Physical and Engineering Sciences in Medicine最新文献

Stereotactic body radiation therapy (SBRT) has been increasingly used for the ablation of liver tumours. CyberKnife and proton beam therapy (PBT) are two advanced treatment technologies suitable to deliver SBRT with high dose conformity and steep dose gradients. However, there is very limited data comparing the dosimetric characteristics of CyberKnife to PBT for liver SBRT. PBT and CyberKnife plans were retrospectively generated using 4DCT datasets of ten patients who were previously treated for hepatocellular carcinoma (HCC, N = 5) and liver metastasis (N = 5). Dose volume histogram data was assessed and compared against selected criteria; given a dose prescription of 54 Gy in 3 fractions for liver metastases and 45 Gy in 3 fractions for HCC, with previously published consensus-based normal tissue dose constraints. Comparison of evaluation parameters showed a statistically significant difference for target volume coverage and liver, lungs and spinal cord (p < 0.05) dose, while chest wall and skin did not indicate a significant difference between the two modalities. A number of optimal normal tissue constraints was violated by both the CyberKnife and proton plans for the same patients due to proximity of tumour to chest wall. PBT resulted in greater organ sparing, the extent of which was mainly dependent on tumour location. Tumours located on the liver periphery experienced the largest increase in organ sparing. Organ sparing for CyberKnife was comparable with PBT for small target volumes.

Inductive links represent a highly promising avenue for both powering and communicating medical implants. Yet they encounter challenges such as constrained communication distance and limited data rate. In Load Shift Keying (LSK), a switch in the secondary side of the inductive link can be placed in parallel with the load (Short-Circuit Technique - SCT), in series with the load (Open-Circuit Technique - OCT), or both (Dual Technique - DLT), to vary the impedance of the secondary. Hence, the impedance reflected to the primary side changes and is used to transmit information externally from the implant. Among these, DLT is a novel LSK technique proposed in this work, which becomes independent from the load on the implant side. This study compares these three methods, confronting measurements to simulations. The evaluation focused on variations in coil distance and load. The proposal is illustrated in the case of an implantable gastric stimulator, with specific constraints in secondary coil size and power requirements. The newly developed DLT consistently outshone SCT and OCT in extending the operational range of communication, registering a maximum modulation index of 0.797 and a bit error rate below 10^- 7 at an operating distance of 95 mm through the air. Its load-independent characteristic allowed DLT to surpass the performance of SCT and OCT, which were each advantageous under high and low loads, respectively. All these results are confirmed by a LTSpice simulation. Consequently, the communication techniques put forward in this work mark a significant progression in medical implant communications, enhancing coil-to-coil operational distance while adhering to a low carrier frequency.

High-density materials used for dental restorations are poorly defined in CT imaging due to scanner limitations. Studies have established that Eclipse offers poor agreement with delivered dose in situations involving high-density material. Defining the accuracy of dose algorithms in situations involving high-density overrides would improve clinical outcomes both for target coverage and OAR sparing. Dental amalgam was placed within a solid water phantom and measurements were taken at 1 cm increments beneath the amalgam down to a depth of 6 cm. Exposed film was compared with Eclipse Treatment Planning system (TPS) calculations on a CT of the experimental setup. The amalgam was overridden with a range of HU values and material selections for dose calculation. AXB performs poorly at describing depth dose downstream of Amalgam, regardless of the override material selected. Applying the known mass density with the Anisotropic Analytical Algorithm (AAA) predicts an average of 1.8% and 2.8% for 6 MV and 10 MV beams. The closest agreement achieved using the Acuros XB (AXB) was overriding with stainless steel, which predicted approximately 1.1% and 1.8% above measured dose for 6 MV and 10 MV respectively. Without overriding the density of amalgam, AAA and AXB return depth dose predictions of 7.3% and 5.8% above film measurement for a 6 MV and 7.6% and 6.5% for 10 MV static beams. Applying override options to a clinical case using an anthropomorphic phantom showed using AXB with Stainless Steel as amalgam override returns the same results as AAA with mass density applied for amalgam. Both of these were in close agreement to the TPS.

Point-spread-function (PSF) correction is not recommended for amyloid PET images due to Gibbs artifacts. Q.Clear™, a Bayesian Penalized Likelihood (BPL) reconstruction method without incorporating PSF correction reduces these artifacts but degrades image contrast by our previous findings. The present study aimed to recover lost contrast by optimizing reconstruction parameters in time-of-flight (TOF) BPL reconstruction of amyloid PET images without PSF correction. We selected candidate conditions based on a phantom study and then determined which were optimal in a clinical study. Phantom images were reconstructed under conditions of 1‒9 iterations, β 300-1000 and γ factors from 2 to 10 in TOF-BPL without PSF correction. We evaluated the %contrast and the coefficients of variation (CV, %). Standardized uptake value ratios (SUVr) and Centiloid scales (CL) were calculated from PET images acquired from 71 participants after an [¹⁸F]flutemetamol injection. Both %contrast and CV were independent of iterations, whereas a trade-off was found between γ factors and β. We selected a γ factors of 5 without PSF correction (iterations, 1; β, 500) and of 10 without PSF correction (iterations, 1; β, 800) as candidates for clinical investigation. The SUVr and CL remained stable across various conditions, and CL scales effectively discriminated amyloid PET using measured values. The optimal reconstruction parameters of TOF-BPL for [¹⁸F]flutemetamol PET images were γ factor 10, iterations 1 and β 800, without PSF correction.

