Prospective Trial of Functional Lung Avoidance Radiation Therapy for Lung Cancer: Quality of Life Report.

PURPOSE: A novel form of lung function imaging has been developed that uses 4-dimensional computed tomography (4DCT) data to generate lung ventilation images (4DCT-ventilation). Functional avoidance uses 4DCT-ventilation to reduce doses to functional lung with the aim of reducing pulmonary side effects. A phase 2, multicenter 4DCT-ventilation functional avoidance clinical trial was completed. The purpose of this work was to quantify changes in patient-reported outcomes (PROs) for patients treated with functional avoidance and determine which metrics are predictive of PRO changes. MATERIALS AND METHODS: Patients with locally advanced lung cancer receiving curative-intent radiation therapy were accrued. Each patient had a 4DCT-ventilation image generated using 4DCT data and image processing. PRO instruments included the Functional Assessment of Cancer Therapy-Lung (FACT-L) questionnaire administered pretreatment; at the end of treatment; and at 3, 6, and 12 months posttreatment. Using the FACT-Trial Outcome Index and the FACT-Lung Cancer Subscale results, the percentage of clinically meaningful declines (CMDs) were determined. A linear mixed-effects model was used to determine which patient, clinical, dose, and dose-function metrics were predictive of PRO decline. RESULTS: Of the 59 patients who completed baseline PRO surveys. 83% had non-small cell lung cancer, with 75% having stage 3 disease. The median dose was 60 Gy in 30 fractions. CMD FACT-Trial Outcome Index decline was 46.3%, 38.5%, and 26.8%, at 3, 6, and 12 months, respectively. CMD FACT-Lung Cancer Subscale decline was 33.3%, 33.3%, and 29.3%, at 3, 6, and 12 months, respectively. Although an increase in most dose and dose-function parameters was associated with a modest decline in PROs, none of the results were significant (all P > .053). CONCLUSIONS: The current work presents an innovative combination of use of functional avoidance and PRO assessment and is the first report of PROs for patients treated with prospective 4DCT-ventilation functional avoidance. Approximately 30% of patients had clinically significant decline in PROs at 12 months posttreatment. The study provides additional data on outcomes with 4DCT-ventilation functional avoidance.

Temporal Considerations in Brain Metastases Radiation Therapy: The Intersection of Chronobiology and Patient Profiles.

The circadian system, a vital temporal regulator influencing physiological processes, has implications for cancer development and treatment response. Our study assessed circadian timing's impact on whole-brain radiotherapy outcomes in brain metastases for personalized cancer therapy insights. The aim of the study was to evaluate circadian influence on radiation treatment timing and its correlation with clinical outcomes and to identify patient populations benefiting from interventions synchronizing circadian rhythms, considering subgroup differences and potential disparities. An IRB-approved retrospective analysis of 237 patients undergoing whole-brain radiotherapy for brain metastases (2017-2021), receiving over 80% of treatments in the morning or afternoon, was performed. Survival analyses utilized Kaplan-Meier curves. This was a single-institution study involving patients receiving whole-brain radiotherapy. Demographic, disease, and socioeconomic parameters from electronic medical records were collected. Morning treatment (n = 158) showed a trend toward improved overall survival vs. afternoon (n = 79); the median survival was 158 vs. 79 days (p = 0.20, HR = 0.84, CI95% 0.84-0.91). Subgroup benefits for morning treatment in females (p = 0.04) and trends in controlled primary disease (p = 0.11) and breast cancer metastases (p = 0.08) were observed. Black patients exhibited diminished circadian influence. The present study emphasized chronobiological factors' relevance in brain metastases radiation therapy. Morning treatment correlated with improved survival, particularly in specific subgroups. Potential circadian influence disparities were identified, laying a foundation for personalized cancer therapy and interventions synchronizing circadian rhythms for enhanced treatment efficacy.

Physician Perceptions on Cancer Screening for LGBTQ+ Patients.

