Evaluating automatically generated normal tissue contours for safe use in head and neck and cervical cancer treatment planning.

PURPOSE: Volumetric-modulated arc therapy (VMAT) is a widely accepted treatment method for head and neck (HN) and cervical cancers; however, creating contours and plan optimization for VMAT plans is a time-consuming process. Our group has created an automated treatment planning tool, the Radiation Planning Assistant (RPA), that uses deep learning models to generate organs at risk (OARs), planning structures and automates plan optimization. This study quantitatively evaluates the quality of contours generated by the RPA tool. METHODS: For patients with HN (54) and cervical (39) cancers, we retrospectively generated autoplans using the RPA. Autoplans were generated using deep-learning and RapidPlan models developed in-house. The autoplans were, then, applied to the original, physician-drawn contours, which were used as a ground truth (GT) to compare with the autocontours (RPA). Using a "two one-sided tests" (TOST) procedure, we evaluated whether the autocontour normal tissue dose was equivalent to that of the ground truth by a margin, δ, that we determined based on clinical judgement. We also calculated the number of plans that met established clinically accepted dosimetric criteria. RESULTS: For HN plans, 91.8% and 91.7% of structures met dosimetric criteria for automatic and manual contours, respectively; for cervical plans, 95.6% and 95.7% of structures met dosimetric criteria for automatic and manual contours, respectively. Autocontours were equivalent to the ground truth for 71% and 75% of common DVH metrics for the HN and cervix, respectively. CONCLUSIONS: This study shows that dosimetrically equivalent normal tissue contours can be created for HN and cervical cancers using deep learning techniques. In general, differences between the contours did not affect the passing or failing of clinical dose tolerances.

Head and Neck Virtual Coach: A Randomized Control Trial of Mobile Health as an Adjunct to Swallowing Therapy During Head and Neck Radiation.

Dysphagia is a common consequence of head and neck radiation and may be mitigated by performance of swallowing exercises during radiation treatment. Given historically poor adherence to such exercise protocols, we created a mobile health application, HNC Virtual Coach as an adjunct to standard clinical care. This randomized control trial investigated the impact of HNC Virtual Coach on adherence as well as swallowing outcomes by comparing those using the mobile app to those receiving only standard clinical care and paper logs. Both treatment groups were provided with the same exercise protocol as well as the same baseline educational information. Outcome measures included adherence rates, physiologic measures obtained during a Modified Barium Swallow Study (PAS, MBS-ImP, DIGEST), patient-reported outcomes (MDADI), diet levels (FOIS, PSS-HN), and quality of information received (INFO-25). Patients using the HNC Virtual Coach tended to have better adherence to treatment recommendations during radiation therapy. Increased adherence was associated with better patient-reported quality of life, but not physiologic function 2-3 months following completion of radiation. Results suggest that a mobile health application may provide benefit for some patients undergoing head and neck radiation.

Identifying the optimal deep learning architecture and parameters for automatic beam aperture definition in 3D radiotherapy.

PURPOSE: Two-dimensional radiotherapy is often used to treat cervical cancer in low- and middle-income countries, but treatment planning can be challenging and time-consuming. Neural networks offer the potential to greatly decrease planning time through automation, but the impact of the wide range of hyperparameters to be set during training on model accuracy has not been exhaustively investigated. In the current study, we evaluated the effect of several convolutional neural network architectures and hyperparameters on 2D radiotherapy treatment field delineation. METHODS: Six commonly used deep learning architectures were trained to delineate four-field box apertures on digitally reconstructed radiographs for cervical cancer radiotherapy. A comprehensive search of optimal hyperparameters for all models was conducted by varying the initial learning rate, image normalization methods, and (when appropriate) convolutional kernel size, the number of learnable parameters via network depth and the number of feature maps per convolution, and nonlinear activation functions. This yielded over 1700 unique models, which were all trained until performance converged and then tested on a separate dataset. RESULTS: Of all hyperparameters, the choice of initial learning rate was most consistently significant for improved performance on the test set, with all top-performing models using learning rates of 0.0001. The optimal image normalization was not consistent across architectures. High overlap (mean Dice similarity coefficient = 0.98) and surface distance agreement (mean surface distance < 2 mm) were achieved between the treatment field apertures for all architectures using the identified best hyperparameters. Overlap Dice similarity coefficient (DSC) and distance metrics (mean surface distance and Hausdorff distance) indicated that DeepLabv3+ and D-LinkNet architectures were least sensitive to initial hyperparameter selection. CONCLUSION: DeepLabv3+ and D-LinkNet are most robust to initial hyperparameter selection. Learning rate, nonlinear activation function, and kernel size are also important hyperparameters for improving performance.

