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Background: Antibody seroprevalence in rural communities remains poorly investigated. We compared the SARS-CoV-2 seroprevalence in two Greek communities in June and July 2021 after the end of the Delta-driven pandemic wave that started in November 2020. One community was affected worse than the other. Methods: The SARS-CoV-2 IgG II Quant method (Architect, Abbott, IL, USA) was used for antibody testing. Results: We found a high rate of SARS-CoV-2 seropositivity in both communities, approaching 77.5%. In the area with a higher burden of COVID-19, Malesina, seropositivity was achieved with vaccine-acquired and naturally acquired immunity, whereas in the low-burden context of Domokos, the high rates of seropositivity were achieved mainly with vaccination. Previously infected individuals were less likely to be vaccinated than previously uninfected adults. The antibody titers were significantly higher in previously infected, vaccinated participants than in unvaccinated ones. In total, 4% and 10% of the unvaccinated population were diagnosed seropositive for the first time while not knowing about the previous infection. Age and gender did not impact antibody titers in high- or low-burden contexts. Conclusions: Before the Omicron pandemic wave, herd immunity was reached in different contexts in Greece. Higher antibody titers were measured in infected vaccinated individuals than in infected unvaccinated ones.

The present paper explores issues concerning Senior High School students’ teaching and understanding of concepts and laws, related to the rotation of a solid body around a fixed axis of rotation, through a properly designed experimental type of teaching intervention, that incorporates custom-made educational material and utilizes ICT. Through an interdisciplinary-exploratory approach of teaching, the alternative ideas of 143 high school students, aged 16-17, were initially identified. The students were divided into a control group and an experimental one and completed a suitably designed questionnaire before and after the didactic interventions. The interventions aimed at investigating the extent to which the experimental student group alternative ideas, taught through an experimental scientific approach, changed compared to the ideas of the students of the control group, who were taught the same subjects in a conventional way. The results, obtained from a quantitative and qualitative analysis of questionnaires and interviews, indicate an improvement of the experimental student group understanding, in relation to the concepts of rotational movement. Additionally, they indicate the development of a positive attitude towards the experimental procedure, applied throughout the intervention, as opposed to that of the control group, where the teaching was carried out in a conventional way.

Background: In this work, we aimed to evaluate antibody-response longevity to SARS-CoV-2 infection and/or vaccination in one of the Greek communities that was worst hit by the pandemic, Deskati, five months after a previous serosurveillance and nine months after the pandemic wave initiation (October 2020). Methods: The SARS-CoV-2 IgG II Quant method (Architect, Abbott, IL, USA) was used for antibody testing. Results: A total of 69 subjects, who previously tested positive or negative for COVID-19 antibodies, participated in the study. We found that 48% of participants turned positive due to vaccination. 27% of participants were both previously infected and vaccinated. However, all previously infected participants retained antibodies to the virus, irrespective of their vaccination status. The antibody titers were significantly higher in previously infected participants that had been vaccinated than those who were unvaccinated and in those that had been previously hospitalized for COVID-19 than those with mild disease. Conclusions: Antibody responses to SARS-CoV-2 infection were maintained nine months after the pandemic. Vaccination alone had generated an immune response in almost half of the population. Higher antibody titers were found in the case of vaccination in previously infected subjects and especially in those with severe disease leading to hospitalization.

Ambient air pollution accounts for an estimated 4.2 million deaths worldwide. Particulate matter (PM)2.5 particles are believed to be the most harmful, as when inhaled they can penetrate deep into the lungs. The aim of this study was to examine the relationship between PM2.5 daily air concentrations and pediatric emergency department (ED) visits for respiratory diseases in a Greek suburban area. All pediatric ED visits for asthma-, pneumonia- and upper respiratory infection (URI)-related complaints were recorded during the one-year period. The 24-h PM2.5 air pollution data were prospectively collected from twelve fully automated air quality monitoring stations. The mean annual concentration of PM2.5 was 30.03 μg/m3 (World Health Organization (WHO) Air Quality Guidelines (AQG) Annual mean concentration: 10 μg/m3). PM2.5 levels rose above the WHO Air Quality Guidelines (AQG) 24-h concentrations (25 μg/m3)), 178 times (48.6% of the study period). When PM2.5 levels were above the daily limit, an increase of 32.44% (p &lt, 0.001) was observed in daily pediatric ED visits for respiratory diseases and the increase was much higher during spring (21.19%, p = 0.018). A 32% (p &lt, 0.001) increase was observed in URI-related visits, when PM2.5 levels were ≥25 μg/m3, compared to the mean daily visits when PM2.5 levels were &lt, 25 μg/m3. Air pollution levels were associated with increased pediatric ED visits for respiratory-related diseases.

