Purpose: A novel technique for beam profiling of megavoltage photon beams was investigated for the first time by capturing images of the inducedČerenkov emission in water, as a potential surrogate for the imparted dose in irradiated media. Methods: A high-sensitivity, intensified CCD camera (ICCD) was configured to acquire 2D projection images ofČerenkov emission from a 4 × 4 cm 2 6 MV linear accelerator (LINAC) x-ray photon beam operating at a dose rate of 400 MU/min incident on a water tank with transparent walls. The ICCD acquisition was gated to the LINAC sync pulse to reduce background light artifacts, and the measurement quality was investigated by evaluating the signal to noise ratio and measurement repeatability as a function of delivered dose. Monte Carlo simulations were used to derive a calibration factor for differences between the optical images and deposited dose arising from the anisotropic angular dependence ofČerenkov emission. Finally,Čerenkov-based beam profiles were compared to a percent depth dose (PDD) and lateral dose profile at a depth of d max from a reference dose distribution generated from the clinical Varian ECLIPSE treatment planning system (TPS). Results: The signal to noise ratio was found to be 20 at a delivered dose of 66.6 cGy, and proportional to the square root of the delivered dose as expected from Poisson photon counting statistics. A 2.1% mean standard deviation and 5.6% maximum variation in successive measurements were observed, and the Monte Carlo derived calibration factor resulted inČerenkov emission images which were directly correlated to deposited dose, with some spatial issues. The dose difference between the TPS and PDD predicted byČerenkov measurements was within 20% in the buildup region with a distance to agreement (DTA) of 1.5-2 mm and ±3% at depths beyond d max . In the lateral profile, the dose difference at the beam penumbra was within ±13% with a DTA of 0-2 mm, ±5% in the central beam region, and 2%-3% in the beam umbra. Conclusions:The results from this initial study demonstrate the first documented use ofČerenkov emission imaging to profile x-ray photon LINAC beams in water. The proposed modality has several potential advantages over alternative methods, and upon future refinement may prove to be a robust and novel dosimetry method.

Localized measurements of scattering in biological tissue provide sensitivity to microstructural morphology but have limited utility to wide-field applications, such as surgical guidance. This study introduces sub-diffusive spatial frequency domain imaging (sd-SFDI), which uses high spatial frequency illumination to achieve wide-field sampling of localized reflectances. Model-based inversion recovers macroscopic variations in the reduced scattering coefficient (μs′) and the phase function backscatter parameter (γ). Measurements in optical phantoms show quantitative imaging of user-tuned phase-function-based contrast with accurate decoupling of parameters that define both the density and the size-scale distribution of scatterers. Measurements of fresh ex vivo breast tissue samples revealed, for the first time, unique clustering of sub-diffusive scattering properties for different tissue types. The results support that sd-SFDI provides maps of microscopic structural biomarkers that cannot be obtained with diffuse wide-field imaging and characterizes spatial variations not resolved by point-based optical sampling.

Breast conserving surgery (BCS) is an effective treatment for early-stage cancers as long as the margins of the resected tissue are free of disease according to consensus guidelines for patient management. However, 15% to 35% of patients undergo a second surgery since malignant cells are found close to or at the margins of the original resection specimen. This review highlights imaging approaches being investigated to reduce the rate of positive margins, and they are reviewed with the assumption that a new system would need high sensitivity near 95% and specificity near 85%. The problem appears to be twofold. The first is for complete, fast surface scanning for cellular, structural, and/or molecular features of cancer, in a lumpectomy volume, which is variable in size, but can be large, irregular, and amorphous. A second is for full, volumetric imaging of the specimen at high spatial resolution, to better guide internal radiologic decision-making about the spiculations and duct tracks, which may inform that surfaces are involved. These two demands are not easily solved by a single tool. Optical methods that scan large surfaces quickly are needed with cellular/molecular sensitivity to solve the first problem, but volumetric imaging with high spatial resolution for soft tissues is largely outside of the optical realm and requires x-ray, micro-CT, or magnetic resonance imaging if they can be achieved efficiently. In summary, it appears that a combination of systems into hybrid platforms may be the optimal solution for these two very different problems. This concept must be cost-effective, image specimens within minutes and be coupled to decision-making tools that help a surgeon without adding to the procedure. The potential for optical systems to be involved in this problem is emerging and clinical trials are underway in several of these technologies to see if they could reduce positive margin rates in BCS.

