Intraoperative radiation therapy with 50 kV x-rays: A multi-institutional review.

This report covers clinical implementation of a low kV intraoperative radiation therapy (IORT) program with the INTRABEAM® System (Carl Zeiss Meditec AG, Jena, Germany). Based on collective user experience from eight institutions, we discuss best methods of INTRABEAM quality assurance (QA) tests, commissioning measurements, clinical workflow, treatment planning, and potential avenues for research. The guide provides pertinent background information and clinical justification for IORT. It describes the INTRABEAM system and commissioning measurements along with a TG100 risk management analysis to ensure safety and accuracy of the IORT program. Following safety checks, dosimetry measurements are performed for verification of field flatness and symmetry, x-ray output, and depth dose. Also discussed are dose linearity checks, beam isotropy, ion chamber measurements, calibration protocols, and in-vivo dosimetry with optically stimulated luminescence dosimeters OSLDs, and radiochromic film. Emphasis is placed on the importance of routine QA procedures (daily, monthly, and annual) performed at regular intervals for a successful IORT program. For safe and accurate dose delivery, tests of important components of IORT clinical workflow are emphasized, such as, dose prescription, pre-treatment QA, treatment setup, safety checks, radiation surveys, and independent checks of delivered dose. Challenges associated with in-vivo dose measurements are discussed, along with special treatment procedures and shielding requirements. The importance of treatment planning in IORT is reviewed with reference to a Monte Carlo-based commercial treatment planning system highlighting its main features and limitations. The report concludes with suggested topics for research including CT-based image-guided treatment planning and improved prescription dose accuracy. We hope that this multi-institutional report will serve as a guidance document on the clinical implementation and use of INTRABEAM IORT.

Estimation and Prediction of Glucose Appearance Rate for Use in a Fully Closed-Loop Dual-Hormone Intraperitoneal Artificial Pancreas.

OBJECTIVE: A fully automated artificial pancreas requires a meal estimator and predictions of blood glucose levels (BGL) to handle disturbances during meal times, all without relying on manual meal announcements and user interventions. This study introduces a technique for estimating the glucose appearance rate (GAR) and predicting BGL in people with type 1 diabetes and insulin and glucagon administration. It is demonstrated for intraperitoneal insulin and glucagon delivery but may be adapted to other delivery sites. METHOD: The estimator is designed based on the moving horizon estimation (MHE) approach, where the underlying cost function incorporates prior statistical information on the GAR in subjects over the course of a day. The proposed prediction scheme is developed to predict GAR using estimated states and an intestinal model, which is then used to predict BGL with the help of an animal glucose metabolic model. RESULTS: The intraperitoneal dual-hormone estimator was evaluated on three anesthetized animals, achieving a 21.8% mean absolute percentage error (MAPE) for GAR estimation and a 10.0% MAPE for BGL prediction when the future GAR is known. For a 120-minute prediction horizon, the proposed predictor achieved an 18.0% MAPE for GAR and a 28.4% MAPE for BGL. CONCLUSION: The findings demonstrate the effectiveness and reliability of the proposed estimator and its potential for use in a fully automated artificial pancreas and reducing user interventions. SIGNIFICANCE: This study represents advancements toward the development of a fully automated artificial pancreas, ultimately enhancing the quality of life for people with type 1 diabetes.

Proposed Priorities for Low-Dose Radiation Research and Their Relevance to the Practice of Radiology.

Because ionizing radiation is widely used in medical imaging and in military, industry, and commercial applications, programmatic management and advancement in knowledge is needed, especially related to the health effects of low-dose radiation. The U.S. Congress in partnership with the U.S. Department of Energy called on the National Academies of Sciences, Engineering, and Medicine (NASEM) to develop a long-term strategic and prioritized agenda for low-dose radiation research. Low doses were defined as dose amounts less than 100 mGy or low-dose rates less than 5 mGy per hour. The 2022 NASEM report was divided into sections detailing the low-dose radiation exposure and health effects, scientific basis for radiation protection, status of low-dose radiation research, a prioritized radiation research agenda, and essential components of a low-dose radiation research program, including resources needed and recommendations for financial recourse. The purpose of this review is to summarize this report and examine the recommendations to assess how these pertain to the practice of radiology and medicine.

