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Cervical cancer radiotherapy is often complicated by significant variability in the quality and consistency of treatment plans. Knowledge-based planning (KBP), which utilizes prior patient data to correlated achievable optimal dosimetry with patient-specific anatomy, has demonstrated promise as a quality control tool for controlling this variability, with consequences for patient outcomes, as well as for the reliability of data from multi-institutional clinical trials. In this article we highlight the application of KBP-based quality control to cervical cancer radiotherapy. We discuss the potential impact of KBP on multi-institutional clinical trials to standardize cervical cancer treatment planning across diverse clinics, and discuss challenges and progress in the implementation of KBP for brachytherapy treatment planning. Additionally, we briefly discuss secondary applications of KBP for cervical cancer. The emerging picture from these studies indicates several exciting opportunities for increasing the utilization of KBP in day-to-day cervical cancer radiotherapy. [ABSTRACT FROM AUTHOR]

To establish a framework for the evaluation of knowledge-based planning routines that empowers new adopters to select systems that best match their clinical priorities. We demonstrate the power of this framework using 4 publicly available prostate routines. Four publicly available prostate routines (CCMB, Miami, UCSD, WUSTL) were automatically applied across a 25-patient cohort using Eclipse scripting and a PTV prescription of V81 Gy = 95%. The institutions' routines differed in contouring guidelines for planning target volume (PTV) and organs at risk, beam arrangements, and optimization parameters. Model-estimated dose-volume histograms (DVHs) and deliverable postoptimization DVHs were extracted from plans to calculate average DVHs for each routine. Each routine's average calculated DVH was subtracted from the average DVH for all plans and from the model's average predicted DVH for comparison. DVH metrics for PTV (DMAX, D1%, D99%, DMIN), Rectum (DMAX, V70, V60, V40), Bladder (V75, V40), Femur (DMAX), and PenileBulb (DMEAN) were compared with the average using 2-sided paired t tests (Bonferroni-corrected P <.05). To control for contouring effects, the full analysis was conducted for 2 PTV margin schemas: 5 mm uniform and 3 mm or 7 mm posterior/else. Calculated plans generally aligned with their routine's DVH estimations, except CCMB organ-at-risk Dmaxes. Dosimetric parameter differences were not significant, with the exception of PTV DMAX (Miami = 111.1% [ P <.001]), PTV D99% (Miami = 97.4% [ P =.05]; UCSD = 97.4% [ P =.03]; CCMB = 98.5% [ P =.001]), Rectum V40 (Miami = 19.1% [ P <.001]; UCSD = 22.7% [ P =.003]; CCMB = 53.5% [ P <.001]), and Femur DMAX (WUSTL = 48.6% [ P =.001.]; CCMB = 37.9% [ P <.001]). Overall, UCSD and Miami had lower rectum doses, and CCMB and WUSTL had higher PTV homogeneity. Conclusions were unchanged with different PTV margin schemas. Using publicly available knowledge-based planning routines spares clinicians substantial effort in developing new models. Our results allow clinicians to select the prostate routine that matches their clinical priorities, and our methodology sets the precedent for comparing routines for different treatment sites. [ABSTRACT FROM AUTHOR]

The application of big data to the quality assurance of radiation therapy is multifaceted. Big data can be used to detect anomalies and suboptimal quality metrics through both statistical means and more advanced machine learning and artificial intelligence. The application of these methods to clinical practice is discussed through examples of guideline adherence, contour integrity, treatment delivery mechanics, and treatment plan quality. The ultimate goal is to apply big data methods to direct measures of patient outcomes for care quality. The era of big data and machine learning is maturing and the implementation for quality assurance promises to improve the quality of care for patients. [ABSTRACT FROM AUTHOR]

The "treatment planning" component of managing a radiotherapy patient currently consumes hours, even days, of human effort. The time and workforce demands of the current planning paradigm can expose patients to delays and potentially substandard treatments, all while standing as seemingly insurmountable roadblocks to adaptive radiotherapy. Automating the treatment planning process is not a new idea, but recent advances have shown that automated planning might finally be turning the corner from niche research endeavor to a standard clinical practice. In this Seminar, we will examine the current state of automated radiotherapy planning, taking particular care to consider the most critical component of the planning problem: how to generate high-quality treatment solutions that account for patient-to-patient anatomical variation. Recommendations for testing and validating automated planning routines will be discussed, as well as potential drawbacks that might persist even after robust validation has been conducted. [ABSTRACT FROM AUTHOR]

Knowledge-based planning (KBP) clinical implementation necessitates significant upfront effort, even within a single disease site. The purpose of this study was to demonstrate an efficient method for clinicians to assess the noninferiority of KBP across multiple disease sites and estimate any systematic dosimetric differences after implementation. We sought to establish these endpoints in a plurality of previously treated patients (validation set) with both closed-loop (training set overlapping validation set) and open-loop (independent training set) KBP routines. We identified 53 prostate, 24 prostatic fossa, 54 hypofractionated lung, and 52 head and neck patients treated with volumetric modulated arc therapy in the year directly preceding our clinic's broad adoption of RapidPlan (Varian Medical Systems, Palo Alto, CA). Using the Varian Eclipse Scripting API, our program takes as input a list of patients, then performs semiautomated structure matching, fully automated RapidPlan-driven optimization, and plan comparison. All plans were normalized to the planning target volume (PTV) D 95% = 100%. Dose metric differences (ΔD x = D x,clinical − D x,KBP) were computed for standard PTV and organ-at-risk (OAR) dose-volume histogram parameters across disease sites. A 2-tailed paired t test quantified statistical significance (P <.001). Statistically significant organ dose-volume histogram improvements were observed in the KBP cohort: the rectum, bladder, and penile bulb in prostate/prostatic fossa; and the larynx, esophagus, cricopharyngeus, parotid glands, and cochlea in head and neck. No OAR dose metric was statistically worse in any KBP sample. PTV ΔD 1% increases in prostatic fossa were deemed acceptable given organ-sparing gains. PTV ΔD 1% and internal target volume ΔD 99% increase for the lung was by design owing to the prescription normalization variance in the pre-KBP lung sample. Our automated method showed multiple disease sites' KBP routines to be noninferior to manual planning, with statistically significant superiority in some aspects of OAR sparing. This method is applicable to any institution implementing either closed-loop or open-loop KBP autoplanning routines. [ABSTRACT FROM AUTHOR]

This paper studies the robust convergence properties of iterative learning control (ILC) for single-input, single-output (SISO), nonrepetitive systems subject to iteration-dependent uncertainties that arise in not only initial states and external disturbances but also plant models. Given an extended relative degree condition, it is possible to propose necessary and sufficient (NAS) conditions for robust ILC convergence. The tracking error bound is shown to depend continuously on the bounds of the iteration-dependent uncertainties. When the iteration-dependent uncertainties are bounded, NAS conditions exist to guarantee bounded system trajectories and output tracking error. If the iteration-dependent uncertainties converge, then NAS conditions ensure bounded system trajectories and zero output tracking error. The results are also extended to a class of affine nonlinear systems satisfying a Lipschitz condition. Simulation tests on a representative batch process demonstrate the validity of the obtained robust ILC convergence results. [ABSTRACT FROM AUTHOR]

