Clinical application of a template-guided automated planning routine.

PURPOSE: Determine the dosimetric quality and the planning time reduction when utilizing a template-based automated planning application. METHODS: A software application integrated through the treatment planning system application programing interface, QuickPlan, was developed to facilitate automated planning using configurable templates for contouring, knowledge-based planning structure matching, field design, and algorithm settings. Validations are performed at various levels of the planning procedure and assist in the evaluation of readiness of the CT image, structure set, and plan layout for automated planning. QuickPlan is evaluated dosimetrically against 22 hippocampal-avoidance whole brain radiotherapy patients. The required times to treatment plan generation are compared for the validations set as well as 10 prospective patients whose plans have been automated by QuickPlan. RESULTS: The generations of 22 automated treatment plans are compared against a manual replanning using an identical process, resulting in dosimetric differences of minor clinical significance. The target dose to 2% volume and homogeneity index result in significantly decreased values for automated plans, whereas other dose metric evaluations are nonsignificant. The time to generate the treatment plans is reduced for all automated plans with a median difference of 9' 50″ ± 4' 33″. CONCLUSIONS: Template-based automated planning allows for reduced treatment planning time with consistent optimization structure creation, treatment field creation, plan optimization, and dose calculation with similar dosimetric quality. This process has potential expansion to numerous disease sites.

EOG Signal Classification with Wavelet and Supervised Learning Algorithms KNN, SVM and DT.

The work carried out in this paper consists of the classification of the physiological signal generated by eye movement called Electrooculography (EOG). The human eye performs simultaneous movements, when focusing on an object, generating a potential change in origin between the retinal epithelium and the cornea and modeling the eyeball as a dipole with a positive and negative hemisphere. Supervised learning algorithms were implemented to classify five eye movements; left, right, down, up and blink. Wavelet Transform was used to obtain information in the frequency domain characterizing the EOG signal with a bandwidth of 0.5 to 50 Hz; training results were obtained with the implementation of K-Nearest Neighbor (KNN) 69.4%, a Support Vector Machine (SVM) of 76.9% and Decision Tree (DT) 60.5%, checking the accuracy through the Jaccard index and other metrics such as the confusion matrix and ROC (Receiver Operating Characteristic) curve. As a result, the best classifier for this application was the SVM with Jaccard Index.

Pattern Recognition of EMG Signals by Machine Learning for the Control of a Manipulator Robot.

Human Machine Interfaces (HMI) principles are for the development of interfaces for assistance or support systems in physiotherapy or rehabilitation processes. One of the main problems is the degree of customization when applying some rehabilitation therapy or when adapting an assistance system to the individual characteristics of the users. To solve this inconvenience, it is proposed to implement a database of surface Electromyography (sEMG) of a channel in healthy individuals for pattern recognition through Neural Networks of contraction in the muscular region of the biceps brachii. Each movement is labeled using the One-Hot Encoding technique, which activates a state machine to control the position of an anthropomorphic manipulator robot and validate the response time of the designed HMI. Preliminary results show that the learning curve decreases when customizing the interface. The developed system uses muscle contraction to direct the position of the end effector of a virtual robot. The classification of Electromyography (EMG) signals is obtained to generate trajectories in real time by designing a test platform in LabVIEW.

Application programming interface guided QA plan generation and analysis automation.

PURPOSE: Linear accelerator quality assurance (QA) in radiation therapy is a time consuming but fundamental part of ensuring the performance characteristics of radiation delivering machines. The goal of this work is to develop an automated and standardized QA plan generation and analysis system in the Oncology Information System (OIS) to streamline the QA process. METHODS: Automating the QA process includes two software components: the AutoQA Builder to generate daily, monthly, quarterly, and miscellaneous periodic linear accelerator QA plans within the Treatment Planning System (TPS) and the AutoQA Analysis to analyze images collected on the Electronic Portal Imaging Device (EPID) allowing for a rapid analysis of the acquired QA images. To verify the results of the automated QA analysis, results were compared to the current standard for QA assessment for the jaw junction, light-radiation coincidence, picket fence, and volumetric modulated arc therapy (VMAT) QA plans across three linacs and over a 6-month period. RESULTS: The AutoQA Builder application has been utilized clinically 322 times to create QA patients, construct phantom images, and deploy common periodic QA tests across multiple institutions, linear accelerators, and physicists. Comparing the AutoQA Analysis results with our current institutional QA standard the mean difference of the ratio of intensity values within the field-matched junction and ball-bearing position detection was 0.012 ± 0.053 (P = 0.159) and is 0.011 ± 0.224 mm (P = 0.355), respectively. Analysis of VMAT QA plans resulted in a maximum percentage difference of 0.3%. CONCLUSION: The automated creation and analysis of quality assurance plans using multiple APIs can be of immediate benefit to linear accelerator quality assurance efficiency and standardization. QA plan creation can be done without following tedious procedures through API assistance, and analysis can be performed inside of the clinical OIS in an automated fashion.

