Augmented reality during parotid surgery: real-life evaluation of voice control of a head mounted display.

PURPOSE: Augmented Reality can improve surgical planning and performance in parotid surgery. For easier application we implemented a voice control manual for our augmented reality system. The aim of the study was to evaluate the feasibility of the voice control in real-life situations. METHODS: We used the HoloLens 1® (Microsoft Corporation) with a special speech recognition software for parotid surgery. The evaluation took place in a audiometry cubicle and during real surgical procedures. Voice commands were used to display various 3D structures of the patient with the HoloLens 1®. Commands had different variations (male/female, 65 dB SPL)/louder, various structures). RESULTS: In silence, 100% of commands were recognized. If the volume of the operation room (OR) background noise exceeds 42 dB, the recognition rate decreases significantly, and it drops below 40% at > 60 dB SPL. With constant speech volume at 65 dB SPL male speakers had a significant better recognition rate than female speakers (p = 0.046). Higher speech volumes can compensate this effect. The recognition rate depends on the type of background noise. Mixed OR noise (52 dB(A)) reduced the detection rate significantly compared to single suction noise at 52 dB(A) (p ≤ 0.00001). The recognition rate was significantly better in the OR than in the audio cubicle (p = 0.00013 both genders, 0.0086 female, and 0.0036 male). CONCLUSIONS: The recognition rate of voice commands can be enhanced by increasing the speech volume and by singularizing ambient noises. The detection rate depends on the loudness of the OR noise. Male voices are understood significantly better than female voices.

Augmented reality with HoloLens in parotid surgery: how to assess and to improve accuracy.

PURPOSE: Augmented reality improves planning and execution of surgical procedures. The aim of this study was to evaluate the feasibility of a 3D augmented reality hologram in live parotic surgery. Another goal was to develop an accuracy measuring instrument and to determine the accuracy of the system. METHODS: We created a software to build and manually align 2D and 3D augmented reality models generated from MRI data onto the patient during surgery using the HoloLens® 1 (Microsoft Corporation, Redmond, USA). To assess the accuracy of the system, we developed a specific measuring tool applying a standard electromagnetic navigation device (Fiagon GmbH, Hennigsdorf, Germany). RESULTS: The accuracy of our system was measured during real surgical procedures. Training of the experimenters and the use of fiducial markers significantly reduced the accuracy of holographic system (p = 0.0166 and p = 0.0132). Precision of the developed measuring system was very high with a mean error of the basic system of 1.3 mm. Feedback evaluation demonstrated 86% of participants agreed or strongly agreed that the HoloLens will play a role in surgical education. Furthermore, 80% of participants agreed or strongly agreed that the HoloLens is feasible to be introduced in clinical routine and will play a role within surgery in the future. CONCLUSION: The use of fiducial markers and repeated training reduces the positional error between the hologram and the real structures. The developed measuring device under the use of the Fiagon navigation system is suitable to measure accuracies of holographic augmented reality images of the HoloLens.

Augmented Reality with HoloLens® in Parotid Tumor Surgery: A Prospective Feasibility Study.

INTRODUCTION: Augmented reality can improve planning and execution of surgical procedures. Head-mounted devices such as the HoloLens® (Microsoft, Redmond, WA, USA) are particularly suitable to achieve these aims because they are controlled by hand gestures and enable contactless handling in a sterile environment. OBJECTIVES: So far, these systems have not yet found their way into the operating room for surgery of the parotid gland. This study explored the feasibility and accuracy of augmented reality-assisted parotid surgery. METHODS: 2D MRI holographic images were created, and 3D holograms were reconstructed from MRI DICOM files and made visible via the HoloLens. 2D MRI slices were scrolled through, 3D images were rotated, and 3D structures were shown and hidden only using hand gestures. The 3D model and the patient were aligned manually. RESULTS: The use of augmented reality with the HoloLens in parotic surgery was feasible. Gestures were recognized correctly. Mean accuracy of superimposition of the holographic model and patient's anatomy was 1.3 cm. Highly significant differences were seen in position error of registration between central and peripheral structures (p = 0.0059), with a least deviation of 10.9 mm (centrally) and highest deviation for the peripheral parts (19.6-mm deviation). CONCLUSION: This pilot study offers a first proof of concept of the clinical feasibility of the HoloLens for parotid tumor surgery. Workflow is not affected, but additional information is provided. The surgical performance could become safer through the navigation-like application of reality-fused 3D holograms, and it improves ergonomics without compromising sterility. Superimposition of the 3D holograms with the surgical field was possible, but further invention is necessary to improve the accuracy.

