When is Better Best? A multiobjective perspective

Purpose: To identify the most informative methods for reporting results of treatment planning comparisons. Methods: Seven papers from the past year of International Journal of Radiation Oncology Biology Physics reported on comparisons of treatment plans for IMRT and IMAT. The papers were reviewed to identify methods of comparisons. Decision theoretical concepts were used to evaluate the study methods and highlight those that provide the most information. Results: None of the studies examined the correlation between objectives. Statistical comparisons provided some information but not enough to make provide support for a robust decision analysis. Conclusion: The increased use of treatment planning studies to evaluate different methods in radiation therapy requires improved standards for designing the studies and reporting the results

A Hierachical Evolutionary Algorithm for Multiobjective Optimization in IMRT

Purpose: Current inverse planning methods for IMRT are limited because they are not designed to explore the trade-offs between the competing objectives between the tumor and normal tissues. Our goal was to develop an efficient multiobjective optimization algorithm that was flexible enough to handle any form of objective function and that resulted in a set of Pareto optimal plans. Methods: We developed a hierarchical evolutionary multiobjective algorithm designed to quickly generate a diverse Pareto optimal set of IMRT plans that meet all clinical constraints and reflect the trade-offs in the plans. The top level of the hierarchical algorithm is a multiobjective evolutionary algorithm (MOEA). The genes of the individuals generated in the MOEA are the parameters that define the penalty function minimized during an accelerated deterministic IMRT optimization that represents the bottom level of the hierarchy. The MOEA incorporates clinical criteria to restrict the search space through protocol objectives and then uses Pareto optimality among the fitness objectives to select individuals. Results: Acceleration techniques implemented on both levels of the hierarchical algorithm resulted in short, practical runtimes for optimizations. The MOEA improvements were evaluated for example prostate cases with one target and two OARs. The modified MOEA dominated 11.3% of plans using a standard genetic algorithm package. By implementing domination advantage and protocol objectives, small diverse populations of clinically acceptable plans that were only dominated 0.2% by the Pareto front could be generated in a fraction of an hour. Conclusions: Our MOEA produces a diverse Pareto optimal set of plans that meet all dosimetric protocol criteria in a feasible amount of time. It optimizes not only beamlet intensities but also objective function parameters on a patient-specific basis

Conditional Ablation of Macrophages Halts Progression of Crescentic Glomerulonephritis

The presence of macrophages in inflamed glomeruli of rat kidney correlates with proliferation and apoptosis of resident glomerular mesangial cells. We assessed the contribution of inflammatory macrophages to progressive renal injury in murine crescentic glomerulonephritis (GN). Using a novel transgenic mouse (CD11b-DTR) in which tissue macrophages can be specifically and selectively ablated by minute injections of diphtheria toxin, we depleted renal inflammatory macrophages through days 15 and 20 of progressive crescentic GN. Macrophage depletion reduced the number of glomerular crescents, improved renal function, and reduced proteinuria. Morphometric analysis of renal tubules and interstitium revealed a marked attenuation of tubular injury that was associated with reduced proliferation and apoptosis of tubular cells. The population of interstitial myofibroblasts decreased after macrophage depletion and interstitial fibrosis also decreased. In the presence of macrophages, interstitial myofibroblasts exhibited increased levels of both proliferation and apoptosis, suggesting that macrophages act to support a population of renal myofibroblasts in a high turnover state and in matrix deposition. Finally, deletion of macrophages reduced CD4 T cells in the diseased kidney. This study demonstrates that macrophages are key effectors of disease progression in crescentic GN, acting to regulate parenchymal cell populations by modulating both cell proliferation and apoptosis

Models of peer support to remediate post-intensive care syndrome: A report developed by the SCCM Thrive International Peer Support Collaborative

Objective: Patients and caregivers can experience a range of physical, psychological, and cognitive problems following critical care discharge. The use of peer support has been proposed as an innovative support mechanism. Design: We sought to identify technical, safety and procedural aspects of existing operational models of peer support, among the Society of Critical Care Medicine Thrive Peer Support Collaborative. We also sought to categorize key distinctions between these models and elucidate barriers and facilitators to implementation. Subjects: 17 Thrive sites from the USA, UK, and Australia were represented by a range of healthcare professionals. Interventions: Via an iterative process of in-person and email/conference calls, members of the Collaborative, defined the key areas on which peer support models could be defined and compared; collected detailed self-reports from all sites; reviewed the information and identified clusters of models. Barriers and challenges to implementation of peer support models were also documented. Results: Within the Thrive Collaborative, six general models of peer support were identified: Community based, Psychologist-led outpatient, Models based within ICU follow-up clinics, Online, Groups based within ICU and Peer mentor models. The most common barriers to implementation were: recruitment to groups, personnel input and training: sustainability and funding, risk management and measuring success. Conclusion: A number of different models of peer support are currently being developed to help patients and families recover and grow in the post-critical care setting

Investigation of effective decision criteria for multiobjective optimization in IMRT

Purpose: To investigate how using different sets of decision criteria impacts the quality of intensity modulated radiation therapy (IMRT) plans obtained by multiobjective optimization

Toward patient-specific, biologically optimized radiation therapy plans for the treatment of glioblastoma.

PURPOSE: To demonstrate a method of generating patient-specific, biologically-guided radiotherapy dose plans and compare them to the standard-of-care protocol. METHODS AND MATERIALS: We integrated a patient-specific biomathematical model of glioma proliferation, invasion and radiotherapy with a multiobjective evolutionary algorithm for intensity-modulated radiation therapy optimization to construct individualized, biologically-guided plans for 11 glioblastoma patients. Patient-individualized, spherically-symmetric simulations of the standard-of-care and optimized plans were compared in terms of several biological metrics. RESULTS: The integrated model generated spatially non-uniform doses that, when compared to the standard-of-care protocol, resulted in a 67% to 93% decrease in equivalent uniform dose to normal tissue, while the therapeutic ratio, the ratio of tumor equivalent uniform dose to that of normal tissue, increased between 50% to 265%. Applying a novel metric of treatment response (Days Gained) to the patient-individualized simulation results predicted that the optimized plans would have a significant impact on delaying tumor progression, with increases from 21% to 105% for 9 of 11 patients. CONCLUSIONS: Patient-individualized simulations using the combination of a biomathematical model with an optimization algorithm for radiation therapy generated biologically-guided doses that decreased normal tissue EUD and increased therapeutic ratio with the potential to improve survival outcomes for treatment of glioblastoma