Physics in medicine and biology最新文献

Objective.Among various deep-network-based sparse-view CT image reconstruction studies, the sinogram upscaling network has been predominantly employed to synthesize additional view information. However, the performance of the sinogram-based network is limited in terms of removing aliasing streak artifacts and recovering low-contrast small structures. In this study, we used a view-by-view back-projection (VVBP) tensor-domain network to overcome such limitations of the sinogram-based approaches.Approach.The proposed method offers advantages of addressing the aliasing artifacts directly in the 3D tensor domain over the 2D sinogram. In the tensor-domain network, the multi-planal anti-aliasing modules were used to remove artifacts within the coronal and sagittal tensor planes. In addition, the data-fidelity-based refinement module was also implemented to successively process output images of the tensor network to recover image sharpness and textures.Main result.The proposed method showed outperformance in terms of removing aliasing artifacts and recovering low-contrast details compared to other state-of-the-art sinogram-based networks. The performance was validated for both numerical and clinical projection data in a circular fan-beam CT configuration.Significance.We observed that view-by-view aliasing artifacts in sparse-view CT exhibit distinct patterns within the tensor planes, making them effectively removable in high-dimensional representations. Additionally, we demonstrated that the co-domain characteristics of tensor space processing offer higher generalization performance for aliasing artifact removal compared to conventional sinogram-domain processing.

Purpose.Cherenkov imaging during radiotherapy provides a real time visualization of beam delivery on patient tissue, which can be used dynamically for incident detection or to review a summary of the delivered surface signal for treatment verification. Very few photons form the images, and one limitation is that the noise level per frame can be quite high, and mottle in the cumulative processed images can cause mild overall noise. This work focused on removing or suppressing noise via image postprocessing.Approach.Images were analyzed for peak-signal-to-noise and spatial frequencies present, and several established noise/mottle reduction algorithms were chosen based upon these observations. These included total variation minimization (TV-L1), non-local means filter (NLM), block-matching 3D (BM3D), alpha (adaptive) trimmed mean (ATM), and bilateral filtering. Each were applied to images acquired using a BeamSite camera (DoseOptics) imaged signal from 6x photons from a TrueBeam linac delivering dose at 600 MU min^-1incident on an anthropomorphic phantom and tissue slab phantom in various configurations and beam angles. The standard denoised images were tested for PSNR, noise power spectrum (NPS) and image sharpness.Results.The average peak-signal-to-noise ratio (PSNR) increase was 17.4% for TV-L1. NLM denoising increased the average PSNR by 19.1%, BM3D processing increased it by12.1% and the bilateral filter increased the average PSNR by 19.0%. Lastly, the ATM filter resulted in the lowest average PSNR increase of 10.9%. Of all of these, the NLM and bilateral filters produced improved edge sharpness with, generally, the lowest NPS curve.Conclusion.For cumulative image Cherenkov data, NLM and the bilateral filter yielded optimal denoising with the TV-L1 algorithm giving comparable results. Single video frame Cherenkov images exhibit much higher noise levels compared to cumulative images. Noise suppression algorithms for these frame rates will likely be a different processing pipeline involving these filters incorporated with machine learning.