This paper studies a class of robust cooperative learning control problems for directed networks of agents (a) with nonidentical nonlinear dynamics that do not satisfy a global Lipschitz condition and (b) in the presence of switching topologies, initial state shifts and external disturbances. All uncertainties are not only time-varying but also iteration-varying. It is shown that the relative formation of nonlinear agents achieved via cooperative learning can be guaranteed to converge to the desired formation exponentially fast as the number of iterations increases. A necessary and sufficient condition for exponential convergence of the cooperative learning process is that at each time step, the network topology graph of nonlinear agents can be rendered quasi-strongly connected through switching along the iteration axis. Simulation tests illustrate the effectiveness of our proposed cooperative learning results in refining arbitrary high precision relative formation of nonlinear agents. [ABSTRACT FROM AUTHOR]

Motivated by the prototypical problem of a marching band, this paper studies a class of multi-agent formation problems characterized by two features: (i) the agents attempt to complete a finite duration, coordinated formation task with high precision by repeating the task and (ii) the feedback mechanism by which the agents control their motions is based on relative differences between nearest neighbors, but the underlying graph topology can vary both during a repetition and from one repetition to the next. Adopting the framework of iterative learning control leads to the notion of multi-agent networks with switching topologies along two directions: a finite time axis and an infinite iteration axis. For such systems, we present distributed algorithms using nearest neighbor information whose exponential convergence can be demonstrated. It is shown that as the number of repetition increases, the relative formation between agents approaches the desired formation exponentially fast if and only if at each time step, the union of the interaction graphs has a spanning tree frequently enough along the iteration axis. That is, the agents can “learn to cooperate.” The remarkable point of this result is that it is not necessary to have a spanning tree at any specific time step or iteration in order for the system to converge. Two examples are given to illustrate the ideas, including a general example, where through iteration the agents can form a desired formation, and a special case of it, where an additional agent specifies a reference to regulate the formation shape simultaneously. [ABSTRACT FROM AUTHOR]

Background and purpose Neurocognitive decline in brain tumor patients treated with radiotherapy (RT) may be linked to cortical atrophy. We developed models to determine radiation treatment-planning objectives for cortex, which were tested on a sample population to identify the dosimetric cost of cortical sparing. Material and methods The relationship between the probability of cortical atrophy in fifteen high-grade glioma patients at 1-year post-RT and radiation dose was fit using logistic mixed effects modeling. Cortical sparing was implemented using two strategies: region-specific sparing using model parameters, and non-specific sparing of all normal brain tissue. Results A dose threshold of 28.6 Gy was found to result in a 20% probability of severe atrophy. Average cortical sparing at 30 Gy was greater for region-specific dose avoidance (4.6%) compared to non-specific (3.6%). Cortical sparing resulted in an increase in heterogeneity index of the planning target volume (PTV) with an average increase of 1.9% (region-specific) and 0.9% (non-specific). Conclusions We found RT doses above 28.6 Gy resulted in a greater than 20% probability of cortical atrophy. Cortical sparing can be achieved using region-specific or non-specific dose avoidance strategies at the cost of an increase in the dose heterogeneity of the PTV. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this study was to quantify the frequency and clinical severity of quality deficiencies in intensity modulated radiation therapy (IMRT) planning in the Radiation Therapy Oncology Group 0126 protocol. Methods and Materials A total of 219 IMRT patients from the high-dose arm (79.2 Gy) of RTOG 0126 were analyzed. To quantify plan quality, we used established knowledge-based methods for patient-specific dose-volume histogram (DVH) prediction of organs at risk and a Lyman-Kutcher-Burman (LKB) model for grade ≥2 rectal complications to convert DVHs into normal tissue complication probabilities (NTCPs). The LKB model was validated by fitting dose-response parameters relative to observed toxicities. The 90th percentile (22 of 219) of plans with the lowest excess risk (difference between clinical and model-predicted NTCP) were used to create a model for the presumed best practices in the protocol (pDVH 0126,top10% ). Applying the resultant model to the entire sample enabled comparisons between DVHs that patients could have received to DVHs they actually received. Excess risk quantified the clinical impact of suboptimal planning. Accuracy of pDVH predictions was validated by replanning 30 of 219 patients (13.7%), including equal numbers of presumed “high-quality,” “low-quality,” and randomly sampled plans. NTCP-predicted toxicities were compared to adverse events on protocol. Results Existing models showed that bladder-sparing variations were less prevalent than rectum quality variations and that increased rectal sparing was not correlated with target metrics (dose received by 98% and 2% of the PTV, respectively). Observed toxicities were consistent with current LKB parameters. Converting DVH and pDVH 0126,top10% to rectal NTCPs, we observed 94 of 219 patients (42.9%) with ≥5% excess risk, 20 of 219 patients (9.1%) with ≥10% excess risk, and 2 of 219 patients (0.9%) with ≥15% excess risk. Replanning demonstrated the predicted NTCP reductions while maintaining the volume of the PTV receiving prescription dose. An equivalent sample of high-quality plans showed fewer toxicities than low-quality plans, 6 of 73 versus 10 of 73 respectively, although these differences were not significant ( P =.21) due to insufficient statistical power in this retrospective study. Conclusions Plan quality deficiencies in RTOG 0126 exposed patients to substantial excess risk for rectal complications. [ABSTRACT FROM AUTHOR]

Purpose The objective of this study was to create a workflow for the automation and standardization of treatment plan generation and evaluation using an application programming interface (API) to access data from a commercial treatment planning system (Varian Medical Systems, Inc, Palo Alto, CA). Methods and materials The automation workflow begins with converting electronic patient-specific physician treatment planning orders that specify demographics, simulation instructions, and dosimetric objectives for targets and organs at risk into XML files. These XML files are used to generate standard contour names, beam, and patient-specific intensity modulated radiation therapy (IMRT) optimization templates to be executed in a commercial treatment planning system (TPS) by the user. A set of computer programs have been developed to provide quality control (QC) reports that verify demographic information in the TPS against the treatment planning orders, ensure the existence and proper naming of organs at risk, and generate patient-specific plan evaluation reports that provide real-time feedback on the concordance of an active treatment plan to the physician-specified treatment planning goals. Results A workflow for lung IMRT was chosen as a test scenario. Contour, beam, and patient-specific IMRT optimization templates were automatically generated from the physician treatment planning orders and loaded into the planning system. The QC reports were developed for lung IMRT, including the option of patient-specific modifications to the standard templates. The API QC reporting includes a dynamic program that runs in parallel to the TPS during the planning process, providing real-time feedback as to whether physician-specified treatment plan parameters have improved or worsened from previous iterations. Conclusions User-created computer programs to access information in the TPS database by means of a commercial TPS API enable automation and standardization of treatment plan generation and evaluation. [ABSTRACT FROM AUTHOR]

