Physical and Engineering Sciences in Medicine最新文献

The treatment, planning, simulation, and setup of radiotherapy patients contain many processes subject to errors involving both staff and equipment. Cone-beam-CT (CBCT) provides a final check of patient positioning and corrections based on this can be made prior to treatment delivery. Statistical Process Control (SPC) techniques are used in various industries for quality management and error mitigation. The utility of SPC techniques to monitor process and equipment changes in our Head and Neck patient treatments was assessed by application to CBCT results from a quality-focused longitudinal study. Individuals and moving range (XmR) as well as exponentially-weighted moving average (EWMA) techniques were explored. The SPC techniques were sensitive to process changes and trends over the 12 years of data collected. A reduction in the random component of patient setup errors needing correction was observed. Systematic components of error remained more stable. An uptick in both datasets was observed correlating with the COVID-19 pandemic. Process control limits for use in prospective process monitoring were established. Challenges that arose from using SPC techniques in a retrospective study are outlined.

In the realm of high-intensity focused ultrasound (HIFU) therapy, the precise prediction of lesion size during treatment planning remains a challenge, primarily due to the difficulty in quantitatively assessing energy deposition at the target site and the acoustic properties of the tissue through which the ultrasound wave propagates. This study investigates the hypothesis that the echo amplitude originating from the focus is indicative of acoustic attenuation and is directly related to the resultant lesion size. Echoes from multi-layered tissues, specifically porcine tenderloin and bovine livers, with varying fat thickness from 0 mm to 35 mm were collected using a focused ultrasound (FUS) transducer operated at a low power output and short duration. Subsequent to HIFU treatment under clinical conditions, the resulting lesion areas in the ex vivo tissues were meticulously quantified. A novel treatment strategy that prioritizes treatment spots based on descending echo amplitudes was proposed and compared with the conventional raster scan approach. Our findings reveal a consistent trend of decreasing echo amplitudes and HIFU-induced lesion areas with the increasing fat thickness. For porcine tenderloin, the values decreased from 2541.7 ± 641.9 mV and 94.4 ± 17.9 mm² to 385(342.5) mV and 24.9 ± 18.7 mm², and for bovine liver, from 1406(1202.5) mV and 94.4 ± 17.9 mm² to 502.1 ± 225.7 mV and 9.4 ± 6.3 mm², respectively, as the fat thickness increases from 0 mm to 35 mm. Significant correlations were identified between preoperative echo amplitudes and the HIFU-induced lesion areas (R = 0.833 and 0.784 for the porcine tenderloin and bovine liver, respectively). These correlations underscore the potential for an accurate and dependable prediction of treatment outcomes. Employing the proposed treatment strategy, the ex vivo experiment yielded larger lesion areas in bovine liver at a penetration depth of 8 cm compared to the conventional approach (58.84 ± 17.16 mm² vs. 44.28 ± 15.37 mm², p < 0.05). The preoperative echo amplitude from the FUS transducer is shown to be a reflective measure of acoustic attenuation within the wave propagation window and is closely correlated with the induced lesion areas. The proposed treatment strategy demonstrated enhanced efficiency in ex vivo settings, affirming the feasibility and accuracy of predicting HIFU-induced lesion size based on echo amplitude.

Particle (proton, carbon ion, or others) radiotherapy for ocular tumors is highly dependent on precise dose distribution, and any misalignment can result in severe complications. The proposed eye positioning and tracking system (EPTS) was designed to non-invasively position eyeballs and is reproducible enough to ensure accurate dose distribution by guiding gaze direction and tracking eye motion. Eye positioning was performed by guiding the gaze direction with separately controlled light sources. Eye tracking was performed by a robotic arm with cameras and a mirror. The cameras attached to its end received images through mirror reflection. To maintain a light weight, certain materials, such as carbon fiber, were utilized where possible. The robotic arm was controlled by a robot operating system. The robotic arm, turntables, and light source were actively and remotely controlled in real time. The videos captured by the cameras could be annotated, saved, and loaded into software. The available range of gaze guidance is 360° (azimuth). Weighing a total of 18.55 kg, the EPTS could be installed or uninstalled in 10 s. The structure, motion, and electromagnetic compatibility were verified via experiments. The EPTS shows some potential due to its non-invasive wide-range flexible eye positioning and tracking, light weight, non-collision with other equipment, and compatibility with CT imaging and dose delivery. The EPTS can also be remotely controlled in real time and offers sufficient reproducibility. This system is expected to have a positive impact on ocular particle radiotherapy.

Immunotherapy is a rapidly evolving field, with many models attempting to describe its impact on the immune system, especially when paired with radiotherapy. Tumor response to this combination involves a complex spatiotemporal dynamic which makes either clinical or pre-clinical in vivo investigation across the resulting extensive solution space extremely difficult. In this review, several in silico models of the interaction between radiotherapy, immunotherapy, and the patient's immune system are examined. The study included only mathematical models published in English that investigated the effects of radiotherapy on the immune system, or the effect of immuno-radiotherapy with immune checkpoint inhibitors. The findings indicate that treatment efficacy was predicted to improve when both radiotherapy and immunotherapy were administered, compared to radiotherapy or immunotherapy alone. However, the models do not agree on the optimal schedule and fractionation of radiotherapy and immunotherapy. This corresponds to relevant clinical trials, which report an improved treatment efficacy with combination therapy, however, the optimal scheduling varies between clinical trials. This discrepancy between the models can be attributed to the variation in model approach and the specific cancer types modeled, making the determination of the optimum general treatment schedule and model challenging. Further research needs to be conducted with similar data sets to evaluate the best model and treatment schedule for a specific cancer type and stage.

