Shape-based multi-spectral optical image reconstruction through genetic algorithm based optimization.

Multi-spectral optical imaging of skin and skin-lesions has been of significant interest for various biomedical applications. A multi-spectral optical imaging instrument called Nevoscope has been developed to acquire images of skin and skin-lesion through trans-illumination. Nevoscope based multi-spectral trans-illumination imaging is aimed at characterization of skin-lesions for early diagnosis of skin-cancers by reconstructing distributions of melanin and blood. Conventional approaches usually involve dividing the field of view into a number of voxels and assuming constant optical properties in each voxel. The optical properties are reconstructed in terms of measurements at multiple wavelengths and the distribution of melanin and blood are subsequently calculated. However, since the inverse problem is generally an ill-posed and under-determined one, it is hard to get quantitatively accurate reconstruction. In this paper, a shape-based multi-constrained reconstruction algorithm is presented, which uses a genetic algorithm based optimization methods to find the best possible reconstruction solution. A skin-lesion such as melanoma is modeled as melanin and blood parts, which are delineated by two cubic tensor-product B-spline surfaces. This reduces the number of unknowns to a few control parameters of the surfaces. The parameters are then coded into a genetic algorithm to find a solution through global optimization. Reasonable constraints are incorporated into the genetic algorithm to stabilize the solution. Results of reconstructions of melanin and blood parts are presented for simulated lesions using multi-spectral wavelengths at 580nm and 800nm.

Editorial Trends and Challenges in Translation of Point-of-Care Technologies in Healthcare.

Point-of-Care Technologies (POCT) in Healthcare have emerged as a potential pathway in global and resource-limited environments towards improving access to healthcare with emphasis on preventive, personalized and precision medicine. The potential uses for POC technologies by patients or clinicians are many-from home-based monitoring to semi-managed and clinical inpatient healthcare. However, it is yet to be proven precisely what technologies are necessary or how they should be used to make an impact in improving access to quality healthcare. Although there is great potential for the application of new technologies in healthcare, physicians are skeptical about POCT since they fear it will generate large amounts of unreliable and overwhelming information of unknown benefit. Because the benefits and acceptance of POCT are unknown, a necessary first step in its development is performing market research of patients and clinicians to determine what POCT protocols would be most beneficial and acceptable. Research into POCT involves first understanding what the needs are of patients and clinicians, and then researching the best way to apply new technology to improve clinical care based on the understanding of these needs. The conference featured 5 keynote, 8 panel and 4 breakout sessions involving leaders from several stakeholder groups, including technology research, federal funding and regulatory agencies, industry and clinical healthcare. Through numerous presentations and group discussions, the conference participants concluded that the future of POCT depends upon facilitation of collaborative translational research towards development and meaningful validation of POCT in addressing specific healthcare and clinical needs with clear benefits and user acceptance.

Concise matrix analysis of point-based prostate targeting for intensity modulated radiation therapy.

Intensity Modulated Radiation Therapy (IMRT) has recently emerged as an effective clinical treatment tool to treat various types of cancers by limiting the external beam dose to the surrounding normal tissue. However, the process of limiting external radiation dose to the tissue surrounding the tumor volume is not a trivial task. Several parameters including tumor volume and inhomogeneity, position and shape of the tumor volume, and the geometrical distribution of the radiation beams directly affect the determination of the external radiation dose. In addition, a major variable in effective delivery of the radiation dose is "set-up error" caused by the changes in patient position. Any changes in the position of the patient affect the geometrical location of the tumor volume and, therefore, need to be accommodated in the delivery of radiation beams during the treatment. This work presents a complete matrix representation required to calculate the three-dimensional rigid body homogeneous transformation matrices corresponding to external beam radiotherapy setup error and subsequent corrections in treatment beam parameters. A new concise orthogonal rotation solution is presented for use with clinical noisy data. Monte Carlo simulations prove the new matrix results are consistently better than the standard inverse solution. The required corrections in beam table, gantry, and collimator angles as function of the planned beam gantry angle are derived. For transformations that include a rotation on the sagittal plane, the required offsets to beam parameters are complex functions of the planned gantry angle but are clearly documented graphically for clinical use. A case study is presented with an error analysis that supports the use of the presented method in a clinical environment. Clinical implementation and evaluation of the presented method with patient data is also included in the paper.

Collaborative Paradigm of Preventive, Personalized, and Precision Medicine With Point-of-Care Technologies.