Background: No previous study has investigated the SARS-CoV-2 prevalence and the changes in the proportion of positive results due to lockdown measures from the angle of workers’ vulnerability to coronavirus in Greece. Two community-based programs were implemented to evaluate the SARS-CoV-2 prevalence and investigate if the prevalence changes were significant across various occupations before and one month after lockdown. Methods: Following consent, sociodemographic, clinical, and job-related information were recorded. The VivaDiag™ SARS-CoV-2 Antigen Rapid Test was used. Positive results confirmed by a real-time Reverse Transcriptase Polymerase Chain Reaction for SARS-COV-2. Results: Positive participants were more likely to work in the catering/food sector than negative participants before the lockdown. Lockdown restrictions halved the new cases. No significant differences in the likelihood of being SARS-CoV-2 positive for different job categories were detected during lockdown. The presence of respiratory symptoms was an independent predictor for rapid antigen test positivity, however, one-third of newly diagnosed patients were asymptomatic at both time points. Conclusions: The catering/food sector was the most vulnerable to COVID-19 at the pre-lockdown evaluation. We highlight the crucial role of community-based screening with rapid antigen testing to evaluate the potential modes of community transmission and the impact of infection control strategies.

Detection of Identical-By-Descent (IBD) segments provides a fundamental measure of genetic relatedness and plays a key role in a wide range of genomic analyses. We developed a new method, called FastSMC, that enables accurate biobank-scale detection of IBD segments transmitted by common ancestors living up to several hundreds of generations in the past. FastSMC combines a fast heuristic search for IBD segments with accurate coalescent-based likelihood calculations and enables estimating the age of common ancestors transmitting IBD regions. We applied FastSMC to 487,409 phased samples from the UK Biobank and detected the presence of ∼214 billion IBD segments transmitted by shared ancestors within the past 1,500 years. We quantified time-dependent shared ancestry within and across 120 postcodes, obtaining a fine-grained picture of genetic relatedness within the past two millennia in the UK. Sharing of common ancestors strongly correlates with geographic distance, enabling the localization of a sample’s birth coordinates from genomic data. We sought evidence of recent positive selection by identifying loci with unusually strong shared ancestry within recent millennia and we detected 12 genome-wide significant signals, including 7 novel loci. We found IBD sharing to be highly predictive of the sharing of ultra-rare variants in exome sequencing samples from the UK Biobank. Focusing on loss-of-function variation discovered using exome sequencing, we devised an IBD-based association test and detected 29 associations with 7 blood-related traits, 20 of which were not detected in the exome sequencing study. These results underscore the importance of modelling distant relatedness to reveal subtle population structure, recent evolutionary history, and rare pathogenic variation.

