Inhomogeneity Correction Research Articles

Relationship between Dose Prescription Methods and Local Control Rate in Stereotactic Body Radiotherapy for Early Stage Non-Small-Cell Lung Cancer: Systematic Review and Meta-Analysis.

Simple SummaryStereotactic body radiotherapy (SBRT) is a standard treatment for inoperable early stage non-small-cell lung cancer (ES-NSCLC), and good local control and low toxicity rates have been reported. However, the optimal dose prescription method remains unclear. Variations in dose prescription methods make it difficult to properly compare the outcomes of SBRT for ES-NSCLC with those of previously published studies. Therefore, in this study, we conducted a comprehensive search of the published literature on the therapeutic results of SBRT for ES-NSCLC to summarize the results and clarify the relationship between LC and dose prescription methods. In our results, the central biologically effective dose of the planning target volume was most correlated with 3-year local control rates. A comparison against a standardized central biologically effective dose would show more definite outcomes of SBRT for ES-NSCLC and would help to strengthen its use in the treatment for ES-NSCLC.Variations in dose prescription methods in stereotactic body radiotherapy (SBRT) for early stage non-small-cell lung cancer (ES-NSCLC) make it difficult to properly compare the outcomes of published studies. We conducted a comprehensive search of the published literature to summarize the outcomes by discerning the relationship between local control (LC) and dose prescription sites. We systematically searched PubMed to identify observational studies reporting LC after SBRT for peripheral ES-NSCLC. The correlations between LC and four types of biologically effective doses (BED) were evaluated, which were calculated from nominal, central, and peripheral prescription points and, from those, the average BED. To evaluate information on SBRT for peripheral ES-NSCLC, 188 studies were analyzed. The number of relevant articles increased over time. The use of an inhomogeneity correction was mentioned in less than half of the articles, even among the most recent. To evaluate the relationship between the four BEDs and LC, 33 studies were analyzed. Univariate meta-regression revealed that only the central BED significantly correlated with the 3-year LC of SBRT for ES-NSCLC (p = 0.03). As a limitation, tumor volume, which might affect the results of this study, could not be considered due to a lack of data. In conclusion, the central dose prescription is appropriate for evaluating the correlation between the dose and LC of SBRT for ES-NSCLC. The standardization of SBRT dose prescriptions is desirable.

Uniting Nonempirical and Empirical Density Functional Approximation Strategies Using Constraint-Based Regularization.

In this work, we present a general framework that unites the two primary strategies for constructing density functional approximations (DFAs): nonempirical (NE) constraint satisfaction and empirical (E) data-driven optimization. The proposed method employs B-splines, bell-shaped spline functions with compact support, to construct each inhomogeneity correction factor (ICF). This choice offers several distinct advantages over traditional polynomial expansions by enabling explicit enforcement of linear and nonlinear constraints as well as ICF smoothness using Tikhonov and penalized B-splines (P-splines) regularization. As proof-of-concept, we use the so-called CASE (constrained and smoothed empirical) framework to construct a constraint-satisfying and data-driven global hybrid that exhibits enhanced performance across a diverse set of chemical properties. We argue that the CASE approach can be used to generate DFAs that maintain the physical rigor and transferability of NE-DFAs while leveraging high-quality quantum-mechanical data to remove the arbitrariness of ansatz selection and improve performance.

Comparison of Dosimetric Parameters and Clinical Outcomes in Inversely Planned Intensity-Modulated Radiotherapy (IMRT) and Field-in-Field Forward Planned IMRT for the Treatment of Breast Cancer.

