Dyspnea in Patients Receiving Radical Radiotherapy for Non-Small Cell Lung Cancer: A Prospective Study

Background and Purpose: Dyspnea is an important symptomatic endpoint for assessment of radiation-induced lung injury (RILI) following radical radiotherapy in locally advanced disease, which remains the mainstay of treatment at the time of significant advances in therapy including combination treatments with immunotherapy and chemotherapy and the use of local ablative radiotherapy techniques. We investigated the relationship between dose-volume parameters and subjective changes in dyspnea as a measure of RILI and the relationship to spirometry. Material and Methods: Eighty patients receiving radical radiotherapy for non-small cell lung cancer were prospectively assessed for dyspnea using two patient-completed tools: EORTC QLQ-LC13 dyspnea quality of life assessment and dyspnea visual analogue scale (VAS). Global quality of life, spirometry and radiation pneumonitis grade were also assessed. Comparisons were made with lung dose-volume parameters. Results: The median survival of the cohort was 26 months. In the evaluable group of 59 patients there were positive correlations between lung dose-volume parameters and a change in dyspnea quality of life scale at 3 months (V30 p=0.017; V40 p=0.026; V50 p=0.049; mean lung dose p=0.05), and a change in dyspnea VAS at 6 months (V30 p=0.05; V40 p=0.026; V50 p=0.028) after radiotherapy. Lung dose-volume parameters predicted a 10% increase in dyspnea quality of life score at 3 months (V40; p=0.041, V50; p=0.037) and dyspnea VAS score at 6 months (V40; p=0.027) post-treatment. Conclusions: Worsening of dyspnea is an important symptom of RILI. We demonstrate a relationship between lung dose-volume parameters and a 10% worsening of subjectiv

Alternating electric fields (TTFields) inhibit metastatic spread of solid tumors to the lungs

Tumor treating fields (TTFields) are low intensity, intermediate frequency, alternating electric fields used to treat cancerous tumors. This novel treatment modality effectively inhibits the growth of solid tumors in vivo and has shown promise in pilot clinical trials in patients with advanced stage solid tumors. TTFields were tested for their potential to inhibit metastatic spread of solid tumors to the lungs in two animal models: (1) Mice injected with malignant melanoma cells (B16F10) into the tail vein, (2) New Zealand White rabbits implanted with VX-2 tumors within the kidney capsule. Mice and rabbits were treated using two-directional TTFields at 100–200 kHz. Animals were either monitored for survival, or sacrificed for pathological and histological analysis of the lungs. The total number of lung surface metastases and the absolute weight of the lungs were both significantly lower in TTFields treated mice then in sham control mice. TTFields treated rabbits survived longer than sham control animals. This extension in survival was found to be due to an inhibition of metastatic spread, seeding or growth in the lungs of TTFields treated rabbits compared to controls. Histologically, extensive peri- and intra-tumoral immune cell infiltration was seen in TTFields treated rabbits only. These results raise the possibility that in addition to their proven inhibitory effect on the growth of solid tumors, TTFields may also have clinical benefit in the prevention of metastatic spread from primary tumors

Application of spiking neural networks for modelling the process of high-temperature hydrogen production in systems with gas-cooled reactors

Hydrogen energy is able to solve the problem of the dependence of modern industries on fossil fuels and significantly reduce the amount of harmful emissions. One of the ways to produce hydrogen is high-temperature water-steam electrolysis. Increasing the temperature of the steam involved in electrolysis makes the process more efficient. The key problem is the use of a reliable heat energy source capable of reaching high temperatures. High-temperature gas-cooled reactors with a gaseous coolant and a graphite moderator provide a solution to the problem of heating the electrolyte. Part of the heat energy is used for producing electrical energy required for electrolysis. Modern electrolyzers built as arrays of tubular or planar electrolytic cells with a nuclear energy source make it possible to produce hydrogen by decomposing water molecules, and the working temperature control leads to a decrease in the Nernst potential. The operation of such facilities is complicated by the need to determine the optimal parameters of the electrolysis cell, the steam flow rate, and the operating current density. To reduce the costs associated with the process optimization, it is proposed to use a low-temperature electrolysis system controlled by a spiking neural network. The results confirm the effectiveness of intelligent technologies that implement adaptive control of hybrid modeling processes in order to organize the most feasible hydrogen production in a specific process, the parameters of which can be modified depending on the specific use of the reactor thermal energy. In addition, the results of the study confirm the feasibility of using a combined functional structure made on the basis of spiking neurons to correct the parameters of the developed electrolytic system. The proposed simulation strategy can significantly reduce the consumption of computational resources in comparison with models based only on neural network prediction methods

