Pancreatic cancer (PC) is one of the most lethal cancers, with frequent local therapy resistance and dismal 5-year survival rate. To date, surgical resection remains to be the only treatment option offering potential cure. Unfortunately, at diagnosis, the majority of patients demonstrate varying levels of vascular infiltration, which can contraindicate surgical resection. Patients unsuitable for immediate

Positron emission tomography (PET) has been used for dose verification in charged particle therapy. The causes of washout of positron emitters by physiological functions should be clarified for accurate dose verification. In this study, we visualized the distribution of irradiated radioactive beams, 11 C and 15 O beams, in the rabbit whole-body using our original depth-of-interaction (DOI)-PET prototype

Several direct algorithms have been proposed to take into account the non-linear path of protons in the reconstruction of a proton CT (pCT) image. This paper presents a comparison between five of them, in terms of spatial resolution and relative stopping power (RSP) accuracy. Our comparison includes (1) a distance-driven algorithm extending the filtered backprojection to non-linear trajectories (DD)

The high dose and dose-per-pulse rates (up to 130 mGy/pulse) produced by some Intraoperative Radiation Therapy (IORT) accelerators pose specific dosimetric problems due to the high density of electric charge per pulse produced in the ionization chamber cavity. In particular, the correction factor for ion recombination, kscalculated with the two-voltage method is significantly overestimated and three

Low-energy X-ray imaging of secondary electron bremsstrahlung X-rays emitted during carbon-ion irradiation is a promising method for range estimation and could be used for imaging with almost clinical dose levels of carbon ion. However, the number of counts in images with clinical dose levels is relatively small, making it difficult to obtain precise range estimations. Since improving the sensitivity

An accurate knowledge of in vivo proton dose distribution is key to fully utilizing the potential advantages of proton therapy. Two representative indirect methods for in vivo range verification, namely, prompt gamma (PG) imaging and positron emission tomography (PET), are available. This study proposes a PG-PET system that combines the advantages of these two methods and presents detector geometry

Recent developments in magnetic resonance (MR) to synthetic computed tomography (sCT) conversion have shown that treatment planning is possible without an initial planning CT. Promising conversion results have been demonstrated recently using conditional generative adversarial networks (cGANs). However, the performance is generally only tested on images from one MR scanner, which neglects the potential

Fibroglandular tissue (FGT) segmentation is a crucial step for quantitative analysis of background parenchymal enhancement (BPE) in magnetic resonance imaging (MRI), which is useful for breast cancer risk assessment. In this study, we develop an automated deep learning method based on a generative adversarial network (GAN) to identify the FGT region in MRI volumes and evaluate its impact on a specific

Edge-illumination x-ray phase-contrast tomography (EIXPCT) is a promising imaging technology where partially opaque masks are utilized with laboratory-based x-ray sources to estimate the distribution of the complex-valued refractive index. EIXPCT resolution is mainly determined by the period of a sample mask, but can be significantly improved by a dithering technique. Here, dithering means that multiple

Delivery times of intensity-modulated proton therapy (IMPT) can be shortened by reducing the number of spots in the treatment plan, but this may affect clinical plan delivery. Here, we assess the experimental deliverability, accuracy and time reduction of spot-reduced treatment planning for a clinical case, as well as its robustness. For a single head-and-neck cancer patient, a spot-reduced plan was

Deep convolutional neural network (DCNN), now popularly called artificial intelligence (AI), has shown the potential to improve over previous computer-assisted tools in medical imaging developed in the past decades. A DCNN has millions of free parameters that need to be trained, but the training sample set is limited in size for most medical imaging tasks so that transfer learning is typically used

Positron emission tomography (PET) and prompt gamma (PG) detection are promising proton therapy monitoring modalities. Fast calculation of the expected distributions is desirable for comparison to measurements and to develop/train algorithms for automatic treatment error detection. A filtering formalism was used for positron-emitter predictions and adapted to allow for its use for the beamline of any