Objective.To assess the accuracy and stability of areal bone-mineral-density (aBMD) measurements from multi-energy CT localizer radiographs acquired using photon-counting detector (PCD) CT.Approach.A European Spine Phantom (ESP) with hydroxyapatite (HA 0.5, 1.0 and 1.5 g cm^-2) was scanned using clinical PCD-CT and a dual-energy x-ray absorptiometry (DXA) to compare aBMD values. To assess aBMD stability and reproducibility, PCD-localizers were acquired twice a day for one week, and once per week for five weeks. Multiple ESP anteroposterior thicknesses (18, 26, 34, and 40 cm) were achieved using a synthetic gel layer and scanned across eight tube current values for both 120 kV (15-120 mA) and 140 kV (10-80 mA). One-way analysis of variance was performed for statistical significance (p< 0.05 considered significant). Quantitative HA and water maps were reconstructed using a prototype material-decomposition software, and aBMD was calculated after background correction.In vivoperformance of PCD-based aBMD was illustrated using a patient scan acquired at 140 kV and 40 mA, and lumbar aBMD values were compared with DXA.Main results.The ESP aBMD values from PCD-localizers demonstrated excellent day-to-day stability with a coefficient-of-variation ranging from 0.42% to 0.53%, with mean absolute percentage errors (MAPE) of less than 5% for all three vertebral bodies. The coefficient-of-variation for weekly scans ranged from 0.17% to 0.60%, again with MAPE below 5% for all three vertebral bodies. Across phantom sizes and tube currents, the MAPE values varied ranging from 1.84% to 13.78% for 120 kV, and 1.38%-9.11% for 140 kV. No significant difference was found between different tube currents. For the standard phantom size, DXA showed 11.21% MAPE whereas PCD-CT showed 3.04% MAPE. For the patient scan, deviation between PCD-based aBMD values and those obtained from DXA ranged from 0.07% to 9.82% for different lumbar vertebra.Significance.This study highlights the accuracy and stability of PCD-CT localizers for measuring aBMD. We demonstrated aBMD accuracy across different sizes and showed that higher radiation doses did not inherently increase aBMD accuracy.

Objective.Radial cine-MRI allows for sliding window reconstruction at nearly arbitrary frame rate, promising high-speed imaging for intra-fractional motion monitoring in magnetic resonance guided radiotherapy. However, motion within the reconstruction window may determine the location of the reconstructed target to deviate from the true real-time position (target positioning errors), particularly in cases of fast breathing or for anatomical structures affected by the heartbeat. In this work, we present a proof-of-concept study aiming to enhance radial cine-MR imaging by implementing deep-learning-based intra-frame motion compensation techniques.Approach.A novel network (TransSin-UNet) was proposed to continuously estimate the final-position image of the target, corresponding to end of the frame acquisition. Within the radial k-space reconstruction window, the spatial-temporal dependencies among the sinogram representation of the spokes were modeled by a transformer encoder subnetwork, followed by a UNet subnetwork operating in the spatial domain for pixel-level fine-tuning. By simulating motion-dependent radial sampling with (tiny) golden angles, we generated datasets from 25 4D digital anthropomorphic lung cancer phantoms. The network was then trained and extensively evaluated across datasets characterized by varying azimuthal radial profile increments.Main Results.The method required additional 4.8 ms per frame over the conventional approach involving direct image reconstruction with motion-corrupted spokes. TransSin-UNet outperformed architectures relying solely on transformer encoders or UNets across all the comparative evaluations, leading to a noticeable enhancement in image quality and target positioning accuracy. The normalized root mean-squared error decreased by 50% from the initial value of 0.188 on average, whereas the mean Dice similarity coefficient of the gross tumor volume increased from 85.1% to 96.2% in the investigated cases. Furthermore, the final-positions of anatomical structures undergoing substantial intra-frame deformations were precisely derived.Significance.The proposed approach enables an effective intra-frame motion compensation, offering an opportunity to reduce errors in radial cine-MR imaging for real-time motion management.

A 750 kHz, 360-element ultrasound array has been built for transcranial histotripsy applications. This study aims to evaluate its performance to determine whether this array is adequate for treating a wide range of brain locations through a human skull. Treatment location profiles in 2 excised human skulls were experimentally characterized based on passive cavitation mapping. Full-wave acoustic simulations were performed in 8 human skulls to analyze the ultrasound propagation at shallow targets in skulls with different properties. Results showed that histotripsy successfully generated cavitation from deep to shallow targets within 5 mm from the skull surface in the skull with high SDR and small thickness, whereas in the skull with low SDR and large thickness, the treatment envelope was limited up to 16 mm from the skull surface. Simulation results demonstrated that the treatment envelope was highly dependent on the skull acoustic properties. Pre-focal pressure hotspots were observed in both simulation and experiments when targeting near the skull. For each skull, the acoustic pressure loss increases significantly for shallow targets compared to central targets due to high attenuation, large incident angles, and pre-focal pressure hotspots. Strategies including array design optimization, pose optimization, and amplitude correction, are proposed to broaden the treatment envelope. This study identifies the capabilities and limitations of the 360-element transcranial histotripsy array and suggests strategies for designing the next-generation transcranial histotripsy array to expand the treatment location profile for a future clinical trial.

