David I. Rosenthal

Head and neck radiation oncology, with its complex locality and epidemiology, requires various imaging techniques to achieve sufficient visualization. Through collaboration with medical physicists, radiation therapists, radiation oncologists, and neuroradiologists, our group clinically implemented a standard set of magnetic resonance imaging (MRI) sequences on an MR-simulation scanner for three anatomical regions: skull base, oral cavity, and larynx/pharynx. A total of 41 patients with head and neck cancer and 3 volunteers were scanned on either a 1.5T or 3T MR-simulation scanner. Sequences described include Dixon-based approaches, SPAIR-based approaches, short T2-based approaches, and quantitative imaging methods. We describe and outline the steps to optimize these notable MRI sequences to aid in successful implementation in a radiation oncology clinic.

Objective: Patient-reported outcomes (PROs) contain valuable information that can be leveraged by providers to perform timely interventions and improve quality of life and survival. However, the implementation of electronic PROs (ePROs) remains a challenge from technical and evaluation perspectives. Our objective was to construct a robust electronic health record (EHR)-integrated ePRO information infrastructure founded on RE-AIM (reach-effectiveness-adoption-implementation-maintenance) principles. Materials and Methods: We used Epic Systems as our EHR platform to build the MD Anderson Symptom Index Head and Neck Module (MDASI-HN) for release to all patients undergoing evaluation and/or treatment in our HN Radiation Oncology clinics. RE-AIM metrics were established and used to design patient, provider, and implementing facilitator information tools. Results: From January 2021 to July 2024, our ePRO program has collected 13,156 patient-submitted ePROs on 3,497 unique HN patients, with a 12-month sustained ePRO compliance rate of 82%. We also propose a dynamic 2-cycle implementation model. This model can be used to continuously (re)define, build, and adapt ePRO information tools for patients, providers, and program facilitators. Discussion: Our ePRO framework has several benefits, including integrated clinical data for enhanced decision-making, potential scalability, and use of a common EHR system. Formative (ie, mid-phase) evaluations were essential to our program, allowing for timely optimization of ePRO compliance, ePRO usage by clinical staff, and secondary use of high-quality ePRO data. Conclusion: In this article, we provide a valuable roadmap toward developing a comprehensive, EHR-based ePRO information infrastructure simultaneously optimized for clinical utility, informatics operations, and implementation evaluation founded on RE-AIM principles.

Objective: Patient-reported outcomes (PROs) contain valuable information that can be leveraged by providers to perform timely interventions and improve quality of life and survival. However, the implementation of electronic PROs (ePROs) remains a challenge from technical, behavioral, and evaluation perspectives. Our objective was to construct a robust electronic health record (EHR)-integrated ePRO information infrastructure founded on RE-AIM (Reach-Effectiveness-Adoption-Implementation-Maintenance) principles. Materials and Methods: We used Epic Systems as our EHR platform to build the MD Anderson Symptom Index-Head and Neck Module (MDASI-HN) for release to all patients undergoing evaluation and/or treatment in our HN Radiation Oncology clinics. RE-AIM metrics were established and used to design patient-, provider-, and implementing facilitator information tools. Results: From January 2021 to July 2024, our ePRO program has collected 13,156 patient-submitted ePROs on 3,497 unique HN patients, with a 12-month sustained ePRO compliance rate of 82%. We also propose a dynamic clinical implementation-evaluation cycle. This model can be used to continuously (re)define, build, and adapt ePRO information tools for patients, providers, and program facilitators. Discussion: Our ePRO framework has several benefits including integrated clinical data for enhanced decision-making, potential scalability, and use of a common EHR system. Formative (i.e., mid-phase) evaluation and feedback were essential in our program, allowing for timely optimization of ePRO compliance, ePRO usage by clinical staff, and secondary use of high-quality ePRO data. Conclusion: In this article, we provide a valuable roadmap towards developing a comprehensive, EHR-based ePRO information infrastructure simultaneously optimized for clinical utility and implementation evaluation founded on RE-AIM principles.

Background/Objectives: Stereotactic body radiation therapy (SBRT) for skull base reirradiation is particularly challenging, as patients have already received substantial radiation doses to the region, and nearby normal organs may have approached their tolerance limit from prior treatments. In this study, we reviewed the characteristics and capabilities of four advanced external beam radiation delivery systems and four modern treatment planning systems and evaluated the treatment plan quality of each technique using skull base reirradiation patient cases. Methods: SBRT plans were generated for sixteen skull base reirradiation patients using four modalities: the GK plan for the Elekta Leksell Gamma Knife Perfexion/ICON, the CyberKnife (CK) plan for the Accuray CyberKnife, the intensity-modulated proton therapy (IMPT) plan for the Hitachi ProBeat-FR proton therapy machine, and the volumetric-modulated arc therapy (VMAT) plan for the Varian TrueBeam STx. These plans were evaluated and compared using two novel gradient indices in addition to traditional dosimetry metrics for targets and organs at risk (OARs). The steepest border gradient quantified the percent prescription dose fall-off per millimeter at the boundary between the target and adjacent critical structures. This gradient index highlighted the system’s ability to spare nearby critical OARs. The volume gradient assessed the extent of dose spread outside the target toward the patient’s body. Results: All plans achieved comparable target coverage and conformity, while IMPT and VMAT demonstrated significantly better uniformity. The GK plans exhibited the highest border gradient, up to 20.9%/mm, followed by small-spot-size IMPT plans and CK plans. Additionally, IMPT plans showed the benefit of reduced dose spread in low-dose regions and the lowest maximum and mean doses to the brainstem and carotid artery. Conclusions: The advanced external beam radiotherapy modalities evaluated in this study are well-suited for SBRT in skull base reirradiation, which demands precise targeting of tumors with highly conformal doses and steep dose gradients to protect nearby normal structures.

