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Hybrid pencil beam model (HPBM) based on photon characteristic line algorithm has been presented to get accurate three-dimensional (3D) dose distribution for lung radiotherapy in small fields. In the model, we introduced a scattering factor to accurately describe the transport behavior of scattered photons and secondary electrons, combined with the equivalent depth correction and the weighted density correction. The pencil beam kernels of heterogeneous lung phantoms were redefined by the scattering factor and depth dose for a reference field by photon characteristic line algorithm. Subsequently, the 3D dose distribution in lung phantoms with density of 0.1, 0.26, and 0.4 g/cm3, was calculated by the Finite-size pencil beam algorithm in five regular fields and an irregular field for 6 MV photon beam. The dose distributions obtained by the HPBM are in agreement with those obtained by the MC simulations, with a relative error of less than 3% in most of the cases. However, there are apparent discrepancies at media interfaces and lung anterior portion. Moreover, at media interfaces, relative dose errors of the two methods decrease with the increase in field size and lung density. The depth range in which relative errors is greater than 3% increases with the increase in field size at lung anterior portion. In these examples, maximum relative errors are between 5 and 29%. Nevertheless, it is shown that the HPBM based on photon characteristic line algorithm has potential research values in lung dose calculation under conditions of small fields.

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Abstract Purpose The purpose of this study is to evaluate the impact of two methods of reporting planned dose distributions on the Gamma analysis pass rates for comparison with measured 2D film dose and simulated delivered 3D dose for proton pencil beam scanning treatment of the Imaging and Radiation Oncology Core (IROC) proton lung and liver mobile phantoms. Methods and materials Four-dimensional (4D) computed-tomography (CT) image sets were acquired for IROC proton lung and liver mobile phantoms, which include dosimetry inserts that contains targets, thermoluminescent dosimeters and EBT2 films for plan dose verification. 4DCT measured fixed motion magnitudes were 1.3 and 1.0 cm for the lung and liver phantoms, respectively. To study the effects of motion magnitude on the Gamma analysis pass rate, three motion magnitudes for each phantom were simulated by creating virtual 4DCT image sets with motion magnitudes scaled from the scanned phantom motion by 50, 100, and 200%. The internal target volumes were contoured on the maximum intensity projection CTs of the 4DCTs for the lung phantom and on the minimum intensity projection CTs of the 4DCTs for the liver phantom. Treatment plans were optimized on the average intensity projection (AVE) CTs of the 4DCTs using the RayStation treatment planning system. Plan doses were calculated on the AVE CTs, which was defined as the planned AVE dose (method one). Plan doses were also calculated on all 10 phase CTs of the 4DCTs and were registered using target alignment to and equal-weight-summed on the 50% phase (T50) CT, which was defined as the planned 4D dose (method two). The planned AVE doses and 4D doses for phantom treatment were reported to IROC, and the 2D-2D Gamma analysis pass rates for measured film dose relative to the planned AVE and 4D doses were compared. To evaluate motion interplay effects, simulated delivered doses were calculated for each plan by sorting spots into corresponding respiratory phases using spot delivery time recorded in the log files by the beam delivery system to calculate each phase dose and accumulate dose to the T50 CTs. Ten random beam starting phases were used for each beam to obtain the range of the simulated delivered dose distributions. 3D-3D Gamma analyses were performed to compare the planned 4D/AVE doses with simulated delivered doses. Results The planned 4D dose matched better with the measured 2D film dose and simulated delivered 3D dose than the planned AVE dose. Using planned 4D dose as institution reported planned dose to IROC improved IROC film dose 2D-2D Gamma analysis pass rate from 92 to 96% on average for three films for the lung phantom (7% 5 mm), and from 92 to 94% in the sagittal plane for the liver phantom (7% 4 mm), respectively, compared with using the planned AVE dose. The 3D-3D Gamma analysis (3% 3 mm) pass rate showed that the simulated delivered doses for lung and liver phantoms using 10 random beam starting phases for each delivered beam matched the planned 4D dose significantly better than the planned AVE dose for phantom motions larger than 1 cm (p ≤ 0.04). Conclusions It is recommended to use the planned 4D dose as the institution reported planned dose to IROC to compare with the measured film dose for proton mobile phantoms to improve film Gamma analysis pass rate in the IROC credentialing process.