Background: Magnetic resonance-guided focused ultrasound (MRgFUS) is used for non-surgical treatment of uterine fibroids, often in patients who have had prior myomectomy or Cesarean section. The presence of post-surgical MRI artifacts along the beam path are a common contraindication to MRgFUS treatment. While potential problems arising from superficial cutaneous scars can be circumvented through scar patching and other techniques, deeper artifacts are difficult to bypass. Consequently, many patients with deeper artifacts are often excluded from treatment because of the assumption that these artifacts could deflect the ultrasound beam resulting in off target heating or perturb accurate MR thermometry. We sought to determine if these deep artifacts affect MRgFUS treatment efficacy or safety. Materials and Methods: A search of a MRgFUS center patient database yielded 19 patients with prior uterine surgery who had artifacts along the FUS beam path visible on MRI. Charts, operative reports (when available), screening MRI scans, and MRgFUS treatment scans were reviewed by an experienced MRgFUS treatment physician and artifacts were graded as mild, moderate, or severe. Results: One-way ANOVA showed no significant correlation between artifact severity and percent non-perfused volume (%NPV) (p = .41) or between fibroid size and % NPV (p = .49). There were no adverse events in this patient population except for one case of endometritis that occurred months after the operation, unlikely to be related to the MRgFUS treatments. Conclusion: Patients with uterine fibroids with post-operative susceptibility artifacts in the near-field can be successfully treated with MRgFUS.

Detection of Identical-By-Descent (IBD) segments provides a fundamental measure of genetic relatedness and plays a key role in a wide range of analyses. We develop FastSMC, an IBD detection algorithm that combines a fast heuristic search with accurate coalescent-based likelihood calculations. FastSMC enables biobank-scale detection and dating of IBD segments within several thousands of years in the past. We apply FastSMC to 487,409 UK Biobank samples and detect ~214 billion IBD segments transmitted by shared ancestors within the past 1500 years, obtaining a fine-grained picture of genetic relatedness in the UK. Sharing of common ancestors strongly correlates with geographic distance, enabling the use of genomic data to localize a sample’s birth coordinates with a median error of 45 km. We seek evidence of recent positive selection by identifying loci with unusually strong shared ancestry and detect 12 genome-wide significant signals. We devise an IBD-based test for association between phenotype and ultra-rare loss-of-function variation, identifying 29 association signals in 7 blood-related traits., Accurately measuring genetic relatedness by Identical-By-Descent (IBD) segments is challenging in biobank-level genome data. The authors present IBD method FastSMC, which when applied to the UK Biobank gives a detailed picture of genetic relatedness and evolutionary history in the UK over the past 2000 years.

Quality Assurance (QA) for medical linear accelerator (linac) is one of the primary concerns in external beam radiation Therapy. Continued advancements in clinical accelerators and computer control technology make the QA procedures more complex and time consuming which often, adequate software accompanied with specific phantoms is required. To ameliorate that matter, we introduce QALMA (Quality Assurance for Linac with MATLAB), a MALAB toolkit which aims to simplify the quantitative analysis of QA for linac which includes Star-Shot analysis, Picket Fence test, Winston–Lutz test, Multileaf Collimator (MLC) log file analysis and verification of light & radiation field coincidence test. Keywords: Star shot, Picket fence, Winston–Lutz, Light radiation coincidence, Log file analysis, Quality assurance

Introduction: Responding to the coronavirus pandemic, Greece implemented the largest quarantine in its history. No data exist regarding its impact on PM2.5 pollution. We aimed to assess PM2.5 levels before, during, and after lockdown (7 March 2020–16 May 2020) in Volos, one of Greece’s most polluted industrialized cities, and compare PM2.5 levels with those obtained during the same period last year. Meteorological conditions were examined as confounders. Methods: The study period was discriminated into three phases (pre-lockdown: 7 March–9 March, lockdown: 10 March–4 May, and post-lockdown period: 5 May–16 May). A wireless sensors network was used to collect PM2.5, temperature, relative humidity, rainfall, and wind speed data every 2 s. Results: The lockdown resulted in a significant drop of PM2.5 by 37.4% in 2020, compared to 2019 levels. The mean daily concentrations of PM2.5 exceeded the WHO’s guideline value for 24-h mean levels of PM2.5 35% of the study period. During the strictest lockdown (23 March to 4 May), the mean daily PM2.5 levels exceeded the standard 41% of the time. The transition from the pre-lockdown period into lockdown or post-lockdown periods was associated with lower PM2.5 concentrations. Conclusions: A reduction in the mean daily PM2.5 concentration was found compared to 2019. Lockdown was not enough to avoid severe exceedances of air pollution in Volos.

