Hand-wrist radiography is the most common and accurate method for evaluating children\'s bone age. To reduce the scattered radiation of radiosensitive organs in bone age assessment, we designed a small X-ray instrument with radioprotection function by adding metal enclosure for X-ray shielding. We used a phantom operator to compare the scattered radiation doses received by sensitive organs under three different protection scenarios (proposed instrument, radiation personal protective equipment, no protection). The proposed instrument showed greater reduction in the mean dose of a single exposure compared with radiation personal protective equipment especially on the left side which was proximal to the X-ray machine (≥80.0% in eye and thyroid,  ≥99.9% in breast and gonad). The proposed instrument provides a new pathway towards more convenient and efficient radioprotection.

OBJECTIVE: This study aimed to explore the interactions between microbubbles and microwave ablation (MWA).
METHODS: The study employed custom-made phantoms (in vitro) and white New Zealand rabbits (in vivo). MWA was performed with or without microbubbles in the phantoms (2 × 105 particles mL-1) and rabbit livers (intravenous injection of 0.05 mL/kg SonoVue). During the MWA, K-type thermocouple probes were used to monitor the MWA-induced temperature increase. Contrast-enhanced ultrasound imaging (CEUS) was used to monitor and analyze the microbubbles signal intensity. After MWA, the ablation-zone volumes were evaluated and compared between the groups with and without microbubbles.
RESULTS: In both the phantom models and rabbits, microbubbles showed no significant influence on MWA, including the ablation range and MWA-induced temperature increase. In phantoms and rabbit livers filled with microbubbles, MWA caused the formation of a gradually expanding microbubble-defect region over the ablation time. An increase in the temperature caused microbubble destruction.
CONCLUSIONS: Microbubbles had no significant influence on MWA. However, MWA induced the destruction of microbubbles in a temperature-dependent manner. Thus, the poor thermotolerance of microbubbles is a non-negligible barrier when using CEUS to monitor the ablation range during MWA in real-time.

Lung cancer remains a leading cause of death among cancer patients. Computed tomography (CT) plays a key role in lung cancer screening. Previous studies have not adequately quantified the effect of scanning protocols on the detected tumor size. The aim of this study was to assess the effect of various CT scanning parameters on tumor size and densitometry based on a phantom study and to investigate the optimal energy and mA image quality for screening assessment.
We proposed a new model using the LUNGMAN N1 phantom multipurpose anthropomorphic chest phantom (diameters: 8, 10, and 12 mm; CT values: - 100, - 630, and - 800 HU) to evaluate the influence of changes in tube voltage and tube current on the size and density of pulmonary nodules. In the LUNGMAN N1 model, three types of simulated lung nodules representing solid tumors of different sizes were used. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were used to evaluate the image quality of each scanning combination. The consistency between the calculated results based on segmentation from two physicists was evaluated using the interclass correlation coefficient (ICC).
In terms of nodule size, the longest diameters of ground-glass nodules (GGNs) were closest to the ground truth on the images measured at 100 kVp tube voltage, and the longest diameters of solid nodules were closest to the ground truth on the images measured at 80 kVp tube voltage. In respect to density, the CT values of GGNs and solid nodules were closest to the ground truth when measured at 80 kVp and 100 kVp tube voltage, respectively. The overall agreement demonstrates that the measurements were consistent between the two physicists.
Our proposed model demonstrated that a combination of 80 kVp and 140 mA scans was preferred for measuring the size of the solid nodules, and a combination of 100 kVp and 100 mA scans was preferred for measuring the size of the GGNs when performing lung cancer screening. The CT values at 80 kVp and 100 kVp were preferred for the measurement of GGNs and solid nodules, respectively, which were closest to the true CT values of the nodules. Therefore, the combination of scanning parameters should be selected for different types of nodules to obtain more accurate nodal data.

UNASSIGNED: The update in technology may impact the accuracy in measuring bone mineral density (BMD). However, the application of the new fast kilovoltage (kV)-switching dual-energy computed tomography (DECT) for BMD measurement has not yet been reported. This study aimed to examine the accuracy and precision of the new fast kV-switching DECT in measuring BMD and to evaluate its applicability in clinical BMD measurement.
UNASSIGNED: Forty sets of the new fast kV-switching DECT scans and one quantitative computed tomography (QCT) scan were performed on the European Spine Phantom. Their relative errors and relative standard deviations were compared. A retrospective analysis was performed on patients who underwent chest plain DECT and abdominal monoenergetic plain CT at the same time. The relationship between hydroxyapatite-water and hydroxyapatite-fat measured using DECT and BMD measured using QCT was analyzed by multivariate regression analysis.
UNASSIGNED: The relative errors of the new fast kV-switching DECT with low tube speeds (0.8 and 1.0 s/r) were all less than 6% and were less than those of QCT, except for those at 515 mA. The relative standard deviation values with high tube rotation speeds (0.5 and 0.6 s/r) were higher than those with low tube speeds (0.8 and 1.0 s/r) under most tube current conditions. The new fast kV-switching DECT-derived BMD values corrected by multiple linear regression (predicted hydroxyapatite) were significantly positively correlated with the QCT-based BMD values (R2=0.912; P<0.001). The results of the Bland-Altman analysis demonstrated high consistency between the 2 measurement methods.
UNASSIGNED: Results of the phantom measurements indicated that the new fast kV-switching DECT could measure BMD with relatively high accuracy and precision. The results of a subsequent clinical in vivo experiment demonstrated that vertebral BMD measurements derived from DECT and QCT were mostly consistent and highly accurate. Therefore, patients who undergo DECT for other clinical indications can simultaneously have their BMD determined.

