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Photodynamic therapy (PDT) offers localized focal ablation in unresectable pancreatic tumors while tissues surrounding the treatment volume experience a lower light dose, termed photodynamic priming (PDP). While PDP does not cause tissue damage, it has been demonstrated to promote vascular permeability, improve drug delivery, alleviate tumor cell density, and reduce desmoplasia and the resultant internal pressure in pre-clinical evaluation. Preclinical data supports PDP as a neoadjuvant therapy beneficial to subsequent chemotherapy or immunotherapy, yet it is challenging to quantify PDP effects in clinical treatment without additional imaging and testing. This study investigated the potential of radiomic analysis using CT scans acquired before and after PDT to identify areas experiencing PDT-induced necrosis as well as quantify PDP effects in the surrounding tissues. A total of 235 CT tumor slices from seven patients undergoing PDT for pancreatic tumors were examined. Radiomic features assessed included intensity metrics (CT number in Hounsfield Units) and texture analysis using several gray-level co-occurrence matrix (GLCM) parameters. Pre-treatment scans of tumor areas that resulted in PDT-induced necrosis showed statistically significant differences in intensity and texture-based features that could be used to predict the regions that did respond (paired t-test, response versus no response, p p

Purpose: The goal of this work was to create a technique that could measure all possible spatial and temporal delivery rates used in pencil-beam scanning (PBS) proton therapy. The proposed system used a fast scintillation screen for full-field imaging to resolve temporal and spatial patterns as it was delivered. Methods and Materials: A fast intensified CMOS camera imaged used continuous mode 10 ms temporal frame rate and 1x1 mm^2 spatial resolution, imaging a scintillation screen during clinical proton PBS delivery. PBS plans with varying dose, dose rate, energy, field size, and spot-spacing were generated, delivered and imaged. The captured images were post processed to provide dose and dose rate values after background subtraction, perspective transformation, uniformity correction for the camera and the scintillation screen, and calibration into dose. Results: The linearity in scintillation response with respect to varying dose rate, dose, and field size was within 2%. The quenching corrected response with varying energy was also within 2%. Large spatio-temporal variations in dose rate were observed, even for plans delivered with similar dose distributions. Dose and dose rate histograms and maximum dose rate maps were generated for quantitative evaluations. With the fastest PBS delivery on a clinical system, dose rates up to 26.0 Gy/s were resolved. Conclusions: The scintillation imaging technique was able to quantify proton PBS dose rate profiles with spot weight as low as 2 MU, with spot-spacing of 2.5 mm, having an ultimate 1x1 mm^2 spatial resolution. These dose rate temporal profiles, spatial maps, and cumulative dose rate histograms provide useful metrics for the potential evaluation and optimization of dose rate in treatment plans.

Surface dosimetry is required for ensuring effective administration of total skin electron therapy (TSET); however, its use is often reduced due to the time consuming and complex nature of acquisition. A new surface dose imaging technique was characterized in this study and found to provide accurate, rapid and remote measurement of surface doses without the need for post-exposure processing. Disc-shaped plastic scintillators (1 mm thick × 15 mm ) were chosen as optimal-sized samples and designed to attach to a flat-faced phantom for irradiation using electron beams. Scintillator dosimeter response to radiation damage, dose rate, and temperature were studied. The effect of varying scintillator diameter and thickness on light output was evaluated. Furthermore, the scintillator emission spectra and impact of dosimeter thickness on surface dose were also quantified. Since the scintillators were custom-machined, dosimeter-to-dosimeter variation was tested. Scintillator surface dose measurements were compared to those obtained by optically stimulated luminescence dosimeters (OSLD). Light output from scintillator dosimeters evaluated in this study was insensitive to radiation damage, temperature, and dose rate. Maximum wavelength of emission was found to be 422 nm. Dose reported by scintillators was linearly related to that from OSLDs. Build-up from placement of scintillators and OSLDs had a similar effect on surface dose (4.9% increase). Variation among scintillator dosimeters was found to be 0.3 ± 0.2%. Scintillator light output increased linearly with dosimeter thickness (~1.9 × /mm). All dosimeter diameters tested were able to accurately measure surface dose. Scintillator dosimeters can potentially improve surface dosimetry-associated workflow for TSET in the radiation oncology clinic. Since scintillator data output can be automatically recorded to a patient medical record, the chances of human error in reading out and recording surface dose are minimized.

