Integrating muscle fiber orientation from visible human data into radiotherapy target volumes.

OBJECTIVE: A major challenge in treatment of tumors near skeletal muscle is defining the target volume for suspected tumor invasion into the muscle. This study develops a framework that generates radiation target volumes with muscle fiber orientation directly integrated into their definition. The framework is applied to nineteen sacral tumor patients with suspected infiltration into surrounding muscles. Approach. To compensate for the poor soft-tissue contrast of CT images, muscle fiber orientation is derived from cryo-images of two cadavers from the Human Visible Project (VHP). The approach consists of (a) detecting image gradients in the cadaver images representative of muscle fibers, (b) mapping this information onto the patient image, and (c) embedding the muscle fiber orientation into an expansion method to generate patient-specific clinical target volumes (CTV). The validation tested the consistency of image gradient orientation across VHP subjects for the piriformis, gluteus maximus, paraspinal, gluteus medius, and gluteus minimus muscles. The model robustness was analyzed by comparing CTVs generated using different VHP subjects. The difference in shape between the new CTVs and standard CTV was analyzed for clinical impact. Main results. Good agreement was found between the image gradient orientation across VHP subjects, as the voxel-wise median cosine similarity was at least 0.86 (for the gluteus minimus) and up to 0.98 for the piriformis. The volume and surface similarity between the CTVs generating from different VHP subjects was on average at least 0.95 and 5.13 mm for the Dice Similarity Coefficient and the Hausdorff 95% Percentile Index, showing excellent robustness. Finally, compared to the standard CTV with different margins in muscle and non-muscle tissue, the new CTV margins are reduced in muscle tissue depending on the chosen clinical margins. Significance. This study implements a method to integrate muscle fiber orientation into the target volume without the need for additional imaging.

The influence of anisotropy on the clinical target volume of brain tumor patients.

Objective.Current radiotherapy guidelines for glioma target volume definition recommend a uniform margin expansion from the gross tumor volume (GTV) to the clinical target volume (CTV), assuming uniform infiltration in the invaded brain tissue. However, glioma cells migrate preferentially along white matter tracts, suggesting that white matter directionality should be considered in an anisotropic CTV expansion. We investigate two models of anisotropic CTV expansion and evaluate their clinical feasibility.Approach.To incorporate white matter directionality into the CTV, a diffusion tensor imaging (DTI) atlas is used. The DTI atlas consists of water diffusion tensors that are first spatially transformed into local tumor resistance tensors, also known as metric tensors, and secondly fed to a CTV expansion algorithm to generate anisotropic CTVs. Two models of spatial transformation are considered in the first step. The first model assumes that tumor cells experience reduced resistance parallel to the white matter fibers. The second model assumes that the anisotropy of tumor cell resistance is proportional to the anisotropy observed in DTI, with an 'anisotropy weighting parameter' controlling the proportionality. The models are evaluated in a cohort of ten brain tumor patients.Main results.To evaluate the sensitivity of the model, a library of model-generated CTVs was computed by varying the resistance and anisotropy parameters. Our results indicate that the resistance coefficient had the most significant effect on the global shape of the CTV expansion by redistributing the target volume from potentially less involved gray matter to white matter tissue. In addition, the anisotropy weighting parameter proved useful in locally increasing CTV expansion in regions characterized by strong tissue directionality, such as near the corpus callosum.Significance.By incorporating anisotropy into the CTV expansion, this study is a step toward an interactive CTV definition that can assist physicians in incorporating neuroanatomy into a clinically optimized CTV.

Association of Sarcopenia With Toxicity-Related Discontinuation of Adjuvant Endocrine Therapy in Women With Early-Stage Hormone Receptor-Positive Breast Cancer.