A 51-year-old man underwent diagnostic work-up for an abnormal-appearing ampulla of Vater. Three hours after biopsy of the ampulla, the patient presented with intense symptoms suggesting acute pancreatitis, which was later confirmed with laboratory and radiographic examinations. Other causes were excluded and the acute pancreatitis was considered a procedural complication. This is a rarely reported complication that must be taken into consideration when biopsies are performed in the ampulla of Vater.

Intensity modulated radiation therapy (IMRT) affords the potential to decrease radiation therapy associated toxicity by creating highly conformal dose distribution to tumor. Inverse optimization of IMRT treatment plans is often a time intensive task due to the large scale solution space, and the indubitably complexity of the task. Furthermore, the incorporation of conflicting dose constraints in the treatment plan, usually introduces an additional degree of intricacy. Metaheuristic algorithms have been proposed in the past for global optimization in IMRT treatment planning. However one disadvantage of the aforementioned methods is their extensive computational cost. One way to ameliorate their performance deficiency is to parallelize the application. In the current study we propose a GPU-based levy-firefly algorithm (LFA) for constrained optimization of IMRT treatment planning. The evaluation of our method was realized for two treatment cases: a prostate and a head and neck (H&N) cancer IMRT plans. The studies indicated an ascendable increase of the speedup factor as a function of the number of pencil beams with a maximum of ~11, whereas the performance of the algorithm was decreasing as a function of the population of the swarm particles. In addition, from our simulation results we concluded that 200 fireflies were sufficient for the algorithm to converge in less than 80 iterations. Finally, we demonstrated the effect of penalizing factors on constraining the maximum dose at the organs at risk (OAR) by impeding the dose coverage of the tumor target. The impetus behind our study was to elucidate the performance and generic attributes of the proposed algorithm, as well as the potential of its applicability for IMRT optimization problems.

The purpose of point cloud registration is to find a 3D rigid body transformation so that the 3D coordinates of the point cloud at different angles can be correctly matched. With the current advances of high definition (HD) 3D cameras, several applications have emerged utilizing stereoscopic cameras. For real time objects tracking, fast point cloud registration calculations are required. In the current study we have considered two methods: a standard Singular Value Decomposition (SVD) and a truncated SVD (TSVD) point cloud registration algorithm. The registration process can be summarized in the following steps; the centroids of the chosen point datasets are first found, then they both are aligned to the origin, and then the optimal rotation and translation are determined based on the SVD or on the TSVD technique. Our strategy was firstly to identify the major computational bottlenecks of our code, and secondly parallelize them on the GPU accordingly. Performance tests were conducted on three GPU cards in comparison to a serial version of the algorithm executed on a CPU. Performance comparisons are also conducted between the parallel SVD and the parallel TSVD in order to test the computational efficiency of them on GPU cards. The studies indicated that there is no computational benefit from the parallization of the simple SVD on GPU. On the contrary, there is computational advantage of the parallel TSVD, but it varies with the GPU architecture. Speedup factors were recorded for every registration steps for all GPU cards. The step 2 of registration process was the most computational expensive task for the algorithm, and when it was parallelized on K40m card gave a maximum speed up of ~100 for the maximum number of pixels, while for other resolution sizes the performance of K40m decreased dramatically. The GTX1080Ti card achieved the highest speed up of ~150 for block 2 calculations, for 8K resolution. In overall, for the full registration process GTX1080Ti indicated a linear increase of speedup factors versus the number of pixels, fact that renders it is the most suitable GPU card with respect to the other GPU cards used for the specific application.