Background Radiation-associated lymphedema and fibrosis (LEF) is a significant toxicity following radiation therapy (RT) for head and neck cancer (HNC) patients. Recently, the CT Lymphedema and Fibrosis Assessment Tool (CT-LEFAT) was developed to standardize LEF diagnosis through fat stranding visualized on CT. This study aims to evaluate the inter-observer reliability and diagnostic accuracy of the CT-LEFAT criteria. Materials and Methods This study retrospectively evaluated 26 HNC patients treated with RT that received a minimum of two contrast-enhanced CT scans. Qualitative review was conducted by five physician raters to assess the fat stranding observed on CT according to the CT-LEFAT criteria. Fleiss’ kappa analysis was used to assess the inter- and intra-rater reliability, and Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) analysis was used to evaluate diagnostic accuracy. Results The inter-rater reliability across the six CT-LEFAT regions generally indicated a slight to fair agreement across all raters (0.04 ≤ kappa ≤ 0.36). Intra-observer agreement was generally fair to moderate (overall kappa=0.44). The ROC AUC analysis varied based on aggregation method used (0.60 ≤ average AUC ≤ 0.70). Conclusion This specific use-case evaluating CT-LEFAT criteria displays limited performance. This suggests that additional materials, such as further training, refinement of imaging methods, or other processes may be required before achieving clinically-ready diagnostic performance of LEF diagnosis.

Purpose:In locoregionally advanced, resectable cutaneous squamous cell carcinoma of the head and neck (CSCC-HN), surgery followed by radiotherapy is standard but can be cosmetically and functionally devastating, and many patients will have recurrence.Patients and Methods:Newly diagnosed or recurrent stage III–IVA CSCC-HN patients amenable to curative-intent surgery received two cycles of neoadjuvant PD-1 inhibition. The primary endpoint was ORR per RECIST 1.1. Secondary endpoints included pathologic response [pathologic complete response (pCR) or major pathologic response (MPR; ≤10% viable tumor)], safety, DSS, DFS, and OS. Exploratory endpoints included immune biomarkers of response.Results:Of 20 patients enrolled, 7 had recurrent disease. While only 6 patients [30%; 95% confidence interval (CI), 11.9–54.3] had partial responses by RECIST, 14 patients (70%; 95% CI, 45.7–88.1) had a pCR (n = 11) or MPR (n = 3). No SAEs ocurred during or after the neoadjuvant treatment. At a median follow-up of 22.6 months (95% CI, 21.7–26.1), one patient progressed and died, one died without disease, and two developed recurrence. The 12-month DSS, DFS, and OS rates were 95% (95% CI, 85.9–100), 89.5% (95% CI, 76.7–100), and 95% (95% CI, 85.9–100), respectively. Gene expression studies revealed an inflamed tumor microenvironment in patients with pCR or MPR, and CyTOF analyses demonstrated a memory CD8+ T-cell cluster enriched in patients with pCR.Conclusions:Neoadjuvant immunotherapy in locoregionally advanced, resectable CSCC-HN is safe and induces a high pathologic response rate. Pathologic responses were associated with an inflamed tumor microenvironment.

(1) Background: Radiotherapy (RT) is a central component for the treatment of many head and neck cancers. In this systematic review of the literature, we aimed to characterize and quantify the published evidence on RT-related hypothyroidism, including estimated incidence, clinical risk factors, and dosimetric parameters that may be used to guide clinical decision making. Furthermore, we aimed to identify potential areas of improvement in the prevention and clinical management of RT-induced hypothyroidism, including the role of modern advanced therapeutic techniques. (2) Methods: We conducted a systemic review of the literature in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. PubMed and Google Scholar were searched to identify original research articles describing the incidence, mechanism, dosimetry, treatment, or prevention of radiation-related hypothyroidism for adults receiving RT for the treatment of head and neck cancers. The snowball method was used to identify additional articles. For identified articles, we tabulated several datapoints, including publication date, patient sample size, estimated hypothyroidism incidence, cancer site/type, follow-up period, radiation modality and technique, use of multimodality therapy, method of thyroid function evaluation, and proposed dosimetric predictors of hypothyroidism. (3) Results: One hundred and eleven articles met inclusion criteria, reflecting a range of head and neck cancer subtypes. There was a large variation in the estimated incidence of RT-related hypothyroidism, with a median estimate of 36% (range 3% to 79%). Reported incidence increased in later publication dates, which was likely related to improved screening and longer follow up. There were a wide variety of predictive metrics used to identify patients at high risk of hypothyroidism, the most common of which were volumetric and mean dosimetrics related to the thyroid gland (Vxx%, Dmean). More recently, there has been increasing evidence to suggest that the thyroid gland volume itself and the volume of the thyroid gland spared from high-dose radiation (VSxx) may better predict thyroid function after RT. There were no identified studies investigating the role of advanced radiotherapeutic techniques such as MRI-guided RT or particle therapy to decrease RT-related hypothyroidism. Conclusions: Hypothyroidism is a common toxicity resulting from therapeutic radiation for head and neck cancer with recent estimates suggesting 40–50% of patients may experience hypothyroidism after treatment. Dosimetric predictive models are increasingly able to accurately identify patients at risk of hypothyroidism, especially those utilizing thyroid VS metrics. Further investigation regarding the potential for advanced radiotherapeutic therapies to decrease RT-induced thyroid dysfunction is needed.