The LGBTQ+ community experiences cancer disparities due to increased risk factors and lower screening rates, attributable to health literacy gaps and systemic barriers. We sought to understand the experiences, perceptions, and knowledge base of healthcare providers regarding cancer screening for LGBTQ+ patients. A 20-item IRB-approved survey was distributed to physicians through professional organizations. The survey assessed experiences and education regarding the LGBTQ+ community and perceptions of patient concerns with different cancer screenings on a 5-point Likert scale. Complete responses were collected from 355 providers. Only 100 (28%) reported past LGBTQ+-related training and were more likely to be female (p = 0.020), have under ten years of practice (p = 0.014), or practice family/internal medicine (p < 0.001). Most (85%) recognized that LGBTQ+ subpopulations experience nuanced health issues, but only 46% confidently understood them, and 71% agreed their clinics would benefit from training. Family/internal medicine practitioners affirmed the clinical relevance of patients' sexual orientation (94%; 62% for medical/radiation oncology). Prior training affected belief in the importance of sexual orientation (p < 0.001), confidence in understanding LGBTQ+ health concerns (p < 0.001), and willingness to be listed as "LGBTQ+-friendly" (p = 0.005). Our study suggests that despite a paucity of formal training, most providers acknowledge that LGBTQ+ patients have unique health needs. Respondents had a lack of consensus regarding cancer screenings for lesbian and transgender patients, indicating the need for clearer screening standards for LGBTQ+ subpopulations and educational programs for providers.

Characterizing Pulmonary Function Test Changes for Patients With Lung Cancer Treated on a 2-Institution, 4-Dimensional Computed Tomography-Ventilation Functional Avoidance Prospective Clinical Trial.

Purpose: Four-dimensional computed tomography (4DCT)-ventilation-based functional avoidance uses 4DCT images to generate plans that avoid functional regions of the lung with the goal of reducing pulmonary toxic effects. A phase 2, multicenter, prospective study was completed to evaluate 4DCT-ventilation functional avoidance radiation therapy. The purpose of this study was to report the results for pretreatment to posttreatment pulmonary function test (PFT) changes for patients treated with functional avoidance radiation therapy. Methods and Materials: Patients with locally advanced lung cancer receiving chemoradiation were accrued. Functional avoidance plans based on 4DCT-ventilation images were generated. PFTs were obtained at baseline and 3 months after chemoradiation. Differences for PFT metrics are reported, including diffusing capacity for carbon monoxide (DLCO), forced expiratory volume in 1 second (FEV1), and forced vital capacity (FVC). PFT metrics were compared for patients who did and did not experience grade 2 or higher pneumonitis. Results: Fifty-six patients enrolled on the study had baseline and posttreatment PFTs evaluable for analysis. The mean change in DLCO, FEV1, and FVC was -11.6% ± 14.2%, -5.6% ± 16.9%, and -9.0% ± 20.1%, respectively. The mean change in DLCO was -15.4% ± 14.4% for patients with grade 2 or higher radiation pneumonitis and -10.8% ± 14.1% for patients with grade <2 radiation pneumonitis (P = .37). The mean change in FEV1 was -14.3% ± 22.1% for patients with grade 2 or higher radiation pneumonitis and -3.9% ± 15.4% for patients with grade <2 radiation pneumonitis (P = .09). Conclusions: The current work is the first to quantitatively characterize PFT changes for patients with lung cancer treated on a prospective functional avoidance radiation therapy study. In comparison with patients treated with standard thoracic radiation planning, the data qualitatively show that functional avoidance resulted in less of a decline in DLCO and FEV1. The presented data can help elucidate the potential pulmonary function improvement with functional avoidance radiation therapy.

Hypomethylating agent-based therapies in older adults with acute myeloid leukemia - A joint review by the Young International Society of Geriatric Oncology and European Society for Blood and Marrow Transplantation Trainee Committee.