PURPOSE: Sarcopenia, an age-related decline in muscle mass and physical function, is associated with increased toxicity and worse outcomes in women with breast cancer (BC). Sarcopenia may contribute to toxicity-related early discontinuation of adjuvant endocrine  therapy (aET) in women with hormone receptor-positive (HR+) BC but remains poorly characterized. METHODS AND MATERIALS: This multicenter, retrospective cohort study included consecutive women with stage 0-II HR+ BC who received breast conserving therapy (lumpectomy and radiation therapy) and aET from 2011 to 2017 with a 5-year follow-up. Skeletal muscle index (SMI, cm2/m2) was analyzed using a deep learning model on routine cross-sectional radiation simulation imaging; sarcopenia was dichotomized according to previously validated reports. The primary endpoint was toxicity-related aET discontinuation; logistic regression analysis evaluated associations between SMI/sarcopenia and aET discontinuation. Cox regression analysis evaluated associations with time to aET toxicity, ipsilateral breast tumor recurrence (IBTR), and disease-free survival (DFS). RESULTS: A total of 305 women (median follow-up, 89 months) were included with a median age of 67 years and early-stage BC (12% stage 0, 65% stage I). A total of 60 (20%) women experienced toxicity-related aET discontinuation. Sarcopenia was associated with toxicity-related early discontinuation of aET (odds ratio, 2.18; P = .036) and shorter time to aET toxicity (hazard ratio [HR], 1.62; P = .031). SMI or sarcopenia were not independently associated with IBTR or DFS; toxicity-related aET discontinuation was associated with worse IBTR (HR, 9.47; P = .002) and worse DFS (HR, 4.53; P = .001). CONCLUSIONS: Among women with early-stage HR+ BC who receive adjuvant radiation therapy and hormone therapy, sarcopenia is associated with toxicity-related early discontinuation of aET. Further studies should validate these findings in women who did not receive adjuvant radiation therapy. These high-risk patients may be candidates for aggressive symptom management and/or alternative treatment strategies to improve outcomes.

Comparing Predicted Toxicities between Hypofractionated Proton and Photon Radiotherapy of Liver Cancer Patients with Different Adaptive Schemes.

With the availability of MRI linacs, online adaptive intensity modulated radiotherapy (IMRT) has become a treatment option for liver cancer patients, often combined with hypofractionation. Intensity modulated proton therapy (IMPT) has the potential to reduce the dose to healthy tissue, but it is particularly sensitive to changes in the beam path and might therefore benefit from online adaptation. This study compares the normal tissue complication probabilities (NTCPs) for liver and duodenal toxicity for adaptive and non-adaptive IMRT and IMPT treatments of liver cancer patients. Adaptive and non-adaptive IMRT and IMPT plans were optimized to 50 Gy (RBE = 1.1 for IMPT) in five fractions for 10 liver cancer patients, using the original MRI linac images and physician-drawn structures. Three liver NTCP models were used to predict radiation-induced liver disease, an increase in albumin-bilirubin level, and a Child-Pugh score increase of more than 2. Additionally, three duodenal NTCP models were used to predict gastric bleeding, gastrointestinal (GI) toxicity with grades >3, and duodenal toxicity grades 2-4. NTCPs were calculated for adaptive and non-adaptive IMRT and IMPT treatments. In general, IMRT showed higher NTCP values than IMPT and the differences were often significant. However, the differences between adaptive and non-adaptive treatment schemes were not significant, indicating that the NTCP benefit of adaptive treatment regimens is expected to be smaller than the expected difference between IMRT and IMPT.

Operational Ontology for Oncology (O3): A Professional Society-Based, Multistakeholder, Consensus-Driven Informatics Standard Supporting Clinical and Research Use of Real-World Data From Patients Treated for Cancer.

PURPOSE: The ongoing lack of data standardization severely undermines the potential for automated learning from the vast amount of information routinely archived in electronic health records (EHRs), radiation oncology information systems, treatment planning systems, and other cancer care and outcomes databases. We sought to create a standardized ontology for clinical data, social determinants of health, and other radiation oncology concepts and interrelationships. METHODS AND MATERIALS: The American Association of Physicists in Medicine's Big Data Science Committee was initiated in July 2019 to explore common ground from the stakeholders' collective experience of issues that typically compromise the formation of large inter- and intra-institutional databases from EHRs. The Big Data Science Committee adopted an iterative, cyclical approach to engaging stakeholders beyond its membership to optimize the integration of diverse perspectives from the community. RESULTS: We developed the Operational Ontology for Oncology (O3), which identified 42 key elements, 359 attributes, 144 value sets, and 155 relationships ranked in relative importance of clinical significance, likelihood of availability in EHRs, and the ability to modify routine clinical processes to permit aggregation. Recommendations are provided for best use and development of the O3 to 4 constituencies: device manufacturers, centers of clinical care, researchers, and professional societies. CONCLUSIONS: O3 is designed to extend and interoperate with existing global infrastructure and data science standards. The implementation of these recommendations will lower the barriers for aggregation of information that could be used to create large, representative, findable, accessible, interoperable, and reusable data sets to support the scientific objectives of grant programs. The construction of comprehensive "real-world" data sets and application of advanced analytical techniques, including artificial intelligence, holds the potential to revolutionize patient management and improve outcomes by leveraging increased access to information derived from larger, more representative data sets.

