Head and Neck Radiation Therapy Patterns of Practice Variability Identified as a Challenge to Real-World Big Data: Results From the Learning from Analysis of Multicentre Big Data Aggregation (LAMBDA) Consortium

Purpose

Outside of randomized clinical trials, it is difficult to develop clinically relevant evidence-based recommendations for radiation therapy (RT) practice guidelines owing to lack of comprehensive real-world data. To address this knowledge gap, we formed the Learning from Analysis of Multicenter Big Data Aggregation consortium to cooperatively implement RT data standardization, develop software solutions for data analysis, and recommend clinical practice change based on real-world data analyzed. The first phase of this "Big Data" study aimed at characterizing variability in clinical practice patterns of dosimetric data for organs at risk (OARs) that would undermine subsequent use of large-scale, electronically aggregated data to characterize associations with outcomes. Evidence from this study was used as the basis for practical recommendations to improve data quality.

Methods and Materials

Dosimetric details of patients with head and neck cancer treated with radiation therapy between 2014 and 2019 were analyzed. Institutional patterns of practice were characterized, including structure nomenclature, volumes, and frequency of contouring. Dose volume histogram (DVH) distributions were characterized and compared with institutional constraints and literature values.

Results

Plans for 4664 patients treated to a mean plan dose of 64.4 ± 13.2 Gy in 32 ± 4 fractions were aggregated. Before implementation of TG-263 guidelines in each institution, there was variability in OAR nomenclature across institutions and structures. With evidence from this study, we identified a targeted and practical set of recommendations aimed at improving the quality of real-world data.

Conclusions

Quantifying similarities and differences among institutions for OAR structures and DVH metrics is the launching point for next steps to investigate potential relationships between DVH parameters and patient outcomes.

Adhering to Eat and Exercise Status During Radiotherapy for Oropharyngeal Cancer for Prevention and Mitigation of Radiotherapy-Associated Dysphagia

Importance

Previously published work reported independent benefit of maintenance of oral intake (eat) and swallowing exercise adherence (exercise) during radiotherapy (RT) on diet and functional outcomes. The current study seeks to validate the authors' previously published findings in a large contemporary cohort of patients with oropharynx cancer (OPC) and address limitations of the prior retrospective study using prospective, validated outcome measures.

Objective

To examine the longitudinal association of oral intake and swallowing exercise using validated, clinician-graded and patient-reported outcomes.

Design, Setting, and Participants

Secondary analysis of a prospective OPC registry including patients who underwent primary RT/chemoradiotherapy (CRT) or primary transoral robotic surgery plus RT/CRT for OPC at a single-institution comprehensive cancer center.

Exposures

Adherence to speech pathology swallowing intervention during RT coded as (1) eat: oral intake at end of RT (nothing by mouth [NPO]; partial oral intake [PO], with feeding tube [FT] supplement; full PO); and (2) exercise: swallowing exercise adherence (nonadherent vs partial/full adherence).

Main Outcomes and Measures

Feeding tube and diet (Performance Status Scale for Head and Neck Cancer) patient-reported swallowing-related quality of life (MD Anderson Dysphagia Inventory; MDADI) and clinician-graded dysphagia severity grade (videofluoroscopic Dynamic Imaging Grade of Swallowing Toxicity; DIGEST) were collected at baseline, 3 to 6 months, and 18 to 24 months post-RT.

