Multifunctional Surface Treatment against Imperfections and Halide Segregation in Wide-Band Gap Perovskite Solar Cells.

Mixed-halide wide-band gap perovskites (WBPs) still suffer from losses due to imperfections within the absorber and the segregation of halide ions under external stimuli. Herein, we design a multifunctional passivator (MFP) by mixing bromide salt, formamidinium bromide (FABr) with a p-type self-assembled monolayer (SAM) to target the nonradiative recombination pathways. Photoluminescence measurement shows considerable suppression of nonradiative recombination rates after treatment with FABr. However, WBPs still remained susceptible to halide segregation for which the addition of 25% p-type SAM was effective to decelerate segregation. It is observed that FABr can act as a passivating agent of the donor impurities, shifting the Fermi-level (Ef) toward the mid-band gap, while p-type SAM could cause an overweight of Ef toward the valence band. Favorable band bending at the interface could prevent the funneling of carriers toward I-rich clusters. Instead, charge carriers funnel toward an integrated SAM, preventing the accumulation of polaron-induced strain on the lattice. Consequently, n-i-p structured devices with an optimal MFP treatment show an average open-circuit voltage (VOC) increase of about 20 mV and fill factor (FF) increase by 4% compared with the control samples. The unencapsulated devices retained 95% of their initial performance when stored at room temperature under 40% relative humidity for 2800 h.

Thermal Disorder-Induced Strain and Carrier Localization Activate Reverse Halide Segregation.

The reversal of halide ions is studied under various conditions. However, the underlying mechanism of heat-induced reversal remains unclear. This work finds that dynamic disorder-induced localization of self-trapped polarons and thermal disorder-induced strain (TDIS) can be co-acting drivers of reverse segregation. Localization of polarons results in an order of magnitude decrease in excess carrier density (polaron population), causing a reduced impact of the light-induced strain (LIS - responsible for segregation) on the perovskite framework. Meanwhile, exposing the lattice to TDIS exceeding the LIS can eliminate the photoexcitation-induced strain gradient, as thermal fluctuations of the lattice can mask the LIS strain. Under continuous 0.1 W cm⁻2 illumination (upon segregation), the strain disorder is estimated to be 0.14%, while at 80 °C under dark conditions, the strain is 0.23%. However, in situ heating of the segregated film to 80 °C under continuous illumination (upon reversal) increases the total strain disorder to 0.25%, where TDIS is likely to have a dominant contribution. Therefore, the contribution of entropy to the system's free energy is likely to dominate, respectively. Various temperature-dependent in situ measurements and simulations further support the results. These findings highlight the importance of strain homogenization for designing stable perovskites under real-world operating conditions.

Anterior Skull Base Osteoradionecrosis in the Age of Intensity-Modulated Radiation Therapy: A Case Series.

Background Despites advances in radiation technology, skull base osteoradionecrosis (ORN) continues to be a rare, devastating, and hard to treat complication of radiotherapy. We present three cases of anterior skull base ORN in a cohort treated with intensity-modulated radiation therapy (IMRT). Case Series Three patients developed anterior skull base ORN after receiving at least one round of IMRT. ORN was diagnosed through either nasal endoscopy or imaging findings. The first was a 59-year-old woman with a sinonasal squamous cell carcinoma. Her chemoradiation history was notable for reirradiation and a high dose of radiation (143.3 Gy). The second was a 55-year-old man with recurrent nasopharyngeal carcinoma, whose history was notable for a high dose of radiation (∼140 Gy) and for being reirradiated. The final patient was a 37-year-old woman with an unremarkable history who received radiotherapy (65.0 Gy) for an esthesioneuroblastoma. One patient was asymptomatic and did not receive ORN-specific therapy. The other two were treated with a combination of medical and surgical intervention with successful short-term outcomes (no evidence of infection). Conclusion Anterior skull base ORN can be treated through conservative and surgical means to achieve successful short-term outcomes. Further investigation of long-term outcomes is warranted.

ASSET: Auto-Segmentation of the Seventeen SEgments for Ventricular Tachycardia Ablation in Radiation Therapy.

