Prevention and Management of Osteoradionecrosis in Patients With Head and Neck Cancer Treated With Radiation Therapy: ISOO-MASCC-ASCO Guideline

PURPOSE

To provide evidence-based recommendations for prevention and management of osteoradionecrosis (ORN) of the jaw secondary to head and neck radiation therapy in patients with cancer.

METHODS

The International Society of Oral Oncology-Multinational Association for Supportive Care in Cancer (ISOO-MASCC) and ASCO convened a multidisciplinary Expert Panel to evaluate the evidence and formulate recommendations. PubMed, EMBASE, and Cochrane Library databases were searched for randomized controlled trials and observational studies, published between January 1, 2009, and December 1, 2023. The guideline also incorporated systematic reviews conducted by ISOO-MASCC, which included studies published from January 1, 1990, through December 31, 2008.

RESULTS

A total of 1,539 publications were initially identified. There were 487 duplicate publications, resulting in 1,052 studies screened by abstract, 104 screened by full text, and 80 included for systematic review evaluation.

RECOMMENDATIONS

Due to limitations of available evidence, the guideline relied on informal consensus for some recommendations. Recommendations that were deemed evidence-based with strong evidence by the Expert Panel were those pertaining to best practices in prevention of ORN and surgical management. No recommendation was possible for the utilization of leukocyte- and platelet-rich fibrin or photobiomodulation for prevention of ORN. The use of hyperbaric oxygen in prevention and management of ORN remains largely unjustified, with limited evidence to support its practice.Additional information is available at www.asco.org/head-neck-cancer-guidelines.

International Expert-Based Consensus Definition, Staging Criteria, and Minimum Data Elements for Osteoradionecrosis of the Jaw: An Inter-Disciplinary Modified Delphi Study

Purpose

Osteoradionecrosis of the jaw (ORNJ) is a severe iatrogenic disease characterized by bone death after radiation therapy (RT) to the head and neck. With over 9 published definitions and at least 16 diagnostic/staging systems, the true incidence and severity of ORNJ are obscured by lack of a standard for disease definition and severity assessment, leading to inaccurate estimation of incidence, reporting ambiguity, and likely under-diagnosis worldwide. This study aimed to achieve consensus on an explicit definition and phenotype of ORNJ and related precursor states through data standardization to facilitate effective diagnosis, monitoring, and multidisciplinary management of ORNJ.

Methods

The ORAL Consortium comprised 69 international experts, including representatives from medical, surgical, radiation oncology, and oral/dental disciplines. Using a web-based modified Delphi technique, panelists classified descriptive cases using existing staging systems, reviewed systems for feature extraction and specification, and iteratively classified cases based on clinical/imaging feature combinations.

Results

The Consortium ORNJ definition was developed in alignment with SNOMED-CT terminology and recent ISOO-MASCC-ASCO guideline recommendations. Case review using existing ORNJ staging systems showed high rates of inability to classify (up to 76%). Ten consensus statements and nine minimum data elements (MDEs) were outlined for prospective collection and classification of precursor/ORNJ stages.

Conclusion

This study provides an international, consensus-based definition and MDE foundation for standardized ORNJ reporting in cancer survivors treated with RT. Head and neck surgeons, radiation, surgical, medical oncologists, and dental specialists should adopt MDEs to enable scalable health information exchange and analytics. Work is underway to develop both a human- and machine-readable knowledge representation for ORNJ (i.e., ontology) and multidisciplinary resources for dissemination to improve ORNJ reporting in academic and community practice settings.

Development and implementation of optimized endogenous contrast sequences for delineation in adaptive radiotherapy on a 1.5T MR-linear-accelerator: a prospective R-IDEAL stage 0-2a quantitative/qualitative evaluation of in vivo site-specific quality-assurance using a 3D T2 fat-suppressed platform for head and neck cancer

Purpose

To improve segmentation accuracy in head and neck cancer (HNC) radiotherapy treatment planning for the 1.5T hybrid magnetic resonance imaging/linear accelerator (MR-Linac), three-dimensional (3D), T2-weighted, fat-suppressed magnetic resonance imaging sequences were developed and optimized.

