Non-invasive optical estimate of tissue composition to differentiate malignant from benign breast lesions: A pilot study

Widefield ultra-high-density optical breast tomography system supplementing x-ray mammography

We report a wide-field compressive diffuse optical tomography (DOT) system - optical mammography co-imager (OMCI) - which aims to augment tens of thousands of existing x-ray mammography or tomosynthesis systems worldwide by adding functional assessment of breast tissue and improve cancer diagnosis. The OMCI system utilizes large field-of-view structured light illumination and single-pixel-camera based detection techniques to produce ultra-high spatial sampling density while ensuring that the inverse problem remains compact via the development of a unique target-adaptive pattern optimization technique to achieve compressive-sensing based measurements. The reconstructed images can be further enhanced by applying a compositional-prior-guided DOT reconstruction algorithm with tissue structural priors derived from a separately acquired x-ray mammography scans. In this report, we describe the design details and performance characterization of the imaging hardware as well as DOT image reconstruction pipelines. To validate this multi-modal breast DOT system, we include reconstruction results from both tissue-mimicking optical phantoms as well as clinical measurements from normal breasts obtained from a clinical study. Sample reconstructions from a breast containing a malignant tumor are also included, showing the potential of localizing and characterizing breast lesions using multi-modal measurements combining x-ray and DOT.

A 675 nm Laser in the Treatment of Facial Melasma in Dark Skin Types

Background: Melasma therapy can be difficult and requires employing different treatment approaches. Laser therapy is a good alternative for treating melasma, especially for patients with refractory cases. Objective: To evaluate the efficacy and safety of newcomer wavelength 675 nm diode laser in treating melasma in darker skin types. Methods: Nineteen female patients with facial melasma were recruited. They received four sessions of 675 nm laser at one-month intervals using the following parameters: power 5-6 W, pulse duration 100-150 ms, spacing 2000 mm, and stack one up to 4 passes. One month after the last treatment session, the evaluation was done subjectively through the modified melasma area and severity index (mMASI) score and objectively using the Antera 3D camera. Results: After treatment, there was a highly statistically significant reduction in mMASI scores. In addition, the scores on the Antera camera recorded highly statistically significant differences in the treated areas' melanin and hemoglobin average levels. Conclusion: The novel 675 nm laser represents a safe and efficient approach in treating melasma in darker phototype patients.

Comparison of red and green light for treating non-muscle invasive bladder cancer in rats using singlet oxygen-cleavable prodrugs with PPIX-PDT

It has been 30 years since Photofrin-PDT was approved for the treatment of bladder cancer in Canada. However, Photofrin-PDT failed to gain popularity due to bladder complications. The PDT with red light and IV-administered Photofrin could permanently damage the bladder muscle. We have been developing a new combination strategy of PpIX-PDT with singlet oxygen-cleavable prodrugs for NMIBC with minimal side effects, avoiding damage to the bladder muscle layer. PpIX can be excited by either green (532 nm) or red (635 nm) light. Red light could be more efficacious in vivo due to its deeper tissue penetration than green light. Since HAL preferentially produces PpIX in tumors, we hypothesized that illuminating PpIX with red light might spare the muscle layer. PpIX-PDT was used to compare green and red laser efficacy in vitro and in vivo. The IC50 of in vitro PpIX-PDT was 18 mW/cm2 with the red laser and 22 mW/cm2 with the green laser. The in vivo efficacy of the red laser with 50, 75, and 100 mW total dose was similar to the same dose of green laser in reducing tumor volume. Combining PpIX-PDT with prodrugs methyl-linked mitomycin C (Mt-L-MMC) and rhodamine-linked SN-38 (Rh-L-SN-38) significantly improved efficacy (tumor volume comparison). PpIX-PDT or PpIX-PDT + prodrug combination did not cause muscle damage in histological analysis. Overall, a combination of PpIX-PDT and prodrug with 635 nm laser is promising for non-muscle invasive bladder cancer treatment.

In vivo optimization of the experimental conditions for the non-invasive optical assessment of breast density

In this study, time domain diffuse optical spectroscopy is performed in the range 600-1100 nm on 11 healthy volunteers with a portable system for the quantitative characterization of breast tissue in terms of optical properties and optically-derived blood parameters, tissue constituent concentrations, and scattering parameters. A measurement protocol involving different geometries (reflectance and transmittance), subject's positions (sitting and lying down), probing locations (outer, lower, and inner breast quadrants), and source-detector distances (2 and 3 cm) allowed us to investigate the effect of tissue heterogeneity and different measurement configurations on the results with the aim of identifying the best experimental conditions for the estimate of breast density (i.e., amount of fibro-glandular tissue in the breast) as a strong independent risk factor for breast cancer. Transmittance results, that in previous studies correlated strongly with mammographic density, are used as a reference for the initial test of the simpler and more comfortable reflectance measurement configuration. The higher source-detector distance, which probes deeper tissue, retrieves optical outcomes in agreement with higher average density tissue. Similarly, results on the outer quadrants indicate higher density than internal quadrants. These findings are coherent with breast anatomy since the concentration of dense fibro-glandular stroma is higher in deep tissue and towards the external portion of the breast, where the mammary gland is located. The dataset generated with this laboratory campaign is used to device an optimal measurement protocol for a future clinical trial, where optical results will be correlated with conventional mammographic density, allowing us to identify a subset of wavelengths and measurement configurations for an effective estimate of breast density. The final objective is the design of a simplified, compact and cost-effective optical device for a non-invasive, routine assessment of density-associated breast cancer risk.

Improving diffuse optical tomography imaging quality using APU-Net: an attention-based physical U-Net model

Significance

Traditional diffuse optical tomography (DOT) reconstructions are hampered by image artifacts arising from factors such as DOT sources being closer to shallow lesions, poor optode-tissue coupling, tissue heterogeneity, and large high-contrast lesions lacking information in deeper regions (known as shadowing effect). Addressing these challenges is crucial for improving the quality of DOT images and obtaining robust lesion diagnosis.

Aim

We address the limitations of current DOT imaging reconstruction by introducing an attention-based U-Net (APU-Net) model to enhance the image quality of DOT reconstruction, ultimately improving lesion diagnostic accuracy.

Approach

We designed an APU-Net model incorporating a contextual transformer attention module to enhance DOT reconstruction. The model was trained on simulation and phantom data, focusing on challenges such as artifact-induced distortions and lesion-shadowing effects. The model was then evaluated by the clinical data.

Results

Transitioning from simulation and phantom data to clinical patients' data, our APU-Net model effectively reduced artifacts with an average artifact contrast decrease of 26.83% and improved image quality. In addition, statistical analyses revealed significant contrast improvements in depth profile with an average contrast increase of 20.28% and 45.31% for the second and third target layers, respectively. These results highlighted the efficacy of our approach in breast cancer diagnosis.

Conclusions

The APU-Net model improves the image quality of DOT reconstruction by reducing DOT image artifacts and improving the target depth profile.