IntroductionRadiotherapy has been an important component of the multimodality approach to breast cancer treatment. Newer techniques like three-dimensional radiotherapy had led to better dose distribution over the target volume, with tissue inhomogeneity corrections. To improve the uniformity in dose distribution, a newer technique of intensity modulation was developed, namely, intensity-modulated radiotherapy (IMRT). The present study was designed to compare inverse planned IMRT (IP IMRT) and field-in-field forward planned IMRT (FP IMRT) in patients with breast cancer receiving post-modified radical mastectomy (MRM) adjuvant radiotherapy in terms of dosimetric parameters and clinical outcomes.Materials and methodsFifty patients with breast cancer who have undergone MRM and need adjuvant radiotherapy were randomly assigned in a 1:1 ratio into two groups (25 each) of IP IMRT and FP IMRT techniques. The prescribed dose was 50 Gy in 25 fractions over five weeks. In IP IMRT, five to seven tangential beams were used for the chest wall, nodal volumes were placed at suitable angles with beam optimization, and calculation was carried out by the analytical anisotropic algorithm. For FP IMRT, two opposing tangential fields were created in such a way to achieve uniform dose distribution to the planning target volume (PTV), minimizing hot spot regions, and limiting dose to the ipsilateral lung and contralateral breast. Multiple subfields were manually designed to boost the area not included in the dose cloud. The dosimetric parameters were compared for PTV, lungs, heart, left anterior descending coronary artery (LAD), opposite breast, and esophagus.ResultsThe dosimetric parameters in terms of PTV are better for IP IMRT plans compared to FP IMRT plans (V95%: 92.3% vs 75.2%, p = 0.0001; D90%: 47.4 Gy vs 42.9 Gy, p = 0.0001; D95%: 44.9 Gy vs 37.1, p = 0.0004). The ipsilateral lung (V10Gy: 71.9% vs 41%, p = 0.00001; V20Gy: 42.14% vs 36.35%, p = 0.03; V40Gy: 17.31% vs 26.95%, p = 0.00004; Dmean: 20.91 Gy vs 17.88 Gy, p = 0.01) and contralateral lung (V5Gy: 31.8% vs 0.1%, p < 0.00001; V10Gy: 6.2% vs 0.08%, p = 0.0001) received statistically significant lesser doses in terms of low dose parameters in FP IMRT. In the heart, the dosimetric parameter V5 was significantly lower for FP IMRT (61.7% vs 9.7%, p = 0.00001) along with Dmean (10.92 Gy vs 4.01 Gy, p = 0.001). Similarly, LAD parameters showed comparable high dose volumes (V40Gy: 21.02% vs 16.26%; p = 0.29) in both groups and a trend toward reduction in mean dose (17.1% vs 9.2%; p = 0.05) in FP IMRT group, although low dose volumes were higher in IP IMRT group. In contralateral breast, doses in smaller volumes were better for FP IMRT plans (V0.5Gy: 59.7% vs 43.8%, p = 0.01; V0.6Gy: 54.07% vs 37.6%, p = 0.007; V1Gy: 40.9% vs 22.1%, p = 0.001; V2Gy: 28.7% vs 9.4%, p = 0.00003; V5Gy: 12.07% vs 4.2%, p = 0.0001). In esophagus, statistically significant lower doses were seen only in terms of Dmean (10.29 Gy vs 5.1 Gy; p = 0.03) with FP IMRT. No significant difference in terms of skin reactions and dysphagia was seen in both the groups.ConclusionBoth IP IMRT and FP IMRT techniques have advantages and disadvantages, and the superiority of one technique over another cannot be established in this study. The decision for choosing one technique over another can also be based on various patient-related factors weighing the risk of loco-regional recurrences to that of manifesting radiation-induced sequelae.

Volume and surface coil simultaneous reception (VSSR) method for intensity inhomogeneity correction in MRI.