Results

A total of 595 patients (mean [SD] age, 65 [10] years; 532 [89%] male) who underwent primary RT (111 of 595 [19%]), CRT (434 of 595 [73%]), or primary transoral robotic surgery plus RT/CRT (50 of 595 [8%]) were included in this cohort study. At the end of RT, 55 (9%) patients were NPO, 115 (19%) were partial PO, 425 (71%) were full PO, and 340 (57%) reported exercise adherence. After multivariate adjustment, subacute return to solid diet and FT were independently associated with oral intake (odds ratio [OR], 2.0; 95% CI, 1.0-4.1; OR, 0.1; 95% CI, 0.0-0.2, respectively) and exercise (OR, 2.9; 95% CI, 1.9-4.5; OR, 0.3; 95% CI, 0.1-0.5, respectively). Subacute MDADI (β = 6.5; 95% CI, 1.8-11.2), FT duration (days; β = -123.4; 95% CI, -148.5 to -98.4), and less severe dysphagia per DIGEST (OR, 0.6; 95% CI, 0.3-1.0) were independently associated with oral intake, while exercise was independently associated with less severe laryngeal penetration/aspiration per DIGEST-safety (OR, 0.7; 95% CI, 0.4-1.0). DIGEST grade associations with oral intake were not preserved long-term; however, exercise was associated with a higher likelihood of solid diet intake and better swallow safety per DIGEST.

Conclusions and Relevance

The findings of this cohort study extend the authors' previously published findings that oral intake and swallowing exercise during RT are associated with favorable functional outcomes, now demonstrated with broader domains of function using validated measures. Patterns of benefit differed in this study. Specifically, better subacute recovery of swallow-related quality of life and less severe dysphagia were found among patients who maintained oral intake independent of exercise adherence, and shorter FT utilization and better long-term diet and swallowing safety were found among those who exercised independent of oral intake.

Neutrophil-to-lymphocyte ratio trend: A novel prognostic predictor in patients with nasopharyngeal carcinoma receiving radiotherapy

BACKGROUND

Peripheral neutrophil-lymphocyte ratio (NLR), reflecting immune-inflammation status, shows great potential for tumor progression and outcome. Pre-treatment NLR does not fully reflect the immune-inflammatory response to treatment. This study aimed to introduce the NLR trend as a new indicator and to investigate its prognostic value in patients with nasopharyngeal carcinoma receiving radiotherapy.

METHODS

This retrospective study evaluated patients with nasopharyngeal carcinoma treated with radiotherapy. The NLR trend value was calculated from the fitted line gradient via the NLRs before, during (at least once), and after each patient's first radiotherapy. The Kaplan-Meier curve and log-rank test were used to calculate and compare survival outcomes of different pretreatment NLRs and NLR trends for progression-free survival, locoregional recurrence-free survival (LRFS), and overall survival at 3 and 5 years. Multivariate Cox regression analyses were performed to assess the association between the NLR trend plus 3- and 5-year overall survival.

RESULTS

The study included 528 patients. A lower NLR trend predicted worse progression-free survival, LRFS, plus 3- and 5-year overall survival. Multivariate Cox regression analysis showed that the NLR trend independently predicted 3- and 5-year overall survival. Sub-group analysis showed that the prognosis of patients with a low pretreatment NLR and a high NLR trend were superior to those of other groups.

CONCLUSION

The NLR trend independently predicted the prognosis of patients with nasopharyngeal carcinoma receiving radiotherapy. The NLR trend and the pretreatment NLR combination is more precise than pretreatment NLR in predicting prognosis. A high NLR trend may be evidence of a positive immune response to radiotherapy in patients with nasopharyngeal carcinoma.

Association between Prior Malignancy Exclusion Criteria and Age Disparities in Cancer Clinical Trials

Simple Summary

Recent studies have shown that the incidence of age disparities in cancer clinical trials may be increasing over time. Excluding patients with prior malignancies is one such eligibility criterion through which elderly may inadvertently be excluded from clinical trial participation. While strict enrollment criteria may improve internal validity of studies, they can also negatively impact generalizability of results. As such, we sought to characterize the incidence of prior malignancy exclusion criteria in phase III cancer clinical trials and assess if this eligibility criterion may directly contribute to age disparities. These data support efforts to modernize eligibility criteria and inform best practices regarding acceptable versus unacceptable exclusionary timeframes for prior malignancy exclusion criteria.