Monitoring of neoadjuvant chemotherapy through time domain diffuse optics: breast tissue composition changes and collagen discriminative potential

The purpose of this clinical study is to test a broad spectral range (635-1060 nm) time-domain diffuse optical spectroscopy in monitoring the response of breast cancer patients to neoadjuvant chemotherapy (NAC). The broadband operation allows us to fully analyze tissue composition in terms of hemoglobin, water, lipids and collagen concentration, which has never been systematically studied until now during the course of therapy. Patients are subjected to multiple breast optical imaging sessions, each one performed at different stages of NAC, both on tumor-bearing and contralateral healthy breasts. We correlate the optical results with conventional imaging techniques and pathological response. Preliminary outcomes on 10 patients' data show an average significant reduction in the concentrations of oxy-hemoglobin (-53%, p = 0.0020), collagen (-36%, p = 0.0039) and water (-15%, p = 0.0195), and increase in lipids (+39%, p = 0.0137) from baseline to the end of therapy in the tumor-bearing breast of patients who responded to therapy at least partially. With respect to scattering, the scattering amplitude, a, increases slightly (+15%, p = 0.0039) by the end of the therapy compared to the baseline, while the scattering slope, b, shows no significant change (+4%, p = 0.9219). Some change in the constituents' concentrations was also noticed in the contralateral healthy breast, even though it was significant only for oxy-hemoglobin concentration. We observed that collagen seems to be the only component distinguishing between complete and partial responders by the end of 2-3 weeks from the baseline. In the complete responder group, collagen significantly decreased after 2-3 weeks with respect to baseline (p = 0.0423). While the partial responder group also showed a decrease, it did not reach statistical significance (p = 0.1012). This suggests that collagen could serve as a potential biomarker to measure NAC effectiveness early during treatment. Even though obtained on a small group of patients, these initial results are consistent with those of standard medical modalities and highlight the sensitivity of the technique to changes that occur in breast composition during NAC.

Deep orthogonal multi-wavelength fusion for tomogram-free diagnosis in diffuse optical imaging

Novel portable diffuse optical tomography (DOT) devices for breast cancer lesions hold great promise for non-invasive, non-ionizing breast cancer screening. Critical to this capability is not just the identification of lesions but rather the complex problem of discriminating between malignant and benign lesions. To accurately reconstruct the highly heterogeneous tissue of a cancer lesion in healthy breast tissue using DOT, multiple wavelengths can be leveraged to maximize signal penetration while minimizing sensitivity to noise. However, these wavelength responses can overlap, capture common information, and correlate, potentially confounding reconstruction and downstream end tasks. We show that an orthogonal fusion loss regularizes multi-wavelength DOT leading to improved reconstruction and accuracy of end-to-end discrimination of malignant versus benign lesions. We further show that our raw-to-task model significantly reduces computational complexity without sacrificing accuracy, making it ideal for real-time throughput, desired in medical settings where handheld devices have severely restricted power budgets. Furthermore, our results indicate that image reconstruction is not necessary for unbiased classification of lesions with a balanced accuracy of 77% and 66% on the synthetic dataset and clinical dataset, respectively, using the raw-to-task model. Code is available at https://github.com/sfu-mial/FuseNet.

MamoRef: an optical mammography device using whole-field CW diffuse reflectance. Presentation, validation and preliminary clinical results

Objective.MamoRef is an mammography device that uses near-infrared light, designed to provide clinically relevant information for the screening of diseases of the breast. Using low power continuous wave lasers and a high sensitivity CCD (Charge-coupled device) that captures a diffusely reflected image of the tissue, MamoRef results in a versatile diagnostic tool that aims to fulfill a complementary role in the diagnosis of breast cancer providing information about the relative hemoglobin concentrations as well as oxygen saturation.Approach.We present the design and development of an initial prototype of MamoRef. To ensure its effectiveness, we conducted validation tests on both the theoretical basis of the reconstruction algorithm and the hardware design. Furthermore, we initiated a clinical feasibility study involving patients diagnosed with breast disease, thus evaluating the practical application and potential benefits of MamoRef in a real-world setting.Main results.Our study demonstrates the effectiveness of the reconstruction algorithm in recovering relative concentration differences among various chromophores, as confirmed by Monte Carlo simulations. These simulations show that the recovered data correlates well with the ground truth, with SSIMs of 0.8 or more. Additionally, the phantom experiments validate the hardware implementation. The initial clinical findings exhibit highly promising outcomes regarding MamoRef's ability to differentiate between lesions.Significance.MamoRef aims to be an advancement in the field of breast pathology screening and diagnostics, providing complementary information to standard diagnostic techniques. One of its main advantages is the ability of determining oxy/deoxyhemoglobin concentrations and oxygen saturation; this constitutes valuable complementary information to standard diagnostic techniques. Besides, MamoRef is a portable and relatively inexpensive device, intended to be not only used in specific medical imaging facilities. Finally, its use does not require external compression of the breast. The findings of this study underscore the potential of MamoRef in fulfilling this crucial role.

Biophotonics as a new application in optical technology: A bibliometric analysis

Biophotonics procures wide practicability in life sciences and medicines. The contribution of biophotonics is well recognized in various Nobel Prizes. Therefore, this paper aims to conduct a bibliometric analysis of biophotonics publications. The scientific database used is the Web of Science database. Harzing's Publish or Perish and VOSviewer are the bibliometric tools used in this analysis. This study found an increasing trend in the number of publications in recent years as the number of publications peaked at 347 publications in 2020. Most of the documents are articles (3361 publications) and proceeding papers (1632 publications). The top three subject areas are Optics (3206 publications), Engineering (1706 publications) and Radiology, Nuclear Medicine, and Medical Imaging (1346 publications). The United States has the highest number of publications (2041 publications) and citation impact (38.07 citations per publication; h-index: 125). The top three publication titles are Proceedings of SPIE (920 publications), Journal of Biomedical Optics (599 publications), and Proceedings of the Society of Photo Optical Instrumentation Engineers SPIE (245 publications). The potential areas for future research include to overcome the optical penetration depth issue and to develop publicly available biosensors for the detection of common diseases.

Efficient algorithm to calculate the optical properties of breast tumors by high-order perturbation theory

An efficient algorithm to obtain the solutions for n-th order terms of perturbation expansions in absorption, scattering, and cross-coupling for light propagating in human tissue is presented. The proposed solution is free of any approximations and makes possible fast and efficient estimates of mammographic, optical tomographic, and fluorescent images, applying a perturbation order of 30 and more. The presented analysis sets the general limits for the applicability of the perturbation approach as a function of tumor size and optical properties of the human tissue. The convergence tests of the efficient calculations for large absorbing objects show excellent agreement with the reference data from finite element method calculations. The applicability of the theory is demonstrated in experiments on breast-like phantoms with high absorbing and low-scattering lesions.

Breast Cancer Diagnosis Using Extended-Wavelength-Diffuse Reflectance Spectroscopy (EW-DRS)-Proof of Concept in Ex Vivo Breast Specimens Using Machine Learning

This study aims to investigate the feasibility of using diffuse reflectance spectroscopy (DRS) to distinguish malignant breast tissue from adjacent healthy tissue, and to evaluate if an extended-wavelength range (450-1550 nm) has an advantage over the standard wavelength range (450-900 nm). Multivariate statistics and machine learning algorithms, either linear discriminant analysis (LDA) or support vector machine (SVM) are used to distinguish the two tissue types in breast specimens (total or partial mastectomy) from 23 female patients with primary breast cancer. EW-DRS has a sensitivity of 94% and specificity of 91% as compared to a sensitivity of 40% and specificity of 71% using the standard wavelength range. The results suggest that DRS can discriminate between malignant and healthy breast tissue, with improved outcomes using an extended wavelength. It is also possible to construct a simple analytical model to improve the diagnostic performance of the DRS technique.

The 675-nm wavelength for treating facial melasma

BACKGROUND

Melasma is an acquired skin problem. It characterises sun-exposed areas, particularly on the face, with irregular borders and bilateral distribution. With this study, we want to strengthen the scientific literature regarding the use of a 675-nm laser device for the treatment of women and men with facial melasma pigmentary and vascular symptoms.