Addressing intensity inhomogeneity is critical in magnetic resonance imaging (MRI) because associated errors can adversely affect post-processing and quantitative analysis of images (i.e., segmentation, registration, etc.), as well as the accuracy of clinical diagnosis. Although several prior methods have been proposed to eliminate or correct intensity inhomogeneity, some significant disadvantages have remained, including alteration of tissue contrast, poor reliability and robustness of algorithms, and prolonged acquisition time. In this study, we propose an intensity inhomogeneity correction method based on volume and surface coils simultaneous reception (VSSR). The VSSR method comprises of two major steps: 1) simultaneous image acquisition from both volume and surface coils and 2) denoising of volume coil images and polynomial surface fitting of bias field. Extensive in vivo experiments were performed considering various anatomical structures, acquisition sequences, imaging resolutions, and orientations. In terms of correction performance, the proposed VSSR method was comparatively evaluated against several popular methods, including multiplicative intrinsic component optimization and improved nonparametric nonuniform intensity normalization bias correction methods. Experimental results show that VSSR is more robust and reliable and does not require prolonged acquisition time with the volume coil. The VSSR may be considered suitable for general implementation.

Deep learning network for integrated coil inhomogeneity correction and brain extraction of mixed MRI data

Magnetic Resonance Imaging (MRI) has been widely used to acquire structural and functional information about the brain. In a group- or voxel-wise analysis, it is essential to correct the bias field of the radiofrequency coil and to extract the brain for accurate registration to the brain template. Although automatic methods have been developed, manual editing is still required, particularly for echo-planar imaging (EPI) due to its lower spatial resolution and larger geometric distortion. The needs of user interventions slow down data processing and lead to variable results between operators. Deep learning networks have been successfully used for automatic postprocessing. However, most networks are only designed for a specific processing and/or single image contrast (e.g., spin-echo or gradient-echo). This limitation markedly restricts the application and generalization of deep learning tools. To address these limitations, we developed a deep learning network based on the generative adversarial net (GAN) to automatically correct coil inhomogeneity and extract the brain from both spin- and gradient-echo EPI without user intervention. Using various quantitative indices, we show that this method achieved high similarity to the reference target and performed consistently across datasets acquired from rodents. These results highlight the potential of deep networks to integrate different postprocessing methods and adapt to different image contrasts. The use of the same network to process multimodality data would be a critical step toward a fully automatic postprocessing pipeline that could facilitate the analysis of large datasets with high consistency.

PO-1630 An analytic method for inhomogeneity correction of Gafchromic EBT3 films

PO-1630 An analytic method for inhomogeneity correction of Gafchromic EBT3 films

Effect of CT number to relative electron density curves acquired at different tube voltage and current on radiotherapy dose calculation

Computed tomography (CT) images contain information of relative electron density (RED) of tissues in terms of CT numbers and hence are utilized for tissue inhomogeneity corrections in radiotherapy dose calculations. The present study has determined the effect of tube voltage and current on CT number to RED calibration (CT sensitometry) curves. Catphan phantom containing materials of REDs from 0.001 to 1.868 has been scanned at tube voltage from 80 kV to 140 kV and tube current from 100 to 475 mA. CT numbers of all the materials except Teflon has been found to increase with tube voltage. Variations up to 80 HU has been observed with voltage. Variations with tube current were random. CT numbers changed by higher values at low voltage than at higher voltages. The radiation dose varied by less than 1 % for different curves used for dose calculation in 3DCRT, VMAT and SRT treatment plans of different anatomical sites. Dose differences decreased with increasing plan complexity. Changes in dose distributions near air cavities and bones have been observed. Variations of CT sensitometry has been found to be statistically significant, however, its dosimetric impact was statistically and clinically insignificant.

Post-Processing Bias Field Inhomogeneity Correction for Assessing Background Parenchymal Enhancement on Breast MRI as a Quantitative Marker of Treatment Response.

