Imaging Setup Research Articles

Super resolution label-free dark-field microscopy by deep learning.

Dark-field microscopy (DFM) is a powerful label-free and high-contrast imaging technique due to its ability to reveal features of transparent specimens with inhomogeneities. However, owing to the Abbe's diffraction limit, fine structures at sub-wavelength scale are difficult to resolve. In this work, we report a single image super resolution DFM scheme using a convolutional neural network (CNN). A U-net based CNN is trained with a dataset which is numerically simulated based on the forward physical model of the DFM. The forward physical model described by the parameters of the imaging setup connects the object ground truths and dark field images. With the trained network, we demonstrate super resolution dark field imaging of various test samples with twice resolution improvement. Our technique illustrates a promising deep learning approach to double the resolution of DFM without any hardware modification.

MosaicMVS: Mosaic-Based Omnidirectional Multi-View Stereo for Indoor Scenes

We present MosaicMVS, a novel learning-based depth estimation framework for a mosaic-based omnidirectional multi-view stereo (MVS) camera setup. It uses a regular field of view (FOV) MVS network for an omnidirectional imaging setup with explicit consideration of hypothetical voxel-wise FOV overlaps. The resulting depth predictions are accurate and agree on the omnidirectional multi-view geometry. Unlike existing MVS setups, MosaicMVS camera setup can be easily applied to omnidirectional indoor scenes without having to account for con-straints such as intricate epipolar constraints and the distortion of omnidirectional cameras. We validate the effectiveness of our framework on a new challenging indoor dataset in terms of depth estimation, reconstruction, and view synthesis. We also present new evaluation metric to check reconstruction performance using post-processed masks for accurate evaluation without any ground truth depth map or laser-scanned reconstructions. Experimental results show that our framework outperforms the state-of-the-art MVS methods in a large margin in all test scenes.

Lensless multi-core-fiber-based imaging from speckle autocorrelation under highly coherent illumination

Flexible fiber-optic lensless endoscopic imaging plays a significant role in medical and biological applications. Lensless imaging based on far-field speckle of multi-core fibers under spatially incoherent light source illumination relied on the angular optical memory effect, resulting in limited field of view and susceptibility to interference effects. Image reconstruction from fiber speckle intensity under the highly coherent light illumination has been investigated using classical coherent diffraction theory, but it imposes limitations on imaging distance and detection positions. However, existing alternative solutions involve reducing coherence level to satisfy the angular optical memory effect, which increases system complexity and sacrifices the advantages of single-frame imaging. The reconstruction of intensity-based images remains a significant challenge under highly coherent illumination, primarily due to the interference effect. In this study, an imaging algorithm that reconstructs the original image solely from the intensity of far-field fiber speckle under coherent illumination conditions is proposed. The proposed method is based on statistical optics theory and aims to extract the relevant information within coherent speckle patterns to reconstruct the image. Our approach expands the imaging field of view, simplifies the imaging setup, and broadens the range of viable light sources for speckle correlation imaging. The effectiveness of the algorithm is verified by simulated experiments and a real imaging system.

Assessing spontaneous sensory neuron activity using in vivo calcium imaging.

Heightened spontaneous activity in sensory neurons is often reported in individuals living with chronic pain. It is possible to study this activity in rodents using electrophysiology, but these experiments require great skill and can be prone to bias. Here, we have examined whether in vivo calcium imaging with GCaMP6s can be used as an alternative approach. We show that spontaneously active calcium transients can be visualised in the fourth lumbar dorsal root ganglion (L4 DRG) through in vivo imaging in a mouse model of inflammatory pain. Application of lidocaine to the nerve, between the inflamed site and the DRG, silenced spontaneous firing and revealed the true baseline level of calcium for spontaneously active neurons. We used these data to train a machine learning algorithm to predict when a neuron is spontaneously active. We show that our algorithm is accurate in 2 different models of pain: intraplantar complete Freund adjuvant and antigen-induced arthritis, with accuracies of 90.0% ±1.2 and 85.9% ±2.1, respectively, assessed against visual inspection by an experienced observer. The algorithm can also detect neuronal activity in imaging experiments generated in a different laboratory using a different microscope configuration (accuracy = 94.0% ±2.2). We conclude that in vivo calcium imaging can be used to assess spontaneous activity in sensory neurons and provide a Google Colaboratory Notebook to allow anyone easy access to our novel analysis tool, for the assessment of spontaneous neuronal activity in their own imaging setups.

