Stent retriever for Tandem Acute Revascularization Technique (START): a novel technique for the endovascular management of tandem occlusions.

Tandem occlusions, characterized by the simultaneous presence of an intracranial large vessel occlusion and extracranial carotid artery stenosis or occlusion,1 pose a unique endovascular challenge.2 3 Typically, the extracranial occlusion is a result of atherosclerotic plaque; however, dissections are also a possible cause. It is currently uncertain whether an intracranial first approach or an extracranial first approach should be employed.4 5 A new technique has been developed which allows for the simultaneous treatment of both the intracranial and the extracranial lesion.6 We describe a variation of this technique: the stent retriever for tandem acute revascularization technique (START), which consists of simultaneously treating the intracranial lesion with stent retriever and contact aspiration, and the extracranial lesion with balloon angioplasty. We present a technical video explaining all the steps of START.(video 1)neurintsurg;jnis-2023-021011v1/V1F1V1Video 1Description and example of the START.

Endometriosis Imaging: Enter the Metaverse of Possibilities.

Although laparoscopy has classically been defined as the gold standard for diagnosis of endometriosis, there is now a strong recommendation for the use of advanced imaging in diagnosing the disease. In addition to playing a crucial role in the diagnosis of endometriosis, advanced imaging is also essential for assisting gynaecologic surgeons in planning the surgical management of complex cases of deep endometriosis. This case demonstrates a metaverse of high-level imaging modalities, including advanced ultrasound and magnetic resonance, which were further enhanced with medical virtual reality and used for the assessment of a patient seen in an outpatient tertiary care gynaecology clinic.

Monitoring Respiratory Motion during VMAT Treatment Delivery Using Ultra-Wideband Radar.

The goal of this paper is to evaluate the potential of a low-cost, ultra-wideband radar system for detecting and monitoring respiratory motion during radiation therapy treatment delivery. Radar signals from breathing motion patterns simulated using a respiratory motion phantom were captured during volumetric modulated arc therapy (VMAT) delivery. Gantry motion causes strong interference affecting the quality of the extracted respiration motion signal. We developed an artificial neural network (ANN) model for recovering the breathing motion patterns. Next, automated classification into four classes of breathing amplitudes is performed, including no breathing, breath hold, free breathing and deep inspiration. Breathing motion patterns extracted from the radar signal are in excellent agreement with the reference data recorded by the respiratory motion phantom. The classification accuracy of simulated deep inspiration breath hold breathing was 94% under the worst case interference from gantry motion and linac operation. Ultra-wideband radar systems can achieve accurate breathing rate estimation in real-time during dynamic radiation delivery. This technology serves as a viable alternative to motion detection and respiratory gating systems based on surface detection, and is well-suited to dynamic radiation treatment techniques. Novelties of this work include detection of the breathing signal using radar during strong interference from simultaneous gantry motion, and using ANN to perform adaptive signal processing to recover breathing signal from large interference signals in real time.

Predicting VMAT patient-specific QA results using a support vector classifier trained on treatment plan characteristics and linac QC metrics.

The use of treatment plan characteristics to predict patient-specific quality assurance (QA) measurement results has recently been reported as a strategy to help facilitate automated pre-treatment verification workflows or to provide a virtual assessment of delivery quality. The goal of this work is to investigate the potential of using treatment plan characteristics and linac performance metrics (i.e. quality control test results) in combination with machine learning techniques to predict the results of VMAT patient-specific QA measurements. Using features that describe treatment plan complexity and linac performance metrics, we trained a linear support vector classifier (SVC) to classify the results of VMAT patient-specific QA measurements. The 'targets' in this model were simple classes representing median dose difference between measured and expected dose distributions-'hot' if the median dose deviation was >1%, 'cold' if it was <-1%, and 'normal' if it was within ±1%. A total of 1620 unique patient-specific QA measurements were available for model development and testing. 75% of the data were used to develop and cross-validate the model, and the remaining 25% were used for an independent assessment of model performance. For the model development phase, a recursive feature elimination (RFE) cross-validation technique was used to eliminate unimportant features. Model performance was assessed using receiver operator characteristic (ROC) curve metrics. Of the ten features found to be most predictive of patient-specific QA measurement results, half were derived from treatment plan characteristics and half from quality control (QC) metrics characterizing linac performance. The model achieved a micro-averaged area under the ROC curve of 0.93, and a macro-averaged area under the ROC curve of 0.88. This work demonstrates the potential of using both treatment plan characteristics and routine linac QC results in the development of machine learning models for VMAT patient-specific QA measurements.

Applying Modern Virtual and Augmented Reality Technologies to Medical Images and Models.