There has been a recent effort to treat high-risk ventricular tachycardia (VT) patients through radio-ablation. However, manual segmentation of the VT target is complex and time-consuming. This work introduces ASSET, or Auto-segmentation of the Seventeen SEgments for Tachycardia ablation, to aid in radiation therapy (RT) planning. ASSET was retrospectively applied to CTs for 26 thoracic RT patients (13 undergoing VT ablation). The physician-defined parasternal long-axis of the left ventricle (LV) and the axes generated from principal component analysis (PCA) were compared using mean distance to agreement (MDA) and angle of separation. The manually selected right ventricle insertion point and LVs were used to apply the ASSET model to automatically generate the 17 segments of the LV myocardium (LVM). Physician-defined parasternal long-axis differed from PCA by 1.2 ± 0.3 mm MDA and 6.9 ± 0.7 degrees. Segments differed by 0.69 ± 0.29 mm MDA and 0.89 ± 0.03 Dice similarity coefficient. Running ASSET takes <5 min where manual segmentation took >2 h/patient. Agreement between ASSET and expert contours was comparable to inter-observer variability. Qualitative scoring conducted by three experts revealed automatically generated segmentations were clinically useable as-is. ASSET offers efficient and reliable automatic segmentations for the 17 segments of the LVM for target generation in RT planning.

A survival prediction model via interpretable machine learning for patients with oropharyngeal cancer following radiotherapy.

PURPOSE: To explore interpretable machine learning (ML) methods, with the hope of adding more prognosis value, for predicting survival for patients with Oropharyngeal-Cancer (OPC). METHODS: A cohort of 427 OPC patients (Training 341, Test 86) from TCIA database was analyzed. Radiomic features of gross-tumor-volume (GTV) extracted from planning CT using Pyradiomics, and HPV p16 status, etc. patient characteristics were considered as potential predictors. A multi-level dimension reduction algorithm consisting of Least-Absolute-Selection-Operator (Lasso) and Sequential-Floating-Backward-Selection (SFBS) was proposed to effectively remove redundant/irrelevant features. The interpretable model was constructed by quantifying the contribution of each feature to the Extreme-Gradient-Boosting (XGBoost) decision by Shapley-Additive-exPlanations (SHAP) algorithm. RESULTS: The Lasso-SFBS algorithm proposed in this study finally selected 14 features, and our prediction model achieved an area-under-ROC-curve (AUC) of 0.85 on the test dataset based on this feature set. The ranking of the contribution values calculated by SHAP shows that the top predictors that were most correlated with survival were ECOG performance status, wavelet-LLH_firstorder_Mean, chemotherapy, wavelet-LHL_glcm_InverseVariance, tumor size. Those patients who had chemotherapy, with positive HPV p16 status, and lower ECOG performance status, tended to have higher SHAP scores and longer survival; who had an older age at diagnosis, heavy drinking and smoking pack year history, tended to lower SHAP scores and shorter survival. CONCLUSION: We demonstrated predictive values of combined patient characteristics and imaging features for the overall survival of OPC patients. The multi-level dimension reduction algorithm can reliably identify the most plausible predictors that are mostly associated with overall survival. The interpretable patient-specific survival prediction model, capturing correlations of each predictor and clinical outcome, was developed to facilitate clinical decision-making for personalized treatment.

Non-invasive Stereotactic Body Radiation Therapy for Refractory Ventricular Arrhythmias: Venturing into the Unknown.

Stereotactic body radiation therapy (SBRT) is a promising new method for non-invasive management of life-threatening ventricular arrhythmias. Numerous case reports and case series have provided encouraging short-term results suggesting good efficacy and safety, but randomized data and long-term outcomes are not yet available. The primary hypothesis as to the mechanism of action for SBRT relates to the development of cardiac fibrosis in arrhythmogenic myocardial substrate; however, limited animal model data offer conflicting insights into this theory. The use of SBRT for patients with refractory ventricular arrhythmias is rapidly increasing, but ongoing translational science work and randomized clinical trials will be critical to address many outstanding questions regarding this novel therapy.

Trends in Adjuvant External Beam Radiation Therapy for Nonanaplastic Thyroid Cancer in California, 2003-2017.

