Comparison of conventional and CT-based planning for intracavitary brachytherapy for cervical cancer: target volume coverage and organs at risk doses

<p>Abstract</p> <p>Background</p> <p>To compare intracavitary brachytherapy (ICBT) planning methods for cervical cancer, based on either orthogonal radiographs (conventional plan) or CT sections (CT plan); the comparison focused on target volume coverage and dose volume analysis of organs at risk (OARs), by representing point doses defined by the International Commission on Radiation Units and Measurement (ICRU) and dose volume histograms (DVHs) from 3D planning.</p> <p>Methods</p> <p>We analyzed the dosimetric data for 62 conventional and CT-based ICBT plans. The gross tumor volume (GTV), clinical target volume (CTV) and organs at risk (OAR)s were contoured on the CT-plan. Point A and ICRU 38 rectal and bladder points were defined on reconstructed CT images.</p> <p>Results</p> <p>Patients were categorized on the basis of whether the >95% isodose line of the point-A prescription dose encompassed the CTV (group 1, n = 24) or not (group 2, n = 38). The mean GTV and CTV (8.1 cc and 20.6 cc) were smaller in group 1 than in group 2 (24.7 cc and 48.4 cc) (<it>P <</it>0.001). The mean percentage of GTV and CTV coverage with the 7 Gy isodose was 93.1% and 88.2% for all patients, and decreased with increasing tumor size and stage. The mean D2 and D5 rectum doses were 1.66 and 1.42 times higher than the corresponding ICRU point doses and the mean D2 and D5 bladder doses were 1.51 and 1.28 times higher. The differences between the ICRU dose and the D2 and D5 doses were significantly higher in group 2 than in group 1 for the bladder, but not for the rectum.</p> <p>Conclusion</p> <p>The CT-plan is superior to the conventional plan in target volume coverage and appropriate evaluation of OARs, as the conventional plan overestimates tumor doses and underestimates OAR doses.</p

Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy Gradient Methods Fail

Changes of synaptic connections between neurons are thought to be the physiological basis of learning. These changes can be gated by neuromodulators that encode the presence of reward. We study a family of reward-modulated synaptic learning rules for spiking neurons on a learning task in continuous space inspired by the Morris Water maze. The synaptic update rule modifies the release probability of synaptic transmission and depends on the timing of presynaptic spike arrival, postsynaptic action potentials, as well as the membrane potential of the postsynaptic neuron. The family of learning rules includes an optimal rule derived from policy gradient methods as well as reward modulated Hebbian learning. The synaptic update rule is implemented in a population of spiking neurons using a network architecture that combines feedforward input with lateral connections. Actions are represented by a population of hypothetical action cells with strong mexican-hat connectivity and are read out at theta frequency. We show that in this architecture, a standard policy gradient rule fails to solve the Morris watermaze task, whereas a variant with a Hebbian bias can learn the task within 20 trials, consistent with experiments. This result does not depend on implementation details such as the size of the neuronal populations. Our theoretical approach shows how learning new behaviors can be linked to reward-modulated plasticity at the level of single synapses and makes predictions about the voltage and spike-timing dependence of synaptic plasticity and the influence of neuromodulators such as dopamine. It is an important step towards connecting formal theories of reinforcement learning with neuronal and synaptic properties

Sales promotions and channel coordination

Consumer sales promotions are usually the result of the decisions of two marketing channel parties, the manufacturer and the retailer. In making these decisions, each party normally follows its own interest: i.e. maximizes its own profit. Unfortunately, this results in a suboptimal outcome for the channel as a whole. Independent profit maximization by channel parties leads to a lack of channel coordination with the implication of leaving money on the table. This may well contribute to the notoriously low profitability of sales promotions. This paper first shows analytically why the suboptimality occurs, and then presents an empirical demonstration, using a unique dataset from an Efficient Consumer Response (ECR) project; ECR is a movement in which parties work together to optimize the distribution channel). In this dataset, actual profit is only a small fraction of potential profit, implying that there is a large degree of suboptimality. It is important that (1) channel parties are aware of this suboptimality; and (2) that they have tools to deal with it. Solutions to the channel coordination problem should ensure that the goals of the individual channel parties are aligned with the goals of the channel as a whole. The paper proposes one particular agreement for this purpose, called proportional discount sharing. Application to the ECR data shows a win-win result for both the manufacturer and the retailer. Recognition of the channel coordination problem by the manufacturer and the retailer is the necessary starting point for agreeing on a way of solving it in a win-win fashion

Small Vessel Ischemic Disease of the Brain and Brain Metastases in Lung Cancer Patients

Brain metastases occur commonly in patients with lung cancer. Small vessel ischemic disease is frequently found when imaging the brain to detect metastases. We aimed to determine if the presence of small vessel ischemic disease (SVID) of the brain is protective against the development of brain metastases in lung cancer patients.A retrospective cohort of 523 patients with biopsy confirmed lung cancer who had received magnetic resonance imaging of the brain as part of their standard initial staging evaluation was reviewed. Information collected included demographics, comorbidities, details of the lung cancer, and the presence of SVID of the brain. A portion of the cohort had the degree of SVID graded. The primary outcome measure was the portion of study subjects with and without SVID of the brain who had evidence of brain metastases at the time of initial staging of their lung cancer.109 patients (20.8%) had evidence of brain metastases at presentation and 345 (66.0%) had evidence of SVID. 13.9% of those with SVID and 34.3% of those without SVID presented with brain metastases (p<0.0001). In a model including age, diabetes mellitus, hypertension, hyperlipidemia, and tobacco use, SVID of the brain was found to be the only protective factor against the development of brain metastases, with an OR of 0.31 (0.20, 0.48; p<0.001). The grade of SVID was higher in those without brain metastases.These findings suggest that vascular changes in the brain are protective against the development of brain metastases in lung cancer patients

Mathematical properties of neuronal TD-rules and differential Hebbian learning: a comparison

A confusingly wide variety of temporally asymmetric learning rules exists related to reinforcement learning and/or to spike-timing dependent plasticity, many of which look exceedingly similar, while displaying strongly different behavior. These rules often find their use in control tasks, for example in robotics and for this rigorous convergence and numerical stability is required. The goal of this article is to review these rules and compare them to provide a better overview over their different properties. Two main classes will be discussed: temporal difference (TD) rules and correlation based (differential hebbian) rules and some transition cases. In general we will focus on neuronal implementations with changeable synaptic weights and a time-continuous representation of activity. In a machine learning (non-neuronal) context, for TD-learning a solid mathematical theory has existed since several years. This can partly be transfered to a neuronal framework, too. On the other hand, only now a more complete theory has also emerged for differential Hebb rules. In general rules differ by their convergence conditions and their numerical stability, which can lead to very undesirable behavior, when wanting to apply them. For TD, convergence can be enforced with a certain output condition assuring that the δ-error drops on average to zero (output control). Correlation based rules, on the other hand, converge when one input drops to zero (input control). Temporally asymmetric learning rules treat situations where incoming stimuli follow each other in time. Thus, it is necessary to remember the first stimulus to be able to relate it to the later occurring second one. To this end different types of so-called eligibility traces are being used by these two different types of rules. This aspect leads again to different properties of TD and differential Hebbian learning as discussed here. Thus, this paper, while also presenting several novel mathematical results, is mainly meant to provide a road map through the different neuronally emulated temporal asymmetrical learning rules and their behavior to provide some guidance for possible applications

Antiangiogenic agents in the treatment of recurrent or newly diagnosed glioblastoma: Analysis of single-agent and combined modality approaches

Surgical resection followed by radiotherapy and temozolomide in newly diagnosed glioblastoma can prolong survival, but it is not curative. For patients with disease progression after frontline therapy, there is no standard of care, although further surgery, chemotherapy, and radiotherapy may be used. Antiangiogenic therapies may be appropriate for treating glioblastomas because angiogenesis is critical to tumor growth. In a large, noncomparative phase II trial, bevacizumab was evaluated alone and with irinotecan in patients with recurrent glioblastoma; combination treatment was associated with an estimated 6-month progression-free survival (PFS) rate of 50.3%, a median overall survival of 8.9 months, and a response rate of 37.8%. Single-agent bevacizumab also exceeded the predetermined threshold of activity for salvage chemotherapy (6-month PFS rate, 15%), achieving a 6-month PFS rate of 42.6% (p < 0.0001). On the basis of these results and those from another phase II trial, the US Food and Drug Administration granted accelerated approval of single-agent bevacizumab for the treatment of glioblastoma that has progressed following prior therapy. Potential antiangiogenic agents-such as cilengitide and XL184-also show evidence of single-agent activity in recurrent glioblastoma. Moreover, the use of antiangiogenic agents with radiation at disease progression may improve the therapeutic ratio of single-modality approaches. Overall, these agents appear to be well tolerated, with adverse event profiles similar to those reported in studies of other solid tumors. Further research is needed to determine the role of antiangiogenic therapy in frontline treatment and to identify the optimal schedule and partnering agents for use in combination therapy