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Background Tobacco and alcohol use are risk factors for Squamous Cell Carcinoma of the Head and Neck (SCCHN); however, there is growing recognition of HPV as a risk factor for SCCHN. HPV‐related SCCHN is thought to affect mostly middle‐aged individuals but as the US population ages, it is important to evaluate the change in incidence of HPV‐ and non‐HPV‐related SCCHN in individuals who are ≥65 years old. Methods This was a retrospective study using data from a population‐based cancer registry (SEER) to identify individuals ≥65 years old diagnosed with SCCHN between 2000 and 2016 also stratified by sex, race, and birth cohort. The subgroups of HPV‐associated and non‐HPV associated sites were analyzed independently. The incidence per year was calculated and joinpoint detection was used to identity significant changes in incidence trends and annual percent change (APC). Results For HPV‐associated sites from 2000 to 2016, there was an average annual rate of 10.8 per 100,000 individuals with an APC of 2.92% (p =, This study reports results that are consistent with other studies demonstrating that the prevalence HPV associated of head and neck cancer overall is increasing in the elderly population age ≥65 years. This increase is occurring when stratified by race, sex, and birth cohort however, the White male population is experiencing the most significant annual percent increase in the incidence of HPV‐associated head and neck cancers. HPV‐associated head and neck cancers are no longer a disease associated with younger patients and the increasing prevalence of this disease in the elderly population is important when considering the unique challenges of treatment for this age group.

Purpose/Objective(s) Normal tissue complication probability (NTCP) models can estimate differences in clinical outcomes between proton therapy (PT) and photon radiation (RT) plans for oropharyngeal cancer. We assessed the accuracy of our rapid comparative planning (RCP) process vs fully optimized clinical treatment plans (OCP) and tested whether anticipated clinical benefits were associated with insurance approval for PT. Materials/Methods We performed RCP of photon VMAT and pencil beam PT in 30 consecutive patients (pts) with oropharyngeal cancer requiring bilateral neck RT to 60-70 Gy, using published NTCP models of Grade (G) 3+ mucositis, G3+ dysphagia, G4 xerostomia, G3+ aspiration, G2 hypothyroidism, and G2 trismus to assess differences between plans. Most (90%) had T1-2 tumors (80%); 93% were node+ (23% bilateral). Predicted risk reduction > 10% for G2 and > 5% for G3+ toxicity were considered clinically relevant thresholds. RCP used diagnostic imaging (n = 16) or simulation CT (n = 14). The latter group also had VMAT and PT OCP using the same CT dataset (4 plans each) and served as a validation cohort (n = 14) for RCP. The positive predictive value (PPV) of the RCPs was assessed by the # of pts anticipated to have at least 1 clinically relevant toxicity reduction with PT therapy in both RCP and OCP (true positives) divided by true positives plus false positives (RCP plans anticipated a benefit but OCP PT plans no longer achieved at least 1 anticipated benefit vs VMAT). The accuracy of individual NTCP models was assessed between RCP and OCP. Results RCP predicted ≥1 clinically relevant toxicity reduction in all 30 pts. In the validation cohort, the OCP PT plans also achieved ≥1 toxicity reduction threshold in all pts, yielding a PPV of 100%. In RCP, a median of 5 toxicity thresholds was achieved by PT. In the validation cohort, 57% of OCP PT plans achieved the same or greater # of toxicity threshold reductions. Models for G3+ mucositis and G2 trismus had the highest PPV and the model for G4 xerostomia the lowest. Pts denied insurance coverage for PT therapy had, on average, more NTCP thresholds of any grade toxicity met by PT therapy in RPC than did those approved (5 vs 4 thresholds met, P = 0.049). There was no difference by insurance approval in the average number of G3+ toxicity reductions achieved or the relative magnitude of predicted benefit in any individual NTCP model. Conclusion RCP incorporating NTCP-based toxicity estimation by RT modality appears to be a reliable predictor based on concordant finding of at least one clinically relevant toxicity reduction in both RCP and OCP. Predicted clinical benefit was not correlated with insurance approval for PT therapy.

Purpose/Objective(s) Intensity modulated proton therapy has become increasingly popular in the treatment of head and neck (HN) cancer because of its high normal tissue sparing compared to photon therapy. However, proton plans are very sensitive to anatomy changes such as weight loss or tumor shrinkage that leads to a 25% replan rate at our center. This analysis aims to predict whether a HN patient will need a replan using various dosimetric and clinical features at the onset of treatment. Materials/Methods Data were gathered from 176 HN patients treated at our institution. The most common sites were the oropharynx (40 cases), lip/oral cavity (20 cases), and nasal cavity/sinuses (14 cases). Beam dose heterogeneity index (BHI) was defined as the ratio of the D0.1cc of beam dose to half of the prescription dose. BHI was calculated for every beam and the average BHI for each plan was calculated. Robustness scenarios included a combination of ± 3 mm setup shifts on 3 coordinate directions and ± 3.5% range uncertainty. Plan robustness was evaluated with several features gathered from the highest dose level CTV. These include the fraction of all scenarios where V100 > 95% (passing rate), mean V100, mean V100 deviation from the nominal plan, and mean max dose change from the nominal. 61% of patients were treated to bilateral neck with multi-dose level simultaneous integrated boost plans. A five-beam arrangement (two posterior, two anterior oblique beams, and an AP beam) were used to treat most bilateral HN patients and a 3-beam arrangement was used to treat most unilateral HN patients. Any portion of the target is typically covered by at least two beams. Results Sixty-three patients were replanned at least once in this subpopulation. Plans were normalized at V100 = 98% when possible for the highest dose level. The BHIs from each planner were significantly different from each other, ranging from 1.01 to 1.27 (P = 0.003). Planner re-plan rates (ranging from 11%-42%) significantly correlate with their BHIs, r = 0.747 (P = 0.03). BHI for re-planned patients was higher than non-replan patients:1.11 ± 0.09 vs. 1.06 ± 0.16 (P = 0.017). The only significant robustness feature was the mean max dose change:3.1 ± 1.3% vs. 2.5 ± 1.4% (P = 0.038). Conclusion We have identified several features that correlate strongly with HN replans. A fine-tuned planning protocol is being developed to reduce the BHI for all HN plans. Our future work is to build a deep-learning model based on our current features and others such as patients’ clinical tumor information, planning image, plan conformity, etc., to predict the probability of a replan before treatment.

MRI-only treatment planning is highly desirable in the current proton radiation therapy workflow due to its appealing advantages such as bypassing MR-CT co-registration, avoiding x-ray CT exposure dose and reduced medical cost. However, MRI alone cannot provide stopping power ratio (SPR) information for dose calculations. Given that dual energy CT (DECT) can estimate SPR with higher accuracy than conventional single energy CT, we propose a deep learning-based method in this study to generate synthetic DECT (sDECT) from MRI to calculate SPR. Since the contrast difference between high-energy and low-energy CT (LECT) is important, and in order to accurately model this difference, we propose a novel label generative adversarial network-based model which can not only discriminate the realism of sDECT but also differentiate high-energy CT (HECT) and LECT from DECT. A cohort of 57 head-and-neck cancer patients with DECT and MRI pairs were used to validate the performance of the proposed framework. The results of sDECT and its derived SPR maps were compared with clinical DECT and the corresponding SPR, respectively. The mean absolute error for synthetic LECT and HECT were 79.98 ± 18.11 HU and 80.15 ± 16.27 HU, respectively. The corresponding SPR maps generated from sDECT showed a normalized mean absolute error as 5.22% ± 1.23%. By comparing with the traditional Cycle GANs, our proposed method significantly improves the accuracy of sDECT. The results indicate that on our dataset, the sDECT image form MRI is close to planning DECT, and thus shows promising potential for generating SPR maps for proton therapy.