BACKGROUND: External beam radiation therapy (EBRT) is rarely used to treat patients with differentiated or medullary thyroid cancer. Although EBRT is generally administered to patients with high-risk or unresectable diseases, neither its indications for the use nor the associated outcomes are well-defined. We used a statewide cohort to assess the trends in EBRT use and postradiation outcomes in California. METHODS: A population-based study of patients within the California Cancer Registry who underwent EBRT after surgery for nonanaplastic thyroid cancer (2003-2017) was conducted. The primary outcome was the annual utilization rate of EBRT. The secondary outcomes included Kaplan-Meier analysis for cause-specific survival and identifying factors associated with improved survival after EBRT. RESULTS: Among the 57 607 patients with nonanaplastic thyroid cancer from 2003 to 2017, 344 (0.6%) patients received EBRT. EBRT was utilized in 0.4% of papillary, 1.1% of follicular, and 7.7% of medullary thyroid cancers in California. Overall, 99 (28.8%) patients treated with EBRT died of thyroid cancer. The 10-year cause-specific survival of all patients with thyroid cancer after EBRT was 61.5% (95% CI: 54.8%-69.1%) and that of patients without distant disease was 80.3% (95% CI: 73.5%-87.8%). The survival outcomes varied by tumor size, histology, disease stage, patient age at diagnosis, and the presence of extrathyroidal extension (P < .05). CONCLUSIONS: The use of adjuvant EBRT for nonanaplastic thyroid cancer remained stable and low in California from 2003 to 2017. The comparative efficacy of EBRT was not discernible in this study, but disease control appeared durable in select patients. Well-controlled observational studies and/or prospective studies are needed to better define which patients benefit from EBRT.

Germline biomarkers predict toxicity to anti-PD1/PDL1 checkpoint therapy.

BACKGROUND: There is great interest in finding ways to identify patients who will develop toxicity to cancer therapies. This has become especially pressing in the era of immune therapy, where toxicity can be long-lasting and life-altering, and primarily comes in the form of immune-related adverse effects (irAEs). Treatment with the first drugs in this class, anti-programmed death 1 (anti-PD1)/programmed death-ligand 1 (PDL1) checkpoint therapies, results in grade 2 or higher irAEs in up to 25%-30% of patients, which occur most commonly within the first 6 months of treatment and can include arthralgias, rash, pruritus, pneumonitis, diarrhea and/or colitis, hepatitis, and endocrinopathies. We tested the hypothesis that germline microRNA pathway functional variants, known to predict altered systemic stress responses to cancer therapies, would predict irAEs in patients across cancer types. METHODS: MicroRNA pathway variants were evaluated for an association with grade 2 or higher toxicity using four classifiers on 62 patients with melanoma, and then the panel's performance was validated on 99 patients with other cancer types. Trained classifiers included classification trees, LASSO-regularized logistic regression, boosted trees, and random forests. Final performance measures were reported on the training set using leave-one-out cross validation and validated on held-out samples. The predicted probability of toxicity was evaluated for its association, if any, with response categories to anti-PD1/PDL1 therapy in the melanoma cohort. RESULTS: A biomarker panel was identified that predicts toxicity with 80% accuracy (F1=0.76, area under the curve (AUC)=0.82) in the melanoma training cohort and 77.6% accuracy (F1=0.621, AUC=0.778) in the pan-cancer validation cohort. In the melanoma cohort, the predictive probability of toxicity was not associated with response categories to anti-PD1/PDL1 therapy (p=0.70). In the same cohort, the most significant biomarker of toxicity in RAC1, predicting a greater than ninefold increased risk of toxicity (p<0.001), was also not associated with response to anti-PD1/PDL1 therapy (p=0.151). CONCLUSIONS: A germline microRNA-based biomarker signature predicts grade 2 and higher irAEs to anti-PD1/PDL1 therapy, regardless of tumor type, in a pan-cancer manner. These findings represent an important step toward personalizing checkpoint therapy, the use of which is growing rapidly.

A Prospective Phase II Study of Automated Non-Coplanar VMAT for Recurrent Head and Neck Cancer: Initial Report of Feasibility, Safety, and Patient-Reported Outcomes.

