Immune System Dose With Proton Versus Photon Radiotherapy for Treatment of Locally Advanced NSCLC.

Purpose: Emerging data have illuminated the impact of effective radiation dose to immune cells (EDIC) on outcomes in patients with locally advanced, unresectable non-small cell lung cancer (NSCLC) treated with intensity-modulated radiotherapy (IMRT). Hypothesizing that intensity-modulated proton therapy (IMPT) may reduce EDIC versus IMRT, we conducted a dosimetric analysis of patients treated at our institution. Materials and Methods: Data were retrospectively collected for 12 patients with locally advanced, unresectable NSCLC diagnosed between 2019 and 2021 who had physician-approved IMRT and IMPT plans. Data to calculate EDIC from both Jin et al (PMID: 34944813) and Ladbury et al's (PMID: 31175902) models were abstracted. Paired t tests were utilized to compare the difference in mean EDIC between IMPT and IMRT plans. Results: IMPT decreased EDIC for 11 of 12 patients (91.7%). The mean EDIC per the Jin model was significantly lower with IMPT than IMRT (3.04 GyE vs 4.99 Gy, P < .001). Similarly, the mean EDIC per the Ladbury model was significantly lower with IMPT than IMRT (4.50 GyE vs 7.60 Gy, P < .002). Modeled 2-year overall survival was significantly longer with IMPT than IMRT (median 71% vs 63%; P = .03). Conclusion: IMPT offers a statistically significant reduction in EDIC compared to IMRT. Given the emergence of EDIC as a modifiable prognostic factor in treatment planning, our dosimetric study highlights a potential role for IMPT to address an unmet need in improving oncologic outcomes in patients with locoregionally advanced NSCLC.

Assessing survival outcomes of patients with oral tongue squamous cell carcinoma: Focus on age, sex, and stage.

BACKGROUND: The purpose of this study was to provide further insights into whether age and/or sex are associated with prognosis in oral tongue squamous cell carcinoma. METHODS: This was a retrospective cohort study utilizing hospital registry data from 2006 to 2016 obtained from the National Cancer Database. Identified patients were divided into various cohorts based on age, sex, and staging. A descriptive analysis was performed using chi-square tests and overall survival rates were estimated using Kaplan-Meier method. RESULTS: A total of 17 642 patients were included in the study. The 5-year overall survival rates were 82.0% (95% CI: 79.8%-84.0%) in younger patients versus 67.5% (95% CI: 66.7%-68.3%, p-value <0.0001) older patients. The median overall survival for females was 143.4 months (95% CI: 133.2-NA) versus 129.8 (95% CI: 125.4-138.7, p-value <0.0001) in males. CONCLUSIONS: Our analysis suggests that younger age and female sex are both predictors of improved survival in oral tongue squamous cell carcinoma.

Diffeomorphic transformer-based abdomen MRI-CT deformable image registration.

BACKGROUND: Stereotactic body radiotherapy (SBRT) is a well-established treatment modality for liver metastases in patients unsuitable for surgery. Both CT and MRI are useful during treatment planning for accurate target delineation and to reduce potential organs-at-risk (OAR) toxicity from radiation. MRI-CT deformable image registration (DIR) is required to propagate the contours defined on high-contrast MRI to CT images. An accurate DIR method could lead to more precisely defined treatment volumes and superior OAR sparing on the treatment plan. Therefore, it is beneficial to develop an accurate MRI-CT DIR for liver SBRT. PURPOSE: To create a new deep learning model that can estimate the deformation vector field (DVF) for directly registering abdominal MRI-CT images. METHODS: The proposed method assumed a diffeomorphic deformation. By using topology-preserved deformation features extracted from the probabilistic diffeomorphic registration model, abdominal motion can be accurately obtained and utilized for DVF estimation. The model integrated Swin transformers, which have demonstrated superior performance in motion tracking, into the convolutional neural network (CNN) for deformation feature extraction. The model was optimized using a cross-modality image similarity loss and a surface matching loss. To compute the image loss, a modality-independent neighborhood descriptor (MIND) was used between the deformed MRI and CT images. The surface matching loss was determined by measuring the distance between the warped coordinates of the surfaces of contoured structures on the MRI and CT images. To evaluate the performance of the model, a retrospective study was carried out on a group of 50 liver cases that underwent rigid registration of MRI and CT scans. The deformed MRI image was assessed against the CT image using the target registration error (TRE), Dice similarity coefficient (DSC), and mean surface distance (MSD) between the deformed contours of the MRI image and manual contours of the CT image. RESULTS: When compared to only rigid registration, DIR with the proposed method resulted in an increase of the mean DSC values of the liver and portal vein from 0.850 ± 0.102 and 0.628 ± 0.129 to 0.903 ± 0.044 and 0.763 ± 0.073, a decrease of the mean MSD of the liver from 7.216 ± 4.513 mm to 3.232 ± 1.483 mm, and a decrease of the TRE from 26.238 ± 2.769 mm to 8.492 ± 1.058 mm. CONCLUSION: The proposed DIR method based on a diffeomorphic transformer provides an effective and efficient way to generate an accurate DVF from an MRI-CT image pair of the abdomen. It could be utilized in the current treatment planning workflow for liver SBRT.