Despite many studies over the last 3 decades that have attempted to explicitly quantify the decision-making process for radiotherapy treatment plan evaluation, judgments of an individual plan''s degree of quality are still largely subjective and can show inter- and intra-practitioner variability even if the clinical treatment goals are the same. Several factors conspire to confound the full quantification of treatment plan quality, including uncertainties in dose response of cancerous and normal tissue, the rapid pace of new technology adoption, and the human component of treatment planning. However, new developments in clinical informatics and automation are lowering the bar for developing and implementing quantitative metrics into the treatment planning process. This review discusses general strategies for using quantitative metrics in the treatment planning process and presents a case study in intensity-modulated radiation therapy planning whereby control was established on a variable system via such techniques. [Copyright &y& Elsevier]

Purpose: To incorporate a quality control tool, according to previous planning experience and patient-specific anatomic information, into the intensity-modulated radiotherapy (IMRT) plan generation process and to determine whether the tool improved treatment plan quality. Methods and Materials: A retrospective study of 42 IMRT plans demonstrated a correlation between the fraction of organs at risk (OARs) overlapping the planning target volume and the mean dose. This yielded a model, predicted dose = prescription dose (0.2 + 0.8 [1 − exp(−3 overlapping planning target volume/volume of OAR)]), that predicted the achievable mean doses according to the planning target volume overlap/volume of OAR and the prescription dose. The model was incorporated into the planning process by way of a user-executable script that reported the predicted dose for any OAR. The script was introduced to clinicians engaged in IMRT planning and deployed thereafter. The script’s effect was evaluated by tracking δ = (mean dose-predicted dose)/predicted dose, the fraction by which the mean dose exceeded the model. Results: All OARs under investigation (rectum and bladder in prostate cancer; parotid glands, esophagus, and larynx in head-and-neck cancer) exhibited both smaller δ and reduced variability after script implementation. These effects were substantial for the parotid glands, for which the previous δ = 0.28 ± 0.24 was reduced to δ = 0.13 ± 0.10. The clinical relevance was most evident in the subset of cases in which the parotid glands were potentially salvageable (predicted dose <30 Gy). Before script implementation, an average of 30.1 Gy was delivered to the salvageable cases, with an average predicted dose of 20.3 Gy. After implementation, an average of 18.7 Gy was delivered to salvageable cases, with an average predicted dose of 17.2 Gy. In the prostate cases, the rectum model excess was reduced from δ = 0.28 ± 0.20 to δ = 0.07 ± 0.15. On surveying dosimetrists at the end of the study, most reported that the script both improved their IMRT planning (8 of 10) and increased their efficiency (6 of 10). Conclusions: This tool proved successful in increasing normal tissue sparing and reducing interclinician variability, providing effective quality control of the IMRT plan development process. [Copyright &y& Elsevier]

Abstract: This paper presents a stability analysis of the iterative learning control (ILC) problem for discrete-time systems when the plant Markov parameters are subject to interval uncertainty. Using the so-called super-vector approach to ILC, vertex impulse response matrices are employed to develop sufficient conditions for both asymptotic stability and monotonic convergence of the ILC process. It is shown that the stability of such interval ILC systems can be determined by checking the stability of the system using only the vertex points of the interval Markov parameters. [Copyright &y& Elsevier]

Abstract: In iterative learning control schemes for linear discrete time systems, conditions to guarantee the monotonic convergence of the tracking error norms are derived. By using the Markov parameters, it is shown in the time-domain that there exists a non-increasing function such that when the properly chosen constant learning gain is multiplied by this function, the convergence of the tracking error norms is monotonic, without resort to high-gain feedback. [Copyright &y& Elsevier]

Examines the biology and enzymology of protein tyrosine O-sulfation. Substrate specificity of tyrosylprotein and sulfotransferases; Two types of tyrosylprotein sulfotransferase; Regulation of tyrosine O-sulfation; Role of tyrosine O-sulfation in protein function.

The omni-directional inspection system (ODIS) is a small, man-portable mobile robotic system that can be used for autonomous or semi-autonomous inspection under vehicles in a parking area. Customers for such a system include military police (MP) and other law enforcement and security entities. The robot features three “smart wheels” in which both the speed and direction of the wheel can be independently controlled and a vehicle electronic capability that includes multiple processors and a sensor array with a laser, sonar and IR sensors, and a video camera. ODIS employs a novel parameterized command language for intelligent behavior generation. A key feature of the ODIS control system is the use of an object recognition system that fits models to sensor data. These models are then used as input parameters to the motion and behavior control commands. [Copyright &y& Elsevier]

By using Lambert function, the analytical stability bound is obtained in this paper for delayed second-order systems with repeatable poles. An example is presented to illustrate the obtained analytical result. [Copyright &y& Elsevier]

Consistency of nomenclature within radiation oncology is increasingly important as big data efforts and data sharing become more feasible. Automation of radiation oncology workflows depends on standardized contour nomenclature that enables toxicity and outcomes research, while also reducing medical errors and facilitating quality improvement activities. Recommendations for standardized nomenclature have been published in the American Association of Physicists in Medicine (AAPM) report from Task Group 263 (TG-263). Transitioning to TG-263 requires creation and management of structure template libraries and retraining of staff, which can be a considerable burden on clinical resources. Our aim is to develop a program that allows users to create TG-263–compliant structure templates in English, Spanish, or French to facilitate data sharing. Fifty-three premade structure templates were arranged by treated organ based on an American Society for Radiation Oncology (ASTRO) consensus paper. Templates were further customized with common target structures, relevant organs at risk (OARs) (eg, spleen for anatomically relevant sites such as the gastroesophageal junction or stomach), subsite- specific templates (eg, partial breast, whole breast, intact prostate, postoperative prostate, etc) and brachytherapy templates. An informal consensus on OAR and target coloration was also achieved, although color selections are fully customizable within the program. The resulting program is usable on any Windows system and generates template files in practice-specific Digital Imaging and Communications In Medicine (DICOM) or XML formats, extracting standardized structure nomenclature from an online database maintained by members of the TG-263U1, which ensures continuous access to up-to-date templates. We have developed a tool to easily create and name DICOM radiation therapy (DICOM-RT) structures sets that are TG-263–compliant for all planning systems using the DICOM standard. The program and source code are publicly available via GitHub to encourage feedback from community users for improvement and guide further development. [ABSTRACT FROM AUTHOR]

This paper presents a methodology for coordination and control of multiple photovoltaic (PV) generators for distributed power generation in a microgrid. Strategies are provided for coordination of active power generation and control of active power flows among distributed energy resources, while achieving supply–demand balance. Distributed approaches for optimal dispatch and control of active power flows are considered for active power support in the continuous-time domain. The effectiveness of the proposed approaches is investigated through an illustrative example. [ABSTRACT FROM AUTHOR]