Intraoperative radiation therapy for locally advanced and recurrent head and neck cancer.

The purpose of the present study was to present a single institution experience with intraoperative radiation therapy (IORT) for patients with head and neck cancer (HNC). The present study included all patients with HNC treated consecutively with IORT at Loyola University Medical Center between January 2014 and December 2018. Charts were reviewed for patient and tumor characteristics, IORT technical details, IORT-induced adverse events and treatment outcomes. The study included 23 eligible patients. Median patient age was 66 years (range, 34-91 years). Tumor sites included the parotid gland (43%), lymph nodes (43%), oral tongue (9%) and ear (4%). A total of 48% of patients received IORT upfront with or without postoperative adjuvant external beam radiation therapy (EBRT), whereas 52% received salvage IORT after local tumor recurrence. The median prescribed IORT dose was 7.5 Gy (range, 5-14 Gy) in a single fraction prescribed to 5 mm depth with flat applicators (median diameter, 5 cm). A total of 92% of patients did not experience wound healing complications. One patient (4%) developed postoperative acute thromboembolic stroke and a second patient (4%) experienced protracted wound healing. At a median follow up of 36 months (range, 2-81 months), overall survival was 52%. In addition, 48% of patients were reported to have no evidence of disease, and although two had died of unrelated causes, 13% of patients were alive with disease and 39% died with the disease. The local-regional recurrence rate was 39% (median time to local recurrence, 11 months; range, 1-34 months), the rate of distant metastasis was 35% (median time to distant metastasis, 16 months; range, 4-40 months), and 21% of patients had both local-regional recurrence and distant metastases. The percentages of local-regional recurrence and distant metastases among patients receiving salvage IORT were 58 and 50% respectively, compared with 18 and 18% respectively in those receiving upfront IORT with or without adjuvant EBRT. In the present single institution retrospective study, it was concluded that IORT for patients with locally advanced and recurrent HNC was a safe treatment modality, with tumor control comparable to historical IORT data. Larger prospective studies are needed to further assess the utility of IORT in the management of locally advanced and recurrent HNC.

A Nonlinear State Observer for the Bi-Hormonal Intraperitoneal Artificial Pancreas.

Currently, continuous glucose monitoring sensors are used in the artificial pancreas to monitor blood glucose levels. However, insulin and glucagon concentrations in different parts of the body cannot be measured in real-time, and determining body glucagon sensitivity is not feasible. Estimating these states provides more information about the current system status, facilitating improved decision-making by the model-based controller. In this regard, the aim of this paper is to design a nonlinear high-gain observer for a bi-hormonal artificial pancreas in the presence of measurement noises, model uncertainties, and disturbances. The model used in the observer is based on an existing intraperitoneal nonlinear animal model in the literature. This model is modified by assuming that insulin can directly transfer from the peritoneal cavity to the bloodstream. Based on a set of realistic assumptions, one model is considered after each hormone infusion, and two observers are separately designed. The model is divided into the insulin-phase and glucagon-phase models based on a set of realistic assumptions. Thereafter, two high-gain observers are designed separately for these phases contributing to estimating the non-measurable states. The observer error is proven to be locally uniformly ultimately bounded, and it is verified that any asymptotically stable control laws remain stable in the presence of the observer. The performance of the observers with different gains is evaluated for a scenario with multiple insulin and glucagon infusions. The proposed observer converges to a finite error, according to the results. Clinical relevance- In Type 1 diabetic patients, the developed observer can be employed in a closed-loop artificial pan-creas to improve the performance of model-based controllers. It estimates the key states, which are necessary for forecasting the body's response to insulin and glucagon boluses.

