The low-LET radiation contribution to the tumor dose in diffusing alpha-emitters radiation therapy.

BACKGROUND: Diffusing alpha-emitters Radiation Therapy ("Alpha DaRT") is a new technique that enables the use of alpha particles for the treatment of solid tumors. Alpha DaRT employs interstitial sources carrying a few µ $\mu$ Ci of 224 $^{224}$ Ra below their surface, designed to release a chain of short-lived atoms (progeny of 224 $^{224}$ Ra) which emit alpha particles, along with beta, Auger, and conversion electrons, x- and gamma rays. These atoms diffuse around the source and create-primarily through their alpha decays-a lethal high-dose region measuring a few millimeters in diameter. PURPOSE: While previous studies focused on the dose from the alpha emissions alone, this work addresses the electron and photon dose contributed by the diffusing atoms and by the atoms remaining on the source surface, for both a single Alpha DaRT source and multi-source lattices. This allows to evaluate the low-LET contribution to the tumor dose and tumor cell survival, and demonstrate the sparing of surrounding healthy tissue. METHODS: The low-LET dose is calculated using the EGSnrc and FLUKA Monte Carlo (MC) codes. We compare the results of a simple line-source approximation with no diffusion to those of a full simulation, which implements a realistic source geometry and the spread of diffusing atoms. We consider two opposite scenarios: one with low diffusion and high 212 $^{212}$ Pb leakage, and the other with high diffusion and low leakage. The low-LET dose in source lattices is calculated by superposition of single-source contributions. Its effect on cell survival is estimated with the linear quadratic model in the limit of low dose rate. RESULTS: For sources carrying 3  µ $\umu$ Ci/cm 224 $^{224}$ Ra arranged in a hexagonal lattice with 4 mm spacing, the minimal low-LET dose between sources is ∼ 18 - 30 $\sim 18-30$  Gy for the two test cases and is dominated by the beta contribution. The low-LET dose drops below 5 Gy ∼ 3 $\sim 3$  mm away from the outermost source in the lattice with an effective maximal dose rate of < 0.04 $<0.04$  Gy/h. The accuracy of the line-source/no-diffusion approximation is ∼ 15 % $\sim 15\%$ for the total low-LET dose over clinically relevant distances (2-4 mm). The low-LET dose reduces tumor cell survival by a factor of ∼ 2 - 200 $\sim 2-200$ . CONCLUSIONS: The low-LET dose in Alpha DaRT can be modeled by conventional MC techniques with appropriate leakage corrections to the source activity. For 3  µ $\umu$ Ci/cm 224 $^{224}$ Ra sources, the contribution of the low-LET dose can reduce cell survival inside the tumor by up to two orders of magnitude. The low-LET dose to surrounding healthy tissue is negligible. Increasing source activities by a factor of 5 can bring the low-LET dose itself to therapeutic levels, in addition to the high-LET dose contributed by alpha particles, leading to a "self-boosted" Alpha DaRT configuration, and potentially allowing to increase the lattice spacing.

Automated thermal imaging monitors the local response to cervical cancer brachytherapy.

Malignant tumors have high metabolic and perfusion rates, which result in a unique temperature distribution as compared to healthy tissues. Here, we sought to characterize the thermal response of the cervix following brachytherapy in women with advanced cervical carcinoma. Six patients underwent imaging with a thermal camera before a brachytherapy treatment session and after a 7-day follow-up period. A designated algorithm was used to calculate and store the texture parameters of the examined tissues across all time points. We used supervised machine learning classification methods (K Nearest Neighbors and Support Vector Machine) and unsupervised machine learning classification (K-means). Our algorithms demonstrated a 100% detection rate for physiological changes in cervical tumors before and after brachytherapy. Thus, we showed that thermal imaging combined with advanced feature extraction could potentially be used to detect tissue-specific changes in the cervix in response to local brachytherapy for cervical cancer.

Label-free bacteria identification for clinical applications.

We have developed a system for bacteria identification based on absorption spectroscopy in the mid-infrared spectral range. The data collected are analyzed with a deep learning algorithm. It is based on a neural-network model which takes one-dimensional signal vectors and outputs a probability score of identification of a bacterium type by extracting micro and macro scale features, using convolutions and nonlinear operations. The results are achieved in real time and do not require any offline postprocessing. The study was done on 12 of the most common bacteria usually seen in clinical microbiology laboratories. The system sensitivity is 0.94 ± 0.04, with a specificity of 0.95 ± 0.02. The system can be extended to additional bacterium types and variants with no change to its hardware or software, but only updating the model's parameters. The system's accuracy, size, ease of operation and low cost make it suitable for use in any type of clinical setting.