Purpose: This study aims to evaluate the performance of four artificial intelligence‐aided diagnostic systems in identifying and measuring four types of pulmonary nodules. Methods: Four types of nodules were implanted in a commercial lung phantom. The phantom was scanned with multislice spiral computed tomography, after which four systems (A, B, C, D) were used to identify the nodules and measure their volumes. Results: The relative volume error (RVE) of system A was the lowest for all nodules, except for small ground glass nodules (SGGNs). System C had the smallest RVE for SGGNs, −0.13 (−0.56, 0.00). In the Bland–Altman test, only systems A and C passed the consistency test, P = 0.40. In terms of precision, the miss rate (MR) of system C was 0.00% for small solid nodules (SSNs), ground glass nodules (GGNs), and solid nodules (SNs) but 4.17% for SGGNs. The comparable system D MRs for SGGNs, SSNs, and GGNs were 71.30%, 25.93%, and 47.22%, respectively, the highest among all the systems. Receiver operating characteristic curve analysis indicated that system A had the best performance in recognizing SSNs and GGNs, with areas under the curve of 0.91 and 0.68. System C had the best performance for SGGNs (AUC = 0.91). Conclusion: Among four types nodules, SGGNs are the most difficult to recognize, indicating the need to improve higher accuracy and precision of artificial systems. System A most accurately measured nodule volume. System C was most precise in recognizing all four types of nodules, especially SGGN. [ABSTRACT FROM AUTHOR]

Purpose: Between July 2013 and August 2019, 22% of the imaging and radiation oncology core (IROC) spine, and 15% of the moving lung phantom irradiations have failed to meet established acceptability criteria. The spine phantom simulates a highly modulated stereotactic body radiation therapy (SBRT) case, whereas the lung phantom represents a low‐to‐none modulation moving target case. In this study, we assessed the contribution of dose calculation errors to these phantom results and evaluated their effects on failure rates. Methods: We evaluated dose calculation errors by comparing the calculation accuracy of various institutions' treatment planning systems (TPSs) vs IROC‐Houston's previously established independent dose recalculation system (DRS). Each calculation was compared with the measured dose actually delivered to the phantom; cases in which the recalculation was more accurate were interpreted as a deficiency in the institution's TPS. A total of 258 phantom irradiation plans (172 lung and 86 spine) were recomputed. Results: Overall, the DRS performed better than the TPSs in 47% of the spine phantom cases. However, the DRS was more accurate in 93% of failing spine phantom cases (with an average improvement of 2.35%), indicating a deficiency in the institution's treatment planning system. Deficiencies in dose calculation accounted for 60% of the overall discrepancy between measured and planned doses among spine phantoms. In contrast, lung phantom DRS calculations were more accurate in only 35% and 42% of all and failing lung phantom cases respectively, indicating that dose calculation errors were not substantially present. These errors accounted for only 30% of the overall discrepancy between measured and planned doses. Conclusions: Dose calculation errors are common and substantial in IROC spine phantom irradiations, highlighting a major failure mode in this phantom and in clinical treatment management of these cases. In contrast, dose calculation accuracy had only a minimal contribution to failing lung phantom results, indicating that other failure modes drive problems with this phantom and similar clinical treatments. [ABSTRACT FROM AUTHOR]

Background/aim: Radiation dosimetry requires special phantoms which are comparable with organs and tissues of a human body. The lung is one of the organs with a low density. Therefore, it is important to create and use lung equivalent phantoms in dosimetric controls. The aim of this study was to investigate the importance of using lung equivalent phantoms for different respiratory phases during measurements with both computed tomography (CT) and linear accelerator. Materials and methods: The maximum lung inhalation phantom (LIP) and lung exhalation phantom (LEP) were created for two respiratory phases. The Hounsfield Unit (HU) values based on the selected slice thickness and CT tube voltages were investigated, as well as the difference between energy and algorithms used in the treatment planning system. Results: It was found that the change in HU values according to slice thickness were more significant in measurements for respiratory phases. The dose difference between LEP and LIP at a point which is located 1 cm below the surface of the phantoms was found as 1·0% for 6 megavolt (MV) and 2·8% for 18 MV. The highest difference between the two algorithms was found to be 7·22% for 6 MV and 10·93% for 18 MV for LIP phantom. Conclusion: It can be said that the LIP and LEP phantoms prepared in accordance with respiratory phases can be a simple and inexpensive method to investigate any difference in dosimetry during respiratory phases. Also, measured and calculated dose values are in good agreement when thinner slice thickness was chosen. [ABSTRACT FROM AUTHOR]