Circulating tumor DNA in head and neck cancer: Early successes and future promise.

LAY SUMMARY: The genetic components (DNA) of human papillomavirus-related throat cancer (in the oropharynx) might be measured after surgery to help to predict whether treatment has been successful.

Assessing the practicality of using a single knowledge-based planning model for multiple linac vendors.

PURPOSE: Knowledge-based planning (KBP) has been shown to be an effective tool in quality control for intensity-modulated radiation therapy treatment planning and generating high-quality plans. Previous studies have evaluated its ability to create consistent plans across institutions and between planners within the same institution as well as its use as teaching tool for inexperienced planners. This study evaluates whether planning quality is consistent when using a KBP model to plan across different treatment machines. MATERIALS AND METHODS: This study used a RapidPlan model (Varian Medical Systems) provided by the vendor, to which we added additional planning objectives, maximum dose limits, and planning structures, such that a clinically acceptable plan is achieved in a single optimization. This model was used to generate and optimize volumetric-modulated arc therapy plans for a cohort of 50 patients treated for head-neck cancer. Plans were generated using the following treatment machines: Varian 2100, Elekta Versa HD, and Varian Halcyon. A noninferiority testing methodology was used to evaluate the hypothesis that normal and target metrics in our autoplans were no worse than a set of clinically-acceptable baseline plans by a margin of 1.8 Gy or 3% dose-volume. The quality of these plans were also compared through the use of common clinical dose-volume histogram criteria. RESULTS: The Versa HD met our noninferiority criteria for 23 of 34 normal and target metrics; while the Halcyon and Varian 2100 machines met our criteria for 24 of 34 and 26 of 34 metrics, respectively. The experimental plans tended to have less volume coverage for prescription dose planning target volume and larger hotspot volumes. However, comparable plans were generated across different treatment machines. CONCLUSIONS: These results support the use of a head-neck RapidPlan models in centralized planning workflows that support clinics with different linac models/vendors, although some fine-tuning for targets may be necessary.

Knowledge-based planning for the radiation therapy treatment plan quality assurance for patients with head and neck cancer.

This study aimed to investigate the feasibility of using a knowledge-based planning technique to detect poor quality VMAT plans for patients with head and neck cancer. We created two dose-volume histogram (DVH) prediction models using a commercial knowledge-based planning system (RapidPlan, Varian Medical Systems, Palo Alto, CA) from plans generated by manual planning (MP) and automated planning (AP) approaches. DVHs were predicted for evaluation cohort 1 (EC1) of 25 patients and compared with achieved DVHs of MP and AP plans to evaluate prediction accuracy. Additionally, we predicted DVHs for evaluation cohort 2 (EC2) of 25 patients for which we intentionally generated plans with suboptimal normal tissue sparing while satisfying dose-volume limits of standard practice. Three radiation oncologists reviewed these plans without seeing the DVH predictions. We found that predicted DVH ranges (upper-lower predictions) were consistently wider for the MP model than for the AP model for all normal structures. The average ranges of mean dose predictions among all structures was 9.7 Gy (MP model) and 3.4 Gy (AP model) for EC1 patients. RapidPlan models identified 7 MP plans as outliers according to mean dose or D1% for at least one structure, while none of AP plans were flagged. For EC2 patients, 22 suboptimal plans were identified by prediction. While re-generated AP plans validated that these suboptimal plans could be improved, 40 out of 45 structures with predicted poor sparing were also identified by oncologist reviews as requiring additional planning to improve sparing in the clinical setting. Our study shows that knowledge-based DVH prediction models can be sufficiently accurate for plan quality assurance purposes. A prediction model built by a small cohort automatically-generated plans was effective in detecting suboptimal plans. Such tools have potential to assist the plan quality assurance workflow for individual patients in the clinic.