A multimodal nanoparticles-based theranostic method and system.

We propose a nanoparticles-based system for the early detection of tumors, treatment under real-time feedback, and monitoring. The building blocks of the system comprise a few modalities that are integrated into one powerful system which can operate at the patient's bedside in an outpatient clinic setting. The method relies on the unique characteristics of superparamagnetic nanoparticles. It takes advantage of their ability to produce acoustical signals under alternating magnetic fields (AMFs) and to produce heat under these same AMFs with different parameters. It utilizes the nanoparticles' coating for specific binding. The manuscript describes the various parts of this method for localization, source separation, confined heat elevation, triggering of cell death, and monitoring the response to treatment through fluorescence signaling. The entire system continues to evolve into a minimally invasive trans-endoscopic set-up. This article is categorized under: Diagnostic Tools > In Vivo Nanodiagnostics and Imaging Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease.

Hollow core photonic crystal fiber-assisted Raman spectroscopy as a tool for the detection of Alzheimer's disease biomarkers.

SIGNIFICANCE: Alzheimer's disease (AD) is an irreversible and progressive disorder that damages brain cells and impairs the cognitive abilities of the affected. Developing a sensitive and cost-effective method to detect Alzheimer's biomarkers appears vital in both a diagnostic and therapeutic perspective. AIM: Our goal is to develop a sensitive and reliable tool for detection of amyloid ß (1-42) peptide (Aß42), a major AD biomarker, using fiber-enhanced Raman spectroscopy (FERS). APPROACH: A hollow core photonic crystal fiber (HCPCF) was integrated with a conventional Raman spectroscopic setup to perform FERS measurements. FERS was then coupled with surface-enhanced Raman spectroscopy (SERS) to further amplify the Raman signal thanks to a combined FERS-SERS assay. RESULTS: A minimum 20-fold enhancement of the Raman signal of Aß42 as compared to a conventional Raman spectroscopy scheme was observed using the HCPCF-based light delivery system. The signal was further boosted by decorating the fiber core with gold bipyramids generating an additional SERS effect, resulting in an overall 200 times amplification. CONCLUSIONS: The results demonstrate that the use of an HCPCF-based platform can provide sharp and intense Raman signals of Aß42, in turn paving the way toward the development of a sensitive label-free detection tool for early diagnosis of AD.

High-resolution imaging system with an annular aperture of coded phase masks for endoscopic applications.

Partial aperture imaging is a combination of two different techniques; coded aperture imaging and imaging through an aperture that is only a part of the complete disk, commonly used as the aperture of most imaging systems. In the present study, the partial aperture is a ring where the imaging through this aperture resolves small details of the observed scene similarly to the full disk aperture with the same diameter. However, unlike the full aperture, the annular aperture enables using the inner area of the ring for other applications. In this study, we consider the implementation of this special aperture in medical imaging instruments, such as endoscopes, for imaging internal cavities in general and of the human body in particular. By using this annular aperture, it is possible to transfer through the internal open circle of the ring other elements such as surgical tools, fibers and illumination devices. In the proposed configuration, light originated from a source point passes through an annular coded aperture and creates a sparse, randomly distributed, intensity dot pattern on the camera plane. A combination of the dot patterns, each one recorded only once, is used as the point spread hologram of the imaging system. The image is reconstructed digitally by cross correlation between the object intensity response and the point spread hologram.

Thermal Monitoring of Tumor and Tissue State during Radiation Therapy - A Complex Case of Radiation Recall.