Human-Machine Interface: Multiclass Classification by Machine Learning on 1D EOG Signals for the Control of an Omnidirectional Robot.

People with severe disabilities require assistance to perform their routine activities; a Human-Machine Interface (HMI) will allow them to activate devices that respond according to their needs. In this work, an HMI based on electrooculography (EOG) is presented, the instrumentation is placed on portable glasses that have the task of acquiring both horizontal and vertical EOG signals. The registration of each eye movement is identified by a class and categorized using the one hot encoding technique to test precision and sensitivity of different machine learning classification algorithms capable of identifying new data from the eye registration; the algorithm allows to discriminate blinks in order not to disturb the acquisition of the eyeball position commands. The implementation of the classifier consists of the control of a three-wheeled omnidirectional robot to validate the response of the interface. This work proposes the classification of signals in real time and the customization of the interface, minimizing the user's learning curve. Preliminary results showed that it is possible to generate trajectories to control an omnidirectional robot to implement in the future assistance system to control position through gaze orientation.

Sensitivity analysis of Monte Carlo model of a gantry-mounted passively scattered proton system.

PURPOSE: This study aimed to present guidance on the correlation between treatment nozzle and proton source parameters, and dose distribution of a passive double scattering compact proton therapy unit, known as Mevion S250. METHODS: All 24 beam options were modeled using the MCNPX MC code. The calculated physical dose for pristine peak, profiles, and spread out Bragg peak (SOBP) were benchmarked with the measured data. Track-averaged LET (LETt ) and dose-averaged LET (LETd ) distributions were also calculated. For the sensitivity investigations, proton beam line parameters including Average Energy (AE), Energy Spread (ES), Spot Size (SS), Beam Angle (BA), Beam Offset (OA), and Second scatter Offset (SO) from central Axis, and also First Scatter (FS) thickness were simulated in different stages to obtain the uncertainty of the derived results on the physical dose and LET distribution in a water phantom. RESULTS: For the physical dose distribution, the MCNPX MC model matched measurements data for all the options to within 2 mm and 2% criterion. The Mevion S250 was found to have a LETt between 0.46 and 8.76 keV.µm-1 and a corresponding LETd between 0.84 and 15.91 keV.µm-1 . For all the options, the AE and ES had the greatest effect on the resulting depth of pristine peak and peak-to-plateau ratio respectively. BA, OA, and SO significantly decreased the flatness and symmetry of the profiles. The LETs were found to be sensitive to the AE, ES, and SS, especially in the peak region. CONCLUSIONS: This study revealed the importance of considering detailed beam parameters, and identifying those that resulted in large effects on the physical dose distribution and LETs for a compact proton therapy machine.

Automated and robust beam data validation of a preconfigured ring gantry linear accelerator using a 1D tank with synchronized beam delivery and couch motions.