Near-field coded-mask technique and its potential for proton therapy monitoring

Objective. Prompt-gamma imaging encompasses several approaches to the online monitoring of the beam range or deposited dose distribution in proton therapy. We test one of the imaging techniques - a coded mask approach - both experimentally and via simulations. Approach. Two imaging setups have been investigated experimentally. Each of them comprised a structured tungsten collimator in the form of a modified uniformly redundant array mask and a LYSO:Ce scintillation detector of fine granularity. The setups differed in detector dimensions and operation mode (1D or 2D imaging). A series of measurements with radioactive sources have been conducted, testing the performance of the setups for near-field gamma imaging. Additionally, Monte Carlo simulations of a larger setup of the same type were conducted, investigating its performance with a realistic gamma source distribution occurring during proton therapy. Main results. The images of point-like sources reconstructed from two small-scale prototypes’ data using the maximum-likelihood expectation maximisation algorithm constitute the experimental proof of principle for the near-field coded-mask imaging modality, both in the 1D and the 2D mode. Their precision allowed us to calibrate out certain systematic offsets appearing due to the limited alignment accuracy of setup elements. The simulation of the full-scale setup yielded a mean distal falloff retrieval precision of 0.72 mm in the studies for beam energy range 89.5–107.9 MeV and with 1 × 108 protons (a typical number for distal spots). The implemented algorithm of image reconstruction is relatively fast—a typical procedure needs several seconds. Significance. Coded-mask imaging appears a valid option for proton therapy monitoring. The results of simulations let us conclude that the proposed full-scale setup is competitive with the knife-edge-shaped and the multi-parallel slit cameras investigated by other groups.

Background-oriented schlieren sensitivity in terms of geometrical parameters of measurement setup

Background-oriented schlieren imaging is a recently proposed noninvasive optical method for imaging of full ultrasound fields. In this work, the impact of uncertainty in geometrical parameters of a background-oriented schlieren measurement setup for imaging of full ultrasound fields is studied using numerical simulations. The studied parameters are focal length of the camera and positions and orientations of the camera, water tank, and ultrasound field. The results demonstrate that the most sensitive parameters affecting the accuracy of the reconstructed ultrasound fields are the orientations of the camera that change the direction of an effective optical axis. Other sensitive parameters are the focal length of the camera and the position of the ultrasound field in perpendicular directions of an optical axis. This synthetic study demonstrates the accuracy requirements for calibrating the geometrical parameters of a measurement setup that would be required to achieve accuracy comparable to that of hydrophone measurements using the background-oriented schlieren imaging. Explicitly, limits of the variation ranges of the geometrical parameters resulting in relative error ranges of 5% and 10% are given. The results of this study may contribute to help design future background-oriented schlieren measurement setups intended for measurement of full ultrasound fields.

Observation of Continuum State Dissociation Enables the Determination of N2 Bond Dissociation Energy to Spectroscopic Accuracy.

Nitrogen (N) is one of the most fundamental elements of life. Precise determination of the bond dissociation energy (BDE) of the corresponding homonuclear diatomic molecule N2 is not only important for calculating the enthalpies of formation for any N-containing molecules but also provides the best benchmark for evaluating theoretical computational methods. Thus, it has attracted many experimental and theoretical studies, while controversies still exist. Here, we report the observation of continuum state dissociation of N2 into the channel N(2D5/2,3/2)+N(2D5/2,3/2) for the first time by using the vacuum ultraviolet (VUV)-pump-VUV-probe time-sliced velocity-mapped imaging setup. The quantum-state-resolved images enable the direct visualization of the dissociation onsets corresponding to each of the correlated spin-orbit fine-structure channels within a few tenths of wavenumber. The BDEs of 14N2 and 15N2 are directly determined to be 78691.8 ± 0.3 cm-1 and 78731.5 ± 0.3 cm-1, respectively, which should represent the most accurate BDE of N2 thus far.