MATERIALS AND METHODS

Eighteen patients were treated for facial melasma. A total of three sessions at 30-day intervals were performed with a 675-nm laser device. A five-point Global Aesthetic Improvement Scale was used to separately assess the improvement of the patient's skin 3 months after the last treatment (T1) compared to baseline (T0). The pain during treatment was measured using a Visual Analog Scale of 10 points. The non-ablative laser system used emits red light with a wavelength of 675 nm through a 13 × 13 mm scanning system.

RESULTS

At T1 , a consistent improvement in the pigmentary and vascular components was visible. This is always combined with a considerable reduction in vascular expression.

CONCLUSION

Our research shows that individuals with Fitzpatrick phototypes II to III can treat facial melasma with the 675-nm laser source system without risk. Due to its interaction with melanin, collagen and haemoglobin chromophores, as well as its excellent capacity to penetrate tissues with less heating, this system is promising in the treatment of pigmentary and vascular illnesses such as melasma. The great success of the technology we used came from the reduced levels of inflammation produced after the treatments and the low energy level implied.

Design of a Low-Cost Diffuse Optical Mammography System for Biomedical Image Processing in Breast Cancer Diagnosis

Worldwide, breast cancer is the most common type of cancer that mainly affects women. Several diagnosis techniques based on optical instrumentation and image analysis have been developed, and these are commonly used in conjunction with conventional diagnostic devices such as mammographs, ultrasound, and magnetic resonance imaging of the breast. The cost of using these instruments is increasing, and developing countries, whose deaths indices due to breast cancer are high, cannot access conventional diagnostic methods and have even less access to newer techniques. Other studies, based on the analysis of images acquired by traditional methods, require high resolutions and knowledge of the origin of the captures in order to avoid errors. For this reason, the design of a low-cost diffuse optical mammography system for biomedical image processing in breast cancer diagnosis is presented. The system combines the acquisition of breast tissue photographs, diffuse optical reflectance (as a biophotonics technique), and the processing of digital images for the study and diagnosis of breast cancer. The system was developed in the form of a medical examination table with a 638 nm red-light source, using light-emitted diode technology (LED) and a low-cost web camera for the acquisition of breast tissue images. The system is automatic, and its control, through a graphical user interface (GUI), saves costs and allows for the subsequent analysis of images using a digital image-processing algorithm. The results obtained allow for the possibility of planning in vivo measurements. In addition, the acquisition of images every 30° around the breast tissue could be used in future research in order to perform a three-dimensional (3D) reconstruction and an analysis of the captures through deep learning techniques. These could be combined with virtual, augmented, or mixed reality environments to predict the position of tumors, increase the likelihood of a correct medical diagnosis, and develop a training system for specialists. Furthermore, the system allows for the possibility to develop analysis of optical characterization for new phantom studies in breast cancer diagnosis through bioimaging techniques.

A feasibility study on deep-neural-network-based dose-neutral dual-energy digital breast tomosynthesis

BACKGROUND

Diagnostic performance based on x-ray breast imaging is subject to breast density. Although digital breast tomosynthesis (DBT) is reported to outperform conventional mammography in denser breasts, mass detection and malignancy characterization are often considered challenging yet.

PURPOSE

As an improved diagnostic solution to the dense breast cases, we propose a dual-energy DBT imaging technique that enables breast compositional imaging at comparable scanning time and patient dose compared to the conventional single-energy DBT.

METHODS

The proposed dual-energy DBT acquires projection data by alternating two different energy spectra. Then, we synthesize unmeasured projection data using a deep neural network that exploits the measured projection data and adjacent projection data obtained under the other x-ray energy spectrum. For material decomposition, we estimate partial path lengths of an x-ray through water, lipid, and protein from the measured and the synthesized projection data with the object thickness information. After material decomposition in the projection domain, we reconstruct material-selective DBT images. The deep neural network is trained with the numerical breast phantoms. A pork meat phantom is scanned with a prototype dual-energy DBT system to demonstrate the feasibility of the proposed imaging method.

RESULTS

The developed deep neural network successfully synthesized missing projections. Material-selective images reconstructed from the synthesized data present comparable compositional contrast of the cancerous masses compared with those from the fully measured data.

CONCLUSIONS

The proposed dual-energy DBT scheme is expected to substantially contribute to enhancing mass malignancy detection accuracy particularly in dense breasts.

How much do time-domain functional near-infrared spectroscopy (fNIRS) moments improve estimation of brain activity over traditional fNIRS?

SIGNIFICANCE

Advances in electronics have allowed the recent development of compact, high channel count time domain functional near-infrared spectroscopy (TD-fNIRS) systems. Temporal moment analysis has been proposed for increased brain sensitivity due to the depth selectivity of higher order temporal moments. We propose a general linear model (GLM) incorporating TD moment data and auxiliary physiological measurements, such as short separation channels, to improve the recovery of the HRF.

AIMS

We compare the performance of previously reported multi-distance TD moment techniques to commonly used techniques for continuous wave (CW) fNIRS hemodynamic response function (HRF) recovery, namely block averaging and CW GLM. Additionally, we compare the multi-distance TD moment technique to TD moment GLM.

APPROACH

We augmented resting TD-fNIRS moment data (six subjects) with known synthetic HRFs. We then employed block averaging and GLM techniques with "short-separation regression" designed both for CW and TD to recover the HRFs. We calculated the root mean square error (RMSE) and the correlation of the recovered HRF to the ground truth. We compared the performance of equivalent CW and TD techniques with paired t-tests.

RESULTS

We found that, on average, TD moment HRF recovery improves correlations by 98% and 48% for HbO and HbR respectively, over CW GLM. The improvement on the correlation for TD GLM over TD moment is 12% (HbO) and 27% (HbR). RMSE decreases 56% and 52% (HbO and HbR) for TD moment compared to CW GLM. We found no statistically significant improvement in the RMSE for TD GLM compared to TD moment.

CONCLUSIONS

Properly covariance-scaled TD moment techniques outperform their CW equivalents in both RMSE and correlation in the recovery of the synthetic HRFs. Furthermore, our proposed TD GLM based on moments outperforms regular TD moment analysis, while allowing the incorporation of auxiliary measurements of the confounding physiological signals from the scalp.

Investigating the feasibility of a hand-held photoacoustic imaging probe for margin assessment during breast conserving surgery

Approximately 19 % of breast cancer patients undergoing breast conserving surgery (BCS) must return for a secondary surgery due to incomplete tumour removal. Our previous work demonstrated that the lower lipid content, characteristic of tumour tissue, was observed as regions of hypo-intense photoacoustic (PA) contrast. The goal of this work was to evaluate feasibility of a low-frequency, hand-held PA imaging probe for surgical margin assessment based on lipid content differences. Here, we describe (i) the design of a prototype hand-held PA imaging probe, (ii) the effect of limited-bandwidth on image contrast, (iii) accuracy towards hypo-intense contrast detection, (iv) the limited-view characteristics of the single sensor design, and (iv) early imaging results of an ex-vivo breast cancer specimen. The probe incorporates a single polyvinylidene fluoride acoustic sensor, a 1-to-4 optical fibre bundle and a polycarbonate axicon lens for light delivery. Imaging results on phantoms designed to mimic positive margins demonstrated the ability to detect gaps in optical absorption as small as 1 mm in width. Compared to images from a near full-view PAI system, the hand-held PAI probe had higher signal to noise ratio but suffered from negativity image artifacts. Lumpectomy specimen imaging showed that strong signals can be obtained from the fatty tissue. Taken together, the results show this imaging approach with a hand-held probe has potential for detection of residual breast cancer tissue during BCS; however, more work is needed to reduce the size of the probe to fit within the surgical cavity.