Approach

After initial testing, spectral attenuated inversion recovery (SPAIR) was chosen as the fat suppression technique. Five candidate SPAIR sequences and a nonsuppressed, T2-weighted sequence were acquired for five HNC patients using a 1.5T MR-Linac. MR physicists identified persistent artifacts in two of the SPAIR sequences, so the remaining three SPAIR sequences were further analyzed. The gross primary tumor volume, metastatic lymph nodes, parotid glands, and pterygoid muscles were delineated using five segmentors. A robust image quality analysis platform was developed to objectively score the SPAIR sequences on the basis of qualitative and quantitative metrics.

Results

Sequences were analyzed for the signal-to-noise ratio and the contrast-to-noise ratio and compared with fat and muscle, conspicuity, pairwise distance metrics, and segmentor assessments. In this analysis, the nonsuppressed sequence was inferior to each of the SPAIR sequences for the primary tumor, lymph nodes, and parotid glands, but it was superior for the pterygoid muscles. The SPAIR sequence that received the highest combined score among the analysis categories was recommended to Unity MR-Linac users for HNC radiotherapy treatment planning.

Conclusions

Our study led to two developments: an optimized, 3D, T2-weighted, fat-suppressed sequence that can be disseminated to Unity MR-Linac users and a robust image quality analysis pathway that can be used to objectively score SPAIR sequences and can be customized and generalized to any image quality optimization protocol. Improved segmentation accuracy with the proposed SPAIR sequence will potentially lead to improved treatment outcomes and reduced toxicity for patients by maximizing the target coverage and minimizing the radiation exposure of organs at risk.

Prevalence and implications of significance testing for baseline covariate imbalance in randomised cancer clinical trials: The Table 1 Fallacy

BACKGROUND

The 'Table 1 Fallacy' refers to the unsound use of significance testing for comparing the distributions of baseline variables between randomised groups to draw erroneous conclusions about balance or imbalance. We performed a cross-sectional study of the Table 1 Fallacy in phase III oncology trials.

METHODS

From ClinicalTrials.gov, 1877 randomised trials were screened. Multivariable logistic regressions evaluated predictors of the Table 1 Fallacy.

RESULTS

A total of 765 randomised controlled trials involving 553,405 patients were analysed. The Table 1 Fallacy was observed in 25% of trials (188 of 765), with 3% of comparisons deemed significant (59 of 2353), approximating the typical 5% type I error assertion probability. Application of trial-level multiplicity corrections reduced the rate of significant findings to 0.3% (six of 2345 tests). Factors associated with lower odds of the Table 1 Fallacy included industry sponsorship (adjusted odds ratio [aOR] 0.29, 95% confidence interval [CI] 0.18-0.47; multiplicity-corrected P < 0.0001), larger trial size (≥795 versus <280 patients; aOR 0.32, 95% CI 0.19-0.53; multiplicity-corrected P = 0.0008), and publication in a European versus American journal (aOR 0.06, 95% CI 0.03-0.13; multiplicity-corrected P < 0.0001).

CONCLUSIONS

This study highlights the persistence of the Table 1 Fallacy in contemporary oncology randomised controlled trials, with one of every four trials testing for baseline differences after randomisation. Significance testing is a suboptimal method for identifying unsound randomisation procedures and may encourage misleading inferences. Journal-level enforcement is a possible strategy to help mitigate this fallacy.