The impetus behind our study was to establish a quantitative comparison between the IRIS collimator and the InCise multileaf collimator (MLC) (Accuray Inc. Synnyvale, CA) for prostate stereotactic body radiation therapy (SBRT). Treatment plans for ten prostate cancer patients were performed on MultiPlan™ 5.1.2 treatment planning system utilizing MLC and IRIS for 36.25 Gy in five fractions. To reduce the magnitude of variations between cases, the planning tumor volume (PTV) was defined and outlined for treating prostate gland only, assuming no seminal vesicle or ex-capsule involvement. Evaluation indices of each plan include PTV coverage, conformity index (CI), Paddick's new CI, homogeneity index, and gradient index. Organ at risk (OAR) dose sparing was analyzed by the bladder wall Dmax and V37Gy, rectum Dmax and V36Gy. The radiobiological response was evaluated by tumor control probability and normal tissue complication probability based on equivalent uniform dose. The dose delivery efficiency was evaluated on the basis of planned monitor units (MUs) and the reported treatment time per fraction. Statistical significance was tested using the Wilcoxon signed rank test. The studies indicated that CyberKnife M6™ IRIS and InCise™ MLC produce equivalent SBRT prostate treatment plans in terms of dosimetry, radiobiology, and OAR sparing, except that the MLC plans offer improvement of the dose fall-off gradient by 29% over IRIS. The main advantage of replacing the IRIS collimator with MLC is the improved efficiency, determined from the reduction of MUs by 42%, and a 36% faster delivery time.

Monte Carlo (MC) nano-scale modeling of the cellular damage is desirable but most times is prohibitive for large scaled systems due to their intensive computational cost. In this study a parallelized computational framework is presented, for accelerated MC simulations of both particle propagation and subsequent radiation chemistry at the subcellular level. Given the inherent parallelism of the electron tracks, the physical stage was “embarrassingly parallelized” into a number of independent tasks. For the chemical stage, the diffusion–reaction of the radical species was simulated with a time-driven kinetic Monte Carlo algorithm (KMC) based on the Smoluchowski formalism and the parallelization was realized by employing a spatio-temporal linked-list cell method based on a spatial subdivision with a uniform grid. The evaluation of our method was established on two metrics: speedup and efficiency. The results indicated a linear speedup ratio for the physical stage and a linear latency for shared- versus a distributed-memory system with a maximum of 3.6 ⋅ 10 − 3 % per electron track. For the chemical stage, a series of simulations were performed to show how the execution time per step was scaling with respect to the number of radical species and a 5.7× speedup was achieved when a larger number of reactants were simulated and eight processors were employed. The simulations were deployed on the Amazon EC2 infrastructure. It is also elucidated how the overhead started becoming significant as the number of reactant species decrease relative to the number of processors. The method reported here lays the methodological foundations for accelerated MC simulations and allows envisaging a future use for large-scale radiobiological modeling of multi-cellular systems involved into a clinical scenario.

Purpose: To investigate the feasibility of artificial neural networks (ANN) to reconstruct dose maps for intensity modulated radiation treatment (IMRT) fields compared with those of the treatment planning system (TPS). Methods: An artificial feed forward neural network and the back-propagation learning algorithm have been used to replicate dose calculations of IMRT fields obtained from PINNACLE{sup 3} v9.0. The ANN was trained with fluence and dose maps of IMRT fields for 6 MV x-rays, which were obtained from the amorphous silicon (a-Si) electronic portal imaging device of Novalis TX. Those fluence distributions were imported to the TPS and the dose maps were calculated on the horizontal midpoint plane of a water equivalent homogeneous cylindrical virtual phantom. Each exported 2D dose distribution from the TPS was classified into two clusters of high and low dose regions, respectively, based on the K-means algorithm and the Euclidian metric in the fluence-dose domain. The data of each cluster were divided into two sets for the training and validation phase of the ANN, respectively. After the completion of the ANN training phase, 2D dose maps were reconstructed by the ANN and isodose distributions were created. The dose maps reconstructed by ANN were evaluated and compared withmore » the TPS, where the mean absolute deviation of the dose and the {gamma}-index were used. Results: A good agreement between the doses calculated from the TPS and the trained ANN was achieved. In particular, an average relative dosimetric difference of 4.6% and an average {gamma}-index passing rate of 93% were obtained for low dose regions, and a dosimetric difference of 2.3% and an average {gamma}-index passing rate of 97% for high dose region. Conclusions: An artificial neural network has been developed to convert fluence maps to corresponding dose maps. The feasibility and potential of an artificial neural network to replicate complex convolution kernels in the TPS for IMRT dose calculations have been demonstrated.« less