Automatic contouring QA method using a deep learning-based autocontouring system.

PURPOSE: To determine the most accurate similarity metric when using an independent system to verify automatically generated contours. METHODS: A reference autocontouring system (primary system to create clinical contours) and a verification autocontouring system (secondary system to test the primary contours) were used to generate a pair of 6 female pelvic structures (UteroCervix [uterus + cervix], CTVn [nodal clinical target volume (CTV)], PAN [para-aortic lymph nodes], bladder, rectum, and kidneys) on 49 CT scans from our institution and 38 from other institutions. Additionally, clinically acceptable and unacceptable contours were manually generated using the 49 internal CT scans. Eleven similarity metrics (volumetric Dice similarity coefficient (DSC), Hausdorff distance, 95% Hausdorff distance, mean surface distance, and surface DSC with tolerances from 1 to 10 mm) were calculated between the reference and the verification autocontours, and between the manually generated and the verification autocontours. A support vector machine (SVM) was used to determine the threshold that separates clinically acceptable and unacceptable contours for each structure. The 11 metrics were investigated individually and in certain combinations. Linear, radial basis function, sigmoid, and polynomial kernels were tested using the combinations of metrics as inputs for the SVM. RESULTS: The highest contouring error detection accuracies were 0.91 for the UteroCervix, 0.90 for the CTVn, 0.89 for the PAN, 0.92 for the bladder, 0.95 for the rectum, and 0.97 for the kidneys and were achieved using surface DSCs with a thickness of 1, 2, or 3 mm. The linear kernel was the most accurate and consistent when a combination of metrics was used as an input for the SVM. However, the best model accuracy from the combinations of metrics was not better than the best model accuracy from a surface DSC as an input. CONCLUSIONS: We distinguished clinically acceptable contours from clinically unacceptable contours with an accuracy higher than 0.9 for the targets and critical structures in patients with cervical cancer; the most accurate similarity metric was surface DSC with a thickness of 1, 2, or 3 mm.

The Emergence of Artificial Intelligence within Radiation Oncology Treatment Planning.

BACKGROUND: The future of artificial intelligence (AI) heralds unprecedented change for the field of radiation oncology. Commercial vendors and academic institutions have created AI tools for radiation oncology, but such tools have not yet been widely adopted into clinical practice. In addition, numerous discussions have prompted careful thoughts about AI's impact upon the future landscape of radiation oncology: How can we preserve innovation, creativity, and patient safety? When will AI-based tools be widely adopted into the clinic? Will the need for clinical staff be reduced? How will these devices and tools be developed and regulated? SUMMARY: In this work, we examine how deep learning, a rapidly emerging subset of AI, fits into the broader historical context of advancements made in radiation oncology and medical physics. In addition, we examine a representative set of deep learning-based tools that are being made available for use in external beam radiotherapy treatment planning and how these deep learning-based tools and other AI-based tools will impact members of the radiation treatment planning team. Key Messages: Compared to past transformative innovations explored in this article, such as the Monte Carlo method or intensity-modulated radiotherapy, the development and adoption of deep learning-based tools is occurring at faster rates and promises to transform practices of the radiation treatment planning team. However, accessibility to these tools will be determined by each clinic's access to the internet, web-based solutions, or high-performance computing hardware. As seen by the trends exhibited by many technologies, high dependence on new technology can result in harm should the product fail in an unexpected manner, be misused by the operator, or if the mitigation to an expected failure is not adequate. Thus, the need for developers and researchers to rigorously validate deep learning-based tools, for users to understand how to operate tools appropriately, and for professional bodies to develop guidelines for their use and maintenance is essential. Given that members of the radiation treatment planning team perform many tasks that are automatable, the use of deep learning-based tools, in combination with other automated treatment planning tools, may refocus tasks performed by the treatment planning team and may potentially reduce resource-related burdens for clinics with limited resources.