The stability of dosiomics features (DFs) and dose-volume histogram (DVH) parameters for detecting disparities in helical tomotherapy planned dose distributions was assessed. Treatment plans of 18 prostate patients were recalculated using the followings: field width (WF) (2.5 vs. 5), pitch factor (PF) (0.433 vs. 0.444), and modulation factor (MF) (2.5 vs. 3). From each of the eight plans per patient, ninety-three original and 744 wavelet-based DFs were extracted, using 3D-Slicer software, across six regions including: target volume (PTV), pelvic lymph nodes (PTV-LN), PTV + PTV-LN (PTV-All), one cm rind around PTV-All (PTV-Ring), rectum, and bladder. For the resulting DFs and DVH parameters, the coefficient of variation (CV) was calculated, and using hierarchical clustering, the features were classified into low/high variability. The significance of parameters on instability was analyzed by a three-way analysis of variance. All DF's were stable in PTV, PTV-LN, and PTV-Ring (average CV ( $\overline{\mathrm{CV}})$  ≤ 0.36). Only one feature in the bladder ( $\overline{\mathrm{CV}}$  = 0.9), rectum ( $\overline{\mathrm{CV}}$  = 0.4), and PTV-All ( $\overline{\mathrm{CV}}$  = 0.37) were considered unstable due to change in MF in the bladder and WF in the PTV-All. The value of $\overline{\mathrm{CV}}$ for the wavelet features was much higher than that for the original features. Out of 225 unstable wavelet features, 84 features had $\overline{\mathrm{CV}}$  ≥ 1. The CVs for all the DVHs remained very small ( $\overline{\mathrm{CV}}$ < 0.06). This study highlights that the sensitivity of DFs to changes in tomotherapy planning parameters is influenced by the region and the DFs, particularly wavelet features, surpassing the effectiveness of DVHs.

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.

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.

In this paper, we proposed a complete study method to achieve accurate aortic dissection diagnosis at the patient level. Based on the CT angiography (CTA) images, a classification model named DAT-DenseNet, which combined the deep attention Transformer module with the DenseNet architecture is proposed. In the first phase, two DAT-DenseNet are combined in parallel. It is used to accurately achieve two classification task at the CTA images. In the second stage, we propose a feature fusion module. It concatenates and fuses the image features output from the two classification models on a patient by patient basis. In the comparison experiments of classification model performance, DAT-DenseNet obtained 92.41 $\%$ accuracy at the image level, which was 2.20 $\%$ higher than the commonly used model. In the comparison experiments of model fusion method, our method obtained 90.83 $\%$ accuracy at the patient level. The experiments showed that DAT-DenseNet model exhibits high performance at the image level. Our feature fusion module achieves the mapping from two classification image features to patient outcomes. It achieves accurate patient classification. The experiments' results in the Discussion section elaborate the details of the experiment and confirmed that the results were reliable.

A fundamental parameter to evaluate the beam delivery precision and stability on a clinical linear accelerator (linac) is the focal spot position (FSP) measured relative to the collimator axis of the radiation head. The aims of this work were to evaluate comprehensive data on FSP acquired on linacs in clinical use and to establish the ability of alternative phantoms to detect effects on patient plan delivery related to FSP. FSP measurements were conducted using a rigid phantom holding two ball-bearings at two different distances from the radiation source. Images of these ball-bearings were acquired using the electronic portal imaging device (EPID) integrated with each linac. Machine QA was assessed using a radiation head-mounted PTW STARCHECK phantom. Patient plan QA was investigated using the SNC ArcCHECK phantom positioned on the treatment couch, irradiated with VMAT plans across a complete 360° gantry rotation and three X-ray energies. This study covered eight Elekta linacs, including those with 6 MV, 18 MV, and 6 MV flattening-filter-free (FFF) beams. The largest range in the FSP was found for 6 MV FFF. The FSP of one linac, retrofitted with 6 MV FFF, displayed substantial differences in FSP compared to 6 MV FFF beams on other linacs, which all had FSP ranges less than 0.50 mm and 0.25 mm in the lateral and longitudinal directions, respectively. The PTW STARCHECK phantom proved effective in characterising the FSP, while the SNC ArcCHECK measurements could not discern FSP-related features. Minor variations in FSP may be attributed to adjustments in linac parameters, component replacements necessary for beam delivery, and the wear and tear of various linac components, including the magnetron and gun filament. Consideration should be given to the ability of any particular phantom to detect a subsequent impact on the accuracy of patient plan delivery.

A need exists for a quick, simple method to accurately assess resection margins and lymph node metastases in gastrointestinal cancer surgeries. We aimed to develop a real-time, non-destructive technique to differentiate between normal and cancerous tissues using dielectric properties. Dielectric properties of tissues from 50 gastric and 120 colorectal cancer patients were measured during surgery using an open-ended coaxial probe, spanning frequencies from 10 MHz to 4 GHz. Lymph nodes were classified based on pathology into metastatic and non-metastatic, and tissues were divided into cancerous and normal, the latter being 3 cm from the cancer edge. Statistically significant differences in dielectric properties were found between metastatic and non-metastatic lymph nodes (P < 0.05), and between normal and malignant tissues. Metastatic lymph nodes showed higher dielectric permittivity and conductivity across the frequency range, with no significant difference between gastric and colorectal cancers. The coaxial probe method distinguishes between metastatic and non-metastatic lymph nodes by their dielectric properties within 10-4000 MHz, offering a potential tool for real-time identification of malignant tissues during surgery, despite not identifying the cancer type.