Michael T. Spiotto

Advanced imaging is the cornerstone of modern radiation oncology, contributing to each phase of patient care, from diagnosis and treatment planning to delivery and follow-up. It has evolved from providing purely geometric guidance to enabling biological and dynamic precision, capturing detailed spatial and functional information about tumors and surrounding tissues. This progress has also generated vast amounts of complex data that remain largely underexplored. AI-based methods have shown promises to unlock the potential of these data, ensuring quality and standardization while extracting previously inaccessible insights. AI-driven tools can enhance accuracy, efficiency, and personalization of radiation oncology through precision diagnosis, automated segmentation, adaptive treatment planning, real-time image guidance, and predictive response assessment. In this review, we conducted a systematic bibliometric analysis of relevant literature published in the last decade and explored current advancements in AI and radiomics applications across radiation oncology. We also addressed ongoing challenges, such as data heterogeneity, model interpretability, and clinical implementation, and discussed future directions for integrating AI-powered imaging solutions into routine practice to advance precision cancer care.

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.

Purpose: Sleep-related symptom prevalence is not well-characterized and likely under-recognized in head and neck cancer. We investigated longitudinal symptom severity trajectory, prevalence of moderate/severe symptoms, and association between severe sleep-related patient-reported symptoms and oncologic endpoints in oropharyngeal cancer (OPC) patients receiving radiotherapy (RT). Methods: A longitudinal cohort of 372 patients with OPC treated with curative-intent RT with/without chemotherapy at a single-site tertiary center was queried at RT start, end of RT, and six months post-RT. All completed baseline MD Anderson Symptom Inventory-Head and Neck (MDASI-HN) at start of RT. Sleep-related symptom items included “fatigue”, “disturbed sleep”, and “drowsiness” (mild, moderate, severe). Clinical data were collected, and overall survival (OS) was evaluated using Kaplan-Meier/log-rank tests and multivariable Cox proportional hazards models with covariate adjustment. Results: Severe fatigue, disturbed sleep, and drowsiness were infrequent at baseline and at RT start, but peaked at RT end (26%, 15% and 18%) and returned to near-baseline prevalence by six months after RT (6%, 4%, 2%). In Cox proportional hazard models, severe longitudinal fatigue (HR 5.05, 95% CI 1.25-17.07, p = 0.013), sleep (HR 3.86, 95% CI 1.23 to 10.16, p = 0.0104), and drowsiness burden (HR 8.24, 95% CI 1.22 to 32.62, p = 0.008) were all independently associated with worse OS. Additionally, severe fatigue (HR = 3.58, 95% CI: 1.09 to 10.11, p = 0.0375), sleep disturbance (HR 5.08, 95% CI 1.60-13.51, p = 0.0081), and drowsiness (HR=7.76, 95% CI 1.45-33.47, p=0.0193) reported at RT start were also independently associated with significantly worse OS. Aside from age, severe average daily symptom scores, and severe symptoms reported at RT start, were independently associated with worse OS. Conclusion: Severe sleep related symptoms were uncommon at baseline or RT start, but a substantial proportion of OPC patients experienced clinically meaningful sleep disturbances by the end of RT. At an average follow up of 84 months, severe longitudinal fatigue, sleep, and drowsiness burden were all independently associated with worse OS in OPC. Severe fatigue, drowsiness and sleep disturbance reported at RT start were also independently associated with worse OS. Assessment of sleep disturbances along with potential physiologic correlates are an important part of comprehensive care.

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.

The cover image is based on the article A prospective cohort study on stereotactic radiotherapy in the management of dural recurrence of olfactory neuroblastoma by Christopher D. Goodman MD et al., https://doi.org/10.1002/hed.27887. image