Oncology Informatics: Status Quo and Outlook.

Oncology has undergone rapid progress, with emerging developments in areas including cancer stem cells, molecularly targeted therapies, genomic analyses, and individually tailored immunotherapy. These advances have expanded the tools available in the fight against cancer. Some of these have seen broad media coverage resulting in justified public attention. However, these achievements have only been possible due to rapid developments in the expanding field of biomedical informatics and information technology (IT). Artificial intelligence, radiomics, electronic health records, and electronic patient-reported outcome measures (ePROMS) are only a few of the developments enabling further progress in oncology. The promising impact of IT in oncology will only become reality through a multidisciplinary approach to the complex challenges ahead.

Molecular profiling of a primary cutaneous signet-ring cell/histiocytoid carcinoma of the eyelid.

Primary cutaneous signet-ring cell/histiocytoid carcinoma of the eyelid is a rare and aggressive neoplasm. Fewer than 50 cases have been reported in the literature, and the genetic driving mutations are unknown. Herein, we present a case of this rare disease along with the results of molecular profiling via targeted next-generation sequencing. The patient is an 85-year-old man who presented with left eyelid swelling initially thought to be a chalazion. After no response to incision and drainage and antibiotics, an incisional biopsy was performed. Histopathologic sections revealed a proliferation of cells with signet-ring and histiocytoid morphology arranged singly and in cords infiltrating the dermis, subcutaneous tissue, and muscle. The lesional cells strongly expressed cytoplasmic cytokeratin 7 and nuclear androgen receptor. Next-generation sequencing revealed a CDH1 mutation, which is known to confer signet-ring morphology in other carcinomas. Pathogenic mutations in NTRK3, CDKN1B, and PIK3CA were also detected. To our knowledge, this is the first documented genetic analysis of this rare disease with findings that offer insights into disease pathogenesis and potential therapeutic targets.

Survival After Definitive Chemoradiotherapy With Concurrent Cisplatin or Carboplatin for Head and Neck Cancer.

BACKGROUND: For definitive chemoradiotherapy (chemoRT) of head and neck squamous cell carcinoma (HNSCC), cisplatin is the preferred concurrent agent, with superiority over cetuximab for HPV-associated oropharyngeal squamous carcinoma recently shown in 2 randomized trials (RTOG 1016 and De-ESCALaTE). Patients who are not candidates for cisplatin may be treated with carboplatin instead, but its comparative efficacy is unclear. We analyzed nationwide patterns of care and cancer-specific outcomes after cisplatin- versus carboplatin-based chemoRT. PATIENTS AND METHODS: Patients with locoregionally advanced (stages III-IVB according to the 6th and 7th editions of the AJCC Cancer Staging Manual) squamous cell carcinoma of the oropharynx, larynx, or hypopharynx who received definitive radiotherapy (RT) were identified in the linked SEER-Medicare database. The concurrent chemotherapy regimen was determined through corresponding Medicare claims. Death caused by HNSCC (cancer-specific mortality [CSM]) was analyzed with competing risks. Propensity score analysis and multivariable Fine-Gray regression were used to adjust for baseline differences, including age and comorbidity. RESULTS: We identified 807 patients who received cisplatin-based chemoRT and 342 who received carboplatin-based chemoRT. Most carboplatin recipients (68%) had combination chemotherapy, predominantly with paclitaxel. Carboplatin- and cisplatin-based chemoRT had similar incidences of death attributable to HNSCC (3-year CSM, 29% vs 26%; P=.19), which persisted in propensity score-matched analysis. In addition, no significant difference in overall survival was seen in the matched cohorts. ChemoRT with either cisplatin or carboplatin was superior to RT alone and RT with concurrent cetuximab. In the multivariable model, the adjusted hazard ratio of CSM for carboplatin relative to cisplatin was 1.01 (95% CI, 0.79-1.28; P=.94). CONCLUSIONS: Definitive carboplatin-based chemoRT was equivalent to cisplatin-based therapy and superior to RT alone and RT with concurrent cetuximab. In light of recent results of the RTOG 1016 and De-ESCALaTE trials, our findings suggest that carboplatin-based regimens warrant prospective investigation as an alternative to cisplatin for patients who are not cisplatin candidates.

