We propose a polynomial approach to approximate equilibrium dose ##IMG## [http://ej.iop.org/images/0031-9155/65/20/20NT01/pmbabb02dieqn1.gif] {${A_{eq}}$} reported in AAPM TG111 method of wide beam CT dosimetry. A formula for ##IMG## [http://ej.iop.org/images/0031-9155/65/20/20NT01/pmbabb02dieqn2.gif] {${A_{eq}}$} was derived by expanding the exponential growth function in a Taylor series and comparing

The aim of dose calculation algorithm research is to improve the calculation accuracy while maximizing the calculation efficiency. In this study, the three-dimensional distribution of total energy release per unit mass (TERMA) and the electron density (ED) distribution are considered inputs in a method for calculating the three-dimensional dose distribution based on a convolutional neural network (CNN)

Studies investigating the effects of computed tomography (CT) image acquisition and reconstruction parameters have mostly been limited to non-human phantoms to limit exposure to patients. This study investigates these variations using a cadaveric liver and determines harmonization methods to mitigate these variations. A reference CT scan of a cadaveric liver was acquired along with 16 modified scans

Thermal ablation by ultrasound is being explored as a local therapy for cancers of soft tissue, such as the liver or breast. One challenge for these treatments are off-target effects, including heating outside of the intended region or skin burns. Improvements in heating efficiency can mitigate these undesired outcomes, and here, we describe methods for using phase-shift nanodroplets (PSNDs) with multi-focus

Multi-needle localization in ultrasound (US) images is a crucial step of treatment planning for US-guided prostate brachytherapy. However, current computer-aided technologies are mostly focused on single-needle digitization, while manual digitization is labor intensive and time consuming. In this paper, we proposed a deep learning-based workflow for fast automatic multi-needle digitization, including

To develop and evaluate a deep learning method to segment parotid glands from MRI using unannotated MRI and unpaired expert-segmented CT datasets. We introduced a new self-derived organ attention deep learning network for combined CT to MRI image-to-image translation (I2I) and MRI segmentation, all trained as an end-to-end network. The expert segmentations available on CT scans were combined with the

The beam quality correction factor k Q for megavoltage photon beams has been calculated for eight PTW (Freiburg, Germany) ionization chambers (Farmer chambers PTW30010, PTW30011, PTW30012, and PTW30013, Semiflex 3D chambers PTW31021, PTW31010, and PTW31013, and the PinPoint 3D chamber PTW31016). Simulations performed on the widely used NE-2571 ionization chamber have been used to benchmark the results

We investigated the sensitivity of regional tumor response prediction to variability in voxel clustering techniques, imaging features, and machine learning algorithms in 25 patients with locally advanced non-small cell lung cancer (LA-NSCLC) enrolled on the FLARE-RT clinical trial. Metabolic tumor volumes (MTV) from pre-chemoradiation (PETpre) and mid-chemoradiation fluorodeoxyglucose-positron emission

Energy-resolved attenuation data in spectral x-ray imaging enables material decomposition, in which the different materials inside an object can be identified and separated virtually. Material decomposition has the drawback of increased noise in the resulting material images relative to the measured images. Recently, spectral x-ray imaging was combined with propagation-based x-ray phase-contrast imaging

The response of Gafchromic TM EBT-XD films to proton irradiation using a Mevion S250 TM proton therapy system is studied in this work. Film samples from different batches were irradiated with doses from 0.25 Gy to 20 Gy using a Mevion S250 spread-out Bragg peak (SOBP) clinical proton beam. Using a fiber-coupled optical spectrometer, transmission spectra of the films were acquired over 400–800 nm range

In recent years, breast imaging using radiolabelled molecules has attracted significant interest. Our group has proposed a multi-pinhole molecular breast tomosynthesis (MP-MBT) scanner to obtain 3D functional molecular breast images at high resolutions. After conducting extensive optimisation studies using simulations, we here present a first prototype of MP-MBT and evaluate its performance using physical