Investigation of blur kernel of terahertz images

The paper discusses issues of digital processing of terahertz images. It is shown that despite the improvement of the hardware part of imaging setups, the acquired images still often have a low resolution and suffer from noise and blurring effects. Thus, to improve their visual quality, it is advisable to use special digital processing methods. While some progress has already been made in terms of denoising of terahertz images, the research of their deblurring is only at the very early stage. Therefore, this paper attempts to analyze the properties of blur functions for real terahertz images to further use them while designing a corresponding deblurring technique. For this purpose, the phase-only image method has been used. A study of blur properties for the three most common blur types (defocus, motion and Gaussian blur) has shown that for test images they can be distinguished and their main parameters can be assessed. However, the application of this method to real terahertz images has shown that the blur characteristics in them are very different from the ones obtained for modelled examples. The real blur demonstrates a quite complex behaviour and estimating its kernel requires additional research.

On evaluation of image quality in nonparaxial single-pixel imaging

High numerical apertures lead to an appearance of distortions in a single-shot image, which make obtaining images troublesome if not impossible. These obstacles can be overcome in single-pixel imaging, where different strategies lead to inspection of objects with a good resolution, contrast and brightness. Recent advances in flat photonic elements have enabled the creation of compact nonparaxial imaging systems, which are especially promising in the THz range of wavelengths, bringing advances to such fields as communication, material inspection and spectroscopy. In this work, we dive into the problematics of single-pixel imaging: we introduce an object sample, which we use to investigate the resolution, contrast and brightness of the classical two-lens imaging setup. We evaluate the nonparaxial imaging of the sample and report that the conditions for the best contrast and the best brightness are decoupled in nonparaxial single pixel imaging. To overcome this hurdle, we use two integral image quality assessment techniques from computational imaging theory and estimate the quality of the image in a virtual numerical THz imaging scenario. The localized mean square error metric did not cause additional constraints to the quality of the image, whereas the global mean square error has restricted the range of possible imaging setups. Thus, the computational integral image quality assessment techniques back up the main claim of this study that in the single-pixel imaging the resolution is decoupled from the image brightness.

Dynamics of mitochondrial membranes under photo-oxidative stress with high spatiotemporal resolution.

In our study, we harnessed an original Enhanced Speed Structured Illumination Microscopy (Fast-SIM) imaging setup to explore the dynamics of mitochondrial and inner membrane ultrastructure under specific photo-oxidation stress induced by Chlorin-e6 and light irradiation. Notably, our Fast-SIM system allowed us to observe and quantify a distinct remodeling and shortening of the mitochondrial structure after 60-80s of irradiation. These changes were accompanied by fusion events of adjacent inner membrane cristae and global swelling of the organelle. Preceding these alterations, a larger sequence was characterized by heightened dynamics within the mitochondrial network, featuring events such as mitochondrial fission, rapid formation of tubular prolongations, and fluctuations in cristae structure. Our findings provide compelling evidence that, among enhanced-resolution microscopy techniques, Fast-SIM emerges as the most suitable approach for non-invasive dynamic studies of mitochondrial structure in living cells. For the first time, this approach allows quantitative and qualitative characterization of successive steps in the photo-induced oxidation process with sufficient spatial and temporal resolution.

Is noncoplanar plan more robust to inter-fractional variations than coplanar plan in treating bilateral HN tumors with pencil-beam scanning proton beams?