This study reports the initial results for the first 15 patients on a prospective phase II clinical trial exploring the safety, feasibility, and efficacy of the HyperArc technique for recurrent head and neck cancer treatment. Eligible patients were simulated and planned with both conventional VMAT and HyperArc techniques and the plan with superior dosimetry was selected for treatment. Dosimetry, delivery feasibility and safety, treatment-related toxicity, and patient-reported quality of life (QOL) were all evaluated. HyperArc was chosen over conventional VMAT for all 15 patients and enabled statistically significant increases in dose conformity (R50% reduced by 1.2 ± 2.1, p < 0.05) and mean PTV and GTV doses (by 15.7 ± 4.9 Gy, p < 0.01 and 17.1 ± 6.0 Gy, p < 0.01, respectively). The average HyperArc delivery was 2.8 min longer than conventional VMAT (p < 0.01), and the mean intrafraction motion was ≤ 0.5 ± 0.4 mm and ≤0.3 ± 0.1°. With a median follow-up of 12 months, treatment-related toxicity was minimal (only one grade 3 acute toxicity above baseline) and patient-reported QOL metrics were favorable. HyperArc enabled superior dosimetry and significant target dose escalation compared to conventional VMAT planning, and treatment delivery was feasible, safe, and well-tolerated by patients.

Voxelwise Prediction of Recurrent High-Grade Glioma via Proximity Estimation-Coupled Multidimensional Support Vector Machine.

PURPOSE: To provide early and localized glioblastoma (GBM) recurrence prediction, we introduce a novel postsurgery multiparametric magnetic resonance-based support vector machine (SVM) method coupling with stem cell niche (SCN) proximity estimation. METHODS AND MATERIALS: This study used postsurgery magnetic resonance imaging (MRI) scans from 50 patients with recurrent GBM, obtained approximately 2 months before clinically diagnosed recurrence. The main prediction pipeline consisted of a proximity-based estimator to identify regions with high risk of recurrence (HRRs) and an SVM classifier to provide voxelwise prediction in HRRs. The HRRs were estimated using the weighted sum of inverse distances to 2 possible origins of recurrence-the SCN and the tumor cavity. Subsequently, multiparametric voxels (from T1, T1 contrast-enhanced, fluid-attenuated inversion recovery, T2, and apparent diffusion coefficient) within the HRR were grouped into recurrent (warped from the clinical diagnosis) and nonrecurrent subregions and fed into the proximity estimation-coupled SVM classifier (SVMPE). The cohort was randomly divided into 40% and 60% for training and testing, respectively. The trained SVMPE was then extrapolated to an earlier time point for earlier recurrence prediction. As an exploratory analysis, the SVMPE predictive cluster sizes and the image intensities from the 5 magnetic resonance sequences were compared across time to assess the progressive subclinical traces. RESULTS: On 2-month prerecurrence MRI scans from 30 test cohort patients, the SVMPE classifier achieved a recall of 0.80, a precision of 0.69, an F1-score of 0.73, and a mean boundary distance of 7.49 mm. Exploratory analysis at early time points showed spatially consistent but significantly smaller subclinical clusters and significantly increased T1 contrast-enhanced and apparent diffusion coefficient values over time. CONCLUSIONS: We demonstrated a novel voxelwise early prediction method, SVMPE, for GBM recurrence based on clinical follow-up MR scans. The SVMPE is promising in localizing subclinical traces of recurrence 2 months ahead of clinical diagnosis and may be used to guide more effective personalized early salvage therapy.

NCCN Guidelines® Insights: Squamous Cell Skin Cancer, Version 1.2022.

The NCCN Guidelines for Squamous Cell Skin Cancer provide recommendations for diagnostic workup, clinical stage, and treatment options for patients with cutaneous squamous cell carcinoma. The NCCN panel meets annually to discuss updates to the guidelines based on comments from panel members and the Institutional Review, as well as submissions from within NCCN and external organizations. These NCCN Guidelines Insights focus on the introduction of a new surgical recommendation terminology (peripheral and deep en face margin assessment), as well as recent updates on topical prophylaxis, immunotherapy for regional and metastatic disease, and radiation therapy.

The impact and efficiency of medical screening exams in forward treatment areas at New York City public hospitals during the initial COVID-19 surge.