Abstract

Prior malignancy exclusion criteria (PMEC) are often utilized in cancer clinical trials; however, the incidence of PMEC and the association of PMEC with trial participant age disparities remain poorly understood. This study aimed to identify age disparities in oncologic randomized clinical trials as a result of PMEC. Using a comprehensive collection of modern phase III cancer clinical trials obtained via ClinicalTrials.gov, we assessed the incidence and covariates associated with trials excluding patients with prior cancers within 5+ years from registration (PMEC-5). Using the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) database, we further sought to determine the correlation between PMEC-5 and age disparities. PMEC-5 were used in 41% of all trials, with higher PMEC-5 utilization among industry-supported trials as well as trials evaluating a targeted therapy. Comparing trial patient median ages with population-matched median ages by disease site and time-period, we assessed the association between PMEC-5 and age disparities among trial participants. PMEC-5 were independently associated with heightened age disparities, which further worsened with longer exclusionary timeframes. Together, PMEC likely contribute to age disparities, suggesting that eligibility criteria modernization through narrower PMEC timeframes may work toward reducing such disparities in cancer clinical trial enrollment.

The PRO-ACTIVE trial protocol: a randomized study comparing the effectiveness of PROphylACTic swallow InterVEntion for patients receiving radiotherapy for head and neck cancer

BACKGROUND

Swallowing therapy is commonly provided as a treatment to lessen the risk or severity of dysphagia secondary to radiotherapy (RT) for head and neck cancer (HNC); however, best practice is not yet established. This trial will compare the effectiveness of prophylactic (high and low intensity) versus reactive interventions for swallowing in patients with HNC undergoing RT.

METHODS

This multi-site, international randomized clinical trial (RCT) will include 952 adult patients receiving radiotherapy for HNC and who are at high risk for post-RT dysphagia. Participants will be randomized to receive one of three interventions for swallowing during RT: RE-ACTIVE, started promptly if/when dysphagia is identified; PRO-ACTIVE EAT, low intensity prophylactic intervention started before RT commences; or, PRO-ACTIVE EAT+EXERCISE, high intensity prophylactic intervention also started before RT commences. We hypothesize that the PRO-ACTIVE therapies are more effective than late RE-ACTIVE therapy; and, that the more intensive PRO-ACTIVE (EAT + EXERCISE) is superior to the low intensive PRO-ACTIVE (EAT). The primary endpoint of effectiveness is duration of feeding tube dependency one year post radiation therapy, selected as a pragmatic outcome valued equally by diverse stakeholders (e.g., patients, caregivers and clinicians). Secondary outcomes will include objective measures of swallow physiology and function, pneumonia and weight loss, along with various patient-reported swallowing-related outcomes, such as quality of life, symptom burden, and self-efficacy.

DISCUSSION

Dysphagia is a common and potentially life-threatening chronic toxicity of radiotherapy, and a priority issue for HNC survivors. Yet, the optimal timing and intensity of swallowing therapy provided by a speech-language pathologist is not known. With no clearly preferred strategy, current practice is fraught with substantial variation. The pragmatic PRO-ACTIVE trial aims to specifically address the decisional dilemma of when swallowing therapy should begin (i.e., before or after a swallowing problem develops). The critical impact of this dilemma is heightened by the growing number of young HNC patients in healthcare systems that need to allocate resources most effectively. The results of the PRO-ACTIVE trial will address the global uncertainty regarding best practice for dysphagia management in HNC patients receiving radiotherapy.

TRIAL REGISTRATION

The protocol is registered with the US Patient Centered Outcomes Research Institute, and the PRO-ACTIVE trial was prospectively registered at ClinicalTrials.gov , under the identifier NCT03455608 ; First posted: Mar 6, 2018; Last verified: Jun 17, 2021. Protocol Version: 1.3 (January 27, 2020).

Factors associated with complex oral treatment device usage in patients with head and neck cancer

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We studied complex oral treatment devices (COTDs) usage for head and neck cancer.

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SEER data (1992–2013) indicated use of COTDs increased from 36 to 67% of patients.

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COTD usage associated with age, gender, and geographic location of care.

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This is the first known study to use SEER data to analyze COTD usage.

Purpose

The objective was to identify clinical and epidemiological factors associated with utilization of a complex oral treatment device (COTD), which may decrease toxicity in patients undergoing radiation therapy for head and neck cancer (HNC).

Materials and Methods

We retrospectively reviewed data from 1992 to 2013 in the Surveillance, Epidemiology, and End Results (SEER)-Medicare databases to analyze COTD usage during intensity-modulated radiation therapy (IMRT) for patients diagnosed with cancer of the tongue, floor of mouth, nasopharynx, tonsil, or oropharynx. Patients with a radiation simulation and complex treatment device code within 4 weeks before the first IMRT claim were identified as meeting COTD usage criteria. Demographic, regional, tumor, and treatment data were analyzed.

Results

Out of 4511 patients who met eligibility criteria, 1932 patients (42.8%) did not utilize a COTD while 2579 (57.2%) met usage criteria. COTD utilization increased over time (36.36% usage in 1992 vs. 67.44% usage in 2013, p < .0001). Patients less likely to receive a COTD included those aged 86 years or older compared to those aged 66–70 (OR = 0.713, 95% CI: 0.528–0.962), male patients (OR = 0.817, 95% CI: 0.710–0.941), non-Hispanic Black patients compared to non-Hispanic White patients (OR = 0.750, 95% CI: 0.582–0.966), and Louisiana residents (OR = 0.367, 95% CI: 0.279–0.483). Cancer site, grade, stage, or function of IMRT had no significant association with COTD usage.

Conclusions

This study serves as the first known SEER-Medicare review of COTD utilization. Despite an increase in COTD usage over time, our results indicate age, gender, and geographic disparities are associated with utilization. Further research and development into methods that increase availability of COTDs may help increase utilization in specific patient populations.

Stability of MRI contrast agents in high-energy radiation of a 1.5T MR-Linac

BACKGROUND

Gadolinium-based contrast is often used when acquiring MR images for radiation therapy planning for better target delineation. In some situations, patients may still have residual MRI contrast agents in their tissue while being treated with high-energy radiation. This is especially true when MRI contrast agents are administered during adaptive treatment replanning for patients treated on MR-Linac systems.

PURPOSE

The purpose of this study was to analyze the molecular stability of MRI contrast agents when exposed to high energy photons and the associated secondary electrons in a 1.5T MR-Linac system. This was the first step in assessing the safety of administering MRI contrast agents throughout the course of treatment.

MATERIALS AND METHODS

Two common MRI contrast agents were irradiated with 7 MV photons to clinical dose levels. The irradiated samples were analyzed using liquid chromatography-high resolution mass spectrometry to detect degradation products or conformational alterations created by irradiation with high energy photons and associated secondary electrons.

RESULTS

No significant change in chemical composition or displacement of gadolinium ions from their chelates was discovered in samples irradiated with 7 MV photons at relevant clinical doses in a 1.5T MR-Linac. Additionally, no significant correlation between concentrations of irradiated MRI contrast agents and radiation dose was observed.

CONCLUSION

The chemical composition stability of the irradiated contrast agents is promising for future use throughout the course of patient treatment. However, in vivo studies are needed to confirm that unexpected metabolites are not created in biological milieus.

Predicting late symptoms of head and neck cancer treatment using LSTM and patient reported outcomes

Patient-Reported Outcome (PRO) surveys are used to monitor patients' symptoms during and after cancer treatment. Acute symptoms refer to those experienced during treatment and late symptoms refer to those experienced after treatment. While most patients experience severe symptoms during treatment, these usually subside in the late stage. However, for some patients, late toxicities persist negatively affecting the patient's quality of life (QoL). In the case of head and neck cancer patients, PRO surveys are recorded every week during the patient's visit to the clinic and at different follow-up times after the treatment has concluded. In this paper, we model the PRO data as a time-series and apply Long-Short Term Memory (LSTM) neural networks for predicting symptom severity in the late stage. The PRO data used in this project corresponds to MD Anderson Symptom Inventory (MDASI) questionnaires collected from head and neck cancer patients treated at the MD Anderson Cancer Center. We show that the LSTM model is effective in predicting symptom ratings under the RMSE and NRMSE metrics. Our experiments show that the LSTM model also outperforms other machine learning models and time-series prediction models for these data.