In proton therapy, the Bragg peak of a proton beam reportedly deteriorates when passing though heterogeneous structures such as human lungs. Previous studies have used heterogeneous random voxel phantoms, in which soft tissues and air are randomly allotted to render the phantoms the same density as human lungs, for conducting Monte Carlo (MC) simulations. However, measurements of these phantoms are complicated owing to their difficult‐to‐manufacture shape. In the present study, we used Voronoi tessellation to design a phantom that can be manufactured, and prepared a Voronoi lung phantom for which both measurement and MC calculations are possible. Our aim was to evaluate the effectiveness of this phantom as a new lung phantom for investigating proton beam Bragg peak deterioration. For this purpose, we measured and calculated the percentage depth dose and the distal falloff widths (DFW) passing through the phantom. For the 155 MeV beam, the measured and calculated DFW values with the Voronoi lung phantom were 0.40 and 0.39 cm, respectively. For the 200 MeV beam, the measured and calculated DFW values with the Voronoi lung phantom were both 0.48 cm. Our results indicate that both the measurements and MC calculations exhibited high reproducibility with plastinated lung sample from human body in previous studies. We found that better results were obtained using the Voronoi lung phantom than using other previous phantoms. The designed phantom may contribute significantly to the improvement of measurement precision. This study suggests that the Voronoi lung phantom is useful for simulating the effects of the heterogeneous structure of lungs on proton beam deterioration. [ABSTRACT FROM AUTHOR]

Lung ultrasound (US) surface wave elastography (SWE) is a novel technique that measures superficial lung tissue elastic properties. A thin pleural fluid layer covers a lung, but its effect on lung measurements in SWE is unknown. We modeled a lung and pleural fluid with sponges and a thin layer of US transmission gel. Sponge surface wave speeds measured from SWE were compared for sponges without and with the thin US gel layer at 3 wave excitation frequencies. The comparison showed that the sponge surface wave speed measurements were not affected by the thin gel layer. [ABSTRACT FROM AUTHOR]

When dealing with computed tomography volume data, the accurate segmentation of lung nodules is of great importance to lung cancer analysis and diagnosis, being a vital part of computer-aided diagnosis systems. However, due to the variety of lung nodules and the similarity of visual characteristics for nodules and their surroundings, robust segmentation of nodules becomes a challenging problem. A segmentation algorithm based on the fast marching method is proposed that separates the image into regions with similar features, which are then merged by combining regions growing with k-means. An evaluation was performed with two distinct methods (objective and subjective) that were applied on two different datasets, containing simulation data generated for this study and real patient data, respectively. The objective experimental results show that the proposed technique can accurately segment nodules, especially in solid cases, given the mean Dice scores of 0.933 and 0.901 for round and irregular nodules. For non-solid and cavitary nodules the performance dropped—0.799 and 0.614 mean Dice scores, respectively. The proposed method was compared to active contour models and to two modern deep learning networks. It reached better overall accuracy than active contour models, having comparable results to DBResNet but lesser accuracy than 3D-UNet. The results show promise for the proposed method in computer-aided diagnosis applications.

Several lung diseases lead to alterations in regional lung mechanics, including ventilator- and radiation-induced lung injuries. Such alterations can lead to localized underventilation of the affected areas, resulting in the overdistension of the surrounding healthy regions. Thus, there has been growing interest in quantifying the dynamics of the lung parenchyma using regional biomechanical markers. Image registration through dynamic imaging has emerged as a powerful tool to assess lung parenchyma's kinematic and deformation behaviors during respiration. However, the difficulty in validating the image registration estimation of lung deformation, primarily due to the lack of ground-truth deformation data, has limited its use in clinical settings. To address this barrier, we developed a method to convert a finite-element (FE) mesh of the lung into a phantom computed tomography (CT) image, advantageously possessing ground-truth information included in the FE model. The phantom CT images generated from the FE mesh replicated the geometry of the lung and large airways that were included in the FE model. Using spatial frequency response, we investigated the effect of " imaging parameters" such as voxel size (resolution) and proximity threshold values on image quality. A series of high-quality phantom images generated from the FE model simulating the respiratory cycle will allow for the validation and evaluation of image registration-based estimations of lung deformation. In addition, the present method could be used to generate synthetic data needed to train machine-learning models to estimate kinematic biomarkers from medical images that could serve as important diagnostic tools to assess heterogeneous lung injuries.