Prospective trial on telemonitoring of geriatric cancer patients using handheld devices.

PURPOSE AND OBJECTIVE: Randomized trials indicate that electronic or app-based assessment of patient-reported outcomes may improve outcomes in cancer patients. To analyze if an app-based follow-up would be accepted by elderly cancer patients, we conducted a single-center prospective feasibility study (NCT03196050). MATERIALS AND METHODS: Cancer patients (≥60 years) without concurrent uncontrolled severe medical conditions and a Karnofsky performance status (KPS) ≥70 were eligible if they were able to use the smartphone app. The primary endpoint was compliance over 1 year, calculated as patient-specific and study date-specific response rate to questions sent as push notifications; in this interim analysis, we report on 4­month data. Secondary outcomes included a comparison of a subjective health status item (SPHS) with the physician-rated KPS. RESULTS: Out of 225 patients screened, 54 patients agreed to participate and 29 activated the app and participated in the study. The mean age was 66 years (61-78). The individual compliance rate averaged at 58.3% (standard deviation SD = 35%). Daily compliance was 53.3% on average (SD = 10.8%) and declined over time. The average percentage of patients who sent answers at least weekly was 75.0% (SD = 14.8%) and declined from 100% in week 1 to 53.8% in week 17 post-enrollment. Secondary outcomes indicated that questionnaires such as the EORTC-QLQ-C30 are accepted via app and that there is a significant moderate correlation between the SPHS and KPS scores (r = 0.566; p < 0.001). CONCLUSION: Our data indicate that an app-based follow-up incorporating EORTC questionnaires might be possible in highly selected elderly cancer patients with modest compliance rates. Further trials should aim at an increased participation rate.

Analysis of Impact of Humidity and Temperature on Excimer Laser Ablation of Polyethylene Terephthalate, Polymethylmethacrylate, and Porcine Corneal Tissue.

BACKGROUND AND OBJECTIVES: To analyze the impact of humidity and temperature on excimer laser ablation of polyethylene terephthalate (PET), polymethylmethacrylate (PMMA) and porcine corneal tissue, and an ablation model to compensate for the temperature and humidity changes on ablation efficiency. STUDY DESIGN/MATERIALS AND METHODS: The study was conducted using an AMARIS 1050RS (Schwind eye-tech-solutions) placed inside a climate chamber at ACTS. Ablations were performed on PET, PMMA, and porcine cornea. The impact of a wide range of temperature (~18°C to ~30°C) and relative humidity (~25% to ~80%) on laser ablation outcomes was tested using nine climate test settings. For porcine eyes, change in defocus was calculated from the difference of post-ablation to pre-ablation average keratometry readings. Laser scanning deflectometry was performed to measure refractive change achieved in PMMA. Multiple linear regression was performed using the least square method with predictive factors: temperature, relative humidity, time stamp. Influence of climate settings was modeled for pulse energy, pulse fluence, ablation efficiency on PMMA and porcine cornea tissue. RESULTS: Temperature changes did not affect laser pulse energy, pulse fluence (PET), and ablation efficiency (on PMMA or porcine corneal tissue) significantly. Changes in relative humidity were critical and significantly affected laser pulse energy, high fluence and low fluence. The opposite trend was observed between the ablation performance on PMMA and porcine cornea. CONCLUSIONS: The proposed well-fitting multi-linear model can be utilized for compensation of temperature and humidity changes on ablation efficiency. Based on this model, a working window for optimum operation has been found (temperature 18°C to 28°C and relative humidity 25% to 65%) for a maximum deviation of ±2.5% in ablation efficiency in PMMA and porcine corneal tissue. Lasers Surg. Med. © 2019 The Authors. Lasers in Surgery and Medicine Published by Wiley Periodicals, Inc.

Multiple retrieval case-based reasoning for incomplete datasets.