Acute myeloid leukemia (AML) is associated with poor outcomes in older adults. A major goal of treatment is to balance quality of life and functional independence with disease control. With the approval of new, more tolerable regimens, more older adults are able to receive AML-directed therapy. Among these options are hypomethylating agents (HMAs), specifically azacitidine and decitabine. HMAs have become an integral part of AML therapy over the last two decades. These agents are used either as monotherapy or nowadays more commonly in combination with other agents such as the Bcl-2 inhibitor venetoclax. Biological AML characteristics, such as molecular and cytogenetic risk factors, play crucial roles in guiding treatment decisions. In patients with high-risk AML, HMAs are increasingly used rather than intensive chemotherapy, although further trials based on a risk-adapted approach using patient- and disease-related factors are needed. Here, we review trials and evidence for the use of HMA monotherapy and combination therapy in the management of older adults with AML. Furthermore, we discuss the use of HMAs and HMA combination therapies in AML, mechanisms of action, their incorporation into hematopoietic stem cell transplantation strategies, and their use in patients with comorbidities and reduced organ function.

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing.

Concurrent chemoradiation and Tumor Treating Fields (TTFields, 200 kHz) for patients with newly diagnosed glioblastoma: patterns of progression in a single institution pilot study.

Current standard of care for glioblastoma (GBM) includes concurrent chemoradiation and maintenance temozolomide (TMZ) with Tumor Treating Fields (TTFields). Preclinical studies suggest TTFields and radiation treatment have synergistic effects. We conducted a pilot clinical trial of concurrent chemoradiation with TTFields and report pattern of progression. MATERIALS AND METHODS: This is a single arm pilot study (clinicaltrials.gov Identifier: NCT03477110). Adult patients (age ≥ 18 years) with KPS ≥ 60 with newly diagnosed GBM were eligible. All patients received concurrent scalp-sparing radiation (60 Gy in 30 fractions), standard concurrent TMZ and TTFields. Maintenance therapy included standard TMZ and continuation of TTFields. Radiation treatment was delivered through TTFields arrays. Incidence and location of progression was documented. Distant recurrence was defined as recurrence more than 2 cm from the primary enhancing lesion. RESULTS: Thirty patients were enrolled on the trial. Twenty were male with median age 58 years (19-77 years). Median KPS was 90 (70-100). Median follow-up was 15.2 months (1.7-23.6 months). Ten (33.3%) patients had a methylated promoter status. Twenty-seven patients (90%) had progression, with median PFS of 9.3 months (range 8.5 to 11.6 months). Six patients presented with distant recurrence, with median distance from primary lesion of 5.05 cm (2.26-6.95 cm). One infratentorial progression was noted. CONCLUSIONS: We observed improved local control using concurrent chemoradiation with TTFields for patients with newly diagnosed when compared to historical controls. Further data are needed to validate this finding. TRIAL REGISTRATION: Clinicaltrials.gov Identifier NCT03477110.

Single-Dose Radiation Therapy Without Additional Surgery as a Treatment for Heterotopic Ossification Developing After Transfemoral Amputation.

ABSTRACT: Heterotopic ossification is the development of mature lamellar bone in soft tissues. Heterotopic ossification can occur in up to 23% of patients after amputation. Heterotopic ossification is often painful, causing significant dysfunction. While radiotherapy is used to prevent heterotopic ossification before formation, there is a dearth of literature on using radiotherapy to treat existing heterotopic ossification. This case report describes the use of late radiotherapy for the management of existing heterotopic ossification that developed after a transfemoral amputation. A 61-yr-old woman with peripheral artery disease of her bilateral lower limbs status post stenting and ultimately left transfemoral amputation was diagnosed with symptomatic heterotopic ossification limiting her function. Another surgery was not felt to be warranted. She was not improving with medical therapy and was prescribed 800 cGy in one fraction. After treatment, she experienced significant relief in her pain, allowing her to resume physical therapy and use of her prosthesis. There are no other published examples of using radiation alone for treatment of heterotopic ossification formation after transfemoral amputation without surgical revision of the bone formation. Our case shows possible utility in single-dose radiation as a treatment to prevent progression of heterotopic ossification, especially when limiting functional progress.

Chronoradiobiology of Breast Cancer: The Time Is Now to Link Circadian Rhythm and Radiation Biology.