Noncoplanar plans (NCPs) are commonly used for proton treatment of bilateral head and neck (HN) malignancies. NCP requires additional verification setup imaging between beams to correct residual errors of robotic couch motion, which increases imaging dose and total treatment time. This study compared the quality and robustness of NCPs with those of coplanar plans (CPs). Under an IRB-approved study, CPs were created retrospectively for 10 bilateral HN patients previously treated with NCPs maintaining identical beam geometry of the original plan but excluding couch rotations. Plan robustness to the inter-fractional variation (IV) of both plans was evaluated through the Dose Volume Histograms (DVH) of weekly quality assurance CT (QACT) sets (39 total). In addition, delivery efficiency for both plans was compared using total treatment time (TTT) and beam-on time (BOT). No significant differences in plan quality were observed in terms of clinical target volume (CTV) coverage (D95) or organ-at-risk (OAR) doses (p>0.4 for all CTVs and OARs). No significant advantage of NCPs in the robustness to IV was found over CP, either. Changes in D95 of QA plans showed a linear correlation (slope=1.006, R2 >0.99) between NCP and CP for three CTV data points (CTV1, CTV2, and CTV3) in each QA plan (117 data points for 39 QA plans). NCPs showed significantly higher beam delivery time than CPs for TTT (539±50vs. 897±142s; p<0.001); however, no significant differences were observed for BOT. NCPs are not more robust to IV than CPs when treating bilateral HN tumors with pencil-beam scanning proton beams. CPs showed plan quality and robustness similar to NCPs while reduced treatment time (∼6min). This suggests that CPs may be a more efficient planning technique for bilateral HN cancer proton therapy.

The wing interference patterns (WIPs) of Parapanteles (Braconidae, Microgastrinae): demonstrating a powerful and accessible tool for species-level identification of small and clear winged insects

Wing interference patterns (WIPs) are color patterns of insect wings caused by thin film interference. Thin film interference is the same phenomenon responsible for the refracted spectral colors sometimes visible on soap bubbles. Insect WIPs are static patterns due to the variable thickness of wing membranes and the colors produced depend on the thicknesses of wing membranes. While WIPs have been studied in several taxa of small insects, they have not been broadly adopted by insect taxonomists. We surveyed WIPs in one moderate-sized genus of parasitoid wasps, Parapanteles (Braconidae: Microgastrinae). Using an inexpensive microscope camera set-up and free imaging and analysis software, we detected consistent WIP differences between Parapanteles species. In some cases, WIPs can be used to diagnose sibling species that would otherwise require SEM images to differentiate or DNA barcodes. Wing interference patters are an underemployed character that may be similarly useful in many other taxa of small clear-winged insects.

Prompt: Probability-conserved cross section biasing Monte Carlo particle transport system

An open source software package for simulating thermal neutron propagation in geometry is presented. In this system, neutron propagation can be treated by either the particle transport method or the ray-tracing method. Supported by an accurate backend scattering physics engine, this system is capable of reproducing neutron scattering experiments in complex geometries and is expected to be used in the areas of instrument characterisation, optimisation and data analysis.In this paper, the relevant theories are briefly introduced. The simulation flow and the user input syntax to control it are provided in detail. Five benchmarking simulations, focusing on different aspects of simulation and scattering techniques, are given to demonstrate the applications of this simulation system. They include an idealised total scattering instrument, a monochromatic powder diffractometer, a neutron guide, a chopper and an imaging setup for complex geometries. Simulated results are benchmarked against experimental data or well-established software packages when appropriate. Good agreements are observed. Program summaryProgram Title:PromptCPC Library link to program files:https://doi.org/10.17632/337frmp9ky.1Developer's repository link:https://gitlab.com/cinema-developers/promptLicensing provisions:Apache-2.0Programming language:C++, C and PythonExternal routines/libraries:NCrystal, VecGeom, MCPL, PyVistaNature of problem: It is challenging for traditional neutron ray-tracing simulation methods to consider multiple scatterings in complex geometries, hence the accuracy and precision of the simulated neutron scattering experiments are limited.Solution method: A hybrid system of Monte Carlo particle transport method and ray-tracing method is proposed.