Methodologies to Increase the Level of Evidence of Real-life Proton Therapy in Head and Neck Tumors

This review aims to present and assess available and new methodologies to increase the clinical evidence of proton therapy data for patients with head and neck cancer. Despite the increasing number of scientific reports showing the feasibility and effectiveness of proton therapy in head and neck cancer, clinical evidence on the potential benefits of its use remains low for several reasons. In this article, the pros and cons of consolidated and new methodologies in this setting such as randomized clinical trials, the model-based approach, and the use of prospective multicentric registries will be detailed.

Radiomic biomarkers of tumor immune biology and immunotherapy response

Immunotherapies are leading to improved outcomes for many cancers, including those with devastating prognoses. As therapies like immune checkpoint inhibitors (ICI) become a mainstay in treatment regimens, many concurrent challenges have arisen - for instance, delineating clinical responders from non-responders. Predicting response has proven to be difficult given a lack of consistent and accurate biomarkers, heterogeneity of the tumor microenvironment (TME), and a poor understanding of resistance mechanisms. For the most part, imaging data have remained an untapped, yet abundant, resource to address these challenges. In recent years, quantitative image analyses have highlighted the utility of medical imaging in predicting tumor phenotypes, prognosis, and therapeutic response. These studies have been fueled by an explosion of resources in high-throughput mining of image features (i.e. radiomics) and artificial intelligence. In this review, we highlight current progress in radiomics to understand tumor immune biology and predict clinical responses to immunotherapies. We also discuss limitations in these studies and future directions for the field, particularly if high-dimensional imaging data are to play a larger role in precision medicine.

Trial Sponsorship and Time to Reporting for Phase 3 Randomized Cancer Clinical Trials

The pace of clinical trial data generation and publication is an area of interest within clinical oncology; however, little is known about the dynamics and covariates of time to reporting (TTR) of trial results. To assess these, ClinicalTrials.gov was queried for phase three clinical trials for patients with metastatic solid tumors, and the factors associated with TTR from enrollment completion to publication were analyzed. Based on the 319 included trials, cooperative-group-sponsored trials were reported at a slower rate than non-cooperative-group trials (median 37.5 vs. 31.0 months; p < 0.001), while industry-funded studies were reported at a faster rate than non-industry-supported trials (31.0 vs. 40.0 months; p = 0.005). Furthermore, successful trials (those meeting their primary endpoint) were reported at a faster rate than unsuccessful studies (27.5 vs. 36.0 months; p < 0.001). Multivariable analysis confirmed that industry funding was independently associated with a shorter TTR (p = 0.006), while cooperative group sponsorship was not associated with a statistically significant difference in TTR (p = 0.18). These data underscore an opportunity to improve cooperative group trial efficiency by reducing TTR.

A predictive model of radiation-related fibrosis based on the radiomic features of magnetic resonance imaging and computed tomography

Background

To establish a predictive model for the fibrotic level of neck muscles after radiotherapy by using radiomic features extracted from the magnetic resonance imaging (MRI) before and after radiotherapy and planning computed tomography (CT) in nasopharyngeal carcinoma patients.

Methods

A total of one hundred and eighty-six patients were finally enrolled in this study. According to the specific standard, all patients were divided into three different fibrosis groups. Regions of interests (ROI), including sternocleidomastoids (SCMs), trapezius (T), levator scapulae (LS), and scalenus muscles (S), were delineated manually and used for features extraction on IBEX. XGBoost, a machine learning algorithm, was used for the establishment of the prediction model. First, the patients were divided into training cohort (80%) and testing cohort (20%) randomly. Then the image features of CT or delta changes calculated from pre- and post-radiotherapy MRI images on each cohort constituted training and testing datasets. Then, based on the training dataset, a well-trained prediction model was produced. We used five-fold cross-validation to validate the predictive models. Afterward, the model performance was assessed on the ‘testing’ set and reported in terms of area under the receiver operating characteristic curve (AUC) under five scenarios: (I) only T1 sequence, (II) only T2 sequence, (III) only T1 post-contrast (T1 + C) sequence, (IV) Combination of all MRI sequences, (V) only CT.