Circadian disruption has been linked to cancer development, progression, and radiation response. Clinical evidence to date shows that circadian genetic variation and time of treatment affect radiation response and toxicity for women with breast cancer. At the molecular level, there is interplay between circadian clock regulators such as PER1, which mediates ATM and p53-mediated cell cycle gating and apoptosis. These molecular alterations may govern aggressive cancer phenotypes, outcomes, and radiation response. Exploiting the various circadian clock mechanisms may enhance the therapeutic index of radiation by decreasing toxicity, increasing disease control, and improving outcomes. We will review the body's natural circadian rhythms and clock gene-regulation while exploring preclinical and clinical evidence that implicates chronobiological disruptions in the etiology of breast cancer. We will discuss radiobiological principles and the circadian regulation of DNA damage responses. Lastly, we will present potential rational therapeutic approaches that target circadian pathways to improve outcomes in breast cancer. Understanding the implications of optimal timing in cancer treatment and exploring ways to entrain circadian biology with light, diet, and chronobiological agents like melatonin may provide an avenue for enhancing the therapeutic index of radiotherapy.

Perceptions of and barriers to cancer screening by the sexual and gender minority community: a glimpse into the health care disparity.

PURPOSE: A disparity exists in cancer screening rates for the Sexual and Gender Minority (SGM) community. We sought to understand the perceptions and baseline knowledge of cancer screening among SGM community members. METHODS: Survey administered via social media from June 2018 to October 2018. We asked 31 questions focused on cancer screening, human papillomavirus, emotional distress, and experience with the health care system. Those included were 18 years or older. Cancer screening attitudes and knowledge, as well as perceptions of the health care system were investigated. RESULTS: There were 422 respondents analyzed: 24.6% identified as female, 25.5% as male, 40.1% transgender, and 9.6% as other. 65.4% of the SGM community is not certain what cancer screening to do for themselves. Only 27.3% and 55.7% knew that HPV was a risk factor associated with head and neck cancer and anal cancer, respectively. Half stated their emotional distress prevents them from getting cancer screening. It was identified that process changes in making appointments, comforts during the visit, and formal training for physicians and nurses could increase cancer screening compliance for this community. The transgender population had a trend in more gaps in knowledge of appropriate cancer screening and significant excess emotional distress. CONCLUSION: Gaps in cancer screening knowledge and emotional and financial distress may be responsible for the disparity of lower cancer screening rates for the SGM population and the transgender population may be most at risk. Appreciating the cancer screening concerns of the SGM population can help shape future clinical and institutional approaches to improve health care delivery.

Interactive Machine Learning-Based Multi-Label Segmentation of Solid Tumors and Organs.

We seek the development and evaluation of a fast, accurate, and consistent method for general-purpose segmentation, based on interactive machine learning (IML). To validate our method, we identified retrospective cohorts of 20 brain, 50 breast, and 50 lung cancer patients, as well as 20 spleen scans, with corresponding ground truth annotations. Utilizing very brief user training annotations and the adaptive geodesic distance transform, an ensemble of SVMs is trained, providing a patient-specific model applied to the whole image. Two experts segmented each cohort twice with our method and twice manually. The IML method was faster than manual annotation by 53.1% on average. We found significant (p < 0.001) overlap difference for spleen (DiceIML/DiceManual = 0.91/0.87), breast tumors (DiceIML/DiceManual = 0.84/0.82), and lung nodules (DiceIML/DiceManual = 0.78/0.83). For intra-rater consistency, a significant (p = 0.003) difference was found for spleen (DiceIML/DiceManual = 0.91/0.89). For inter-rater consistency, significant (p < 0.045) differences were found for spleen (DiceIML/DiceManual = 0.91/0.87), breast (DiceIML/DiceManual = 0.86/0.81), lung (DiceIML/DiceManual = 0.85/0.89), the non-enhancing (DiceIML/DiceManual = 0.79/0.67) and the enhancing (DiceIML/DiceManual = 0.79/0.84) brain tumor sub-regions, which, in aggregation, favored our method. Quantitative evaluation for speed, spatial overlap, and consistency, reveals the benefits of our proposed method when compared with manual annotation, for several clinically relevant problems. We publicly release our implementation through CaPTk (Cancer Imaging Phenomics Toolkit) and as an MITK plugin.