Abstract Lung ultrasound surface wave elastography (LUSWE) is a novel technique used to measure superficial lung tissue stiffness. A phantom study was carried out in the study described here to evaluate the application of LUSWE to assess lung water for pulmonary edema. A lung phantom model with cellulose sponge was used; various volumes of water were injected into the sponge to model lung water. Shaker-generated surface wave propagation on the sponge surface was recorded by a 10-MHz ultrasound probe at three shaker frequencies: 100, 150 and 200 Hz. Surface wave speeds were calculated but did not exhibit dependence on the volume of injected water. However, the shear viscosity of the sponge increased with water content, and shear elasticity also exhibited a subtle increase. This study suggests that sponge viscoelasticity might change with the water content, which can be detected by LUSWE. [ABSTRACT FROM AUTHOR]

Lung cancer is the leading cause of cancer-related deaths. Many methods and devices help acquire more accurate clinical and localization information during lung interventions and may impact the death rate for lung cancer. However, there is a learning curve for operating these tools due to the complex structure of the airway. In this study, we first discuss the creation of a lung phantom model from medical images, which is followed by a comparison of 3D printing in terms of quality and consistency. Two tests were conducted to test the performance of the developed phantom, which was designed for training simulations of the target and ablation processes in endochonchial interventions. The target test was conducted through an electromagnetic tracking catheter with navigation software. An ablation catheter with a recently developed thermochromic ablation gel conducted the ablation test. The results of two tests show that the phantom was very useful for target and ablation simulation. In addition, the thermochromic gel allowed doctors to visualize the ablation zone. Many lung interventions may benefit from custom training or accuracy with the proposed low-cost and patient-specific phantom.

Background and purpose The objective of this study was to compare the latest respiratory motion-management strategies, namely the internal-target-volume (ITV) concept, the mid-ventilation (MidV) principle, respiratory gating and dynamic couch tracking. Materials and methods An anthropomorphic, deformable and dynamic lung phantom was used for the dosimetric validation of these techniques. Stereotactic treatments were adapted to match the techniques and five distinct respiration patterns, and delivered to the phantom while radiographic film measurements were taken inside the tumor. To report on tumor coverage, these dose distributions were used to calculate mean doses ( D mean ), changes in homogeneity indices (Δ H 2 - 98 ), gamma agreement, and areas covered by the planned minimum dose ( A >Dmin ). Results All techniques achieved good tumor coverage ( A >Dmin > 99.0%) and minor changes in D mean (±3.2%). Gating and tracking strategies showed superior results in gamma agreement and Δ H 2 - 98 compared to ITV and MidV concepts, which seem to be more influenced by the interplay and the gradient effect. For lung, heart and spinal cord, significant dose differences between the four techniques were found ( p < 0.05), with lowest doses for gating and tracking strategies. Conclusion Active motion-management techniques, such as gating or tracking, showed superior tumor dose coverage and better organ dose sparing than the passive techniques based on tumor margins. [ABSTRACT FROM AUTHOR]

Purpose: Most clinically deployed strategies for respiratory motion management in lung radiotherapy (e.g., gating and tracking) use external markers that serve as surrogates for tumor motion. However, typical lung phantoms used to validate these strategies are based on a rigid exterior and a rigid or a deformable-interior. Such designs do not adequately represent respiration because the thoracic anatomy deforms internally as well as externally. In order to create a closer approximation of respiratory motion, the authors describe the construction and experimental testing of an externally as well as internally deformable, programmable lung phantom. Methods: The outer shell of a commercially available lung phantom (RS-1500, RSD, Inc.) was used. The shell consists of a chest cavity with a flexible anterior surface, and embedded vertebrae, rib-cage and sternum. A custom-made insert was designed using a piece of natural latex foam block. A motion platform was programmed with sinusoidal and ten patient-recorded lung tumor trajectories. The platform was used to drive a rigid foam "diaphragm" that compressed/decompressed the phantom interior. Experimental characterization comprised of determining the reproducibility and the external-internal correlation of external and internal marker trajectories extracted from kV x-ray fluoroscopy. Experiments were conducted to illustrate three example applications of the phantom--(i) validating the geometric accuracy of the VisionRT surface photogrammetry system; (ii) validating an image registration tool, NiftyReg; and (iii) quantifying the geometric error due to irregular motion in four-dimensional computed tomography (4DCT). Results: The phantom correctly reproduced sinusoidal and patient-derived motion, as well as realistic respiratory motion-related effects such as hysteresis. The reproducibility of marker trajectories over multiple runs for sinusoidal as well as patient traces, as characterized by fluoroscopy, was within 0.25 mm RMS error. The motion trajectories of internal and external radio-opaque markers as measured by fluoroscopy were found to be highly correlated (R > 0.95). Using the phantom, it was demonstrated that the motion trajectories of regions-of-interest on the surface as measured by VisionRT are highly consistent with corresponding fluoroscopically acquired surface marker trajectories, with RMS errors within 0.26 mm. Furthermore, it was shown that the trajectories of external and internal marker trajectories derived from NiftyReg deformation vector fields were within 1 mm root mean square errors comparing to trajectories obtained by segmenting markers from individual fluoro frames. Finally, it was shown that while 4DCT can be used to localize internal markers for sinusoidal motion with reasonable accuracy, the localization error increases significantly (by a factor of ~2) in the presence of cycle-to-cycle variations that are observed in patient-derived respiratory motion. Conclusions: The authors have developed a realistic externally and internally deformable, programmable lung phantom that will serve as a valuable tool for clinical and investigational motion management studies in thoracic and abdominal radiation therapies. [ABSTRACT FROM AUTHOR]

