Project description:Glioblastomas are the most common primary brain tumours. They are known for their highly aggressive growth and invasion, leading to short survival times. Treatments for glioblastomas commonly involve a combination of surgical intervention, chemotherapy, and external beam radiation therapy (XRT). Previous works have not only successfully modelled the natural growth of glioblastomas in vivo, but also show potential for the prediction of response to radiation prior to treatment. This suggests that the efficacy of XRT can be optimized before treatment in order to yield longer survival times. However, while current efforts focus on optimal scheduling of radiotherapy treatment, they do not include a similarly sophisticated spatial optimization. In an effort to improve XRT, we present a method for the spatial optimization of radiation profiles. We expand upon previous results in the general problem and examine the more physically reasonable cases of 1-step and 2-step radiation profiles during the first and second XRT fractions. The results show that by including spatial optimization in XRT, while retaining a constant prescribed total dose amount, we are able to increase the total cell kill from the clinically-applied uniform case.
Project description:Lung tumors are often associated with a poor prognosis although different schedules and treatment modalities have been extensively tested in the clinical practice. The complexity of this disease and the use of combined therapeutic approaches have been investigated and the use of high dose-rates is emerging as effective strategy. Technological improvements of clinical linear accelerators allow combining high dose-rate and a more conformal dose delivery with accurate imaging modalities pre- and during therapy. This paper aims at reporting the state of the art and future direction in the use of radiobiological models and radiobiological-based optimizations in the clinical practice for the treatment of lung cancer. To address this issue, a search was carried out on PubMed database to identify potential papers reporting tumor control probability and normal tissue complication probability for lung tumors. Full articles were retrieved when the abstract was considered relevant, and only papers published in English language were considered. The bibliographies of retrieved papers were also searched and relevant articles included. At the state of the art, dose-response relationships have been reported in literature for local tumor control and survival in stage III non-small cell lung cancer. Due to the lack of published radiobiological models for SBRT, several authors used dose constraints and models derived for conventional fractionation schemes. Recently, several radiobiological models and parameters for SBRT have been published and could be used in prospective trials although external validations are recommended to improve the robustness of model predictive capability. Moreover, radiobiological-based functions have been used within treatment planning systems for plan optimization but the advantages of using this strategy in the clinical practice are still under discussion. Future research should be directed toward combined regimens, in order to potentially improve both local tumor control and survival. Indeed, accurate knowledge of the relevant parameters describing tumor biology and normal tissue response is mandatory to correctly address this issue. In this context, the role of medical physicists and the AAPM in the development of radiobiological models is crucial for the progress of developing specific tool for radiobiological-based optimization treatment planning.
Project description:Intensity modulated proton therapy (IMPT) is highly sensitive to range uncertainties and uncertainties caused by setup variation. The conventional inverse treatment planning of IMPT optimized based on the planning target volume (PTV) is not often sufficient to ensure robustness of treatment plans. In this paper, a method that takes the uncertainties into account during plan optimization is used to mitigate the influence of uncertainties in IMPT.The authors use the so-called "worst-case robust optimization" to render IMPT plans robust in the face of uncertainties. For each iteration, nine different dose distributions are computed-one each for ± setup uncertainties along anteroposterior (A-P), lateral (R-L) and superior-inferior (S-I) directions, for ± range uncertainty, and the nominal dose distribution. The worst-case dose distribution is obtained by assigning the lowest dose among the nine doses to each voxel in the clinical target volume (CTV) and the highest dose to each voxel outside the CTV. Conceptually, the use of worst-case dose distribution is similar to the dose distribution achieved based on the use of PTV in traditional planning. The objective function value for a given iteration is computed using this worst-case dose distribution. The objective function used has been extended to further constrain the target dose inhomogeneity.The worst-case robust optimization method is applied to a lung case, a skull base case, and a prostate case. Compared with IMPT plans optimized using conventional methods based on the PTV, our method yields plans that are considerably less sensitive to range and setup uncertainties. An interesting finding of the work presented here is that, in addition to reducing sensitivity to uncertainties, robust optimization also leads to improved optimality of treatment plans compared to the PTV-based optimization. This is reflected in reduction in plan scores and in the lower normal tissue doses for the same coverage of the target volume when subjected to uncertainties.The authors find that the worst-case robust optimization provides robust target coverage without sacrificing, and possibly even improving, the sparing of normal tissues. Our results demonstrate the importance of robust optimization. The authors assert that all IMPT plans should be robustly optimized.
Project description:The general concept of radiation therapy used in conventional cancer treatment is to increase the therapeutic index by creating a physical dose differential between tumors and normal tissues through precision dose targeting, image guidance, and radiation beams that deliver a radiation dose with high conformality, e.g., protons and ions. However, the treatment and cure are still limited by normal tissue radiation toxicity, with the corresponding side effects. A fundamentally different paradigm for increasing the therapeutic index of radiation therapy has emerged recently, supported by preclinical research, and based on the FLASH radiation effect. FLASH radiation therapy (FLASH-RT) is an ultra-high-dose-rate delivery of a therapeutic radiation dose within a fraction of a second. Experimental studies have shown that normal tissues seem to be universally spared at these high dose rates, whereas tumors are not. While dose delivery conditions to achieve a FLASH effect are not yet fully characterized, it is currently estimated that doses delivered in less than 200 ms produce normal-tissue-sparing effects, yet effectively kill tumor cells. Despite a great opportunity, there are many technical challenges for the accelerator community to create the required dose rates with novel compact accelerators to ensure the safe delivery of FLASH radiation beams.
Project description:Despite the historically limited role of radiotherapy in the management of primary hepatic malignancies, modern advances in treatment design and delivery have renewed enthusiasm for radiation as a potentially curative treatment modality. Surgical resection and/or liver transplantation are traditionally regarded as the most effective forms of therapy, although the majority of patients with hepatocellular carcinoma and intrahepatic cholangiocarcinoma present with locally advanced or unresectable disease on the basis of local vascular invasion or inadequate baseline hepatobiliary function. In this context, many efforts have focused on nonoperative treatment approaches including novel systemic therapies, transarterial chemoembolization, ethanol ablation, radiofrequency ablation, and stereotactic body radiation therapy (SBRT). This review aims to summarize modern advances in radiotherapy, particularly SBRT, in the treatment of primary hepatic malignancies.
Project description:The aim of this study was to review institutional outcomes for advanced thyroid cancers treated with fast neutron radiation therapy (FNRT) and photon radiation therapy (RT).In all, 62 consecutive patients were analyzed. Fifty-nine had stage IV disease. Twenty-three were treated with FNRT and 39 with photon RT. Median follow-up was 14 months. The primary endpoint was overall survival (OS).There was no significant difference in median OS between FNRT and photon RT (26 vs 16 months; P = .49). Patients with well-differentiated histologies had superior median OS with photon RT (17 vs 69 months; P = .04). There was a nonsignificant trend toward improved OS with FNRT for medullary and anaplastic histologies.Outcomes in this study are in line with historical results. There is an apparent detriment in OS with FNRT for well-differentiated histologies and a trend toward improved OS with medullary and anaplastic histologies that warrants further investigation.
Project description:Radiation therapy (RT) represents an integral part of a multimodality treatment plan in the definitive, preoperative and postoperative management of non-small cell lung cancer (NSCLC). Technological advances in RT have enabled a shift from two-dimensional radiotherapy to more conformal techniques. Three-dimensional conformal radiotherapy (3DCRT), the current minimum technological standard for treating NSCLC, allows for more accurate delineation of tumor burden by using computed tomography-based treatment planning instead of two-dimensional radiographs. Intensity-modulated RT (IMRT) and proton therapy represent advancements over 3DCRT that aim to improve the conformity of RT and provide the possibility for dose escalation to the tumor by minimizing radiation dose to organs at risk. Both techniques likely confer benefits to certain anatomic subgroups of NSCLC requiring RT. This article reviews pertinent studies evaluating the use of IMRT and proton therapy in locally advanced NSCLC, and outlines challenges, indications for use, and areas for future research.