Results

Most of the patients enrolled are male (73.1%), mean age was 47 years, receiving concurrent chemo-radiotherapy as the primary treatment (90.9%). By the end of the final follow-up, most of the patients were rated as mild fibrosis (60.8%). We found the prediction model based on the CT image features outperform all MRI features with an AUC of 0.69 and accuracy of 0.65. Contrarily, the model based on features from all MRI sequence showed lower AUC less than 0.5 and lower accuracy less than 0.6.

Conclusions

The prediction model based on CT radiomics features has better performance in the prediction of the grade of post-radiotherapy neck fibrosis. This might help guide radiotherapy treatment planning to achieve a better quality of life.

Prospective, longitudinal digital activity monitoring before and after treatment of low-risk oropharyngeal squamous cell carcinoma: A feasibility study

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Background: Given the expected excellent prognosis of low-risk oropharyngeal squamous cell carcinoma (OPSCC), consideration of long-term toxicity and functional outcomes has become increasingly important. Activity monitors (e.g. FITBIT) are imperfect but have been shown to have reasonable validity in healthy adults. Here we aimed to test the feasibility of using medical grade longitudinal digital activity monitoring to better define objective functional outcomes after treatment of low-risk OPSCC. Methods: This prospective, observational parallel cohort study included patients with previously untreated stage I-III (AJCC 7) OPSCC eligible for standard of care single-modality treatment with either Intensity-Modulated Proton Therapy (IMPT) or TransOral Robotic Surgery (TORS). Objective Actigraph accelerometer data (Actigraph, Pensacola, FL) were collected continuously for 1 week at baseline, 3, 6 and 12 months after treatment along with subjective patient-reported outcome (PRO) measures. Results: Forty-four patients (34M, 10F) enrolled with median age 59 years (range: 42-78). Baseline, 3 and 6 month activity data were available for 40 patients (91%): 16 IMPT and 24 TORS. There was a significant decrease in mean percent of day performing moderate to vigorous physical activity (MVPA) (-0.78, 0.021) mean number of steps/minute (-1.1, p = 0.035), and mean kcals/day (-115.9, p < 0.001) from baseline to 3 months after treatment for the overall cohort. A significant decrease in mean kcals/day (-82.2, p = 0.004) persisted for the overall cohort at 6 months with no significant difference between groups. Conclusions: Longitudinal digital activity monitoring is feasible before and after treatment of low-risk OPSCC. This approach may offer objective functional endpoints for future de-escalation trials. Similar short-term decreases in objective activity measurements were observed after IMPT and TORS. Long-term (12 month) activity data and correlations to subjective PRO measures will be available at the time of presentation. Clinical trial information: 02663583 .

Patterns of Failure After Intensity Modulated Radiation Therapy in Head and Neck Squamous Cell Carcinoma of Unknown Primary: Implication of Elective Nodal and Mucosal Dose Coverage

Purpose

We evaluated the geometric and dosimetric-based distribution of mucosal and nodal recurrences in patients with metastatic head and neck squamous cell carcinoma to cervical lymph nodes of unknown primary after intensity modulated radiation therapy using validated typology-indicative taxonomy.