Retrospective Clinical Evaluation of a Decision-Support Software for Adaptive Radiotherapy of Head and Neck Cancer Patients.

Purpose: This study aimed to evaluate the clinical need for an automated decision-support software platform for adaptive radiation therapy (ART) of head and neck cancer (HNC) patients. Methods: We tested RTapp (SegAna), a new ART software platform for deciding when a treatment replan is needed, to investigate a set of 27 HNC patients' data retrospectively. For each fraction, the software estimated key components of ART such as daily dose distribution and cumulative doses received by targets and organs at risk (OARs) from daily 3D imaging in real-time. RTapp also included a prediction algorithm that analyzed dosimetric parameter (DP) trends against user-specified thresholds to proactively trigger adaptive re-planning up to four fractions ahead. The DPs evaluated for ART were based on treatment planning dose constraints. Warning (V95<95%) and adaptation (V95<93%) thresholds were set for PTVs, while OAR adaptation dosimetric endpoints of +10% (DE10) were set for all Dmax and Dmean DPs. Any threshold violation at end of treatment (EOT) triggered a review of the DP trends to determine the threshold-crossing fraction Fx when the violations occurred. The prediction model accuracy was determined as the difference between calculated and predicted DP values with 95% confidence intervals (CI95). Results: RTapp was able to address the needs of treatment adaptation. Specifically, we identified 18/27 studies (67%) for violating PTV coverage or parotid Dmean at EOT. Twelve PTVs had V95<95% (mean coverage decrease of -6.8 ± 2.9%) including six flagged for adaptation at median Fx = 6 (range, 1-16). Seventeen parotids were flagged for exceeding Dmean dose constraints with a median increase of +2.60 Gy (range, 0.99-6.31 Gy) at EOT, including nine with DP>DE10. The differences between predicted and calculated PTV V95 and parotid Dmean was up to 7.6% (mean ± CI95, -2.7 ± 4.1%) and 5 Gy (mean ± CI95, 0.3 ± 1.6 Gy), respectively. The most accurate predictions were obtained closest to the threshold-crossing fraction. For parotids, the results showed that Fx ranged between fractions 1 and 23, with a lack of specific trend demonstrating that the need for treatment adaptation may be verified for every fraction. Conclusion: Integrated in an ART clinical workflow, RTapp aids in predicting whether specific treatment would require adaptation up to four fractions ahead of time.

Reinforcement Learning-Based Tracking Control of USVs in Varying Operational Conditions.

We present a reinforcement learning-based (RL) control scheme for trajectory tracking of fully-actuated surface vessels. The proposed method learns online both a model-based feedforward controller, as well an optimizing feedback policy in order to follow a desired trajectory under the influence of environmental forces. The method's efficiency is evaluated via simulations and sea trials, with the unmanned surface vehicle (USV) ReVolt performing three different tracking tasks: The four corner DP test, straight-path tracking and curved-path tracking. The results demonstrate the method's ability to accomplish the control objectives and a good agreement between the performance achieved in the Revolt Digital Twin and the sea trials. Finally, we include an section with considerations about assurance for RL-based methods and where our approach stands in terms of the main challenges.

Spectral characterization of tissues in high spectral and spatial resolution MR images: Implications for a classification-based synthetic CT algorithm.