The performance of case-based reasoning (CBR) depends on an accurate ranking of similar cases in the retrieval phase that affects all subsequent phases and profits from the potential of large databases. Unfortunately, growing databases come along with a rising amount of missing data that reduces the stability of the ranking since incomplete cases cannot be ranked as reliable as complete ones. In context of CBR hardly any work was done so far to rigorously analyze the impact of missing data and solutions to tackle this issue. In particular, a generalized solution which is able to process data under different missingness conditions for different variable types is missing. In this paper we present a multiple retrieval case-based reasoning (MRCBR) framework for incomplete databases that provides a statistically accurate ranking for similar cases. It unifies the advantages of multiple imputation and CBR while it preserves both the data distribution and database structure. Built as generalized CBR system, MRCBR was optimized and tested for medical decision support but can be extended to any CBR requirement as well. It is suitable for numerical and categorical variables and all sorts of missingness conditions. The approach was compared to eight competing methods applicable to handle incomplete databases in context of CBR. The comparison to the true ranking was based on two various error measures. In the evaluation we tested four representative scenarios that considered different conditions for missing data analysis. The outcome for every method in each scenario resulted in 200 miscellaneous setups. MRCBR outperforms all compared CBR methods in presence of missing data and shows reliable and stable results in every scenario. Especially with larger databases and rising number of incomplete variables it enlarges its lead to all other methods. Our study demonstrates that missing data must not be ignored when a correct CBR outcome is required.

Real-time, ray casting-based scatter dose estimation for c-arm x-ray system.

OBJECTIVES: Dosimetric control of staff exposure during interventional procedures under fluoroscopy is of high relevance. In this paper, a novel ray casting approximation of radiation transport is presented and the potential and limitation vs. a full Monte Carlo transport and dose measurements are discussed. METHOD: The x-ray source of a Siemens Axiom Artix C-arm is modeled by a virtual source model using single Gaussian-shaped source. A Geant4-based Monte Carlo simulation determines the radiation transport from the source to compute scatter from the patient, the table, the ceiling and the floor. A phase space around these scatterers stores all photon information. Only those photons are traced that hit a surface of phantom that represents medical staff in the treatment room, no indirect scattering is considered; and a complete dose deposition on the surface is calculated. To evaluate the accuracy of the approximation, both experimental measurements using Thermoluminescent dosimeters (TLDs) and a Geant4-based Monte Carlo simulation of dose depositing for different tube angulations of the C-arm from cranial-caudal angle 0° and from LAO (Left Anterior Oblique) 0°-90° are realized. Since the measurements were performed on both sides of the table, using the symmetry of the setup, RAO (Right Anterior Oblique) measurements were not necessary. RESULTS: The Geant4-Monte Carlo simulation agreed within 3% with the measured data, which is within the accuracy of measurement and simulation. The ray casting approximation has been compared to TLD measurements and the achieved percentage difference was -7% for data from tube angulations 45°-90° and -29% from tube angulations 0°-45° on the side of the x-ray source, whereas on the opposite side of the x-ray source, the difference was -83.8% and -75%, respectively. Ray casting approximation for only LAO 90° was compared to a Monte Carlo simulation, where the percentage differences were between 0.5-3% on the side of the x-ray source where the highest dose usually detected was mainly from primary scattering (photons), whereas percentage differences between 2.8-20% are found on the side opposite to the x-ray source, where the lowest doses were detected. Dose calculation time of our approach was 0.85 seconds. CONCLUSION: The proposed approach yields a fast scatter dose estimation where we could run the Monte Carlo simulation only once for each x-ray tube angulation to get the Phase Space Files (PSF) for being used later by our ray casting approach to calculate the dose from only photons which will hit an movable elliptical cylinder shaped phantom and getting an output file for the positions of those hits to be used for visualizing the scatter dose propagation on the phantom surface. With dose calculation times of less than one second, we are saving much time compared to using a Monte Carlo simulation instead. With our approach, larger deviations occur only in regions with very low doses, whereas it provides a high precision in high-dose regions.

Influence of regional cerebral blood volume on voxel-based morphometry.