Significance: Gas in scattering media absorption spectroscopy (GASMAS) enables noninvasive gas sensing in the body. It is developing as a tool for diagnosis and monitoring of respiratory conditions in neonates. Phantom models with relevant features to the clinical translation of GASMAS technology are necessary to understand technical challenges and potential applications of this technique. State-of-the-art phantoms designed for this purpose have focused on the optical properties and anthropomorphic geometry of the thorax, contributing to the source–detector placement, design, and optimization. Lung phantom mimicking the alveolar anatomy has not been included in the existent models due to the inherent complexity of the tissue. We present a simplified model that recreates inflated alveoli embedded in lung phantom. Aim: The goal of this study was to build a lung model with air-filled structures mimicking inflated alveoli surrounded by optical phantom with accurate optical properties (μa = 0.50 cm − 1 and μs′=5.4 cm−1) and physiological parameters [37°C and 100% relative humidity (RH)], and to control the air volume within the phantom to demonstrate the feasibility of GASMAS in sensing changes in pulmonary air volume. Approach: The lung model was built using a capillary structure with analogous size to alveolar units. Part of the capillaries were filled with liquid lung optical phantom to recreate scattering and absorption, whereas empty capillaries mimicked air filled alveoli. The capillary array was placed inside a custom-made chamber that maintained pulmonary temperature and RH. The geometry of the chamber permitted the placement of the laser head and detector of a GASMAS bench top system (MicroLab Dual O2 / H2O), to test the changes in volume of the lung model in transmittance geometry. Results: The lung tissue model with air volume range from 6.89 × 10 − 7 m3 to 1.80 × 10 − 3 m3 was built. Two measurement sets, with 10 different capillary configurations each, were arranged to increase or decrease progressively (in steps of 3.93 × 10 − 8 m3) the air volume in the lung model. The respective GASMAS data acquisition was performed for both data sets. The maximum absorption signal was obtained for configurations with the highest number of air-filled capillaries and decreased progressively when the air spaces were replaced by capillaries filled with liquid optical phantom. Further studies are necessary to define the minimum and maximum volume of air that can be measured with GASMAS-based devices for different source–detector geometries. Conclusions: The optical properties and the structure of tissue from the respiratory zone have been modeled using a simplified capillary array immersed in a controlled environment chamber at pulmonary temperature and RH. The feasibility of measuring volume changes with GASMAS technique has been proven, stating a new possible application of GASMAS technology in respiratory treatment and diagnostics. [ABSTRACT FROM AUTHOR]

• An experimental analysis of miniaturized microwave holographic setup is described for detection of tumors in lung tissues. • A precise human tissue equivalent lung phantom is proposed and developed along with the validation of its dielectric behaviour. • Imaging of tumor inside the lungs for various depth and positions is done using microwave holographic reflectometry. • The tumor of size 5 mm is detected and identified at several depths during multiple experiments. • Dielectric properties are also used to calculate the depth of tumours. In recent statistics, lung cancer is the most severe cause of death among all type of cancers. Here, we are presenting a nondestructive and noninvasive imaging methodology for lung cancer detection i.e., microwave holographic reflectometry. A precise tissue equivalent lung phantom is proposed and developed with the tumor inside for various depth and positions. Multiple experiments have been performed with the tumor at multiple depths inside the lung at operating frequency i.e., 10 GHz. The qualitative findings show that the tumor of size 5 mm is detected and identified at various depths during multiple experiments. The reconstructed phase values and dielectric properties are used to calculate the exact depth of tumors. The proof of concept presented in the paper determines the position and depth of the tumor within the lungs. Since, there is a utilization of miniaturized components, the entire system becomes small, which can be further improved to make the technique a viable alternative to CT scanning. [ABSTRACT FROM AUTHOR]