Photodynamic therapy (PDT) can be a highly complex treatment, with many parameters influencing treatment efficacy. The extent to which dosimetry is used to monitor and standardize treatment delivery varies widely, ranging from measurement of a single surrogate marker to comprehensive approaches that aim to measure or estimate as many relevant parameters as possible. Today, most clinical PDT treatments are still administered with little more than application of a prescribed drug dose and timed light delivery, and thus the role of patient-specific dosimetry has not reached widespread clinical adoption. This disconnect is at least partly due to the inherent conflict between the need to measure and understand multiple parameters in vivo in order to optimize treatment, and the need for expedience in the clinic and in the regulatory and commercialization process. Thus, a methodical approach to selecting primary dosimetry metrics is required at each stage of translation of a treatment procedure, moving from complex measurements to understand PDT mechanisms in pre-clinical and early phase I trials, towards the identification and application of essential dose-limiting and/or surrogate measurements in phase II/III trials. If successful, identifying the essential and/or reliable surrogate dosimetry measurements should help facilitate increased adoption of clinical PDT. In this paper, examples of essential dosimetry points and surrogate dosimetry tools that may be implemented in phase II/III trials are discussed. For example, the treatment efficacy as limited by light penetration in interstitial PDT may be predicted by the amount of contrast uptake in CT, and so this could be utilized as a surrogate dosimetry measurement to prescribe light doses based upon pre-treatment contrast. Success of clinical ALA-based skin lesion treatment is predicted almost uniquely by the explicit or implicit measurements of photosensitizer and photobleaching, yet the individualization of treatment based upon each patients measured bleaching needs to be attempted. In the case of ALA, lack of PpIX is more likely an indicator that alternative PpIX production methods must be implemented. Parsimonious dosimetry, using surrogate measurements that are clinically acceptable, might strategically help to advance PDT in a medical world that is increasingly cost and time sensitive. Careful attention to methodologies that can identify and advance the most critical dosimetric measurements, either direct or surrogate, are needed to ensure successful incorporation of PDT into niche clinical procedures.

During external beam radiotherapy (EBRT), in vivo Cherenkov optical emissions can be used as a dosimetry tool or to excite luminescence, termed Cherenkov-excited luminescence (CEL) with microsecond-level time-gated cameras. The goal of this work was to develop a complete theoretical foundation for the detectable signal strength, in order to provide guidance on optimization of the limits of detection and how to optimize near real time imaging. The key parameters affecting photon production, propagation and detection were considered and experimental validation with both tissue phantoms and a murine model are shown. Both the theoretical analysis and experimental data indicate that the detection level is near a single photon-per-pixel for the detection geometry and frame rates commonly used, with the strongest factor being the signal decrease with the square of distance from tissue to camera. Experimental data demonstrates how the SNR improves with increasing integration time, but only up to the point where the dominance of camera read noise is overcome by stray photon noise that cannot be suppressed. For the current camera in a fixed geometry, the signal to background ratio limits the detection of light signals, and the observed in vivo Cherenkov emission is on the order of 100× stronger than CEL signals. As a result, imaging signals from depths 15 mm is reasonable for Cherenkov light, and depths 3 mm is reasonable for CEL imaging. The current investigation modeled Cherenkov and CEL imaging of two oxygen sensing phosphorescent compounds, but the modularity of the code allows for easy comparison of different agents or alternative cameras, geometries or tissues.

The development of methods to accurately quantify cell-surface receptors in living tissues would have a seminal impact in oncology. For example, accurate measures of receptor density in vivo could enhance early detection or surgical resection of tumors via protein-based contrast, allowing removal of cancer with high phenotype specificity. Alternatively, accurate receptor expression estimation could be used as a biomarker to guide patient-specific clinical oncology targeting of the same molecular pathway. Unfortunately, conventional molecular contrast-based imaging approaches are not well adapted to accurately estimating the nanomolar-level cell-surface receptor concentrations in tumors, as most images are dominated by nonspecific sources of contrast such as high vascular permeability and lymphatic inhibition. This article reviews approaches for overcoming these limitations based upon tracer kinetic modeling and the use of emerging protocols to estimate binding potential and the related receptor concentration. Methods such as using single time point imaging or a reference-tissue approach tend to have low accuracy in tumors, whereas paired-agent methods or advanced kinetic analyses are more promising to eliminate the dominance of interstitial space in the signals. Nuclear medicine and optical molecular imaging are the primary modalities used, as they have the nanomolar level sensitivity needed to quantify cell-surface receptor concentrations present in tissue, although each likely has a different clinical niche.