The investigation of structural brain alterations is one focus in research of brain diseases like depression. Voxel-based morphometry (VBM) based on high-resolution 3D MRI images is a widely used non-invasive tool for such investigations. However, the result of VBM might be sensitive to local physiological parameters such as regional cerebral blood volume (rCBV) changes. In order to investigate whether rCBV changes may contribute to variation in VBM, we performed analyses in a study with the congenital learned helplessness (cLH) model for long-term findings. The 3D structural and rCBV data were acquired with T2 -weighted rapid acquisition with relaxation enhancement (RARE) pulse sequences. The group effects were determined by standard statistical parametric mapping (SPM) and biological parametric mapping (BPM) and examined further using atlas-based regions. In our genetic animal model of depression, we found co-occurrence of differences in gray matter volume and rCBV, while there was no evidence of significant interaction between both. However, the multimodal analysis showed similar gray matter differences compared with the standard VBM approach. Our data corroborate the idea that two group VBM differences might not be influenced by rCBV differences in genetically different strains. Copyright © 2016 John Wiley & Sons, Ltd.

Towards clinical implementation of ultrafast combined kV-MV CBCT for IGRT of lung cancer : Evaluation of registration accuracy based on phantom study.

PURPOSE: Combined kV-MV cone-beam CT (CBCT) is a promising approach to accelerate imaging for patients with lung tumors treated with deep inspiration breath-hold. During a single breath-hold (15 s), a 3D kV-MV CBCT can be acquired, thus minimizing motion artifacts and increasing patient comfort. Prior to clinical implementation, positioning accuracy was evaluated and compared to clinically established imaging techniques. METHODS AND MATERIALS: An inhomogeneous thorax phantom with four tumor-mimicking inlays was imaged in 10 predefined positions and registered to a planning CT. Novel kV-MV CBCT imaging (90° arc) was compared to clinically established kV-chest CBCT (360°) as well as nonclinical kV-CBCT and low-dose MV-CBCT (each 180°). Manual registration, automatic registration provided by the manufacturer and an additional in-house developed manufacturer-independent framework based on the MATLAB registration toolkit were applied. RESULTS: Systematic setup error was reduced to 0.05 mm by high-precision phantom positioning with optical tracking. Stochastic mean displacement errors were 0.5 ± 0.3 mm in right-left, 0.4 ± 0.4 mm in anteroposterior and 0.0 ± 0.4 mm in craniocaudal directions for kV-MV CBCT with manual registration (maximum errors of no more than 1.4 mm). Clinical kV-chest CBCT resulted in mean errors of 0.2 mm (other modalities: 0.4-0.8 mm). Similar results were achieved with both automatic registration methods. CONCLUSION: The comparison study of repositioning accuracy between novel kV-MV CBCT and clinically established volume imaging demonstrated that registration accuracy is maintained below 1 mm. Since imaging time is reduced to one breath-hold, kV-MV CBCT is ideal for image guidance, e.g., in lung stereotactic ablative radiotherapy.

Accurate low-dose iterative CT reconstruction from few projections by Generalized Anisotropic Total Variation minimization for industrial CT.

BACKGROUND: Reducing the amount of time for data acquisition and reconstruction in industrial CT decreases the operation time of the X-ray machine and therefore increases the sales. This can be achieved by reducing both, the dose and the pulse length of the CT system and the number of projections for the reconstruction, respectively. OBJECTIVE: In this paper, a novel generalized Anisotropic Total Variation regularization for under-sampled, low-dose iterative CT reconstruction is discussed and compared to the standard methods, Total Variation, Adaptive weighted Total Variation and Filtered Backprojection. METHOD: The novel regularization function uses a priori information about the Gradient Magnitude Distribution of the scanned object for the reconstruction. We provide a general parameterization scheme and evaluate the efficiency of our new algorithm for different noise levels and different number of projection views. RESULTS: When noise is not present, error-free reconstructions are achievable for AwTV and GATV from 40 projections. In cases where noise is simulated, our strategy achieves a Relative Root Mean Square Error that is up to 11 times lower than Total Variation-based and up to 4 times lower than AwTV-based iterative statistical reconstruction (e.g. for a SNR of 223 and 40 projections). CONCLUSION: To obtain the same reconstruction quality as achieved by Total Variation, the projection number and the pulse length, and the acquisition time and the dose respectively can be reduced by a factor of approximately 3.5, when AwTV is used and a factor of approximately 6.7, when our proposed algorithm is used.