Purpose: Programmed death-1 immune checkpoint blockade improves survival of patients with recurrent/metastatic head and neck squamous cell carcinoma (HNSCC), but the benefits of addition to (chemo)radiation for newly diagnosed patients with HNSCC remain unknown.Methods and Materials: We evaluated the safety of nivolumab concomitant with 70 Gy intensity modulated radiation therapy and weekly cisplatin (arm 1), every 3-week cisplatin (arm 2), cetuximab (arm 3), or alone for platinum-ineligible patients (arm 4) in newly diagnosed intermediate- or high-risk locoregionally advanced HNSCC. Patients received nivolumab from 2 weeks prior to radiation therapy until 3 months post-radiation therapy. The primary endpoint was dose-limiting toxicity (DLT). If ≤2 of the first 8 evaluable patients experienced a DLT, an arm was considered safe. Secondary endpoints included toxicity and feasibility of adjuvant nivolumab to 1 year, defined as all 7 additional doses received by ≥4 of the first 8 evaluable patients across arms.Results: Of 39 patients (10 in arms 1, 3, 4 and 9 in arm 2), 72% had T3-4 tumors, 85% had N2-3 nodal disease, and 67% had >10 pack-years of smoking. There were no DLTs in arms 1 and 2, 1 in arm 3 (mucositis), and 2 in arm 4 (lipase elevation and mucositis in 1 and fatigue in another). The most common grade ≥3 nivolumab-related adverse events were lipase increase, mucositis, diarrhea, lymphopenia, hyponatremia, leukopenia, fatigue, and serum amylase increase. Adjuvant nivolumab was feasible as defined in the protocol.Conclusions: Concomitant nivolumab with the 4 tested regimens was safe for patients with intermediate- and high-risk HNSCC, and subsequent adjuvant nivolumab was feasible as defined (NCT02764593). [ABSTRACT FROM AUTHOR]

Our purpose was to investigate the effect of physicist-patient consults on patient anxiety and patient satisfaction with a randomized prospective phase III clinical trial. Sixty-six patients were randomly assigned to the physics direct patient care (PDPC) arm or the control arm of the trial. Patients assigned to the PDPC arm received 2 physicist-patient consults to educate them on the technical aspects of their radiation therapy, while patients assigned to the control arm received the standard of care (ie, standard radiation therapy workflow without any additional physicist-patient consults). Questionnaires were administered to all patients at 4 time points (after enrollment, after the simulation, after the first treatment, and after the last treatment) to assess anxiety and satisfaction. The decrease in anxiety for the PDPC arm, compared with the control arm, was statistically significant at the first treatment (P =.027) time point. The increase in technical satisfaction for the PDPC arm, compared with the control arm, was statistically significant at the simulation (P =.005), first treatment (P <.001), and last treatment (P =.002) time points. The increase in overall satisfaction for the PDPC arm, compared with the control arm, was statistically significant at the first treatment (P =.014) and last treatment (P =.001) time points. Physicist-patient consults improved the patient experience by decreasing anxiety and increasing satisfaction. Future work is needed to modify current radiation oncology workflows and medical physics responsibilities to allow all patients to benefit from this advancement in patient care. [ABSTRACT FROM AUTHOR]

The purpose of this work was to develop a knowledge-based dose prediction system using a convolution neural network (CNN) for cervical brachytherapy treatments with a tandem-and-ovoid applicator. A 3D U-NET CNN was utilized to make voxel-wise dose predictions based on organ-at-risk (OAR), high-risk clinical target volume (HRCTV), and possible source location geometry. The model comprised 395 previously treated cases: training (273), validation (61), test (61). To assess voxel prediction accuracy, we evaluated dose differences in all cohorts across the dose range of 20−130% of prescription, mean (SD) and standard deviation (σ) , as well as isodose dice similarity coefficients for clinical and/or predicted dose distributions. We examined discrete Dose-Volume Histogram (DVH) metrics utilized for brachytherapy plan quality assessment (HRCTV D90%; bladder, rectum, and sigmoid D2cc) with Δ D x = D x , a c t u a l − D x , p r e d i c t e d mean, standard deviation, and Pearson correlation coefficient further quantifying model performance. Ranges of voxel-wise dose difference accuracy ( δ D ¯ ± σ) for 20−130% dose interval in training (test) sets ranged from [-0.5% ± 2.0% to +2.0% ± 14.0%] ([-0.1% ± 4.0% to +4.0% ± 26.0%]) in all voxels, [-1.7% ± 5.1% to -3.5% ± 12.8%] ([-2.9% ± 4.8% to -2.6% ± 18.9%]) in HRCTV, [-0.02% ± 2.40% to +3.2% ± 12.0%] ([-2.5% ± 3.6% to +0.8% ± 12.7%]) in bladder, [-0.7% ± 2.4% to +15.5% ± 11.0%] ([-0.9% ± 3.2% to +27.8% ± 11.6%]) in rectum, and [-0.7% ± 2.3% to +10.7% ± 15.0%] ([-0.4% ± 3.0% to +18.4% ± 11.4%]) in sigmoid. Isodose dice similarity coefficients ranged from [0.96,0.91] for training and [0.94,0.87] for test cohorts. Relative DVH metric prediction in the training (test) set were HRCTV Δ D ¯ 90 ± σ Δ D = -0.19 ± 0.55Gy (-0.09 ± 0.67 Gy), bladder Δ D ¯ 2 c c ± σ Δ D = -0.06 ± 0.54Gy (-0.17 ± 0.67 Gy), rectum Δ D ¯ 2 c c ± σ Δ D = -0.03 ± 0.36Gy (-0.04 ± 0.46 Gy), and sigmoid Δ D ¯ 2 c c ± σ Δ D = -0.01 ± 0.34Gy (0.00 ± 0.44 Gy). A 3D knowledge-based dose predictions provide voxel-level and DVH metric estimates that could be used for treatment plan quality control and data-driven plan guidance. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we present two iterative learning control (ILC) frameworks for tracking problems with specified data points that are desired points at certain time instants. To design ILC systems for such problems, unlike traditional ILC approaches, we first develop an algorithm in which not only the control signal but also the reference trajectory is updated at each trial. We investigate the relationship between the reference trajectory and ILC tracking control as it relates to the rate of convergence. Second, a new ILC scheme is proposed to produce output curves that pass close to the desired points. Here, the control signals are generated by solving an optimal ILC problem with respect to the desired sampling points. One of the key advantages of the proposed approaches is a significant reduction of the computational cost. [Copyright &y& Elsevier]

Currently, there is a lack of patient-specific tools to guide brachytherapy planning and applicator choice for cervical cancer. The purpose of this study is to evaluate the accuracy of organ-at-risk (OAR) dose predictions using knowledge-based intracavitary models, and the use of these models and clinical data to determine the dosimetric differences of tandem-and-ring (T&R) and tandem-and-ovoids (T&O) applicators. Knowledge-based models, which predict organ D 2cc , were trained on 77/75 cases and validated on 32/38 for T&R/T&O applicators. Model performance was quantified using ΔD 2cc =D 2cc,actual –D 2cc,predicted , with standard deviation (σ(ΔD 2cc)) representing precision. Model-predicted applicator dose differences were determined by applying T&O models to T&R cases, and vice versa, and compared to clinically-achieved D 2cc differences. Applicator differences were assessed using a Student's t -test (p < 0.05 significant). Validation T&O/T&R model precision was 0.65/0.55 Gy, 0.55/0.38 Gy, and 0.43/0.60 Gy for bladder, rectum and sigmoid, respectively, and similar to training. When applying T&O/T&R models to T&R/T&O cases, bladder, rectum and sigmoid D 2cc values in EQD2 were on average 5.69/2.62 Gy, 7.31/6.15 Gy and 3.65/0.69 Gy lower for T&R, with similar HRCTV volume and coverage. Clinical data also showed lower T&R OAR doses, with mean EQD2 D 2cc deviations of 0.61 Gy, 7.96 Gy (p < 0.01) and 5.86 Gy (p < 0.01) for bladder, rectum and sigmoid. Accurate knowledge-based dose prediction models were developed for two common intracavitary applicators. These models could be beneficial for standardizing and improving the quality of brachytherapy plans. Both models and clinical data suggest that significant OAR sparing can be achieved with T&R over T&O applicators, particularly for the rectum. [ABSTRACT FROM AUTHOR]