The gamma probe is a commonly used detector for localizing sentinel lymph nodes after the injection of radiopharmaceuticals. In recent years, studies have focused on improving the features of gamma probes to achieve more consistent localization of the radiotracer uptake. As part of this effort, a novel gamma probe prototype based on an active shielding was developed, and its characteristics, including sensitivity, resolution and shielding effectiveness, were determined. The prototype integrates trapezoidal-shaped bismuth germanate (BGO) array coupled with a silicon photomultiplier (SiPM) array, accompanied by dedicated electronics and software for stand alone usage. We conducted a thorough characterization, validating experimental observations through Monte Carlo simulations using the GEANT4 simulation package. In scattering environment, with a probe-source distance of 30 mm, the experimental results show that the detector sensitivity is $120\pm 5$ cps/MBq, and the spatial and angular resolutions, in terms of full width at half maximum (FWHM), are $44.8\pm 1.3$ mm and $87.3\pm 1.5^{\circ }$ , respectively. The shielding effectiveness of the probe was determined to be greater than 95 $\%$ . The prototype with active shielding was found to have comparable performance to conventional gamma probes.

This study aimed to identify potential anatomical variation triggers using magnetic resonance imaging for plan adaption of cervical cancer patients to ensure dose requirements were met over an external beam radiotherapy course. Magnetic resonance images (MRIs) acquired before and during treatment were rigidly registered to a pre-treatment computerised tomography (CT) image for 11 retrospective cervix cancer datasets. Target volumes (TVs) and organs at risk (OARs) were delineated on both MRIs and propagated onto the CT. Treatment plans were generated based on the pre-treatment contours and applied to the mid-treatment contours. Anatomical and dosimetric changes between each timepoint were assessed. The anatomical changes included the change in centroid position and volume size. Dosimetric changes included the V30Gy and V40Gy for the OARs, and V95%, V100%, D95% and D98% for the TVs. Correlation with dosimetric and anatomical changes were assessed to determine potential replan triggers. Changes in the bowel volume and position in the superior-inferior direction, and the high-risk CTV anterior posterior position were highly correlated with a change in dose to the bowel and target, respectively. Hence changes in bowel and high-risk CTV could be used as a potential replan triggers.

Impedance cardiography (ICG) plays a crucial role in clinically evaluating cardiac systolic and diastolic functions, along with various other cardiac parameters. However, its accuracy heavily depends on precisely identifying feature points reflecting cardiac function. Moreover, traditional signal processing techniques used to mitigate random noise and breathing artifacts may inadvertently distort the amplitude and temporal characteristics of ICG signals. To address this issue, this study investigates a noise and artifact elimination method based on Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) and Particle Swarm Optimization-based Variational Mode Decomposition Algorithm (PSO-VMD). The goal is to preserve the amplitude and temporal features of ICG signals to ensure accurate feature point extraction and computation of associated cardiac parameters. Comparative analysis with signal processing methods employing various wavelet families and Ensemble Empirical Mode Decomposition (EEMD) in ICG signal processing applications reveals that the proposed method achieves superior signal-to-noise ratio (SNR) and lower root-mean-square error (RMSE), while demonstrating enhanced correlation and waveform consistency with the original signal.

Intensity-modulated radiation therapy (IMRT) has been widely used in treating head and neck tumors. However, due to the complex anatomical structures in the head and neck region, it is challenging for the plan optimizer to rapidly generate clinically acceptable IMRT treatment plans. A novel deep learning multi-scale Transformer (MST) model was developed in the current study aiming to accelerate the IMRT planning for head and neck tumors while generating more precise prediction of the voxel-level dose distribution. The proposed end-to-end MST model employs the shunted Transformer to capture multi-scale features and learn a global dependency, and utilizes 3D deformable convolution bottleneck blocks to extract shape-aware feature and compensate the loss of spatial information in the patch merging layers. Moreover, data augmentation and self-knowledge distillation are used to further improve the prediction performance of the model. The MST model was trained and evaluated on the OpenKBP Challenge dataset. Its prediction accuracy was compared with three previous dose prediction models: C3D, TrDosePred, and TSNet. The predicted dose distributions of our proposed MST model in the tumor region are closest to the original clinical dose distribution. The MST model achieves the dose score of 2.23 Gy and the DVH score of 1.34 Gy on the test dataset, outperforming the other three models by 8%-17%. For clinical-related DVH dosimetric metrics, the prediction accuracy in terms of mean absolute error (MAE) is 2.04% for $D_{99}$ , 1.54% for $D_{95}$ , 1.87% for $D_1$ , 1.87% for $D_{\mathrm{mean}}$ , 1.89% for $D_{0.1cc}$ , respectively, superior to the other three models. The quantitative results demonstrated that the proposed MST model achieved more accurate voxel-level dose prediction than the previous models for head and neck tumors. The MST model has a great potential to be applied to other disease sites to further improve the quality and efficiency of radiotherapy planning.