Optimizing efficiency and safety in external beam radiotherapy using automated plan check (APC) tool and six sigma methodology.

PURPOSE: To develop and implement an automated plan check (APC) tool using a Six Sigma methodology with the aim of improving safety and efficiency in external beam radiotherapy. METHODS: The Six Sigma define-measure-analyze-improve-control (DMAIC) framework was used by measuring defects stemming from treatment planning that were reported to the departmental incidence learning system (ILS). The common error pathways observed in the reported data were combined with our departmental physics plan check list, and AAPM TG-275 identified items. Prioritized by risk priority number (RPN) and severity values, the check items were added to the APC tool developed using Varian Eclipse Scripting Application Programming Interface (ESAPI). At 9 months post-APC implementation, the tool encompassed 89 check items, and its effectiveness was evaluated by comparing RPN values and rates of reported errors. To test the efficiency gains, physics plan check time and reported error rate were prospectively compared for 20 treatment plans. RESULTS: The APC tool was successfully implemented for external beam plan checking. FMEA RPN ranking re-evaluation at 9 months post-APC demonstrated a statistically significant average decrease in RPN values from 129.2 to 83.7 (P < .05). After the introduction of APC, the average frequency of reported treatment-planning errors was reduced from 16.1% to 4.1%. For high-severity errors, the reduction was 82.7% for prescription/plan mismatches and 84.4% for incorrect shift note. The process shifted from 4σ to 5σ quality for isocenter-shift errors. The efficiency study showed a statistically significant decrease in plan check time (10.1 ± 7.3 min, P = .005) and decrease in errors propagating to physics plan check (80%). CONCLUSIONS: Incorporation of APC tool has significantly reduced the error rate. The DMAIC framework can provide an iterative and robust workflow to improve the efficiency and quality of treatment planning procedure enabling a safer radiotherapy process.

Survival of patients with head and neck cancer treated with definitive radiotherapy and concurrent cisplatin or concurrent cetuximab: A Surveillance, Epidemiology, and End Results-Medicare analysis.

BACKGROUND: Cisplatin and cetuximab are both systemic therapies commonly used in combination with radiation (RT) for the definitive treatment of head and neck cancers, but their comparative efficacy is unclear. METHODS: Patients with locoregionally advanced (American Joint Committee on Cancer stage III-IVB) squamous cell carcinomas of the oropharynx, larynx, or hypopharynx were identified in the Surveillance, Epidemiology, and End Results-Medicare database. Patients received either cisplatin or cetuximab concurrent with RT, as determined by Medicare claims. The primary study outcome was head and neck cancer-specific mortality (CSM) analyzed with competing risks. Filtering, propensity score matching, and multivariable Fine-Gray regression were used to adjust for differences between the cisplatin and cetuximab cohorts, including age, comorbidity, and cycles of systemic therapy received. RESULTS: The total cohort consisted of 1395 patients, of whom 786 (56%) received cisplatin and 609 (44%) received cetuximab; the median follow-up was 3.5 years in the patients who remained alive. In the cetuximab cohort, CSM was significantly higher than in the cisplatin cohort (39% vs 25% at 3 years; P < .0001). In the matched cohorts (n = 414), the adjusted hazard ratio of CSM for cetuximab was 1.65 (95% confidence interval, 1.30-2.09; P < .0001) relative to cisplatin, corresponding to an absolute difference of approximately 10% in both CSM and overall survival at 3 years. Cetuximab was associated with less dysphagia, more dermatitis, and a similar incidence of mucositis. CONCLUSIONS: In this sizeable, national patient population, treatment with cetuximab was associated with significantly higher CSM than cisplatin. These results suggest that cisplatin may be the preferred chemotherapeutic agent in this setting.