Recent advances in biosensors, medical instrumentation, and information processing and communication technologies (ICT) have enabled significant improvements in healthcare. However, these technologies have been mainly applied in clinical environments, such as hospitals and healthcare facilities, under managed care by well-trained and specialized individuals. The global challenge of providing quality healthcare at affordable cost leads to the proposed paradigm of P reventive, Personalized, and Precision Medicine that requires a seamless use of technology and infrastructure support for patients and healthcare providers at point-of-care (POC) locations including homes, semi or pre-clinical facilities, and hospitals. The complexity of the global healthcare challenge necessitates strong collaborative interdisciplinary synergies involving all stakeholder groups including academia, federal research institutions, industry, regulatory agencies, and clinical communities. It is critical to evolve with collaborative efforts on the translation of research to technology development toward clinical validation and potential healthcare applications. This special issue is focused on technology innovation and translational research for POC applications with potential impact in improving global healthcare in the respective areas. Some of these papers were presented at the NIH-IEEE Strategic Conference on Healthcare Innovations and POC Technologies for Precision Medicine (HI-POCT) held at the NIH on November 9-10, 2015. The papers included in the Special Issue provide a spectrum of critical issues and collaborative resources on translational research of advanced POC devices and ICT into global healthcare environment.

Monte Carlo simulation of light-tissue interaction: three-dimensional simulation for trans-illumination-based imaging of skin lesions.

Three-dimensional, voxel-based, and wavelength-dependent skin lesion models are developed and simulated using Monte Carlo techniques. The optical geometry of the Nevoscope with trans-illumination is used in the simulations for characterizing the lesion thickness. Based on the correlation analysis between the lesion thickness and the diffuse reflectance, optical wavelengths are selected for multispectral imaging of skin lesions using the Nevoscope. Tissue optical properties reported by various researchers are compiled together to form a voxel library. Tissue models used in the simulations are developed using the voxel library which offers flexibility in updating the optical properties and adding new media types into the models independent of the Monte Carlo simulation code.

Multi-spectral image analysis and classification of melanoma using fuzzy membership based partitions.

The sensitivity and specificity of melanoma diagnosis can be improved by adding the lesion depth and structure information obtained from the multi-spectral, trans-illumination images to the surface characteristic information obtained from the epi-illumination images. Wavelet transform based bi-modal channel energy features obtained from the images are used in the analysis. Methods using both crisp and fuzzy membership based partitioning of the feature space are evaluated. For this purpose, the ADWAT classification method that uses crisp partitioning is extended to handle multi-spectral image data. Also, multi-dimensional fuzzy membership functions with Gaussian and Bell profiles are proposed for classification. Results show that the fuzzy membership functions with Bell profile are more effective than the extended ADWAT method in discriminating melanoma from dysplastic nevus.

Current and Future Challenges in Point-of-Care Technologies: A Paradigm-Shift in Affordable Global Healthcare With Personalized and Preventive Medicine.

This paper summarizes the panel discussion at the IEEE Engineering in Medicine and Biology Point-of-Care Healthcare Technology Conference (POCHT 2013) held in Bangalore India from Jan 16-18, 2013. Modern medicine has witnessed interdisciplinary technology innovations in healthcare with a continuous growth in life expectancy across the globe. However, there is also a growing global concern on the affordability of rapidly rising healthcare costs. To provide quality healthcare at reasonable costs, there has to be a convergence of preventive, personalized, and precision medicine with the help of technology innovations across the entire spectrum of point-of-care (POC) to critical care at hospitals. The first IEEE EMBS Special Topic POCHT conference held in Bangalore, India provided an international forum with clinicians, healthcare providers, industry experts, innovators, researchers, and students to define clinical needs and technology solutions toward commercialization and translation to clinical applications across different environments and infrastructures. This paper presents a summary of discussions that took place during the keynote presentations, panel discussions, and breakout sessions on needs, challenges, and technology innovations in POC technologies toward improving global healthcare. Also presented is an overview of challenges and trends in developing and developed economies with respect to priority clinical needs, technology innovations in medical devices, translational engineering, information and communication technologies, infrastructure support, and patient and clinician acceptance of POC healthcare technologies.

Classification of melanoma using tree structured wavelet transforms.

This paper presents a wavelet transform based tree structure model developed and evaluated for the classification of skin lesion images into melanoma and dysplastic nevus. The tree structure model utilizes a semantic representation of the spatial-frequency information contained in the skin lesion images including textural information. Results show that the presented method is effective in discriminating melanoma from dysplastic nevus. The results are also compared with those obtained using another method of developing tree structures utilizing the maximum channel energy criteria with a fixed energy ratio threshold.

MIRD pamphlet No. 25: MIRDcell V2.0 software tool for dosimetric analysis of biologic response of multicellular populations.