BACKGROUND: New York City (NYC) emergency departments (EDs) experienced a surge of patients because of coronavirus disease 2019 (COVID-19) in March 2020. NYC Health and Hospitals established rapid medical screening exams (MSE) and each hospital designated areas to perform their MSE. Five of the 11 hospitals created a forward treatment area (FTA) external to the ED to disposition patients before entering who presented with COVID-like symptoms. Three hospitals used paper-based, and 2 used an electronic medical record (EMR)-based MSE. This study evaluated the effectiveness of safely discharging patients home from the FTA while also evaluating the efficiency of using paper-based versus EMR-based MSEs. METHODS: Charts were reviewed using standardized data extraction templates. Patients discharged from the FTA were contacted by phone, and a structured interview captured additional data regarding subsequent clinical courses. Chi-square tests were used to compare proportions of patients hospitalized, as well as proportions of patients with vital signs recorded. Mortality rates were compared with Fisher exact test. A logistic regression model with fixed effects to account for clustering at hospitals was used to compare the odds of being sent to the ED for further evaluation based on vital signs and adjusted for age and sex. RESULTS: Across 5 EDs, 3335 patients were evaluated in their FTAs from March 17, 2020, to April 27, 2020. A total of 970 (29.1%) patients were referred for further evaluation into the ED, of which 203 (20.9%) were hospitalized and 19 (2.0%) died. Of 2302 patients discharged from the FTA, 182 (7.9%) returned to the ED within 7 days, resulting in 42 (1.8%) hospitalizations and 7 (0.3%) deaths. Facilities using EMR-MSE discharged more patients from their FTA (81.9% vs 65.3%, P < 0.001) and had similar 7-day return (9.3% vs 7.1%, P = 0.055) and mortality rates (0.49% vs 0.20%, P = 0.251). CONCLUSION: MSEs in an FTA are an effective process to disposition patients safely in a high-volume situation. Differences exist in paper- versus EMR-based approaches, suggesting EMR-MSEs provide better data, efficiency, and effectiveness. This suggests prioritizing an EMR-based MSE should be considered in future circumstances.

Simultaneous radiosurgery for multiple brain metastases: technical overview of the UCLA experience.

PURPOSE/OBJECTIVE(S): To communicate our institutional experience with single isocenter radiosurgery treatments for multiple brain metastases, including challenges with determining planning target volume (PTV) margins and resulting consequences, image-guidance translational and rotational tolerances, intra-fraction patient motion, and prescription considerations with larger PTV margins. MATERIALS/METHODS: Eight patient treatments with 51 targets were planned with various margins using Elements Multiple Brain Mets SRS treatment planning software (Brainlab, Munich, Germany). Forty-eight plans with 0 mm, 1 mm and 2 mm margins were created, including plans with variable margins, where targets more than 6 cm away from the isocenter were planned with larger margins. The dosimetric impact of the margins were analyzed with V5Gy, V8Gy, V10Gy, V12Gy values. Additionally, 12 patient motion data were analyzed to determine both the impact of the repositioning threshold and the distributions of the patient translational and rotational movements. RESULTS: The V5Gy, V8Gy, V10Gy, V12Gy volumes approximately doubled when margins change from 0 to 1 mm and tripled when change from 0 to 2 mm. With variable margins, the aggregated results are similar to results from plans using the lower of two margins, since only 12.2% of the targets were more than 6 cm away from the isocenter. With 0.5 mm re-positioning threshold, 57.4% of the time the patients are repositioned. Reducing the threshold to 0.25 mm results in 91.7% repositioning rate, due to limitations of the fusion algorithm and actual patient motion. The 90th percentile of translational movements in all directions is 0.7 mm, while the 90th percentile of rotational movements in all directions is 0.6 degrees. Median translations and rotations are 0.2 mm and 0.2 degrees, respectively. CONCLUSIONS: Based on the data presented, we have switched our modus operandi from 2 to 1 mm PTV margins, with an eventual goal of using 0.5 and 1.0 mm variable margins when an automated margin assignment method becomes available. The 0.5 mm and 0.5 degrees repositioning thresholds are clinically appropriate with small residual patient movements.

Clinical assessment of geometric distortion for a 0.35T MR-guided radiotherapy system.