Phenotypic profiling of the human genome reveals gene products involved in plasma membrane targeting of SRC kinases.

SRC proteins are non-receptor tyrosine kinases that play key roles in regulating signal transduction by a diverse set of cell surface receptors. They contain N-terminal SH4 domains that are modified by fatty acylation and are functioning as membrane anchors. Acylated SH4 domains are both necessary and sufficient to mediate specific targeting of SRC kinases to the inner leaflet of plasma membranes. Intracellular transport of SRC kinases to the plasma membrane depends on microdomains into which SRC kinases partition upon palmitoylation. In the present study, we established a live-cell imaging screening system to identify gene products involved in plasma membrane targeting of SRC kinases. Based on siRNA arrays and a human model cell line expressing two kinds of SH4 reporter molecules, we conducted a genome-wide analysis of SH4-dependent protein targeting using an automated microscopy platform. We identified and validated 54 gene products whose down-regulation causes intracellular retention of SH4 reporter molecules. To detect and quantify this phenotype, we developed a software-based image analysis tool. Among the identified gene products, we found factors involved in lipid metabolism, intracellular transport, and cellular signaling processes. Furthermore, we identified proteins that are either associated with SRC kinases or are related to various known functions of SRC kinases such as other kinases and phosphatases potentially involved in SRC-mediated signal transduction. Finally, we identified gene products whose function is less defined or entirely unknown. Our findings provide a major resource for future studies unraveling the molecular mechanisms that underlie proper targeting of SRC kinases to the inner leaflet of plasma membranes.

Assessment of the axial resolution of a compact gamma camera with coded aperture collimator.

PURPOSE: Handheld gamma cameras with coded aperture collimators are under investigation for intraoperative imaging in nuclear medicine. Coded apertures are a promising collimation technique for applications such as lymph node localization due to their high sensitivity and the possibility of 3D imaging. We evaluated the axial resolution and computational performance of two reconstruction methods. METHODS: An experimental gamma camera was set up consisting of the pixelated semiconductor detector Timepix3 and MURA mask of rank 31 with round holes of 0.08 mm in diameter in a 0.11 mm thick Tungsten sheet. A set of measurements was taken where a point-like gamma source was placed centrally at 21 different positions within the range of 12-100 mm. For each source position, the detector image was reconstructed in 0.5 mm steps around the true source position, resulting in an image stack. The axial resolution was assessed by the full width at half maximum (FWHM) of the contrast-to-noise ratio (CNR) profile along the z-axis of the stack. Two reconstruction methods were compared: MURA Decoding and a 3D maximum likelihood expectation maximization algorithm (3D-MLEM). RESULTS: While taking 4400 times longer in computation, 3D-MLEM yielded a smaller axial FWHM and a higher CNR. The axial resolution degraded from 5.3 mm and 1.8 mm at 12 mm to 42.2 mm and 13.5 mm at 100 mm for MURA Decoding and 3D-MLEM respectively. CONCLUSION: Our results show that the coded aperture enables the depth estimation of single point-like sources in the near field. Here, 3D-MLEM offered a better axial resolution but was computationally much slower than MURA Decoding, whose reconstruction time is compatible with real-time imaging.

3D-localization of single point-like gamma sources with a coded aperture camera.

Objective.3D-localization of gamma sources has the potential to improve the outcome of radio-guided surgery. The goal of this paper is to analyze the localization accuracy for point-like sources with a single coded aperture camera.Approach.We both simulated and measured a point-like241Am source at 17 positions distributed within the field of view of an experimental gamma camera. The setup includes a0.11mmthick Tungsten sheet with a MURA mask of rank 31 and pinholes of0.08mmin diameter and a detector based on the photon counting readout circuit Timepix3. Two methods, namely an iterative search including either a symmetric Gaussian fitting or an exponentially modified Gaussian fitting (EMG) and a center of mass method were compared to estimate the 3D source position.Main results.Considering the decreasing axial resolution with source-to-mask distance, the EMG improved the results by a factor of 4 compared to the Gaussian fitting based on the simulated data. Overall, we obtained a mean localization error of0.77mmon the simulated and2.64mmon the experimental data in the imaging range of20-100mm.Significance.This paper shows that despite the low axial resolution, point-like sources in the nearfield can be localized as well as with more sophisticated imaging devices such as stereo cameras. The influence of the source size and the photon count on the imaging and localization accuracy remains an important issue for further research.