Intensity-Modulated Reirradiation Therapy With Nivolumab in Recurrent or Second Primary Head and Neck Squamous Cell Carcinoma: A Nonrandomized Controlled Trial.

Importance: Intensity-modulated radiation therapy (IMRT) reirradiation of nonmetastatic recurrent or second primary head and neck squamous cell carcinoma (HNSCC) results in poor progression-free survival (PFS) and overall survival (OS). Objective: To investigate the tolerability, PFS, OS, and patient-reported outcomes with nivolumab (approved standard of care for patients with HNSCC) during and after IMRT reirradiation. Design, Setting, and Participants: In this multicenter nonrandomized phase 2 single-arm trial, the treatment outcomes of patients with recurrent or second primary HNSCC who satisfied recursive partitioning analysis class 1 and 2 definitions were evaluated. Between July 11, 2018, and August 12, 2021, 62 patients were consented and screened. Data were evaluated between June and December 2023. Intervention: Sixty- to 66-Gy IMRT in 30 to 33 daily fractions over 6 to 6.5 weeks with nivolumab, 240 mg, intravenously 2 weeks prior and every 2 weeks for 5 cycles during IMRT, then nivolumab, 480 mg, intravenously every 4 weeks for a total nivolumab duration of 52 weeks. Main Outcomes and Measures: The primary end point was PFS. Secondary end points included OS, incidence, and types of toxic effects, including long-term treatment-related toxic effects, patient-reported outcomes, and correlatives of tissue and blood biomarkers. Results: A total of 62 patients were screened, and 51 were evaluable (median [range] age was 62 [56-67] years; 42 [82%] were male; 6 [12%] had p16+ disease; 38 [75%] had salvage surgery; and 36 [71%.] had neck dissection). With a median follow-up of 24.5 months (95% CI, 19.0-25.0), the estimated 1-year PFS was 61.7% (95% CI, 49.2%-77.4%), rejecting the null hypothesis of 1-year PFS rate of less than 43.8% with 1-arm log-rank test P = .002 within a 1-year timeframe. The most common treatment-related grade 3 or higher adverse event (6 [12%]) was lymphopenia with 2 patients (4%) and 1 patient each (2%) exhibiting colitis, diarrhea, myositis, nausea, mucositis, and myasthenia gravis. Functional Assessment of Cancer Therapy-General and Functional Assessment of Cancer Therapy-Head and Neck Questionnaire quality of life scores remained stable and consistent across all time points. A hypothesis-generating trend favoring worsening PFS and OS in patients with an increase in blood PD1+, KI67+, and CD4+ T cells was observed. Conclusions and Relevance: This multicenter nonrandomized phase 2 trial of IMRT reirradiation therapy and nivolumab suggested a promising improvement in PFS over historical controls. The treatment was well tolerated and deserves further evaluation. Trial Registration: ClinicalTrials.gov Identifier: NCT03521570.

Diffeomorphic Transformer-based Abdomen MRI-CT Deformable Image Registration.