Megavoltage radiation beams used in External Beam Radiotherapy (EBRT) generate Cherenkov light emission in tissues and equivalent phantoms. This optical emission was utilized to excite an oxygen-sensitive phosphorescent probe, PtG4, which has been developed specifically for NIR lifetime-based sensing of the partial pressure of oxygen (pO2). Phosphorescence emission, at different time points with respect to the excitation pulse, was acquired by an intensifier-gated CCD camera synchronized with radiation pulses delivered by a medical linear accelerator. The pO2 distribution was tomographically recovered in a tissue-equivalent phantom during EBRT with multiple beams targeted from different angles at a tumor-like anomaly. The reconstructions were tested in two different phantoms that have fully oxygenated background, to compare a fully oxygenated and a fully deoxygenated inclusion. To simulate a realistic situation of EBRT, where the size and location of the tumor is well known, spatial information of a prescribed region was utilized in the recovery estimation. The phantom results show that region-averaged pO2 values were recovered successfully, differentiating aerated and deoxygenated inclusions. Finally, a simulation study was performed showing that pO2 in human brain tumors can be measured to within 15 mmHg for edge depths less than 10-20 mm using the Cherenkov Excited Phosphorescence Oxygen imaging (CEPhOx) method and PtG4 as a probe. This technique could allow non-invasive monitoring of pO2 in tumors during the normal process of EBRT, where beams are generally delivered from multiple angles or arcs during each treatment fraction.

Recent studies have proposed that light emitted by the Cherenkov effect may be used for a number of radiation therapy dosimetry applications. There is a correlation between the captured light and expected dose under certain conditions, yet discrepancies have also been observed and a complete examination of the theoretical differences has not been done. In this study, a fundamental comparison between the Cherenkov emission and absorbed dose was explored for x-ray photons, electrons, and protons using both a theoretical and Monte Carlo-based analysis. Based on the findings of where dose correlates with Cherenkov emission, it was concluded that for x-ray photons the light emission would be optimally suited for narrow beam stereotactic radiation therapy and surgery validation studies, for verification of dynamic intensity-modulated and volumetric modulated arc therapy treatment plans in water tanks, near monoenergetic sources (e.g., Co-60 and brachy therapy sources) and also for entrance and exit surface imaging dosimetry of both narrow and broad beams. For electron use, Cherenkov emission was found to be only suitable for surface dosimetry applications. Finally, for proton dosimetry, there exists a fundamental lack of Cherenkov emission at the Bragg peak, making the technique of little use, although post-irradiation detection of light emission from radioisotopes could prove to be useful.

Dual-tracer molecular imaging is a powerful approach to quantify receptor expression in a wide range of tissues by using an untargeted tracer to account for any nonspecific uptake of a molecular-targeted tracer. This approach has previously required the pharmacokinetics of the receptor-targeted and untargeted tracers to be identical, requiring careful selection of an ideal untargeted tracer for any given targeted tracer. In this study, methodology capable of correcting for tracer differences in arterial input functions, as well as binding-independent delivery and retention, is derived and evaluated in a mouse U251 glioma xenograft model using an Affibody tracer targeted to epidermal growth factor receptor (EGFR), a cell membrane receptor overexpressed in many cancers. Simulations demonstrated that blood, and to a lesser extent vascular-permeability, pharmacokinetic differences between targeted and untargeted tracers could be quantified by deconvolving the uptakes of the two tracers in a region of interest devoid of targeted tracer binding, and therefore corrected for, by convolving the uptake of the untargeted tracer in all regions of interest by the product of the deconvolution. Using fluorescently labeled, EGFR-targeted and untargeted Affibodies (known to have different blood clearance rates), the average tumor concentration of EGFR in four mice was estimated using dual-tracer kinetic modeling to be 3.9 ± 2.4 nM compared to an expected concentration of 2.0 ± 0.4 nM. However, with deconvolution correction a more equivalent EGFR concentration of 2.0 ± 0.4 nM was measured.

