Physica Medica : PM

PURPOSE: We investigated interplay effects and treatment time (TT) in scanned proton therapy for lung cancer patients. We compared free-breathing (FB) approaches with multiple rescanning strategies and respiratory-gating (RG) methods with various gating widths to identify the superior irradiation technique. METHODS: Plans were created with 4/1, 2/2, and 1/4 layered/volume rescans of FB (L4V1, L2V2, and L1V4), and 50%, 30%, and 10% gating widths of the total respiratory curves (G50, G30, and G10) of the RG plans with L4V1...

PURPOSE: During any radiological procedure, it is important to know the dose to be-administered to the patient and this can be done by estimating the output of the X-ray tube either with a dosimeter or with a mathematical equation or Monte Carlo simulations. The aim of this work is to develop a new mathematical model equation (NMME) for estimating the output of high-frequency X-ray tubes. METHODS: To achieve this, data collected from ten machines in many regions of Cameroon were used (for nine machines) to build an initial model that does not take into account the anode angle and the tenth machine was used to test the model...

PURPOSE: This study aimed to evaluate the ability of MRI-based intratumoral and peritumoral radiomics features of liver tumors to differentiate between hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) and to predict ICC differentiation. METHODS: This study retrospectively collected 87 HCC patients and 75 ICC patients who were confirmed pathologically. The standard region of interest (ROI) of the lesion drawn by the radiologist manually shrank inward and expanded outward to form multiple ROI extended regions...

BACKGROUND: Classical radiation protocols are guided by physical dose delivered homogeneously over the target. Protocols are chosen to keep normal tissue complication probability (NTCP) at an acceptable level. Organs at risk (OAR) adjacent to the target volume could lead to underdosage of the tumor and a decrease of tumor control probability (TCP). The intent of our study was to explore a biology-based dose escalation: by keeping NTCP for OAR constant, radiation dose was to be maximized, allowing to result in heterogeneous dose distributions...

PURPOSE: To characterise the impact of Precise Image (PI) deep learning reconstruction algorithm on image quality, compared to filtered back-projection (FBP) and iDose4 iterative reconstruction for brain computed tomography (CT) phantom images. METHODS: Catphan-600 phantom was acquired with an Incisive CT scanner using a dedicated brain protocol, at six different dose levels (volume computed tomography dose index (CTDIvol ): 7/14/29/49/56/67 mGy). Images were reconstructed using FBP, levels 2/5 of iDose4 , and PI algorithm (Sharper/Sharp/Standard/Smooth/Smoother)...

BACKGROUND: End-to-end dosimetry audit for brachytherapy is challenging due to the steep dose gradient. However, it is an efficient method to detect unintended errors in actual clinical practice. PURPOSE: We aimed to develop an on-site end-to-end test phantom for three-dimensional image-guided brachytherapy (IGBT) for cervical cancer. METHODS: The test phantom we developed consisted of a water tank with an applicator/detector holder. The holder was designed to accommodate the applicator and insert an ionization chamber (PinPoint; PTW, Freiburg, Germany) to measure the dose at point A...

PURPOSE: This study explores the feasibility of employing Generative Adversarial Networks (GANs) to model the RefleXion X1 Linac. The aim is to investigate the accuracy of dose simulation and assess the potential computational benefits. METHODS: The X1 Linac is a new radiotherapy machine with a binary multi-leaf collimation (MLC) system, facilitating innovative biology-guided radiotherapy. A total of 34 GAN generators, each representing a desired MLC aperture, were developed...

BACKGROUND: The physical characterisation of FFF-beam profiles in the presence of a magnetic field requires a new standardization procedure and formulation. PURPOSE: The aim of this multicentric experience is to propose new normalisation factors to allow for the calculation of standard parameters typical of flattened beams, such as dosimetric field size and penumbra, for a 6 MV FFF beam from an MR-linac. METHODS: The measurements were carried out on three ViewRay-MRIdiansystems...

PURPOSE: This work set out to propose an attention-based deep neural network to predict partial volume corrected images from PET data not utilizing anatomical information. METHODS: An attention-based convolutional neural network (ATB-Net) is developed to predict PVE-corrected images in brain PET imaging by concentrating on anatomical areas of the brain. The performance of the deep neural network for performing PVC without using anatomical images was evaluated for two PVC methods, including iterative Yang (IY) and reblurred Van-Cittert (RVC) approaches...

UNLABELLED: Physiologically based pharmacokinetic (PBPK) models offer the ability to simulate and predict the biodistribution of radiopharmaceuticals and have the potential to enable individualised treatment planning in molecular radiotherapy. The objective of this study was to develop and implement a whole-body compartmental PBPK model for peptide receptor radionuclide therapy (PRRT) with [177 Lu]Lu-DOTA-TATE in SimBiology to allow for more complex analyses. The correctness of the model implementation was ensured by comparing its outputs, such as the time-integrated activity (TIA), with those of a PBPK model implemented in SAAM II software...