Project description:We assessed the effect of beam size on plan robustness for intensity-modulated proton therapy (IMPT) of head and neck cancer (HNC) and compared the plan quality including robustness with that of intensity-modulated radiation therapy (IMRT). IMPT plans were generated for six HNC patients using six beam sizes (air-sigma 3-17 mm at isocenter for a 70-230 MeV) and two optimization methods for planning target volume-based non-robust optimization (NRO) and clinical target volume (CTV)-based robust optimization (RO). Worst-case dosimetric parameters and plan robustness for CTV and organs-at-risk (OARs) were assessed under different scenarios, assuming a ± 1-5 mm setup error and a ± 3% range error. Statistical comparisons of NRO-IMPT, RO-IMPT and IMRT plans were performed. In regard to CTV-D99%, RO-IMPT with smaller beam size was more robust than RO-IMPT with larger beam sizes, whereas NRO-IMPT showed the opposite (P < 0.05). There was no significant difference in the robustness of the CTV-D99% and CTV-D95% between RO-IMPT and IMRT. The worst-case CTV coverage of IMRT (±5 mm/3%) for all patients was 96.0% ± 1.4% (D99%) and 97.9% ± 0.3% (D95%). For four out of six patients, the worst-case CTV-D95% for RO-IMPT (±1-5 mm/3%) were higher than those for IMRT. Compared with IMRT, RO-IMPT with smaller beam sizes achieved lower worst-case doses to OARs. In HNC treatment, utilizing smaller beam sizes in RO-IMPT improves plan robustness compared to larger beam sizes, achieving comparable target robustness and lower worst-case OARs doses compared to IMRT.
Project description:Clinical evidence is crucial in enabling the judicious adoption of technological innovations in radiation therapy (RT). Pharmaceutical evidence development frameworks are not useful for understanding how technical advances are maturing. In this paper, we introduce a new framework, the Radiation Therapy Technology Evidence Matrix (rtTEM), that helps visualize how the clinical evidence supporting new technologies is developing. The matrix is a unique 2D model based on the R-IDEAL clinical evaluation framework. It can be applied to clinical hypothesis testing trials, as well as publications reporting clinical treatment. We present the rtTEM and illustrate its application, using emerging and mature RT technologies as examples. The model breaks down the type of claim along the vertical axis and the strength of the evidence for that claim on the horizontal axis, both of which are inherent in clinical hypothesis testing. This simplified view allows for stakeholders to understand where the evidence is and where it is heading. Ultimately, the value of an innovation is typically demonstrated through superiority studies, which we have divided into three key categories - administrative, toxicity and control, to enable more detailed visibility of evidence development in that claim area. We propose the rtTEM can be used to track evidence development for new interventions in RT. We believe it will enable researchers and sponsors to identify gaps in evidence and to further direct evidence development. Thus, by highlighting evidence looked for by key policy decision makers, the rtTEM will support wider, timely patient access to high value technological advances.
Project description:The lateral hypothalamus (LH) is critically involved in the regulation of homeostatic energy balance. Some neurons in the LH express receptors for leptin (LepRb), a hormone known to increase energy expenditure and decrease energy intake. However, the neuroanatomical inputs to LepRb-expressing LH neurons remain unknown. We used rabies virus tracing technology to map these inputs, but encountered non-specific tracing. To optimize this technology for a minor cell population (LepRb is not ubiquitously expressed in LH), we used LepRb-Cre mice and assessed how different titers of the avian tumor virus receptor A (TVA) helper virus affected rabies tracing efficiency and specificity. We found that rabies expression is dependent on TVA receptor expression, and that leakiness of TVA receptors is dependent on the titer of TVA virus used. We concluded that a titer of 1.0-3.0 × 107 genomic copies per µl of the TVA virus is optimal for rabies tracing. Next, we successfully applied modified rabies virus tracing technology to map inputs to LepRb-expressing LH neurons. We discovered that other neurons in the LH itself, the periventricular hypothalamic nucleus (Pe), the posterior hypothalamic nucleus (PH), the bed nucleus of the stria terminalis (BNST), and the paraventricular hypothalamic nucleus (PVN) are the most prominent input areas to LepRb-expressing LH neurons.