Background: Stereotactic body radiotherapy (SBRT) is a well-established treatment modality for liver metastases in patients unsuitable for surgery. Both CT and MRI are useful during treatment planning for accurate target delineation and to reduce potential organs-at-risk (OAR) toxicity from radiation. MRI-CT deformable image registration (DIR) is required to propagate the contours defined on high-contrast MRI to CT images. An accurate DIR method could lead to more precisely defined treatment volumes and superior OAR sparing on the treatment plan. Therefore, it is beneficial to develop an accurate MRI-CT DIR for liver SBRT. Purpose: To create a new deep learning model that can estimate the deformation vector field (DVF) for directly registering abdominal MRI-CT images. Methods: The proposed method assumed a diffeomorphic deformation. By using topology-preserved deformation features extracted from the probabilistic diffeomorphic registration model, abdominal motion can be accurately obtained and utilized for DVF estimation. The model integrated Swin transformers, which have demonstrated superior performance in motion tracking, into the convolutional neural network (CNN) for deformation feature extraction. The model was optimized using a cross-modality image similarity loss and a surface matching loss. To compute the image loss, a modality-independent neighborhood descriptor (MIND) was used between the deformed MRI and CT images. The surface matching loss was determined by measuring the distance between the warped coordinates of the surfaces of contoured structures on the MRI and CT images. To evaluate the performance of the model, a retrospective study was carried out on a group of 50 liver cases that underwent rigid registration of MRI and CT scans. The deformed MRI image was assessed against the CT image using the target registration error (TRE), Dice similarity coefficient (DSC), and mean surface distance (MSD) between the deformed contours of the MRI image and manual contours of the CT image. Results: When compared to only rigid registration, DIR with the proposed method resulted in an increase of the mean DSC values of the liver and portal vein from 0.850±0.102 and 0.628±0.129 to 0.903±0.044 and 0.763±0.073, a decrease of the mean MSD of the liver from 7.216±4.513 mm to 3.232±1.483 mm, and a decrease of the TRE from 26.238±2.769 mm to 8.492±1.058 mm. Conclusion: The proposed DIR method based on a diffeomorphic transformer provides an effective and efficient way to generate an accurate DVF from an MRI-CT image pair of the abdomen. It could be utilized in the current treatment planning workflow for liver SBRT.

A retrospective study on the investigation of potential dosimetric benefits of online adaptive proton therapy for head and neck cancer.

PURPOSE: Proton therapy is sensitive to anatomical changes, often occurring in head-and-neck (HN) cancer patients. Although multiple studies have proposed online adaptive proton therapy (APT), there is still a concern in the radiotherapy community about the necessity of online APT. We have performed a retrospective study to investigate the potential dosimetric benefits of online APT for HN patients relative to the current offline APT. METHODS: Our retrospective study has a patient cohort of 10 cases. To mimic online APT, we re-evaluated the dose of the in-use treatment plan on patients' actual treatment anatomy captured by cone-beam CT (CBCT) for each fraction and performed a templated-based automatic replanning if needed, assuming that these were performed online before treatment delivery. Cumulative dose of the simulated online APT course was calculated and compared with that of the actual offline APT course and the designed plan dose of the initial treatment plan (referred to as nominal plan). The ProKnow scoring system was employed and adapted for our study to quantify the actual quality of both courses against our planning goals. RESULTS: The average score of the nominal plans over the 10 cases is 41.0, while those of the actual offline APT course and our simulated online course is 25.8 and 37.5, respectively. Compared to the offline APT course, our online course improved dose quality for all cases, with the score improvement ranging from 0.4 to 26.9 and an average improvement of 11.7. CONCLUSION: The results of our retrospective study have demonstrated that online APT can better address anatomical changes for HN cancer patients than the current offline replanning practice. The advanced artificial intelligence based automatic replanning technology presents a promising avenue for extending potential benefits of online APT.

What is microbial dormancy?

Life can be stressful. One way to deal with stress is to simply wait it out. Microbes do this by entering a state of reduced activity and increased resistance commonly called 'dormancy'. But what is dormancy? Different scientific disciplines emphasize distinct traits and phenotypic ranges in defining dormancy for their microbial species and system-specific questions of interest. Here, we propose a unified definition of microbial dormancy, using a broad framework to place earlier discipline-specific definitions in a new context. We then discuss how this new definition and framework may improve our ability to investigate dormancy using multi-omics tools. Finally, we leverage our framework to discuss the diversity of genomic mechanisms for dormancy in an extreme environment that challenges easy definitions - the permafrost.

Proton liver stereotactic body radiation therapy: Treatment techniques and dosimetry feasibility from a single institution.