Phantoms are widely used during the development of new imaging systems and algorithms. For development and optimization of new imaging systems such as tomosynthesis, where conventional image quality metrics may not be applicable, a realistic phantom that can be used across imaging systems is desirable. A novel anthropomorphic lung phantom was developed by plastination of an actual pig lung. The plastinated phantom is characterized and compared with reference to in vivo images of the same tissue prior to plastination using high resolution 3D CT. The phantom is stable over time and preserves the anatomical features and relative locations of the in vivo sample. The volumes for different tissue types in the phantom are comparable to the in vivo counterparts, and CT numbers for different tissue types fall within a clinically useful range. Based on the measured CT numbers, the phantom cardiac tissue experienced a 92% decrease in bulk density and the phantom pulmonary tissue experienced a 78% decrease in bulk density compared to their in vivo counterparts. By-products in the phantom from the room temperature vulcanizing silicone and plastination process are also identified. A second generation phantom, which eliminates most of the by-products, is presented. Such anthropomorphic phantoms can be used to evaluate a wide range of novel imaging systems. [ABSTRACT FROM AUTHOR]

The benefits of using Synchrony™ Respiratory Tracking System (RTS) in conjunction with the CyberKnife robotic treatment device to treat a “breathing tumor” in an anthropomorphic, tissue-equivalent, thoracic phantom have been investigated. The following have been studied: (a) Synchrony’s ability to allow the CyberKnife to deliver accurately a planned dose distribution to the free-breathing phantom and (b) the dosimetric implications when irregularities in the breathing cycle and phase differences between internal (tumor) and external (chest) motion exist in the course of one treatment fraction. The breathing phantom PULMONE (phantom used in lung motion experiments) has been used, which can imitate regular or irregular breathing patterns. The breathing traces from two patients with lung cancer have been selected as input. Both traces were irregular in amplitude, frequency, and base line. Patient B demonstrated a phase difference between internal and external motion, whereas patient A did not. The experiment was divided into three stages: In stage I-static, the treatment was delivered to the static phantom. In stage II-motion, the phantom was set to breathe, following the breathing trace of each of the two patients. Synchrony™ was switched off, so no motion compensation was made. In stage III-compensation, the phantom was set to breathe and Synchrony™ was switched on. A linear correspondence model was chosen to allow for phase differences between internal and external motion. Gafchromic EBT film was inserted in the phantom tumor to measure dose. To eradicate small errors in film alignment during readout, a gamma comparison with pass criteria of 3%/3 mm was selected. For a more quantitative approach, the percentage of pixels in each gamma map that exceeded the value of 1 (P1) was also used. For both breathing signals, the dose blurring caused by the respiratory motion of the tumor in stage II was degraded considerably compared with stage I (P1=15% for patient A and 8% for patient B). The motion compensation via the linear correspondence model was sufficient to provide a dose distribution that satisfied the set gamma criteria (P1=3% for patient A and 2% for patient B). Synchrony™ RTS has been found satisfactory in recovering the initial detail in dose distribution, for realistic breathing signals, even in the case where a phase delay between internal tumor motion and external chest displacement exists. For the signals applied here, a linear correspondence model provided an acceptable degree of motion compensation. [ABSTRACT FROM AUTHOR]

The proposed work focuses on the detection of lung cancer using a microstrip patch antenna. A compact microstrip patch antenna operating at ISM band has been designed and placed on healthy as well as cancer affected lung (different stages) phantom. Scatter and other parameters are observed, and data set is created for healthy as well as for each stage of cancerous lung. Variation because of cancer and its stages in the antenna parameters such as electric field, magnetic field, surface current, power flow, current density, power loss density, electrical energy density, and magnetic energy density, return loss, antenna gain, and tumor radius is observed. The created dataset has been further classified to differentiate a healthy lung from a cancerous one and its stages using Random Forest machine learning algorithm with an accuracy of 93.75%. [ABSTRACT FROM AUTHOR]