Distinguishing tumor from healthy tissue in human liver ex vivo using machine learning and multivariate analysis of diffuse reflectance spectra

The aim of this work was to evaluate the capability of diffuse reflectance spectroscopy to distinguish malignant liver tissues from surrounding tissues and to determine whether an extended wavelength range (450-1550 nm) offers any advantages over using the conventional wavelength range. Furthermore, multivariate analysis combined with a machine learning algorithm, either linear discriminant analysis or the more advanced support vector machine, was used to discriminate between and classify freshly excised human liver specimens from 18 patients. Tumors were distinguished from surrounding liver tissues with a sensitivity of 99%, specificity of 100%, classification rate of 100% and a Matthews correlation coefficient of 100% using the extended wavelength range and a combination of principal component analysis and support vector techniques. The results indicate that this technology may be useful in clinical applications for real-time tissue diagnostics of tumor margins where rapid classification is important.

Anthropomorphic Polydimethylsiloxane silicone-based phantom for Diffuse Optical Imaging

This work presents a method for constructing phantoms suitable for diffuse optical mammography. They are based on Polydimethylsiloxane silicones, with the characteristic of being anthropomorphic, and having similar mechanical and optical properties as a real breast. These phantoms are useful for testing the performance of diffuse optical imaging devices in the near infrared, both in transmittance and reflectance geometries, since they can be constructed containing inclusions, to simulate breast tumors. An alternative component to be used as scattering agent, that is easier to handle than traditional scattering agents, is also studied.

The optical properties of the phantoms were tested varying the concentration of scattering and absorbing agents, while their mechanical properties were modified by adding a silicone fluid to the basic mixture.

Finally, the phantoms were tested by Diffuse Optical Imaging experiments, and these images were compared to the ones obtained by conventional ultrasound techniques.

Results show that the constructed anthropomorphic phantoms properly reproduce the optical and mechanical characteristics of human breasts, and are suitable to be used in Diffuse Optical Imaging.

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We constructed anthropomorphic phantoms for Diffuse Optical Imaging.

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They simulate the optical and mechanical characteristics of a human breast.

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A new scattering agent was successfully introduced.

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Results of Diffuse Optical images are compared to Ultrasound images.

Assessment of repeated reference measurements to inform the validity of optical breast spectroscopy

Mammographic breast density is a strong breast cancer risk factor, and its routine clinical measurement could potentially be used to identify women at higher risk of breast cancer and/or monitor primary prevention strategies. Previous reports of optical breast spectroscopy (OBS), a novel approach to measuring breast density, demonstrated that it is safe (no ionizing radiation), portable, low-cost, and does not require image interpretation but have been limited to small, single-center studies. Reference measurements taken on a phantom breast prior to and after each woman's OBS assessment are required for the calibration of the system transfer function as a part of processing participant data. To inform the validity of participant data, a detailed description of the reference measurements and a repeatability analysis of these measurements taken before and after participant assessment is presented. Reference measurements for OBS from 539 women aged 18-40 years were obtained as a part of a high-throughput epidemiological pilot study. Of these, measurements from 20 women with no useable data due to device failure (3.7%) were excluded and from another 12 women due to user error. The intra-class correlation (ICC) within complete pairs of reference data (taken before and after assessment) was high (all ICC > 0.84). The analysis presented here confirms the OBS participant data as valid for use in ongoing epidemiological research, providing further supporting evidence of OBS as a measure of breast density. A novel method of measuring breast density is needed to bridge large gaps in the knowledge of breast density in younger women and its relation to later-life breast cancer risk.

Multitask Deep Learning Reconstruction and Localization of Lesions in Limited Angle Diffuse Optical Tomography

Diffuse optical tomography (DOT) leverages near-infrared light propagation through tissue to assess its optical properties and identify abnormalities. DOT image reconstruction is an ill-posed problem due to the highly scattered photons in the medium and the smaller number of measurements compared to the number of unknowns. Limited-angle DOT reduces probe complexity at the cost of increased reconstruction complexity. Reconstructions are thus commonly marred by artifacts and, as a result, it is difficult to obtain an accurate reconstruction of target objects, e.g., malignant lesions. Reconstruction does not always ensure good localization of small lesions. Furthermore, conventional optimization-based reconstruction methods are computationally expensive, rendering them too slow for real-time imaging applications. Our goal is to develop a fast and accurate image reconstruction method using deep learning, where multitask learning ensures accurate lesion localization in addition to improved reconstruction. We apply spatial-wise attention and a distance transform based loss function in a novel multitask learning formulation to improve localization and reconstruction compared to single-task optimized methods. Given the scarcity of real-world sensor-image pairs required for training supervised deep learning models, we leverage physics-based simulation to generate synthetic datasets and use a transfer learning module to align the sensor domain distribution between in silico and real-world data, while taking advantage of cross-domain learning. Applying our method, we find that we can reconstruct and localize lesions faithfully while allowing real-time reconstruction. We also demonstrate that the present algorithm can reconstruct multiple cancer lesions. The results demonstrate that multitask learning provides sharper and more accurate reconstruction.

2.5 Hz sample rate time-domain near-infrared optical tomography based on SPAD-camera image tissue hemodynamics

Time-domain near-infrared optical tomography (TD NIROT) techniques based on diffuse light were gaining performance over the last years. They are capable of imaging tissue at several centimeters depth and reveal clinically relevant information, such as tissue oxygen saturation. In this work, we present the very first in vivo results of our SPAD camera-based TD NIROT reflectance system with a temporal resolution of ∼116 ps. It provides 2800 time of flight source-detector pairs in a compact probe of only 6 cm in diameter. Additionally, we describe a 3-step reconstruction procedure that enables accurate recovery of structural information and of the optical properties. We demonstrate the system's performance firstly in reconstructing the 3D-structure of a heterogeneous tissue phantom with tissue-like scattering and absorption properties within a volume of 9 cm diameter and 5 cm thickness. Furthermore, we performed in vivo tomography of an index finger located within a homogeneous scattering medium. We employed a fast sampling rate of 2.5 Hz to detect changes in tissue oxygenation. Tomographic reconstructions were performed in true 3D, and without prior structural information, demonstrating the powerful capabilities of the system. This shows its potential for clinical applications.

A novel method for objectively, rapidly and accurately evaluating burn depth via near infrared spectroscopy

The accurate and objective evaluation of burn depth is a significant challenge in burn wound care. Herein, we used near infrared spectroscopy (NIRS) technology to measure the different depth of thermal burns in ex vivo porcine models. Based on the intensity of the spectral signals and the diffuse reflection theory, we extracted the optical parameters involved in functional (total hemoglobin and water content) and structural (tissue scattered size and scattered particles) features that reflect the changes in burn depth. Next, we applied support vector regression to construct a model including the optical property parameters and the burn depth. Finally, we histologically verified the burn depth data collected via NIRS. The results showed that our inversion model could achieve an average relative error of about 7.63%, while the NIRS technology diagnostic accuracy was in the range of 50 μm. For the first time, this novel technique provides physicians with real-time burn depth information objectively and accurately.

Narrowband diffuse reflectance spectroscopy in the 900-1000 nm wavelength region to quantify water and lipid content of turbid media

We report a narrow wavelength band diffuse reflectance spectroscopy (nb-DRS) method to determine water and fat ratios of scattering media in the 900-1000 nm range. This method was shown to be linearly correlated with absolute water and fat concentrations as tested on a set of turbid emulsion phantoms with a range of water and lipid compositions. Robustness to scattering assumptions was demonstrated and compared against measured scattering by a frequency-domain photon migration system. nb-DRS was also tested on ex-vivo porcine samples and compared against direct tissue water extraction by analytical chemistry methods. We speculate nb-DRS has potential applications in portable devices such as clinical and digital health wearables.

