground-truth labels as responders (R) or non-responders (NR) were assigned to patients based on Miller-Payne pathological response criteria. The capability of DOS-textural features computed on volumetric tumour data before the start of treatment (i.e. “pre-treatment”) to predict patient responses to NAC was evaluated using a leave-one-out validation scheme at subject level. Data were analysed using a logistic regression, naïve Bayes, and k-nearest neighbour (k-NN) classifiers. Results: Data indicated that textural characteristics of pre-treatment DOS parametric maps can differentiate between treatment response outcomes. The HbO2-homogeneity resulted in the highest accuracy amongst univariate parameters in predicting response to chemotherapy: sensitivity (%Sn) and specificity (%Sp) were 86.5 and 89.0%, respectively and accuracy was 87.8%. The highest predictors using multivariate (binary) combination features were the Hb-Contrast + HbO2-Homogeneity which resulted in a %Sn/%Sp = 78.0/81.0% and an accuracy of 79.5%. Conclusions: This study demonstrated that pre-treatment tumour DOS-texture features can predict breast cancer response to NAC and potentially guide treatments

Using an oblique incident laser beam to measure the optical properties of stomach mucosa/submucosa tissue

<p>Abstract</p> <p>Background</p> <p>The purpose of the study is to determine the optical properties and their differences for normal human stomach mucosa/submucosa tissue in the cardiac orifice <it>in vitro </it>at 635, 730, 808, 890 and 980 nm wavelengths of laser.</p> <p>Methods</p> <p>The measurements were performed using a CCD detector, and the optical properties were assessed from the measurements using the spatially resolved reflectance, and nonlinear fitting of diffusion equation.</p> <p>Results</p> <p>The results of measurement showed that the absorption coefficients, the reduced scattering coefficients, the optical penetration depths, the diffusion coefficients, the diffuse reflectance and the shifts of diffuse reflectance of tissue samples at five different wavelengths vary with a change of wavelength. The maximum absorption coefficient for tissue samples is 0.265 mm^-1at 980 nm, and the minimum absorption coefficient is 0.0332 mm^-1at 730 nm, and the maximum difference in the absorption coefficients is 698% between 730 and 980 nm, and the minimum difference is 1.61% between 635 and 808 nm. The maximum reduced scattering coefficient for tissue samples is 1.19 mm^-1at 635 nm, and the minimum reduced scattering coefficient is 0.521 mm^-1at 980 nm, and the maximum difference in the reduced scattering coefficients is 128% between 635 and 980 nm, and the minimum difference is 1.15% between 890 and 980 nm. The maximum optical penetration depth for tissue samples is 3.57 mm at 808 nm, and the minimum optical penetration depth is 1.43 mm at 980 nm. The maximum diffusion constant for tissue samples is 0.608 mm at 890 nm, and the minimum diffusion constant is 0.278 mm at 635 nm. The maximum diffuse reflectance is 3.57 mm^-1at 808 nm, and the minimum diffuse reflectance is 1.43 mm^-1at 980 nm. The maximum shift Δx of diffuse reflectance is 1.11 mm^-1at 890 nm, and the minimum shift Δx of diffuse reflectance is 0.507 mm^-1at 635 nm.</p> <p>Conclusion</p> <p>The absorption coefficients, the reduced scattering coefficients, the optical penetration depths, the diffusion coefficients, the diffuse reflectance and the shifts of diffuse reflectance of tissue samples at 635, 730, 808, 890 and 980 nm wavelengths vary with a change of wavelength. There were significant differences in the optical properties for tissue samples at five different wavelengths (<it>P </it>< 0.01).</p

Non-randomness of the anatomical distribution of tumors

Background: Why does a tumor start where it does within an organ? Location is traditionally viewed as a random event, yet the statistics of the location of tumors argues against this being a random occurrence. There are numerous examples including that of breast cancer. More than half of invasive breast cancer tumors start in the upper outer quadrant of the breast near the armpit, even though it is estimated that only 35 to 40% of breast tissue is in this quadrant. This suggests that there is an unknown microenvironmental factor that significantly increases the risk of cancer in a spatial manner and that is not solely due to genes or toxins. We hypothesize that tumors are more prone to form in healthy tissue at microvascular ‘hot spots’ where there is a high local concentration of microvessels providing an increased blood flow that ensures an ample supply of oxygen, nutrients, and receptors for growth factors that promote the generation of new blood vessels. Results: To show the plausibility of our hypothesis, we calculated the fractional probability that there is at least one microvascular hot spot in each region of the breast assuming a Poisson distribution of microvessels in two-dimensional cross sections of breast tissue. We modulated the microvessel density in various regions of the breast according to the total hemoglobin concentration measured by near infrared diffuse optical spectroscopy in different regions of the breast. Defining a hot spot to be a circle of radius 200 μm with at least 5 microvessels, and using a previously measured mean microvessel density of 1 microvessel/mm2, we find good agreement of the fractional probability of at least one hot spot in different regions of the breast with the observed invasive tumor occurrence. However, there is no reason to believe that the microvascular distribution obeys a Poisson distribution. Conclusions: The spatial location of a tumor in an organ is not entirely random, indicating an unknown risk factor. Much work needs to be done to understand why a tumor occurs where it does. Electronic supplementary material The online version of this article (10.1186/s41236-017-0006-7) contains supplementary material, which is available to authorized users