This work aims to develop an automatic multi-organ segmentation approach based on deep learning for head - and- neck region on dual energy CT. The proposed method proposed a Mask scoring R-CNN where comprehensive features are first learnt from two independent pyramid networks and then are combined via deep attention strategy to highlight the informative ones extracted from both two channels of low and high energy CT. To perform multi-organ segmentation and solve the problem of misclassification, a mask scoring subnetwork was integrated into the Mask R-CNN framework to build the correlation between the class of potential detected organ’s ROI and the shape of that organ’s segmentation within that ROI. We trained and tested our model on DECT images from 66 head-and-neck cancer patients with manual contours of 19 organs as training target and ground truth. For large- and mid-sized organs such as brain and parotid, the proposed method successfully achieved average Dice similarity coefficient (DSC) larger than 0.8. For small-sized organs with very low contrast such as chiasm, cochlea, lens and optic nerves, the DSCs ranged between 0.5 and 0.8. With the propose method, using DECT images outperforms using SECT in all 19 organs with statistical significance in DSC (p

The delineation of target and organs-at-risk (OARs) is a necessary step in radiotherapy treatment planning. The accuracy of the target and OAR contours directly affects the quality of radiotherapy plans. Manual contouring of OARs is the routine procedure at present, which, however, is very time-consuming and requires significant expertise, especially for those head-and-neck (HN) cancer cases, where OARs densely distribute around tumors with complex anatomical structures. In this study, we propose a deep learning-based fully automated delineation method, namely, mask scoring regional convolutional neural network (MS-RCNN), to obtain consistent and reliable OAR contours in HN CT. In the model, MR images were synthesized by a cycle-consistent generative adversarial network given CT images. A backbone network was utilized to extract features from MRI and CT independently. The high bony-structure contrast in CT and soft-tissue contrast in MRI are complementary in nature. Through combining those complementary contrasts, the accuracy of OAR delineation is expected to be improved. Due to the ability of various object detection and classification, ResNet 101 was used as backbone in MS-RCNN. Quantities including Dice similarity coefficient (DSC), 95th percentile Hausdorff distance (HD95), mean surface distance (MSD), and residual mean square distance (RMS) were calculated to evaluate the performance of the proposed method. An average DSC, HD95, MSD and RMS of 0.78 (0.58 - 0.89), 4.88 mm (2.79 mm - 7.46 mm), 1.39 mm (0.69 mm - 1.99 mm), and 2.23 mm (1.30 mm - 3.23 mm), were respectively achieved across all of the 12 OARs by our proposed method. The proposed method is promising in facilitating auto-contouring for radiotherapy treatment planning.

This work presents a learning-based method to synthesize dual energy CT (DECT) images from conventional single energy CT (SECT). The proposed method uses a residual attention generative adversarial network. Residual blocks with attention gates were used to force the model to focus on the difference between DECT maps and SECT images. To evaluate the accuracy of the method, we retrospectively investigated 20 headand-neck cancer patients with both DECT and SECT scans available. The high and low energy CT images acquired from DECT acted as learning targets in the training process for SECT datasets and were evaluated against results from the proposed method using a leave-one-out cross-validation strategy. The synthesized DECT images showed an average mean absolute error around 30 Hounsfield Unit (HU) across the wholebody volume. These results strongly indicate the high accuracy of synthesized DECT image by our machinelearning-based method.

Purpose; For shoot-through proton treatments, like FLASH radiotherapy, there will be protons exiting the patient which can be used for proton portal imaging (PPI), revealing valuable information for the validation of tumor location in the beam's-eye-view at native gantry angles. However, PPI has poor inherent contrast and spatial resolution. To deal with this issue, we propose a deep-learning-based method to use kV digitally reconstructed radiographs (DRR) to improve PPI image quality. Method; We used a residual generative adversarial network (GAN) framework to learn the nonlinear mapping between PPIs and DRRs. Residual blocks were used to force the model to focus on the structural differences between DRR and PPI. To assess the accuracy of our method, we used 149 images for training and 30 images for testing. PPIs were acquired using a double-scattered proton beam. The DRRs acquired from CT acted as learning targets in the training process and were used to evaluate results from the proposed method using a six-fold cross-validation scheme. Results; Qualitatively, the corrected PPIs showed enhanced spatial resolution and captured fine details present in the DRRs that are missed in the PPIs. The quantitative results for corrected PPIs show average normalized mean error (NME), normalized mean absolute error (NMAE), peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) index of -0.1%, 0.3%, 39.14 dB, and 0.987, respectively. Conclusion; The results indicate the proposed method can generate high quality corrected PPIs and this work shows the potential to use a deep-learning model to make PPI available in proton radiotherapy. This will allow for beam's-eye-view (BEV) imaging with the particle used for treatment, leading to a valuable alternative to orthogonal x-rays or cone-beam CT for patient position verification.

PURPOSE: Human papilloma virus (HPV) association remains one of the most important predictors of clinical outcome in oropharyngeal squamous cell carcinoma (OPSCC). We aimed to determine whether the relationship between HPV status and overall survival was influenced by socioeconomic factors. MATERIALS AND METHODS: Using the National Cancer Database, we examined the relationship between socioeconomic status and overall survival, controlling for demographics and socioeconomic variables (age at diagnosis, race, sex, clinical stage, facility type, facility location, insurance status, median-income quartiles, percent of no high-school education quartiles, rural-urban dwelling, Charlson-Deyo score, primary site, and treatment type). RESULTS: HPV-positive patients with private insurance have improved overall survival compared with HPV-positive patients who are uninsured (hazard ratio [HR], 0.51, 95% CI, 0.41 to 0.63, P < .001). HPV-negative patients with private insurance have improved overall survival compared with HPV-negative patients who were uninsured (HR, 0.62, 95% CI, 0.53 to 0.73, P < .001). HPV-positive patients living in the south had improved overall survival compared with HPV-positive patients living in the west (HR, 0.83, 95% CI, 0.72 to 0.96, P = .013). As assessed through interaction, relationships between survival and insurance ( P = .004), rural-urban status ( P = .009), and facility location ( P = .021) statistically differed between HPV-positive and HPV-negative patients. CONCLUSION: HPV status impact on overall survival for patients with OPSCC is influenced by socioeconomic factors including insurance status and treatment facility. A deeper understanding of these interactions is needed to improve equity of care for patients with OPSCC.

Organ-at-risk (OAR) delineation is a key step for cone-beam CT (CBCT) based adaptive radiotherapy planning that can be a time-consuming, labor-intensive, and subject-to-variability process. We aim to develop a fully automated approach aided by synthetic MRI for rapid and accurate CBCT multi-organ contouring in head-and-neck (HN) cancer patients. MRI has superb soft-tissue contrasts, while CBCT offers bony-structure contrasts. Using the complementary information provided by MRI and CBCT is expected to enable accurate multi-organ segmentation in HN cancer patients. In our proposed method, MR images are firstly synthesized using a pre-trained cycle-consistent generative adversarial network given CBCT. The features of CBCT and synthetic MRI (sMRI) are then extracted using dual pyramid networks for final delineation of organs. CBCT images and their corresponding manual contours were used as pairs to train and test the proposed model. Quantitative metrics including Dice similarity coefficient (DSC), Hausdorff distance 95% (HD95), mean surface distance, and residual mean square distance (RMS) were used to evaluate the proposed method. The proposed method was evaluated on a cohort of 65 HN cancer patients. CBCT images were collected from those patients who received proton therapy. Overall, DSC values of 0.87 ± 0.03, 0.79 ± 0.10/0.79 ± 0.11, 0.89 ± 0.08/0.89 ± 0.07, 0.90 ± 0.08, 0.75 ± 0.06/0.77 ± 0.06, 0.86 ± 0.13, 0.66 ± 0.14, 0.78 ± 0.05/0.77 ± 0.04, 0.96 ± 0.04, 0.89 ± 0.04/0.89 ± 0.04, 0.83 ± 0.02, and 0.84 ± 0.07 for commonly used OARs for treatment planning including brain stem, left/right cochlea, left/right eye, larynx, left/right lens, mandible, optic chiasm, left/right optic nerve, oral cavity, left/right parotid, pharynx, and spinal cord, respectively, were achieved. This study provides a rapid and accurate OAR auto-delineation approach, which can be used for adaptive radiation therapy.