PURPOSE: To estimate the overall spatial distortion on clinical patient images for a 0.35 T MR-guided radiotherapy system. METHODS: Ten patients with head-and-neck cancer underwent CT and MR simulations with identical immobilization. The MR images underwent the standard systematic distortion correction post-processing. The images were rigidly registered and landmark-based analysis was performed by an anatomical expert. Distortion was quantified using Euclidean distance between each landmark pair and tagged by tissue interface: bone-tissue, soft tissue, or air-tissue. For baseline comparisons, an anthropomorphic phantom was imaged and analyzed. RESULTS: The average spatial discrepancy between CT and MR landmarks was 1.15 ± 1.14 mm for the phantom and 1.46 ± 1.78 mm for patients. The error histogram peaked at 0-1 mm. 66% of the discrepancies were <2 mm and 51% <1 mm. In the patient data, statistically significant differences (p-values < 0.0001) were found between the different tissue interfaces with averages of 0.88 ± 1.24 mm, 2.01 ± 2.20 mm, and 1.41 ± 1.56 mm for the air/tissue, bone/tissue, and soft tissue, respectively. The distortion generally correlated with the in-plane radial distance from the image center along the longitudinal axis of the MR. CONCLUSION: Spatial distortion remains in the MR images after systematic distortion corrections. Although the average errors were relatively small, large distortions observed at bone/tissue interfaces emphasize the need for quantitative methods for assessing and correcting patient-specific spatial distortions.

Using neural networks to extend cropped medical images for deformable registration among images with differing scan extents.

PURPOSE: Missing or discrepant imaging volume is a common challenge in deformable image registration (DIR). To minimize the adverse impact, we train a neural network to synthesize cropped portions of head and neck CT's and then test its use in DIR. METHODS: Using a training dataset of 409 head and neck CT's, we trained a generative adversarial network to take in a cropped 3D image and output an image with synthesized anatomy in the cropped region. The network used a 3D U-Net generator along with Visual Geometry Group (VGG) deep feature losses. To test our technique, for each of the 53 test volumes, we used Elastix to deformably register combinations of a randomly cropped, full, and synthetically full volume to a single cropped, full, and synthetically full target volume. We additionally tested our method's robustness to crop extent by progressively increasing the amount of cropping, synthesizing the missing anatomy using our network, and then performing the same registration combinations. Registration performance was measured using 95% Hausdorff distance across 16 contours. RESULTS: We successfully trained a network to synthesize missing anatomy in superiorly and inferiorly cropped images. The network can estimate large regions in an incomplete image, far from the cropping boundary. Registration using our estimated full images was not significantly different from registration using the original full images. The average contour matching error for full image registration was 9.9 mm, whereas our method was 11.6, 12.1, and 13.6 mm for synthesized-to-full, full-to-synthesized, and synthesized-to-synthesized registrations, respectively. In comparison, registration using the cropped images had errors of 31.7 mm and higher. Plotting the registered image contour error as a function of initial preregistered error shows that our method is robust to registration difficulty. Synthesized-to-full registration was statistically independent of cropping extent up to 18.7 cm superiorly cropped. Synthesized-to-synthesized registration was nearly independent, with a -0.04 mm of change in average contour error for every additional millimeter of cropping. CONCLUSIONS: Different or inadequate in scan extent is a major cause of DIR inaccuracies. We address this challenge by training a neural network to complete cropped 3D images. We show that with image completion, the source of DIR inaccuracy is eliminated, and the method is robust to varying crop extent.

Automated Non-Coplanar VMAT for Dose Escalation in Recurrent Head and Neck Cancer Patients.

This study evaluates the potential for tumor dose escalation in recurrent head and neck cancer (rHNC) patients with automated non-coplanar volumetric modulated arc therapy (VMAT) stereotactic body radiation therapy (SBRT) planning (HyperArc). Twenty rHNC patients are planned with conventional VMAT SBRT to 40 Gy while minimizing organ-at-risk (OAR) doses. They are then re-planned with the HyperArc technique to match these minimal OAR doses while escalating the target dose as high as possible. Then, we compare the dosimetry, tumor control probability (TCP), and normal tissue complication probability (NTCP) for the two plan types. Our results show that the HyperArc technique significantly increases the mean planning target volume (PTV) and gross tumor volume (GTV) doses by 10.8 ± 4.4 Gy (25%) and 11.5 ± 5.1 Gy (26%) on average, respectively. There are no clinically significant differences in OAR doses, with maximum dose differences of <2 Gy on average. The average TCP is 23% (± 21%) higher for HyperArc than conventional plans, with no significant differences in NTCP for the brainstem, cord, mandible, or larynx. HyperArc can achieve significant tumor dose escalation while maintaining minimal OAR doses in the head and neck-potentially enabling improved local control for rHNC SBRT patients without increased risk of treatment-related toxicities.