PURPOSE: To develop an efficient and automated methodology for beam data validation for a preconfigured ring gantry linear accelerator using scripting and a one-dimensional (1D) tank with automated couch motions. MATERIALS AND METHODS: Using an application programming interface, a program was developed to allow the user to choose a set of beam data to validate with measurement. Once selected the program generates a set of instructions for radiation delivery with synchronized couch motions for the linear accelerator in the form of an extensible markup language (XML) file to be delivered on the ring gantry linear accelerator. The user then delivers these beams while measuring with the 1D tank and data logging electrometer. The program also automatically calculates this set of beams on the measurement geometry within the treatment planning system (TPS) and extracts the corresponding calculated dosimetric data for comparison to measurement. Once completed the program then returns a comparison of the measurement to the predicted result from the TPS to the user and prints a report. In this work lateral, longitudinal, and diagonal profiles were taken for fields sizes of 6 × 6, 8 × 8, 10 × 10, 20 × 20, and 28 × 28 cm2 at depths of 1.3, 5, 10, 20, and 30 cm. Depth dose profiles were taken for all field sizes. RESULTS: Using this methodology, the TPS was validated to agree with measurement. All compared points yielded a gamma value less than 1 for a 1.5%/1.5 mm criteria (100% passing rate). Off axis profiles had >98.5% of data points producing a gamma value <1 with a 1%/1 mm criteria. All depth profiles produced 100% of data points with a gamma value <1 with a 1%/1 mm criteria. All data points measured were within 1.5% or 2 mm distance to agreement. CONCLUSIONS: This methodology allows for an increase in automation in the beam data validation process. Leveraging the application program interface allows the user to use a single system to create the measurement files, predict the result, and then compare to actual measurement increasing efficiency and reducing the chance for user input errors.

A Monte Carlo based analytic model of the in-room neutron ambient dose equivalent for a Mevion gantry-mounted passively scattered proton system.

The goal of this study was to develop a Monte Carlo (MC)-based analytical model that can predict the in-room ambient dose equivalent from a Mevion gantry-mounted passively scattered proton system. The Mevion S250 and treatment vault were simulated using the MCNPX MC code. The results of the in-room neutron dose measurements, using an FHT 762 WENDI-II detector, were employed to benchmark the MC-derived values. After tuning the MCNPX MC code, for the same beam delivery parameters, the code was used to calculate the neutron spectra and ambient dose equivalent in the vault and at varying angles from the isocenter. Then, based on the calculations, an analytical model was reconstructed and data were fitted to derive the model parameters at 95% confidence intervals (CI). The MCNPX codes were tuned to within about 19% of the measured values for most of the measurements in the vault. For the maze, up to 0.08 mSv Gy-1 discrepancies were found between the experimental measurements and MCNPX calculated results. The analytical model showed up to 18% discrepancy for distances between 100 and 600 cm from the isocenter compared to the MC calculations. The model may underestimate the neutron ambient dose equivalent up to 21% for distances less than 100 cm from the isocenter. The proposed analytical model can be used to estimate the contribution of the secondary neutron dose from the Mevion S250 for the design of local shielding inside the proton therapy treatment vault.

High-sensitivity imaging and quantification of intratumoral distributions of gold nanoparticles using a benchtop x-ray fluorescence imaging system.

A high-sensitivity benchtop x-ray fluorescence (XRF) imaging system, based on a high-power x-ray source and silicon drift detector, has been developed. This system allows gold L-shell XRF-based quantitative imaging of gold nanoparticles (GNPs) at concentrations as low as 0.007 mg/cm3 (7 ppm) in biological tissues/water. Its capability for biomedical applications was demonstrated by imaging the GNP distribution within a small (∼12×11×2 mm3) ex vivo sample (extracted from a murine tumor after intravenous GNP administration). The results suggest direct translatability for routine preclinical ex vivo imaging tasks involving GNPs, as well as the possibility for in vivo imaging of small/superficial animal tumors.

Technical Note: Monte Carlo calculations of the AAPM TG-43 brachytherapy dosimetry parameters for a new titanium-encapsulated Yb-169 source.

Due to a number of distinct advantages resulting from the relatively low energy gamma ray spectrum of Yb-169, various designs of Yb-169 sources have been developed over the years for brachytherapy applications. Lately, Yb-169 has also been suggested as an effective and practical radioisotope option for a novel radiation treatment approach often known as gold nanoparticle-aided radiation therapy (GNRT). In a recently published study, the current investigators used the Monte Carlo N-Particle Version 5 (MCNP5) code to design a novel titanium-encapsulated Yb-169 source optimized for GNRT applications. In this study, the original MC source model was modified to accurately match the specifications of the manufactured Yb-169 source. The modified MC model was then used to obtain a complete set of the AAPM TG-43 parameters for the new titanium-encapsulated Yb-169 source. The MC-calculated dose rate constant for this titanium-encapsulated Yb-169 source was 1.19 ± 0.03 cGy·h-1·U-1, indicating no significant change from the values reported for stainless steel-encapsulated Yb-169 sources. The source anisotropy and radial dose function for the new source were also found similar to those reported for the stainless steel-encapsulated Yb-169 sources. The current results suggest that the use of titanium, instead of stainless steel, to encapsulate the Yb-169 core would not lead to any major change in the dosimetric characteristics of the Yb-169 source. The results also show that the titanium encapsulation of the Yb-169 source could be accomplished while meeting the design goals as described in the current investigators' published MC optimization study for GNRT applications.