Organ delineation is crucial to diagnosis and therapy, while it is also labor-intensive and observer-dependent. Dual energy CT (DECT) provides additional image contrast than conventional single energy CT (SECT), which may facilitate automatic organ segmentation. This work aims to develop an automatic multi-organ segmentation approach using deep learning for head-and-neck region on DECT. We proposed a mask scoring regional convolutional neural network (R-CNN) where comprehensive features are firstly learnt from two independent pyramid networks and are then combined via deep attention strategy to highlight the informative ones extracted from both two channels of low and high energy CT. To perform multi-organ segmentation and avoid misclassification, a mask scoring subnetwork was integrated into the Mask R-CNN framework to build the correlation between the class of potential detected organ’s region-of-interest (ROI) and the shape of that organ’s segmentation within that ROI. We evaluated our model on DECT images from 127 head-and-neck cancer patients (66 training, 61 testing) with manual contours of 19 organs as training target and ground truth. For large- and mid-sized organs such as brain and parotid, the proposed method successfully achieved average Dice similarity coefficient (DSC) larger than 0.8. For small-sized organs with very low contrast such as chiasm, cochlea, lens and optic nerves, the DSCs ranged between around 0.5 and 0.8. With the proposed method, using DECT images outperforms using SECT in almost all 19 organs with statistical significance in DSC (p

Southern fin whales (Balaenoptera physalus) are known to migrate from the Antarctic to mid-latitudes during winter for breeding, but the occurrence and distribution of this species is not well known in the waters around New Zealand. The ‘doublet’ calls are one of the main calls emitted specifically by fin whales and repeated in a regular pattern, which make the acoustic detection of these calls relevant to detect the presence of fin whales. Using a signal processing algorithm to detect ‘doublet’ calls emitted by fin whales, we studied the occurrence, characteristics and seasonality of these ‘doublet’ calls in two regions around New Zealand; Cook Strait in 2016/2017 and offshore Gisborne in 2014/2015. The call detection procedure consisted of binarization of the spectrogram and a cross-correlation between the binarized spectrogram and a template of binarized ‘doublet’ calls spectrogram. A binarization threshold for the data spectrograms and a cross correlation threshold were then determined through multiple trials on a training dataset and a Receiver Operating Characteristics (ROC) curve. Fin whale ‘doublet’ calls occurred on the east side of New Zealand’s Cook Strait during austral winter, specifically in June 2017 and offshore Gisborne in June-August 2014. No ‘doublet’ calls were detected on the west side of Cook Strait. The ‘doublet’ calls’ Inter-Note Interval (INI) was similar in both datasets. However, there was a difference in alternation of the mean frequency for both HF components of ‘doublet’ calls in Cook Strait and Gisborne. As the song types were compared with those previously described in the literature, our findings suggest that some fin whales wintering in New Zealand waters may be part of a broader ‘acoustic population’ whose range extends west to southern Australia and south to Antarctica.

No-tillage has been used for mitigating wind erosion on the Southern High Plains US for decades. This study investigated the effects of tillage and nitrogen (N) fertilizer timing on cotton lint yield, fiber quality, and seed N content during a three-year transition from conventional tillage (CT) to a no-tillage system both with a wheat (Triticum aestivum) cover crop (NTW) and without a cover crop (NT). Lint yield was different between tillage systems within each year with the NTW system producing greater lint yield than the CT system in the second and third year of the transition period. The concentration of cotton seed N was not different within years, although it was decreased in the no N added control in the third year. Cotton fiber strength was increased in the NTW system compared to the CT system in the second year of the study. However, the CT system produced increased fiber strength compared to the other two systems in 2018 and is likely the result of late-season weather conditions. It was determined that implementing a NTW system may increase lint yield within the first few years and has no effect on most fiber quality parameters, especially in environmentally challenging conditions.

Proton radiation therapy has shown highly conformal distribution of prescribed dose in target with outstanding normal tissue sparing stemming from its steep dose gradient at the distal end of the beam. However, the uncertainty in everyday patient setup can lead to a discrepancy between treatment dose distribution and the planning dose distribution. Conebeam CT (CBCT) can be acquired daily before treatment to evaluate such inter-fraction setup error, while a further evaluation on resulted dose distribution error is currently not available. In this study, we developed a novel deep-learning based method to predict the relative stopping power maps from daily CBCT images to allow for online dose calculation in a step towards adaptive proton radiation therapy. 20 head-and-neck patients with CT and CBCT images are included for training and testing. Our CBCT RSP results were evaluated with RSP maps created from CT images as the ground truth. Among all the 20 patients, the averaged mean absolute error between CT-based and CBCT-based RSP was 0.04±0.02, the averaged mean error was -0.01±0.03 and the averaged normalized correlation coefficient was 0.97±0.01. The proposed method provides sufficiently accurate RSP map generation from CBCT images, possibly allowing for CBCT-guided adaptive treatment planning for proton radiation therapy.

Radiotherapy treatment is based on 3D anatomical models which require accurate organs-at-risk (OARs) delineation. In current clinical practice, the OARs are generally delineated from computed tomography (CT). Because of its superior soft-tissue contrast, magnetic resonance imaging (MRI) information can be introduced to improve the quality of these 3D OAR delineation and therefore the treatment plan itself. Manual segmentation of relevant tissue regions from MR image is a tedious and time-consuming procedure, which is also subject to inter- and intra-observer variation. In this work, we propose to use a 3D Faster R-CNN to automatically detect the locations of head and neck OARs, then utilize an attention U-Net to automatically segment the multiple OARs. We tested our method using 15 head and neck cancer patients. The mean Dice similarity coefficient (DSC) of esophagus, larynx, mandible, oral cavity, left parotid, right parotid, pharynx and spinal cord were 84%, 79%, 85%, 89%, 82%, 81%, 85% and 89%, which demonstrated the segmentation accuracy of the proposed U-Faster-RCNN method. This segmentation technique could be a useful tool to facilitate the routine clinical workflow of H&N radiotherapy.

OBJECTIVES/HYPOTHESIS For locally advanced oral squamous cell carcinoma (OSCC) treated by surgery and adjuvant therapy, consensus has yet to be reached on whether the optimal time to initiate surveillance positron emission tomography/computed tomography (PET/CT) scan is before or after adjuvant therapy. In this study, we characterize the utility of PET/CT scans obtained 3 months after adjuvant therapy. STUDY DESIGN PET/CT scans were obtained for 220 patients with stage III, IVA, or IVB OSCC who underwent resection followed by adjuvant radiotherapy or chemoradiotherapy. METHODS Using the Neck Imaging Reporting and Data System, PET/CT scans were dichotomized as suspicious (primary or neck category ≥3, or distant lesion present) versus nonsuspicious. We then computed differences in locoregional progression, distant progression, and overall survival; positive predictive value (PPV), negative predictive value (NPV), sensitivity, and specificity; and success rate of salvage. RESULTS Sixty-seven patients (30%) had suspicious PET/CT scans, which were significantly associated with local failure (hazard ratio [HR] 14.0, 95% confidence interval [CI] 7.3-26.6), distant failure (HR 18.4, 95% CI 9.6-35.3), and poorer overall survival (HR 9.5, 95% CI 5.0-17.9). Overall PPV, locoregional PPV, NPV, sensitivity, and specificity were 85%, 79%, 73%, 58%, and 92%, respectively. Among those with biopsy-confirmed progression, 37 patients (65%) underwent salvage therapy; four (11%) were without evidence of disease at last follow-up. CONCLUSIONS For locally advanced OSCC, PET/CT scan 3 months after adjuvant therapy is strongly predictive of disease recurrence and survival, demonstrating improved performance over postoperative imaging in previous studies. Following a suspicious post-adjuvant therapy PET/CT scan, cure of locoregional recurrence is possible but unlikely. LEVEL OF EVIDENCE 4 Laryngoscope, 2020.