Background parenchymal enhancement (BPE) of breast fibroglandular tissue (FGT) in dynamic contrast-enhanced breast magnetic resonance imaging (MRI) has shown an association with response to neoadjuvant chemotherapy (NAC) in patients with breast cancer. Fully automated segmentation of FGT for BPE calculation is a challenge when image artifacts are present. Low spatial frequency intensity nonuniformity due to coil sensitivity variations is known as bias or inhomogeneity and can affect FGT segmentation and subsequent BPE measurement. In this study, we utilized the N4ITK algorithm for bias correction over a restricted bilateral breast volume and compared the contralateral FGT segmentations based on uncorrected and bias-corrected images in three MRI examinations at pre-treatment, early treatment and inter-regimen timepoints during NAC. A retrospective analysis of 2 cohorts was performed: one with 735 patients enrolled in the multi-center I-SPY 2 TRIAL and the sub-cohort of 340 patients meeting a high-quality benchmark for segmentation. Bias correction substantially increased the FGT segmentation quality for 6.3–8.0% of examinations, while it substantially decreased the quality for no examination. Our results showed improvement in segmentation quality and a small but statistically significant increase in the resulting BPE measurement after bias correction at all timepoints in both cohorts. Continuing studies are examining the effects on pCR prediction.

Inhomogeneous drag correction based on surrounding solid volume fraction in low-Reynolds-number regime

Lattice Boltzmann simulations of flows past fixed monodisperse spheres are employed to obtain the drag force on spheres at low Reynolds numbers. The fixed spheres are comprised of center and surrounding parts. Spheres in the center part are distributed with structures, while those in the surrounding part are distributed in random homogeneous configurations. The results show that the solid volume fraction in the surrounding part (also referred to as “surrounding solid volume fraction”) has a significant impact on the drag force of the center particles. This drag variation due to the change of surrounding solid volume fraction becomes even larger as the solid volume fraction or the inhomogeneities of the central particles increase. A new drag model considering the surrounding influence is proposed and it is very promising in resolving the gas-solid interactions in flows with complex structures such as riser flows.

Linear projection-based chemical exchange saturation transfer parameter estimation.

Isolated evaluation of multiparametric in vivo chemical exchange saturation transfer (CEST) MRI often requires complex computational processing for both correction of B0 and B1 inhomogeneity and contrast generation. For that, sufficiently densely sampled Z-spectra need to be acquired. The list of acquired frequency offsets largely determines the total CEST acquisition time, while potentially representing redundant information. In this work, a linear projection-based multiparametric CEST evaluation method is introduced that offers fast B0 and B1 inhomogeneity correction, contrast generation and feature selection for CEST data, enabling reduction of the overall measurement time. To that end, CEST data acquired at 7T in six healthy subjects and in one brain tumor patient were conventionally evaluated by interpolation-based inhomogeneity correction and Lorentzian curve fitting. Linear regression was used to obtain coefficient vectors that directly map uncorrected data to corrected Lorentzian target parameters. L1-regularization was applied to find subsets of the originally acquired CEST measurements that still allow for such a linear projection mapping. The linear projection method allows fast and interpretable mapping from acquired raw data to contrast parameters of interest, generalizing from healthy subject training data to unseen healthy test data and to the tumor patient dataset. The L1-regularization method shows that a fraction of the acquired CEST measurements is sufficient to preserve tissue contrasts, offering up to a 2.8-fold reduction of scan time. Similar observations as for the 7-T data can be made for data from a clinical 3-T scanner. Being a fast and interpretable computation step, the proposed method is complementary to neural networks that have recently been employed for similar purposes. The scan time acceleration offered by the L1-regularization ("CEST-LASSO") constitutes a step towards better applicability of multiparametric CEST protocols in a clinical context.

Optimized multi-axis spiral projection MR fingerprinting with subspace reconstruction for rapid whole-brain high-isotropic-resolution quantitative imaging.