Functional network disorganization and cognitive decline following fractionated whole-brain radiation in mice.

Cognitive dysfunction following radiotherapy (RT) is one of the most common complications associated with RT delivered to the brain, but the precise mechanisms behind this dysfunction are not well understood, and to date, there are no preventative measures or effective treatments. To improve patient outcomes, a better understanding of the effects of radiation on the brain's functional systems is required. Functional magnetic resonance imaging (fMRI) has shown promise in this regard, however, compared to neural activity, hemodynamic measures of brain function are slow and indirect. Understanding how RT acutely and chronically affects functional brain organization requires more direct examination of temporally evolving neural dynamics as they relate to cerebral hemodynamics for bridging with human studies. In order to adequately study the underlying mechanisms of RT-induced cognitive dysfunction, the development of clinically mimetic RT protocols in animal models is needed. To address these challenges, we developed a fractionated whole-brain RT protocol (3Gy/day for 10 days) and applied longitudinal wide field optical imaging (WFOI) of neural and hemodynamic brain activity at 1, 2, and 3 months post RT. At each time point, mice were subject to repeated behavioral testing across a variety of sensorimotor and cognitive domains. Disruptions in cortical neuronal and hemodynamic activity observed 1 month post RT were significantly worsened by 3 months. While broad changes were observed in functional brain organization post RT, brain regions most impacted by RT occurred within those overlapping with the mouse default mode network and other association areas similar to prior reports in human subjects. Further, significant cognitive deficits were observed following tests of novel object investigation and responses to auditory and contextual cues after fear conditioning. Our results fill a much-needed gap in understanding the effects of whole-brain RT on systems level brain organization and how RT affects neuronal versus hemodynamic signaling in the cortex. Having established a clinically-relevant injury model, future studies can examine therapeutic interventions designed to reduce neuroinflammation-based injury following RT. Given the overlap of sequelae that occur following RT with and without chemotherapy, these tools can also be easily incorporated to examine chemotherapy-related cognitive impairment.

A Pilot Study of Simulation-Free Hippocampal-Avoidance Whole Brain Radiation Therapy Using Diagnostic MRI-Based and Online Adaptive Planning.

PURPOSE: We aimed to demonstrate the clinical feasibility and safety of simulation-free hippocampal avoidance whole brain radiation therapy (HA-WBRT) in a pilot study (National Clinical Trial 05096286). METHODS AND MATERIALS: Ten HA-WBRT candidates were enrolled for treatment on a commercially available computed tomography (CT)-guided linear accelerator with online adaptive capabilities. Planning structures were contoured on patient-specific diagnostic magnetic resonance imaging (MRI), which were registered to a CT of similar head shape, obtained from an atlas-based database (AB-CT). These patient-specific diagnostic MRI and AB-CT data sets were used for preplan calculation, using NRG-CC001 constraints. At first fraction, AB-CTs were used as primary data sets and deformed to patient-specific cone beam CTs (CBCT) to give patient-matched density information. Brain, ventricle, and brain stem contours were matched through rigid translation and rotation to the corresponding anatomy on CBCT. Lens, optic nerve, and brain contours were manually edited based on CBCT visualization. Preplans were then reoptimized through online adaptation to create final, simulation-free plans, which were used if they met all objectives. Workflow tasks were timed. In addition, patients underwent CT-simulation to create immobilization devices and for prospective dosimetric comparison of simulation-free and simulation-based plans. RESULTS: Median time from MRI importation to completion of "preplan" was 1 weekday (range, 1-4). Median on-table workflow duration was 41 minutes (range, 34-70). NRG-CC001 constraints were achieved by 90% of the simulation-free plans. One patient's simulation-free plan failed a planning target volume coverage objective (89% instead of 90% coverage); this was deemed acceptable for first-fraction delivery, with an offline replan used for subsequent fractions. Both simulation-free and simulation CT-based plans otherwise met constraints, without clinically meaningful differences. CONCLUSIONS: Simulation-free HA-WBRT using online adaptive radiation therapy is feasible, safe, and results in dosimetrically comparable treatment plans to simulation CT-based workflows while providing convenience and time savings for patients.