Evaluating the effect of setup uncertainty reduction and adaptation to geometric changes on normal tissue complication probability using online adaptive head and neck intensity modulated proton therapy.

Objective. To evaluate the impact of setup uncertainty reduction (SUR) and adaptation to geometrical changes (AGC) on normal tissue complication probability (NTCP) when using online adaptive head and neck intensity modulated proton therapy (IMPT).Approach.A cohort of ten retrospective head and neck cancer patients with daily scatter corrected cone-beam CT (CBCT) was studied. For each patient, two IMPT treatment plans were created: one with a 3 mm setup uncertainty robustness setting and one with no explicit setup robustness. Both plans were recalculated on the daily CBCT considering three scenarios: the robust plan without adaptation, the non-robust plan without adaptation and the non-robust plan with daily online adaptation. Online-adaptation was simulated using an in-house developed workflow based on GPU-accelerated Monte Carlo dose calculation and partial spot-intensity re-optimization. Dose distributions associated with each scenario were accumulated on the planning CT, where NTCP models for six toxicities were applied. NTCP values from each scenario were intercompared to quantify the reduction in toxicity risk induced by SUR alone, AGC alone and SUR and AGC combined. Finally, a decision tree was implemented to assess the clinical significance of the toxicity reduction associated with each mechanism.Main results. For most patients, clinically meaningful NTCP reductions were only achieved when SUR and AGC were performed together. In these conditions, total reductions in NTCP of up to 30.48 pp were obtained, with noticeable NTCP reductions for aspiration, dysphagia and xerostomia (mean reductions of 8.25, 5.42 and 5.12 pp respectively). While SUR had a generally larger impact than AGC on NTCP reductions, SUR alone did not induce clinically meaningful toxicity reductions in any patient, compared to only one for AGC alone.SignificanceOnline adaptive head and neck proton therapy can only yield clinically significant reductions in the risk of long-term side effects when combining the benefits of SUR and AGC.

Large anatomical changes in head-and-neck cancers - A dosimetric comparison of online and offline adaptive proton therapy.

Purpose: This work evaluates an online adaptive (OA) workflow for head-and-neck (H&N) intensity-modulated proton therapy (IMPT) and compares it with full offline replanning (FOR) in patients with large anatomical changes. Methods: IMPT treatment plans are created retrospectively for a cohort of eight H&N cancer patients that previously required replanning during the course of treatment due to large anatomical changes. Daily cone-beam CTs (CBCT) are acquired and corrected for scatter, resulting in 253 analyzed fractions. To simulate the FOR workflow, nominal plans are created on the planning-CT and delivered until a repeated-CT is acquired; at this point, a new plan is created on the repeated-CT. To simulate the OA workflow, nominal plans are created on the planning-CT and adapted at each fraction using a simple beamlet weight-tuning technique. Dose distributions are calculated on the CBCTs with Monte Carlo for both delivery methods. The total treatment dose is accumulated on the planning-CT. Results: Daily OA improved target coverage compared to FOR despite using smaller target margins. In the high-risk CTV, the median D98 degradation was 1.1 % and 2.1 % for OA and FOR, respectively. In the low-risk CTV, the same metrics yield 1.3 % and 5.2 % for OA and FOR, respectively. Smaller setup margins of OA reduced the dose to all OARs, which was most relevant for the parotid glands. Conclusion: Daily OA can maintain prescription doses and constraints over the course of fractionated treatment, even in cases of large anatomical changes, reducing the necessity for manual replanning in H&N IMPT.