To improve image quality and accelerate the acquisition of 3D MR fingerprinting (MRF). Building on the multi-axis spiral-projection MRF technique, a subspace reconstruction with locally low-rank constraint and a modified spiral-projection spatiotemporal encoding scheme called tiny golden-angle shuffling were implemented for rapid whole-brain high-resolution quantitative mapping. Reconstruction parameters such as the locally low-rank regularization parameter and the subspace rank were tuned using retrospective in vivo data and simulated examinations. B0 inhomogeneity correction using multifrequency interpolation was incorporated into the subspace reconstruction to further improve the image quality by mitigating blurring caused by off-resonance effect. The proposed MRF acquisition and reconstruction framework yields high-quality 1-mm isotropic whole-brain quantitative maps in 2 min at better quality compared with 6-min acquisitions of prior approaches. The proposed method was validated to not induce bias in T1 and T2 mapping. High-quality whole-brain MRF data were also obtained at 0.66-mm isotropic resolution in 4 min using the proposed technique, where the increased resolution was shown to improve visualization of subtle brain structures. The proposed tiny golden-angle shuffling, MRF with optimized spiral-projection trajectory and subspace reconstruction enables high-resolution quantitative mapping in ultrafast acquisition time.

Feasibility Study of Stereotactic Radiosurgery Treatment of Glomus Jugulare Tumors via HyperArc VMAT.

This study aims to report on the clinical validation and feasibility of utilizing a novel fully automated treatment planning and delivery system, HyperArc VMAT stereotactic radiosurgery (SRS) for glomus jugulare tumors (GJT). Independent dose verification of the HyperArc module via the MD Anderson's SRS head phantom irradiation and credentialing results showed compliance with the SRS treatment requirements per IROC MD Anderson's standard. Following the Alliance clinical trial, AAPM, RTOG protocols, and QUANTEC requirements, utilizing selected three-partial arc geometry of HyperArc module on TrueBeam Linac with 6MV-FFF beam, GJT SRS plans were generated for nine previously treated Gamma Knife (GK) radiosurgery patients using advanced Acuros-based algorithm to account for tissue inhomogeneity corrections and frameless immobilization with Q-fix mask and Encompass device insert. HyperArc VMAT produced highly conformal SRS dose distributions to GJT, a steep dose gradient around the GJT, and spared adjacent critical organs including the spinal cord (< 3.0 Gy). Due to faster patient setup and less MLC modulation through the target (average beam-on time, 6.2 minutes), the HyperArc VMAT plan can deliver a single high-dose of 18 Gy to the GJT in less than 15 minutes overall treatment time, significantly improving patient comfort and clinic workflow. Pretreatment portal dosimetry quality assurance results and independent dose verification via Monte Carlo-based physics second check met our clinical SRS protocol's requirements for treatment. Due to the highly conformal dose distribution, rapid dose fall-off, excellent sparing of adjacent critical organs, and highly precise and accurate treatment, clinical implementation of frameless HyperArc VMAT for GJT patients who may not have access to nor tolerate frame-based GK SRS treatment are underway.

Effect of a lead block on alveolar bone protection in image-guided high-dose-rate interstitial brachytherapy for tongue cancer: using model-based dose calculation algorithms to correct for inhomogeneity.

PurposeThe purpose of this study was to evaluate the effect of a lead block for alveolar bone protection in image-guided high-dose-rate interstitial brachytherapy for tongue cancer.Material and methodsWe treated 6 patients and delivered 5,400 cGy in 9 fractions using a lead block. Effects of lead block (median thickness, 4 mm) on dose attenuation by distance were visually examined using TG-43 formalism-based dose distribution curves to determine whether or not the area with the highest dose is located in the alveolar bone, where there is a high-risk of infection. Dose re-calculations were performed using TG-186 formalism with advanced collapsed cone engine (ACE) for inhomogeneity correction set to cortical bone density for the whole mandible and alveolar bone, water density for clinical target volume (CTV), air density for outside body and lead density, and silastic density for lead block and its’ silicon replica, respectively.ResultsThe highest dose was detected outside the alveolar bone in five of the six cases. For dose-volume histogram analysis, median minimum doses delivered per fraction to the 0.1 cm3 of alveolar bone (D0.1cm3TG-43, ACE-silicon, and ACE-lead) were 344.3 (range, 262.9-427.4) cGy, 336.6 (253.3-425.0) cGy, and 169.7 (114.9-233.3) cGy, respectively. D0.1cm3ACE-lead was significantly lower than other parameters. No significant difference was observed between CTV-related parameters.ConclusionsThe results suggested that using a lead block for alveolar bone protection with a thickness of about 4 mm, can shift the highest dose area to non-alveolar regions. In addition, it reduced D0.1cm3 of alveolar bone to about half, without affecting tumor dose.

