Dataset Information

Impact of Fractionation and Dose in a Multivariate Model for Radiation-Induced Chest Wall Pain.

ABSTRACT: To determine the role of patient/tumor characteristics, radiation dose, and fractionation using the linear-quadratic (LQ) model to predict stereotactic body radiation therapy-induced grade ? 2 chest wall pain (CWP2) in a larger series and develop clinically useful constraints for patients treated with different fraction numbers.A total of 316 lung tumors in 295 patients were treated with stereotactic body radiation therapy in 3 to 5 fractions to 39 to 60 Gy. Absolute dose-absolute volume chest wall (CW) histograms were acquired. The raw dose-volume histograms (?/? = ? Gy) were converted via the LQ model to equivalent doses in 2-Gy fractions (normalized total dose, NTD) with ?/? from 0 to 25 Gy in 0.1-Gy steps. The Cox proportional hazards (CPH) model was used in univariate and multivariate models to identify and assess CWP2 exposed to a given physical and NTD.The median follow-up was 15.4 months, and the median time to development of CWP2 was 7.4 months. On a univariate CPH model, prescription dose, prescription dose per fraction, number of fractions, D83cc, distance of tumor to CW, and body mass index were all statistically significant for the development of CWP2. Linear-quadratic correction improved the CPH model significance over the physical dose. The best-fit ?/? was 2.1 Gy, and the physical dose (?/? = ? Gy) was outside the upper 95% confidence limit. With ?/? = 2.1 Gy, VNTD99Gy was most significant, with median VNTD99Gy = 31.5 cm(3) (hazard ratio 3.87, P<.001).There were several predictive factors for the development of CWP2. The LQ-adjusted doses using the best-fit ?/? = 2.1 Gy is a better predictor of CWP2 than the physical dose. To aid dosimetrists, we have calculated the physical dose equivalent corresponding to VNTD99Gy = 31.5 cm(3) for the 3- to 5-fraction groups.

SUBMITTER: Din SU

PROVIDER: S-EPMC4886343 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Impact of Fractionation and Dose in a Multivariate Model for Radiation-Induced Chest Wall Pain.

Din Shaun U SU Williams Eric L EL Jackson Andrew A Rosenzweig Kenneth E KE Wu Abraham J AJ Foster Amanda A Yorke Ellen D ED Rimner Andreas A

International journal of radiation oncology, biology, physics 20150614 2

<h4>Purpose</h4>To determine the role of patient/tumor characteristics, radiation dose, and fractionation using the linear-quadratic (LQ) model to predict stereotactic body radiation therapy-induced grade ≥ 2 chest wall pain (CWP2) in a larger series and develop clinically useful constraints for patients treated with different fraction numbers.<h4>Methods and materials</h4>A total of 316 lung tumors in 295 patients were treated with stereotactic body radiation therapy in 3 to 5 fractions to 39 t ...[more]

PMID: 26254680

Similar Datasets

Project description:Radiation-induced pulmonary fibrosis (RIPF) is the most common bottleneck of radiation therapy (RT) that limits its tumor-killing effect. Up to date, there is no effective therapeutic agent for RIPF treatment due to absence of realistic preclinical models. Lungs of mice exposed to focal, highly localized dose of 75Gy-100Gy represents short time-taking (up to 6 weeks) modality for mimicking recent advanced RT, stereotactic body RT-associated lung fibrosis. However, extensive fibrosis and possibility of animal lethality resulted from exposure to high dose raises a question regarding the appropriate dose threshold for limiting unnecessary responses and obtain clinically relevant results. We observed in preliminary trials that lung tissues of 65Gy-exposed mice are still able to develop inflammation and fibrosis at the same time cap. But the molecular changes associated with dose reduction is still unknown. To examine this, bulk RNA from 65Gy and 75Gy irradiated as well as normal lung tissues of mice were obtained, and analysed using computational approach to uncover the transcriptomal similarities and differences between the differentially irradiated samples. Differentially expressed genes (DEGs) were analysed and 2-week and 6-week intersected DEGs as well as 65 and 75Gy exclusive DEGs at 2-week and 6-week time points were detected using venn diagramme. Expression direction of intersected DEGs between 65Gy and 75Gy was checked and found to be consistent at both inflammation and fibrosis stages proven visually by MDS and heatmap graphs. All-times intersected DEGs are 488 and involved in inflammation, cytokine production, and cell proliferation; 2-week intersected DEGs are 221 and involved in cell cycle and DNA damage; 6-week intersected DEGs are 403 and involved in immunoglobin production, extracellular matrix (ECM) deposition, and ECM-receptor interactions. Interestingly, only 75Gy exclusive DEGs of 2 and 6 weeks presented inflammation and fibrosis-related biological process, respectively. These include anti-inflammatory process, cytokine production, EMT, vasculogenesis, and angiogenesis. These results suggested that 65Gy maybe a better dose for delivering less exaggerated, clinically relevant inflammation and fibrotic events, and thus, it can be utilised in establishing appropriate preclinical models for studying RIPF pathology and therapy.