BACKGROUND: With an expectation of excellent locoregional control, ongoing efforts to de-intensify therapy for patients with HPV associated squamous cell oropharyngeal cancer necessitate a better understanding of the metastatic risk for patients with this disease. The objective was to determine what factors affect the risk of metastases in patients with squamous cell cancers of the oropharynx METHODS: Under a shared use agreement, 547 RTOG 0129 and 0522 patients with non. metastatic oropharyngeal squamous cell cancers who had known p16 status and smoking status were analyzed to assess the association of clinical features with the development of distant metastases. Factors analyzed included p16 status, gender, T stage, N Stage, age, and smoking history. RESULTS: Multivariable analysis of 547 patients with a median follow-up of 4.6 years revealed that age ≥ 50 (HR=3.28, p=0.003), smoking > 0 pack-years (HR=3.09, p

Objectives The patterns of care for salivary gland adenoid cystic carcinomas (ACC) are unknown. We sought to assess predictors of receiving postoperative radiation and/or chemotherapy for patients with nonmetastatic, definitively resected ACC, as well as report unexpected nodal disease. Methods The National Cancer Data Base was queried for definitively resected nonmetastatic ACC from 2004 to 2014. Logistic regression, Kaplan-Meier, and Cox proportional-hazard models were utilized. Propensity-score matched analysis was employed to reduce confounding variables. Results A total of 3,136 patients met entry criteria: 2,252 (71.8%) received postoperative radiation, with 223 (7.4%) also receiving concurrent chemotherapy. Median follow-up was 4.87 years. In clinically lymph node negative (cN0) patients, 7.4% had pathologically positive lymph nodes (pN) + after elective neck dissection. Patients who lived closer to their treatment facility and had positive margins were more likely to receive postoperative radiation. Black patients and uninsured patients were less likely to receive radiation. Older age, male sex, advancing stage, and positive surgical margins were associated with worse overall survival (OS). With limited follow-up, receipt of radiation or chemotherapy was not associated with OS. Conclusion Postoperative radiation was frequently given for resected ACC, with a minority receiving chemotherapy. Black patients and uninsured patients were less likely to receive radiation. Postoperative radiation and/or chemotherapy had no association with OS but were given in greater frequency in more advanced disease, and our series is limited by short follow-up. The disparity findings for this rare disease need to be addressed in future studies. Level of evidence 2c Laryngoscope, 129:377-386, 2019.

PURPOSE/OBJECTIVE(S) Daily online treatment evaluation is essential for proton therapy, which is sensitive to daily anatomy and setup uncertainties. We have developed a program based on a commercial treatment planning system (TPS) to streamline the online evaluation process using pre-treatment cone-beam CT (CBCT) images. Herein, we evaluate the speed and accuracy of the tool based on clinical proton plans. MATERIALS/METHODS Data from 25 previously treated proton patients (7 HN, 11 lung, and 7 prostate) at our institution were evaluated. Corrected CBCT (cCBCT) images were generated using a research version of the TPS, which removes artifacts and calibrates HU for proton dose calculation. A quality assurance simulation CT (QACT) scanned on the same day as the CBCT is deformed to the cCBCT and used as a reference (dQACT). The cCBCT is deformed to the treatment planning CT (TPCT), and all contours on the initial TPCT were deformed to the cCBCT and then rigidly copied to the dQACT. Original clinical treatment plans were applied to both the cCBCT and dQACT, and the doses were calculated with the GPU-based Monte-Carlo dose calculation engine at 0.5% statistical uncertainty. The entire evaluation time (Eval_time) from importing CBCT image to completing final dose calculation for cCBCT was recorded. Plan parameters, including the number of beams (N_bm), proton spot number (N_sp), dose grid voxel numbers (N_voxel), were collected. Pearson correlation coefficient between the Eval_time and the N_bm, N_sp, and N_vosel were calculated. Dosimetric parameters were calculated for the cCBCT and compared to those calculated from the reference dQACT. Dosimetric parameters of interest included the following: for all, CTV D99, D95, and V100, and plan maximum dose (Dmax); for HN and for H&N and lung cases, spinal cord max dose (SC_Dmax). RESULTS Mean online Eval_time is 106.6 ± 24.9s for all patients, with HN as the fastest site 87.9 ± 17.5s for HN, 104.5 ± 15.9s for lung, 128.5 ± 28.0s for prostate, P < 0.01. The corresponding (N_bm, N_sp, N_voxel) were (3.9, 7781, 2.6E6) for HN, (3.3, 11080, 2.4E6) for lung, and (3.0, 10484, 3.8E6) for prostate. Eval_time was significantly correlated to N_sp (P = 0.02), but not to N_bm and N_voxel. The absolute differences for CTV D99, D95, V100, plan Dmax, HN P_Dmean, P_V30, C_Dmean, and SC_Dmax are 0.85 ± 0.60%, 0.39 ± 0.22%, 0.48 ± 0.41%, 0.46 ± 0.48%, 0.08 ± 0.05Gy, 0.05 ± 0.06%, 0.21 ± 0.20 Gy, and 0.57 ± 0.53Gy, respectively. CONCLUSION Online evaluation can be achieved within 2 minutes for most clinical proton cases (80% in this study) with the commercial TPS. The speed can be further increased with reduced OAR mapping, fine-tuned deformable registration, optimized and reduced spot number in the initial plans, and upgraded computer server. This proposed method may optimize the efficiency and quality of care for proton radiotherapy.

Purpose/Objective(s) Proton-based stereotactic body radiotherapy (SBRT) may provide a dosimetric benefit vs photon SBRT in certain cases, seeking to reduce toxicity risks or facilitate reirradiation, though data are limited. We assessed the feasibility and patient tolerance of proton SBRT for palliation and ablation. Materials/Methods From Sep. 2019 to Dec. 2020, 58 patients were simulated for proton SBRT to 68 lesions. Acute toxicities were prospectively recorded using CTCAE grading without attribution, and patient-reported outcomes were assessed prior to and at completion of treatment using the MD Anderson Symptom Inventory (MDASI) and EQ-5D5L visual analogue score (VAS). Results 52 of 58 patients (90%) received SBRT treatment. Treatment was not initiated in 6 patients due insurance denial (n = 1), change in treatment plan (n = 1), interval disease progression (n = 1), transition to hospice (n = 2), or death (n = 1). Fractionation varied by indication and disease site with a median of 5 fractions and a median fractional dose of 8 Gy. Proton range uncertainty (RU) was ± 3.5% in soft tissue and ± 5% in lung. For bone or immobile lesions, a target equivalent to a standard photon SBRT PTV was defined and optimized with RU. For mobile targets, 4D CT was used to define an ITV for robust optimization, typically with 5 mm positional uncertainty + RU, using a PTV Evaluation for assessment of comparable SBRT plan metrics. Among 27 patients with 4D CT assessment of target motion, 20 (74%) were treated with beam-gated breath hold, 4 (15%) with abdominal compression, and 3 (11%) free breathing. Cone beam CT (CBCT) was used for image guidance at each fraction. Average conformity index was 1.06 and average number of treatment fields per target was 4 (range of 2-8). The median treatment time per fraction was 41 minutes (range 18-171 mins). There was a significant difference in treatment time for patients requiring breath hold (67 vs 47 mins, P = 0.006). Five patients (10%) required adaptive replanning due to set up uncertainties (n = 3) or tumor growth (n = 2). 11 patients (21%) had concurrent systemic therapy. 21 patients (40%) had no observable acute toxicity associated with treatment. Maximum recorded toxicities, related or unrelated to SBRT treatment, were grade 1 in 25 patients (48%), grade 2 (fatigue, depression, anorexia, proctitis) in 5 patients (10%), and grade 3 (dysphagia and hoarseness) in 1 patient (2%). Comparing pretreatment to end of treatment timepoints, there was a significant improvement in the mean VAS (68 to 76, P = 0.027, n = 33), with no significant change in the mean MDASI symptom (1.8, 1.8) or interference (2.2, 2.3) scores. Conclusion Proton-based SBRT was feasible and well-tolerated with no decrement in patient reported outcomes and a mean 8 point improvement in VAS at the conclusion of SBRT. Further follow-up is necessary for tumor control and late effects analysis.