Broadband diffuse optical spectroscopy of absolute methemoglobin concentration can distinguish benign and malignant breast lesions

SIGNIFICANCE

Noninvasive diffuse optical spectroscopy (DOS) is a promising adjunct diagnostic imaging technique for distinguishing benign and malignant breast lesions. Most DOS approaches require normalizing lesion biomarkers to healthy tissue since major tissue constituents exhibit large interpatient variations. However, absolute optical biomarkers are desirable as it avoids reference measurements which may be difficult or impractical to acquire.

AIM

Our goal is to determine whether absolute measurements of minor absorbers such as collagen and methemoglobin (metHb) can successfully distinguish lesions. We hypothesize that metHb would exhibit less interpatient variability and be more suitable as an absolute metric for malignancy. However, we would expect collagen to exhibit more variability, because unlike metHb, collagen is also present in the healthy tissue.

APPROACH

In this retrospective clinical study, 30 lesions with breast imaging reporting and database system score   (  BIRADS  )    >    =  3 (12 benign and 18 malignant) measured with broadband quantitative DOS were analyzed for their oxyhemoglobin (HbO), deoxyhemoglobin (HHb), water, lipids, collagen, metHb concentrations, and optical scattering characteristics. Wilcoxon rank sum test was used to compare benign and malignant lesions for all variables in both normalized and absolute forms.

RESULTS

Among all absolute DOS parameters considered, only absolute metHb was observed to be significant for lesion discrimination (0.43  ±  0.18  μM for benign versus 0.87  ±  0.32  μM for malignant, p  =  0.0002). Absolute metHb concentration was also determined to be the best predictor of malignancy with an area under the curve of 0.89.

CONCLUSIONS

Our findings demonstrate that lesion metHb concentration measured by DOS can improve noninvasive optical diagnosis of breast malignancies. Since metHb concentration found in normal breast tissue is extremely low, metHb may be a more direct indicator of malignancy that does not depend on other biomarkers found in healthy tissue with significant variability. Furthermore, absolute parameters require reduced measurement time and can be utilized in cases where healthy reference tissue is not available.

Optical tissue measurements of invasive carcinoma and ductal carcinoma in situ for surgical guidance

Background

Although the incidence of positive resection margins in breast-conserving surgery has decreased, both incomplete resection and unnecessary large resections still occur. This is especially the case in the surgical treatment of ductal carcinoma in situ (DCIS). Diffuse reflectance spectroscopy (DRS), an optical technology based on light tissue interactions, can potentially characterize tissue during surgery thereby guiding the surgeon intraoperatively. DRS has shown to be able to discriminate pure healthy breast tissue from pure invasive carcinoma (IC) but limited research has been done on (1) the actual optical characteristics of DCIS and (2) the ability of DRS to characterize measurements that are a mixture of tissue types.

Methods

In this study, DRS spectra were acquired from 107 breast specimens from 107 patients with proven IC and/or DCIS (1488 measurement locations). With a generalized estimating equation model, the differences between the DRS spectra of locations with DCIS and IC and only healthy tissue were compared to see if there were significant differences between these spectra. Subsequently, different classification models were developed to be able to predict if the DRS spectrum of a measurement location represented a measurement location with “healthy” or “malignant” tissue. In the development and testing of the models, different definitions for “healthy” and “malignant” were used. This allowed varying the level of homogeneity in the train and test data.

Results

It was found that the optical characteristics of IC and DCIS were similar. Regarding the classification of tissue with a mixture of tissue types, it was found that using mixed measurement locations in the development of the classification models did not tremendously improve the accuracy of the classification of other measurement locations with a mixture of tissue types. The evaluated classification models were able to classify measurement locations with > 5% malignant cells with a Matthews correlation coefficient of 0.41 or 0.40. Some models showed better sensitivity whereas others had better specificity.

Conclusion

The results suggest that DRS has the potential to detect malignant tissue, including DCIS, in healthy breast tissue and could thus be helpful for surgical guidance.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-021-01436-5.

Hybrid Spectral-IRDx: Near-IR and Ultrasound Attenuation System for Differentiating Breast Cancer From Adjacent Normal Tissue

OBJECTIVE

While performing surgical excision for breast cancer (lumpectomy), it is important to ensure a clear margin of normal tissue around the cancer to achieve complete resection. The current standard is histopathology; however, it is time-consuming and labour-intensive requiring skilled personnel.

METHOD

We describe a Hybrid Spectral-IRDx - a combination of the previously reported Spectral-IRDx tool with multimodal ultrasound and NIR spectroscopy techniques. We show how this portable, cost-effective, minimal-contact tool could provide rapid diagnosis of cancer using formalin-fixed (FF) and deparaffinized (DP) breast biopsy tissues.

RESULTS

Using this new tool, measurements were performed on cancerous/fibroadenoma and its adjacent normal tissues from the same patients (N = 14). The acoustic attenuation coefficient (α) and reduced scattering coefficient (µ'_s) (at 850, 940, and 1060 nm) for the cancerous/fibroadenoma tissues were reported to be higher compared to adjacent normal tissues, a basis of delineation. Comparing FF cancerous and adjacent normal tissue, the difference in µ'_s at 850 nm and 940 nm were statistically significant (p = 3.17e-2 and 7.94e-3 respectively). The difference in α between the cancerous and adjacent normal tissues for DP and FF tissues were also statistically significant (p = 2.85e-2 and 7.94e-3 respectively). Combining multimodal parameters α and µ'_s (at 940 nm) show highest statistical significance (p = 6.72e-4) between FF cancerous/fibroadenoma and adjacent normal tissues.

CONCLUSION

We show that Hybrid Spectral-IRDx can accurately delineate between cancerous and adjacent normal breast biopsy tissue.

SIGNIFICANCE

The results obtained establish the proof-of-principle and large-scale testing of this multimodal breast cancer diagnostic platform for core biopsy diagnosis.

Single probe diffuse reflectance spectroscopy to assess the effect of sarcopoterium spinosum treatment on the cerebral tissue properties of ApoE knockout mouse

In this work, diffuse near-infrared light reflectance spectroscopy based on a single optical probe, contains central single collection fiber surrounded by a circular array of illumination fibers, was used to quantify cerebral tissue properties in ApoE knockout mice following Sarcopoterium spinosum treatment. Sarcopoterium spinosum, also known as Thorny burnet, is a Mediterranean plant widely used as a traditional therapy for the treatment of a variety of pathologies, primarily type 2 diabetes mellitus (T2D). While it's efficacy in the treatment of T2D, and of other components of metabolic syndrome, have already been validated by us, the aim of this study was to investigate the effects of Sarcopoterium spinosum extract (SSE) on dyslipidemia and vascular functions. We utilized ApoE deficient mice (ApoE^-/- , Atherosclerosis-prone apolipoprotein E-deficient), who have a severe impairment in plasma lipoprotein clearance and thus develop alterations in blood lipid profile and are highly susceptible to atherogenic plaque formation. A total of 34 male mice were divided into five groups representing various genetic, dietary, and treatment configurations. Optical measurements were used to assess changes in diffused reflectance spectra, optical properties (absorption and scattering), and cerebral tissue chromophore contents. Specifically, significant improvement in cerebral hemoglobin level was observed in ApoE KO mice, fed an artherogenic diet (ATD), upon SSE treatment. Biochemical and histological analyses of ApoE^-/- ATD mice showed elevated body weight and a high level of blood triglycerides, free fatty acids and cholesterol. In contrast, in SSE treated mice improvement was observed, suggesting beneficial effects of SSE. In ApoE^-/- ATD mice group a higher levels of deoxyhemoglobin was monitored indicating that the rate of oxygen release to the tissue is low. This was supported by decrease in oxygen saturation. It was also shown a reduction in water content in the brain of ApoE KO. Mice fed with the atherogenic diet demonstrated increased water content as compared to STD-fed ApoE KO mice, while SSE administration reversed the effect of the diet. To our knowledge, no such study has been reported before.