Stereotactic Boost and Short-Course Radiotherapy for p16-Associated Oropharynx Cancer (SHORT-OPC): First Planned Interim Safety Analysis from a Randomized Phase II Trial

PURPOSE/OBJECTIVE(S)

There is a need for safe treatment de-intensification in p16+ oropharynx cancer (OPC). The standard of care (SOC) radiotherapy (RT) regimen is cumbersome and associated with high toxicity. Stereotactic radiotherapy (SBRT) and multimodality image guidance is an opportunity to precisely target the gross tumor while safely reducing elective irradiation dose. We aim to assess the safety and efficacy of a short course RT for p16+ OPC, consisting of an SBRT boost to the gross tumor volume (GTV) followed by de-escalated elective irradiation.

MATERIALS/METHODS

In this randomized phase II trial, patients with p16-positive, stage I-II OPSCC with primary tumor <30 cc (8th Ed AJCC) are planned with combined CT, MRI and FDG-PET, and randomized to 1) SBRT boost (14 Gy in 2 fractions) to the GTV followed with de-escalated RT (+/- Cisplatin) to a dose of 40 Gy in 20 fractions, or 2) SOC RT (+/- Cisplatin) to a dose of 70 Gy in 33 fractions to the GTV and 59.4-54Gy (or equivalent) to the intermediate-to-low dose elective region. Patients are stratified by stage (I vs. II) and use of chemotherapy. The primary endpoint of the trial is locoregional control at 2 years, powered for a sample size of 100 patients. A Bayesian adaptive design includes 2 planned safety interim analysis using grade ≥ 3 subacute toxicities >40% as a stopping criterion, and 1 planned futility analysis. Acute adverse events (AE) are defined as those occurring ≤ 60 days from RT, subacute AE between 60-180 days after RT, and late AE >180 days from RT. This is the first planned toxicity analysis.

RESULTS

Twenty-one patients were randomly assigned and eligible (11 in SOC and 10 in experimental arm). Median age was 69 years (range 49-84); 29% and 71% had stage T1 and T2, while 10%, 85% and 1 patient had N0, N1 and N2 disease, respectively. RT alone and chemoradiation was administered in 67% and 33% of patients, respectively. At a median follow-up of 11 months (range 1.7-17.6), there was 1 local recurrence at the primary tumor site in the SOC arm (at 10 month) and no recurrence in the experimental arm. All enrolled patients remain alive at the time of analysis. There was a 54.5% rate of grade 3 acute AE in the SOC arm and 30.0% rate of grade 3 acute AE in the experimental arm. More specifically, 1, 5 (45%), 2 (18%), and 2 (18%) versus 0, 1, 1 and 1 patient developed acute grade 3 dysphagia, mucositis, pain and dermatitis in the SOC and experimental arm, respectively. There was no acute grade 4 or 5 toxicity. There was no grade ≥ 3 subacute toxicity or late toxicity in both arms.

CONCLUSION

This primary safety analysis showed that SBRT boost followed by a short course of de-escalated elective irradiation in p16+ OPC has limited early toxicity and meets criteria for study continuation.

Dynamic Contrast Enhanced MRI as a Biomarker of Tumor Response and Oncologic Outcomes in Head and Neck Cancer: Results of a Single Institution Prospective Imaging Study

PURPOSE/OBJECTIVE(S)

We aim to determine the correlation between vascular parameters of Dynamic contrast enhanced (DCE) MRIs and tumor response and outcomes in head and neck (HNC) patients treated with definitive radiation therapy (RT).

MATERIALS/METHODS

Eighty-two HNC patients are included in this prospective study in one institute. All patients had malignant head and neck neoplasm indicative of curative- intent treatment. Patients were imaged using MRIs pre-, mid-, and post-RT completion at 8-12 weeks. T2-weighted sequences were used for tumor contouring then it was co-registered to respective DCE images. The response to treatment was checked at mid-radiotherapy (mid-RT) and at the end of RT. Mid-RT MRI was co-registered to baseline images and the manually segmented baseline primary tumor regions of interest were propagated to mid-RT images. Quantitative maps (Ktrans, Kep, Ve and Vp) were generated with the extended Tofts pharmacokinetic models and were used for analysis. These vascular parameters were presented as a mean value and percentile using histogram analysis and the following parameters were extracted using an in-house programming environment script: mean, 5th, 10th, 20th, 30th, 40th, 50th (i.e., median), 60th, 70th, 80th, 90th, 95th percentile. The non-parametric Wilcoxon signed-rank test was used to assess the changes of mid-RT DCE parameters compared to baseline. Recursive partitioning analysis (RPA) was used to identify the delta DCE threshold associated with relapse. We assessed the identified thresholds' correlation with oncological and survival endpoints using Cox regression with and without standard clinical variables.