Neighborhood social organization exposures and racial/ethnic disparities in hypertension risk in Los Angeles.

Despite a growing evidence base documenting associations between neighborhood characteristics and the risk of developing high blood pressure, little work has established the role played by neighborhood social organization exposures in racial/ethnic disparities in hypertension risk. There is also ambiguity around prior estimates of neighborhood effects on hypertension prevalence, given the lack of attention paid to individuals' exposures to both residential and nonresidential spaces. This study contributes to the neighborhoods and hypertension literature by using novel longitudinal data from the Los Angeles Family and Neighborhood Survey to construct exposure-weighted measures of neighborhood social organization characteristics-organizational participation and collective efficacy-and examine their associations with hypertension risk, as well as their relative contributions to racial/ethnic differences in hypertension. We also assess whether the hypertension effects of neighborhood social organization vary across our sample of Black, Latino, and White adults. Results from random effects logistic regression models indicate that adults living in neighborhoods where people are highly active in informal and formal organizations have a lower probability of being hypertensive. This protective effect of exposure to neighborhood organizational participation is also significantly stronger for Black adults than Latino and White adults, such that, at high levels of neighborhood organizational participation, the observed Black-White and Black-Latino hypertension differences are substantially reduced to nonsignificance. Nonlinear decomposition results also indicate that almost one-fifth of the Black-White hypertension gap can be explained by differential exposures to neighborhood social organization.

A stochastic control approach to intrafraction motion management in intensity-modulated radiotherapy.

Objective.The goal of this research is to demonstrate proof-of-principle for managing intrafraction motion via feedback control of delivered dose to achieve dosimetry comparable to respiratory gating without compromising delivery efficiency.Approach. We develop a stochastic control approach for step-and-shoot intensity-modulated radiotherapy (IMRT) in which the cumulative delivered dose and future trajectory of intrafraction motion are dynamically estimated by combining pre-treatment four-dimensional computed tomography imaging and intrafraction respiratory-motion surrogates. The IMRT plan is then re-optimized in real time to ensure delivery of the planned dose in the presence of free-breathing motion. We compare the performance of the proposed approach against traditional motion-management techniques, namely, respiratory gating and internal target volume (ITV) planning, using the four-dimensional extended cardiac-torso computational phantom.Main results.We simulate the delivery of treatment plans for a lung tumor in the presence of variable breathing amplitude, tumor size, and location. Results show that the proposed method reduces irradiated tissue volume compared to ITV treatment. Additionally, it significantly reduces treatment time compared to traditional respiratory-gated treatment, without compromising the dosimetric quality.Significance.Respiratory gating is a common technique to manage intrafraction motion. While gating supports reduced treatment volumes, it also prolongs the treatment delivery time. The proposed stochastic control approach can help improve the delivery efficiency of respiratory gating without compromising the dose quality.

Low-Dose Computed Tomography Scanning Protocols for Online Adaptive Proton Therapy of Head-and-Neck Cancers.

PURPOSE: To evaluate the suitability of low-dose CT protocols for online plan adaptation of head-and-neck patients. METHODS: We acquired CT scans of a head phantom with protocols corresponding to CT dose index volume CTDIvol in the range of 4.2-165.9 mGy. The highest value corresponds to the standard protocol used for CT simulations of 10 head-and-neck patients included in the study. The minimum value corresponds to the lowest achievable tube current of the GE Discovery RT scanner used for the study. For each patient and each low-dose protocol, the noise relative to the standard protocol, derived from phantom images, was applied to a virtual CT (vCT). The vCT was obtained from a daily CBCT scan corresponding to the fraction with the largest anatomical changes. We ran an established adaptive workflow twice for each low-dose protocol using a high-quality daily vCT and the corresponding low-dose synthetic vCT. For a relative comparison of the adaptation efficacy, two adapted plans were recalculated in the high-quality vCT and evaluated with the contours obtained through deformable registration of the planning CT. We also evaluated the accuracy of dose calculation in low-dose CT volumes using the standard CT protocol as reference. RESULTS: The maximum differences in D98 between low-dose protocols and the standard protocol for the high-risk and low-risk CTV were found to be 0.6% and 0.3%, respectively. The difference in OAR sparing was up to 3%. The Dice similarity coefficient between propagated contours obtained with low-dose and standard protocols was above 0.982. The mean 2%/2 mm gamma pass rate for the lowest-dose image, using the standard protocol as reference, was found to be 99.99%. CONCLUSION: The differences between low-dose protocols and the standard scanning protocol were marginal. Thus, low-dose CT protocols are suitable for online adaptive proton therapy of head-and-neck cancers. As such, considering scanning protocols used in our clinic, the imaging dose associated with online adaption of head-and-neck cancers treated with protons can be reduced by a factor of 40.