Objective. Bragg peak measurements play a key role in the beam quality assurance in proton therapy. Used as base data for the treatment planning softwares, the accuracy of the data is crucial when defining the range of the protons in the patient.Approach. In this paper a protocol to reconstruct a Pristine Bragg Peak exploring the direct correlation between the particle flux and the dose deposited by particles is presented. Proton flux measurements at the HollandPTC and FLUKA Monte Carlo simulations are used for this purpose. This new protocol is applicable to plastic scintillator detectors developed for Quality Assurance applications. In order to obtain the Bragg curve using a plastic fiber detector, a PMMA phantom with a decoupled and moveable stepper was designed. The step phantom allows to change the depth of material in front of the fiber detector during irradiations. The Pristine Bragg Peak reconstruction protocol uses the measured flux of particles at each position and multiplies it by the average dose obtained from the Monte Carlo simulation at each position.Main results. The results show that with this protocol it is possible to reconstruct the Bragg Peak with an accuracy of about 470µm, which is in accordance with the tolerances set by the AAPM.Significance. It has the advantage to be able to overcome the quenching problem of scintillators in the high ionization density region of the Bragg peak.

Objective. Image-guided and adaptive proton therapy rely on daily CBCT or CT imaging, which increases radiation dose and radiation-induced cancer risk. Online adaptation however also reduces setup uncertainty, and the additional risk might be compensated by reducing the setup robustness margin. This work developed a framework to investigate how much this robustness margin should be reduced to offset the secondary cancer risk from additional imaging dose and applied it to proton therapy for head-and-neck cancer.Approach. For five patients with head-and-neck cancer, voxel-wise CT and CBCT imaging doses were estimated with Monte Carlo radiation transport simulations, calibrated with air and PMMA phantom measurements. The total dose of several image-guided and adaptive treatments protocols was calculated by summing the planning CT dose, daily and weekly CBCT or CT dose, and therapy dose, robustly optimized with setup margins between 0 and 4 mm. These were compared to a reference protocol with 4 mm setup margin without daily imaging. All plans further used 3% range robustness. Organ-wise excess absolute risk (EAR) of cancer was calculated with three models to determine at which setup margin the total EAR of image-guided and adaptive treatment protocols was equal to the total EAR of the reference.Results. The difference between the simulated and measured CT and CBCT doses was within 10%. Using the Monte Carlo models, we found that a 1 mm setup margin reduction was sufficient for most patients, treatment protocols, and cancer risk models to compensate the additional risk imposed by daily and weekly imaging. For some protocols, even a smaller reduction sufficed, depending on the imaging frequency and type. The risk reduction by reducing the margin was mainly due to reducing the risk for carcinomas in the brain and, for some patients, the oral cavity.Significance. Our framework allows to compare an increased imaging dose with the reduced treatment dose from margin reductions in terms of radiation-induced cancer risk. It is extendable to different treatment sites, modalities, and imaging protocols, in clinic-specific or even patient-specific assessments.