Camera-based CW Diffuse Optical Tomography for obtaining 3D absorption maps by means of digital tomosynthesis

We present a novel method for obtaining a 3D absorption map of a tissue-like turbid slab in the near-infrared spectral range by tomosynthesis. Transmittance data are obtained for a large number of oblique projection directions by scanning a cw laser source across the surface of the slab and by using a CCD camera for spatially resolved light detection. A perturbation model of light transport is used to convert the intensity maps for the different projections into absorption maps. By applying the tomosynthesis approach to these new maps, 3D absorption information on embedded inclusions has been obtained for the first time. The number and the positions of the lateral offset detectors have been optimized by employing a structural similarity index for comparison of the reconstructed with the true absorption data. We present 3D reconstruction of absorption maps using both Monte Carlo simulations and experiments on phantoms with breast-like optical properties. A comparison with conventional 3D reconstruction by a finite element approach shows the superior location performance of tomosynthesis.

Application of Multispectral Imaging in the Human Tympanic Membrane

Multispectral imaging has recently shown good performance in determining information about physiology, morphology, and composition of tissue. In the endoscopy field, many researches have shown the ability to apply multispectral or narrow-band images in surveying vascular structure based on the interaction of light wavelength with tissue composition. However, there has been no mention to assess the contrast between other components in the middle ear such as the tympanic membrane, malleus, and the surrounding area. Using CT, OCT, or ODT can clearly describe the tympanic membrane structure; nevertheless, these approaches are expensive, more complex, and time-consuming and are not suitable for most common middle ear diagnoses. Here, we show the potential of using the multispectral imaging technique to enhance the contrast of the tympanic membrane compared to the surrounding tissue. The optical absorption and scattering of biological tissues constituents are not the same at different wavelengths. In this pilot study, multiwavelength images of the tympanic membrane were captured by using the otoscope with LED light source at three distinct spectral regions: 450 nm, 530 nm, and 630 nm. Subsequently, analyses of the intensity images as well as the histogram of these images point out that the 630 nm illumination image features an evident contrast in the intensity of the tympanic membrane and malleus compared to the surrounding area. Analysis of such images could facilitate the boundary determination and segmentation of the tympanic membrane (TM) with high precision.

Towards a Portable Platform Integrated With Multispectral Noncontact Probes for Delineating Normal and Breast Cancer Tissue Based on Near-Infrared Spectroscopy

Currently, the confirmation of diagnosis of breast cancer is made by microscopic examination of an ultra-thin slice of a needle biopsy specimen. This slice is conventionally formalin-fixed and stained with hematoxylin-eosin and visually examined under a light microscope. This process is labor-intensive and requires highly skilled doctors (pathologists). In this paper, we report a novel tool based on near-infrared spectroscopy (Spectral-IRDx) which is a portable, non-contact, and cost-effective system and could provide a rapid and accurate diagnosis of cancer. The Spectral-IRDx tool performs absorption spectroscopy at near-infrared (NIR) wavelengths of 850, 935, and 1060 nm. We measure normalized detected voltage (V_dn) with the tool in 10 deparaffinized breast biopsy tissue samples, 5 of which were cancer (C) and 5 were normal (N) tissues. The difference in V_dn at 935 nm and 1060 nm between cancer and normal tissues is statistically significant with p-values of 0.0038 and 0.0022 respectively. Absorption contrast factor (N/C) of 1.303, 1.551, and 1.45 are observed for 850, 935, and 1060 nm respectively. The volume fraction contrast (N/C) of lipids and collagens are reported as 1.28 and 1.10 respectively. Higher absorption contrast factor (N/C) and volume fraction contrast (N/C) signifies higher concentration of lipids in normal tissues as compared to cancerous tissues, a basis for delineation. These preliminary results support the envisioned concept for noninvasive and noncarcinogenic NIR-based breast cancer diagnostic platform, which will be tested using a larger number of samples.

Resolving tissue chromophore concentration at MRI resolution using multi-wavelength photo-magnetic imaging

Photo-magnetic imaging (PMI) is an emerging optical imaging modality that showed great performance on providing absorption maps with high resolution and quantitative accuracy. As a multi-modality technology, PMI warms up the imaged object using a near infrared laser while temperature variation is measured using magnetic resonance imaging. By probing tissue at multiple wavelengths, concentration of the main tissue chromophores such as oxy- and deoxy-hemoglobin, lipid, and water are obtained then used to derive functional parameters such as total hemoglobin concentration and relative oxygen saturation. In this paper, we present a multi-wavelength PMI system that was custom-built to host five different laser wavelengths. After recovering the high-resolution absorption maps, a least-squared minimization process was used to resolve the different chromophore concentration. The performance of the system was experimentally tested on a phantom with two different dyes. Their concentrations were successfully assessed with high spatial resolution and average accuracy of nearly 80%.

Lipid-weighted intraoperative photoacoustic tomography of breast tumors: Volumetric comparison to preoperative MRI

With a lifetime risk of 1 in 8, breast cancer continues to be a major concern for women and their physicians. The optimal treatment of the disease depends on the stage of the cancer at diagnosis, which is typically assessed using medical imaging. However, currently employed imaging systems for breast tumor measurement rarely agree perfectly. Our group developed an Intraoperative Photoacoustic Screening (iPAS) soft tissue scanner featuring high bulk tissue sensitivity, a clinically compatible scan-time of 6 min, imaging depths greater than 2 cm and the capability to visualize whole breast tumors based on their lipid, rather than hemoglobin, profile. Here, we report on the first clinical experience with breast cancer patients by comparing tumor-measurement using iPAS, preoperative dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) and gold-standard pathology. Tumor size was measured volumetrically for iPAS and DCE-MRI, and separately using maximum diameters for pathology, DCE-MRI and iPAS. Comparisons were performed using Pearson's correlation coefficients, and the non-parametric Wilcoxon signed-rank test. Twelve consecutive patients were included in the study, contingent on pathologically documented invasive carcinoma. iPAS volumetric tumor size was positively correlated to DCE-MRI (Pearson's r = 0.78, p = 0.003) and not significantly different (Wilcoxon, p = 0.97). In comparison to pathology, tumor diameters given by iPAS were positively correlated (Pearson's r = 0.87, p = 0.0002) and significantly different (Wilcoxon, p = 0.0015). The results indicated that volumetric-measurement of invasive breast tumors with iPAS is similar to that of DCE-MRI. On the other hand, tumor diameter measurements were less reliable. Beyond enhancing surgical specimen examination, an extension of this technology to diagnostic imaging promises a new perspective on tumor assessment, potentially improving our current understanding and treatment of breast cancer.