Čerenkov emission is generated from ionizing radiation in tissue above 264 keV energy. This study presents the first examination of this optical emission as a surrogate for the absorbed superficial dose. Čerenkov emission was imaged from the surface of flat tissue phantoms irradiated with electrons, using a range of field sizes from 6 cm × 6 cm to 20 cm × 20 cm, incident angles from 0° to 50°, and energies from 6 to 18 MeV. The Čerenkov images were compared with the estimated superficial dose in phantoms from direct diode measurements, as well as calculations by Monte Carlo and the treatment planning system. Intensity images showed outstanding linear agreement (R(2) = 0.97) with reference data of the known dose for energies from 6 to 18 MeV. When orthogonal delivery was carried out, the in-plane and cross-plane dose distribution comparisons indicated very little difference (± 2-4% differences) between the different methods of estimation as compared to Čerenkov light imaging. For an incident angle 50°, the Čerenkov images and Monte Carlo simulation show excellent agreement with the diode data, but the treatment planning system had a larger error (OPT = ± 1~2%, diode = ± 2~3%, TPS = ± 6-8% differences) as would be expected. The sampling depth of superficial dosimetry based on Čerenkov radiation has been simulated in a layered skin model, showing the potential of sampling depth tuning by spectral filtering. Taken together, these measurements and simulations indicate that Čerenkov emission imaging might provide a valuable method of superficial dosimetry imaging from incident radiotherapy beams of electrons.

Full 3D beam profiling and quality assurance (QA) of therapeutic megavoltage linear accelerator (LINAC) x-ray photon beams is not routinely performed due to the slow point-by-point measurement nature of conventional scanning ionization chamber systems. In this study we explore a novel optical-based dose imaging approach using a standard commercial camera, water tank, and fluorescent dye, which when excited by the Čerenkov emission induced by the radiation beam, allows 2D projection imaging in a fast timeframe, potentially leading toward 3D tomographic beam profiling. Detailed analysis was carried out to optimize the imaging parameters in the experimental setup. The results demonstrate that the captured images are linear with delivered dose, independent of dose rate, and comparison of experimentally captured images to a reference dose distribution for a 4 × 4 cm(2) 6 MV x-ray photon beam yielded results with improved accuracy over a previous study which used direct imaging and Monte Carlo calibration of the Čerenkov emission itself. The agreement with the reference dose distribution was within 1-2% in the lateral direction, and ±3% in the depth direction. The study was restricted to single 2D image projection, with the eventual goal of creating full 3D profiles after tomographic reconstruction from multiple projections. Given the increasingly complex advances in radiation therapy, and the increased emphasis on patient-specific treatment plans, further refinement of the technique could prove to be an important tool for fast and robust QA of x-ray photon LINAC beams.

Ionizing radiation delivered by a medical linear accelerator (LINAC) generates Cherenkov emission within the treated tissue. A fraction of this light, in the 600-900 nm wavelength region, propagates through centimeters of tissue and can be used to excite optical probes in vivo, enabling molecular sensing of tissue analytes. The success of isolating the emission signal from this Cherenkov excitation background is dependent on key factors such as: (i) the Stokes shift of the probe spectra; (ii) the excited state lifetime; (iii) the probe concentration; (iv) the depth below the tissue surface; and (v) the radiation dose used. Previous studies have exclusively focused on imaging phosphorescent dyes, rather than fluorescent dyes. However there are only a few biologically important phosphorescent dyes and yet in comparison there are thousands of biologically relevant fluorescent dyes. So in this study the focus was a study of efficacy of Cherenkov-excited luminescence using fluorescent commercial near-infrared probes, IRDye 680RD, IRDye 700DX, and IRDye 800CW, and comparing them to the well characterized phosphorescent probe Oxyphor PtG4, an oxygen sensitive dye. Each probe was excited by Cherenkov light from a 6 MV external radiation beam, and measured in continuous wave or time-gated modes. The detection was performed by spectrally resolving the luminescence signals, and measuring them with spectrometer-based separation on an ICCD detector. The results demonstrate that IRDye 700DX and PtG4 allowed for the maximal signal to noise ratio. In the case of the phosphorescent probe, PtG4, with emission decays on the microsecond (μs) time scale, time-gated acquisition was possible, and it allowed for higher efficacy in terms of the probe concentration and detection depth. Phantoms containing the probe at 5 mm depth could be detected at concentrations down to the nanoMolar range, and at depths into the tissue simulating phantom near 3 cm. In vivo studies showed that 5 nmol of dye was readily detected with radiation doses less than 5 cGy. Since concentration, radiation dose and depth each contribute to the level of the detected signal, it may be possible to improve any of these parameters at expense of the others. This paradigm of nanoMolar sensitivity for optical reporters in vivo introduces the concept of molecular sensing of tumors during therapy or diagnostically with biologically relevant concentrations of fluorescent reporters.