A Pilot Trial Using Telemedicine in Radiation Oncology: The Future of Health Care Is Virtual.

Background: Social determinants of health directly affect cancer survival. Driven by advances in technology and recent demands due to COVID-19, telemedicine has the ability to improve patient access to care, lower health care costs, and increase workflow efficiency. The role of telemedicine in radiation oncology is not established. Materials and Methods: We conducted an IRB-approved pilot trial using a telehealth platform for the first post-radiation visit in patients with any cancer diagnosis. The primary endpoint was feasibility of using telehealth defined by completion of five telehealth visits per month in a single department. Secondary endpoints included the ability to assess patients appropriately, patient and physician satisfaction. Physicians were surveyed again during the pandemic to determine whether viewpoints changed. Results: Between May 27, 2016 and August 1, 2018, 37 patients were enrolled in the Telehealth in Post-operative Radiation Therapy (TelePORT) trial, with 24 evaluable patients who completed their scheduled telehealth visit. On average, 1.4 patients were accrued per month. All patients were satisfied with their care, had enough time with their physician and 85.7% believed the telehealth communication was excellent. All physicians were able to accurately assess the patient's symptoms via telehealth, whereas 82.3% felt they could accurately assess treatment-related toxicity. Physicians assessing skin toxicity from breast radiation were those who did not feel they were able to assess toxicity. Discussion and Conclusions: Both health care providers and patients have identified telemedicine as a suitable platform for radiation oncology visits. Although there are limitations, telemedicine has significant potential for increasing access of cancer care delivery in radiation oncology.

Personalized Nutrition as a Key Contributor to Improving Radiation Response in Breast Cancer.

Understanding metabolic and immune regulation inherent to patient populations is key to improving the radiation response for our patients. To date, radiation therapy regimens are prescribed based on tumor type and stage. Patient populations who are noted to have a poor response to radiation such as those of African American descent, those who have obesity or metabolic syndrome, or senior adult oncology patients, should be considered for concurrent therapies with radiation that will improve response. Here, we explore these populations of breast cancer patients, who frequently display radiation resistance and increased mortality rates, and identify the molecular underpinnings that are, in part, responsible for the radiation response and that result in an immune-suppressive tumor microenvironment. The resulting immune phenotype is discussed to understand how antitumor immunity could be improved. Correcting nutrient deficiencies observed in these populations should be considered as a means to improve the therapeutic index of radiation therapy.

Brain extraction on MRI scans in presence of diffuse glioma: Multi-institutional performance evaluation of deep learning methods and robust modality-agnostic training.

Brain extraction, or skull-stripping, is an essential pre-processing step in neuro-imaging that has a direct impact on the quality of all subsequent processing and analyses steps. It is also a key requirement in multi-institutional collaborations to comply with privacy-preserving regulations. Existing automated methods, including Deep Learning (DL) based methods that have obtained state-of-the-art results in recent years, have primarily targeted brain extraction without considering pathologically-affected brains. Accordingly, they perform sub-optimally when applied on magnetic resonance imaging (MRI) brain scans with apparent pathologies such as brain tumors. Furthermore, existing methods focus on using only T1-weighted MRI scans, even though multi-parametric MRI (mpMRI) scans are routinely acquired for patients with suspected brain tumors. In this study, we present a comprehensive performance evaluation of recent deep learning architectures for brain extraction, training models on mpMRI scans of pathologically-affected brains, with a particular focus on seeking a practically-applicable, low computational footprint approach, generalizable across multiple institutions, further facilitating collaborations. We identified a large retrospective multi-institutional dataset of n=3340 mpMRI brain tumor scans, with manually-inspected and approved gold-standard segmentations, acquired during standard clinical practice under varying acquisition protocols, both from private institutional data and public (TCIA) collections. To facilitate optimal utilization of rich mpMRI data, we further introduce and evaluate a novel ''modality-agnostic training'' technique that can be applied using any available modality, without need for model retraining. Our results indicate that the modality-agnostic approach1 obtains accurate results, providing a generic and practical tool for brain extraction on scans with brain tumors.