B1 inhomogeneity correction of RARE MRI at low SNR: Quantitative in vivo 19 F MRI of mouse neuroinflammation with a cryogenically-cooled transceive surface radiofrequency probe.

Low SNR in fluorine-19 (19 F) MRI benefits from cryogenically-cooled transceive surface RF probes (CRPs), but strong B1 inhomogeneities hinder quantification. Rapid acquisition with refocused echoes (RARE) is an SNR-efficient method for MRI of neuroinflammation with perfluorinated compounds but lacks an analytical signal intensity equation to retrospectively correct B1 inhomogeneity. Here, a workflow was proposed and validated to correct and quantify 19 F-MR signals from the inflamed mouse brain using a 19 F-CRP. In vivo 19 F-MR images were acquired in a neuroinflammation mouse model with a quadrature 19 F-CRP using an imaging setup including 3D-printed components to acquire co-localized anatomical and 19 F images. Model-based corrections were validated on a uniform 19 F phantom and in the neuroinflammatory model. Corrected 19 F-MR images were benchmarked against reference images and overlaid on in vivo 1 H-MR images. Computed concentration uncertainty maps using Monte Carlo simulations served as a measure of performance of the B1 corrections. Our study reports on the first quantitative in vivo 19 F-MR images of an inflamed mouse brain using a 19 F-CRP, including in vivo T1 calculations for 19 F-nanoparticles during pathology and B1 corrections for 19 F-signal quantification. Model-based corrections markedly improved 19 F-signal quantification from errors > 50% to < 10% in a uniform phantom (p < 0.001). Concentration uncertainty maps ex vivo and in vivo yielded uncertainties that were generally < 25%. Monte Carlo simulations prescribed SNR ≥ 10.1 to reduce uncertainties < 10%, and SNR ≥ 4.25 to achieve uncertainties < 25%. Our model-based correction method facilitated 19 F signal quantification in the inflamed mouse brain when using the SNR-boosting 19 F-CRP technology, paving the way for future low-SNR 19 F-MRI applications in vivo.

Implementation of MR-Based Synthetic CT for Stereotactic Radiosurgery Dose Calculation

Most Gamma Knife stereotactic radiosurgery (GKRS) procedures have been performed using water-based dose calculation algorithms with magnetic resonance imaging (MRI) only. We present a dose calculation method that can take into account the inhomogeneity effect in routine GKRS treatment planning without CT imaging for every patient.Twenty-five patients who underwent GKRS at our institution with T1- and T2-weighted whole head MRI as well as brain CT images were selected for this study. Two set of synthetic computed tomographies (sCT) were generated from T1 and T2 MRI using cycle consistent generative adversial networks architecture (cGAN). Images from 20 patients were used to train the algorithm. The other 5 sets of data were used for testing and validation. The sCT images generated were evaluated in terms of the preservation of anatomical structures, the Hounsfield unit accuracy and the overall image quality. All sCT images from the 5 test patients were imported into GammaPlan version 11.1 for dosimetric analyses. We performed dose calculations for each test patient using the water-based TMR algorithm and the convolution algorithm with electron densities from the original CT, the T1-based sCT and the T2-based sCT.The main features of the original CT images (skull shape, bone & air inhomogeneity etc.) for the 5 test patients were successfully reproduced in the sCT images. sCT images from the T1-weighted MRI are in general closer to the original CT images compared to the T2-weighted MR images. For the same dose prescription and same shot arrangement, the maximum difference between the treatment shot times from the CT-based convolution calculation and the TMR calculation is 10.2%. The maximum differences between the treatment shot times from the CT-based convolution calculation and the convolution calculations from the sCTs from the T1 and T2 MR images are 2.3% and 3.8%, respectively.sCT images from brain MRI can be used for the inhomogeneity correction in GKRS dose calculation. T1-weighted MRI may work better than T2-weighted MRI for this purpose.F. Li: None. Y. Xu: None. O.D. Lemus: None. T.J. Wang: Research Grant; AbbVie, Merck, RTOG Foundation, Genentech. Honoraria; Elekta, Wolters Kluwer, Cancer Panels, Rutgers, University of Iowa. Consultant; Doximity, Elekta. Advisory Board; Novocure, AstraZeneca. Travel Expenses; AbbVie, Elekta, Novocure. Stock Options; Doximity. M.B. Sisti: None. C. Wuu: None.