Over the years, high intensity focused ultrasound (FUS) therapy has become a promising therapeutic alternative for non-invasive tumor treatment. The basic idea of FUS therapy is the elevation of the tissue temperature by the application of focused ultrasound beams to focal spot in the tumor. Biothermal modeling is utilized to predict dynamic temperature distributions generated and altered by the therapeutic heating modality, tissue energy storage and dissipation, and blood flow. Implementation of biothermal modeling in the planning, monitoring, control and evaluation of MR guided Focused Ultrasound (MRgFUS) therapies can help to minimize treatment time, maximize efficacy, and ensure the safety of healthy normal tissues, while increasing clinical confidence in MRgFUS treatments. Fast calculations of thermal doses can support in planning, conduction, and monitoring of such treatments. In the current study a GPU-based method in Matlab is proposed, for fast calculations of the temperature and cumulative equivalent minutes at 43° (CEM 43°) based on the bioheat equation. The performance of our proposed method was assessed with three GPUs (GTX 750, GTX 770 and Tesla C2050) for five grid sizes. The maximum speedup was achieved with the Tesla C2050 (~29) while GTX 750 demonstrated the lower performance (~15).

Recent developments in radiation therapy have been focused on applications of charged particles, especially—protons. Proton therapy can allow higher dose conformality compared to conventional radiation therapy. Dose calculations have an integral role in the successful application of proton therapy. Over the years several dose calculation methods have been proposed in proton therapy. A common characteristic of all these methods is their extensive computational burden. One way to ameliorate that issue is the parallelization of the algorithm. Graphics processing units (GPUs) have recently been employed to accelerate the proton dose calculation process. Pencil-beam dose calculation algorithms for proton therapy have been widely utilized in clinical routine for treatment planning purposes in most clinical settings, due to their simplicity of calculation scheme and acceptable accuracy. In the current study a GPU-based pencil beam algorithm for dose calculations with protons is proposed. The studies indicated a maximum speedup factor of \(\sim \)127 in a homogeneous phantom.

In intensity modulated radiation therapy (IMRT) a treatment plan is a high dimensionality optimization problem with the goal to give the prescribed radiation dose to the Planning Target Volume (PTV) while sparing critical organs. A clinically acceptable plan is usually generated by a numerical optimization process in pursuit of attaining the above mentioned goal. Incorporation of dose volume constraints (DVCs) for the OARs introduce an additional degree of impediment to the optimization task. Heuristic algorithms have been ascertained in the past as a powerful tool for various problems in radiation therapy, such as beam angle optimization (BAO) and IMRT treatment planning. Simulated Annealing (SA) algorithm has the capability to find global minima for bound-constrained optimization problems. However, its performance depends on the penalty method which is utilized for the constraints. In the current study we investigate the performance of three penalty methods for IMRT treatment planning for five prostate cases with dose volume constraints. In addition, sensitivity analysis was performed in order to study the effect of the penalty variables on the treatment plan. Finally the merits and demerits of each method have been discussed.

Theoretical studies have shown that calcium influx through N-methyl-d-aspartate (NMDA) receptors is a sufficient signal to account for various induction protocols of bidirectional synaptic plasticity, including spike time–dependent plasticity (STDP). The STDP curves obtained by these different models exhibits a form of spike time–dependent long-term depression that occurs when a presynaptic spike precedes the postsynaptic spike (pre-post LTD). We have previously proposed that this novel form of LTD can serve as an experimental test for the validity of these models. These calcium based theoretical models assumed deterministic calcium dynamics that reflect average properties of synaptic calcium currents. In this paper, we show that taking into account the stochastic properties of synaptic transmission significantly alters the form of STDP curves and may significantly reduce the magnitude of pre-post LTD.