Cardiovascular calcification: artificial intelligence and big data accelerate mechanistic discovery

Cardiovascular calcification is a health disorder with increasing prevalence and high morbidity and mortality. The only available therapeutic options for calcific vascular and valvular heart disease are invasive transcatheter procedures or surgeries that do not fully address the wide spectrum of these conditions; therefore, an urgent need exists for medical options. Cardiovascular calcification is an active process, which provides a potential opportunity for effective therapeutic targeting. Numerous biological processes are involved in calcific disease, including matrix remodelling, transcriptional regulation, mitochondrial dysfunction, oxidative stress, calcium and phosphate signalling, endoplasmic reticulum stress, lipid and mineral metabolism, autophagy, inflammation, apoptosis, loss of mineralization inhibition, impaired mineral resorption, cellular senescence and extracellular vesicles that act as precursors of microcalcification. Advances in molecular imaging and big data technology, including in multiomics and network medicine, and the integration of these approaches are helping to provide a more comprehensive map of human disease. In this Review, we discuss ectopic calcification processes in the cardiovascular system, with an emphasis on emerging mechanistic knowledge obtained through patient data and advances in imaging methods, experimental models and multiomics-generated big data. We also highlight the potential and challenges of artificial intelligence, machine learning and deep learning to integrate imaging and mechanistic data for drug discovery.

Broadband Time Domain Diffuse Optical Reflectance Spectroscopy: A Review of Systems, Methods, and Applications

This review presents recent developments and a wide overview of broadband time domain diffuse optical spectroscopy (TD-DOS). Various topics including physics of photon migration, advanced instrumentation, methods of analysis, applications covering multiple domains (tissue chromophore, in vivo studies, food, wood, pharmaceutical industry) are elaborated. The key role of standardization and recent studies in that direction are discussed. Towards the end, a brief outlook is presented on the current status and future trends in broadband TD-DOS.

Detection of collagens by multispectral optoacoustic tomography as an imaging biomarker for Duchenne muscular dystrophy

Biomarkers for monitoring of disease progression and response to therapy are lacking for muscle diseases such as Duchenne muscular dystrophy. Noninvasive in vivo molecular imaging with multispectral optoacoustic tomography (MSOT) uses pulsed laser light to induce acoustic pressure waves, enabling the visualization of endogenous chromophores. Here we describe an application of MSOT, in which illumination in the near- and extended near-infrared ranges from 680-1,100 nm enables the visualization and quantification of collagen content. We first demonstrated the feasibility of this approach to noninvasive quantification of tissue fibrosis in longitudinal studies in a large-animal Duchenne muscular dystrophy model in pigs, and then applied this approach to pediatric patients. MSOT-derived collagen content measurements in skeletal muscle were highly correlated to the functional status of the patients and provided additional information on molecular features as compared to magnetic resonance imaging. This study highlights the potential of MSOT imaging as a noninvasive, age-independent biomarker for the implementation and monitoring of newly developed therapies in muscular diseases.

VIS-NIR spectral signature and quantitative analysis of HeLa and DU145 cell line

Cancer is increasing in incidence and the leading cause of death worldwide. Controlling and reducing cancer requires early detection and technique to accurately detect and quantify predictive biomarkers. Optical spectroscopy has shown promising non-destructive ability to display distinctive spectral characteristics between cancerous and normal tissues from different part of human organ. Nonetheless, not many information is available on spectroscopic properties of cancer cell lines. In this research, the visible-near infrared (VIS-NIR) absorbance spectroscopy measurement of cultured cervical cancer (HeLa) and prostate cancer cells (DU145) lines has been performed to develop spectral signature of cancer cells and to generate algorithm to quantify cancer cells. Spectroscopic measurement on mouse skin fibroblast (L929) was also taken for comparative purposes. In visible region, the raw cells' spectra do not produce any noticeable peak absorbance that provides information on color because the medium used for cells is colorless and transparent. NIR wavelength between 950 and 975 nm exhibit significant peak due to water absorbance by the medium. Development of spectral signature for the cells through the application of regression technique significantly enhances the diverse characteristics between L929, HeLa and DU145. The application of multiple linear regression allows high measurement accuracy of the cells with coefficient of determination above 0.94.

Influence of neoadjuvant chemotherapy on diffuse reflectance spectra of tissue in breast surgery specimens

Diffuse reflectance spectroscopy (DRS) can discriminate different tissue types based on optical characteristics. Since this technology has the ability to detect tumor tissue, several groups have proposed to use DRS for margin assessment during breast-conserving surgery for breast cancer. Nowadays, an increasing number of patients with breast cancer are being treated by neoadjuvant chemotherapy. Limited research has been published on the influence of neoadjuvant chemotherapy on the optical characteristics of the tissue. Hence, it is unclear whether margin assessment based on DRS is feasible in this specific group of patients. We investigate whether there is an effect of neoadjuvant chemotherapy on optical measurements of breast tissue. To this end, DRS measurements were performed on 92 ex-vivo breast specimens from 92 patients, treated with neoadjuvant chemotherapy and without neoadjuvant chemotherapy. Generalized estimating equation (GEE) models were generated, comparing the measurements of patients with and without neoadjuvant chemotherapy in datasets of different tissue types using a significance level of 5%. As input for the GEE models, either the intensity at a specific wavelength or a fit parameter, derived from the spectrum, was used. In the evaluation of the intensity, no influence of neoadjuvant chemotherapy was found, since none of the wavelengths were significantly different between the measurements with and the measurements without neoadjuvant chemotherapy in any of the datasets. These results were confirmed by the analysis of the fit parameters, which showed a significant difference for the amount of collagen in only one dataset. All other fit parameters were not significant for any of the datasets. These findings may indicate that assessment of the resection margin with DRS is also feasible in the growing population of breast cancer patients who receive neoadjuvant chemotherapy. However, it is possible that we did not detect neoadjuvant chemotherapy effect in the some of the datasets due to the small number of measurements in those datasets.

Broadband hyperspectral imaging for breast tumor detection using spectral and spatial information

Complete tumor removal during breast-conserving surgery remains challenging due to the lack of optimal intraoperative margin assessment techniques. Here, we use hyperspectral imaging for tumor detection in fresh breast tissue. We evaluated different wavelength ranges and two classification algorithms; a pixel-wise classification algorithm and a convolutional neural network that combines spectral and spatial information. The highest classification performance was obtained using the full wavelength range (450-1650 nm). Adding spatial information mainly improved the differentiation of tissue classes within the malignant and healthy classes. High sensitivity and specificity were accomplished, which offers potential for hyperspectral imaging as a margin assessment technique to improve surgical outcome.

Diffuse optical spectroscopic imaging for the investigation of human lactation physiology: a case study on mammary involution

Relatively few imaging and sensing technologies are employed to study human lactation physiology. In particular, human mammary development during pregnancy as well as mammary involution after lactation have been poorly described, despite their importance for breast cancer diagnosis and treatment during these phases. Our case study shows the potential of diffuse optical spectroscopic imaging (DOSI) to uniquely study the spatiotemporal changes in mammary tissue composition during the involution of the lactating breast toward its pre-pregnant state. At nine time intervals over a period of eight months after the cessation of breastfeeding, we reconstructed 2-D maps of mammary water content, lipid content, total hemoglobin (THb) concentration, oxygen saturation (StO2), and tissue optical scattering. Mammary lipid content in the nonareolar region showed a significant relative increase of 59%, whereas water content and THb concentration showed a significant relative decrease of 50% and 48%, respectively. Significant changes were also found in StO2 and tissue optical scattering. Our findings are consistent with the gradual replacement of fibroglandular tissue by adipose tissue and vascular regression during mammary involution. Moreover, our data provide unique insight into the dynamics of breast tissue composition and demonstrate the effectiveness of DOSI as a technique to study human lactation physiology.