Patients undergoing nuclear medicine procedures for cancer therapy are administered radiopharmaceuticals that emit various types of radiation. Because radiation has differential delivery to and uptake by cells in tissue, radiation exposures are often highly nonuniform. Some cell populations in a tissue may contain widely different amounts of radioactivity, whereas other cell populations in the same tissue may contain no radioactivity, referred to as labeled and unlabeled cells, respectively. Furthermore, the toxicity of the radiations emitted can depend on the location of the radioactive decay within the cell (e.g., nucleus vs. cytoplasm). Therefore, the response of a given cell depends on the absorbed dose received from radiations emitted by decays within the cell (self-dose) and emitted by decays in neighboring cells (cross-dose), among other factors. Taken together, these variables make it difficult to predict the response of cell populations to radiopharmaceuticals. Accordingly, to assist in designing treatment plans for therapeutic radiopharmaceuticals, an applet software application called MIRDcell was developed. This applet models the distribution of radiopharmaceuticals in tissues, calculates the distribution of radiation dose, models responses on a cell-by-cell basis, and predicts the surviving fraction of the labeled and unlabeled cell populations. MIRDcell can be accessed at http://mirdcell.njms.rutgers.edu/.

Transillumination imaging for blood oxygen saturation estimation of skin lesions.

Detecting the early stages of melanoma can be greatly assisted by an accurate estimate of subsurface blood volume and blood oxygen saturation, indicative of angiogenesis. Visualization of this blood volume present beneath a skin lesion can be achieved through the transillumination of the skin. As the absorption of major chromophores in the skin is wavelength dependent, multispectral imaging can provide the needed information to separate out relative amounts of each chromophore. However, a critical challenge to this strategy is relating the pixel intensities observed in a given image to the wavelength-dependent total absorption existing at each spatial location. Consequently, in this paper, we develop an extension to Beer's law, estimated through a novel voxel-based, parallel processing Monte Carlo simulation of light propagation in skin which takes into account the specific geometry of our transillumination imaging apparatus. We then use this relation in a linear mixing model, solved using a multispectral image set, for chromophore separation and oxygen saturation estimation of an absorbing object located at a given depth within the medium. Validation is performed through the Monte Carlo simulation, as well as by imaging on a skin phantom. Results show that subsurface oxygen saturation can be reasonably estimated with good implications for the reconstruction of 3-D skin lesion volumes using transillumination toward early detection of malignancy.

3-D volume reconstruction of skin lesions for melanin and blood volume estimation and lesion severity analysis.

Subsurface information about skin lesions, such as the blood volume beneath the lesion, is important for the analysis of lesion severity towards early detection of skin cancer such as malignant melanoma. Depth information can be obtained from diffuse reflectance based multispectral transillumination images of the skin. An inverse volume reconstruction method is presented which uses a genetic algorithm optimization procedure with a novel population initialization routine and nudge operator based on the multispectral images to reconstruct the melanin and blood layer volume components. Forward model evaluation for fitness calculation is performed using a parallel processing voxel-based Monte Carlo simulation of light in skin. Reconstruction results for simulated lesions show excellent volume accuracy. Preliminary validation is also done using a set of 14 clinical lesions, categorized into lesion severity by an expert dermatologist. Using two features, the average blood layer thickness and the ratio of blood volume to total lesion volume, the lesions can be classified into mild and moderate/severe classes with 100% accuracy. The method therefore has excellent potential for detection and analysis of pre-malignant lesions.

Voxel-based, parallel simulation of light in skin tissue for the reconstruction of subsurface skin lesion volumes.

Early detection and diagnosis of skin cancer is essential to treating the malignancy and preventing death. Subsurface features and depth information are critical in evaluating a skin lesion for this early malignancy screening. We present a novel voxel-based Monte Carlo simulation of light propagation in skin tissue which runs in a highly parallel environment on desktop graphics processors, resulting in an extremely fast simulation of millions of photons in less than one second. We then use this model in a genetic algorithm for the inverse 3D volume reconstruction of a skin lesion, given a set of multispectral images obtained using non-invasive transillumination imaging. Our method demonstrates improved accuracy at a superior resolution to existing methods.

Computer aided analysis of epi-illumination and transillumination images of skin lesions for diagnosis of skin cancers.