Purpose/Objective(s) Approximately 30-40% of patients irradiated for HNSCC will develop locoregional recurrence or second primary tumors (RSPT). Treatment of RSPT originating within a previously radiated field presents a technical challenge and typically portends worse outcomes than an initial course of RT. Anti-PD-1 therapy has shown promise in the treatment of advanced HNSCC. CA209-9KY aimed to investigate the potential benefit of nivo during and after IMRT based re-irradiation in RSPT. We report here the toxicity and QOL data for 44 enrolled patients. Materials/Methods Following IRB approval at 3 participating institutions, patients were enrolled if they had RSPT arising in a previously irradiated field (> 40 Gy) and met criteria for reirradiation classes I or II (Ward et al, IJROBP 2018); prior salvage resection was allowed regardless of HPV status provided patients had positive margins, extranodal extension, gross residual disease, N2/3 or T3/4 disease, multifocal perineural invasion, and/or lymphovascular space invasion. IMRT reirradiation with photons was delivered in 60-66 Gy in 30-33 daily fractions over 6-6.5 weeks with Nivo (240 mg) two weeks prior to and every 2 weeks during IMRT for a total of 5 doses then at 480 mg every 4 weeks for a total of 52 weeks. The Functional Assessment of Cancer Therapy (FACT-G) (Version 4) was assessed pre-therapy and weeks 6, 18, 30 and 52. The sum of FACT-G subscales (SUMQOL) score was also computed. Median and interquartile range (IQR) for each subscale and SUMQOL were recorded per cycle visit. FACT-HN was assessed at the same time intervals. Internal consistency reliability was measured using Cronbach's alpha and reported for each FACT sub-scale at each cycle Results As of 1/2021, a total of 44 patients have completed IMRT with nivolumab with a median follow up duration of 6.3 mos [95% CI (4.5-11.2)]. The most common toxicities of any grade-(CTCAE version 4.0) were fatigue (77%), dermatitis (54%), and dysphagia (52%). Grade 3 or 4 toxicities occurred in 47% of patients, with lymphopenia being the most common (11%), followed by diarrhea (7%). Serious Adverse Event (SAEs) occurred in 20% of patients with the most reported being dyspnea (4%). The median total sumQoL scores for FACT-HN per visit were 71 (61-80), 73 (67-77), 70 (67.8-76.2), 74 (66.2-79.7) and 71 (66-79), respectively. Similar observations were seen for FACT-G Scores for subscales with a median total FACT-G sumQoL scores per visit 54 (46.2-56.8), 55(53.5-59.2), 54 (50-57), 55.5(52-58.2), and 55 (52.5-57.5), respectively. FACT-G and FACT-H&N QOL scores remained consistent across all time points analyzed. The internal consistency and reliability for the FACT scores per sub-scale, per cycle and for all response items had a Cronbach's alpha of > 0.7. Conclusion Reirradiation with IMRT with concurrent and adjuvant nivo in patients with RSPT appears to be well tolerated with preservation of QOL measures during and following completion of therapy. Follow up for clinical efficacy measures of IMRT-nivo continues.

The LAP07 randomized trial calls into question the role of radiation therapy (RT) in the modern treatment of locally advanced pancreatic cancer (LAPC). However, advances in chemotherapy and RT limit application of the LAP07 results to current clinical practice. Here we utilize the National Cancer Database (NCDB) to evaluate the effects of RT in patients receiving chemotherapy for LAPC. Using the NCDB, patients with American Joint Committee on Cancer (AJCC) clinical stage T2–4, N0–1, M0 adenocarcinoma of the pancreas from 2004 to 2014 were analyzed. Patients were stratified into chemotherapy only (CT) and chemoradiation (CRT) cohorts. Patients undergoing definitive RT, defined as at least 20 fractions or ≥ 5 Gy per fraction [i.e., stereotactic body radiation therapy (SBRT)] were included in the CRT cohort. Propensity-score matching (PSM) and landmark analysis were used to address selection bias and lead-time bias, respectively. 13,004 patients met inclusion criteria, of whom 7034 (54%) received CT and 5970 (46%) received CRT. After PSM, 5215 patients remained in each cohort. The CRT cohort demonstrated better overall survival (OS) compared with CT alone, with median and 1-year OS of 12 versus 10 months, and 50% and 41%, respectively (p

Radiation (RT) dose to the central nervous system (CNS) has been implicated as a contributor to treatment-related fatigue in head and neck cancer (HNC) patients undergoing radiation therapy (RT). This study evaluates the association of RT dose to CNS structures with patient-reported (PRO) fatigue scores in a population of HNC patients.At pre-RT (baseline), 6th week of RT, and 1-month post-RT time points, Multidimensional Fatigue Inventory (MFI-20) scores were prospectively obtained from 124 patients undergoing definitive treatment for HNC. Medulla, pons, midbrain, total brainstem, cerebellum, posterior fossa, and pituitary dosimetry were evaluated using summary statistics and dose-volume histograms, and associations with MFI-20 scores were analyzed.Maximum dose (Dmax) to the brainstem and medulla was significantly associated with MFI-20 scores at 6th week of RT and 1-month post-RT time points, after controlling for baseline scores (p0.05). Each 1Gy increase in medulla Dmax resulted in an increase in total MFI-20 score over baseline of 0.30 (p=0.026), and 0.25 (p=0.037), at the 6th week of RT and 1-month post-RT, respectively. Each 1Gy increase in brainstem Dmax resulted in an increase in total MFI-20 score over baseline of 0.30 (p=0.027), and 0.25 (p=0.037) at the 6th week of RT, 1-month post-RT, respectively. Statistically significant associations were not found between dosimetry for the other CNS structures and MFI-20 scores.In this analysis of PRO fatigue scores from a population of patients undergoing definitive RT for HNC, maximum dose to the brainstem and medulla was associated with a significantly increased risk of acute patient fatigue.

Hydropower operations optimization subject to environmental constraints is limited by challenges associated with dimensionality and spatial and temporal resolution. The need for high-fidelity hydrodynamic and water quality models within optimization schemes is driven by improved computational capabilities, increased requirements to meet specific points of compliance with greater resolution, and the need to optimize operations of not just single reservoirs but systems of reservoirs. This study describes an important advancement for computing hourly power generation schemes for a hydropower reservoir using high-fidelity models, surrogate modeling techniques, and optimization methods. The predictive power of the high-fidelity hydrodynamic and water quality model CE-QUAL-W2 is successfully emulated by an artificial neural network, then integrated into a genetic algorithm optimization approach to maximize hydropower generation subject to constraints on dam operations and water quality. This methodology is applied to a multipurpose reservoir near Nashville, Tennessee, USA. The model successfully reproduced high-fidelity reservoir information while enabling 6.8 and 6.6 percent increases in hydropower production value relative to actual operations for dissolved oxygen (DO) limits of 5 and 6 mg/L, respectively, while witnessing an expected decrease in power generation at more restrictive DO constraints. Exploration of simultaneous temperature and DO constraints revealed capability to address multiple water quality constraints at specified locations. The reduced computational requirements of the new modeling approach demonstrated an ability to provide decision support for reservoir operations scheduling while maintaining high-fidelity hydrodynamic and water quality information as part of the optimization decision support routines.