Methods and Materials

We reviewed the data of 260 patients who were irradiated between 2000 and 2015 and had a median follow-up time for surviving patients of 61 months. The mucosal and nodal recurrences were manually delineated on computed tomography images demonstrating the recurrences. The images were overlaid on the treatment plan using deformable image registration. The locations of the recurrences were determined relative to the original planning target volumes and doses using centroid-based approaches. Subsequently, the pattern of failures were classified into 5 types based on combined spatial and dosimetric criteria: A (central high dose), B (peripheral high dose), C (central elective dose), D (peripheral elective dose), and E (extraneous dose). For patients with type A failure with simultaneous nontype A lesions, the overall pattern of failures was defined as type A.

Results

Thirty-two patients had mucosal or nodal recurrences. The most common clinical nodal stage was N2b (66%). Preradiation therapy neck dissections were performed in 6 patients. The median dose delivered to clinical tumor volume 1 was 66 Gy. The majority (84%) had total/partial pharyngeal mucosa elective irradiation. Twenty-three patients had nodal recurrences, 8 had mucosal recurrences, and 1 had both nodal and mucosal recurrences. Twenty-one patients (91%) had type A nodal failure, and 7 of the mucosal failures (89%) were type C.

Conclusions

The majority of nodal recurrences occurred within the high-dose area, demanding the need for identification of radioresistant areas within malignant nodes. Future studies should focus on either dose escalation of high-risk volumes or novel radiosensitizers.

Stability analysis of CT radiomic features with respect to segmentation variation in oropharyngeal cancer

INTRODUCTION

Accurate segmentation of tumors and quantification of tumor features are important for cancer detection, diagnosis, monitoring, and planning therapeutic intervention. Due to inherent noise components in multi-parametric imaging and inter-observer and intra-observer variations, it is common that various segmentation methods may produce large segmentation errors in tumor volumes and their associated radiomic features. The purpose of this study is to carry out the stability analysis for radiomic features with respect to segmentation variation in oropharyngeal cancer (OPC).

METHODS

In this study, 436 contrast-enhanced computed tomography (CT) axial images were collected from patients with OPC. In order to derive various segmentations of tumor volumes, two additional segmentations were obtained via resizing the original segmented regions of interest (ROIs) based on their geometric information on the boundary. For three ROI image groups, we calculated 109 radiomic features. Then, a logistic regression model was built to investigate the correlation between the radiomic features extracted from GTVp and the response to chemotherapy and radiation in terms of overall survival (OS). Finally, in order to evaluate the stability of each feature with respect to segmentation results, based on the prediction probabilities, we assessed the inter-rater reliability and reproducibility by calculating the intra-class correlation coefficients (ICC) and concordance correlation coefficients (CCC).

RESULTS

Most radiomic features in this study varied a lot when the ROIs were not well segmented. For both the representation agreement and predictive agreement, the ICC and CCC were below 0.5 for all the features. We still found some robust features with relatively high ICC and CCC compared to most features. For example, 25percentile (ICC = 0.38, CCC = 0.37 in representation agreement and ICC = CCC = 0.27 in predictive agreement) is a quantile based feature, which is robust to the extremely high or low values; and Hu_1_std (ICC = 0.31, CCC = 0.31 in representation agreement) is a feature calculated based on the first Hu moment, which is invariant to the transformation of ROIs.

CONCLUSION

In OPC studies, the tumor segmentation variation affects the radiomic features from CT images in terms of both representation and prediction. Some features that are robust to the extreme values or invariant to the transformation of ROIs may be treated as radiomic markers to assist with OPC treatment monitoring and prognostic prediction.

A spatial neighborhood methodology for computing and analyzing lymph node carcinoma similarity in precision medicine

Precision medicine seeks to tailor therapy to the individual patient, based on statistical correlates from patients who are similar to the one under consideration. These correlates can and should go beyond genetics, and in general, beyond tabular or array data that can be easily represented computationally and compared. For example, in many types of cancer, cancer treatment and toxicity depend in large measure on the spatial disease spread-e.g., metastasizes to regional lymph nodes in head and neck cancer. However, there is currently a lack of methodology for integrating spatial information when considering patient similarity. We present a novel modeling methodology for the comparison of cancer patients within a cohort, based on the spatial spread of the lymph nodes affected in each patient. The method uses a topological map, bigrams, and hierarchical clustering to group patients based on their similarity. We compare this approach against a nonspatial (categorical) similarity approach where patients are binned solely by their affected nodes. We present similarity results on a 582 head and neck cancer patient cohort, along with two visual abstractions for analysis of the results, and we present clinician feedback. Our novel methodology partitions a patient cohort into clinically meaningful groups more susceptible to treatment side-effects. Such spatially-aware similarity approaches can help maximize the effectiveness of each patient's treatment.