Integrating Structure Propagation Uncertainties in the Optimization of Online Adaptive Proton Therapy Plans.

Currently, adaptive strategies require time- and resource-intensive manual structure corrections. This study compares different strategies: optimization without manual structure correction, adaptation with physician-drawn structures, and no adaptation. Strategies were compared for 16 patients with pancreas, liver, and head and neck (HN) cancer with 1-5 repeated images during treatment: 'reference adaptation', with structures drawn by a physician; 'single-DIR adaptation', using a single set of deformably propagated structures; 'multi-DIR adaptation', using robust planning with multiple deformed structure sets; 'conservative adaptation', using the intersection and union of all deformed structures; 'probabilistic adaptation', using the probability of a voxel belonging to the structure in the optimization weight; and 'no adaptation'. Plans were evaluated using reference structures and compared using a scoring system. The reference adaptation with physician-drawn structures performed best, and no adaptation performed the worst. For pancreas and liver patients, adaptation with a single DIR improved the plan quality over no adaptation. For HN patients, integrating structure uncertainties brought an additional benefit. If resources for manual structure corrections would prevent online adaptation, manual correction could be replaced by a fast 'plausibility check', and plans could be adapted with correction-free adaptation strategies. Including structure uncertainties in the optimization has the potential to make online adaptation more automatable.

Community social environments and cigarette smoking.

Cigarette smoking remains a primary contributor to health disparities in the United States, and significant evidence suggests that smoking behavior is socially influenced. Though residential neighborhoods are important for health disparities, recent evidence suggests that people spend the majority of their waking time away from the residential neighborhood. We advance research on neighborhoods and smoking by using individual, neighborhood, and activity space data for adults in the Los Angeles Family and Neighborhood Survey (L.A.FANS). Moving beyond socioeconomic indicators of neighborhoods, we investigate the ways in which residential neighborhood social cohesion, neighborly exchange, and perceived danger impact smoking behavior after accounting for confounding factors in both the residential neighborhood and other activity spaces in which adults spend their days. We find that perceptions of danger in the residential neighborhood is robustly associated with the likelihood of smoking cigarettes. Further, measures of community social organization interact with perceived danger to influence smoking behavior. Adults with high levels of perceived danger are twice as likely to smoke if residing in communities with lower levels of social organization in the form of helpful, trusting, and supportive relationships. Understanding how the social organization of communities contributes to smoking disparities is important for curbing smoking's impact on population health.

Utility of Noncancerous Chest CT Features for Predicting Overall Survival and Noncancer Death in Patients With Stage I Lung Cancer Treated With Stereotactic Body Radiotherapy.