Prediction of the moderator temperature field in a heavy water reactor based on a cellular neural network

Reactors with heavy water coolants and moderators have been used extensively in today's power industry. Monitoring of the moderator condition plays an important role in ensuring normal operation of a power plant. A cellular neural network, the architecture of which has been adapted for hardware implementation, is proposed for use in a system for prediction of the heavy water moderator temperature. A reactor model composed in accordance with the CANDU Darlington heavy water reactor design was used to form the training sample collection and to control correct operation of the neural network structure. The sample components for the adjustment and configuration of the network topology include key parameters that characterize the energy generation process in the core. The paper considers the feasibility of the temperature prediction only for the calandria's central cross-section. To solve this problem, the cellular neural network architecture has been designed, and major parts of the digital computational element and methods for their implementation based on an FPLD have also been developed. The method is described for organizing an optical coupling between individual neural modules within the network, which enables not only the restructuring of the topology in the training process, but also the assignment of priorities for the propagation of the information signals of neurons depending on the activity in a situation analysis at the neural network structure inlet. Asynchronous activation of cells was used based on an oscillating fractal network, the basis for which was a modified ring oscillator. The efficiency of training the proposed architecture using stochastic diffusion search algorithms is evaluated. A comparative analysis of the model behavior and the results of the neural network operation have shown that the use of the neural network approach is effective in safety systems of power plants

Effective avoidance of a functional spect-perfused lung using intensity modulated radiotherapy (IMRT) for non-small cell lung cancer (NSCLC): an update of a planning study.

IMRT and 3-dimensional conformal radiotherapy (3-DCRT) plans of 25 patients with non-small cell lung (NSCLC) were compared in terms of planning target volume (PTV) coverage and sparing of functional lung (FL) defined by a SPECT perfusion scan. IMRT resulted in significant reduction of functional V(20) and mean lung dose in stage III patients with inhomogeneous hypoperfusion. If the dose to FL is shown to be the determinant of lung toxicity, IMRT would allow for effective dose escalation by specific avoidance of functional lung

A potential to reduce pulmonary toxicity: The use of perfusion SPECT with IMRT for functional lung avoidance in radiotherapy of non-smalt cell lung cancer

BACKGROUND AND PURPOSE: The study aimed to examine specific avoidance of functional lung (FL) defined by a single photon emission computerized tomography (SPECT) lung perfusion scan, using intensity modulated radiotherapy (IMRT) and three-dimensional conformal radiotherapy (3-DCRT) in patients with non-small cell lung cancer (NSCLC). MATERIALS AND METHODS: Patients with NSCLC underwent planning computerized tomography (CT) and lung perfusion SPECT scan in the treatment position using fiducial markers to allow co-registration in the treatment planning system. Radiotherapy (RT) volumes were delineated on the CT scan. FL was defined using co-registered SPECT images. Two inverse coplanar RT plans were generated for each patient: 4-field 3-DCRT and 5-field step-and-shoot IMRT. 3-DCRT plans were created using automated AutoPlan optimisation software, and IMRT plans were generated employing Pinnacle(3) treatment planning system (Philips Radiation Oncology Systems). All plans were prescribed to 64 Gy in 32 fractions using data for the 6 MV beam from an Elekta linear accelerator. The objectives for both plans were to minimize the volume of FL irradiated to 20 Gy (fV(20)) and dose variation within the planning target volume (PTV). A spinal cord dose was constrained to 46 Gy. Volume of PTV receiving 90% of the prescribed dose (PTV(90)), fV(20), and functional mean lung dose (fMLD) were recorded. The PTV(90)/fV(20) ratio was used to account for variations in both measures, where a higher value represented a better plan. RESULTS: Thirty-four RT plans of 17 patients with stage I-IIIB NSCLC suitable for radical RT were analysed. In 6 patients with stage I-II disease there was no improvement in PTV(90), fV(20), PTV/fV(20) ratio and fMLD using IMRT compared to 3-DCRT. In 11 patients with stage IIIA-B disease, the PTV was equally well covered with IMRT and 3-DCRT plans, with IMRT producing better PTV(90)/fV(20) ratio (mean ratio - 7.2 vs. 5.3, respectively, p=0.001) and reduced fMLD figures compared to 3-DCRT (mean value - 11.5 vs. 14.3 Gy, p=0.001). This was due to reduction in fV(20) while maintaining PTV coverage. CONCLUSION: The use of IMRT compared to 3-DCRT improves the avoidance of FL defined by perfusion SPECT scan in selected patients with locally advanced NSCLC. If the dose to FL is shown to be the primary determinant of lung toxicity, IMRT would allow for effective dose escalation by specific avoidance of FL