CD8 infiltration is associated with disease control and tobacco exposure in intermediate-risk oropharyngeal cancer

Oropharyngeal squamous cell carcinoma (OPSCC) incidence is increasing at a nearly epidemic rate, largely driven by the human papillomavirus (HPV). Despite the generally favorable clinical outcomes of patients with HPV driven (HPV+) OPSCC, a significant subset of HPV tumors associated with tobacco exposure have diminished treatment response and worse survival. The tumor immune microenvironment (TIME) has been shown to be a critical driver of treatment response and oncologic outcomes in OPSCC generally and HPV+ OPSCC more specifically. However, the impact of tobacco exposure on the TIME in OPSCC patients remains unclear. We analyzed the relationship between TIME, tobacco exposure and clinical outcomes in OPSCC patients (n = 143) with extensive tobacco exposure (median pack-years = 40). P16 overexpression, a surrogate marker of HPV association, was a strong predictor of relapse-free (RFS) and overall survival (OS) (p < 0.001, p < 0.001 respectively) regardless of tobacco exposure and associated strongly with differential infiltration of the tumor by both CD3 and CD8 lymphocytes measured via immunohistochemistry (p < 001, p < 0.001 respectively). CD3 and CD8 infiltration was a strong predictor of RFS and OS and associated strongly with disease stage (AJCC 8th Edition Staging Manual). Tobacco exposure correlated significantly (p < 0.001) with decreased CD8 infiltration in p16+ OPSCC tumors. Our findings demonstrate that the HPV+ OPSCC clinical outcomes are strongly correlated with the TIME, which is potentially modulated by tobacco exposure. Immunomodulatory strategies targeting this disease in smokers must take into consideration the potential modifying effects of tobacco exposure on treatment effectiveness and clinical outcomes.

Cohort-based T-SSIM Visual Computing for Radiation Therapy Prediction and Exploration

We describe a visual computing approach to radiation therapy (RT) planning, based on spatial similarity within a patient cohort. In radiotherapy for head and neck cancer treatment, dosage to organs at risk surrounding a tumor is a large cause of treatment toxicity. Along with the availability of patient repositories, this situation has lead to clinician interest in understanding and predicting RT outcomes based on previously treated similar patients. To enable this type of analysis, we introduce a novel topology-based spatial similarity measure, T-SSIM, and a predictive algorithm based on this similarity measure. We couple the algorithm with a visual steering interface that intertwines visual encodings for the spatial data and statistical results, including a novel parallel-marker encoding that is spatially aware. We report quantitative results on a cohort of 165 patients, as well as a qualitative evaluation with domain experts in radiation oncology, data management, biostatistics, and medical imaging, who are collaborating remotely.

Imaging for Response Assessment in Radiation Oncology: Current and Emerging Techniques

Imaging in radiation oncology is essential for the evaluation of treatment response in tumors and organs at risk. This influences further treatment decisions and could possibly be used to adapt therapy. This review article focuses on the currently used imaging modalities for response assessment in radiation oncology and gives an overview of new and promising techniques within this field.

Imaging for Target Delineation and Treatment Planning in Radiation Oncology: Current and Emerging Techniques

Imaging in radiation oncology has a wide range of applications. It is necessary not only for tumor staging and treatment response assessment after therapy but also for the treatment planning process, including definition of target and organs at risk, as well as treatment plan calculation. This article provides a comprehensive overview of the main imaging modalities currently used for target delineation and treatment planning and gives insight into new and promising techniques.