Tracheal resection and anastomosis in postintubation tracheal stenosis: a systematic review.

Surgical resection of the stenotic segment with end-to-end anastomosis is considered the gold standard in postintubation tracheal stenosis. However, outcomes of this concrete aetiology are not well described. With the aim to examine the extent, range and characteristics of the existing evidence, a scoping review was performed. Data sources included MEDLINE, Scopus, Ovid and the Cochrane databases. Inclusion criteria consisted of studies in adult patients with postintubation tracheal stenosis that reported characteristics, surgical management and outcomes. A total of 125 articles were identified, of which 10 were included in the final analysis. All studies were case reports or case series (level 4 evidence) grouping 110 patients, 75 males and 35 females. The age ranged from 15 to 71 years. Cotton-Myer stenosis grade was 1 [1 (0.9%)], 2 [25 (22.7%)], 3 [70 (63.6%)] and 4 [14 (12.7%)]. Stenosis location was in the tracheal upper-third in 108 (98.2%), in the middle-third in 1 (0.9%) and in the lower-third in 1 (0.9%). Stenosis length ranged from 1 to 5.6 cm. Follow-up ranged from 1 to 60 months (2 years for the most). Most frequent complications were transitory dysphagia in 13 (11.3%), granuloma formation in 8 (7.3%), dehiscence or air leak in 5 (4.5%) and wound infection in 4 (3.6%). Restenosis rate ranged from 2% to 25%. There was no perioperative mortality. Tracheal resection and primary anastomosis in postintubation tracheal stenosis appear to be safe and effective in the short and mid-terms; however, the very low level of evidence found prevents definitive conclusions.

A Collaborative Platform for Advancing Automatic Interpretation in ECG Signals.

Numerous papers report the efficiency of the automatic interpretation capabilities of commercial algorithms. Unfortunately, these algorithms are proprietary, and academia has no means of directly contributing to these results. In fact, nothing at the same stage of development exists in academia. Despite the extensive research in ECG signal processing, from signal conditioning to expert systems, a cohesive single application for clinical use is not ready yet. This is due to a serious lack of coordination in the academic efforts, which involve not only algorithms for signal processing, but also the signal acquisition equipment itself. For instance, the different sampling rates and the different noise levels frequently found in the available signal databases can cause severe incompatibility problems when the integration of different algorithms is desired. Therefore, this work aims to solve this incompatibility problem by providing the academic community with a diagnostic-grade electrocardiograph. The intention is to create a new standardized ECG signals database in order to address the automatic interpretation problem and create an electrocardiography system that can fully assist clinical practitioners, as the proprietary systems do. Achieving this objective is expected through an open and coordinated collaboration platform for which a webpage has already been created.

In silico trial of simulation-free hippocampal-avoidance whole brain adaptive radiotherapy.

Background and Purpose: Hippocampal-avoidance whole brain radiotherapy (HA-WBRT) can be a time-consuming process compared to conventional whole brain techniques, thus potentially limiting widespread utilization. Therefore, we evaluated the in silico clinical feasibility, via dose-volume metrics and timing, by leveraging a computed tomography (CT)-based commercial adaptive radiotherapy (ART) platform and workflow in order to create and deliver patient-specific, simulation-free HA-WBRT. Materials and methods: Ten patients previously treated for central nervous system cancers with cone-beam computed tomography (CBCT) imaging were included in this study. The CBCT was the adaptive image-of-the-day to simulate first fraction on-board imaging. Initial contours defined on the MRI were rigidly matched to the CBCT. Online ART was used to create treatment plans at first fraction. Dose-volume metrics of these simulation-free plans were compared to standard-workflow HA-WBRT plans on each patient CT simulation dataset. Timing data for the adaptive planning sessions were recorded. Results: For all ten patients, simulation-free HA-WBRT plans were successfully created utilizing the online ART workflow and met all constraints. The median hippocampi D100% was 7.8 Gy (6.6-8.8 Gy) in the adaptive plan vs 8.1 Gy (7.7-8.4 Gy) in the standard workflow plan. All plans required adaptation at first fraction due to both a failing hippocampal constraint (6/10 adaptive fractions) and sub-optimal target coverage (6/10 adaptive fractions). Median time for the adaptive session was 45.2 min (34.0-53.8 min). Conclusions: Simulation-free HA-WBRT, with commercially available systems, was clinically feasible via plan-quality metrics and timing, in silico.