BACKGROUND. Noncancerous imaging markers can be readily derived from pre-treatment diagnostic and radiotherapy planning chest CT examinations. OBJECTIVE. The purpose of this article was to explore the ability of noncancerous features on chest CT to predict overall survival (OS) and noncancer-related death in patients with stage I lung cancer treated with stereotactic body radiation therapy (SBRT). METHODS. This retrospective study included 282 patients (168 female, 114 male; median age, 75 years) with stage I lung cancer treated with SBRT between January 2009 and June 2017. Pretreatment chest CT was used to quantify coronary artery calcium (CAC) score, pulmonary artery (PA)-to-aorta ratio, emphysema, and body composition in terms of the cross-sectional area and attenuation of skeletal muscle and subcutaneous adipose tissue at the T5, T8, and T10 vertebral levels. Associations of clinical and imaging features with OS were quantified using a multivariable Cox proportional hazards (PH) model. Penalized multivariable Cox PH models to predict OS were constructed using clinical features only and using both clinical and imaging features. The models' discriminatory ability was assessed by constructing time-varying ROC curves and computing AUC at prespecified times. RESULTS. After a median OS of 60.8 months (95% CI, 55.8-68.0), 148 (52.5%) patients had died, including 83 (56.1%) with noncancer deaths. Higher CAC score (11-399: hazard ratio [HR], 1.83 [95% CI, 1.15-2.91], p = .01; ≥ 400: HR, 1.63 [95% CI, 1.01-2.63], p = .04), higher PA-to-aorta ratio (HR, 1.33 [95% CI, 1.16-1.52], p < .001, per 0.1-unit increase), and lower thoracic skeletal muscle index (HR, 0.88 [95% CI, 0.79-0.98], p = .02, per 10-cm2/m2 increase) were independently associated with shorter OS. Discriminatory ability for 5-year OS was greater for the model including clinical and imaging features than for the model including clinical features only (AUC, 0.75 [95% CI, 0.68-0.83] vs 0.61 [95% CI, 0.53-0.70]; p < .01). The model's most important clinical or imaging feature according to mean standardized regression coefficients was the PA-to-aorta ratio. CONCLUSION. In patients undergoing SBRT for stage I lung cancer, higher CAC score, higher PA-to-aorta ratio, and lower thoracic skeletal muscle index independently predicted worse OS. CLINICAL IMPACT. Noncancerous imaging features on chest CT performed before SBRT improve survival prediction compared with clinical features alone.

Adaptive proton therapy.

Radiation therapy treatments are typically planned based on a single image set, assuming that the patient's anatomy and its position relative to the delivery system remains constant during the course of treatment. Similarly, the prescription dose assumes constant biological dose-response over the treatment course. However, variations can and do occur on multiple time scales. For treatment sites with significant intra-fractional motion, geometric changes happen over seconds or minutes, while biological considerations change over days or weeks. At an intermediate timescale, geometric changes occur between daily treatment fractions. Adaptive radiation therapy is applied to consider changes in patient anatomy during the course of fractionated treatment delivery. While traditionally adaptation has been done off-line with replanning based on new CT images, online treatment adaptation based on on-board imaging has gained momentum in recent years due to advanced imaging techniques combined with treatment delivery systems. Adaptation is particularly important in proton therapy where small changes in patient anatomy can lead to significant dose perturbations due to the dose conformality and finite range of proton beams. This review summarizes the current state-of-the-art of on-line adaptive proton therapy and identifies areas requiring further research.

A generalized framework for analytic regularization of uniform cubic B-spline displacement fields.

Image registration is an inherently ill-posed problem that lacks the constraints needed for a unique mapping between voxels of the two images being registered. As such, one must regularize the registration to achieve physically meaningful transforms. The regularization penalty is usually a function of derivatives of the displacement-vector field and can be calculated either analytically or numerically. The numerical approach, however, is computationally expensive depending on the image size, and therefore a computationally efficient analytical framework has been developed. Using cubic B-splines as the registration transform, we develop a generalized mathematical framework that supports five distinct regularizers: diffusion, curvature, linear elastic, third-order, and total displacement. We validate our approach by comparing each with its numerical counterpart in terms of accuracy. We also provide benchmarking results showing that the analytic solutions run significantly faster-up to two orders of magnitude-than finite differencing based numerical implementations.

Anatomic changes in head and neck intensity-modulated proton therapy: Comparison between robust optimization and online adaptation.