The clinical value of multiple b-value diffusion-weighted (DW) magnetic resonance imaging (MRI) has been shown in many studies. However, DW-MRI often suffers from low signal-to-noise ratio, especially at high b-values. To address this limitation, we present an image denoising method based on the concept of deep image prior (DIP). In this method, high-quality prior images obtained from the same patient

The in-phantom calibration method for radiotherapy kilovoltage x-ray beams requires ionization chamber correction factors. The overall ionization chamber correction factor accounts for changes in the chamber response due to the displacement of water by the chamber cavity and wall, the presence of the stem and the change in incident photon energy and angular distribution in the phantom to that in air

Epicardial adipose tissue (EAT) is a visceral fat deposit, that's known for its association with factors, such as obesity, diabetes mellitus, age, and hypertension. Segmentation of the EAT in a fast and reproducible way is important for the interpretation of its role as an independent risk marker intricate. However, EAT has a variable distribution, and various diseases may affect the volume of the

The physical range uncertainty limits the exploitation of the full potential of charged particle therapy. In this work, we face this issue aiming to measure the absolute Bragg peak position in the target. We investigate p, 4He, 12C and 16O beams accelerated at the Heidelberg Ion-Beam Therapy Center. The residual range of the primary 12C ions is correlated to the energy spectrum of the prompt gamma

Arterial spin labeling (ASL) is a non-contrast enhanced method for perfusion measurements. The obtained information is in general a snap-shot of the whole-brain perfusion. Image acquisition is performed after a certain delay time after the labeling of the arterial blood. Time-resolved information alongside flow territory mapping of individual arteries can become useful for the collection of important

This work proposes using artificial neural networks (ANNs) for the regression of the dosimetric quantities employed in mammography. The data were generated by Monte Carlo (MC) simulations using a modified and validated version of the PENELOPE (v. 2014) + penEasy (v. 2015) code. A breast model of a homogeneous mixture of adipose and glandular tissue was adopted. The ANNs were constructed using the Keras

Scattered radiation unavoidably generated in the patient will negatively impact both kilovoltage (KV) and megavoltage (MV) imaging applications. Recently, 'hybrid' methods (i.e. combining analytical and Monte Carlo (MC) techniques) are being investigated as a solution to accurately yet quickly calculate the scattered contribution for both KV and MV images. We have developed a customized MC simulation

Previous work has shown that PRESAGE® can be used successfully to perform 3D dosimetric measurements of complex radiotherapy treatments. However, measurements near the sample edges are known to be difficult to achieve. This is an issue when the doses at air-material interfaces are of interest, for example when investigating the electron return effect (ERE) present in treatments delivered by magnetic

Prompt gamma (PG) imaging is widely investigated for spot-by-spot in vivo range verification for proton therapy. Previous studies pointed out that the accuracy of prompt gamma imaging is affected by the statistics (number of protons delivered per pencil beam) of the proton beams and the conformity between prompt gamma and dose distribution (PG-dose correlation). Recently a novel approach to re-optimize

This study demonstrates remote imaging for in vivo detection of radiation-induced tumor microstructural changes by tracking the diffusive spread of injected intratumor UV excited tattoo ink using Cherenkov-excited luminescence imaging (CELI). Micro-liter quantities of luminescent tattoo ink with UV absorption and visible emission were injected at a depth of 2 mm into mouse tumors prior to receiving

Measurement of the blood T 1 time using conventional myocardial T 1 mapping methods has gained clinical significance in the context of extracellular volume (ECV) mapping and synthetic hematocrit (Hct). However, its accuracy is potentially compromised by in-flow of non-inverted/non-saturated spins and in-flow of spins which are not partially saturated from previous imaging pulses. Bloch simulations

Radio-resistance induced under low oxygen pressure plays an important role in malignant progression in fractionated radiotherapy. For the general approach to predict cell killing under hypoxia, cell-killing models (e.g. the Linear-Quadratic model) have to be fitted to in vitro experimental survival data for both normoxia and hypoxia to obtain the oxygen enhancement ratio (OER). In such a case, model

In-room imaging is a prerequisite for adaptive proton therapy. The use of onboard cone-beam computed tomography (CBCT) imaging, which is routinely acquired for patient position verification, can enable daily dose reconstructions and plan adaptation decisions. Image quality deficiencies though, hamper dose calculation accuracy and make corrections of CBCTs a necessity. This study compared three methods

The geometry and stiffness of a vessel are pertinent to blood dynamics and vessel wall mechanical behavior and may alter in diseased conditions. Ultrasound-based ultrafast Doppler (uDoppler) imaging and shear wave imaging (SWI) techniques have been extensively exploited for the assessment of vascular hemodynamics and mechanics. Their performance is conventionally validated on vessel-mimicking phantoms

Accurate beam range prediction during clinical treatment planning is key to improve targeted dose delivery in proton and heavy ion therapy. A substantial source of beam range uncertainty is the prediction of ion stopping power ratio (SPR) relative to water from an empirical calibration based on conventional x-ray computed tomography (CT) used in clinical practice today. The aim of this study was to

Accelerated MRI involves undersampling k-space, creating unwanted artifacts when reconstructing the data. While the strategy of incoherent k-space acquisition is proven for techniques such as compressed sensing, it may not be optimal for all techniques. This study compares the use of coherent low-resolution (coherent-LR) and incoherent undersampling phase-encoding for real-time 3D CNN image reconstruction

The purpose of the present development is to employ 3D printing to prototype an ion chamber array with a scalable design potentially allowing increased spatial resolution and a larger active area. An additional goal is to design and fabricate a custom size thin-panel detector array with low-Z components. As a proof of principle demonstration, a medium size detector array with 30 × 30 air-vented ion

To improve respiratory-gated radiotherapy accuracy, we developed a machine learning approach for markerless tumor tracking and evaluated it using lung cancer patient data. Digitally reconstructed radiography (DRR) datasets were generated using planning 4DCT data. Tumor positions were selected on respective DRR images to place the GTV center of gravity in the center of each DRR. DRR subimages around

Monte Carlo (MC) track structure simulation tools are commonly used for predicting radiation induced DNA damage by modeling the physical and chemical reactions at the nanometer scale. However, the outcome of these MC simulations is particularly sensitive to the adopted parameters which vary significantly across studies. In this study, a previously developed full model of nuclear DNA was used to describe

Novel iterative image reconstruction methods can help reduce the required radiation dose in x-ray diagnostics such as computed tomography (CT), while maintaining sufficient image quality. Since some of the established image quality measures are not appropriate for reliably judging the quality of images derived by iterative methods, alternative approaches such as task-specific quality assessment would

Despite well-established dosimetry in clinical radiotherapy, dose measurements in pre-clinical and radiobiology studies are frequently inadequate, thus undermining the reliability and reproducibility of published findings. The lack of suitable dosimetry protocols, coupled with the increasing complexity of pre-clinical irradiation platforms, undermines confidence in preclinical studies and represents

The annotation of three-dimensional (3D) cephalometric landmarks in 3D computerized tomography (CT) has become an essential part of cephalometric analysis, which is used for diagnosis, surgical planning, and treatment evaluation. The automation of 3D landmarking with high-precision remains challenging due to the limited availability of training data and the high computational burden. This paper addresses

Computed tomography has greatly improved over the last decade, especially through x-ray dose exposure reduction while maintaining image quality. Herein, a new concept is proposed to improve the contrast-to-noise ratio (CNR) by including the time-of-flight (TOF) information of individual photons to obtain further insight on the photon's trajectory and to reject scatter contribution. The proof of the

In ultrasound elastography, plane-wave acquisitions and angular displacement compounding (ADC) are often used and combined to allow high frame rates and to improve accuracy of lateral displacement estimates, respectively. This study investigates the performance of displacement and strain estimation for ADC as a function of; the main-to-grating-lobe-amplitude ratio which decreases as a function of steering

Deformable image registration (DIR) of 4D-CT images is important in multiple radiation therapy applications including motion tracking of soft tissue or fiducial markers, target definition, image fusion, dose accumulation and treatment response evaluations. It is very challenging to accurately and quickly register 4D-CT abdominal images due to its large appearance variances and bulky sizes. In this

The aim of this paper is to investigate the feasibility and limitations of activity-concentration estimation for 223Ra using SPECT. Phantom measurements are performed using spheres (volumes 5.5 mL to 26.4 mL, concentrations 1.6 kBq mL-1 to 4.5 kBq mL-1). Furthermore, SPECT projections are simulated using the SIMIND Monte Carlo program for two geometries, one similar to the physical phantom and the

While the pursuit of better time resolution in positron emission tomography (PET) is rapidly evolving, little work has been performed on time of flight (TOF) image quality at high time resolution in the presence of modelling inconsistencies. This works focuses on the effect of using the wrong attenuation map in the system model, causing perturbations in the reconstructed radioactivity image. Previous

The current study aims to determine the optimal irradiation interval of fractionated stereotactic radiosurgery (SRS) by using an improved cellular automata (CA) model. The tumor growth process was simulated by considering the amount of oxygen and the density of blood vessels, which supplied oxygen and nutrient required for cell growth. Cancer cells died by the mitotic death process due to radiation

Proton imaging is a promising technology for proton radiotherapy as it can be used for: (1) direct sampling of the tissue stopping power, (2) input information for multi-modality RSP reconstruction, (3) gold-standard calibration against concurrent techniques, (4) tracking motion and (5) pre-treatment positioning. However, no end-to-end characterization of the image quality (signal-to-noise ratio and

A novel meshless reconstruction algorithm for digital tomosynthesis (DT) is presented and assessed against experimental data. The algorithm does not require a three-dimensional grid or mesh allocation and performs a slice-by-slice reconstruction where each slice position can be chosen at runtime. The methodology is based on the filtered backprojection algorithm adapted to DT. However, in the traditional

This paper presents a prospective study evaluating the impact on image quality and quantitative dynamic contrast-enhanced (DCE)-MRI perfusion parameters when varying the number of respiratory motion states when using an eXtra-Dimensional Golden-Angle Radial Sparse Parallel (XD-GRASP) MRI sequence. DCE acquisition was performed using a 3D stack-of-stars gradient-echo golden-angle radial acquisition

Brachytherapy accelerated partial breast irradiation (APBI) is well tolerated, but reported acute toxicities including moist desquamation rates range from 7% to 39%. Moist desquamation is correlated to long-term skin toxicity and high skin dose is the main risk factor. This study uses radiochromic films for in vivo skin dosimetry of low dose rate (LDR) APBI brachytherapy and prediction of skin toxicity

Breathing variations during 4D CT imaging often manifest as geometric irregularities known as respiratory-induced image artifacts and ultimately effect radiotherapy treatment efficacy. To reduce such image artifacts we developed Respiratory Adaptive Computed Tomography (REACT) to trigger CT acquisition during periods of regular breathing. For the first time, we integrate REACT with clinical hardware

We present DeepDose, a deep learning framework for fast dose calculations in radiation therapy. Given a patient anatomy and linear-accelerator IMRT multi-leaf-collimator shape or segment, a novel set of physics-based inputs is calculated that encode the linac machine parameters into the underlying anatomy. These inputs are then used to train a deep convolutional network to derive the dose distribution

High-Z material nanoparticles are being studied as localized dose enhancers in radiotherapeutic applications. Here, the nano-scale physical dose en\-hance\-ment of proton, carbon and oxygen ion beam radiation by gold nanoparticles was studied by means of Monte Carlo track structure simulation with the TRAX code. We present 2D distributions and radial profiles of the additional dose and the dose enhancement