Purpose: To assess the resulting dosimetry characteristics of simulation and planning techniques for proton stereotactic body radiation therapy (SBRT) of primary and secondary liver tumors. Methods: Consecutive patients treated under volumetric daily image guidance with liver proton SBRT between September 2019 and March 2022 at Emory Proton Therapy Center were included in this study. Prescriptions ranged from 40 Gy to 60 Gy in 3- or 5-fraction regimens, and motion management techniques were used when target motion exceeded 5 mm. 4D robust optimization was used when necessary. Dosimetry evaluation was conducted for ITV V100, D99, Dmax, and liver-ITV mean dose and D700cc. Statistical analysis was performed using independent-samples Mann-Whitney U tests. Results: Thirty-six tumors from 29 patients were treated. Proton therapy for primary and secondary liver tumors using motion management techniques and robust optimization resulted in high target coverage and low doses to critical organs. The median ITV V100% was 100.0%, and the median ITV D99% was 111.3%. The median liver-ITV mean dose and D700cc were 499 cGy and 5.7 cGy, respectively. The median conformity index (CI) was 1.03, and the median R50 was 2.56. Except for ITV D99% (primary 118.1% vs. secondary 107.2%, p = 0.005), there were no significant differences in age, ITV volume, ITV V100%, ITV maximum dose, liver-ITV mean dose, or D700cc between primary and secondary tumor groups. Conclusion: The study demonstrated that proton therapy with motion management techniques and robust optimization achieves excellent target coverage with low normal liver doses for primary and secondary liver tumors. The results showed high target coverage, high conformality, and low doses to the liver.

Sex differences in acute telestroke care: more to the story.

Background: Previous studies have shown sex differences in stroke care. Female patients have both lower thrombolytic treatment rates with OR reported as low as 0.57 and worse outcomes. With updated standards of care and improved access to care through telestroke, there is potential to reduce or alleviate these disparities. Methods: Acute stroke consultations seen by TeleSpecialists, LLC physicians in the emergency department in 203 facilities (23 states) from January 1, 2021 to April 30, 2021 were extracted from the Telecare by TeleSpecialists™ database. The encounters were reviewed for demographics, stroke time metrics, thrombolytics candidate, premorbid modified Rankin Score, NIHSS score, stroke risk factors, antithrombotic use, admitting diagnosis of suspected stroke, and reason not treated with thrombolytic. The treatment rates, door to needle (DTN) times, stroke metric times, and variables of treatment were compared for females and males. Results: There were 18,783 (10,073 female and 8,710 male) total patients included. Of the total, 6.9% of females received thrombolytics compared to 7.9% of males (OR 0.86, 95% CI 0.75-0.97, p = 0.006). Median DTN times were shorter for males than females (38 vs. 41 min, p < 0.001). Male patients were more likely to have an admitting diagnosis of suspected stroke, p < 0.001. Analysis by age showed the only decade with significant difference in thrombolytics treatment rate was 50-59 with increased treatment of males, p = 0.047. When multivariant logistic regression analysis was performed with stroke risk factors, NIHSS score, age, and admitting diagnosis of suspected stroke, the adjusted odds ratio for females was 0.9 (95% CI 0.8, 1.01), p = 0.064. Conclusion: While treatment differences between sexes existed in the data and were apparent in univariate analysis, no significant difference was seen in multivariate analysis once stroke risk factors, age, NIHSS score and admitting diagnosis were taken into consideration in the telestroke setting. Differences in rates of thrombolysis between sexes may therefore be reflective of differences in risk factors and symptomatology rather than a healthcare disparity.

Pembrolizumab and cabozantinib in recurrent metastatic head and neck squamous cell carcinoma: a phase 2 trial.

