Rapid tilt-series method for cryo-electron tomography: Characterizing stage behavior during FISE acquisition

We and others recently developed rapid tilt-series acquisition methods for cryo-electron tomography on a Titan Krios G3i equipped with a single axis holder and a K-series direct electron detector and showed that one of these, the fast-incremental single exposure (FISE) method, significantly accelerates tilt-series acquisition when compared to traditional methods while preserving the quality of the images. Here, we characterize the behavior of our single axis holder in detail during a FISE experiment to optimally balance data quality with speed. We explain our methodology in detail so others can characterize their own stages, and conclude with recommendations for projects with different resolution goals

Best practices for managing large CryoEM facilities

This paper provides an overview of the discussion and presentations from the Workshop on the Management of Large CryoEM Facilities held at the New York Structural Biology Center, New York, NY on February 6–7, 2017. A major objective of the workshop was to discuss best practices for managing cryoEM facilities. The discussions were largely focused on supporting single-particle methods for cryoEM and topics included: user access, assessing projects, workflow, sample handling, microscopy, data management and processing, and user training

A GPU-based multi-criteria optimization algorithm for HDR brachytherapy

Currently in HDR brachytherapy planning, a manual fine-tuning of an objective function is necessary to obtain case-specific valid plans. This study intends to facilitate this process by proposing a patient-specific inverse planning algorithm for HDR prostate brachytherapy: GPU-based multi-criteria optimization (gMCO). Two GPU-based optimization engines including simulated annealing (gSA) and a quasi-Newton optimizer (gL-BFGS) were implemented to compute multiple plans in parallel. After evaluating the equivalence and the computation performance of these two optimization engines, one preferred optimization engine was selected for the gMCO algorithm. Five hundred sixty-two previously treated prostate HDR cases were divided into validation set (100) and test set (462). In the validation set, the number of Pareto optimal plans to achieve the best plan quality was determined for the gMCO algorithm. In the test set, gMCO plans were compared with the physician-approved clinical plans. Over 462 cases, the number of clinically valid plans was 428 (92.6%) for clinical plans and 461 (99.8%) for gMCO plans. The number of valid plans with target V100 coverage greater than 95% was 288 (62.3%) for clinical plans and 414 (89.6%) for gMCO plans. The mean planning time was 9.4 s for the gMCO algorithm to generate 1000 Pareto optimal plans. In conclusion, gL-BFGS is able to compute thousands of SA equivalent treatment plans within a short time frame. Powered by gL-BFGS, an ultra-fast and robust multi-criteria optimization algorithm was implemented for HDR prostate brachytherapy. A large-scale comparison against physician approved clinical plans showed that treatment plan quality could be improved and planning time could be significantly reduced with the proposed gMCO algorithm.Comment: 18 pages, 7 figure

Performance-based plastic design of self-centering steel braced frame

This study proposes a performance-based seismic design (PBSD) method for steel braced frames with novel self-centering (SC) braces that utilizes shape memory alloys (SMA) as a kernel component. The presented PBSD method is essentially a modified version of the performance-based plastic design. A few concentrically braced frames with SC braces are designed as examples to illustrate the efficacy of the proposed design method. The seismic performance of the designed frames is examined at various seismic intensity levels. Results of nonlinear time-history analyses indicate that the designed SC braced frames can successfully achieve the prescribed performance objectives at three seismic hazard levels

Rapid Tilt-Series Method for Cryo-Electron Tomography: Characterizing Stage Behavior During FISE Acquisition

We and others recently developed rapid tilt-series acquisition methods for cryo-electron tomography on a Titan Krios G3i equipped with a single axis holder and a K-series direct electron detector and showed that one of these, the fast-incremental single exposure (FISE) method, significantly accelerates tilt-series acquisition when compared to traditional methods while preserving the quality of the images. Here, we characterize the behavior of our single axis holder in detail during a FISE experiment to optimally balance data quality with speed. We explain our methodology in detail so others can characterize their own stages, and conclude with recommendations for projects with different resolution goals

Resilient Civil Infrastructure under Dynamic Loadings

A resilient infrastructural system is an important component of a modern city. The main principles are safety, sustainability, functionality, maintainability, and fast recoverability following natural and/or man-made hazards. This special issue addresses new research developments in resilient infrastructural systems under dynamic loadings, for example, wind, traffic, tsunamis, and earthquakes

Multi-criteria optimization algorithms for high dose rate brachytherapy

L’objectif général de cette thèse est d’utiliser les connaissances en physique de la radiation, en programmation informatique et en équipement informatique à la haute pointe de la technologie pour améliorer les traitements du cancer. En particulier, l’élaboration d’un plan de traitement en radiothérapie peut être complexe et dépendant de l’utilisateur. Cette thèse a pour objectif de simplifier la planification de traitement actuelle en curiethérapie de la prostate à haut débit de dose (HDR). Ce projet a débuté à partir d’un algorithme de planification inverse largement utilisé, la planification de traitement inverse par recuit simulé (IPSA). Pour aboutir à un algorithme de planification inverse ultra-rapide et automatisé, trois algorithmes d’optimisation multicritères (MCO) ont été mis en oeuvre. Suite à la génération d’une banque de plans de traitement ayant divers compromis avec les algorithmes MCO, un plan de qualité a été automatiquement sélectionné. Dans la première étude, un algorithme MCO a été introduit pour explorer les frontières de Pareto en curiethérapie HDR. L’algorithme s’inspire de la fonctionnalité MCO intégrée au système Raystation (RaySearch Laboratories, Stockholm, Suède). Pour chaque cas, 300 plans de traitement ont été générés en série pour obtenir une approximation uniforme de la frontière de Pareto. Chaque plan optimal de Pareto a été calculé avec IPSA et chaque nouveau plan a été ajouté à la portion de la frontière de Pareto où la distance entre sa limite supérieure et sa limite inférieure était la plus grande. Dans une étude complémentaire, ou dans la seconde étude, un algorithme MCO basé sur la connaissance (kMCO) a été mis en oeuvre pour réduire le temps de calcul de l’algorithme MCO. Pour ce faire, deux stratégies ont été mises en oeuvre : une prédiction de l’espace des solutions cliniquement acceptables à partir de modèles de régression et d’un calcul parallèle des plans de traitement avec deux processeurs à six coeurs. En conséquence, une banque de plans de traitement de petite taille (14) a été générée et un plan a été sélectionné en tant que plan kMCO. L’efficacité de la planification et de la performance dosimétrique ont été comparées entre les plans approuvés par le médecin et les plans kMCO pour 236 cas. La troisième et dernière étude de cette thèse a été réalisée en coopération avec Cédric Bélanger. Un algorithme MCO (gMCO) basé sur l’utilisation d’un environnement de développement compatible avec les cartes graphiques a été mis en oeuvre pour accélérer davantage le calcul. De plus, un algorithme d’optimisation quasi-Newton a été implémenté pour remplacer le recuit simulé dans la première et la deuxième étude. De cette manière, un millier de plans de traitement avec divers compromis et équivalents à ceux générés par IPSA ont été calculés en parallèle. Parmi la banque de plans de traitement généré par l’agorithme gMCO, un plan a été sélectionné (plan gMCO). Le temps de planification et les résultats dosimétriques ont été comparés entre les plans approuvés par le médecin et les plans gMCO pour 457 cas. Une comparaison à grande échelle avec les plans approuvés par les radio-oncologues montre que notre dernier algorithme MCO (gMCO) peut améliorer l’efficacité de la planification du traitement (de quelques minutes à 9:4 s) ainsi que la qualité dosimétrique des plans de traitements (des plans passant de 92:6% à 99:8% selon les critères dosimétriques du groupe de traitement oncologique par radiation (RTOG)). Avec trois algorithmes MCO mis en oeuvre, cette thèse représente un effort soutenu pour développer un algorithme de planification inverse ultra-rapide, automatique et robuste en curiethérapie HDR.The overall purpose of this thesis is to use the knowledge of radiation physics, computer programming and computing hardware to improve cancer treatments. In particular, designing a treatment plan in radiation therapy can be complex and user-dependent, and this thesis aims to simplify current treatment planning in high dose rate (HDR) prostate brachytherapy. This project was started from a widely used inverse planning algorithm, Inverse Planning Simulated Annealing (IPSA). In order to eventually lead to an ultra-fast and automatic inverse planning algorithm, three multi-criteria optimization (MCO) algorithms were implemented. With MCO algorithms, a desirable plan was selected after computing a set of treatment plans with various trade-offs. In the first study, an MCO algorithm was introduced to explore the Pareto surfaces in HDR brachytherapy. The algorithm was inspired by the MCO feature integrated in the Raystation system (RaySearch Laboratories, Stockholm, Sweden). For each case, 300 treatment plans were serially generated to obtain a uniform approximation of the Pareto surface. Each Pareto optimal plan was computed with IPSA, and each new plan was added to the Pareto surface portion where the distance between its upper boundary and its lower boundary was the largest. In a companion study, or the second study, a knowledge-based MCO (kMCO) algorithm was implemented to shorten the computation time of the MCO algorithm. To achieve this, two strategies were implemented: a prediction of clinical relevant solution space with previous knowledge, and a parallel computation of treatment plans with two six-core CPUs. As a result, a small size (14) plan dataset was created, and one plan was selected as the kMCO plan. The planning efficiency and the dosimetric performance were compared between the physician-approved plans and the kMCO plans for 236 cases. The third and final study of this thesis was conducted in cooperation with Cédric Bélanger. A graphics processing units (GPU) based MCO (gMCO) algorithm was implemented to further speed up the computation. Furthermore, a quasi-Newton optimization engine was implemented to replace simulated annealing in the first and the second study. In this way, one thousand IPSA equivalent treatment plans with various trade-offs were computed in parallel. One plan was selected as the gMCO plan from the calculated plan dataset. The planning time and the dosimetric results were compared between the physician-approved plans and the gMCO plans for 457 cases. A large-scale comparison against the physician-approved plans shows that our latest MCO algorithm (gMCO) can result in an improved treatment planning efficiency (from minutes to 9:4 s) as well as an improved treatment plan dosimetric quality (Radiation Therapy Oncology Group (RTOG) acceptance rate from 92.6% to 99.8%). With three implemented MCO algorithms, this thesis represents a sustained effort to develop an ultra-fast, automatic and robust inverse planning algorithm in HDR brachytherapy

Best practices for managing large CryoEM facilities

This paper provides an overview of the discussion and presentations from the Workshop on the Management of Large CryoEM Facilities held at the New York Structural Biology Center, New York, NY on February 6–7, 2017. A major objective of the workshop was to discuss best practices for managing cryoEM facilities. The discussions were largely focused on supporting single-particle methods for cryoEM and topics included: user access, assessing projects, workflow, sample handling, microscopy, data management and processing, and user training

Rapid Tilt-Series Acquisition for Electron Cryotomography

Using a new Titan Krios stage equipped with a single-axis holder, we developed two methods to accelerate the collection of tilt-series. We demonstrate a continuous-tilting method that can record a tilt-series in seconds, but with loss of details finer than ∼4 nm. We also demonstrate a fast-incremental method that can record a tilt-series several-fold faster than current methods and with similar resolution. We characterize the utility of both methods in real biological electron cryotomography workflows. We identify opportunities for further improvements in hardware and software and speculate on the impact such advances could have on structural biology