A soft and highly directive, proximity-coupled split-ring resonator fabricated with a liquid alloy, copper and polydimethylsiloxane (PDMS) is presented. The same was designed for sensing osteogenesis of calvarial bone. As dielectric properties of bone grafts in ossifying calvarial defects should change during the osteogenesis process, devices like this could monitor the gradual transformation of the defect into bone by differentiating changes in the dielectric properties as shifts in the resonance frequency. Computational Software Technology (CST) Microwave Studio®-based simulation results on computational head models were in good agreement with laboratory results on head phantom models, which also included the comparison with an in-vivo measurement on the human head. A discussion based on an inductive reasoning regarding dynamics\' considerations is provided as well. Since the skin elasticity of newborn children is high, stretching and crumpling could be significant. In addition, due to typical head curvatures in newborn children, bending should not be a significant issue, and can provide higher energy focus in the defect area and improve conformability. The present concept could support the development of soft, cheap and portable follow-up monitoring systems to use in outpatient hospital and home care settings for post-operative monitoring of bone healing after reconstructive surgical procedures.

Non-invasive reconstruction of electrophysiological activity in the heart is of great significance for clinical disease prevention and surgical treatment. The distribution of transmembrane potential (TMP) in three-dimensional myocardium can help us diagnose heart diseases such as myocardial ischemia and ectopic pacing. However, the problem of solving TMP is ill-posed, and appropriate constraints need to be added. The existing state-of-art method total variation minimisation only takes advantage of the local similarity in space, which has the problem of over-smoothing, and fails to take into account the relationship among frames in the dynamic TMP sequence. In this work, the authors introduce a novel regularisation method called graph-based total variation to make up for the above shortcomings. The graph structure takes the TMP value of a time sequence on each heart node as the criterion to establish the similarity relationship among the heart. Two sets of phantom experiments were set to verify the superiority of the proposed method over the traditional constraints: infarct scar reconstruction and activation wavefront reconstruction. In addition, experiments with ten real premature ventricular contractions patient data were used to demonstrate the accuracy of the authors\' method in clinical applications.

Depth estimation plays an important role in vision-based laparoscope surgical navigation systems. Most learning-based depth estimation methods require ground truth depth or disparity images for training; however, these data are difficult to obtain in laparoscopy. The authors present an unsupervised learning depth estimation approach by fusing traditional stereo knowledge. The traditional stereo method is used to generate proxy disparity labels, in which unreliable depth measurements are removed via a confidence measure to improve stereo accuracy. The disparity images are generated by training a dual encoder-decoder convolutional neural network from rectified stereo images coupled with proxy labels generated by the traditional stereo method. A principled mask is computed to exclude the pixels, which are not seen in one of views due to parallax effects from the calculation of loss function. Moreover, the neighbourhood smoothness term is employed to constrain neighbouring pixels with similar appearances to generate a smooth depth surface. This approach can make the depth of the projected point cloud closer to the real surgical site and preserve realistic details. The authors demonstrate the performance of the method by training and evaluation with a partial nephrectomy da Vinci surgery dataset and heart phantom data from the Hamlyn Centre.

To establish a cost-effective and easily available phantom for training residents in ultrasound-guided fine needle thyroid nodule targeting punctures.
Tofu, drinking straws filled with coupling gel, a urine tube, and 21-gauge needles were used to generate a phantom thyroid with nodules for training. Twelve radiology residents were involved in the study. The puncture success rates were recorded and compared before and after phantom training using the Wilcoxon signed-rank test.
On ultrasonography, tofu mimicked the texture of the thyroid. Drinking straws filled with coupling gel mimicked vessels. The urine tube filled with air mimicked the trachea, and 21-gauge needles mimicked small nodules in the transverse section. The entire phantom was similar to the structure of the thyroid and surrounding tissues. The puncture success rates of radiology residents were significantly increased from 34.4 ± 14.2% to 66.7 ± 19.5% after training (p = 0.003). The phantom was constructed in approximately 10 minutes and materials cost less than CNY 10 (approximately $ 1.5) at a local store.
The tofu model was cost-effective, easily attainable, and effective for training residents in ultrasound-guided fine needle thyroid nodule targeting punctures in vitro.

Noise, partial volume (PV) effect, and image-intensity inhomogeneity render a challenging task for segmentation of brain magnetic resonance (MR) images. Most of the current MR image segmentation methods focus on only one or two of the above-mentioned effects. The objective of this paper is to propose a unified framework, based on the maximum a posteriori probability principle, by taking all these effects into account simultaneously in order to improve image segmentation performance. Instead of labeling each image voxel with a unique tissue type, the percentage of each voxel belonging to different tissues, which we call a mixture, is considered to address the PV effect. A Markov random field model is used to describe the noise effect by considering the nearby spatial information of the tissue mixture. The inhomogeneity effect is modeled as a bias field characterized by a zero mean Gaussian prior probability. The well-known fuzzy C-mean model is extended to define the likelihood function of the observed image. This framework reduces theoretically, under some assumptions, to the adaptive fuzzy C-mean (AFCM) algorithm proposed by Pham and Prince. Digital phantom and real clinical MR images were used to test the proposed framework. Improved performance over the AFCM algorithm was observed in a clinical environment where the inhomogeneity, noise level, and PV effect are commonly encountered.