Magnetic particle imaging (MPI) is a new medical imaging technique visualizing the concentration distribution of superparamagnetic nanoparticles used as tracer material. MPI is not yet in clinical routine, since one of the challenges is the upscaling of scanners. Typically, the magnetic fields of MPI scanners are generated electromagnetically, resulting in an immense power consumption but providing

We developed a generative adversarial network (GAN)-based deep learning approach to estimate the multileaf collimator (MLC) aperture and corresponding monitor units (MUs) from a given 3D dose distribution. The proposed design of the adversarial network, which integrates a residual block into pix2pix framework, jointly trains a ‘U-Net’-like architecture as the generator and a convolutional ‘PatchGAN’

In daily adaptive proton therapy (DAPT), the treatment plan is re-optimized on a daily basis. It is a straightforward idea to incorporate information from the previous deliveries during the optimization to refine this daily proton delivery. A feedback signal was used to correct for delivery errors and errors from an inaccurate dose calculation used for plan optimization. This feedback signal consisted

The aim of this multicentric study is an inter-center benchmarking, to assess how different set tools applied to the same radiomics workflow affected the radiomics features (RFs) values. This topic is of key importance to start collaboration between different centers and to bring radiomic studies from benchmark to bedside. A per-lesion analysis was performed on 56 metastases (mts) selected from 14

As automation in radiation oncology becomes more common, it is important to determine which algorithms are equivalent for a given workflow. Often, algorithm comparisons are performed in isolation; however, clinical context can provide valuable insight into the importance of algorithm features and error magnification in subsequent workflow steps. We propose a strategy for deriving workflow-specific

Magnetic resonance imaging (MRI) offers outstanding soft tissue contrast that may reduce uncertainties in target and organ-at-risk delineation and enable online adaptive image-guided treatment. Spatial distortions resulting from non-linearities in the gradient fields and non-uniformity in the main magnetic field must be accounted for across the imaging field-of-view to prevent systematic errors during

We propose a multi-view data analysis approach using radiomics and dosiomics (R&D) texture features for predicting acute-phase weight loss (WL) in lung cancer radiotherapy. Baseline weight of 388 patients who underwent intensity modulated radiation therapy (IMRT) was measured between one month prior to and one week after the start of IMRT. Weight change between one week and two months after the commencement

The layer-stacking method can provide three-dimensional conformal dose distributions to the target based on a passive scattering method using mini-spread-out Bragg peak (SOBP). The purpose of this work is to demonstrate the effectiveness of a new weight optimization algorithm that can enhance the robustness of dose distributions against layer depth variation in layer-stacking proton beam therapy. In

The efficacy of dose-enhancing gold nanoparticles (AuNPs) is negatively impacted by low tumor uptake, low cell membrane penetration, limited diffusion distance, and short lifetime of radiation-induced secondary particles. To overcome these limitations, we have developed a novel AuNP system capable of radiation-triggered release of nitrite, a precursor of reactive nitrogen species, and report here on

Proton computed tomography (pCT) has high accuracy and dose efficiency in producing spatial maps of the relative stopping power (RSP) required for treatment planning in proton therapy. With fluence-modulated pCT (FMpCT), prescribed noise distributions can be achieved, which allows to decrease imaging dose by employing object-specific dynamically modulated fluence during the acquisition. For FMpCT acquisitions

The susceptibility of MRI to metallic objects leads to void MR signal and missing information around metallic implants. In addition, body truncation occurs in MR imaging for large patients who exceed the transaxial field-of-view of the scanner. Body truncation and metal artefacts translate to incomplete MRI-derived attenuation correction (AC) maps, consequently resulting in large quantification errors

Gadolinium aluminum gallium garnet (GAGG) is a promising scintillator crystal for positron emission tomography (PET) detectors owing to its advantages of energy resolution, light yield, and absence of intrinsic radiation. However, a large portion of the incident photons undergoes Compton scattering within GAGG crystal because of its low stopping power compared to that of lutetium-based crystals such