Feasibility of a Mobile Application to Enhance Swallowing Therapy for Patients Undergoing Radiation-Based Treatment for Head and Neck Cancer.

Dysphagia following treatment for head and neck cancer is one of the most significant morbidities impacting quality of life. Despite the value of prophylactic exercises to mitigate the impact of radiation on long-term swallowing function, adherence to treatment is limited. The purpose of this investigation was to explore the feasibility of a mobile health application to support patient adherence to swallowing therapy during radiation-based treatment. 36 patients undergoing radiation therapy were provided with the Vibrent™ mobile application as an adjunct to standard swallowing therapy. The application included exercise videos, written instructions, reminders, exercise logging, and educational content. 80% of participants used the app during treatment and logged an average of 102 exercise sessions over the course of treatment. 25% of participants logged at least two exercise sessions per day over the 7-week treatment period, and 53% recorded at least one session per day. Exit interviews regarding the patient experience with the Vibrent™ mobile application were largely positive, but also provided actionable strategies to improve future versions of the application. The Vibrent™ mobile application appears to be a tool that can be feasibly integrated into existing patient care practices and may assist patients in adhering to treatment recommendations and facilitate communication between patients and providers between encounters.

Role of radiotherapy fractionation in head and neck cancers (MARCH): an updated meta-analysis.

BACKGROUND: The Meta-Analysis of Radiotherapy in squamous cell Carcinomas of Head and neck (MARCH) showed that altered fractionation radiotherapy is associated with improved overall and progression-free survival compared with conventional radiotherapy, with hyperfractionated radiotherapy showing the greatest benefit. This update aims to confirm and explain the superiority of hyperfractionated radiotherapy over other altered fractionation radiotherapy regimens and to assess the benefit of altered fractionation within the context of concomitant chemotherapy with the inclusion of new trials. METHODS: For this updated meta-analysis, we searched bibliography databases, trials registries, and meeting proceedings for published or unpublished randomised trials done between Jan 1, 2009, and July 15, 2015, comparing primary or postoperative conventional fractionation radiotherapy versus altered fractionation radiotherapy (comparison 1) or conventional fractionation radiotherapy plus concomitant chemotherapy versus altered fractionation radiotherapy alone (comparison 2). Eligible trials had to start randomisation on or after Jan 1, 1970, and completed accrual before Dec 31, 2010; had to have been randomised in a way that precluded prior knowledge of treatment assignment; and had to include patients with non-metastatic squamous cell carcinoma of the oral cavity, oropharynx, hypopharynx, or larynx undergoing first-line curative treatment. Trials including a non-conventional radiotherapy control group, investigating hypofractionated radiotherapy, or including mostly nasopharyngeal carcinomas were excluded. Trials were grouped in three types of altered fractionation: hyperfractionated, moderately accelerated, and very accelerated. Individual patient data were collected and combined with a fixed-effects model based on the intention-to-treat principle. The primary endpoint was overall survival. FINDINGS: Comparison 1 (conventional fractionation radiotherapy vs altered fractionation radiotherapy) included 33 trials and 11 423 patients. Altered fractionation radiotherapy was associated with a significant benefit on overall survival (hazard ratio [HR] 0·94, 95% CI 0·90-0·98; p=0·0033), with an absolute difference at 5 years of 3·1% (95% CI 1·3-4·9) and at 10 years of 1·2% (-0·8 to 3·2). We found a significant interaction (p=0·051) between type of fractionation and treatment effect, the overall survival benefit being restricted to the hyperfractionated group (HR 0·83, 0·74-0·92), with absolute differences at 5 years of 8·1% (3·4 to 12·8) and at 10 years of 3·9% (-0·6 to 8·4). Comparison 2 (conventional fractionation radiotherapy plus concomitant chemotherapy versus altered fractionation radiotherapy alone) included five trials and 986 patients. Overall survival was significantly worse with altered fractionation radiotherapy compared with concomitant chemoradiotherapy (HR 1·22, 1·05-1·42; p=0·0098), with absolute differences at 5 years of -5·8% (-11·9 to 0·3) and at 10 years of -5·1% (-13·0 to 2·8). INTERPRETATION: This update confirms, with more patients and a longer follow-up than the first version of MARCH, that hyperfractionated radiotherapy is, along with concomitant chemoradiotherapy, a standard of care for the treatment of locally advanced head and neck squamous cell cancers. The comparison between hyperfractionated radiotherapy and concomitant chemoradiotherapy remains to be specifically tested. FUNDING: Institut National du Cancer; and Ligue Nationale Contre le Cancer.