Technical note: A fast and accurate analytical dose calculation algorithm for 125 I seed-loaded stent applications.

The safety and clinical efficacy of 125 I seed-loaded stent for the treatment of portal vein tumor thrombosis (PVTT) have been shown. Accurate and fast dose calculation of the 125 I seeds with the presence of the stent is necessary for the plan optimization and evaluation. However, the dosimetric characteristics of the seed-loaded stents remain unclear and there is no fast dose calculation technique available. This paper aims to explore a fast and accurate analytical dose calculation method based on Monte Carlo (MC) dose calculation, which takes into account the effect of stent and tissue inhomogeneity. A detailed model of the seed-loaded stent was developed using 3D modeling software and subsequently used in MC simulations to calculate the dose distribution around the stent. The dose perturbation caused by the presence of the stent was analyzed, and dose perturbation kernels (DPKs) were derived and stored for future use. Then, the dose calculation method from AAPM TG-43 was adapted by integrating the DPK and appropriate inhomogeneity correction factors (ICF) to calculate dose distributions analytically. To validate the proposed method, several comparisons were performed with other methods in water phantom and voxelized CT phantoms for three patients. The stent has a considerable dosimetric effect reducing the dose up to 47.2% for single-seed stent and 11.9%-16.1% for 16-seed stent. In a water phantom, dose distributions from MC simulations and TG-43-DP-ICF showed a good agreement with the relative error less than 3.3%. In voxelized CT phantoms, taking MC results as the reference, the relative errors of TG-43 method can be up to 33%, while those of TG-43-DP-ICF method were less than 5%. For a dose matrix with 256 × 256 × 46 grid (corresponding to a phantom of 17.2 × 17.2 × 11.5cm3 ) for 16-seed-loaded stent, it only takes 17s for TG-43-DP-ICF to compute, compared to 25h for the full MC calculation. The combination of DPK and inhomogeneity corrections is an effective approach to handle both the presence of stent and tissue heterogeneity. Exhibiting good agreement with MC calculation and computational efficiency, the proposed TG-43-DP-ICF method is adequate for dose evaluation and optimization in seed-loaded stent implantation treatment planning.

Reconstruction of the Electron–Phonon Interaction Function for Superconductors Using Inhomogeneous Point-Contacts and Correction Background in Yanson Spectra

Reconstruction of the Electron–Phonon Interaction Function for Superconductors Using Inhomogeneous Point-Contacts and Correction Background in Yanson Spectra

A Prototype Therapy System for Boiling Histotripsy in Abdominal Targets Based on a 256-Element Spiral Array.

Boiling histotripsy (BH) uses millisecond-long ultrasound (US) pulses with high-amplitude shocks to mechanically fractionate tissue with potential for real-time lesion monitoring by US imaging. For BH treatments of abdominal organs, a high-power multielement phased array system capable of electronic focus steering and aberration correction for body wall inhomogeneities is needed. In this work, a preclinical BH system was built comprising a custom 256-element 1.5-MHz phased array (Imasonic, Besançon, France) with a central opening for mounting an imaging probe. The array was electronically matched to a Verasonics research US system with a 1.2-kW external power source. Driving electronics and software of the system were modified to provide a pulse average acoustic power of 2.2 kW sustained for 10 ms with a 1-2-Hz repetition rate for delivering BH exposures. System performance was characterized by hydrophone measurements in water combined with nonlinear wave simulations based on the Westervelt equation. Fully developed shocks of 100-MPa amplitude are formed at the focus at 275-W acoustic power. Electronic steering capabilities of the array were evaluated for shock-producing conditions to determine power compensation strategies that equalize BH exposures at multiple focal locations across the planned treatment volume. The system was used to produce continuous volumetric BH lesions in ex vivo bovine liver with 1-mm focus spacing, 10-ms pulselength, five pulses/focus, and 1% duty cycle.