Over the last 30 years, there have been dramatic changes in phased array coil technology leading to increasing channel density and parallel imaging functionality. Current receiver array coils are rigid and often mismatched to patient’s size. Recently there has been a move towards flexible coil technology, which is more conformal to the human anatomy. Despite the advances of so-called flexible surface

Imaging technologies that allow non-radiative visualization and quantification of apoptosis have a great potential for assessing therapy response, early diagnosis, and disease monitoring. Magnetic particle imaging (MPI), the direct imaging of magnetic nanoparticles as positive contrast agent and sole signal source, enables high image contrast (no tissue background signal), potential high sensitivity

The 1990 code of practice (COP), produced by the IPSM (now the Institute of Physics and Engineering in Medicine, IPEM) and the UK National Physical Laboratory (NPL), gave instructions for determining absorbed dose to water for megavoltage photon (MV) radiotherapy beams (Lillicrap et al 1990). The simplicity and clarity of the 1990 COP led to widespread uptake and high levels of consistency in external

Three-dimensional cone-beam imaging has become valuable in interventional radiology. Currently, this tool, referred to as C-arm CT, employs a circular short-scan for data acquisition, which limits the axial volume coverage and yields unavoidable cone-beam artifacts. To improve flexibility in axial coverage and image quality, there is a critical need for novel data acquisition geometries and related

The pencil beam algorithm (PBA) has become the predominant dose calculation method in proton therapy, due to its high level of efficiency. However, density heterogeneity decreases the accuracy of PBA. To improve PBA’s accuracy, a beam splitting method is used to divide the original scanning beam into multiple thinner beamlets. Beam splitting should ensure that the beamlets’ summed fluence is as close

The segmentation of neoplasms is an important part of radiotherapy treatment planning, monitoring disease progression, and predicting patient outcome. In the brain, functional magnetic resonance imaging (MRI) like dynamic susceptibility contrast enhanced (DSCE) or T1-weighted dynamic contrast enhanced (DCE) perfusion MRI are important tools for diagnosis. They play a crucial role in providing pre-operative

Grating-based x-ray phase-contrast imaging provides three simultaneous image channels originating from a single image acquisition. While the phase signal provides direct access to the electron density in tomography, there is additional information on sub-resolutional structural information which is called dark-field signal in analogy to optical microscopy. The additional availability of the conventional

This paper expands the linear iterative near-field phase retrieval (LIPR) formalism to achieve quantitative material thickness decomposition. Propagation-based phase contrast x-ray imaging with subsequent phase retrieval has been shown to improve the signal-to-noise ratio (SNR) by factors of up to hundreds compared to conventional x-ray imaging. This is a key step in biomedical imaging, where radiation

High spatial resolution PET relies on having excellent depth-of-interaction (DOI) resolution and small detector elements. Depth-encoding in PET modules has traditionally been performed using dual-ended readout. In recent years, researchers have explored the feasibility of replacing the second readout array with a light guide at the entrance layer that introduces intercrystal light sharing in order

Treating multiple brain metastases with a single isocenter improves efficiency but requires margins to account for rotation induced shifts that increase with target-to-isocenter distance. A method to select the single isocenter position that minimizes the total volume of normal tissue treated during multi-target stereotactic radiosurgery (SRS) is presented. A statistical framework was developed to

This study aims to develop a silent, fast and 3D method for T1 and proton density (PD) mapping, while generating time series of T1-weighted (T1w) images with bias-field correction. Undersampled T1w images at different effective inversion times (TIs) were acquired using the inversion recovery prepared RUFIS sequence with an interleaved k-space trajectory. Unaliased images were reconstructed by constraining

The magnetic particle imaging (MPI) performance of collections of chains of magnetic nanoparticles with Néel and Brownian relaxation mechanisms was studied by carrying out simulations based on the Landau–Lifshitz–Gilbert equation and rotational Brownian dynamics, respectively. The effect of magnetic dipole–dipole interactions within chains on the time-domain average magnetic dipole moment and corresponding

Numerical simulations are increasingly employed in safety assessment of high-field magnetic resonance imaging (MRI) in patients with conductive medical implants such as those with deep brain stimulation (DBS) devices. Performing numerical simulations with realistic patient models and implant geometry is the preferred method as it provides the most accurate results; however, in many cases such an approach