Anti-programmed cell death protein 1 (PD-1) therapy is a standard of care in recurrent metastatic head and neck squamous cell carcinoma (RMHNSCC). Vascular endothelial growth factor inhibitors, including tyrosine kinase inhibitors, have immunomodulatory properties and have offered promising results when combined with anti-PD-1 agents. We conducted a phase 2, multicenter, single-arm trial of pembrolizumab and cabozantinib in patients with RMHNSCC who had Response Evaluation Criteria in Solid Tumors v.1.1 measurable disease and no contraindications to either agent. We assessed the primary end points of tolerability and overall response rate to the combination with secondary end points of progression-free survival and overall survival and performed correlative studies with PDL-1 and combined positive score, CD8+ T cell infiltration and tumor mutational burden. A total of 50 patients were screened and 36 were enrolled with 33 evaluable for response. The primary end point was met, with 17 out of 33 patients having a partial response (52%) and 13 (39%) stable disease with an overall clinical benefit rate of 91%. Median and 1-year overall survival were 22.3 months (95% confidence interval (CI) = 11.7-32.9) and 68.4% (95% CI = 45.1%-83.5%), respectively. Median and 1-year progression-free survival were 14.6 months (95% CI = 8.2-19.6) and 54% (95% CI = 31.5%-72%), respectively. Grade 3 or higher treatment-related adverse events included increased aspartate aminotransferase (n = 2, 5.6%). In 16 patients (44.4%), the dose of cabozantinib was reduced to 20 mg daily. The overall response rate correlated positively with baseline CD8+ T cell infiltration. There was no observed correlation between tumor mutational burden and clinical outcome. Pembrolizumab and cabozantinib were well tolerated and showed promising clinical activity in patients with RMHNSCC. Further investigation of similar combinations are needed in RMHNSCC. The trial is registered at ClinicalTrials.gov under registration no. NCT03468218 .

The impact of race and ethnicity on acute telestroke care: A multistate experience.

INTRODUCTION: Previous analyses suggest that ethnic and racial differences exist in acute stroke care including thrombolytic treatment rates. The current study evaluates ethnic or racial differences in acute stroke treatment within a multi-state telestroke program. METHODS: Acute telestroke consultations seen in the Emergency Department in 203 facilities and 23 states were extracted from the Telecare by TeleSpecialistsTM database. Cases were reviewed for age, race, ethnicity, sex, last known normal time, arrival time, treatment with thrombolytic therapy, door-to-needle (DTN) time, and baseline National Institutes of Health Stroke Scale score. Race was defined as Black, White, or Other; ethnicity was defined as Hispanic or non-Hispanic. RESULTS: The current study included 13,221 acute telestroke consultations consisting of 9890 White, 2048 Black, and 1283 patients classified as Other. A total of 934 patients were Hispanic and 12,287 patients were non-Hispanic. There were no statistically significant differences noted in thrombolytic treatment rates when comparing White (7.9%) patients with non-White patients (7.4%), p = 0.36, or comparing Black (8.1%) with non-Black patients (7.8%), p = 0.59. In addition, there were no statistically significant differences in treatment rates comparing Hispanic (6.3%) with non-Hispanic (7.9%) patients, p = 0.072. We noted no measurable differences in DTN times by race or ethnicity. CONCLUSIONS: Contrary to previous reports, we failed to detect any significant differences in thrombolytic treatment rates and DTN times by race or ethnicity among stroke patients in a multistate telestroke program. These findings support the hypothesis that telestroke may mitigate racial and ethnic disparities which may be attributable to local variability in stroke procedures or access to healthcare.

Insurance Authorization and Access to Proton Therapy for Patients With Head and Neck Cancers.

PURPOSE: We evaluated our institutional experience to assess potential racial inequities in insurance coverage for proton therapy in patients with head and neck (HN) cancer. METHODS AND MATERIALS: We examined the demographics of 1519 patients with HN cancer seen in consultation at our HN multidisciplinary clinic (HN MDC) and 805 patients for whom a proton insurance authorization was sought (PAS) from January 2020 to June 2022. The prospects for proton therapy insurance authorization were prospectively noted based on each patient's ICD-10 (International Classification of Diseases, 10th Revision) diagnosis code and their specific insurance plan. Proton-unfavorable (PU) insurance were those plans whose policy describes proton beam therapy as "experimental" or "not medically necessary" for the given diagnosis. RESULTS: For patients seen in our HN MDC, Black, Indigenous, and people of color (BIPOC) were significantly more likely to have PU insurance than non-Hispanic White (NHW) patients (24.9% vs 18.4%, P = .005). In multivariable analysis including race, average income of residence ZIP code, and Medicare eligibility age, BIPOC patients had an odds ratio of 1.25 for PU insurance (P = .041). In the PAS cohort, while there was no difference in the percentage of patients receiving insurance approval for proton therapy between NHW and BIPOC populations (88% vs 88.2%, P = .80), for patients with PU insurance, the median time to determination was significantly longer (median, 15.5 days), and the median time to start any radiation of any modality was longer (46 vs 35 days, P = .08). Compared with NHW patients, the median time from consultation to start of radiation therapy was longer for BIPOC patients (37 vs 43 days, P = .01). CONCLUSIONS: BIPOC patients were significantly more likely to have insurance plans unfavorable to proton therapy coverage. These PU insurance plans were associated with a longer median time to determination, a lower approval rate for proton therapy, and a longer time to start radiation of any modality.

