Linda Ahnen

Clinical evaluation of an anatomy-based patient specific quality assurance system

The Delta4DVH Anatomy 3D quality assurance (QA) system (ScandiDos), which converts the measured detector dose into the dose distribution in the patient geometry was evaluated. It allows a direct comparison of the calculated 3D dose with the measured back‐projected dose. In total, 16 static and 16 volumetric‐modulated arc therapy (VMAT) fields were planned using four different energies. Isocenter dose was measured with a pinpoint chamber in homogeneous phantoms to investigate the dose prediction by the Delta4DVH Anatomy algorithm for static fields. Dose distributions of VMAT fields were measured using GAFCHROMIC film. Gravitational gantry errors up to 10° were introduced into all VMAT plans to study the potential of detecting errors. Additionally, 20 clinical treatment plans were verified. For static fields, the Delta4DVH Anatomy predicted the isocenter dose accurately, with a deviation to the measured phantom dose of 1.1%±0.6%. For VMAT fields the predicted Delta4DVH Anatomy dose in the isocenter plane corresponded to the measured dose in the phantom, with an average gamma agreement index (GAI) (3u2009mm/3%) of 96.9±0.4%. The Delta4DVH Anatomy detected the induced systematic gantry error of 10° with a relative GAI (3u2009mm/3%) change of 5.8%±1.6%. The conventional Delta4PT QA system detected a GAI change of 4.2%±2.0%. The conventional Delta4PT GAI (3u2009mm/3%) was 99.8%±0.4% for the clinical treatment plans. The mean body and PTV‐GAI (3u2009mm/5%) for the Delta4DVH Anatomy were 96.4%±2.0% and 97.7%±1.8%; however, this dropped to 90.8%±3.4% and 87.1%±4.1% for passing criteria of 3u2009mm/3%. The anatomy‐based patient specific quality assurance system predicts the dose distribution correctly for a homogeneous case. The limiting factor for the error detection is the large variability in the error‐free plans. The dose calculation algorithm is inferior to that used in the TPS (Eclipse). PACS numbers: 87.56.Fc, 87.56.‐v

Near-Infrared Image Reconstruction of Newborns’ Brains: Robustness to Perturbations of the Source/Detector Location

The brain of preterm infants is the most vulnerable organ and can be severely injured by cerebral ischemia. We are working on a near-infrared imager to early detect cerebral ischemia. During imaging of the brain, movements of the newborn infants are inevitable and the near-infrared sensor has to be able to function on irregular geometries. Our aim is to determine the robustness of the near-infrared image reconstruction to small variations of the source and detector locations. In analytical and numerical simulations, the error estimations for a homogeneous medium agree well. The worst case estimates of errors in reduced scattering and absorption coefficient for distances of r=40 mm are acceptable for a single source-detector pair. The optical properties of an inhomogeneity representing an ischemia are reconstructed correctly within a homogeneous medium, if the error in placement is random.

Multispectral Near-Infrared Optical Tomography for Cancer Hypoxia Study in Mice

Oxygenation of a tumor is one of the most important predictive factors: hypoxia is associated with aggressive tumors and substantially lower survival rate. Despite this high relevance of tumor oxygenation, there is currently no bedside technique available to measure it in clinical routine care. The aim of this work is to determine the oxygenation of tissue in mice by a continuous wave multispectral near-infrared optical tomograph (mNIROT). Tomographic reconstructions were processed by a massively modified NIRFAST software. We quantitatively measured the tissue oxygen saturation of the tumors in 4 BALB/c nude, female mice with human colon carcinoma cancer cells DLD-1 KRASwt injected subcutaneously. The study revealed changes of oxygenation in tumors on the long-term.

Discrimination of Complex Activation Patterns in Near Infrared Optical Tomography with Artificial Neural Networks

Near-infrared optical tomography (NIROT) has great promise for many clinical problems. Here we focus on the study of brain function. During NIROT image reconstruction of brain activity, an inverse problem has to be solved that is sensitive to small superficial perturbations on the head such as e.g. birthmarks on the skin and hair. To consider these perturbations, standard physical modeling is unpractical, since it requires the implementation of detailed information that is generally unavailable. The aim here was to test whether artificial neural networks (ANN) are able to handle such perturbations and thus detect brain activity correctly. For simplicity, we created a virtual test model, where we simulated a pattern of activated and resting brain regions, which was covered by skin features like hair or melanin. We compared the performance of this ANN approach with that of an inverse problem based on a Monte Carlo (MC) model for light propagation. We conclude that ANNs tolerate substantially higher levels of skin perturbations than MC models and consequently are more suitable for detecting brain activity.

A New Method Based on Virtual Fluence Detectors and Software Toolbox for Handheld Spectral Optoacoustic Tomography

A minimal setup for optoacoustic (OA) imaging requires an ultrasound probe and a pulsed laser. Such a system is capable of imaging small blood vessels and is sensitive to variations in their oxygen saturation. However, absolute oxygenation values cannot be obtained without a proper correction for the varying light fluence resulting from the optical attenuation in the surrounding tissue. Other techniques, such as near-infrared optical tomography (NIROT) can be employed to assist OA imaging for fluence compensation. In this paper, we propose using blood vessels as virtual fluence detectors (VD), which serve as light detectors for NIROT image reconstructions. By avoiding the use of real photon detectors, a simpler system could be implemented in a hand-held device comparable in size with conventional ultrasound probes. Even for a low number of VDs it provides increased informational value which, in combination with a large number of light sources, results in precise reconstructions. We define a tomographic inverse problem based on ratios of OA signals measured at several wavelengths where optical properties of VDs, tumor and normal tissue can be reconstructed simultaneously. The use of ratio data effectively removes light source skin coupling errors for the case of emission in a single point, which is required for clinical applications. We have defined the mathematical structure of an inverse problem where chromophore concentrations for normal, tumor and embedded VDs are obtained simultaneously from this ratio data. To test the performance of our approach we show an image reconstruction on a virtual phantom with an embedded tumor in the vicinity of eight blood vessels. We conclude that this limited number of VDs, located in areas of maximum sensitivity result in high quality reconstructions. For the simplest case of a single blood vessel located in a homogeneous tissue, we present a graphical user interface based toolbox for conducting virtual experiments. The toolbox can be used to assist in the design and optimization of suitable hardware for different applications, among which imaging tumor oxygenation and ischemic lesions in the brain of preterm infants are of great clinical value.