Project description:ObjectiveFew studies have explored the clinical feasibility of using deep-learning reconstruction to reduce the radiation dose of CT. We aimed to compare the image quality and lung nodule detectability between chest CT using a quarter of the low dose (QLD) reconstructed with vendor-agnostic deep-learning image reconstruction (DLIR) and conventional low-dose (LD) CT reconstructed with iterative reconstruction (IR).Materials and methodsWe retrospectively collected 100 patients (median age, 61 years [IQR, 53-70 years]) who received LDCT using a dual-source scanner, where total radiation was split into a 1:3 ratio. QLD CT was generated using a quarter dose and reconstructed with DLIR (QLD-DLIR), while LDCT images were generated using a full dose and reconstructed with IR (LD-IR). Three thoracic radiologists reviewed subjective noise, spatial resolution, and overall image quality, and image noise was measured in five areas. The radiologists were also asked to detect all Lung-RADS category 3 or 4 nodules, and their performance was evaluated using area under the jackknife free-response receiver operating characteristic curve (AUFROC).ResultsThe median effective dose was 0.16 (IQR, 0.14-0.18) mSv for QLD CT and 0.65 (IQR, 0.57-0.71) mSv for LDCT. The radiologists' evaluations showed no significant differences in subjective noise (QLD-DLIR vs. LD-IR, lung-window setting; 3.23 ± 0.19 vs. 3.27 ± 0.22; P = .11), spatial resolution (3.14 ± 0.28 vs. 3.16 ± 0.27; P = .12), and overall image quality (3.14 ± 0.21 vs. 3.17 ± 0.17; P = .15). QLD-DLIR demonstrated lower measured noise than LD-IR in most areas (P < .001 for all). No significant difference was found between QLD-DLIR and LD-IR for the sensitivity (76.4% vs. 72.2%; P = .35) or the AUFROCs (0.77 vs. 0.78; P = .68) in detecting Lung-RADS category 3 or 4 nodules. Under a noninferiority limit of -0.1, QLD-DLIR showed noninferior detection performance (95% CI for AUFROC difference, -0.04 to 0.06).ConclusionQLD-DLIR images showed comparable image quality and noninferior nodule detectability relative to LD-IR images.

Project description:BackgroundNormal lung tissue tolerance constitutes a limiting factor in delivering the required dose of radiotherapy to cure thoracic and chest wall malignancies. Radiation-induced lung fibrosis (RILF) is considered a critical determinant for late normal tissue complications. While RILF mouse models are frequently approached e.g., as a single high dose thoracic irradiation to investigate lung fibrosis and candidate modulators, a systematic radiobiological characterization of RILF mouse model is urgently needed to compare relative biological effectiveness (RBE) of particle irradiation with protons, helium-, carbon and oxygen ions now available at HIT. We aimed to study the dose-response relationship and fractionation effect of photon irradiation in development of pulmonary fibrosis in C57BL/6 mouse.MethodsLung fibrosis was evaluated 24 weeks after single and fractionated whole thoracic irradiation by quantitative assessment of lung alterations using CT. The fibrosis index (FI) was determined based on 3D-segmentation of the lungs considering the two key fibrosis parameters affected by ionizing radiation i.e., a dose/fractionation dependent reduction of the total lung volume and increase of the mean lung density.ResultsThe effective dose required to induce 50% of the maximal possible fibrosis (ED 50 ) was 14.55 ± 0.34Gy and 27.7 ± 1.22Gy, for single and five- fractions irradiation, respectively. Applying a deterministic model an α/β = 4.49 ± 0.38 Gy for the late lung radiosensitivity was determined. Intriguingly, we found that a linear-quadratic model could be applied to in-vivo log transformed fibrosis (FI) vs. irradiation doses. The LQ model revealed an α/β for lung radiosensitivity of 4.4879 Gy for single fraction and 3.9474 for 5-fractions. Our FI based data were in good agreement with a meta-analysis of previous lung radiosensitivity data derived from different clinical endpoints and various mouse strains. The effect of fractionation on RILF development was further estimated by the biologically effective dose (BED) model with threshold BED (BED Tr ) = 30.33 Gy and BED ED50 = 61.63 Gy, respectively.ConclusionThe systematic radiobiological characterization of RILF in the C57BL/6 mouse reported in this study marks an important step towards precise estimation of dose-response for development of lung fibrosis. These radiobiological parameters combined with a large repertoire of genetically engineered C57BL/6 mouse models, build a solid foundation for further biologically individualized risk assessment of RILF and functional RBE prediction on novel of particle qualities.

Dataset Information

Impact of Fractionation and Dose in a Multivariate Model for Radiation-Induced Chest Wall Pain.

Publications

Impact of Fractionation and Dose in a Multivariate Model for Radiation-Induced Chest Wall Pain.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets