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PURPOSE/OBJECTIVE: Field size limitations on Halcyon and Ethos treatment machines largely preclude use of the conventional monoisocentric three-field technique for breast/chest wall and regional lymph nodes. We present an alternative, IMRT-based planning approach that facilitates treatment on Halcyon and Ethos while preserving plan quality. MATERIALS/METHODS: Eight breast and regional node cases (four left-sided, four right-sided) were planned for an Ethos machine using a 15-17 field IMRT technique. Institutional plan quality metrics for CTV and PTV coverage and OAR sparing were assessed. Five plans (four right-sided, one left-sided) were also planned using a hybrid 3D multisocenter technique. CTV coverage and OAR sparing were compared to the IMRT plans. Eclipse scripting tools were developed to aid in beam placement and plan evaluation through a set of dosimetric scorecards, and both are shared publicly. RESULTS: On average, the IMRT plans achieved breast CTV and PTV coverage at 50 Gy of 97.9% and 95.7%, respectively. Supraclavicular CTV and PTV coverages at 45 Gy were 100% and 95.5%. Axillary lymph node CTV and PTV coverages at 45 Gy were 100% and 97.1%, and IMN CTV coverage at 45 Gy was 99.2%. Mean ipsilateral lung V20 Gy was 19.3%, and average mean heart dose was 1.6 Gy for right-sided cases and 3.0 Gy for left-sided. In comparison to the hybrid 3D plans, IMRT plans achieved higher breast and supraclavicular CTV coverage (99.9% vs. 98.6% and 99.9% vs. 93.4%), higher IMN coverage (99.6% vs. 78.2%), and lower ipsilateral lung V20 Gy (19.6% vs. 28.2%). CONCLUSION: Institutional plan quality benchmarks were achieved for all eight cases using the IMRT-based planning approach. The IMRT-based planning approach offered superior conformity and OAR sparing than a competing hybrid 3D approach.
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Neoplasias da Mama , Linfonodos , Órgãos em Risco , Dosagem Radioterapêutica , Planejamento da Radioterapia Assistida por Computador , Radioterapia de Intensidade Modulada , Parede Torácica , Humanos , Planejamento da Radioterapia Assistida por Computador/métodos , Radioterapia de Intensidade Modulada/métodos , Feminino , Parede Torácica/efeitos da radiação , Órgãos em Risco/efeitos da radiação , Neoplasias da Mama/radioterapia , Linfonodos/efeitos da radiaçãoRESUMO
Urbanization alters natural landscapes and creates unique challenges for urban wildlife. Similarly, the Urban Heat Island (UHI) effect can produce significantly elevated temperatures in urban areas, and we have a relatively poor understanding of how this will impact urban biodiversity. In particular, most studies quantify the UHI using broad-scale climate data rather than assessing microclimate temperatures actually experienced by organisms. In addition, studies often fail to address spatial and temporal complexities of the UHI. Here we examine the thermal microclimate and UHI experienced in the web of Western black widow spiders (Latrodectus hesperus), a medically-important, superabundant urban pest species found in cities across the Western region of North America. We do this using replicate urban and desert populations across an entire year to account for seasonal variation in the UHI, both within and between habitats. Our findings reveal a strong nighttime, but no daytime, UHI effect, with urban spider webs being 2-5 °C warmer than desert webs at night. This UHI effect is most prominent during the spring and least prominent in winter, suggesting that the UHI need not be most pronounced when temperatures are most elevated. Urban web temperatures varied among urban sites in the daytime, whereas desert web temperatures varied among desert sites in the nighttime. Finally, web temperature was significantly positively correlated with a spider's boldness, but showed no relationship with voracity towards prey, web size, or body condition. Understanding the complexities of each organism's thermal challenges, the "functional microclimate", is crucial for predicting the impacts of urbanization and climate change on urban biodiversity and ecosystem functioning.
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Artrópodes , Viúva Negra , Animais , Temperatura , Temperatura Alta , Cidades , Microclima , EcossistemaRESUMO
Purpose: The Adaptive Radiation Therapy Individualized Approach-Cervix clinical trial uses predefined clinical directive templates (CDTs) combined with RapidPlan dose-volume histogram estimations (DVHe) to guide plan optimization in the Ethos treatment planning system. The dosimetric scorecard is a scoring tool that quantifies improvements in plan quality after physicians have precisely expressed their complete clinical intent. To our knowledge, this is the first study to use the dosimetric scorecard tool to tune an Ethos CDT to improve resulting plan quality. Methods and Materials: Iterative replanning was used to modify the draft CDT (CDT-1) in Ethos 1.1 to generate a new CDT (CDT-2) that maximized the clinical consensus scorecard's total score compared with CDT-1. CDT-2 was established, and resulting plans were compared with and without a DVHe. Additional fixed field intensity modulated radiation therapy beam geometries were compared between CDT-1 and CDT-2, both with DVHe. After obtaining favorable results when comparing CDT-1 versus CDT-2 for 2 test cases, 10 additional cases were retrospectively identified and tested. Results: CDT-2 reduced organ at risk doses without compromising planning target volume coverage in the initial test cases. When combined with DVHe, CDT-2 marginally outperformed CDT-1. Plan quality further improved with a 19-field geometry. In the expanded analysis, CDT-2 achieved higher scores than CDT-1 in most cases, with the 19-field approach showing superiority. Optimization and calculation time increased by 1.9 minutes, monitor unit (MU)/field decreased by 44.4, whereas beam-on time increased by 2.8 minutes when increasing fields to 19 from 9. Reoptimization with Ethos 1.1 Maintenance Release 1 resulted in decreased MU and minimal score changes. Conclusions: The scorecard is an effective tool to adjust an Ethos CDT to improve the average calculated plan quality. It also allowed for easy evaluation of the dosimetric impact of other planning parameters (beam arrangements and use of DVHe) to identify the best approach. Using a finely tuned CDT is expected to improve planning efficiency and decrease intrainstitutional plan quality variability, benefiting cone beam computed tomography-guided adaptive radiation therapy.
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Purpose: The autosegmentation algorithm of Siemens Healthineers version VA 30 (AASH) (Siemens Healthineers, Erlangen, Germany) was trained and developed in the male pelvis, with no published data on its usability in the female pelvis. This is the first multi-institutional study to describe and evaluate an artificial intelligence algorithm for autosegmentation of the pelvic nodal region by gender. Methods and Materials: We retrospectively evaluated AASH pelvic nodal autosegmentation in both male and female patients treated at our network of institutions. The automated pelvic nodal contours generated by AASH were evaluated by 1 board-certified radiation oncologist. A 4-point scale was used for each nodal region contour: a score of 4 is clinically usable with minimal edits; a score of 3 requires minor edits (missing nodal contour region, cutting through vessels, or including bowel loops) in 3 or fewer computed tomography slices; a score of 2 requires major edits, as previously defined but in 4 or more computed tomography slices; and a score of 1 requires complete recontouring of the region. Pelvic nodal regions included the right and left side of the common iliac, external iliac, internal iliac, obturator, and midline presacral nodes. In addition, patients were graded based on their lowest nodal contour score. Statistical analysis was performed using Fisher exact tests and Yates-corrected χ2 tests. Results: Fifty-two female and 51 male patients were included in the study, representing a total of 468 and 447 pelvic nodal regions, respectively. Ninety-six percent and 99% of contours required minor edits at most (score of 3 or 4) for female and male patients, respectively (P = .004 using Fisher exact test; P = .007 using Yates correction). No nodal regions had a statistically significant difference in scores between female and male patients. The percentage of patients requiring no more than minor edits was 87% (45 patients) and 92% (47 patients) for female and male patients, respectively (P = .53 using Fisher exact test; P = .55 using Yates correction). Conclusions: AASH pelvic nodal autosegmentation performed very well in both male and female pelvic nodal regions, although with better male pelvic nodal autosegmentation. As autosegmentation becomes more widespread, it may be important to have equal representation from all sexes in training and validation of autosegmentation algorithms.
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PURPOSE/OBJECTIVE S: Due to manual OAR contouring challenges, various automatic contouring solutions have been introduced. Historically, common clinical auto-segmentation algorithms used were atlas-based, which required maintaining a library of self-made contours. Searching the collection was computationally intensive and could take several minutes to complete. Deep learning approaches have shown significant benefits compared to atlas-based methods in improving segmentation accuracy and efficiency in auto-segmentation algorithms. This work represents the first multi-institutional study to describe and evaluate an AI algorithm for the auto-segmentation of organs at risk (OARs) based on a deep image-to-image network (DI2IN). MATERIALS/METHODS: The AI-Rad Companion Organs RT (AIRC) algorithm (Siemens Healthineers, Erlangen, Germany) uses a two-step approach for segmentation. In the first step, the target organ region in the optimal input image is extracted using a trained deep reinforcement learning network (DRL), which is then used as input to create the contours in the second step based on DI2IN. The study was initially designed as a prospective single-center evaluation. The automated contours generated by AIRC were evaluated by three experienced board-certified radiation oncologists using a four-point scale where 4 is clinically usable and 1 requires re-contouring. After seeing favorable results in a single-center pilot study, we decided to expand the study to six additional institutions, encompassing eight additional evaluators for a total of 11 physician evaluators across seven institutions. RESULTS: One hundred and fifty-six patients and 1366 contours were prospectively evaluated. The five most commonly contoured organs were the lung (136 contours, average rating = 4.0), spinal cord (106 contours, average rating = 3.1), eye globe (80 contours, average rating = 3.9), lens (77 contours, average rating = 3.9), and optic nerve (75 contours, average rating = 4.0). The average rating per evaluator per contour was 3.6. On average, 124 contours were evaluated by each evaluator. 65% of the contours were rated as 4, and 31% were rated as 3. Only 4% of contours were rated as 1 or 2. Thirty-three organs were evaluated in the study, with 19 structures having a 3.5 or above average rating (ribs, abdominopelvic cavity, skeleton, larynx, lung, aorta, brachial plexus, lens, eye globe, glottis, heart, parotid glands, bladder, kidneys, supraglottic larynx, submandibular glands, esophagus, optic nerve, oral cavity) and the remaining organs having a rating of 3.0 or greater (female breast, proximal femur, seminal vesicles, rectum, sternum, brainstem, prostate, brain, lips, mandible, liver, optic chiasm, spinal cord, spleen). No organ had an average rating below 3. CONCLUSION: AIRC performed well with greater than 95% of contours accepted by treating physicians with no or minor edits. It supported a fully automated workflow with the potential for time savings and increased standardization with the use of AI-powered algorithms for high-quality OAR contouring.
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Algoritmos , Aprendizado Profundo , Órgãos em Risco , Planejamento da Radioterapia Assistida por Computador , Humanos , Planejamento da Radioterapia Assistida por Computador/métodos , Órgãos em Risco/efeitos da radiação , Neoplasias/diagnóstico por imagem , Processamento de Imagem Assistida por Computador/métodos , Estudos Prospectivos , Tomografia Computadorizada por Raios X/métodos , Institutos de Câncer/normasRESUMO
Directing immunometabolism presents new opportunities to modulate key cell types associated with the formation of foreign body response (FBR) capsule. Contrasting approaches directing immunometabolism are investigated to mitigate FBR: a broadly suppressive metabolic inhibitor (MI) cocktail comprised of 2-deoxyglucose (2-DG), metformin, and 6-diazo-5-oxo-l-norleucine (DON) with daily systemic dosing regimen, and local weekly injection of the more narrowly focused tryptophan catabolizing IDO-Gal3 fusion protein. Treatments significantly decrease FBR capsule formed around subcutaneously implanted cellulose disks. MI cocktail results in a substantially thinner FBR capsule (40% of control), while weekly local injection of IDO-Gal3 also results in a thinner FBR capsule (69% of control). RNA-sequencing capsule transcripts reveal MI cocktail promotes quiescence, with decreased antigen processing and presentation, T helper subset differentiation, and cytokine-cytokine receptor pathway. IDO-Gal3 promotes pro-regenerative, alternatively activated M2-like macrophages and T helper 2 cells, with increased expression of type 2 response-associated genes (Il4, Il13, Arg1, Mrc1, Chil3, Gata3). IDO-Gal3 decreases pro-inflammatory innate sensing pathways, and C-type lectin receptor, NOD-like receptor, RIG-I-like receptor, and Toll-like receptor signaling. This work helps define key gene targets and pathways concomitantly regulated in the FBR capsule during immunometabolic modulation compared to control FBR capsule.
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Pregnant women and individuals with sickle cell trait (SCT) and underlying comorbidities are both independently more vulnerable to severe illness from coronavirus disease 2019 (COVID-19) compared to nonpregnant women and those without SCT. However, our understanding of the specific factors influencing susceptibility to COVID-19 infection among pregnant women with SCT is currently constrained by limited available data. This study aims to determine the risk and protective factors that influence the likelihood of COVID-19 infection in this population. A retrospective analysis was done among 151 women with SCT in the reproductive age group. Multivariable analysis was performed to determine the various factors affecting COVID-19 infection among pregnant women with SCT. The study found that COVID-19-vaccinated pregnant women with SCT had a 90% lower risk of contracting COVID-19 and were 9 times more likely to have a COVID-19 infection if they had a history of pulmonary conditions such as asthma or chronic obstructive pulmonary disease. The present study further emphasizes the importance of the COVID-19 vaccine in preventing infection and safeguarding the health of pregnant women with SCT, particularly those with underlying comorbidities.