PURPOSE: To characterize the spectral parameters of tissues with high spectral and spatial resolution magnetic resonance images to be used as a foundation for a classification-based synthetic CT algorithm. METHODS: A phantom was constructed consisting of a section of fresh beef leg with bone embedded in 1% agarose gel. The high spectral and spatial (HiSS) resolution MR imaging sequence used had 1.0 mm in-plane resolution and 11.1 Hz spectral resolution. This sequence was used to image the phantom and one patient. Post-processing was performed off-line with IDL and included Fourier transformation of the time-domain data, labeling of fat and water peaks, and fitting the magnitude spectra with Lorentzian functions. Images of the peak height and peak integral of both the water and fat resonances were generated and analyzed. Several regions-of-interest (ROIs) were identified in phantom: bone marrow, cortical bone, adipose tissue, muscle, agar gel, and air; in the patient, no agar gel was present but an ROI of saline in the bladder was analyzed. All spectra were normalized by the noise within each voxel; thus, all parameters are reported in terms of signal-to-noise (SNR). The distributions of tissue spectral parameters were analyzed and scatterplots generated. Water peak height in cortical bone was compared to air using a nonparametric t-test. Composition of the various ROIs in terms of water, fat, or fat and water was also reported. RESULTS: In phantom, the scatterplot of peak height (water versus fat) showed good separation of bone marrow and adipose tissue. Water versus fat integral scatterplot showed better separation of muscle and cortical bone than the peak height scatterplot. In the patient data, the distributions of water and fat peak heights were similar to that in phantom, with more overlap of bone marrow and cortical bone than observed in phantom. The relationship between bone marrow and cortical bone for peak integral was better separated than those of peak heights in the patient data. For both the phantom and patient, there was a significant amount of overlap in spectral parameters of cortical bone versus air. CONCLUSION: These results show promising results for utilizing HiSS imaging in a classification-based synthetic CT algorithm. Cortical bone and air overlap was expected due to the short T2* of bone; reducing early echo times would improve the SNR in bone and image data from these early echoes could help differentiate these tissue types. Further studies need to be done with the goal of better separation of air and bone, and to extend the concept to volumetric imaging before it can be clinically applied.

A novel surrogate to identify anatomical changes during radiotherapy of head and neck cancer patients.

PURPOSE: To develop a novel method to monitor external anatomical changes in head and neck cancer patients in order to triage possible adaptive radiotherapy needs. METHODS: The presented approach aims to provide information on internal anatomical changes based on variations observed in external anatomy. Setup Cone Beam Computed Tomography (CBCT) images are processed to produce an accurate external contour of the patient's skin. After registering the CBCTs to the reference planning CT, the external contours from each CBCT are transferred to the initial - first week - CBCT. Contour radii, defined as the distances between an external contour and the isocenter projection in each CBCT slice, are calculated for each scan over the full 360 degrees. The changes in external anatomy are then quantified by the difference in radial distance between the external contours of any secondary CBCT relative to the initial CBCT. Finally, the radial difference is displayed in cylindrical coordinates as a 2D intensity map to highlight regions of interests with significant changes. Weekly CBCT scans from 15 head and neck patients were retrospectively analyzed to demonstrate the utility of this approach as a proof of principle. External changes suggested by the 2D radial difference map of an example patient after 23 fractions were then correlated with the changes in the gross tumor volumes and organs at risks. The resulting dosimetric effects were evaluated. An interactive standalone software application has been developed to facilitate the generation and the interpretation of the 2D intensity map. RESULTS: The 2D radial difference maps provided qualitative and quantitative information, such as the location and the magnitude of external contour changes and the rate at which these deviations occur. Out of the 15 patients, 10 presented clear evidence of general external volume shrinkage due to weight loss, and nine patients had at least one site of local shrinkage. Only two patients showed no signs of anatomical change during their entire treatment course. For the example patient, the mean (±σ) radial difference was 6.7 (±3.0) mm for the left parotid and 7.3 (±2.5) mm for the right parotid. The mean dose to the left and right parotids increased from 20.1 Gy to 30 Gy and from 16.3 Gy to 29.6 Gy, respectively. CONCLUSION: This novel method provides an efficient tool to visualize 3D external anatomical changes on a single 2D map. It quickly pinpoints the location of differences in anatomy during the course of radiotherapy, which can help physicians determine if a treatment plan needs to be adapted. The interactive graphic user interface developed in this study will be evaluated in an adaptive radiotherapy workflow for head and neck patients in a future prospective trial.