Comparison of Lipid and Water Contents by Time-domain Diffuse Optical Spectroscopy and Dual-energy Computed Tomography in Breast Cancer Patients

We previously compared time-domain diffuse optical spectroscopy (TD-DOS) with magnetic resonance imaging (MRI) using various water/lipid phantoms. However, it is difficult to conduct similar comparisons in the breast, because of measurement differences due to modality-dependent differences in posture. Dual-energy computed tomography (DECT) examination is performed in the same supine position as a TD-DOS measurement. Therefore, we first verified the accuracy of the measured fat fraction of fibroglandular tissue in the normal breast on DECT by comparing it with MRI in breast cancer patients (n = 28). Then, we compared lipid and water signals obtained in TD-DOS and DECT from normal and tumor-tissue regions (n = 16). The TD-DOS breast measurements were carried out using reflectance geometry with a source–detector separation of 3 cm. A semicircular region of interest (ROI), with a transverse diameter of 3 cm and a depth of 2 cm that included the breast surface, was set on the DECT image. Although the measurement area differed between the modalities, the correlation coefficients of lipid and water signals between TD-DOS and DECT were rs = 0.58 (p < 0.01) and rs = 0.90 (p < 0.01), respectively. These results indicate that TD-DOS captures the characteristics of the lipid and water contents of the breast.

Time-Domain Near-Infrared Spectroscopy and Imaging: A Review

This article reviews the past and current statuses of time-domain near-infrared spectroscopy (TD-NIRS) and imaging. Although time-domain technology is not yet widely employed due to its drawbacks of being cumbersome, bulky, and very expensive compared to commercial continuous wave (CW) and frequency-domain (FD) fNIRS systems, TD-NIRS has great advantages over CW and FD systems because time-resolved data measured by TD systems contain the richest information about optical properties inside measured objects. This article focuses on reviewing the theoretical background, advanced theories and methods, instruments, and studies on clinical applications for TD-NIRS including some clinical studies which used TD-NIRS systems. Major events in the development of TD-NIRS and imaging are identified and summarized in chronological tables and figures. Finally, prospects for TD-NIRS in the near future are briefly described.

Stable tissue-simulating phantoms with various water and lipid contents for diffuse optical spectroscopy

We introduced a method for producing solid phantoms with various water-to-lipid ratios that can simulate the absorption, and to some extent the scattering characteristics of human breast tissue. We also achieved phantom stability for a minimum of one month by solidifying the emulsion phantoms. The characteristics of the phantoms were evaluated using the six-wavelength time-domain diffuse optical spectroscopy (TD-DOS) system we developed to measure water and lipid contents and hemoglobin concentration. The TD-DOS measurements were validated with a magnetic resonance imaging system.

Hemoglobin state-flux: A finite-state model representation of the hemoglobin signal for evaluation of the resting state and the influence of disease

SUMMARY

In this report we introduce a weak-model approach for examination of the intrinsic time-varying properties of the hemoglobin signal, with the aim of advancing the application of functional near infrared spectroscopy (fNIRS) for the detection of breast cancer, among other potential uses. The developed methodology integrates concepts from stochastic network theory with known modulatory features of the vascular bed, and in doing so provides access to a previously unrecognized dense feature space that is shown to have promising diagnostic potential. Notable features of the methodology include access to this information solely from measures acquired in the resting state, and analysis of these by treating the various components of the hemoglobin (Hb) signal as a co-varying interacting system.

APPROACH

The principal data-transform kernel projects Hb state-space trajectories onto a coordinate system that constitutes a finite-state representation of covariations among the principal elements of the Hb signal (i.e., its oxygenated (ΔoxyHb) and deoxygenated (ΔdeoxyHb) forms and the associated dependent quantities: total hemoglobin (ΔtotalHb = ΔoxyHb + ΔdeoxyHb), hemoglobin oxygen saturation (ΔHbO2Sat = 100Δ(oxyHb/totalHb)), and tissue-hemoglobin oxygen exchange (ΔHbO2Exc = ΔdeoxyHb-ΔoxyHb)). The resulting ten-state representation treats the evolution of this signal as a one-space, spatiotemporal network that undergoes transitions from one state to another. States of the network are defined by the algebraic signs of the amplitudes of the time-varying components of the Hb signal relative to their temporal mean values. This assignment produces several classes of coefficient arrays, most with a dimension of 10×10.

BIOLOGICAL MOTIVATION

Motivating our approach is the understanding that effector mechanisms that modulate blood delivery to tissue operate on macroscopic scales, in a spatially and temporally varying manner. Also recognized is that this behavior is sensitive to nonlinear actions of these effectors, which include the binding properties of hemoglobin. Accessible phenomenology includes measures of the kinetics and probabilities of network dynamics, which we treat as surrogates for the actions of feedback mechanisms that modulate tissue-vascular coupling.

FINDINGS

Qualitative and quantitative features of this space, and their potential to serve as markers of disease, have been explored by examining continuous-wave fNIRS 3D tomographic time series obtained from the breasts of women who do and do not have breast cancer. Inspection of the coefficient arrays reveals that they are governed predominantly by first-order rate processes, and that each array class exhibits preferred structure that is mainly independent of the others. Discussed are strategies that may serve to extend evaluation of the accessible feature space and how the character of this information holds potential for development of novel clinical and preclinical uses.

Comparison of spatially and temporally resolved diffuse transillumination measurement systems for extraction of optical properties of scattering media

This paper discusses the main differences between two different methods for determining the optical properties of tissue optical phantoms by fitting the spatial and temporal intensity distribution functions to the diffusion approximation theory. The consistency in the values of the optical properties is verified by changing the width of the recipient containing the turbid medium; as the optical properties are an intrinsic value of the scattering medium, independently of the recipient width, the stability in these values for different widths implies a better measurement system for the acquisition of the optical properties. It is shown that the temporal fitting method presents higher stability than the spatial fitting method; this is probably due to the addition of the time of flight parameter into the diffusion theory.

Collagen quantification in breast tissue using a 12-wavelength near infrared spectral tomography (NIRST) system

A portable near infrared spectral tomography (NIRST) system was adapted for breast cancer detection and treatment monitoring with improved speed of acquisition for parallel 12 wavelengths of parallel frequency-domain (FD) and continuous-wavelength (CW) measurement. Using a novel gain adjustment scheme in the Photomultiplier Tube detectors (PMTs), the data acquisition time for simultaneous acquisition involving three FD and three CW wavelengths, has been reduced from 90 to 55 seconds, while signal variation was also reduced from 2.1% to 1.1%. Tomographic images of breast collagen content have been recovered for the first time, and image reconstruction approaches with and without collagen content included have been validated in simulation studies and normal subject exams. Simulations indicate that including collagen content into the reconstruction procedure can significantly reduce the overestimation in total hemoglobin, water and lipid by 8.9μM, 1.8% and 15.8%, respectively, and underestimates in oxygen saturation by 9.5%, given an average 10% background collagen content. A breast cancer patient with invasive ductal carcinoma was imaged and the reconstructed images show that the recovered tumor/background contrast in total hemoglobin increased from 1.5 to 1.7 when collagen was included in reconstruction.

Broadband diffuse optical characterization of elastin for biomedical applications

Elastin is a key structural protein of dynamic connective tissues widely found in the extracellular matrix of skin, arteries, lungs and ligaments. It is responsible for a range of diseases related to aging of biological tissues. The optical characterization of elastin can open new opportunities for its investigation in biomedical studies. In this work, we present the absorption spectra of elastin using a broadband (550-1350nm) diffuse optical spectrometer. Distortions caused by fluorescence and finite bandwidth of the laser source on estimated absorption were effectively accounted for in measurements and data analysis and compensated. A comprehensive summary and comparison between collagen and elastin is presented, highlighting distinct features for its accurate quantification in biological applications.