Recent technological innovations have created new opportunities for the increased adoption of virtual reality (VR) and augmented reality (AR) applications in medicine. While medical applications of VR have historically seen greater adoption from patient-as-user applications, the new era of VR/AR technology has created the conditions for wider adoption of clinician-as-user applications. Historically, adoption to clinical use has been limited in part by the ability of the technology to achieve a sufficient quality of experience. This article reviews the definitions of virtual and augmented reality and briefly covers the history of their development. Currently available options for consumer-level virtual and augmented reality systems are presented, along with a discussion of technical considerations for their adoption in the clinical environment. Finally, a brief review of the literature of medical VR/AR applications is presented prior to introducing a comprehensive conceptual framework for the viewing and manipulation of medical images in virtual and augmented reality. Using this framework, we outline considerations for placing these methods directly into a radiology-based workflow and show how it can be applied to a variety of clinical scenarios.

Evaluation of a new commercial Monte Carlo dose calculation algorithm for electron beams.

PURPOSE: In this report the authors present the validation of a Monte Carlo dose calculation algorithm (XiO EMC from Elekta Software) for electron beams. METHODS: Calculated and measured dose distributions were compared for homogeneous water phantoms and for a 3D heterogeneous phantom meant to approximate the geometry of a trachea and spine. Comparisons of measurements and calculated data were performed using 2D and 3D gamma index dose comparison metrics. RESULTS: Measured outputs agree with calculated values within estimated uncertainties for standard and extended SSDs for open applicators, and for cutouts, with the exception of the 17 MeV electron beam at extended SSD for cutout sizes smaller than 5 × 5 cm(2). Good agreement was obtained between calculated and experimental depth dose curves and dose profiles (minimum number of measurements that pass a 2%/2 mm agreement 2D gamma index criteria for any applicator or energy was 97%). Dose calculations in a heterogeneous phantom agree with radiochromic film measurements (>98% of pixels pass a 3 dimensional 3%/2 mm γ-criteria) provided that the steep dose gradient in the depth direction is considered. CONCLUSIONS: Clinically acceptable agreement (at the 2%/2 mm level) between the measurements and calculated data for measurements in water are obtained for this dose calculation algorithm. Radiochromic film is a useful tool to evaluate the accuracy of electron MC treatment planning systems in heterogeneous media.

Position-probability-sampled Monte Carlo calculation of VMAT, 3DCRT, step-shoot IMRT, and helical tomotherapy dose distributions using BEAMnrc/DOSXYZnrc.

PURPOSE: The commercial release of volumetric modulated arc therapy techniques using a conventional linear accelerator and the growing number of helical tomotherapy users have triggered renewed interest in dose verification methods, and also in tools for exploring the impact of machine tolerance and patient motion on dose distributions without the need to approximate time-varying parameters such as gantry position, MLC leaf motion, or patient motion. To this end we have developed a Monte Carlo-based calculation method capable of simulating a wide variety of treatment techniques without the need to resort to discretization approximations. METHODS: The ability to perform complete position-probability-sampled Monte Carlo dose calculations was implemented in the BEAMnrc/DOSXZYnrc user codes of EGSnrc. The method includes full accelerator head simulations of our tomotherapy and Elekta linacs, and a realistic representation of continous motion via the sampling of a time variable. The functionality of this algorithm was tested via comparisons with both measurements and treatment planning dose distributions for four types of treatment techniques: 3D conformal, step-shoot intensity modulated radiation therapy, helical tomotherapy, and volumetric modulated are therapy. RESULTS: For static fields, the absolute dose agreement between the EGSnrc Monte Carlo calculations and measurements is within 2%/1 mm. Absolute dose agreement between Monte Carlo calculations and treatment planning system for the four different treatment techniques is within 3%/3 mm. Discrepancies with the tomotherapy TPS on the order of 10%/5 mm were observed for the extreme example of a small target located 15 cm off-axis and planned with a low modulation factor. The increase in simulation time associated with using position-probability sampling, as opposed to the discretization approach, was less than 2% in most cases. CONCLUSIONS: A single Monte Carlo simulation method can be used to calculate patient dose distribution for various types of treatment techniques delivered with either tomotherapy or a conventional linac. The method simplifies the simulation process, improves dose calculation accuracy, and involves an acceptably small change in computation time.

Accuracy of EGSnrc calculations at 60Co energies for the response of ion chambers configured with various wall materials and cavity dimensions.