Characterization of single synthetic polymers via magnetic tweezers

AbstractDue to the ability to perform the parallel measurement of multiple single chains and exert precise control over stretching force in the sub‐nanonewton regime, magnetic tweezers (MT) are a suitable tool to study the individual chain conformations and inherent behaviors of polymers. Herein, we examined the applications of MT in studying single synthetic polymers, distinct from previous reviews focusing on biological polymers such as DNAs. We first presented an overview of the technical aspects of MT, including the imaging setup, the algorithm of three‐dimensional single particle tracking, the configuration of magnets, the calibration and control of magnetic forces, the assembly of flow cells, and the polymer tethering methods. Then, we discussed selected examples highlighting the utilization of MT in studying the chain conformation, mechanical properties, ion and ligands effect, regime transition mechanism, and polymerization dynamics of single synthetic polymers. We envision that MT can serve as a powerful toolbox for delving into the structure–property correlations at the single chain level, which provides quantitative validations for building the theoretical models of synthetic polymers. In the end, we contemplated potential avenues and opportunities for future research in this domain.

FLASH radiotherapy and the associated dosimetric challenges

At Lund University and Skåne University Hospital in Lund, Sweden, we have, as the first clinic, modified a clinical Elekta Precise linear accelerator for convertible delivery of ultra-high dose rate (FLASH) irradiation. Whereas recently published reviews highlighted the need for standardised protocols for ultra-high dose rate beam dosimetry to be able to determine the true potential of FLASH irradiation, several dosimetry studies as well as in-vitro and in-vivo experiments have been carried out at our unit. Dosimetric procedures for verification of accurate dose delivery of FLASH irradiation to cell cultures, zebrafish embryos and small animals have been established using radiochromic films and thermo-luminescent dosimeters. Also, recently the first experience of electron FLASH radiotherapy (FLASH-RT) in canine patients in our clinical setting was published. Our research facilities also include a laboratory for 3D polymer gel manufacturing. Recently, we started investigating the feasibility of a NIPAM polymer gel dosimeter for ultra-high dose rate dosimetry. Furthermore, in the bunker of the modified Elekta linear accelerator, a Surface Guided Radiotherapy (SGRT) system is accessible. The Catalyst™ system (C-Rad Positioning, Uppsala, Sweden) provides optical surface imaging for patient setup, real-time motion monitoring and breathing adapted treatment. Aiming at treating patients using ultra-high dose rates, a real-time validation of the alignment between the beam and the target is crucial as the dose is delivered in a fraction of a second. Our research group has during the last decade investigated and developed SGRT workflows which improved patient setup and breathing adapted treatment for several cancer patient groups. Recently, we also started investigating the feasibility of a real-time motion monitoring system for surface guided FLASH-RT. Both FLASH related studies; 3D polymer gel dosimetry and surface guided FLASH-RT are to our knowledge the first of their kind. Following an introduction to the field of FLASH and the associated dosimetric challenges, we here aim to present the two ongoing studies including some preliminary results.

High-quality Agar and Polyacrylamide Tumor-mimicking Phantom Models for Magnetic Resonance-guided Focused Ultrasound Applications.