Precise delineation of brain glioblastoma or tumor through segmentation is pivotal in the diagnosis, formulating treatment strategies, and evaluating therapeutic progress in patients. Precisely identifying brain glioblastoma within multimodal MRI scans poses a significant challenge in the field of medical image analysis as different intensity profiles are observed across the sub-regions, reflecting diverse tumor biological properties. For segmenting glioblastoma areas, convolutional neural networks have displayed astounding performance in recent years...

PURPOSE: MRI-linear accelerator (MRI-Linac) systems allow for daily tracking of MRI changes during radiotherapy (RT). Since one common MRI-Linac operates at 0.35 T, there are efforts towards developing protocols at that field strength. In this study we demonstrate the implementation of a post-contrast 3DT1-weighted (3D-T1w) and dynamic contrast-enhancement (DCE) protocol to assess glioblastoma response to RT using a 0.35 T MRI-Linac. METHODS AND MATERIALS: The protocol implemented was used to acquire 3D-T1w and DCE data from a flow phantom and two patients with glioblastoma (a responder and a non-responder) who underwent RT on a 0...

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PURPOSE: Ventilation Perfusion SPECT is important in the diagnostics of e.g. pulmonary embolism and chronic obstructive pulmonary disease. Classical and reverse mismatched defects can be identified by utilizing the ventilation-perfusion ratio. Unfortunately, this ratio is only linear in the ventilation, the scale is not symmetrical regarding classical and reversed mismatches and small perfusion values give rise to artifacts. The ventilation-perfusion (VQ) difference is developed as an alternative...

PURPOSE: The purpose of this study was to directly calculate [Formula: see text] correction factors for four cylindrical ICs for a 0.35 T MR-linac using the Monte Carlo (MC) method. METHODS: A previously-validated TOPAS/GEANT4 MC head model of the 0.35 T MR-linac was employed. The MR-compatible Exradin A12, A1SL, A26, and A28 cylindrical ICs were modeled considering the dead volume in the air cavity. The [Formula: see text] correction factor was determined for initial electron energies of 5-7 MeV...

Quantitative values of positron emission tomography (PET) images using non-local-mean in a silicon photomultiplier (SiPM)-PET/computed tomography (CT) system with phantom and clinical images. The evaluation was conducted on a National Electrical Manufacturers Association body phantom with micro-spheres (4, 5, 6, 8, 10, 13 mm) and clinical images using the SiPM-PET/CT system. The signal-to-background ratio of the phantom was set to 4, and all PET image data was obtained and reconstructed using three-dimensional ordered subset expectation maximization, time-of-flight, point-spread function, and a 4-mm Gaussian filter (GF) and clear adaptive low-noise method (CaLM) in mild, standard, and strong intensities...

PURPOSE: Radiotherapy outcome modelling often suffers from class imbalance in the modelled endpoints. One of the main options to address this issue is by introducing new synthetically generated datapoints, using generative models, such as Denoising Diffusion Probabilistic Models (DDPM). In this study, we implemented DDPM to improve performance of a tumor local control model, trained on imbalanced dataset, and compare this approach with other common techniques. METHODS: A dataset of 535 NSCLC patients treated with SBRT (50 Gy/5 fractions) was used to train a deep learning outcome model for tumor local control prediction...

PURPOSE: The aim of the present study, conducted by a working group of the Italian Association of Medical Physics (AIFM), was to define typical z-resolution values for different digital breast tomosynthesis (DBT) models to be used as a reference for quality control (QC). Currently, there are no typical values published in internationally agreed QC protocols. METHODS: To characterize the z-resolution of the DBT models, the full width at half maximum (FWHM) of the artifact spread function (ASF), a technical parameter that quantifies the signal intensity of a detail along reconstructed planes, was analyzed...

PURPOSE: To propose an artificial intelligence (AI)-based method for personalized and real-time dosimetry for chest CBCT acquisitions. METHODS: CT images from 113 patients who underwent radiotherapy treatment were collected for simulating thorax examinations using cone-beam computed tomography (CBCT) with the Monte Carlo technique. These simulations yielded organ dose data, used to train and validate specific AI algorithms. The efficacy of these AI algorithms was evaluated by comparing dose predictions with the actual doses derived from Monte Carlo simulations, which are the ground truth, utilizing Bland-Altman plots for this comparative analysis...

PURPOSE: Manual recontouring of targets and Organs At Risk (OARs) is a time-consuming and operator-dependent task. We explored the potential of Generative Adversarial Networks (GAN) to auto-segment the rectum, bladder and femoral heads on 0.35T MRIs to accelerate the online MRI-guided-Radiotherapy (MRIgRT) workflow. METHODS: 3D planning MRIs from 60 prostate cancer patients treated with 0.35T MR-Linac were collected. A 3D GAN architecture and its equivalent 2D version were trained, validated and tested on 40, 10 and 10 patients respectively...