In this investigation, five experimental data sets are used to evaluate the ability of the EGSnrc Monte Carlo code to calculate the change in chamber response associated with changes in wall material and cavity dimension at 60Co energies. Calculations of the ratios of response per unit mass of air as a function of cavity volume for walls ranging from polystyrene to lead are generally within 1%-3% of experiments. A few exceptions, which are discussed, include 20%-30% discrepancies with experiments involving lead-walled chambers used by Attix et al. [J. Res. Natl. Bur. Stand. 60, 235-243 (1958)] and Cormack and Johns [Radiat. Res. 1, 133-157 (1954)], and 5% discrepancies for the graphite chamber of Attix et al. (relative to data for other wall materials). Simulations of the experiment by Whyte [Radiat. Res. 6, 371-379 (1957)], which varied cavity air pressure in a large cylindrical chamber, are generally within 0.5% (wall/electrode materials ranging from beryllium to copper). In all cases, the agreement between measurements and EGSnrc calculations is much better when the response as a function of cavity height or air pressure is considered for each wall material individually. High-precision measurements [Burns et al., Phys. Med. Biol. 52, 7125-7135 (2007)] of the response per unit mass as a function of cavity height for a graphite chamber are also accurately reproduced, and validate previous tests of the transport mechanics of EGSnrc. Based on the general agreement found in this work between corresponding experimental results and EGSnrc calculations it can be concluded that EGSnrc can reliably be used to calculate changes in response with changes in various wall materials and cavity dimensions at 60Co energies within a accuracy of a few percent or less.

An experimental and computational investigation of the standard temperature-pressure correction factor for ion chambers in kilovoltage x rays.

For ion chambers with cavities open to the surrounding atmosphere, the response measured at a given temperature and pressure must be corrected using the standard temperature-pressure correction factor (P(TP)). A previous paper based solely on Monte Carlo simulations [D. J. La Russa and D. W. O. Rogers, Med. Phys. 33, 4590-4599 (2006)] pointed out the shortcomings of the P(TP) correction factor when used to correct the response of non-air-equivalent chambers for low-energy x-ray beams. This work presents the results of several experiments that corroborate these calculations for a number of ion chambers. Monte Carlo simulations of the experimental setup revealed additional insight into the various factors affecting the extent of the breakdown of P(TP), including the effect of impurities and the sensitivity to chamber dimensions. For an unfiltered 60 kV beam, the P(TP)-corrected response of an NE 2571 ion chamber measured at 0.7 atm was 2.5% below the response measured at reference conditions. In general, Monte Carlo simulations of the experimental setup using EGSnrc were within 0.5% of measured values. EGSnrc-calculated values of air kerma calibration coefficients (N(K)) at low x-ray energies are also provided as a means of estimating the level of impurities in the chambers investigated. Calculated values of N(K) normalized to the value measured for a 250 kV beam were obtained for three chambers and were within 1% of experiment with one exception, the Exradin A12 in a 50 kV beam.

An Egsnrc investigation of the P(TP) correction factor for ion chambers in kilovoltage X rays.

As part of the standard practice for obtaining consistent ion chamber measurements with cavities open to the surrounding atmosphere, the raw measured response is corrected to the response at a reference temperature and pressure using the standard temperature-pressure correction factor (P(TP)). In this study, the EGSnrc Monte Carlo code was used to investigate the validity of the P(TP) correction factor for kilovoltage x rays incident on various geometrically distinct ion chambers. The calculated P(TP)-corrected chamber response deviated by over 2% relative to expected values for a 40 kV spectrum incident on a graphite thimble chamber at an air density typical of Mexico City. The relative deviation from the expected response was much worse for a large spherical graphite chamber, exceeding 16% at an air density of 0.6 kg/m3 (approximately 0.5 atm at 22 degrees C) for the same beam energy. The breakdown of the P(TP) correction factor was also observed for a 26 kV mammography spectrum incident on two mammography chambers. For 60Co beams, the P(TP) correction factor behaved as expected. For day-to-day variations in pressure, only a negligible of the P(TP) correction factor was observed with low x-ray energies. Factors contributing to the breakdown of the P(TP) correction factor at low x-ray energies and large pressure variations, such as the range of electrons, the material of the wall, the chamber dimensions and air-photon interactions, are discussed in depth.

Effect of the iridium oxide thin film on the electrochemical activity of platinum nanoparticles.

The influence of the iridium oxide thin film on the electrocatalytic properties of platinum nanoparticles was investigated using the electro-oxidation of methanol and CO as a probe. The presence of the IrO(2) thin film leads to the homogeneous dispersion of Pt nanoparticles. For comparison, polycrystalline platinum and Pt nanoparticles dispersed on a Ti substrate in the absence of an IrO(2) layer (Ti/Pt) were also investigated in this study. Inverted and enhanced CO bipolar peaks were observed using an in situ electrochemical Fourier transform infrared technique during the methanol oxidation on the Pt nanoparticles dispersed on a Ti substrate. Electrochemical impedance studies showed that the charge transfer resistance was significantly lower for the Ti/IrO(2)/Pt electrode compared with that of the massive Pt and Ti/Pt nanoparticles. The presence of the IrO(2) thin film not only greatly increases the active surface area but also promotes CO oxidation at a much lower electrode potential, thus, significantly enhancing the electrocatalytic activity of Pt nanoparticles toward methanol electro-oxidation.