Factors Affecting Clinical Outcomes Among Patients Infected With HIV and Anal Cancer Treated With Modern Definitive Chemotherapy and Radiation Therapy.

Purpose: Anal cancer affects a disproportionate percentage of persons infected with human immunodeficiency virus (HIV). We analyzed a cohort of patients with HIV and anal cancer who received modern radiation therapy (RT) and concurrent chemotherapy to assess whether certain factors are associated with poor oncologic outcomes. Patients and Methods: We performed a retrospective chart review of 75 consecutive patients with HIV infection and anal cancer who received definitive chemotherapy and RT from 2008 to 2018 at a single academic institution. Local recurrence, overall survival, changes in CD4 counts, and toxicities were investigated. Results: Most patients were male (92%) with large representation from Black patients (77%). The median pretreatment CD4 count was 280 cells/mm3, which was persistently lower at 6 and 12 months' posttreatment, 87 cells/mm3 and 182 cells/mm3, respectively (P < .001). Most (92%) patients received intensity modulated RT; median dose was 54 Gy (Range, 46.8-59.4 Gy). At a median follow-up 5.4 years (Range, 4.37-6.21 years), 20 (27%) patients had disease recurrence and 10 (13%) had isolated local failures. Nine patients died due to progressive disease. In multivariable analysis, clinically node negative involvement was significantly associated with better overall survival (hazard ratio, 0.39; 95% confidence interval, 0.16-1.00, P = .049). Acute grade 2 and 3 skin toxicities were common, at 83% and 19%, respectively. Acute grade 2 and 3 gastrointestinal toxicities were 9% and 3%, respectively. Acute grade 3 hematologic toxicity was 20%, and one grade 5 toxicity was reported. Several late grade 3 toxicities persisted: gastrointestinal (24%), skin (17%), and hematologic (6%). Two late grade 5 toxicities were noted. Conclusions: Most patients with HIV and anal cancer did not experience local recurrence; however, acute and late toxicities were common. CD4 counts at 6 and 12 months' posttreatment remained lower than pretreatment CD4 counts. Further attention to treatment of the HIV-infected population is needed.

Steering particles via micro-actuation of chemical gradients using model predictive control.

Biological systems rely on chemical gradients to direct motion through both chemotaxis and signaling, but synthetic approaches for doing the same are still relatively naïve. Consequently, we present a novel method for using chemical gradients to manipulate the position and velocity of colloidal particles in a microfluidic device. Specifically, we show that a set of spatially localized chemical reactions that are sufficiently controllable can be used to steer colloidal particles via diffusiophoresis along an arbitrary trajectory. To accomplish this, we develop a control method for steering colloidal particles with chemical gradients using nonlinear model predictive control with a model based on the unsteady Green's function solution of the diffusion equation. We illustrate the effectiveness of our approach using Brownian dynamics simulations that steer single particles along paths, such as circle, square, and figure-eight. We subsequently compare our results with published techniques for steering colloids using electric fields, and we provide an analysis of the physical parameter space where our approach is useful. Based on these findings, we conclude that it is theoretically possible to explicitly steer particles via chemical gradients in a microfluidics paradigm.

Active control of equilibrium, near-equilibrium, and far-from-equilibrium colloidal systems.

The development of top-down active control over bottom-up colloidal assembly processes has the potential to produce materials, surfaces, and objects with applications in a wide range of fields spanning from computing to materials science to biomedical engineering. In this review, we summarize recent progress in the field using a taxonomy based on how active control is used to guide assembly. We find there are three distinct scenarios: (1) navigating kinetic pathways to reach a desirable equilibrium state, (2) the creation of a desirable metastable, kinetically trapped, or kinetically arrested state, and (3) the creation of a desirable far-from-equilibrium state through continuous energy input. We review seminal works within this framework, provide a summary of important application areas, and present a brief introduction to the fundamental concepts of control theory that are necessary for the soft materials community to understand this literature. In addition, we outline current and potential future applications of actively-controlled colloidal systems, and we highlight important open questions and future directions.