BACKGROUND/PURPOSE: Setup variations and anatomical changes can severely affect the quality of head and neck intensity-modulated proton therapy (IMPT) treatments. The impact of these changes can be alleviated by increasing the plan's robustness a priori, or by adapting the plan online. This work compares these approaches in the context of head and neck IMPT. MATERIALS/METHODS: A representative cohort of 10 head and neck squamous cell carcinoma (HNSCC) patients with daily cone-beam computed tomography (CBCT) was evaluated. For each patient, three IMPT plans were created: 1- a classical robust optimization (cRO) plan optimized on the planning CT, 2- an anatomical robust optimization (aRO) plan additionally including the two first daily CBCTs and 3- a plan optimized without robustness constraints, but online-adapted (OA) daily, using a constrained spot intensity re-optimization technique only. RESULTS: The cumulative dose following OA fulfilled the clinical objective of both the high-risk and low-risk clinical target volumes (CTV) coverage in all 10 patients, compared to 8 for aRO and 4 for cRO. aRO did not significantly increase the dose to most organs at risk compared to cRO, although the integral dose was higher. OA significantly reduced the integral dose to healthy tissues compared to both robust methods, while providing equivalent or superior target coverage. CONCLUSION: Using a simple spot intensity re-optimization, daily OA can achieve superior target coverage and lower dose to organs at risk than robust optimization methods.

Physics of Particle Beam and Hypofractionated Beam Delivery in NSCLC.

The dosimetric advantages of particle therapy lead to significantly reduced integral dose to normal tissues, making it an attractive treatment option for body sites such as the thorax. With reduced normal tissue dose comes the potential for dose escalation, toxicity reduction, or hypofractionation. While proton and heavy ion therapy have been used extensively for NSCLC, there are challenges in planning and delivery compared with X-ray-based radiation therapy. Particularly, range uncertainties compounded by breathing motion have to be considered. This article summarizes the current state of particle therapy for NSCLC with a specific focus on the impact of dosimetric uncertainties in planning and delivery.

Comparison of weekly and daily online adaptation for head and neck intensity-modulated proton therapy.

The high conformality of intensity-modulated proton therapy (IMPT) dose distributions causes treatment plans to be sensitive to geometrical changes during the course of a fractionated treatment. This can be addressed using adaptive proton therapy (APT). One important question in APT is the frequency of adaptations performed during a fractionated treatment, which is related to the question whether plan adaptation has to be done online or offline. The purpose of this work is to investigate the impact of weekly and daily online IMPT plan adaptation on the treatment quality for head and neck patients. A cohort of ten head and neck patients with daily acquired cone-beam CT (CBCT) images was evaluated retrospectively. Dose tracking of the IMPT treatment was performed for three scenarios: base plan with no adaptation (BP), weekly online adaptation (OAW), and daily online adaptation (OAD). Both adaptation schemes used an in-house developed online APT workflow, performing Monte Carlo dose calculations on scatter-corrected CBCTs. IMPT plan adaptation was achieved by only tuning the weights of a subset of beamlets, based on deformable image registration from the planning CT to each CBCT. Although OADmitigated random delivery errors more effectively than OAWon a fraction per fraction basis, both OAWand OADachieved the clinical goals for all ten patients, while BP failed for six cases. In the high-risk CTV, accumulated values ofD98%ranged between 97.15% and 99.73% of the prescription dose for OAD, with a median of 98.07%. For OAW, values between 95.02% and 99.26% were obtained, with a median of 97.61% of the prescription dose. Otherwise, the dose to most organs at risk was similar for all three scenarios. Globally, our results suggest that OAWcould be used as an alternative approach to OADfor most patients in order to reduce the clinical workload.

Neighborhood social environments, healthy resources, and adult diabetes: Accounting for activity space exposures.

This study broadens contextual environments to include adults' activity spaces-inside and outside the residential neighborhood-to examine how contextual exposures shape type 2 diabetes risk. We use novel longitudinal data from the Los Angeles Family and Neighborhood Survey, construct time-weighted exposure measures of adults' social-structural and healthy resource environments, and execute random effects logistic models predicting the probability of being diabetic. Results indicate that residential and activity space exposures are independently associated with adult diabetes, and that residential and activity space healthy resources combine to influence diabetes risk in synergistic ways. Living in more socioeconomically advantaged neighborhoods reduces diabetes risk, particularly when spending time in activity spaces with greater access to recreational facilities. Moreover, healthier activity space environments may compensate for living in neighborhoods devoid of healthy food options to lessen diabetes risk. Adopting an activity space framework can inform multilevel interventions aimed at alleviating type 2 diabetes and other chronic ailments.