The literature is reviewed to identify the main clinical and dose-volume predictors for acute and late radiation-induced heart disease. A clear quantitative dose and/or volume dependence for most cardiac toxicity has not yet been shown, primarily because of the scarcity of the data. Several clinical factors, such as age, comorbidities and doxorubicin use, appear to increase the risk of injury. The existing dose-volume data is presented, as well as suggestions for future investigations to better define radiation-induced cardiac injury.

The biological effectiveness of proton beams relative to photon beams in radiation therapy has been taken to be 1.1 throughout the history of proton therapy. While potentially appropriate as an average value, actual relative biological effectiveness (RBE) values may differ. This Task Group report outlines the basic concepts of RBE as well as the biophysical interpretation and mathematical concepts. The current knowledge on RBE variations is reviewed and discussed in the context of the current clinical use of RBE and the clinical relevance of RBE variations (with respect to physical as well as biological parameters). The following task group aims were designed to guide the current clinical practice: Assess whether the current clinical practice of using a constant RBE for protons should be revised or maintained. Identifying sites and treatment strategies where variable RBE might be utilized for a clinical benefit. Assess the potential clinical consequences of delivering biologically weighted proton doses based on variable RBE and/or LET models implemented in treatment planning systems. Recommend experiments needed to improve our current understanding of the relationships among in vitro, in vivo, and clinical RBE, and the research required to develop models. Develop recommendations to minimize the effects of uncertainties associated with proton RBE for well‐defined tumor types and critical structures.

Each year, 500,000 patients are treated with radiotherapy for head and neck cancer, resulting in relatively high survival rates. However, in 40% of patients, quality of life is severely compromised because of radiation-induced impairment of salivary gland function and consequent xerostomia (dry mouth). New radiation treatment technologies enable sparing of parts of the salivary glands. We have determined the parts of the major salivary gland, the parotid gland, that need to be spared to ensure that the gland continues to produce saliva after irradiation treatment. In mice, rats, and humans, we showed that stem and progenitor cells reside in the region of the parotid gland containing the major ducts. We demonstrated in rats that inclusion of the ducts in the radiation field led to loss of regenerative capacity, resulting in long-term gland dysfunction with reduced saliva production. Then we showed in a cohort of patients with head and neck cancer that the radiation dose to the region of the salivary gland containing the stem/progenitor cells predicted the function of the salivary glands one year after radiotherapy. Finally, we showed that this region of the salivary gland could be spared during radiotherapy, thus reducing the risk of post-radiotherapy xerostomia.

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Background and Purpose Brain radiotherapy is limited in part by damage to white matter, contributing to neurocognitive decline. We utilized diffusion tensor imaging (DTI) with multiple b-values (diffusion weightings) to model the dose-dependency and time course of radiation effects on white matter. Materials and Methods Fifteen patients with high-grade gliomas treated with radiotherapy and chemotherapy underwent MRI with DTI prior to radiotherapy, and after months 1, 4-6, and 9-11. Diffusion tensors were calculated using three weightings (high, standard, and low b-values) and maps of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (λ‖), and radial diffusivity (λ⊥) were generated. The region of interest was all white matter. Results MD, λ‖, and λ⊥increased significantly with time and dose, with corresponding decrease in FA. Greater changes were seen at lower b-values, except for FA. Time-dose interactions were highly significant at 4-6 months and beyond (p < .001), and the difference in dose response between high and low b-values reached statistical significance at 9-11 months for MD, λ‖, and λ⊥ (p < .001, p < .001, p = .005 respectively) as well as at 4-6 months for λ‖ (p = .04). Conclusions We detected dose-dependent changes across all doses, even <10 Gy. Greater changes were observed at low b-values, suggesting prominent extracellular changes possibly due to vascular permeability and neuroinflammation.