A rare case ofSphingomonas paucimobilisendophthalmitis secondary to a penetrating globe injury with a retained intraocular foreign body is presented. A 30-year-old man presented with severe pain following a penetrating left eye injury. Visual acuity (VA) was 6/120. Slit-lamp examination revealed perforation of the temporal cornea and iris, hypopyon, and a fibrinous membrane covering the pupil. Ultrasonography showed dense vitreous infiltration and an orbital CT-scan confirmed the presence of a metallic foreign body in the vitreous cavity. Topical and systemic therapy were initiated. Pars-plana vitrectomy combined with phacoemulsification was performed in order to remove the foreign body; vitreous samples were acquired andSphingomonas paucimobilis, sensitive to ceftazidime, was identified. To the best of our knowledge, this is the first report ofSphingomonas paucimobilisendophthalmitis following penetrating ocular injury. In this case,Sphingomonas paucimobiliswas not resistant to antibiotics. This allowed for a good healing response following vitrectomy despite the fact that long-term retinal complications resulted in low VA.

In recent years we have witnessed tremendous progress in selective internal radiation therapy. In clinical practice, quite often, radionuclide therapy is planned using simple models based on standard activity values or activity administered per unit body weight or surface area in spite of the admission that radiation-dose methods provide more accurate dosimetric results. To address that issue, the authors developed a Matlab-based computational software, named Patient Specific Yttrium-90 Dosimetry Toolkit (PSYDT). PSYDT was designed for patient specific voxel-based dosimetric calculations and radiobiological modeling of selective internal radiation therapy with (90)Y microspheres. The developed toolkit is composed of three dimensional dose calculations for both bremsstrahlung and beta emissions. Subsequently, radiobiological modeling is performed on a per-voxel basis and cumulative dose volume histograms (DVHs) are generated. In this report we describe the functionality and visualization features of PSYDT.

In this study, a novel reduced order prioritized algorithm is presented for optimization in radiation therapy treatment planning. The proposed method consists of three stages. In the first stage, the intensity space was sampled by solving a series of unconstrained optimization problems. The objective function of the first stage is expressed as a scalarized weighted sum of partial objectives for the target and organ at risk. Latin hypercube sampling was utilized to define the weights for each run of the unconstrained optimizations. In the second stage, principal component analysis is applied to the solutions determined in the first stage to identify the major eigen modes in the intensities space, significantly reducing the number of independent variables. In the third stage, treatment planning goals/objectives are prioritized, and the problem is solved in the reduced order space. After each objective is optimized, that objective function is converted into a constraint for the lower-priority objectives. In the current formulation, a slip factor is used to relax the hard constraints for planning target volume (PTV) coverage. The applicability of the proposed method is demonstrated for one prostate and one lung intensity-modulated radiation therapy treatment plan. Upon completion of the sequential prioritized optimization, the mean dose at the rectum and bladder was reduced by 21.3% and 22.4%, respectively. Additionally, we investigated the effect of the slip factor `s' on PTV coverage and we found minimal degradation of the tumor dose (~4%). Finally, the speed up factors upon the dimensionality reduction were as high as 49.9 without compromising the quality of the results.

In this paper, a novel hybrid genetic algorithm is presented for optimization in radiation therapy treatment planning. The proposed Reduced Order Memetic Algorithm (ROMA) is a combination of an evolutionary multi-objective optimization algorithm and gradient-based local search in a reduced order space. The gradient-based optimizer is used for a fast local search and is a variant of the sequential quadratic programming method. The execution time of the local search is improved by applying dynamically a principal component analysis to the solutions generated by the genetic optimizer and reducing the high-dimensionality search-space. In particular, for intensity modulated radiation therapy (IMRT) we observed reduction of the search-space dimensionality from several hundreds to less than twenty. Latin hypercube sampling was used to define the weights of the scalarization scheme for the local search fitness function for each individual solution. The proposed hybrid algorithm obtains efficiently a set of diverse non-dominated solutions for a large scale multi-objective problem such as in radiation treatment planning optimization. The applicability of the proposed algorithm is demonstrated for IMRT optimization for a case of prostate cancer.