In many cases, kinetic modeling requires that the arterial input function (AIF)--the time-dependent arterial concentration of a tracer--be characterized. A straightforward method to measure the AIF of red and near-infrared optical dyes (e.g., indocyanine green) using a pulse oximeter is presented. The method is motivated by the ubiquity of pulse oximeters used in both preclinical and clinical applications, as well as the gap in currently available technologies to measure AIFs in small animals. The method is based on quantifying the interference that is observed in the derived arterial oxygen saturation (SaO₂) following a bolus injection of a light-absorbing dye. In other words, the change in SaO₂ can be converted into dye concentration knowing the chromophore-specific extinction coefficients, the true arterial oxygen saturation, and total hemoglobin concentration. A simple error analysis was performed to highlight potential limitations of the approach, and a validation of the method was conducted in rabbits by comparing the pulse oximetry method with the AIF acquired using a pulse dye densitometer. Considering that determining the AIF is required for performing quantitative tracer kinetics, this method provides a flexible tool for measuring the arterial dye concentration that could be used in a variety of applications.

The quantification of tumor molecular expression in vivo could have a significant impact for informing and monitoring immerging targeted therapies in oncology. Molecular imaging of targeted tracers can be used to quantify receptor expression in the form of a binding potential (BP) if the arterial input curve or a surrogate of it is also measured. However, the assumptions of the most common approaches (reference tissue models) may not be valid for use in tumors. In this study, the validity of reference tissue models is investigated for use in tumors experimentally and in simulations. Three different tumor lines were grown subcutaneously in athymic mice and the mice were injected with a mixture of an epidermal growth factor receptor- (EGFR-) targeted fluorescent tracer and an untargeted fluorescent tracer. A one-compartment plasma input model demonstrated that the transport kinetics of both tracers were significantly different between tumors and all potential reference tissues, and using the reference tissue model resulted in a theoretical underestimation in BP of 50 ± 37%. On the other hand, the targeted and untargeted tracers demonstrated similar transport kinetics, allowing a dual-tracer approach to be employed to accurately estimate binding potential (with a theoretical error of 0.23 ± 9.07%). These findings highlight the potential for using a dual-tracer approach to quantify receptor expression in tumors with abnormal hemodynamics, possibly to inform the choice or progress of molecular cancer therapies.

In this work, development and evaluation of a three dimensional (3D) finite element model (FEM) based on the diffusion approximation of time-domain (TD) near-infrared fluorescence light transport in biological tissue is presented. This model allows both excitation and fluorescence temporal point-spread function (TPSF) data to be generated for heterogeneous scattering and absorbing media of arbitrary geometry. The TD FEM model is evaluated via comparisons with analytical and Monte Carlo (MC) calculations and is shown to provide a quantitative accuracy which has less than 0.72% error in intensity and less than 37 ps error for mean-time. The use of the Born-Ratio normalized data is demonstrated to reduce data-mismatch between MC and FEM to less than 0.22% for intensity and less than 22 ps in mean-time. An image reconstruction framework, based on a 3D FEM formulation, is outlined and simulation results based on a heterogeneous mouse model with a source of fluorescence in the pancreas is presented. It is shown that using early photons (i.e. the photons detected within the first 200 picoseconds of the TPSF) improves the spatial resolution compared to using continuous-wave signals. It is also demonstrated, as expected, that the utilization of two time-gates (early and latest photons) can improve the accuracy both in terms of spatial resolution and recovered contrast.