The construction of a breathing lung phantom that can be used to measure the amount of radioactive gas in the lungs as well as to determine the absorbed dose is described. For a lung ventilation study that consists of 6 views of 300 kents each, an effective dose equivalent of 50 μSv was calculated. The phantom is also suitable for comparison of different generator systems. [ABSTRACT FROM AUTHOR]

When dealing with computed tomography volume data, the accurate segmentation of lung nodules is of great importance to lung cancer analysis and diagnosis, being a vital part of computer-aided diagnosis systems. However, due to the variety of lung nodules and the similarity of visual characteristics for nodules and their surroundings, robust segmentation of nodules becomes a challenging problem. A segmentation algorithm based on the fast marching method is proposed that separates the image into regions with similar features, which are then merged by combining regions growing with k-means. An evaluation was performed with two distinct methods (objective and subjective) that were applied on two different datasets, containing simulation data generated for this study and real patient data, respectively. The objective experimental results show that the proposed technique can accurately segment nodules, especially in solid cases, given the mean Dice scores of 0.933 and 0.901 for round and irregular nodules. For non-solid and cavitary nodules the performance dropped—0.799 and 0.614 mean Dice scores, respectively. The proposed method was compared to active contour models and to two modern deep learning networks. It reached better overall accuracy than active contour models, having comparable results to DBResNet but lesser accuracy than 3D-UNet. The results show promise for the proposed method in computer-aided diagnosis applications. [ABSTRACT FROM AUTHOR]

Terahertz (THz) frequency is finding vast application in health monitoring and disease diagnosis as it has been proven safe for humans. This paper presents design and steps involved in designing the terahertz antenna operating at 257.04 THz for In-Vivo lung cancer detection. The proposed antenna aids in detecting and differentiating between the different stages of lung cancer. The cancer changes the permittivity of the lung. The radiation pattern of the antenna when placed on the infected lung phantom shows variation in comparison to the healthy lung. The stages of the lung cancer can also be deciphered by radiation pattern of the designed antenna as the tumor differs in size and location with advancement in each stage. [ABSTRACT FROM AUTHOR]

Proton therapy treatment for lungs remains challenging as images enabling the detection of inter- and intra-fractional motion, which could be used for proton dose adaptation, are not readily available. 4D computed tomography (4DCT) provides high image quality but is rarely available in-room, while in-room 4D cone beam computed tomography (4DCBCT) suffers from image quality limitations stemming mostly from scatter detection. This study investigated the feasibility of using virtual 4D computed tomography (4DvCT) as a prior for a phase-per-phase scatter correction algorithm yielding a 4D scatter corrected cone beam computed tomography image (4DCBCT cor ), which can be used for proton dose calculation. 4DCT and 4DCBCT scans of a porcine lung phantom, which generated reproducible ventilation, were acquired with matching breathing patterns. Diffeomorphic Morphons, a deformable image registration algorithm, was used to register the mid-position 4DCT to the mid-position 4DCBCT and yield a 4DvCT. The 4DCBCT was reconstructed using motion-aware reconstruction based on spatial and temporal regularization (MA-ROOSTER). Successively for each phase, digitally reconstructed radiographs of the 4DvCT, simulated without scatter, were exploited to correct scatter in the corresponding CBCT projections. The 4DCBCT cor was then reconstructed with MA-ROOSTER using the corrected CBCT projections and the same settings and deformation vector fields as those already used for reconstructing the 4DCBCT. The 4DCBCT cor and the 4DvCT were evaluated phase-by-phase, performing proton dose calculations and comparison to those of a ground truth 4DCT by means of dose-volume-histograms (DVH) and gamma pass-rates (PR). For accumulated doses, DVH parameters deviated by at most 1.7% in the 4DvCT and 2.0% in the 4DCBCT cor case. The gamma PR for a (2%, 2 mm) criterion with 10% threshold were at least 93.2% (4DvCT) and 94.2% (4DCBCT cor ), respectively. The 4DCBCT cor technique enabled accurate proton dose calculation, which indicates the potential for applicability to clinical 4DCBCT scans., (Creative Commons Attribution license.)