The use of interstitial needles, combined with intracavitary applicators, enables customized dose distributions and is beneficial for complex cases, but increases procedure time. Overall, applicator selection is not standardized and depends on physician expertise and preference. The purpose of this study is to determine whether dose prediction models can guide needle supplementation decision-making for cervical cancer. Intracavitary knowledge-based models for organ-at-risk (OAR) dose estimation were trained and validated for tandem-and-ring/ovoids (T&R/T&O) implants. Models were applied to hybrid cases with 1–3 implanted needles to predict OAR dose without needles. As a reference, 70/67 hybrid T&R/T&O cases were replanned without needles, following a standardized procedure guided by dose predictions. If a replanned dose exceeded the dose objective, the case was categorized as requiring needles. Receiver operating characteristic (ROC) curves of needle classification accuracy were generated. Optimal classification thresholds were determined from the Youden Index. Needle supplementation reduced dose to OARs. However, 67%/39% of replans for T&R/T&O met all dose constraints without needles. The ROC for T&R/T&O models had an area-under-curve of 0.89/0.86, proving high classification accuracy. The optimal threshold of 99%/101% of the dose limit for T&R/T&O resulted in classification sensitivity and specificity of 78%/86% and 85%/78%. Needle supplementation reduced OAR dose for most cases but was not always required to meet standard dose objectives, particularly for T&R cases. Our knowledge-based dose prediction model accurately identified cases that could have met constraints without needle supplementation, suggesting that such models may be beneficial for applicator selection. [ABSTRACT FROM AUTHOR]

Purpose: Our purpose was to investigate the effect of automated knowledge-based planning (KBP) on real-world clinical workflow efficiency, assess whether manual refinement of KBP plans improves plan quality across multiple disease sites, and develop a data-driven method to periodically improve KBP automated planning routines.Methods and Materials: Using clinical knowledge-based automated planning routines for prostate, prostatic fossa, head and neck, and hypofractionated lung disease sites in a commercial KBP solution, workflow efficiency was compared in terms of planning time in a pre-KBP (n = 145 plans) and post-KBP (n = 503) patient cohort. Post-KBP, planning was initialized with KBP (KBP-only) and subsequently manually refined (KBP +human). Differences in planning time were tested for significance using a 2-tailed Mann-Whitney U test (P < .05, null hypothesis: planning time unchanged). Post-refinement plan quality was assessed using site-specific dosimetric parameters of the original KBP-only plan versus KBP +human; 2-tailed paired t test quantified statistical significance (Bonferroni-corrected P < .05, null hypothesis: no dosimetric difference after refinement). If KBP +human significantly improved plans across the cohort, optimization objectives were changed to create an updated KBP routine (KBP'). Patients were replanned with KBP' and plan quality was compared with KBP +human as described previously.Results: KBP significantly reduced planning time in all disease sites: prostate (median: 7.6 hrs → 2.1 hrs; P < .001), prostatic fossa (11.1 hrs → 3.7 hrs; P = .001), lung (9.9 hrs → 2.0 hrs; P < .001), and head and neck (12.9 hrs → 3.5 hrs; P <.001). In prostate, prostatic fossa, and lung disease sites, organ-at-risk dose changes in KBP +human versus KBP-only were minimal (<1% prescription dose). In head and neck, KBP +human did achieve clinically relevant dose reductions in some parameters. The head and neck routine was updated (KBP'HN) to incorporate dose improvements from manual refinement. The only significant dosimetric differences to KBP +human after replanning with KBP'HN were in favor of the new routine.Conclusions: KBP increased clinical efficiency by significantly reducing planning time. On average, human refinement offered minimal dose improvements over KBP-only plans. In the single disease site where KBP +human was superior to KBP-only, differences were eliminated by adjusting optimization parameters in a revised KBP routine. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the efficacy of a training program designed to teach medical physicists how to communicate with patients effectively in the clinical environment.Methods and Materials: The training program was offered 3 times between 2016 and 2019. Participants were asked to rank their level of confidence in 5 categories relevant to patient communication on a 5-point Likert scale at 3 separate time points over the course of the training program. Participants were also asked to provide written responses to 5 common questions from patients at 2 separate time points, and these responses were numerically scored using the Constant Comparative Method. Competency in patient communication was assessed during simulated patient consults using a 9-element clinical competency assessment form. Changes in participants' stated level of confidence over the course of the training program and differences between faculty and residents were analyzed using the Student t test, and participants' scored responses to common questions were analyzed using analysis of variance.Results: Fifteen medical physicists participated in the training program: 6 resident physicists (4 first year and 2 second year) and 9 faculty physicists. Mean participant-stated level of confidence increased significantly across all categories (P < .05) between the first and second training intervention and between the second and third training intervention. There was no significant difference in mean participant-stated level of confidence between faculty and resident medical physicists. We observed statistically significant improvements in scored responses to common patient questions between the 2 assessment time points (P < .05). Of the 15 participants, 14 met competency assessment goals during simulated patient consults.Conclusions: The patient communication skills training program increases medical physicists' level of confidence across 5 patient communication categories and improves their responses to common questions from patients. In addition, the program can discern differences in communication competency between physicists. [ABSTRACT FROM AUTHOR]

Purpose: Sparing active bone marrow (ABM) can reduce acute hematologic toxicity in patients undergoing chemoradiotherapy for cervical cancer, but ABM segmentation based on positron emission tomography/computed tomography (PET/CT) is costly. We sought to develop an atlas-based ABM segmentation method for implementation in a prospective clinical trial.Methods and Materials: A multiatlas was built on a training set of 144 patients and validated in 32 patients from the NRG-GY006 clinical trial. ABM for individual patients was defined as the subvolume of pelvic bone greater than the individual mean standardized uptake value on registered 18F-fluorodeoxyglucose PET/CT images. Atlas-based and custom ABM segmentations were compared using the Dice similarity coefficient and mean distance to agreement and used to generate ABM-sparing intensity modulated radiation therapy plans. Dose-volume metrics and normal tissue complication probabilities of the two approaches were compared using linear regression.Results: Atlas-based ABM volumes (mean [standard deviation], 548.4 [88.3] cm3) were slightly larger than custom ABM volumes (535.1 [93.2] cm3), with a Dice similarity coefficient of 0.73. Total pelvic bone marrow V20 and Dmean were systematically higher and custom ABM V10 was systematically lower with custom-based plans (slope: 1.021 [95% confidence interval (CI), 1.005-1.037], 1.014 [95% CI, 1.006-1.022], and 0.98 [95% CI, 0.97-0.99], respectively). We found no significant differences between atlas-based and custom-based plans in bowel, rectum, bladder, femoral heads, or target dose-volume metrics.Conclusions: Atlas-based ABM segmentation can reduce pelvic bone marrow dose while achieving comparable target and other normal tissue dosimetry. This approach may allow ABM sparing in settings where PET/CT is unavailable. [ABSTRACT FROM AUTHOR]