Here we derived analytical solutions to diffuse light transport in biological tissue based on spectral deformation of diffused near-infrared measurements. These solutions provide a closed-form mathematical expression which predicts that the depth of a fluorescent molecule distribution is linearly related to the logarithm of the ratio of fluorescence at two different wavelengths. The slope and intercept values of the equation depend on the intrinsic values of absorption and reduced scattering of tissue. This linear behavior occurs if the following two conditions are satisfied: the depth is beyond a few millimeters, and the tissue is relatively homogenous. We present experimental measurements acquired with a broad-beam non-contact multi-spectral fluorescence imaging system using a hemoglobin-containing diffusive phantom. Preliminary results confirm that a significant correlation exists between the predicted depth of a distribution of protoporphyrin IX (PpIX) molecules and the measured ratio of fluorescence at two different wavelengths. These results suggest that depth assessment of fluorescence contrast can be achieved in fluorescence-guided surgery to allow improved intra-operative delineation of tumor margins.

Manipulation of interstitial fluid pressure (IFP) has a clinical potential when used in conjunction with near-infrared spectroscopy for the detection of breast cancer. In order to better interpret how the applied pressure alters the vascular space and interstitial water volumes in breast tissue, a study on tissue-mimicking, gelatin phantoms was carried out to mimic the translation of external force into internal pressures. A complete set of three-dimensional (3D) pressure maps were obtained for the interior volumes of phantoms as an external force of 10 mmHg was applied, using mixtures of elastic moduli 19 and 33 kPa to simulate adipose and fibroglandular values of breast tissue. Corresponding linear elastic finite element analysis (FEA) cases were formulated. Shear stress, nonlinear mechanical properties, gravity and tissue geometry were all observed to contribute to internal pressure distribution, with surface shear stresses increasing internal pressures near the surface to greater than twice the applied external pressure. Average pressures by depth were predicted by the linear elastic FEA models. FEA models were run for cases mimicking a 93 kPa tumor inclusion within regions of adipose, fibroglandular tissue, and a composite of the two tissue types to illustrate the localized high fluid pressures caused by a tumor when an external force is applied. The conclusion was that external contact forces can generate potentially clinically useful fluid pressure magnitudes in regions of sharp effective elastic modulus gradients, such as tumor boundaries.

Near-infrared (NIR) tomography is a technique used to measure light propagation through tissue and generate images of internal optical property distributions from boundary measurements. Most popular applications have concentrated on female breast imaging, neonatal and adult head imaging, as well as muscle and small animal studies. In most instances a highly scattering medium with a homogeneous refractive index is assumed throughout the imaging domain. Using these assumptions, it is possible to simplify the model to the diffusion approximation. However, biological tissue contains regions of varying optical absorption and scatter, as well as varying refractive index. In this work, we introduce an internal boundary constraint in the finite element method approach to modelling light propagation through tissue that accounts for regions of different refractive indices. We have compared the results to data from a Monte Carlo simulation and show that for a simple two-layered slab model of varying refractive index, the phase of the measured reflectance data is significantly altered by the variation in internal refractive index, whereas the amplitude data are affected only slightly.

A Monte Carlo model developed to simulate time-resolved fluorescence propagation in a semi-infinite turbid medium was validated against previously reported theoretical and computational results. Model simulations were compared to experimental measurements of fluorescence spectra and lifetimes on tissue-simulating phantoms for single and dual fibre-optic probe geometries. Experiments and simulations using a single probe revealed that scattering-induced artefacts appeared in fluorescence emission spectra, while fluorescence lifetimes were unchanged. Although fluorescence lifetime measurements are generally more robust to scattering artefacts than are measurements of fluorescence spectra, in the dual-probe geometry scattering-induced changes in apparent lifetime were predicted both from diffusion theory and via Monte Carlo simulation, as well as measured experimentally. In all cases, the recovered apparent lifetime increased with increasing scattering and increasing source-detector separation. Diffusion theory consistently underestimated the magnitude of these increases in apparent lifetime (predicting a maximum increase of approximately 15%), while Monte Carlo simulations and experiment were closely matched (showing increases as large as 30%). These results indicate that quantitative simulations of time-resolved fluorescence propagation in turbid media will be important for accurate recovery of fluorophore lifetimes in biological spectroscopy and imaging applications.