Tissue-mimicking phantoms (TMPs) have been used extensively in clinical and nonclinical settings to simulate the thermal effects of focus ultrasound (FUS) technology in real tissue or organs. With recent technological developments in the FUS technology and its monitoring/guided techniques such as ultrasound-guided FUS and magnetic resonance-guided FUS (MRgFUS) the need for TMPs are more important than ever to ensure the safety of the patients before being treated with FUS for a variety of diseases (e.g., cancer or neurological). The purpose of this study was to prepare a tumor-mimicking phantom (TUMP) model that can simulate competently a tumor that is surrounded by healthy tissue. The TUMP models were prepared using polyacrylamide (PAA) and agar solutions enriched with MR contrast agents (silicon dioxide and glycerol), and the thermosensitive component bovine serum albumin (BSA) that can alter its physical properties once thermal change is detected, therefore offering real-time visualization of the applied FUS ablation in the TUMPs models. To establish if these TUMPs are good candidates to be used in thermoablation, their thermal properties were characterized with a custom-made FUS system in the laboratory and a magnetic resonance imaging (MRI) setup with MR-thermometry. The BSA protein's coagulation temperature was adjusted at 55°C by setting the pH of the PAA solution to 4.5, therefore simulating the necrosis temperature of the tissue. The experiments carried out showed that the TUMP models prepared by PAA can change color from transparent to cream-white due to the BSA protein coagulation caused by the thermal stress applied. The TUMP models offered a good MRI contrast between the TMPs and the TUMPs including real-time visualization of the ablation area due to the BSA protein coagulation. Furthermore, the T2-weighted MR images obtained showed a significant change in T2 when the BSA protein is thermally coagulated. MR thermometry maps demonstrated that the suggested TUMP models may successfully imitate a tumor that is present in soft tissue. The TUMP models developed in this study have numerous uses in the testing and calibration of FUS equipment including the simulation and validation of thermal therapy treatment plans with FUS or MRgFUS in oncology applications.

Contactless estimation of apple fruit respiration rate using machine learning models based on laser speckle imaging

This article presents the application of the laser speckle imaging method, a nondestructive and contactless method monitoring the gas exchange rate of intact apples. Red and infrared lasers in a typical setup for laser speckle imaging were used. A new parameter, speckle pattern relaxation time, has been proposed to evaluate speckle dynamics. Machine learning methods were used to develop a set of predictive models calibrated and validated against the respiration rate of two apple fruit cultivars measured with the flush system. The model with the highest performance used three variables: the speckle pattern relaxation time (τRED or τIR), fruit mass, and categorical variables describing apple varieties. This model provided satisfactorily low values of mean absolute prediction errors of 6.04%. Data from laser light scattering measurements combined with modern machine learning algorithms provided a nondestructive and fast method for estimating the apple fruit respiration rate. The developed solution has the potential for a wide range of industrial applications, especially in fruit storage, where the fruit respiration rate indicates optimal storage conditions.

Smart soil image classification system using lightweight convolutional neural network

In the agriculture sector, soil classification plays a significant task, as it helps in soil tillage, crop selection, moisture level estimation, and automation. Conventionally, soil classification is carried out with the help of physical, chemical, and biological characteristics of the geo-referenced and mapped soil. Soil classification by conventional and laboratory methods is time-consuming, high-cost, and requires proficiency. This study presents a quick and cost-effective prediction of soil type by using soil images. A soil image dataset has been created to classify the soil type using images. To create the soil image dataset, 392 soil samples are collected from different agricultural fields in Andhra Pradesh, India. The collected samples are dried and the soil type is identified using a sieve and hydrometer analysis in the laboratory. An imaging setup has been made to capture the images of the dried soil samples using a smartphone camera. The captured images are pre-processed using: RGB extraction, and V extraction from HSV bins, and adaptive histogram are applied to highlight the texture features of the soil images. A novel lightweight convolutional neural network called Light-SoilNet is proposed to classify five soil sample images: sand, clay, loam, loamy sand, and sandy loam. The proposed network is designed to take care of the imbalanced soil image dataset. The proposed network is tested and compared with state-of-the-art lightweight and pre-trained deep learning networks. The proposed Light-SoilNet network architecture has produced an overall accuracy of 97.2% in classifying the soils. The comparison of the results shows the performance of the proposed model using the image and deep learning techniques in classifying the soil types.

Investigation of Intra-fraction Stability and Inter-fraction Consistency of Active Breathing Coordinator (ABC)-Based Deep Inspiration Breath Holds in Left-Sided Breast Cancer.