The purpose of this study is to explore knowledge-based organ-at-risk dose estimation for intracavitary brachytherapy planning for cervical cancer. Using established external-beam knowledge-based dose-volume histogram (DVH) estimation methods, we sought to predict bladder, rectum, and sigmoid D 2cc for tandem and ovoid treatments. A total of 136 patients with loco-regionally advanced cervical cancer treated with 456 (356:100 training:validation ratio) CT-based tandem and ovoid brachytherapy fractions were analyzed. Single fraction prescription doses were 5.5–8 Gy with dose criteria for the high-risk clinical target volume, bladder, rectum, and sigmoid. DVH estimations were obtained by subdividing training set organs-at-risk into high-risk clinical target volume boundary distance subvolumes and computing cohort-averaged differential DVHs. Full DVH estimation was then performed on the training and validation sets. Model performance was quantified by ΔD 2cc = D 2cc (actual)-D 2cc (predicted) (mean and standard deviation). ΔD 2cc between training and validation sets were compared with a Student's t test (p < 0.01 significant). Categorical variables (physician, fraction-number, total fractions, and case complexity) that might explain model variance were examined using an analysis of variance test (Bonferroni-corrected p < 0.01 threshold). Training set deviations were bladder ΔD 2cc = −0.04 ± 0.61 Gy, rectum ΔD 2cc = 0.02 ± 0.57 Gy, and sigmoid ΔD 2cc = −0.05 ± 0.52 Gy. Model predictions on validation set did not statistically differ: bladder ΔD 2cc = −0.02 ± 0.46 Gy (p = 0.80), rectum ΔD 2cc = −0.007 ± 0.47 Gy (p = 0.53), and sigmoid ΔD 2cc = −0.07 ± 0.47 Gy (p = 0.70). The only significant categorical variable was the attending physician for bladder and rectum ΔD 2cc. A simple boundary distance-driven knowledge-based DVH estimation exhibited promising results in predicting critical brachytherapy dose metrics. Future work will examine the utility of these predictions for quality control and automated brachytherapy planning. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate whether automated knowledge-based planning (KBP) (a) is noninferior to human-driven planning across multiple disease sites and (b) systematically affects dosimetric plan quality and variability.Methods and Materials: Clinical KBP automated planning routines were developed for prostate, prostatic fossa, hypofractionated lung, and head and neck. Clinical implementation consisted of independent generation of human-generated and KBP plans (145 cases across all sites), followed by blinded plan selection. Reviewing physicians were prompted to select a single plan; when plan equivalence was volunteered, this scored as KBP selection. Plan selection analysis used a noninferiority framework testing the hypothesis that KBP is not worse than human-driven planning (threshold: lower 95% confidence interval [CI] > 0.45 = noninferiority; > 0.5 = superiority). Target and organ-at-risk metrics were compared by dose differencing: ΔDx = Dx, human-Dx, KBP (2-tailed paired t test, Bonferroni-corrected P < .05 significance threshold). To evaluate the aggregated effect of KBP on planning performance, we examined post-KBP dosimetric parameters against 183 plans generated just before KBP implementation (2-tailed unpaired t test, Bonferroni-corrected P < .05).Results: Across all disease sites, the KBP success rate (physician preferred + equivalent) was noninferior compared with human-driven planning (83 of 145 = 57.2%; range, 49.2%-65.3%) but did not cross the threshold for superiority. The KBP success rate in respective disease sites was superior with head and neck ([22 + 2]/36 = 66.7%; 95% CI, 51%-82%) and noninferior for lung stereotactic body radiation therapy ([21 + 2]/36 = 63.9%; 95% CI, 48%-80%) but did not meet noninferiority criteria with prostate ([16 + 3]/41 = 46.3%; 95% CI, 31%-62%) or prostatic fossa ([17 + 0]/32 = 53.1%; 95% CI, 36%-70%). Prostate, prostatic fossa, and head and neck showed significant differences in KBP-selected plans versus human-selected plans, with KBP generally exhibiting greater organ-at-risk sparing and human plans exhibiting better target homogeneity. Analysis of plan quality pre- and post-KBP showed some reductions in organ doses and quality metric variability in prostate and head and neck.Conclusions: Fully automated KBP was noninferior to human-driven plan optimization across multiple disease sites. Dosimetric analysis of treatment plans before and after KBP implementation showed a systematic shift to higher plan quality and lower variability with the introduction of KBP. [ABSTRACT FROM AUTHOR]

Research demonstrates that instructing patients to have a full bladder for pelvic radiotherapy results in highly variable bladder volumes at daily treatment. We aimed to determine bladder volume variation in patients with intact cervical cancer treated with intensity-modulated radiotherapy (IMRT) on an empty bladder and estimate the difference in radiation dose to the small bowel compared to treating on a full bladder. We identified 29 patients treated with IMRT from 2010 to 2013 who underwent 2 planning computed tomography (CT) scans, 1 with a full bladder followed by 1 with an empty bladder. Interfractional variation in bladder volume was measured using 782 daily cone beam computed tomography (CBCT) scans. To estimate dose to small bowel, radiation plans were created on both empty and full bladder CT scans using an automated knowledge-based planning modeling program. Mean bladder volume with empty bladder instructions was 67 ± 26 cc compared to 91 ± 43 cc for no bladder instructions and 154 ± 54 cc for full bladder instructions (p < 0.001). There was a significant reduction in the absolute bladder volume variation in patients given empty bladder instructions compared to full bladder instructions (p < 0.05) The intraclass correlation coefficient showed low reliability of bladder filling across all groups (p = 0.6). The average bowel V45 for the empty bladder plans was 188 cc, compared to 139 cc for the full bladder plans (p < 0.05). More plans created on an empty bladder exceeded Quantitative Analyses of Normal Tissue Effects in the Clinic (QUANTEC) guidelines but this was not significant (31% vs 14%, p = 0.12). Reliability of bladder volume at the time of radiation treatment is low, regardless of bladder filling instructions, although an empty bladder reduces absolute variation in bladder volume. Radiation planning on an empty bladder predicts a larger volume of small bowel receiving 45 Gy compared to a full bladder, although bowel dose on average is still within QUANTEC guidelines (V45 < 195 cc). [ABSTRACT FROM AUTHOR]