Objective.Deep learning (DL) is becoming increasingly important in generating attenuation maps for accurate attenuation correction (AC) in cardiac perfusion SPECT imaging. Typically, DL models take inputs from initial reconstructed SPECT images, which are performed on the photopeak window and often also on scatter windows. While prior studies have demonstrated improvements in DL performance when scatter window images are incorporated into the DL input, the comprehensive analysis of the impact of employing different scatter windows remains unassessed. Additionally, existing research mainly focuses on applying DL to SPECT scans obtained at clinical standard count levels. This study aimed to assess utilities of DL from two aspects: (1) investigating the impact when different scatter windows were used as input to DL, and (2) evaluating the performance of DL when applied on SPECT scans acquired at a reduced count level.Approach.We utilized 1517 subjects, with 386 subjects for testing and the remaining 1131 for training and validation.Main results.The results showed that as scatter window width increased from 4% to 30%, a slight improvement was observed in DL estimated attenuation maps. The application of DL models to quarter-count (¼-count) SPECT scans, compared to full-count scans, showed a slight reduction in performance. Nonetheless, discrepancies across different scatter window configurations and between count levels were minimal, with all normalized mean square error (NMSE) values remaining within 2.1% when comparing the different DL attenuation maps to the reference CT maps. For attenuation corrected SPECT slices using DL estimated maps, NMSE values were within 0.5% when compared to CT correction.Significance.This study, leveraging an extensive clinical dataset, showed that the performance of DL seemed to be consistent across the use of varied scatter window settings. Moreover, our investigation into reduced count studies indicated that DL could provide accurate AC even at a ¼-count level.

Cone beam CT is integral to most modern radiotherapy treatments. The application of daily and repeat CBCT imaging can lead to high imaging doses over a large volume of tissue that extends beyond the treatment site. Hence, it is important to ensure exposures are optimised to keep doses as low as reasonably achievable, whilst ensuring images are suitable for the clinical task. This IPEM topical report presents the results of the first UK survey of dose indices in radiotherapy CBCT. Dose measurements, as defined by the cone beam dose index (CBDI_w), were collected along with protocol information for seven treatment sites. Where a range of optimised protocols were available in a centre, a sample of patient data demonstrating the variation in protocol use were requested. Protocol CBDI_wvalues were determined from the average dosimetry data for each type of linear accelerator, and median CBDI_wand scan length were calculated for each treatment site at each centre. Median CBDI_wvalues were compared and summary statistics derived that enable the setting of national dose reference levels (DRLs). A total of 63 UK radiotherapy centres contributed data. The proposed CBDI_wDRLs are; prostate 20.6 mGy, gynaecological 20.8 mGy, breast 5.0 mGy, 3D-lung 6.0 mGy, 4D-lung 11.8 mGy, brain 3.5 mGy and head/neck 4.2 mGy. However, large differences between models of imaging system were noted. Where centres had pro-active optimisation strategies in place, such as sized based protocols with selection criteria, dose reductions on the 'average' patient were possible compared with vendor defaults. Optimisation of scan length was noted in some clinical sites, with Elekta users tending to fit different collimators for prostate imaging (relatively short) compared with gynaecological treatments (longest). This contrasts with most Varian users who apply the default scan length in most cases.

Objective.The highly conformal carbon-ion radiotherapy is associated with an increased sensitivity of the dose distributions to internal changes in the patient during the treatment course. Hence, monitoring methodologies capable of detecting such changes are of vital importance. We established experimental setup conditions to address the sensitivity of a monitoring approach based on secondary-fragment tracking for detecting clinically motivated air cavity dimensions in a homogeneous head-sized PMMA phantom in 40 mm depth.Approach.The air cavities were positioned within the entrance channel of a treatment field of 50 mm diameter at three lateral positions. The measured secondary-fragment emission profiles were compared to a reference measurement without cavities. The experiments were conducted at the Heidelberg Ion-Beam Therapy Center in Germany at typical doses and dose rates.Main results.Significances above a detectability threshold of 2σfor the larger cavities (20 mm diameter and 4 mm thickness, and 20 mm diameter and 2 mm thickness) across the entire treatment field. The smallest cavity of 10 mm diameter and 2 mm thickness, which is on the lower limit of clinical interest, could not be detected at any position. We also demonstrated that it is feasible to reconstruct the lateral position of the cavity on average within 2.8 mm, once the cavity is detected. This is sufficient for the clinicians to estimate medical effects of such a cavity and to decide about the need for a control imaging CT.Significance.This investigation defines well-controlled reference conditions for the evaluation of the performance of any kind of treatment monitoring method and its capability to detect internal changes within head-sized objects. Four air cavities with volumes between 0.31 cm³and 1.26 cm³were narrowed down around the detectability threshold of this secondary-fragment-based monitoring method.