Reduced feeding tube duration with intensity-modulated radiation therapy for head and neck cancer: A Surveillance, Epidemiology, and End Results-Medicare Analysis.

BACKGROUND: Intensity-modulated radiation therapy (IMRT) is a technologically advanced and resource-intensive method of delivering radiation therapy (RT) and is used to minimize toxicity for patients with head and neck cancer (HNC). Dependence on feeding tubes is a significant marker of toxicity of RT. The objective of this analysis was to compare the placement and duration of feeding tube use among patients with HNC from 1999 through 2011. METHODS: The cohort, demographics, and cancer-related variables were determined using the linked Surveillance, Epidemiology, and End Results (SEER)-Medicare database, and claims data were used to analyze treatment details. RESULTS: In total, 2993 patients were identified. At a median follow-up of 47 months, 54.4% of patients had ever had a feeding tube placed. The median duration from feeding tube placement to removal was 277 days. On zero-inflated negative binomial regression, patients who received IMRT and 3-dimensional RT (3DRT) (non-IMRT) had similar rates of feeding tube placement (odds ratio, 1.10; P = .35); however, patients who received 3DRT had a feeding tube in place 1.18 times longer than those who received IMRT (P = .03). The difference was only observed among patients who received definitive RT; patients who underwent surgery and also received adjuvant RT had no statistically significant difference in feeding tube placement or duration. CONCLUSIONS: Patients with HNC who received definitive IMRT had a significantly shorter duration of feeding tube placement than those who received 3DRT. These data suggest that there may be significant quality-of-life benefits to IMRT with respect to long-term swallowing function in patients with HNC. Cancer 2017;123:283-293. © 2016 American Cancer Society.

Reproducibility of patient setup in the seated treatment position: A novel treatment chair design.

Radiotherapy in a seated position may be indicated for patients who are unable to lie on the treatment couch for the duration of treatment, in scenarios where a seated treatment position provides superior anatomical positioning and dose distributions, or for a low-cost system designed using a fixed treatment beam and rotating seated patient. In this study, we report a novel treatment chair that was constructed to allow for three-dimensional imaging and treatment delivery while ensuring robust immobilization, providing reproducibility equivalent to that in the traditional supine position. Five patients undergoing radiation treatment for head-and-neck cancers were enrolled and were setup in the chair, with immobilization devices created, and then imaged with orthogonal X-rays in a scenario that mimicked radiation treatments (without treatment delivery). Six subregions of the acquired images were rigidly registered to evaluate intra- and interfraction displacement and chair construction. Displacements under conditions of simulated image guidance were acquired by first registering one subregion; the residual displacement of other subregions was then measured. Additionally, we administered a patient questionnaire to gain patient feedback and assess comparison to the supine position. Average inter- and intrafraction displacements of all subregions in the seated position were less than 2 and 3 mm, respectively. When image guidance was simulated, L-R and A-P interfraction displacements were reduced by an average of 1 mm, providing setup of comparable quality to supine setups. The enrolled patients, who had no indication for a seated treatment position, reported no preference in the seated or the supine position. The novel chair design provides acceptable inter- and intrafraction displacement, with reproducibility equivalent to that reported for patients in the supine position. Patient feedback will be incorporated in the refinement of the chair, facilitating treatment of head-and-neck cancer in patients who are unable to lie for the duration of treatment or for use in an economical fixed-beam setup.