Purpose: Geometric indicators of contouring accuracy suffer from lack of clinical context in radiation therapy. To provide clinical relevance, treatment plans should be generated from the candidate contours, but manual planning could introduce confounding variations. Therefore, our objectives in this study were as follows: (1) determine the feasibility of using automated knowledge-based planning as an objective tool to generate dosimetric parameters for contour evaluation, (2) evaluate the correlation between geometric indices and dosimetric endpoints, and (3) report the dosimetric impact of multiple observations of head and neck target and organ-at-risk (OAR) volumes contoured by resident physicians.Methods and Materials: Twenty-two resident physicians contoured the clinical target volumes, parotids, and cochleae for a nasopharyngeal cancer case, and expert-generated contours were defined as the gold standard for this study. A validated knowledge-based planning routine generated 67 treatment plans with various resident/gold-standard and target/OAR combinations. Dosimetric indices (dose to hottest 98% volume of planning target volume, and mean dose of OAR) were calculated on gold-standard contours. Commonly used geometric indices (Dice coefficients, Hausdorff maximum/mean/median distances, volume differences, and centroid distances) were also calculated. R2 quantified the correlation between geometric and dosimetric indices.Results: The correlation between geometric and dosimetric indices was weak (R2 < 0.2 for 61% of the correlations studied-77 of 126) and inconsistent (no single geometric index consistently exhibited superior/inferior correlation with dosimetric endpoints). The lack of consistent correlations between geometric and dosimetric indices resulted in the inability to define any geometric index thresholds for clinical acceptability. Geometric indices also exhibited a high propensity for false positives and false negatives as a classifier of dosimetric impact. Finally, we found substantial interresident contour variation, whether quantified using geometric or dosimetric indices, with significant negative dosimetric impact should these contours be used clinically.Conclusions: Contour variation among resident physicians significantly affected dosimetric endpoints, highlighting the importance of resident education in head and neck anatomy delineation. Whenever available, dosimetric indices generated from automated planning should be used alongside geometric indices in radiation therapy contouring studies. [ABSTRACT FROM AUTHOR]

Purpose: To investigate a new clinical role for medical physicists in direct patient care with a prospective phase 2 clinical trial.Materials and Methods: Medical physicists participated in the Physics Direct Patient Care (PDPC) protocol, establishing independent professional relationships with radiation oncology patients. After attending a dedicated patient communication training program, medical physicists routinely met with patients for 2 physicist-patient consults to explain the treatment planning and delivery process, review the patient's treatment plan, and answer all technical questions. The first physicist-patient consult took place immediately before the computed tomography simulation, and the second took place immediately before the first treatment. Questionnaires were administered to each patient on the PDPC protocol at 3 time points to assess both anxiety and satisfaction. The first questionnaire was given shortly after the first physicist-patient consult, the second questionnaire was given shortly after the second physicist-patient consult, and the third questionnaire was given after the last treatment appointment, with no associated physicist-patient consult.Results: The mean patient anxiety score was considered to be low at all questionnaire time points. There was a statistically significant decrease (P < .0001) in anxiety from the simulation time point to the first treatment time point. The mean patient technical satisfaction score was considered to be high at all measurement time points. There was a statistically significant increase (P = .0012) in technical satisfaction from the simulation time point to the first treatment time point. There was a statistically significant decrease (P < .023) in technical satisfaction from the first treatment time point to the last treatment time point.Conclusions: Establishing a new clinical role for medical physicists and investigating its effects on patient anxiety and satisfaction have created the foundation for future studies. Based on the results of this trial, the PDPC protocol will be expanded to a larger group of medical physicists, radiation oncologists, and patient disease sites and investigated with a randomized phase 3 clinical trial. [ABSTRACT FROM AUTHOR]

Brachytherapy treatment planning for cervical cancer is performed real-time while patients are sedated and requires expertise to optimally tailor the radiation to patients' anatomy. While numerous tools have been developed to increase the efficiency of treatment planning, these methods have not achieved widespread adoption. As a result, many centers are still performing treatment planning manually, which can take 95 minutes on average1. The goal of this work was to automate treatment planning for both intracavitary and hybrid interstitial brachytherapy of cervical cancer using a single neural network model for dose prediction. The automated planning pipeline takes 3D dose predictions from a neural network model and feeds them into an optimizer, which iteratively determines the dwell times required to reproduce the predicted dose distribution. 907 treatment plans from 273 patients treated with HDR brachytherapy for cervical cancer from 2010 onwards were used to develop the model. The train/test/validation split was 70%/15%/15%, with approximately 49% tandem-and-ovoid (TO), 11% TO with 1-7 needles, 18% tandem-and-ring (TR) and 21% TR with 1-4 needles in each dataset. Model inputs included 4 channels for anatomical masks (high-risk CTV (HRCTV), bladder, rectum and sigmoid), a mask representing the location of digitized dwell positions, and 4 applicator channels (1 for each of tandem, ovoids, ring and needles). Applicator channels were created by mapping a 3D dose kernel to each dwell position within that applicator type (if any) and summing over all dwell positions with equal weighting. A 3D Cascade U-Net architecture2 and a mean squared error (MSE) loss function were used. To convert model dose predictions into deliverable treatment plans, a COBYLA optimizer was used to minimize the MSE between the 3D dose calculated for a given set of dwell times and the predicted dose. Automated plans were produced for 60 test cases (15 for each applicator type). Automated plans were compared to clinical plans using mean absolute differences (MAD) in dose over all voxels and dwell times. HRCTV D90 and organ D2cc were compared with mean differences (MD) and paired t-tests (p value significance threshold 0.013 after Bonferroni correction). Figure 1 shows a comparison of automated and clinical plan dose and dwell times for a randomly selected patient from each applicator type. MAD in dose was 32cGy, or 4.6% relative to prescription. MAD in dwell times was 10.2s, or 2.0% relative to total plan dwell time. On average, automated plans had slightly reduced HRCTV D90 (MD 22cGy, or 3.2% relative to prescription, p=0.02), rectal D2cc (MD 8cGy or 1.1%, p=0.3) and sigmoid D2cc (MD 25cGy or 3.6%, p<0.001). Bladder D2cc averaged 11cGy (1.6%) higher for automated plans (p=0.1). Qualitatively, the shape of automated dose distributions matched those of clinical plans (e.g. pear-shaped dose for intracavitary cases) and dwell time weighting between applicator types was acceptable (e.g. reduced dwell times within needles). Automated plans were produced in around 3 minutes, which includes the time to produce inputs (2 min), 20s to run model predictions and 25s for optimization. Automated planning with neural network dose predictions produced treatment plans with significantly lower sigmoid dose and otherwise similar dose distributions and metrics as clinically treated plans, in under 3 minutes. Automated plans could be further manually optimized if necessary, but with far less time. The major time savings and standardization across practitioners, regardless of experience, brings value to the brachytherapy treatment planning process. References: 1Michaud et al. Brachytherapy 2016;15(5):578-83. 2Liu et al. Med. Phys. 2021;48(9):5574-82. [ABSTRACT FROM AUTHOR]