Purpose Radiation-induced cognitive deficits may be mediated by tissue damage to cortical regions. Volumetric changes in cortex can be reliably measured using high-resolution magnetic resonance imaging (MRI). We used these methods to study the association between radiation therapy (RT) dose and change in cortical thickness in high-grade glioma (HGG) patients. Methods and Materials We performed a voxel-wise analysis of MR imaging from 15 HGG patients who underwent fractionated partial brain RT. Three-dimensional MRI was acquired pre- and 1-year post-RT. Cortex was parcellated with well-validated segmentation software (Freesufer). Surgical cavities were censored. Each cortical voxel was assigned a change in cortical thickness between time points, RT dose value, and neuroanatomic label by lobe. Effect of dose, neuroanatomic location, age, and chemotherapy on cortical thickness was tested using linear mixed effects (LME) modeling. Results Cortical atrophy was seen after 1-year post RT, with greater effects at higher doses. Estimates from LME modeling showed that cortical thickness decreased by −0.0033 mm (p<0.001) for every 1 Gy increase in RT dose. Temporal and limbic cortex exhibited the largest change in cortical thickness per Gy, compared to other regions (p<0.001). Age and chemotherapy were not significantly associated with cortical thickness change. Conclusions We found dose-dependent thinning of the cerebral cortex, with varying neuroanatomical regional sensitivity, one year after fractionated partial brain RT. The magnitude of thinning parallels one-year atrophy rates seen in neurodegenerative diseases, and may contribute to cognitive decline following high-dose RT.

Background and Purpose Regional differences in sensitivity to white matter damage after brain radiotherapy (RT) are not well-described. We characterized the spatial heterogeneity of dose-response across white matter tracts using diffusion tensor imaging (DTI). Materials and Methods Forty-nine patients with primary brain tumors underwent MRI with DTI before and 9–12 months after partial-brain RT. Maps of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were generated. Atlas-based white matter tracts were identified. A secondary analysis using skeletonized tracts was also performed. Linear mixed-model analysis of the relationship between mean and max dose and percent change in DTI metrics was performed. Results Tracts with the strongest correlation of FA change with mean dose were the fornix (−0.46 percent/Gy), cingulum bundle (−0.44 percent/Gy), and body of corpus callosum (−0.23 percent/Gy), p<.001. These tracts also showed dose-sensitive changes in MD and RD. In the skeletonized analysis, the fornix and cingulum bundle remained highly dose-sensitive. Maximum and mean dose were similarly predictive of DTI change. Conclusions The corpus callosum, cingulum bundle, and fornix show the most prominent dose-dependent changes following RT. Future studies examining correlation with cognitive functioning and potential avoidance of critical white matter regions are warranted.

Purpose/Objectives Following brain radiation therapy (RT), patients often experience memory impairment, which may be partially mediated by damage to the hippocampus. Hippocampal sparing in RT planning is the subject of recent and ongoing clinical trials. Calculating appropriate hippocampal dose constraints would be improved by efficient in vivo measurements of hippocampal damage. In this study we sought to determine whether brain RT was associated with dose-dependent hippocampal atrophy. Materials/Methods Hippocampal volume was measured with MRI in 52 patients who underwent fractionated, partial brain RT for primary brain tumors. Study patients had high-resolution, 3D volumetric MRI prior to and one year post-RT. Images were processed using software with FDA clearance and CE (Conformité Européene) marking for automated measurement of hippocampal volume. Automated results were inspected visually for accuracy. Tumor and surgical changes were censored. Mean hippocampal dose was tested for correlation with hippocampal atrophy one year post-RT. Average hippocampal volume change was also calculated for hippocampi receiving high (>40 Gy) or low (<10 Gy) mean RT dose. A multivariate analysis was conducted with linear mixed-effects modeling to evaluate other potential predictors of hippocampal volume change, including patient (random effect), age, hemisphere, sex, seizure history, and baseline volume. Statistical significance was evaluated at α=0.05. Results Mean hippocampal dose was significantly correlated with hippocampal volume loss (r=−0.24, p=0.03). Mean hippocampal volume was significantly reduced one year after high-dose RT (mean −6%, p=0.009), but not after low-dose RT. In multivariate analysis, both RT dose and patient age were significant predictors of hippocampal atrophy (p<0.01). Conclusions The hippocampus demonstrates radiation dose-dependent atrophy following treatment for brain tumors. Quantitative MRI is a non-invasive imaging technique capable of measuring radiation effects on intracranial structures. This technique could be investigated as a potential biomarker for development of reliable dose constraints for improved cognitive outcomes.