Purpose . To improve the prediction accuracy of respiratory signals by adapting the multi-layer perceptron neural network (MLP-NN) model to changing respiratory signals. We have previously developed an MLP-NN to predict respiratory signals obtained from a real-time position management (RPM) device. Preliminary testing results indicated that poor prediction accuracy may be observed after several seconds

We developed a machine learning framework in order to establish the correlation between dose and activity distributions in proton therapy. A recurrent neural network was used to predict dose distribution in three dimensions based on the information of proton-induced positron emitters. Hounsfield Unit (HU) information from CT images and analytically derived stopping power (SP) information were incorporated

In vivo dosimetry methods can verify the prescription dose is delivered to the patient during treatment. Unfortunately, in exit dosimetry, the megavoltage image is contaminated with patient-generated scattered photons. However, estimation and removal of the effect of this fluence improves accuracy of in vivo dosimetry methods. This work develops a ‘tri-hybrid’ algorithm combining analytical, Monte

Previous studies have demonstrated the feasibility of reducing noise with deep learning-based methods for low-dose fluorodeoxyglucose (FDG) positron emission tomography (PET). This work aimed to investigate the feasibility of noise reduction for tracers without sufficient training datasets using a deep transfer learning approach, which can utilize existing networks trained by the widely available FDG

Temperature measurement during superficial hyperthermia is limited by poor spatial resolution. We investigated two sheets to improve temperature monitoring of the skin surface. Two different sheets were studied with a grid of temperature sensors with one sensor per ∼5 cm 2 . The first was a matrix of multisensor thermocouple probes laced through a silicone sheet. The second sheet had rows of thermistors

Four-dimensional (4D) cone-beam CT (CBCT) reconstructs temporally-resolved phases of 3D volumes often with the same amount of projection data that are meant for reconstructing a single 3D volume. 4D CBCT is a sparse-data problem that is very challenging for high-quality 4D CBCT image reconstruction. Here we develop a new method, namely 4D-AirNet, that synergizes analytical and iterative method with

Motivation and objective. For each institute, the selection and calibration of the most suitable approach to assign material properties for Monte Carlo (MC) patient simulation in proton therapy is a major challenge. Current conventional approaches based on computed tomography (CT) depend on CT acquisition and reconstruction settings. This study proposes a material assignment approach, referred to as

In this paper, a nonuniform projection distribution (NUPD) CT method is proposed for the region-of-interest-specific examination in the solitary lung nodule follow-up application in order to reduce redundant x-ray projections exposed on normal tissues. The method exploits personal previous lung CT scan information to design a nonuniform x-ray projection modulation scheme where x-rays are sparsely modulated

Positron emission tomography (PET) has been used for in vivo treatment verification, mainly for range verification, in proton therapy. Evaluating the direct dose from PET measurements remains challenging; however, it is highly desirable from a clinical perspective. In this study, a method for estimating the dose distribution from the positron emitter distributions was developed using the maximum likelihood

Quality control tests of molecular imaging systems are hampered by the complexity of phantom preparation. It is proposed that radioisotopes can be directly incorporated into photo-polymer resins. Use of the radio-polymer in a 3D printer allows phantoms with more complex and reliable activity distributions to be produced whilst simplifying source preparation. Initial tests have been performed to determine

The accuracy of delivered radiation dose and the reproducibility of employed radiotherapy methods are key factors for preclinical radiobiology applications and research studies. In this work, ionization chamber (IC) measurements and Monte Carlo (MC) simulations were used to accurately determine the dose rate for total body irradiation (TBI), a classic radiobiologic and immunologic experimental method

Small-field dosimetry is central to the planning and delivery of radiotherapy to patients with cancer. Small-field dosimetry is beset by complex issues, such as loss of charged-particle equilibrium (CPE), source occlusion and electron-scattering effects in low-density tissues. The purpose of the present research is the elucidation of the fundamental physics of small fields through the computation of