The goal of this study was to determine dominant factors affecting treatment response in pancreatic cancer photodynamic therapy (PDT), based on clinically available information in the VERTPAC-01 trial. This trial investigated the safety and efficacy of verteporfin PDT in 15 patients with locally advanced pancreatic adenocarcinoma. CT scans before and after contrast enhancement from the 15 patients in the VERTPAC-01 trial were used to determine venous-phase blood contrast enhancement and this was correlated with necrotic volume determined from post-treatment CT scans, along with estimation of optical absorption in the pancreas for use in light modeling of the PDT treatment. Energy threshold contours yielded estimates for necrotic volume based on this light modeling. Both contrast-derived venous blood content and necrotic volume from light modeling yielded strong correlations with observed necrotic volume (R² = 0.85 and 0.91, respectively). These correlations were much stronger than those obtained by correlating energy delivered versus necrotic volume in the VERTPAC-01 study and in retrospective analysis from a prior clinical study. This demonstrates that contrast CT can provide key surrogate dosimetry information to assess treatment response. It also implies that light attenuation is likely the dominant factor in the VERTPAC treatment response, as opposed to other factors such as drug distribution. This study is the first to show that contrast CT provides needed surrogate dosimetry information to predict treatment response in a manner which uses standard-of-care clinical images, rather than invasive dosimetry methods.

Diffuse optical tomography is an imaging technique whereby spatial maps of absorption and scattering coefficients are derived from the characteristics of multiply scattered light transmitted through the object. The system described here used four intensity-modulated light sources and measurements of the intensity and phase (relative to each source) at 16 or 20 detectors on the surface of a 10 cm diameter cylinder. An iterative Newton-Raphson algorithm was used to estimate the absorption and scattering coefficients at each pixel in a 17 x 17 array minimizing the difference between measured and calculated values of the intensity and phase at the measurement sites. Forward calculations of the intensity and phase were based on a multigrid finite-difference solution of the frequency domain diffusion equation. Numerical simulations were used to examine the resolution, contrast, and accuracy of the reconstructions as well as the effects of measurement noise, systematic uncertainties in source-detector location, and accuracy of the initial estimates for the optical properties. Experimental tests also confirmed that the system could identify and locate both scattering and absorbing inhomogeneities in a tissue-simulating phantom.

The goal of frequency-domain optical absorption spectroscopy is the non-invasive determination of the absorption coefficient of a specific tissue volume. Since this allows the concentration of endogenous and exogenous chromophores to be calculated, there is considerable potential for clinical application. The technique relies on the measurement of the phase and modulation of light, which is diffusely reflected or transmitted by the tissue when it is illuminated by an intensity-modulated source. A model of light propagation must then be used to deduce the absorption coefficient. For simplicity, it is usual to assume the tissue is either infinite in extent (for transmission measurements) or semi-infinite (for reflectance measurements). The goal of this paper is to examine the errors introduced by these assumptions when measurements are actually performed on finite volumes. Diffusion-theory calculations and experimental measurements were performed for slabs, cylinders and spheres with optical properties characteristic of soft tissues in the near infrared. The error in absorption coefficient is presented as a function of object size as a guideline to when the simple models may be used. For transmission measurements, the error is almost independent of the true absorption coefficient, which allows absolute changes in absorption to be measured accurately. The implications of these errors in absorption coefficient for two clinical problems--quantitation of an exogenous photosensitizer and measurement of haemoglobin oxygenation--are presented and discussed.

Near infrared tomography (NIR) is a novel imaging technique that can be used to reconstruct tissue optical properties from measurements of light propagation through tissue. More specifically NIR measurements over a range of wavelengths can be used to obtain internal images of physiologic parameters and these images can be used to detect and characterize breast tumour. To obtain good NIR measurements, it is essential to have good contact between the optical fibres and the breast which in-turn results in the deformation of the breast due to the soft plasticity of the tissue. In this work, a tissue deformation model of the female breast is presented that will account for the altered shape of the breast during clinical NIR measurements. Using a deformed model of a breast, simulated NIR data were generated and used to reconstruct images of tissue absorption and reduced scatter using several assumptions about the imaging domain. Using either a circular or irregular 2D geometry for image reconstruction produces good localization of the absorbing anomaly, but it leads to degradation of the image quality. By modifying the assumptions about the imaging domain to a 3D conical model, with the correct diameter at the plane of NIR measurement, significantly improves the quality of reconstructed images and helps reduce image artefacts. Finally, assuming a non-deformed breast shape for image reconstruction is shown to lead to poor quality images since the geometry of the breast is greatly altered, whereas using the correct deformed geometry produces the best images.