Diffuse domain approach for flexible needle insertion and relaxation.

Needle insertion simulations play an important role in medical training and surgical planning. Most simulations require boundary conforming meshes, while the diffuse domain approach, currently limited to stiff needles, eliminates the need for meshing geometries. In this article the diffuse domain approach for needle insertion simulations is first extended to the use of flexible needles with bevel needle tips, which are represented by an Euler-Bernoulli beam. The model parameters are tuned and the model is evaluated on a real-world phantom experiment. Second, a new method for the relaxation of the needle-tissue system after the user releases the needle is introduced. The equilibrium state of the system is determined by minimizing the potential energy. The convergence rate of the coupled Laplace equations for solving the Euler-Bernoulli beam is 1.92 ± 0.14 for decreasing cell size. The diffuse penalty method for the application of Dirichlet boundary conditions results in a convergence rate of 0.73 ± 0.21 for decreasing phase field width. The simulated needle deviates on average by 0.29 mm compared to the phantom experiment. The error of the tissue deformation is below 1 mm for 97.5% of the attached markers. Two additional experiments demonstrate the feasibility of the relaxation process. The simulation method presented here is a valuable tool for patient-specific medical simulations using flexible needles without the need for boundary conforming meshing. To the best of the authors' knowledge this is the first work to introduce a relaxation model, which is a major step for simulating accurate needle-tissue positioning during realistic medical interventions.

Real-time definition of single seed placement sensitivity in low-dose-rate prostate brachytherapy.

PURPOSE: In low-dose-rate brachytherapy, iodine-125 seeds are implanted based on a treatment plan, generated with respect to different dose constraints. The quality of the dose distribution depends on a precise seed placement, however, during treatment planning the impact on the dose parameters when certain seeds fail to be placed precisely is not clear. METHODS AND MATERIALS: We developed a method using automatic differentiation to calculate gradients of dose parameters with regard to the seeds' positions. Thus, we understand their sensitivity with respect to the seed placement. A statistical analysis is performed on a data set with 35 prostate brachytherapy patients. RESULTS: The most sensitive seeds regarding the dosimetric parameters of both rectum and urethra are close to the corresponding organ. Their gradient directions are mainly orthogonal to their surfaces. However, not all seeds close to the surface are equally sensitive with regard to the dose parameter. The most sensitive seeds regarding the prostate's dose parameters are distributed throughout the prostate and the direction of the gradients are mainly parallel to its surface. A linear regression with respect to different patient parameters shows that dose constraints which are barely fulfilled have large gradients and thus are additionally sensitive to misplacement. CONCLUSION: Automatic differentiation can be used to analyze dose parameter sensitivity with respect to seed placement. Integrating this into treatment planning systems is valuable as it speeds up the planning procedure, making it more robust and less dependent on user experience while showing the operating physician which needle placements require greater accuracy than others.

Point Cloud Registration for Measuring Shape Dependence of Soft Tissue Deformation by Digital Twins in Head and Neck Surgery.

Introduction: A 2½ D point cloud registration method was developed to generate digital twins of different tissue shapes and resection cavities by applying a machine learning (ML) approach. This demonstrates the feasibility of quantifying soft tissue shifts. Methods: An ML model was trained using simulated surface scan data obtained from tumor resections in a pig head cadaver model. It hereby uses 438 2½ D scans of the tissue surface. Tissue shift was induced by a temperature change from 7.91 ± 4.1°C to 36.37 ± 1.28°C. Results: Digital twins were generated from various branched and compact resection cavities (RCs) and cut tissues (CT). A temperature increase induced a tissue shift with a significant volume increase of 6 mL and 2 mL in branched and compact RCs, respectively (p = 0.0443; 0.0157). The volumes of branched and compact CT were decreased by 3 and 4 mL (p < 0.001). In the warm state, RC and CT no longer fit together because of the significant tissue deformation. Although not significant, the compact RC showed a greater tissue deformation of 1 µL than the branched RC with 0.5 µL induced by the temperature change (p = 0.7874). The branched and compact CT forms responded almost equally to changes in temperature (p = 0.1461). Conclusions: The simulation experiment of induced soft tissue deformation using digital twins based on 2½ D point cloud models proved that our method helps to quantify shape-dependent tissue shifts.