Summary The coleopteran insect western corn rootworm (WCR, Diabrotica virgifera virgifera) is an economically important pest in North America and Europe. Transgenic corn plants producing Bacillus thuringiensis (Bt) insecticidal proteins have been useful against this devastating pest, but evolution of resistance has reduced their efficacy. Here, we report the discovery of a novel insecticidal protein, PIP‐47Aa, from an isolate of Pseudomonas mosselii. PIP‐47Aa sequence shows no shared motifs, domains or signatures with other known proteins. Recombinant PIP‐47Aa kills WCR, two other corn rootworm pests (Diabrotica barberi and Diabrotica undecimpunctata howardi) and two other beetle species (Diabrotica speciosa and Phyllotreta cruciferae), but it was not toxic to the spotted lady beetle (Coleomegilla maculata) or seven species of Lepidoptera and Hemiptera. Transgenic corn plants expressing PIP‐47Aa show significant protection from root damage by WCR. PIP‐47Aa kills a WCR strain resistant to mCry3A and does not share rootworm midgut binding sites with mCry3A or AfIP‐1A/1B from Alcaligenes that acts like Cry34Ab1/Cry35Ab1. Our results indicate that PIP‐47Aa is a novel insecticidal protein for controlling the corn rootworm pests.

BACKGROUND Octogenarians and nonagenarians with stage II/III rectal adenocarcinomas are underrepresented in the randomized trials that have established the standard-of-care therapy of preoperative chemoradiation followed by definitive resection (ie, chemoradiation and then surgery [CRT+S]). The purpose of this study was to evaluate the impact of therapies on overall survival (OS) for patients with stage II/III rectal cancers and determine predictors of therapy within the National Cancer Data Base (NCDB). METHODS In the NCDB, patients who were 80 years old or older and had clinical stage II/III rectal adenocarcinoma from 2004 to 2013 were queried. Kaplan-Meier analysis, log-rank testing, logistic regression, Cox proportional hazards regression, interaction effect testing, and propensity score–matched analysis were conducted. RESULTS The criteria were met by 2723 patients: 14.9% received no treatment, 29.7% had surgery alone, 5.0% underwent short-course radiation and then surgery (RT+S), 45.3% underwent CRT+S, and 5.1% underwent surgery and then chemoradiation (S+CRT). African American race and residence in a less educated county were associated with not receiving treatment. Male sex, older age, worsening comorbidities, and receiving no treatment or undergoing surgery alone were associated with worse OS. There was no statistical difference in OS between RT+S, S+CRT, and CRT+S. Interaction testing found that CRT+S improved OS independently of age, comorbidity status, sex, race, and tumor stage. In the propensity score–matched analysis, CRT+S was associated with improved OS in comparison with surgery alone. CONCLUSIONS A significant portion of octogenarians and nonagenarians with stage II/III rectal adenocarcinomas do not receive treatment. African American race and living in a less educated community are associated with not receiving therapy. This series suggests that CRT+S is a reasonable strategy for elderly patients who can tolerate therapy. Cancer 2017;123:4325-36. © 2017 American Cancer Society.

When confounding variables exist that inhibit the ability to diagnose brain death clinically in pediatric patients, ancillary tests may provide additional information for the practitioner in evaluating for the presence or absence of brain death. Multiple options exist but differ in availability, ease of administration, cost, safety profile, and reliability to accurately diagnose brain death. An important desirable quality of an ancillary test is eliminating false positives, which imply brain death when brain death is in fact not present. More commonly available ancillary studies include electroencephalograms, brain angiography through various modalities, brain stem auditory evoked potentials, and transcranial Doppler ultrasound. At this time, there is not an ancillary test with 100% reliability in diagnosing brain death that can replace the clinical brain death exam. Therefore, practitioners need to understand the strengths and limitations of the ancillary studies available at their hospital.

Fantasy sport participation represents an increasingly popular consumer experience among the contemporary sport consumption alternatives. Previous work on fantasy sports draws attention to both its positive and negative effects on traditional sport consumption. This study investigates fantasy football participants’ perspectives, meanings, and experiences regarding their fantasy football and NFL consumption behavior. Employing a grounded theory methodology, the study draws on literatures spanning from sport consumption and fantasy sports to consumer co-creation and intrapersonal conflict, and combines them with data collection and analysis. The outcome is a new organizing framework that illustrates why there is conflict between fantasy and favorite team fandom and how fantasy sport participants cope with this conflict. First, the study illustrates that this conflict stems from the non-traditional co-creation opportunities inherent in the empowering fantasy sports experience, which leads to a psychological connection to the fantasy team and players through the feeling of self-achievement. Second, the study identifies various coping strategies that sport consumers employ to manage conflicts with player selection (i.e., safe selection, convergent selection, divergent selection, and impartial selection strategies) and rooting interests (i.e., balanced interest, principal interest-shift, temporal interest-shift, and benefit-seeking interest-shift strategies).

Purpose Because the manual contouring process is labor-intensive and time-consuming, segmentation of organs-at-risk (OARs) is a weak link in radiotherapy treatment planning process. Our goal was to develop a synthetic MR (sMR)-aided dual pyramid network (DPN) for rapid and accurate head and neck multi-organ segmentation in order to expedite the treatment planning process. Methods Forty-five patients' CT, MR, and manual contours pairs were included as our training dataset. Nineteen OARs were target organs to be segmented. The proposed sMR-aided DPN method featured a deep attention strategy to effectively segment multiple organs. The performance of sMR-aided DPN method was evaluated using five metrics, including Dice similarity coefficient (DSC), Hausdorff distance 95% (HD95), mean surface distance (MSD), residual mean square distance (RMSD), and volume difference. Our method was further validated using the 2015 head and neck challenge data. Results The contours generated by the proposed method closely resemble the ground truth manual contours, as evidenced by encouraging quantitative results in terms of DSC using the 2015 head and neck challenge data. Mean DSC values of 0.91 ± 0.02, 0.73 ± 0.11, 0.96 ± 0.01, 0.78 ± 0.09/0.78 ± 0.11, 0.88 ± 0.04/0.88 ± 0.06 and 0.86 ± 0.08/0.85 ± 0.1 were achieved for brain stem, chiasm, mandible, left/right optic nerve, left/right parotid, and left/right submandibular, respectively. Conclusions We demonstrated the feasibility of sMR-aided DPN for head and neck multi-organ delineation on CT images. Our method has shown superiority over the other methods on the 2015 head and neck challenge data results. The proposed method could significantly expedite the treatment planning process by rapidly segmenting multiple OARs.