Skin lesion pigmentation area from surface, or, epi-illumination (ELM) images and blood volume area from transillumination (TLM) images are useful features to aid a dermatologist in the diagnosis of melanoma and other skin cancers in early curable stages. However, segmentation of these areas is difficult. In this work, we present an automatic segmentation tool for ELM and TLM images that also provides additional choices for user selection and interaction with adaptive learning. Our tool uses a combination of k-means clustering, wavelet analysis, and morphological operations to segment the lesion and blood volume, and then presents the user with six segmentation suggestions for both ELM and TLM images. The final selection of segmentation boundary may then be iteratively improved through scoring by multiple users. The ratio of TLM to ELM segmented areas is an indicator of dysplasia in skin lesions for detection of skin cancers, and this ratio is found to show a statistically significant trend in association with lesion dysplasia on a set of 81 pathologically validated lesions (p = 0.0058). We then present a support vector machine classifier using the results from the interactive segmentation method along with ratio, color, texture, and shape features to characterize skin lesions into three degrees of dysplasia with promising accuracy.

Depth-dependent hemoglobin analysis from multispectral transillumination images.

Multispectral transillumination imaging is a promising modality for noninvasive imaging of living tissue. Multispectral Nevoscope imaging is directed toward the imaging of skin lesions for the detection and characterization of skin cancers through the volumetric analysis of selected chromophores, such as melanin, oxy-, and deoxyhemoglobin. In this letter, we present a novel method of recovering depth-dependent measurements from transillumination images obtained through the Nevoscope. A method for estimating the depth-dependent point spread function is presented and used in recovering multispectral transillumination images of a skin phantom or lesion through blind deconvolution. A method for ratiometric analysis for the quantification of oxy- and deoxyhemoglobin is then presented and evaluated on a skin phantom. The presented methods would allow reliable quantitative analysis of multispectral Nevoscope images for early detection of angiogenesis leading to early diagnosis of skin cancers.

Multispectral transillumination imaging of skin lesions for oxygenated and deoxygenated hemoglobin measurement.

The early detection of melanoma is critical for patient survival. One of the indentifying features of new malignancy is increased blood flow to the lesion. Multispectral transillumination using the Nevoscope has been demonstrated to be an effective tool for imaging the sub-surface vascular architecture of skin lesions. Using multispectral images obtained from this tool in the visible and near-infrared range, as well as the relative difference in spectral absorption due to oxyhemoglobin and deoxyhemoglobin, we propose an empirical method to estimate the blood flow volume within a skin lesion. From the images, estimates of the distribution of both Hb and HbO(2) are calculated along with a ratiometric feature describing the relative oxygen saturation level in the blood. We validate our proposed method through the imaging of a skin phantom with embedded capillaries which can be filled with either an artificial Hb or HbO(2) liquid. Our near-IR, multispectral computations nicely differentiate the Hb filled phantom versus the HbO(2) filled phantom, demonstrating that these chromophores can be successfully separated and individually characterized for use in estimating the relative oxygen saturation of skin tissue.

Optical imaging modalities for biomedical applications.

Optical photographic imaging is a well known imaging method that has been successfully translated into biomedical applications such as microscopy and endoscopy. Although several advanced medical imaging modalities are used today to acquire anatomical, physiological, metabolic, and functional information from the human body, optical imaging modalities including optical coherence tomography, confocal microscopy, multiphoton microscopy, multispectral endoscopy, and diffuse reflectance imaging have recently emerged with significant potential for non-invasive, portable, and cost-effective imaging for biomedical applications spanning tissue, cellular, and molecular levels. This paper reviews methods for modeling the propagation of light photons in a biological medium, as well as optical imaging from organ to cellular levels using visible and near-infrared wavelengths for biomedical and clinical applications.

Multispectral optical imaging of skin-lesions for detection of malignant melanomas.

Optical imaging of skin-lesions for early detection and management of the most fatal skin-cancer malignant melanoma is of significant interest in mass screening of skin-lesions with high-risk population. Surface illumination based optical imaging methods such as epiluminescence light microscopy (ELM) through "Dermascopy" has shown a significant potential in improving early diagnosis of malignant melanomas. Limitations of surface reflectance based imaging systems have been realized in analyzing images for important vascular and depth dependent information. We have developed a novel optical imaging system, the Nevoscope, that uses multispectral transillumination as to provide images of skin-lesions showing sub-surface pigmentation as well as vascular architecture based blood volume information. This paper presents multispectral Nevoscope transillumination method to compare and analyze ratiometric measurements to epiluminescence imaging for its ability to discriminate malignant melanomas from dysplastic nevi and other normal skin-lesions.

Multi-spectral imaging and analysis for classification of melanoma.

Wavelengths in the visible spectrum are selected for multi-spectral trans-illumination imaging of the skin lesions using the Nevoscope. The multi-spectral image data is analyzed using crisp and fuzzy partitioning techniques for classification of melanoma. It is shown that the multi-spectral images add the lesion depth and structural information to the superficial lesion characteristics obtained from the surface illumination images and hence, improve the sensitivity and specificity of melanoma diagnosis.