This study investigates the hypothesis that structured light reflectance imaging with high spatial frequency patterns [Formula: see text] can be used to quantitatively map the anisotropic scattering phase function distribution [Formula: see text] in turbid media. Monte Carlo simulations were used in part to establish a semi-empirical model of demodulated reflectance ([Formula: see text]) in terms of dimensionless scattering [Formula: see text] and [Formula: see text], a metric of the first two moments of the [Formula: see text] distribution. Experiments completed in tissue-simulating phantoms showed that simultaneous analysis of [Formula: see text] spectra sampled at multiple [Formula: see text] in the frequency range [0.05-0.5] [Formula: see text] allowed accurate estimation of both [Formula: see text] in the relevant tissue range [0.4-1.8] [Formula: see text], and [Formula: see text] in the range [1.4-1.75]. Pilot measurements of a healthy volunteer exhibited [Formula: see text]-based contrast between scar tissue and surrounding normal skin, which was not as apparent in wide field diffuse imaging. These results represent the first wide-field maps to quantify sub-diffuse scattering parameters, which are sensitive to sub-microscopic tissue structures and composition, and therefore, offer potential for fast diagnostic imaging of ultrastructure on a size scale that is relevant to surgical applications.

The importance of preexisting versus acquired drug resistance in patients with cancer treated with small-molecule tyrosine kinase inhibitors (TKI) remains controversial. The goal of this study is to provide a general estimate of the size and dynamics of a preexisting, drug-resistant tumor cell population versus a slow-growing persister population that is the precursor of acquired TKI resistance. We describe a general model of resistance development, including persister evolution and preexisting resistance, solely based on the macroscopic trajectory of tumor burden during treatment. We applied the model to 20 tumor volume trajectories of EGFR-mutant lung cancer patients treated with the TKI erlotinib. Under the assumption of only preexisting resistant cells or only persister evolution, it is not possible to explain the observed tumor trajectories with realistic parameter values. Assuming only persister evolution would require very high mutation induction rates, while only preexisting resistance would lead to very large preexisting populations of resistant cells at the initiation of treatment. However, combining preexisting resistance with persister populations can explain the observed tumor volume trajectories and yields an estimated preexisting resistant fraction varying from 10 À4 to 10 À1 at the time of treatment initiation for this study cohort. Our results also demonstrate that the growth rate of the resistant population is highly correlated to the time to tumor progression. These estimates of the size of the resistant and persistent tumor cell population during TKI treatment can inform combination treatment strategies such as multi-agent schedules or a combination of targeted agents and radiotherapy.Significance: These findings quantify pre-existing resistance and persister cell populations, which are essential for the integration of targeted agents into the management of locally advanced disease and the timing of radiotherapy in metastatic patients.

Fluorescence guided surgery (FGS) is an emerging technology that has demonstrated improved surgical outcomes. However, dim lighting conditions required bycurrent FGS systems are disruptive to standard surgical workflow. We present a novel FGS system capable of imaging fluorescence under normal room lightby using pulsed excitation and gated acquisition. Images from tissue-simulating phantoms confirm visual detection down to 0.25 μM of protopor-phyrin IX under 125 μW/cm2 of ambient light, more than an order of magnitude lower than that measured with the Zeiss Pentero in the dark. Resection of orthotopic brain tumors in mice also suggests that the pulsed-light system provides superior sensitivity in vivo.

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Subdiffuse spatial frequency domain imaging (sd-SFDI) data of 42 freshly excised, bread-loafed tumor resections from breast-conserving surgery (BCS) were evaluated using texture analysis and a machine learning framework for tissue classification. Resections contained 56 regions of interest (RoIs) determined by expert histopathological analysis. RoIs were coregistered with sd-SFDI data and sampled into ∼4 × 4 mm 2 subimage samples of confirmed and homogeneous histological categories. Sd-SFDI reflectance textures were analyzed using gray-level co-occurrence matrix pixel statistics, image primitives, and power spectral density curve parameters. Texture metrics exhibited statistical significance (p-value < 0.05) between three benign and three malignant tissue subtypes. Pairs of benign and malignant subtypes underwent texture-based, binary classification with correlation-based feature selection. Classification performance was evaluated using fivefold cross-validation and feature grid searching. Classification using subdiffuse, monochromatic reflectance (illumination spatial frequency of f x ¼ 1.37 mm −1 , optical wavelength of λ ¼ 490 nm) achieved accuracies ranging from 0.55 (95% CI: 0.41 to 0.69) to 0.95 (95% CI: 0.90 to 1.00) depending on the benign-malignant diagnosis pair. Texture analysis of sd-SFDI data maintains the spatial context within images, is free of light transport model assumptions, and may provide an alternative, computationally efficient approach for wide field-of-view (cm 2) BCS tumor margin assessment relative to pixel-based optical scatter or color properties alone.