Background Deep inspiration breath-hold (DIBH) has been established as a standard technique to reduce cardiac dose. The part of the heart exposed to radiation can be significantly decreased using the DIBH technique during tangential left-sided breast cancer (LSBC) irradiation. Aim The objective of this study was to investigate the intra-fraction breath-hold stability and inter-fraction consistency of patient breath-hold against the threshold as a function of air volumes in the setting of active breathing coordinator (ABC)-based DIBH (ABC-DIBH) treatment to LSBC. Methods A total of 34 patients treated with external beam radiation therapy (EBRT) to the left breast using the ABC-DIBH device were included. The frequency of breath-holds perfraction and the entire course of treatment along with the total treatment time was evaluated for all patients.A prescription dose of either 200 cGy (conventional) or 267 cGy (hypofractionation) was administered during 649 fractions, resulting in a total of 4,601 breath-hold measurements being evaluated. The amplitude of deviation in terms of air volumes between the baseline threshold and the patient-specific measurement (during each breath-hold) per fraction was used to define the DIBH stability. Likewise, the consistency of the breathing amplitudes was used to define the compliance of patient breath-holds throughout the entire treatment period. Positional accuracy was evaluated using orthogonal (portal) images. Results The average number of breath-holds measured over the entire course of treatment for each patient was 144 inspirations (58-351). Similarly, the average number of breath-holds for each fraction during the course of treatment was 11 inspirations (7-21), which included setup imaging and treatment. The total number of breath-holds reduced significantly (p-value < 0.05) with hypofractionation (104 inspirations; range 58-170) as compared to conventional fractionation (145 inspirations; 58-351). The average breath-hold threshold in terms of air volume was 1.41 L(0.6-2.1 L) for all patients. The total treatment time reduced significantly after the third fraction (p-value < 0.05).The average deviation between the measured and baseline threshold breath-holds during the course of treatment was 0.5 L/sec (0.12-1.32 L/sec). The consistency of the breathing amplitudes were maintained within±0.05 Lduring the entire treatment for all patients. The average translational shifts measured during setup were 0.28 cm ± 0.3 cm, 0.38 cm ± 0.4 cm, and 0.21 cm ± 0.3 cm in the lateral, longitudinal, and vertical directions, respectively. Conclusion The study has demonstrated the variations in intra-fraction breath-hold stability and inter-fraction breath-hold consistency in terms of air volumes for patients who were treated for LSBC. The frequency of breath-holds was observed to be higher with increased total treatment time for the first few fractions and reduced over the course of treatment.

Dose distribution estimation toward CT-less adaptive carbon ion radiotherapy for liver tumors using the divided-volume matching technique

Objective. Dose distribution estimation during the treatment course is essential for carbon ion radiotherapy because beam ranges are highly sensitive to density changes along beam paths, triggering the adaptive re-planning at an appropriate time. This study aims to investigate the feasibility of evaluating daily dose distributions using the divided-volume matching (DVM) technique without additional daily computed tomography (CT) scans for adaptive carbon ion radiotherapy for liver tumors. Approach. Phantom and patient data were included in this study. The developed in-house DVM software generated DVM CTs based on the existing resources, the planning CT, and orthogonal two-dimensional (2D) setup images. Bone matching (BM) and tumor matching (TM) are the two common ways of patient positioning correction to determine the isocenter for the irradiation of the day. We compared the dose distributions between DVM and in-room CTs with different isocenters based on BM or TM to verify whether the DVM CTs sufficiently represent the in-room CTs for daily dose distribution evaluations. Main results. For the phantom study, the clinical target volume coverage (V95%) differences between the in-room and the DVM CTs were <2%, and their dose distribution patterns were similar. For clinical data, the 3%/3 mm gamma passing rates were over 96%, and the planning target volume coverage (V95%) differences were <3% between the in-room and DVM CTs in nine out of ten patients. With different isocenters, the dose coverage of the DVM CT changed consistently with those of the in-room CT. Significance. The DVM technique enabled the evaluation of daily dose distributions without additional CT scans and was shown to be feasible in carbon ion radiotherapy for liver tumors.