Purpose: The purpose of this study is to evaluate the impact of two methods of reporting planned dose distributions on the Gamma analysis pass rates for comparison with measured 2D film dose and simulated delivered 3D dose for proton pencil beam scanning treatment of the Imaging and Radiation Oncology Core (IROC) proton lung and liver mobile phantoms.Methods and Materials: Four-dimensional (4D) computed-tomography (CT) image sets were acquired for IROC proton lung and liver mobile phantoms, which include dosimetry inserts that contains targets, thermoluminescent dosimeters and EBT2 films for plan dose verification. 4DCT measured fixed motion magnitudes were 1.3 and 1.0 cm for the lung and liver phantoms, respectively. To study the effects of motion magnitude on the Gamma analysis pass rate, three motion magnitudes for each phantom were simulated by creating virtual 4DCT image sets with motion magnitudes scaled from the scanned phantom motion by 50, 100, and 200%. The internal target volumes were contoured on the maximum intensity projection CTs of the 4DCTs for the lung phantom and on the minimum intensity projection CTs of the 4DCTs for the liver phantom. Treatment plans were optimized on the average intensity projection (AVE) CTs of the 4DCTs using the RayStation treatment planning system. Plan doses were calculated on the AVE CTs, which was defined as the planned AVE dose (method one). Plan doses were also calculated on all 10 phase CTs of the 4DCTs and were registered using target alignment to and equal-weight-summed on the 50% phase (T50) CT, which was defined as the planned 4D dose (method two). The planned AVE doses and 4D doses for phantom treatment were reported to IROC, and the 2D-2D Gamma analysis pass rates for measured film dose relative to the planned AVE and 4D doses were compared. To evaluate motion interplay effects, simulated delivered doses were calculated for each plan by sorting spots into corresponding respiratory phases using spot delivery time recorded in the log files by the beam delivery system to calculate each phase dose and accumulate dose to the T50 CTs. Ten random beam starting phases were used for each beam to obtain the range of the simulated delivered dose distributions. 3D-3D Gamma analyses were performed to compare the planned 4D/AVE doses with simulated delivered doses.Results: The planned 4D dose matched better with the measured 2D film dose and simulated delivered 3D dose than the planned AVE dose. Using planned 4D dose as institution reported planned dose to IROC improved IROC film dose 2D-2D Gamma analysis pass rate from 92 to 96% on average for three films for the lung phantom (7% 5 mm), and from 92 to 94% in the sagittal plane for the liver phantom (7% 4 mm), respectively, compared with using the planned AVE dose. The 3D-3D Gamma analysis (3% 3 mm) pass rate showed that the simulated delivered doses for lung and liver phantoms using 10 random beam starting phases for each delivered beam matched the planned 4D dose significantly better than the planned AVE dose for phantom motions larger than 1 cm (p ≤ 0.04).Conclusions: It is recommended to use the planned 4D dose as the institution reported planned dose to IROC to compare with the measured film dose for proton mobile phantoms to improve film Gamma analysis pass rate in the IROC credentialing process. [ABSTRACT FROM AUTHOR]

Respiratory motion is known to affect the quantitation of FDG18 uptake in lung lesions. The aim of the study was to investigate the magnitude of errors in tracer activity determination due to motion, and its dependence upon CT attenuation at different phases of the motion cycle. To estimate these errors we have compared maximum activity concentrations determined from PET/CT images of a lung phantom at rest and under simulated respiratory motion. The NEMA 2001 IEC body phantom, containing six hollow spheres with diameters 37, 28, 22, 17, 13, and 10 mm, was used in this study. To mimic lung tissue density, the phantom (excluding spheres) was filled with low density polystyrene beads and water. The phantom spheres were filled with FDG18 solution setting the target-to-background activity concentration ratio at 8:1. PET/CT data were acquired with the phantom at rest, and while it was undergoing periodic motion along the longitudinal axis of the scanner with a range of displacement being 2 cm, and a period of 5 s. The phantom at rest and in motion was scanned using manufacturer provided standard helical/clinical protocol, a helical CT scan followed by a PET emission scan. The moving phantom was also scanned using a 4D-CT protocol that provides volume image sets at different phases of the motion cycle. To estimate the effect of motion on quantitation of activities in six spheres, we have examined the activity concentration data for (a) the stationary phantom, (b) the phantom undergoing simulated respiratory motion, and (c) a moving phantom acquired with PET/4D-CT protocol in which attenuation correction was performed with CT images acquired at different phases of motion cycle. The data for the phantom at rest and in motion acquired with the standard helical/clinical protocol showed that the activity concentration in the spheres can be underestimated by as much as 75%, depending on the sphere diameter. We have also demonstrated that fluctuations in sphere's activity concentration from one PET/CT scan to another acquired with standard helical/clinical protocol can arise as a consequence of spatial mismatch between the sphere's location in PET emission and the CT data., (© 2005 American Association of Physicists in Medicine.)