Ninety-day mortality following transoral robotic surgery or radiation at Commission on Cancer-accredited facilities.

BACKGROUND: Postoperative mortality for oropharynx squamous cell carcinoma (OPSCC) with transoral robotic surgery (TORS) varies from 0.2% to 6.5% on trials; the real-world rate is unknown. METHODS: NCDB study from 2010 to 2017 for patients with cT1-2N0-2M0 OPSCC with Charleson-Deyo score 0-1. Ninety-day mortality assessed from start and end of treatment at Commission on Cancer-accredited facilities. RESULTS: 3639 patients were treated with TORS and 1937 with radiotherapy. TORS cohort had more women and higher income, was younger, more often treated at academic centers, and more likely to have private insurance (all p < 0.05). Ninety-day mortality was 1.3% with TORS and 0.7% or 1.4% from start or end of radiotherapy, respectively. From end of therapy, there was no significant difference on MVA between treatment modality. CONCLUSIONS: There is minimal difference between 90-day mortality in patients treated with TORS or radiotherapy for early-stage OPSCC. While overall rates are low, for patients with expectation of cure, work is needed to identify optimal treatment.

A component method to delineate surgical spine implants for proton Monte Carlo dose calculation.

PURPOSE: Metallic implants have been correlated to local control failure for spinal sarcoma and chordoma patients due to the uncertainty of implant delineation from computed tomography (CT). Such uncertainty can compromise the proton Monte Carlo dose calculation (MCDC) accuracy. A component method is proposed to determine the dimension and volume of the implants from CT images. METHODS: The proposed component method leverages the knowledge of surgical implants from medical supply vendors to predefine accurate contours for each implant component, including tulips, screw bodies, lockers, and rods. A retrospective patient study was conducted to demonstrate the feasibility of the method. The reference implant materials and samples were collected from patient medical records and vendors, Medtronic and NuVasive. Additional CT images with extensive features, such as extended Hounsfield units and various reconstruction diameters, were used to quantify the uncertainty of implant contours. RESULTS: For in vivo patient implant estimation, the reference and the component method differences were 0.35, 0.17, and 0.04 cm3 for tulips, screw bodies, and rods, respectively. The discrepancies by a conventional threshold method were 5.46, 0.76, and 0.05 cm3 , respectively. The mischaracterization of implant materials and dimensions can underdose the clinical target volume coverage by 20 cm3 for a patient with eight lumbar implants. The tulip dominates the dosimetry uncertainty as it can be made from titanium or cobalt-chromium alloys by different vendors. CONCLUSIONS: A component method was developed and demonstrated using phantom and patient studies with implants. The proposed method provides more accurate implant characterization for proton MCDC and can potentially enhance the treatment quality for proton therapy. The current proof-of-concept study is limited to the implant characterization for lumbar spine. Future investigations could be extended to cervical spine and dental implants for head-and-neck patients where tight margins are required to spare organs at risk.

Human vs. Machine Learning Based Detection of Facial Weakness Using Video Analysis.

Background: Current EMS stroke screening tools facilitate early detection and triage, but the tools' accuracy and reliability are limited and highly variable. An automated stroke screening tool could improve stroke outcomes by facilitating more accurate prehospital diagnosis and delivery. We hypothesize that a machine learning algorithm using video analysis can detect common signs of stroke. As a proof-of-concept study, we trained a computer algorithm to detect presence and laterality of facial weakness in publically available videos with comparable accuracy, sensitivity, and specificity to paramedics. Methods and Results: We curated videos of people with unilateral facial weakness (n = 93) and with a normal smile (n = 96) from publicly available web-based sources. Three board certified vascular neurologists categorized the videos according to the presence or absence of weakness and laterality. Three paramedics independently analyzed each video with a mean accuracy, sensitivity and specificity of 92.6% [95% CI 90.1-94.7%], 87.8% [95% CI 83.9-91.7%] and 99.3% [95% CI 98.2-100%]. Using a 5-fold cross validation scheme, we trained a computer vision algorithm to analyze the same videos producing an accuracy, sensitivity and specificity of 88.9% [95% CI 83.5-93%], 90.3% [95% CI 82.4-95.5%] and 87.5 [95% CI 79.2-93.4%]. Conclusions: These preliminary results suggest that a machine learning algorithm using computer vision analysis can detect unilateral facial weakness in pre-recorded videos with an accuracy and sensitivity comparable to trained paramedics. Further research is warranted to pursue the concept of augmented facial weakness detection and external validation of this algorithm in independent data sets and prospective patient encounters.