Common radiation dermatitis over radiation fields can be mild as minor erythema but can also be associated with blisters and skin desquamation. This phenomenon has been widely investigated and documented, especially in breast cancer patients. Obesity, smoking, and diabetes are known risk factors; however, we cannot predict the severity of radiation dermatitis prior to treatment. The overwhelming radiation recall dermatitis is an acute inflammatory reaction confined to previously irradiated areas that can be triggered when chemotherapy agents are administered after radiotherapy. This rare, painful skin reaction leads to treatment cessation or alteration. In this study, we investigate the feasibility of using thermography as a tool to predict the response of normal breast tissue and skin to radiation therapy and the risk of developing radiation recall dermatitis. Six women with viable in-breast tumor (breast cancer) and eight women who underwent tumor resection (lumpectomy) were monitored by a thermal camera prior to radiotherapy treatment (breast region) and on weekly basis, in the same environmental conditions, through the radiation course of treatment. One patient developed radiation recall dermatitis when treated with chemotherapy following radiation therapy, and needed intensive local treatments and narcotics with full recovery thereafter. Clinical and treatment data as well as response to radiation were collected prospectively. The ongoing thermal changes observed during the radiation treatment for all patients, with and without viable tumor in the breast, were documented, analyzed, and reported here with detailed comparison to the recognized data for the patient diagnosed with radiation recall dermatitis.

Thermal imaging as a tool for evaluating tumor treatment efficacy.

Breast cancer is the most frequently diagnosed cancer among women in the Western world. Thermography is a nonionizing, noninvasive, portable, and low-cost method that can be used in an outpatient clinic. It was tried as a tool to detect breast cancer tumors, however, it had too many false readings. Thermography has been extensively studied as a breast cancer detection tool but was not used as a treatment monitoring tool. The purpose of this study was to investigate the possibility of using thermal imaging as a feedback system to optimize radiation therapy. Patients were imaged with a thermal camera prior and throughout the radiotherapy sessions. At the end of the session, the images were analyzed for temporal vasculature changes through vessels segmentation image processing tools. Tumors that were not responsive to treatment were observed before the radiation therapy sessions were concluded. Assessing the efficacy of radiotherapy during treatment makes it possible to change the treatment regimen, dose, and radiation field during treatment as well as to individualize treatment schedules to optimize treatment effectiveness.

A Reconstruction Method for the Estimation of Temperatures of Multiple Sources Applied for Nanoparticle-Mediated Hyperthermia.

Solid malignant tumors are one of the leading causes of death worldwide. Many times complete removal is not possible and alternative methods such as focused hyperthermia are used. Precise control of the hyperthermia process is imperative for the successful application of such treatment. To that end, this research presents a fast method that enables the estimation of deep tissue heat distribution by capturing and processing the transient temperature at the boundary based on a bio-heat transfer model. The theoretical model is rigorously developed and thoroughly validated by a series of experiments. A 10-fold improvement is demonstrated in resolution and visibility on tissue mimicking phantoms. The inverse problem is demonstrated as well with a successful application of the model for imaging deep-tissue embedded heat sources. Thereby, allowing the physician then ability to dynamically evaluate the hyperthermia treatment efficiency in real time.

Quantitative study of optical and mechanical bone status using multispectral photoacoustics.

Osteoporosis is a major public health problem worldwide. Here, we present a quantitative multispectral photoacoustic method for the evaluation of bone pathologies which has significant advantages over pure ultrasonic or pure optical methods as it provides both molecular information and bone mechanical status. This is enabled via a simultaneous measurement of the bone's optical properties as well as the speed of sound and ultrasonic attenuation in the bone. To test the method's quantitative predictions, a combined ultrasonic and photoacoustic system was developed. Excitation was performed optically via a portable triple laser-diode system and acoustically via a single element transducer. Additional dual transducers were used for detecting the acoustic waves that were generated by the two modalities. Both temporal and spectral parameters were compared between different excitation wavelengths and measurement modalities. Short photoacoustic excitation wavelengths allowed sensing of the cortical layer while longer wavelengths produced results which were compatible with the quantitative ultrasound measurements.

Proposed method for internal electron therapy based on high-intensity laser acceleration.

Radiotherapy is one of the main methods to treat cancer. However, due to the propagation pattern of high-energy photons in tissue and their inability to discriminate between healthy and malignant tissues, healthy tissues may also be damaged, causing undesired side effects. A possible method for internal electron therapy, based on laser acceleration of electrons inside the patient's body, is suggested. In this method, an optical waveguide, optimized for high intensities, is used to transmit the laser radiation and accelerate electrons toward the tumor. The radiation profile can be manipulated in order to create a patient-specific radiation treatment profile by changing the laser characteristics. The propagation pattern of electrons in tissues minimizes the side effects caused to healthy tissues. A simulation was developed to demonstrate the use of this method, calculating the trajectories of the accelerated electron as a function of laser properties. The simulation was validated by comparison to theory, showing a good fit for laser intensities of up to 2 × 10(20) (W/cm2), and was then used to calculate suggested treatment profiles for two tumor test cases (with and without penetration to the tumor). The results show that treatment profiles can be designed to cover tumor area with minimal damage to adjacent tissues.