Purpose: To demonstrate an efficient method for training and validation of a knowledge-based planning (KBP) system as a radiation therapy clinical trial plan quality-control system.Methods and Materials: We analyzed 86 patients with stage IB through IVA cervical cancer treated with intensity modulated radiation therapy at 2 institutions according to the standards of the INTERTECC (International Evaluation of Radiotherapy Technology Effectiveness in Cervical Cancer, National Clinical Trials Network identifier: 01554397) protocol. The protocol used a planning target volume and 2 primary organs at risk: pelvic bone marrow (PBM) and bowel. Secondary organs at risk were rectum and bladder. Initial unfiltered dose-volume histogram (DVH) estimation models were trained using all 86 plans. Refined training sets were created by removing sub-optimal plans from the unfiltered sample, and DVH estimation models… and DVH estimation models were constructed by identifying 30 of 86 plans emphasizing PBM sparing (comparing protocol-specified dosimetric cutpoints V10 (percentage volume of PBM receiving at least 10 Gy dose) and V20 (percentage volume of PBM receiving at least 20 Gy dose) with unfiltered predictions) and another 30 of 86 plans emphasizing bowel sparing (comparing V40 (absolute volume of bowel receiving at least 40 Gy dose) and V45 (absolute volume of bowel receiving at least 45 Gy dose), 9 in common with the PBM set). To obtain deliverable KBP plans, refined models must inform patient-specific optimization objectives and/or priorities (an auto-planning "routine"). Four candidate routines emphasizing different tradeoffs were composed, and a script was developed to automatically re-plan multiple patients with each routine. After selection of the routine that best met protocol objectives in the 51-patient training sample (KBPFINAL), protocol-specific DVH metrics and normal tissue complication probability were compared for original versus KBPFINAL plans across the 35-patient validation set. Paired t tests were used to test differences between planning sets.Results: KBPFINAL plans outperformed manual planning across the validation set in all protocol-specific DVH cutpoints. The mean normal tissue complication probability for gastrointestinal toxicity was lower for KBPFINAL versus validation-set plans (48.7% vs 53.8%, P<.001). Similarly, the estimated mean white blood cell count nadir was higher (2.77 vs 2.49 k/mL, P<.001) with KBPFINAL plans, indicating lowered probability of hematologic toxicity.Conclusions: This work demonstrates that a KBP system can be efficiently trained and refined for use in radiation therapy clinical trials with minimal effort. This patient-specific plan quality control resulted in improvements on protocol-specific dosimetric endpoints. [ABSTRACT FROM AUTHOR]

We study a generalized integrator consensus network, each node of which is a single-integrator cascaded with some heterogeneous non-integrator internal dynamics. Under the assumption that the interconnection graph is undirected and connected, we first investigate the convergence property of the consensus network and show that the interconnection is beneficial for the enhancement of the convergence rate if the non-integrator internal dynamics of each node is strictly passive. We then show that the interconnection is also advantageous for the disturbance attenuation in the consensus network. [ABSTRACT FROM AUTHOR]

Tyrosine O-sulfation is a post-translational modification catalyzed by two tyrosylprotein sulfotransferases (TPST-1 and TPST-2) in the trans-Golgi network. Tpst2-deficient mice have male infertility, sperm motility defects, and possible abnormalities in sperm-egg membrane interactions. Studies here show that compared with wild-type sperm, fewer Tpst2-null sperm bind to the egg membrane, but more of these bound sperm progress to membrane fusion. Similar outcomes were observed with wild-type sperm treated with the anti-sulfotyrosine antibody PSG2. The increased extent of sperm-egg fusion is not due to a failure of Tpst2-null sperm to trigger establishment of the egg membrane block to polyspermy. Anti-sulfotyrosine staining of sperm showed localization similar to that of IZUMO1, a sperm protein that is essential for gamete fusion, but we detected little to no tyrosine sulfation of IZUMO1 and found that IZUMO1 expression and localization were normal in Tpst2-null sperm. Turning to a discovery-driven approach, we used mass spectrometry to characterize sperm proteins that associated with PSG2. This identified ADAM6, a member of the A disintegrin and A metalloprotease (ADAM) family; members of this protein family are associated with multiple sperm functions. Subsequent studies revealed that Tpst2-null sperm lack ADAM6 and ADAM3. Loss of ADAM3 is strongly associated with male infertility and is observed in knockouts of male germ line-specific endoplasmic reticulum-resident chaperones, raising the possibility that TPST-2 may function in quality control in the secretory pathway. These data suggest that TPST-2-mediated tyrosine O-sulfation participates in regulating the sperm surface proteome or membrane order, ultimately affecting male fertility. [ABSTRACT FROM AUTHOR]

Protein tyrosine O-sulfation is a post-translational modification mediated by one of two Golgi tyrosyiprotein sulfotransferases (TPST1 and TPST2) that catalyze the transfer of sulfate to tyrosine residues in secreted and transmembrane proteins. Tyrosine sulfation plays a role in protein-protein interactions in several well defined systems. Although dozens of tyrosine-sulfated proteins are known, many more are likely to exist and await description. Advancing our understanding of the importance of tyrosine sulfation in biological systems requires the development of new tools for the detection and study of tyrosine-sulfated proteins. We have developed a novel anti-sulfotyrosine monoclonal antibody (called PSG2) that binds with high affinity and exquisite specificity to sulfotyrosine residues in peptides and proteins independently of sequence context. We show that it can detect tyrosine-sulfated proteins in complex biological samples and can be used as a probe to assess the role of tyrosine sulfation in protein function. We also demonstrate the utility of PSG2 in the purification of tyrosine-sulfated proteins from crude tissue samples. Finally, Western blot analysis using PSG2 showed that certain sperm/epididymal proteins are undersulfated in Tpst2-/- mice. This indicates that TPST1 and TPST2 have distinct macromolecular substrate specificities and provides clues as to the molecular mechanism of the infertility of Tpst2-/- males. PSG2 should be widely applicable for identification of tyrosine-sulfated proteins in other systems and organisms. [ABSTRACT FROM AUTHOR]

Tyrosine O-sulfation is a post-translational modification mediated by one of two Golgi tyrosylprotein sulfotransferases (TPST-1 and -2) expressed in all mammalian cells. Tyrosine sulfation plays an important role in the function of some known TPST substrates by enhancing protein-protein interactions. To explore the role of these enzymes in vivo and gain insight into other potential TPST substrates, TPST-2-deficient mice were generated by targeted disruption of the Tpst2 gene. Tpst2+/- mice appear normal and, when interbred, yield litters of normal size with a Mendelian distribution of the targeted mutation. Tpst2+/- mice have moderately delayed growth but appear healthy and attain normal body weight by 10 weeks of age. In contrast to Tpst1-/- males that have normal fertility, Tpst2-/- males are infertile. Tpst2-/- sperm are normal in number, morphology, and motility in normal media and appear to capacitate and undergo acrosomal exocytosis normally. However, they are severely defective in their motility in viscous media and in their ability to fertilize zona pellucida-intact eggs. Adhesion of Tpst2-/- sperm to the egg plasma membrane is reduced compared with wild type sperm, but sperm-egg fusion is similar or even increased. These data strongly suggest that tyrosine sulfation of unidentified substrate(s) play a crucial role in these processes and document for the first time the critical importance of post-translational tyrosine sulfation in male fertility. [ABSTRACT FROM AUTHOR]

Tyrosylprotein sulfotransferases (TPSTs) catalyze the sulfation of tyrosine residues within secreted and membrane-bound proteins. The modification modulates protein–protein interactions in the extracellular environment. Here we use combinatorial target-guided ligand assembly to discover the first known inhibitors of human TPST-2. [Copyright &y& Elsevier]