Analysis of hydrogen peroxide production in pure water: Ultrahigh versus conventional dose-rate irradiation and mechanistic insights.

BACKGROUND: Ultrahigh dose-rate radiation (UHDR) produces less hydrogen peroxide (H2O2) in pure water, as suggested by some experimental studies, and is used as an argument for the validity of the theory that FLASH spares the normal tissue due to less reactive oxygen species (ROS) production. In contrast, most Monte Carlo simulation studies suggest the opposite. PURPOSE: We aim to unveil the effect of UHDR on H2O2 production in pure water and its underlying mechanism, to serve as a benchmark for Monte Carlo simulation. We hypothesized that the reaction of solvated electrons ( e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ ) removing hydroxyl radicals (•OH), the precursor of H2O2, is the reason why UHDR leads to a lower G-value (molecules/100 eV) for H2O2 (G[H2O2]), because: 1, the third-order reaction between e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ and •OH is more sensitive to increased instantaneous ROS concentration by UHDR than a two-order reaction of •OH self-reaction producing H2O2; 2, e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ has two times higher diffusion coefficient and higher reaction rate constant than that of •OH, which means e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ would dominate the competition for •OH and benefit more from the inter-track effect of UHDR. Meanwhile, we also experimentally verify the theory of long-lived radicals causing lower G(H2O2) in conventional irradiation, which is mentioned in some simulation studies. METHODS AND MATERIALS: H2O2 was measured by Amplex UltraRed assay. 430.1 MeV/u carbon ions (50 and 0.1 Gy/s), 9 MeV electrons (600 and 0.62 Gy/s), and 200 kV x-ray tube (10 and 0.1 Gy/s) were employed. For three kinds of water (real hypoxic: 1% O2; hypoxic: 1% O2 and 5% CO2; and normoxic: 21% O2), unbubbled and bubbled samples with N2O, the scavenger of e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ , were irradiated by carbon ions and electrons with conventional and UHDR at different absolute dose levels. Normoxic water dissolved with sodium nitrate (NaNO3), another scavenger of e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ , and bubbled with N2O was irradiated by x-ray to verify the results of low-LET electron beam. RESULTS: UHDR leads to a lower G(H2O2) than conventional irradiation. O2 and CO2 can both increase G(H2O2). N2O increases G(H2O2) of both UHDR and conventional irradiation and eliminates the difference between them for carbon ions. However, N2O decreases G(H2O2) in electron conventional irradiation but increases G(H2O2) in the case of UHDR, ending up with no dose-rate dependency of G(H2O2). Three-spilled carbon UHDR does not have a lower G(H2O2) than one-spilled UHDR. However, the electron beam shows a lower G(H2O2) for three-spilled UHDR than for one-spilled UHDR. Normoxic water with N2O or NaNO3 can both eliminate the dose rate dependency of H2O2 production for x-ray. CONCLUSIONS: UHDR has a lower G(H2O2) than the conventional irradiation for both high LET carbon and low LET electron and x-ray beams. Both scavengers for e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ , N2O and NaNO3, eliminate the dose-rate dependency of G(H2O2), which suggests e aq - ${\mathrm{e}}_{{\mathrm{aq}}}^ - $ is the reason for decreased G(H2O2) for UHDR. Three-spilled UHDR versus one-spilled UHDR indicates that the assumption of residual radicals reducing G(H2O2) of conventional irradiation may only be valid for low LET electron beam.

Dose-response relationship of locally applied nimodipine in an ex vivo model of cerebral vasospasm.