Monitoring tumor state from thermal images in animal and human models.

PURPOSE: Thermography is a potentially useful method for tumor progress monitoring since it is noninvasive, nonradiative, low-cost, and rapid. Perfusion and metabolism are dominant factors for determining tumor temperature difference and are also correlated to the tumor's growth rate. Therefore, estimating them from the tumor thermal image can be a very useful tumor monitoring method, since thermal changes occur before physical changes. The goal of this work was to study the effect of tumor state on the thermal image in different tumor types, using simulations and measurements. METHODS: Simulated tumor models, representing flat and extruding tumors, typical to transplantable and natural tumors, respectively, were simulated and the effects of tumor metabolism and perfusion on the temperature difference were analyzed. Data regarding tumor size and measured temperature differences were obtained from the literature, discussing five types of transplantable tumors in mice and rats. The growth rates of all tumors were calculated by fitting tumor size measurements to a tumor growth model and were used as an indicator to tumor aggressiveness. Tumor temperature difference was calculated by taking the effect of its extruding shape into account, according to a previously published method. Tumor state was estimated from the normalized temperature differences using simulations and compared to the calculated aggressiveness rates. Computational models of human breast cancers, both in round and flat breast models, were recreated using a finite-element-method heat transfer simulation. Tumor size and state were simulated according to the results obtained from the animal tumor analysis, representing two different tumor aggressiveness levels. The calculated temperature difference as a function of tumor size was calculated for each test case. RESULTS: Perfusion was shown to be highly dominant in determining the tumor's temperature difference. Since both metabolism and perfusion were shown to have a linear effect on the temperature difference, a conversion value was defined between them. The analysis of the animal experimental results showed correlations between tumor aggressiveness and the following factors: the normalized temperature difference, the estimated tumor state, and the temperature difference change rate. The simulated human breast cancer models analysis showed highly varying temperature differences between the simulated models. Although for each model there is a clear difference between the temperature differences of the test cases simulated, the large differences between the results might make tumor state estimation difficult. However, reviewing the gradient of the tumor temperature change as a function of tumor size showed that the ratio between the gradients of both test cases was similar for all models. Therefore, the effect of model errors and differences in the simulated tissue structure and properties and the environmental conditions between the different models, can be mitigated. This pattern may be used to estimate tumor state in in vivo experiments. CONCLUSIONS: Continuous monitoring of tumor temperature difference produces valuable information on tumor state and aggressiveness that can be used both in the clinic and in the laboratory. Monitoring can be either performed on a single image, or continuous on multiple images, revealing changes in tumor state.

The effect of geometry on tumor thermal profile and its use in tumor functional state estimation.

Thermal differences between transplanted tumors and tumors in humans prevent the implementation of thermographic methods developed in mice models to human models and vise-versa. Transplantable tumors tend to have an extruding shape, which may affect the thermal patterns. This hypothesis was studied in phantom experiments and simulations. A correlation between tumor dimensions and relative temperature was found and used to estimate tumor functional state from previously published in vivo experiments. A correlation was found between temperature differences and tumor growth rates (tumor aggressiveness) and the effect of tumor treatment was demonstrated, showing the potential for in vivo, non-invasive tumor monitoring.

3D discrete angiogenesis dynamic model and stochastic simulation for the assessment of blood perfusion coefficient and impact on heat transfer between nanoparticles and malignant tumors.