Radiation therapy (with or without neck surgery) for phenotypic human papillomavirus-associated oropharyngeal cancer.

BACKGROUND: Favorable outcomes for human papillomavirus-associated oropharyngeal cancer have led to interest in identifying a subgroup of patients with the lowest risk of disease recurrence after therapy. De-intensification of therapy for this group may result in survival outcomes that are similar to those associated with current therapy but with less toxicity. To advance this effort, this study analyzed the outcomes of oropharyngeal cancer patients treated with or without systemic therapy. METHODS: This was a retrospective study of patients with oropharyngeal cancer treated between 1985 and 2012. The criteria for inclusion were ≤10 pack-years of cigarette smoking and stage III/IVA cancer limited to T1-3, N1-N2b, and T3N0 disease. A survival analysis was performed with the primary endpoint of progression-free survival (PFS). RESULTS: The cohort included 857 patients. Systemic therapy was given to 439 patients (51%). The median survival was 80 months. The 2-year PFS rate was 91%. When the analysis was limited to 324 patients irradiated without systemic therapy, the 2- and 5-year PFS rates were 90% and 85%, respectively. Furthermore, for these 324 patients, the 5-year PFS rates for T1, T2, and T3 disease were 90%, 83%, and 70%, respectively. The 5-year PFS rate for patients treated with systemic therapy for T3 disease was 77% (P = .07). CONCLUSIONS: According to the low-risk definition currently established in cooperative trials, the patients had a 2-year PFS rate approximating 90%. When patients who were treated with radiation alone were evaluated, no compromise was observed in this high rate of PFS, which is higher than the 2-year PFS thresholds used in current cooperative trials. Cancer 2016;122:1702-7. © 2016 American Cancer Society.

Improved survival using intensity-modulated radiation therapy in head and neck cancers: a SEER-Medicare analysis.

BACKGROUND: Intensity-modulated radiation therapy (IMRT) is a technologically advanced, and more expensive, method of delivering radiation therapy with a goal of minimizing toxicity. It has been widely adopted for head and neck cancers; however, its comparative impact on cancer control and survival remains unknown. The goal of this analysis was to compare the cause-specific survival (CSS) for patients with head and neck cancers treated with IMRT versus non-IMRT from 1999 to 2007. METHODS: CSS was determined using the Surveillance, Epidemiology, and End Results (SEER)-Medicare database and analyzed regarding treatment details, including the use of IMRT versus non-IMRT, using claims data. Hazard ratios (HRs) were estimated by the frailty model with a propensity score matching cohort and instrumental variable analysis. RESULTS: A total of 3172 patients were identified. With a median follow-up of 40 months, patients treated with IMRT had a statistically significant improvement in CSS compared with those treated with non-IMRT (84.1% versus 66.0%; P < .001). When each anatomic subsite was analyzed separately, all respective subgroups of patients treated with IMRT had better CSS than those treated with non-IMRT. In multivariable survival analyses, patients treated with IMRT were associated with better CSS (HR = 0.72, 95% confidence interval = 0.59 to 0.90 for propensity score matching; HR = 0.60, 95% confidence interval = 0.41 to 0.88 for instrumental variable analysis). CONCLUSIONS: Patients with head and neck cancers who were treated with IMRT experienced significant improvements in CSS compared with patients treated with non-IMRT techniques. This suggests there may be benefits to IMRT in cancer outcomes, in addition to toxicity reduction, for this patient population.