Quantification of lung water density with UTE Yarnball MRI.

An efficient Yarnball ultrashort-TE k-space trajectory, in combination with an optimized pulse sequence design and automated image-processing approach, is proposed for fast and quantitative imaging of water density in the lung parenchyma. Three-dimensional Yarnball k-space trajectories (TE = 0.07 ms) were designed at 3 T for breath-hold and free-breathing navigator acquisitions targeting the lung parenchyma (full torso spatial coverage) with minimal T1 and weighting. A composite of all solid tissues surrounding the lungs (muscle, liver, heart, blood pool) was used for user-independent lung water density signal referencing and B1 -inhomogeneity correction needed for the calculation of relative lung water density images. Sponge phantom experiments were used to validate absolute water density quantification, and relative lung water density was evaluated in 10 healthy volunteers. Phantom experiments showed excellent agreement between sponge wet weight and imaging-derived water density. Breath-hold (13 seconds) and free-breathing (~2 minutes) Yarnball acquisitions in volunteers (2.5-mm isotropic resolution) had negligible artifacts and good lung parenchyma SNR (>10). Whole-lung average relative lung water density values with fully automated analysis were 28.2 ± 1.9% and 28.6 ± 1.8% for breath-hold and free-breathing acquisitions, respectively, with good test-retest reproducibility (intraclass correlation coefficient = 0.86 and 0.95, respectively). Quantitative lung water density imaging with an optimized Yarnball k-space acquisition approach is possible in a breath-hold or short free-breathing study with automated signal referencing and segmentation.

Building a local climate reference dataset: Application to the Abruzzo region (Central Italy), 1930–2019

AbstractReliable secular time series of essential climatic variables are a fundamental element for the assessment of vulnerability, impact and adaptation to climate change. Here, we implement a readily portable procedure for building an upgradable long‐term homogeneous climate dataset using monthly and daily observations of temperature and precipitation over a given area of interest, exemplified here with Abruzzo, a region in Central Italy characterized by complex orography. We process the dataset according to a preliminary ranking of stations based on data quantity and quality, and we exploit the Climatol algorithm for inhomogeneity correction. The corrected time series show trends in broad agreement with external databases (CRU, Berkeley Earth, E‐OBS), and highlight the importance of relying on a local network for a better representation of gradients and variability over the territory. We estimate that maximum (TX) and minimum temperature (TN) increased by ~1.6 and ~2.2°C/century, respectively, over the period 1930–2019, while in the recent decades 1980–2019 we found an accelerated trend of ~5.7 and ~3.9°C/century. Precipitation (RR) decreased by ~10%/century in 1930–2019, while it has been increasing at a rate of ~26%/century in 1980–2019. The Köppen–Geiger climate classification is sensitive to the increase of precipitation in the recent decades, which is attributable to decreased summer precipitation overcompensated by more rain in late spring and early autumn. The cold climate types are retreating upwards along the slopes of the mountain ranges. Over the period 1980–2019, extreme values are also displaying significant trends. Every 2 years, there is one less frost day (TN &lt;0°C) and one more summer day (TX &gt;25°C) in the Apennines area, while there is one more tropical night (TN &gt;20°C) in the Adriatic coastal area. Precipitation extremes are increasing, especially along the coast, with rain accumulated in the rainiest days increasing at a rate of 1–2%/year.