Optical properties of mice's stool in 550 to 1000 nm wavelength range

The aim of this work was to measure optical properties of stool of mice to provide this relevant wavelength-dependent behavior for optical imaging modalities such as fluorescent molecular tomography and near-infrared optical tomography. BALB/c nude female mice were studied and optical properties of the stool were determined by employing the inverse adding-doubling approach. The animals were kept on chlorophyll-free diet. Nine stool samples were measured. The wavelength-dependent behavior of absorption and scattering in 550 to 1000u2009nm range is presented. The reduced scattering spectrum is fitted to the Mie scattering approximation in the near-infrared (NIR) wavelength range and to the Mieu2009+u2009Rayleigh approximation in visible/NIR range with the fitting coefficients presented. The study revealed that the absorption spectrum of stool can lead to crosstalk with the spectrum of hemoglobin in the NIR range.

Spectral correction for handheld optoacoustic imaging by means of near-infrared optical tomography in reflection mode

In vivo imaging of tissue/vasculature oxygen saturation levels is of prime interest in many clinical applications. To this end, the feasibility of combining two distinct and complementary imaging modalities is investigated: optoacoustics (OA) and near‐infrared optical tomography (NIROT), both operating noninvasively in reflection mode. Experiments were conducted on two optically heterogeneous phantoms mimicking tissue before and after the occurrence of a perturbation. OA imaging was used to resolve submillimetric vessel‐like optical absorbers at depths up to 25u2009mm, but with a spectral distortion in the OA signals. NIROT measurements were utilized to image perturbations in the background and to estimate the light fluence inside the phantoms at the wavelength pair (760u2009nm, 830u2009nm). This enabled the spectral correction of the vessel‐like absorbers OA signals: the error in the ratio of the absorption coefficient at 830u2009nm to that at 760u2009nm was reduced from 60%‐150% to 10%‐20%. The results suggest that oxygen saturation (SO 2) levels in arteries can be determined with <10% error and furthermore, that relative changes in vessels SO 2 can be monitored with even better accuracy. The outcome relies on a proper identification of the OA signals emanating from the studied vessels.

Time Domain Near-Infrared Optical Tomography with Time-of-Flight SPAD Camera: The New Generation, Biophotonics Congress: Biomedical Optics Congress 2018 (Microscopy/Translational/Brain/OTS)

We present the first laboratory results of the new generation of time domain near-infrared optical tomography setup, which is based on a time-of-flight 32×32 SPAD camera with high photon detection probability in the NIR range.

A New Method Based on Graphics Processing Units for Fast Near-Infrared Optical Tomography

The accuracy of images obtained by Diffuse Optical Tomography (DOT) could be substantially increased by the newly developed time resolved (TR) cameras. These devices result in unprecedented data volumes, which present a challenge to conventional image reconstruction techniques. In addition, many clinical applications require taking photons in air regions like the trachea into account, where the diffusion model fails. Image reconstruction techniques based on photon tracking are mandatory in those cases but have not been implemented so far due to computing demands. We aimed at designing an inversion algorithm which could be implemented on commercial graphics processing units (GPUs) by making use of information obtained with other imaging modalities. The method requires a segmented volume and an approximately uniform value for the reduced scattering coefficient in the volume under study. The complex photon path is reduced to a small number of partial path lengths within each segment resulting in drastically reduced memory usage and computation time. Our approach takes advantage of wavelength normalized data which renders it robust against instrumental biases and skin irregularities which is critical for realistic clinical applications. The accuracy of this method has been assessed with both simulated and experimental inhomogeneous phantoms showing good agreement with target values. The simulation study analyzed a phantom containing a tumor next to an air region. For the experimental test, a segmented cuboid phantom was illuminated by a supercontinuum laser and data were gathered by a state of the art TR camera. Reconstructions were obtained on a GPU-installed computer in less than 2xa0h. To our knowledge, it is the first time Monte Carlo methods have been successfully used for DOT based on TR cameras. This opens the door to applications such as accurate measurements of oxygenation in neck tumors where the presence of air regions is a problem for conventional approaches.

Development and Validation of a Sensor Prototype for Near-Infrared Imaging of the Newborn Brain

Imaging brain oxygenation is crucial for preventing brain lesions in preterm infants. Our aim is to build and validate a near-infrared optical tomography (NIROT) sensor for the head of neonates. This sensor, combined with an optoacoustic device, will enable quantitative monitoring of the structural and functional information of the brain. Since the head of preterm infants is small and fragile great care must be taken to produce a comfortable and compact device in which a sufficient number of light sources and detectors can be implemented. Here we demonstrate our first prototype. Heterogeneous silicone phantoms were produced to validate the prototypes data acquisition, data processing, and image reconstruction. Reconstructed optical properties agree well with the target values. The mechanical performance of the new NIROT sensor prototype confirms its suitability for the clinical application.