The purpose of this work was to develop a deep learning (DL) based algorithm, Automatic intensity-modulated radiotherapy (IMRT) Planning via Static Field Fluence Prediction (AIP-SFFP), for automated prostate IMRT planning with real-time planning efficiency. The following method was adopted: AIP-SFFP generates a prostate IMRT plan through predictions of fluence maps using patient anatomy. No inverse

A maximum likelihood approach to the problem of calculating the proton paths inside the scanned object in proton computed tomography is presented. Molière theory is used for the first time to derive a physical model that describes proton multiple Coulomb scattering, avoiding the need for the Gaussian approximation currently used. To enable this, the proposed method approximates proton paths with cubic

A newly-designed large-area plane-parallel ionization chamber (of type PTW 34089), denoted BPC150, with a nominal active volume diameter of 147 mm is characterized in this study. Such chambers exhibit benefits compared to smaller chambers in the field of scanned light-ion beam dosimetry because they capture a larger fraction of the laterally-spread beam fragments and ease positioning with respect to

The medical imaging of patients with a cochlear implant inside a Magnetic Resonance Imaging (MRI) scanner carries the risk of power deposition in the tissues at the tip of the implant lead, which may result in their heating. In order to assess this risk, ISO/TS 10 974 (2018) describes a methodology (Tier 3 approach) whereby a radiofrequency electrical model for the implant lead in the form of a transfer

Microdosimetry has been traditionally performed through gaseous proportional counters, although in recent years different solid-state microdosimeters have been proposed and constructed for this task. In this paper, we analyze the response of solid-state devices of micrometric size with no intrinsic gain developed by CNM-CSIC (Spain). There are two major aspects of the operation of these devices that

High-frame-rate volume imaging (HFR-VI) aims to provide high-quality images with high-temporal information. Despite its potential, HFR-VI translation into clinical applications has been challenging due to the high cost of the equipment required to drive matrix probes with a large number of elements. The goal of this study is to introduce and test sparse-random-aperture compounding (SRAC), a technique

Semiconductor dosimeters are ubiquitous in modern external-beam radiation therapy. They possess key features. The response, electronically available in real time, is stable and linear with absorbed dose for given irradiation conditions; the radiation-sensitive volume can be rather small in size, while retaining mechanical strength and high sensitivity. We describe three common semiconductor dosimeters:

Identification of surgical instruments is crucial in understanding surgical scenarios and providing an assistive process in endoscopic image-guided surgery. This study proposes a novel multilevel feature-aggregated deep convolutional neural network (MLFA-Net) for identifying surgical instruments in endoscopic images. First, a global feature augmentation layer is created on the top layer of the backbone

Multi-energy CT imaging of large patients with conventional dual-energy (DE)-CT using an energy-integrating-detector (EID) is challenging due to photon starvation-induced image artifacts, especially in lower tube potential (80–100 kV) images. Here, we performed phantom experiments to investigate the performance of DECT for morbidly obese patients, using an iodine and water material decomposition task

Conventional thoracic 4DCBCT scans take 1320 projections over 4 min. This paper investigates which reconstruction algorithms best leverage Respiratory-Motion-Guided (RMG) acquisition in order to reduce scan time and dose while maintaining image quality. We investigated a 200 projection, on average 1 min RMG acquisition. RMG acquisition ensures even angular separation between projections at each respiratory

Over the last decade, the performance of benchtop x-ray fluorescence computed tomography (XFCT) systems has been significantly enhanced through hardware and software optimizations. Recent studies have indicated the need of energy-resolving pixelated/array detectors in the x-ray detection component to further improve the sensitivity and image resolution of benchtop XFCT systems while meeting the realistic

Radiotherapy treatment planning requires accurate modeling of the delivered patient dose, including radiation scatter effects, multi-leaf collimator (MLC) leaf transmission, interleaf-leakage, etc. In fluence map optimization (FMO), a simple dose model is used to first generate an intermediate plan based on pencil-beams. In a second step (segmentation phase), this intermediate plan is then converted