Background Existing studies on osteoradionecrosis of the jaw (ORNJ) have primarily used cross-sectional data, assessing risk factors at a single time point. Determining the time-to-event profile of ORNJ has important implications to monitor oral health in head and neck cancer (HNC) long-term survivors. Methods Demographic, clinical and dosimetric data were retrospectively obtained for a clinical observational cohort of 1129 patients with HNC treated with radiotherapy (RT) at The University of Texas MD Anderson Cancer Center. ORNJ was diagnosed in 198 patients (18%). A multivariable logistic regression analysis with forward stepwise variable selection identified significant predictors for ORNJ. These predictors were then used to train a Weibull Accelerated Failure Time (AFT) model, which was externally validated using an independent cohort of 265 patients (92 ORNJ cases and 173 controls) treated at Guy’s and St. Thomas’ Hospitals. Findings Our model identified that each unit increase in D25% is significantly associated with a 12% shorter time to ORNJ (Adjusted Time Ratio [ATR] 0·88, pInterpretation This study is the first to demonstrate a direct relationship between radiation dose and the time to ORNJ onset, providing a novel characterization of the impact of delivered dose not only on the probability of a late effect (ORNJ), but the conditional risk during survivorship. Funding This work was supported by various funding sources including NIH, NIDCR, NCI, NAPT, NASA, BCM, Affirmed Pharma, CRUK, KWF Dutch Cancer Society, NWO ZonMw, and the Apache Corporation.

Background: Treatment for dural recurrence of olfactory neuroblastoma (ONB) is not standardized. We assess the outcomes of stereotactic body radiotherapy (SBRT) in this population.Methods: ONB patients with dural recurrences treated between 2013 and 2022 on a prospective registry were included. Tumor control, survival, and patient‐reported quality of life were analyzed.Results: Fourteen patients with 32 dural lesions were evaluated. Time to dural recurrence was 58.3 months. Thirty lesions (94%) were treated with SBRT to a median dose of 27 Gy in three fractions. Two patients (3 of 32 lesions; 9%) developed in‐field radiographic progression, five patients (38%) experienced progression in non‐contiguous dura. Two‐year local control was 85% (95% CI: 51–96%). There were no >grade 3 acute toxicities and 1 case of late grade 3 brain radionecrosis.Conclusion: In this largest study of SBRT reirradiation for ONB dural recurrence to date, high local control rates with minimal toxicity were attainable.

Radiotherapy and/or chemotherapy have been used for nearly 100 years to treat lymphoma. Recently, immunotherapy has been incorporated into the treatment of lymphomas. Here, we will review both the role of immunotherapy in lymphoma as well as the feasibility of incorporating immunotherapies with conventional lymphoma treatments, especially radiotherapy. Immunotherapy agents include checkpoint inhibitors that target the PD-1/PD-L1 axis, CTLA-4, or CD47. In addition, other immunotherapy agents such as bi-specific antibodies and CD19 CAR-T cell therapy are being implemented in various non-Hodgkin’s lymphomas. Extrapolating from observations in other disease sites and incorporating immunotherapy with conventional treatments of lymphoma, including radiotherapy, may have opposing effects. Radiotherapy may stimulate anti-tumor immune responses that synergize with immunotherapies. In contrast, radiotherapy, as well as chemotherapy, may also induce local and systemic immune dysfunction which reduces the efficacy of immunotherapies. With newer radiation treatment techniques and limited radiation fields, it is likely that the efficacy of immunotherapy can be maintained when included with conventional treatments. Therefore, there remains an unmet need to better understand the role of immunotherapy alone and in combination with current treatments in lymphoma patients.

(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.

Background: There are limited studies and no surveillance protocols on pituitary dysfunction for adults who underwent anterior skull base radiation.Methods: Cross‐sectional study of 50 consecutive patients with sinonasal or nasopharyngeal cancer who underwent definitive radiotherapy. The mean radiation doses, prevalence of pituitary dysfunction, and associated factors were calculated.Results: Pituitary hormone levels were abnormal in 23 (46%) patients, including 6 (12%) with symptomatic abnormalities requiring treatment. The most common hormonal abnormality was hyperprolactinemia (30%), central hypothyroidism (8%) and central hypogonadism (6%). Patients with abnormal pituitary hormone values received higher mean radiation doses to the pituitary gland (1143 cGy, P = 0.04), pituitary stalk (1129 cGy, P = 0.02), optic chiasm (1094 cGy, P = 0.01), and hypothalamus (900 cGy, P = 0.01).Conclusions: Nearly half of the patients had abnormal pituitary function, including over a tenth requiring treatment. There may be a dose‐dependent association between hormonal dysfunction and radiation.