The ionization quenching phenomenon in scintillators must be corrected to obtain accurate dosimetry in particle therapy. The purpose of this study was to develop a methodology for correcting camera projection measurements of a 3D scintillator detector exposed to proton pencil beams. Birks' ionization quenching model and the energy deposition by secondary electrons (EDSE) model were used to correct

Intravital imaging of brain vasculature through the intact cranium in vivo is based on the evolution of the fluorescence intensity and provides an ability to characterize various physiological processes in the natural context of cellular resolution. The involuntary motions of the examined subjects often limit in vivo non-invasive functional optical imaging. Conventional imaging diagnostic modalities

Electromagnetic (EM) radiofrequency (RF) safety testing of elongated active implantable medical devices (AIMD) during magnetic resonance imaging (MRI) requires an RF response model of the implant to assess a wide range of exposure conditions. The model must be validated using a sufficiently large set of incident tangential electric field (Etan) conditions that provide diversified exposure. Until now

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Microbeam radiation therapy (MRT) utilizes highly collimated synchrotron generated x-rays to create narrow planes of high dose radiation for the treatment of tumors. Individual microbeams have a typical width of 30–50 µm and are separated by a distance of 200–500 µm. The dose delivered at the center of the beam is lethal to cells in the microbeam path, on the order of hundreds of Grays (Gy). The tissue

In this study, a functioning and ventilated anthropomorphic phantom was further enhanced for the purpose of CT and MR imaging of the lung and liver. A deformable lung, including respiratory tract was 3D printed. Within the lung's inner structures is a solid region shaped from a patient's lung tumour and six nitro-glycerine capsules as reference landmarks. The full internal mesh was coated, and the

PURPOSE To calculate 3D distributions of microdosimetric-based restricted dose-averaged LET (LETd) and dose-mean lineal energy (y_D) in order to explore their similarities and differences between each other and with the traditional unrestricted LETd. Additionally, a new expression for optimum restricted LETd calculation is derived, allowing for disregarding straggling-associated functions in the classical

The beam quality correction factor,kQ, which corrects for the difference in the ionization chamber response between the reference and clinical beam quality, is an integral part of radiation therapy dosimetry. The uncertainty ofkQis one of the most significant sources of uncertainty in the dose determination. To improve the accuracy of availablekQdata, four partners calculatedkQfactors for 10 ionization

Technologies enabling in vivo range verification during proton therapy are actively sought as a means to reduce the clinical safety margins currently adopted to avoid tumor underdosage. In this contribution, we applied the semi-empirical theory of radiation-induced vaporization of superheated liquids to coated nanodroplets. Nanodroplets are injectable phase-change contrast agents that can vaporize

Multi-material decomposition (MMD) technique decomposes the CT images into basis material images and has been promising in clinical practice for material composition quantification within the human body. MMD could be implemented using the image data acquired from spectral CT or its special case, dual-energy CT (DECT) while the spectral CT data acquisition usually requires a hardware modification. In

The in vivo sensitivity limits and quantification performance of Cerenkov luminescence imaging have been studied using a tissue-like mouse phantom and 90Y. For a small, 9 mm deep target in the phantom, with no background activity present, the Cerenkov luminescence 90Y detection limit determined from contrast-to-noise ratios is 10 nCi for a 2 min exposure with a sensitive CCD camera and no filters.

For external irradiation, the variability in organ dose estimation found between computational phantom generations arises particularly from the differences in organ positioning. This work represents the first effort to quantify the differences in organ depth below the body surface between a stylized and voxel phantom series. Herein, the revised Oak Ridge National Laboratory stylized phantom series

We present a 3-D extension of the Autoprogressive Method (AutoP) for quantitative quasi-static ultrasonic elastography (QUSE) based on sparse sampling of force-displacement measurements. Compared to current model-based inverse methods, our approach requires neither geometric nor constitutive model assumptions. We build upon our previous report for 2-D QUSE [1] and demonstrate the feasibility of recovering