Initial clinical experience building a dual CT- and MR-guided adaptive radiotherapy program.

Introduction: Our institution was the first in the world to clinically implement MR-guided adaptive radiotherapy (MRgART) in 2014. In 2021, we installed a CT-guided adaptive radiotherapy (CTgART) unit, becoming one of the first clinics in the world to build a dual-modality ART clinic. Herein we review factors that lead to the development of a high-volume dual-modality ART program and treatment census over an initial, one-year period. Materials and Methods: The clinical adaptive service at our institution is enabled with both MRgART (MRIdian, ViewRay, Inc, Mountain View, CA) and CTgART (ETHOS, Varian Medical Systems, Palo Alto, CA) platforms. We analyzed patient and treatment information including disease sites treated, radiation dose and fractionation, and treatment times for patients on these two platforms. Additionally, we reviewed our institutional workflow for creating, verifying, and implementing a new adaptive workflow on either platform. Results: From October 2021 to September 2022, 256 patients were treated with adaptive intent at our institution, 186 with MRgART and 70 with CTgART. The majority (106/186) of patients treated with MRgART had pancreatic cancer, and the most common sites treated with CTgART were pelvis (23/70) and abdomen (20/70). 93.0% of treatments on the MRgART platform were stereotactic body radiotherapy (SBRT), whereas only 72.9% of treatments on the CTgART platform were SBRT. Abdominal gated cases were allotted a longer time on the CTgART platform compared to the MRgART platform, whereas pelvic cases were allotted a shorter time on the CTgART platform when compared to the MRgART platform. Our adaptive implementation technique has led to six open clinical trials using MRgART and seven using CTgART. Conclusions: We demonstrate the successful development of a dual platform ART program in our clinic. Ongoing efforts are needed to continue the development and integration of ART across platforms and disease sites to maximize access and evidence for this technique worldwide.

Cardiac radiation improves ventricular function in mice and humans with cardiomyopathy.

BACKGROUND: Rapidly dividing cells are more sensitive to radiation therapy (RT) than quiescent cells. In the failing myocardium, macrophages and fibroblasts mediate collateral tissue injury, leading to progressive myocardial remodeling, fibrosis, and pump failure. Because these cells divide more rapidly than cardiomyocytes, we hypothesized that macrophages and fibroblasts would be more susceptible to lower doses of radiation and that cardiac radiation could therefore attenuate myocardial remodeling. METHODS: In three independent murine heart failure models, including models of metabolic stress, ischemia, and pressure overload, mice underwent 5 Gy cardiac radiation or sham treatment followed by echocardiography. Immunofluorescence, flow cytometry, and non-invasive PET imaging were employed to evaluate cardiac macrophages and fibroblasts. Serial cardiac magnetic resonance imaging (cMRI) from patients with cardiomyopathy treated with 25 Gy cardiac RT for ventricular tachycardia (VT) was evaluated to determine changes in cardiac function. FINDINGS: In murine heart failure models, cardiac radiation significantly increased LV ejection fraction and reduced end-diastolic volume vs. sham. Radiation resulted in reduced mRNA abundance of B-type natriuretic peptide and fibrotic genes, and histological assessment of the LV showed reduced fibrosis. PET and flow cytometry demonstrated reductions in pro-inflammatory macrophages, and immunofluorescence demonstrated reduced proliferation of macrophages and fibroblasts with RT. In patients who were treated with RT for VT, cMRI demonstrated decreases in LV end-diastolic volume and improvements in LV ejection fraction early after treatment. CONCLUSIONS: These results suggest that 5 Gy cardiac radiation attenuates cardiac remodeling in mice and humans with heart failure. FUNDING: NIH, ASTRO, AHA, Longer Life Foundation.