Early detection of malignant tumors plays a crucial role in the survivability chances of the patient. Therefore, new and innovative tumor detection methods are constantly searched for. Tumor-specific magnetic-core nano-particles can be used with an alternating magnetic field to detect and treat tumors by hyperthermia. For the analysis of the method effectiveness, the bio-heat transfer between the nanoparticles and the tissue must be carefully studied. Heat diffusion in biological tissue is usually analyzed using the Pennes Bio-Heat Equation, where blood perfusion plays an important role. Malignant tumors are known to initiate an angiogenesis process, where endothelial cell migration from neighboring vasculature eventually leads to the formation of a thick blood capillary network around them. This process allows the tumor to receive its extensive nutrition demands and evolve into a more progressive and potentially fatal tumor. In order to assess the effect of angiogenesis on the bio-heat transfer problem, we have developed a discrete stochastic 3D model & simulation of tumor-induced angiogenesis. The model elaborates other angiogenesis models by providing high resolution 3D stochastic simulation, capturing of fine angiogenesis morphological features, effects of dynamic sprout thickness functions, and stochastic parent vessel generator. We show that the angiogenesis realizations produced are well suited for numerical bio-heat transfer analysis. Statistical study on the angiogenesis characteristics was derived using Monte Carlo simulations. According to the statistical analysis, we provide analytical expression for the blood perfusion coefficient in the Pennes equation, as a function of several parameters. This updated form of the Pennes equation could be used for numerical and analytical analyses of the proposed detection and treatment method.

Fluorescent probes concentration estimation in vitro and ex vivo as a model for early detection of Alzheimer's disease.

The pathogenic process of Alzheimer's disease (AD) begins years before clinical diagnosis. Here, we suggest a method that may detect AD several years earlier than current exams. The method is based on previous reports that relate the concentration ratio of biomarkers (amyloid-beta and tau) in the cerebrospinal fluid (CSF) to the development of AD. Our method replaces the lumbar puncture process required for CSF drawing by using fluorescence measurements. The system uses an optical fiber coupled to a laser source and a detector. The laser radiation excites two fluorescent probes which may bond to the CSF biomarkers. Their concentration ratio is extracted from the fluorescence intensities and can be used for future AD detection. First, we present a theoretical model for fluorescence concentration ratio estimation. The method's feasibility was validated using Monte Carlo simulations. Its accuracy was then tested using multilayered tissue phantoms simulating the epidural fat, CSF, and bone. These phantoms have various optical properties, thicknesses, and fluorescence concentrations in order to simulate human anatomy variations and different fiber locations. The method was further tested using ex vivo chicken tissue. The average errors of the estimated concentration ratios were low both in vitro (4.4%) and ex vivo (10.9%), demonstrating high accuracy.

Robust estimation of cerebral hemodynamics in neonates using multilayered diffusion model for normal and oblique incidences.

The diffusion approximation is useful for many optical diagnostics modalities, such as near-infrared spectroscopy. However, the simple normal incidence, semi-infinite layer model may prove lacking in estimation of deep-tissue optical properties such as required for monitoring cerebral hemodynamics, especially in neonates. To answer this need, we present an analytical multilayered, oblique incidence diffusion model. Initially, the model equations are derived in vector-matrix form to facilitate fast and simple computation. Then, the spatiotemporal reflectance predicted by the model for a complex neonate head is compared with time-resolved Monte Carlo (TRMC) simulations under a wide range of physiologically feasible parameters. The high accuracy of the multilayer model is demonstrated in that the deviation from TRMC simulations is only a few percent even under the toughest conditions. We then turn to solve the inverse problem and estimate the oxygen saturation of deep brain tissues based on the temporal and spatial behaviors of the reflectance. Results indicate that temporal features of the reflectance are more sensitive to deep-layer optical parameters. The accuracy of estimation is shown to be more accurate and robust than the commonly used single-layer diffusion model. Finally, the limitations of such approaches are discussed thoroughly.

Monitoring LITT thermal penetration depth using real-time analysis of backscattered light.

Real-time monitoring of the thermal penetration depth (TPD) is essential in various clinical procedures, such as Laser Interstitial Thermal Therapy (LITT). MRI is commonly used to this end, though bulky and expensive. In this paper, we present an alternative novel method for an optical feedback system based on changes in the diffused reflection from the tissue during treatment. Monte-Carlo simulation was used to deduce the relations between the backscattered pattern and the TPD. Several methods of image analysis are developed for TPD estimation. Each yields a set of parameters which are linearly dependent on the TPD. In order to test these experimentally, tissue samples were monitored in-vitro during treatment at multiple wavelengths. The SNR and coefficient of determination were used to compare the various methods and wavelengths and to determine the preferred method. Such system and algorithms may be used for real-time in-vivo control during laser thermotherapy and other clinical procedures.