Deformable CT image registration via a dual feasible neural network.

PURPOSE: A quality assurance (QA) CT scans are usually acquired during cancer radiotherapy to assess for any anatomical changes, which may cause an unacceptable dose deviation and therefore warrant a replan. Accurate and rapid deformable image registration (DIR) is needed to support contour propagation from the planning CT (pCT) to the QA CT to facilitate dose volume histogram (DVH) review. Further, the generated deformation maps are used to track the anatomical variations throughout the treatment course and calculate the corresponding accumulated dose from one or more treatment plans. METHODS: In this study, we aim to develop a deep learning (DL)-based method for automatic deformable registration to align the pCT and the QA CT. Our proposed method, named dual-feasible framework, was implemented by a mutual network that functions as both a forward module and a backward module. The mutual network was trained to predict two deformation vector fields (DVFs) simultaneously, which were then used to register the pCT and QA CT in both directions. A novel dual feasible loss was proposed to train the mutual network. The dual-feasible framework was able to provide additional DVF regularization during network training, which preserves the topology and reduces folding problems. We conducted experiments on 65 head-and-neck cancer patients (228 CTs in total), each with 1 pCT and 2-6 QA CTs. For evaluations, we calculated the mean absolute error (MAE), peak-signal-to-noise ratio (PSNR), structural similarity index (SSIM), target registration error (TRE) between the deformed and target images and the Jacobian determinant of the predicted DVFs. RESULTS: Within the body contour, the mean MAE, PSNR, SSIM, and TRE are 122.7 HU, 21.8 dB, 0.62 and 4.1 mm before registration and are 40.6 HU, 30.8 dB, 0.94, and 2.0 mm after registration using the proposed method. These results demonstrate the feasibility and efficacy of our proposed method for pCT and QA CT DIR. CONCLUSION: In summary, we proposed a DL-based method for automatic DIR to match the pCT to the QA CT. Such DIR method would not only benefit current workflow of evaluating DVHs on QA CTs but may also facilitate studies of treatment response assessment and radiomics that depend heavily on the accurate localization of tissues across longitudinal images.

A prediction model to determine the untapped lung donor pool outside of the DonateLife network in Victoria.

Lung transplantation is limited by a lack of suitable lung donors. In Australia, the national donation organisation (DonateLife) has taken a major role in optimising organ donor identification. However, the potential outside the DonateLife network hospitals remains uncertain. We aimed to create a prediction model for lung donation within the DonateLife network and estimate the untapped lung donors outside of the DonateLife network. We reviewed all deaths in the state of Victoria's intensive care units using a prospectively collected population-based intensive care unit database linked to organ donation records. A logistic regression model derived using patient-level data was developed to characterise the lung donors within DonateLife network hospitals. Consequently, we estimated the expected number of lung donors in Victorian hospitals outside the DonateLife network and compared the actual number. Between 2014 and 2018, 291 lung donations occurred from 8043 intensive care unit deaths in DonateLife hospitals, while only three lung donations occurred from 1373 ICU deaths in non-DonateLife hospitals. Age, sex, postoperative admission, sepsis, neurological disease, trauma, chronic respiratory disease, lung oxygenation and serum creatinine were factors independently associated with lung donation. A highly discriminatory prediction model with area under the receiver operator characteristic curve of 0.91 was developed and accurately estimated the number of lung donors. Applying the model to non-DonateLife hospital data predicted only an additional five lung donors. This prediction model revealed few additional lung donor opportunities outside the DonateLife network, and the necessity of alternative and novel strategies for lung donation. A donor prediction model could provide a useful benchmarking tool to explore organ donation potential across different jurisdictions, hospitals and transplanting centres.