INTRODUCTION: Cerebral vasospasm is a severe complication of subarachnoid hemorrhage (SAH). The calcium channel inhibitor nimodipine has been used for treatment of cerebral vasospasm. No evidence-based recommendations for local nimodipine administration at the site of vasospasm exist. The purpose of this study was to quantify nimodipine's local vasodilatory effect in an ex vivo model of SAH-induced vasospasm. METHODS: SAH-induced vasospasm was modeled by contracting isolated segments of rat superior cerebellar arteries with a combination of serotonin and a synthetic analog of prostaglandin A(2). A pressure myograph system was used to determine vessel reactivity of spastic as well as non-spastic arteries. RESULTS: Compared to the initial vessel diameter, a combination of serotonin and prostaglandin induced considerable vasospasm (55 ± 2.5 % contraction; n = 12; p < 0.001). Locally applied nimodipine dilated the arteries in a concentration-dependent manner starting at concentrations as low as 1 nM (n = 12; p < 0.05). Concentrations higher than 100 nM did not relevantly increase the vasodilatory effect. Nimodipine's vasodilatory effect was smaller in spastic than in non-spastic vessels (n = 12; p < 0.05), which we assume to be due to structural changes in the vessel wall. CONCLUSION: The described ex vivo model allows to investigate the dose-dependent efficacy of spasmolytic drugs prior to in vivo experiments. Low concentrations of locally applied nimodipine have a strong vasodilatory effect, which is of relevance when considering the local application of nimodipine in cerebral vasospasm.

A theoretical study of H2 O2 as the surrogate of dose in minibeam radiotherapy, with a diffusion model considering radical removal process.

BACKGROUND: Minibeam radiation therapy (MBRT) is an innovative dose delivery method with the potential to spare normal tissue while achieving similar tumor control as conventional radiotherapy. However, it is difficult to use a single dose parameter, such as mean dose, to compare different patterns of MBRT due to the spatially fractionated radiation. Also, the mechanism leading to the biological effects is still unknown. PURPOSE: This study aims to demonstrate that the hydrogen peroxide (H2 O2 ) distribution could serve as a surrogate of dose distribution when comparing different patterns of MBRT. METHODS: A free diffusion model (FDM) for H2 O2 developed with Fick's second law was compared with a previously published model based on Monte Carlo & convolution method. Since cells form separate compartments that can eliminate H2 O2 radicals diffusing inside the cell, a term describing the elimination was introduced into the equation. The FDM and the diffusion model considering removal (DMCR) were compared by simulating various dose rate irradiation schemes and uniform irradiation. Finally, the DMCR was compared with previous microbeam and minibeam animal experiments. RESULTS: Compared with a previous Monte Carlo & Convolution method, this analytical method provides more accurate results. Furthermore, the new model shows H2 O2 concentration distribution instead of the time to achieve a certain H2 O2 uniformity. The comparison between FDM and DMCR showed that H2 O2 distribution from FDM varied with dose rate irradiation, while DMCR had consistent results. For uniform irradiation, FDM resulted in a Gaussian distribution, while the H2 O2 distribution from DMCR was close to the dose distribution. The animal studies' evaluation showed a correlation between the H2 O2 concentration in the valley region and treatment outcomes. CONCLUSION: DMCR is a more realistic model for H2 O2 simulation than the FDM. In addition, the H2 O2 distribution can be a good surrogate of dose distribution when the minibeam effect could be observed.

Simulation-to-real generalization for deep-learning-based refraction-corrected ultrasound tomography image reconstruction.

Objective. The image reconstruction of ultrasound computed tomography is computationally expensive with conventional iterative methods. The fully learned direct deep learning reconstruction is promising to speed up image reconstruction significantly. However, for direct reconstruction from measurement data, due to the lack of real labeled data, the neural network is usually trained on a simulation dataset and shows poor performance on real data because of the simulation-to-real gap.Approach. To improve the simulation-to-real generalization of neural networks, a series of strategies are developed including a Fourier-transform-integrated neural network, measurement-domain data augmentation methods, and a self-supervised-learning-based patch-wise preprocessing neural network. Our strategies are evaluated on both the simulation dataset and real measurement datasets from two different prototype machines.Main results. The experimental results show that our deep learning methods help to improve the neural networks' robustness against noise and the generalizability to real measurement data.Significance. Our methods prove that it is possible for neural networks to achieve superior performance to traditional iterative reconstruction algorithms in imaging quality and allow for real-time 2D-image reconstruction. This study helps pave the path for the application of deep learning methods to practical ultrasound tomography image reconstruction based on simulation datasets.