Purpose: Dual-energy CT (DECT) has been shown to derive stopping power ratio (SPR) map with higher accuracy than conventional single energy CT (SECT) by obtaining the energy dependence of photon interactions. However, DECT is not as widely implemented as SECT in proton radiation therapy simulation. This work presents a learning-based method to synthetize DECT images from SECT for proton radiation therapy. Methods: The proposed method uses a residual attention generative adversarial network. Residual blocks with attention gates were used to force the model focus on the difference between DECT maps and SECT images. To evaluate the accuracy of the method, we retrospectively investigated 20 head-and-neck cancer patients with both DECT and SECT scans available. The high and low energy CT images acquired from DECT acted as learning targets in the training process for SECT datasets and were evaluated against results from the proposed method using a leave-one-out cross-validation strategy. To evaluate our method in the context of a practical application, we generated SPR maps from sDECT using physics-based dual-energy stoichiometric method and compared the maps to those generated from DECT. Results: The synthesized DECT images showed an average mean absolute error around 30 Hounsfield Unit (HU) across the whole-body volume. The corresponding SPR maps generated from synthetic DECT showed an average normalized mean square error of about 1% with reduced noise level and artifacts than those from original DECT. Conclusions: The accuracy of the synthesized DECT image by our machine-learning-based method was evaluated on head and neck patient, and potential feasibility for proton treatment planning and dose calculation was shown by generating SPR map using the synthesized DECT., Comment: arXiv admin note: text overlap with arXiv:2003.09058

Purpose Treatment planning systems (TPSs) from different vendors can involve different implementations of Monte Carlo dose calculation (MCDC) algorithms for pencil beam scanning (PBS) proton therapy. There are currently no guidelines for validating non-water materials in TPSs. Furthermore, PBS-specific parameters can vary by 1-2 orders of magnitude among different treatment delivery systems (TDSs). This paper proposes a standardized framework on the use of commissioning data and steps to validate TDS-specific parameters and TPS-specific heterogeneity modeling to potentially reduce these uncertainties. Methods A standardized commissioning framework was developed to commission the MCDC algorithms of RayStation 8A and Eclipse AcurosPT v13.7.20 using water and non-water materials. Measurements included Bragg peak depth-dose and lateral spot profiles and scanning field outputs for Varian ProBeam. The phase-space parameters were obtained from in-air measurements and the number of protons per MU from output measurements of 10 × 10 cm2 square fields at a 2 cm depth. Spot profiles and various PBS field measurements at additional depths were used to validate TPS. Human tissues in TPS, Gammex phantom materials, and artificial materials were used for the TPS benchmark and validation. Results The maximum differences of phase parameters, spot sigma, and divergence between MCDC algorithms are below 4.5 µm and 0.26 mrad in air, respectively. Comparing TPS to measurements at depths, both MC algorithms predict the spot sigma within 0.5 mm uncertainty intervals, the resolution of the measurement device. Beam Configuration in AcurosPT is found to underestimate number of protons per MU by ~2.5% and requires user adjustment to match measured data, while RayStation is within 1% of measurements using Auto model. A solid water phantom was used to validate the range accuracy of non-water materials within 1% in AcurosPT. Conclusions The proposed standardized commissioning framework can detect potential issues during PBS TPS MCDC commissioning processes, and potentially can shorten commissioning time and improve dosimetric accuracies. Secondary MCDC can be used to identify the root sources of disagreement between primary MCDC and measurement.

The purpose of this work is to validate the application of a deep learning-based method for pelvic synthetic CT (sCT) generation that can be used for prostate proton beam therapy treatment planning. We propose to integrate dense block minimization into 3D cycle-consistent generative adversarial networks (cycleGAN) framework to effectively learn the nonlinear mapping between MRI and CT pairs. A cohort of 17 patients with co-registered CT and MR pairs were used to test the deep learning-based sCT generation method by leave-one-out cross-validation. Image quality between the sCT and CT images, gamma analysis passing rate, dose-volume metrics, distal range displacement, and the individual pencil beam Bragg peak shift between sCT- and CT-based proton plans were evaluated. The average mean absolute error (MAE) was 51.32 ± 16.91 HU. The relative differences of the statistics of the PTV dose-volume histogram (DVH) metrics in between sCT and CT were generally less than 1%. Mean values of dose difference, absolute dose difference (in percent of the prescribed dose) were -0.07% ± 0.07% and 0.23% ± 0.08%. Mean gamma analysis pass rate of 1 mm/1%, 2 mm/2%, 3 mm/3% criteria with 10% dose threshold were 92.39% ± 5.97%, 97.95% ± 2.95% and 98.97% ± 1.62% respectively. The median, mean and standard deviation of absolute maximum range differences were 0.09 cm and 0.23 ± 0.25 cm. The median and mean Bragg peak shifts among the 17 patients were 0.09 cm and 0.18 ± 0.07 cm. The image similarity, dosimetric and distal range agreement between sCT and original CT suggests the feasibility of further development of an MRI-only workflow for prostate proton radiotherapy.

Background Perioperative chemotherapy (POC) is one standard approach for the treatment of resectable cancers of the stomach and gastroesophageal junction (GEJ), whereas there has been growing interest in preoperative therapies. The objective of the current study was to compare survival between patients treated with preoperative chemoradiotherapy and adjuvant chemotherapy (PCRT) with those receiving POC using a large database. Methods The National Cancer Data Base was queried for patients diagnosed between 2004 and 2013 with American Joint Committee on Cancer clinical group stage IB to stage IIIC (excluding T2N0 disease) adenocarcinoma of the stomach or GEJ. Patients treated with definitive surgery and POC with or without preoperative radiotherapy of 41 to 54 Gy were included. Overall survival (OS) was defined from the date of definitive surgery and estimated using the Kaplan-Meier method. A total of 14 patient and treatment variables were used for propensity score matching (PSM). Results A total of 1048 patients were analyzed: 53.2% received POC and 46.8% received PCRT. The primary tumor site was the GEJ in 69.1% of patients and stomach in 30.9% of patients. The median age of the patients was 60 years, and the median follow-up was 25.8 months. The use of PCRT was associated with a greater pathologic complete response rate of 13.1% versus 8.2% (P = .01). POC was associated with a decreased risk of death in unmatched groups (hazard ratio [HR], 0.83; P = .043). Using PSM cohorts, POC decreased the risk of death with a median OS of 45.1 months versus 31.4 months (HR, 0.70; P = .016). The 2-year OS rate was 72.9% versus 62.5% and the 5-year OS rate was 40.7% versus 33.1% for POC versus PCRT, respectively. Survival favored POC in PSM gastric (HR, 0.41; P = .07) and GEJ (HR, 0.77; P = .08) patient subgroups. Conclusions The addition of preoperative radiotherapy to POC appears to be associated with an increased risk of death in patients with resectable gastric and GEJ cancers.

A novel Bacillus thuringiensis Cry protein, Cry8Hb, active against Diabrotica virgifera virgifera (Western corn rootworm, WCRW) was discovered. Unexpectedly, the anti-rootworm activity of the Cry8Hb toxin was enhanced significantly by fusing Escherichia coli maltose binding protein (MBP) to this Cry toxin. While the exact mechanism of the activity enhancement remains indefinite, it is probable that the enhancement is a result of increased solubility of the MBP-Cry8Hb fusion in the rootworm midgut. This hypothesis was examined using a synthetic Cry3 protein called IP3-1, which was not soluble at a neutral pH like Cry8Hb and marginally active to WCRW. When IP3-1 was fused to MBP, its anti-WCRW activity was enhanced 13-fold. To further test the hypothesis, DNA shuffling was performed on IP3-1 to increase the solubility without MBP. Screening of shuffled libraries found six new IP3 variants showing very high anti-WCRW activity without MBP. Sequence and 3D structure analysis of those highly active, shuffled IP3 variants revealed several charge-altering mutations such as Lys to Glu on the putative MBP-attaching side of the IP3 molecule. It is likely that those mutations make the protein acidic to substitute the functions of MBP including enhancing the solubility of IP3 at a neutral pH.

Background: Hispanic patients with esophageal cancer (EC) have racially disparate survival outcomes compared with white patients. Objectives:We explored the impact on survival of racial differences in socioeconomic factors, tumor characteristics, and rates of surgical utilization in patients with EC. Method:Using the SEER (Surveillance, Epidemiology, and End Results) registry, we identified 22,531 cases of EC in Hispanic and white patients between the ages of 18 and 65 years in 2003–2014. Of these, 6,250 cases had locoregional EC. Patients were categorized according to age, gender, education, tumor grade, histology, primary tumor site, and surgical status. Postdiagnosis survival was examined over time and compared by race and stratified by surgical status. Results: Compared with whites, Hispanics with EC had significantly higher unadjusted mortality (hazard ratio [HR] 1.11; 95% confidence interval [CI] 1.06–1.17; p < 0.001) as did Hispanics with locoregional EC (HR 1.15; 95% CI 1.03–1.29; p = 0.01). In the multivariate analysis, several socioeconomic and tumor factors were found to be independently associated with survival by race, including county of residence income and prevalence of smoking, tumor grade, stage, and primary site, and surgical utilization. After adjusting for demographic and tumor characteristics, surgical utilization in patients with locoregional EC had a significant interaction with race on overall mortality (p = 0.01). Hispanics with locoregional EC were significantly less likely to receive surgery than whites (46 vs. 60%; p < 0.001) and not receiving surgery was associated with a significantly lower overall survival (HR 2.84; 95% CI 2.65–3.04; p < 0.001). Conclusions: A lower rate of surgery among Hispanics with potentially resectable esophageal cancer was associated with a decreased survival rate when compared to whites, even when adjusting for relevant socioeconomic and tumor factors. These data support the need to better address patient barriers to surgical treatment and the systemic biases present in medical care.

Pygmy sperm whales (Kogia breviceps) and dwarf sperm whales (Kogia sima) are deep diving cetaceans that commonly strand along the coast of the southeast US, but that are difficult to study visually at sea because of their elusive behavior. Conventional visual surveys are thought to significantly underestimate the presence of Kogia and they have proven difficult to approach for tracking and tagging. An approach is presented for density estimation of signals presumed to be from Kogia spp. based on passive acoustic monitoring data collected at sites in the Gulf of Mexico (GOM) from the period following the Deepwater Horizon oil spill (2010-2013). Both species of Kogia are known to inhabit the GOM, although it is not possible to acoustically separate the two based on available knowledge of their echolocation clicks. An increasing interannual density trend is suggested for animals near the primary zone of impact of the oil spill, and to the southeast of the spill. Densities were estimated based on both counting individual echolocation clicks and counting the presence of groups of animals during one-min time windows. Densities derived from acoustic monitoring at three sites are all substantially higher (4-16 animals/1000 km 2 ) than those that have been derived for Kogia from line transect visual surveys in the same region (0.5 animals/1000 km 2 ). The most likely explanation for the observed discrepancy is that the visual surveys are underestimating Kogia spp. density, due to the assumption of perfect detectability on the survey trackline. We present an alternative approach for density estimation, one that derives echolocation and behavioral parameters based on comparison of modeled and observed sound received levels at sites of varying depth.

With limited high-level evidence, we carried out a comparative effectiveness study for the effect of proton beam therapy (PBT) on overall survival compared to external-beam radiotherapy (EBRT) and brachytherapy (BT) among patients with localized prostate cancer using a national database. PBT was associated with a significant overall survival benefit compared to EBRT and had a similar performance as BT. Background: There are few comparative outcomes data regarding the therapeutic delivery of proton beam therapy (PBT) versus the more widely used photon-based external-beam radiation (EBRT) and brachytherapy (BT). We evaluated the impact of PBT on overall survival (OS) compared to EBRT or BT on patients with localized prostate cancer. Patients and Methods: The National Cancer Data Base (NCDB) was queried for 2004–2015. Men with clinical stage T1–3, N0, M0 prostate cancer treated with radiation, without surgery or chemotherapy, were included. OS, the primary clinical outcome, was fit by Cox proportional hazard model. Propensity score matching was implemented for covariate balance. Results: There were 276,880 eligible patients with a median follow-up of 80.9 months. A total of 4900 (1.8%) received PBT, while 158,111 (57.1%) received EBRT and 113,869 (41.1%) BT. Compared to EBRT and BT, PBT patients were younger and were less likely to be in the high-risk group. On multivariable analysis, compared to PBT, men had worse OS after EBRT (adjusted hazard ratio [HR] = 1.72; 95% confidence interval [CI], 1.51–1.96) or BT (adjusted HR = 1.38; 95% CI, 1.21–1.58). After propensity score matching, the OS benefit of PBT remained significant compared to EBRT (HR = 1.64; 95% CI, 1.32–2.04) but not BT (adjusted HR = 1.18; 95% CI, 0.93–1.48). The improvement in OS with PBT was most prominent in men ≤ 65 years old with low-risk disease compared to other subgroups (interaction P < .001). Conclusion: In this national data set, PBT was associated with a significant OS benefit compared to EBRT, and with outcomes similar to BT. These results remain to be validated by ongoing prospective trials.

Soil microbes yield insecticidal peptide The microbial peptide BT, derived from the bacterium Bacillus thuringiensis , is widely used to protect crops from insect pests. Schellenberger et al. identified another insecticidal peptide from a different soil-dwelling bacterium, Pseudomonas chlororaphis (see the Perspective by Tabashnik). Corn plants expressing the Pseudomonas peptide were protected from attack by western corn rootworm. Rootworms that were resistant to BT were susceptible to the Pseudomonas peptide. Addition of another insecticidal peptide diversifies the arsenal against insect pests, which may slow down the development of resistance. Science , this issue p. 634 ; see also p. 552

Background The unique radiobiological properties of protons have been understood for many years. In addition, many of the clinical benefits of radiotherapy were first noted in tumors involving the skull base. More public attention has been given to proton beam therapy due to the increasing number of centers now in operation or in the planning stages for offering this treatment option. Methods We reviewed the physical properties of protons and the clinical studies performed to justify their use in the management of skull-base tumors and determine the benefits of proton beam therapy. Results Published reports suggest a benefit to proton beam therapy for use in tumors of the skull base, including craniopharyngiomas, chordomas, skull-base sarcomas, and unresectable meningiomas. Conclusions Use of proton beam therapy may be beneficial in select patients. Surgical and medical oncologists should have a general understanding of such cases to facilitate their appropriate referral.

PURPOSE: We sought to quantify the optimum number of beams by using a midline sagittal arrangement for midline brain tumors when considering the competing demands of a high degree of target conformation and maximizing reduction of nontarget brain dose. The volume of nontarget brain tissue receiving between 5 and 20 Gy (V5-V20) was selected to measure “low-dose bath” to normal brain. MATERIALS AND METHODS: An exploratory model was developed with 6 midline brain targets created by using spheres of 1-, 3-, and 5-cm diameters located in superficial and deep locations. For each, five 3-dimensional proton treatment plans with uniform beam scanning were generated by using 1 to 5 fields. Dose-volume histograms were analyzed to calculate conformation number and V5-V20. A benefit/cost analysis was performed to determine the marginal gain in conformation number and the marginal cost of V5-V20 for the addition of each field and hypothesize the optimum number of treatment fields. We tested our hypothesis by re-planning 10 actual patient tumors with the same technique to compare the averages of these 50 plans to our model. RESULTS: Our model and validation cohort demonstrated the largest marginal benefit in target conformation and the lowest marginal cost in normal brain V5-V20 with the addition of a second proton field. The addition of a third field resulted in a relative marginal benefit in target conformation of just 3.9% but a relative marginal cost in V5-V20 of 78.7%. Normal brain absolute V5-V20 increased in a nearly linear fashion with each additional field. CONCLUSIONS: When treating midline brain lesions with 3-dimensional proton therapy in an array of midline sagittal beams, our model suggests the most appropriate number of fields is 2. There was little marginal benefit in target conformation and increasing cost of normal brain dose when increasing the number of fields beyond this.

Due to the continually increasing popularity of metal powder-based additive manufacturing as a production process in recent years, there has been growing research into improving the surface quality of the parts manufactured in this way. Laser polishing offers great potential as a finishing technique due to its flexibility and suitability for automation. However, the complexity of components that can be produced with additive manufacturing processes presents challenges in developing practical and flexible arrangements for implementing a laser polishing process. In this paper, we offer methods to manage height variations of parts using weakly focused beams, process components that are (roughly) cylindrical using rotational stages, and polishing of internal surfaces using simple optics. As an example application, we present finishing of additively manufactured cobalt chrome dental implants to a surface roughness of 0.45 μm in only 60 s using a low-cost fiber delivered diode array laser.