RESULTS

The median age for patients is 61 years old (33-78 range). Never smokers are 39 (47%), 35 (43%) are former smoker and 8 (10%) are current smoker with a mean value of 14 pack per year and 26 standard deviations. Using AJCC 8th edition, 39 (47%) are stage I and 19 (23%) are stage II and stage III and IV are 15 (18%) and 9 (10%) respectively. HPV positive are 72 (88%). For patients with GTV-P at baseline (n = 60), 11 (18%) had mid-RT CR at the primary site which increased to 50 (83%) post-RT. The LC and RFS for the entire cohort were 91.4%, and 79.2% respectively. In GTV-P, none of the pre-radiotherapy DCE parameters were correlated with LC or RFS. Wilcoxon signed rank test was statistically significant in 80, 90 and 95 percentiles with (p<0.05). RPA analysis identified different thresholds for each DCE parameter, and its inclusions to the multivariate model improved its performance. In GTV-P, RPA analysis identified ΔKtrans 40 percentiles >15.6% at mid-RT as the most significant point. When this value of ΔKtrans added to the multivariate analysis it was associated with a significantly better model performance in RFS (p = 0.00001).

CONCLUSION

DCE parameters are a very promising tool to correlate with response and outcomes in H&N cancer patients. Future work is warranted for external validation of our findings.

Clinical Acceptability of Automatically Generated Elective Lymph Node Volumes for Head and Neck Cancer Patients

PURPOSE/OBJECTIVE(S)

Manual contouring of head and neck lymph node levels is a time-intensive process prone to provider-specific variation. The purpose of this work is to generate a clinical segmentation tool while minimizing the amount of manual effort required by physicians to develop training datasets and review contours. Here we investigate an approach to curate, develop, and clinically validate an auto-contouring model for standard cervical lymph node volumes in the head and neck using a publicly available deep learning architecture. This model updates our previously validated tool to reflect modern practices in lymph node segmentation.

MATERIALS/METHODS

With the assistance of a resident physician, five radiation oncologists manually contoured individual lymph node levels on CT scans for three separate patients treated definitively with radiation or chemoradiation for oropharynx cancer, resulting in 15 unique ground truth cases. These cases were then used to train an nnUnet deep-learning model to generate automated contours for 32 additional cases. These 32 cases were reviewed, manually edited, and used to create the final model. Finally, the model was used to generate contours on the original 15 CT scans (testing cohort), and providers compared these automated contours with the ground-truth (manual) contours. Two blinded studies were performed. In a double-blinded fashion, providers were first asked to select which set of contours they would prefer to use in clinical practice as a starting point for actual cases. Second, they scored each contour on a Likert scale (1-5) to indicate clinical acceptability, ranging from completely unusable to usable without modification.

RESULTS

Across all lymph node levels (IA, IB, II, III, IV, V, RP), average Dice Similarity Coefficient ranged from 0.77 to 0.89 for AI vs manual contours in the testing cohort. These AI and manual lymph node contours were reviewed by 5 physicians each, resulting in 525 preference scores. Across all lymph nodes, the AI contour was superior to or equally preferred to the manual contours at rates ranging from 75% to 91% in the first blinded study. In the second blinded study, physician preference for the manual vs AI contour was statistically different for only the RP contours (p < 0.01). Thus, there was not a significant difference in clinical acceptability for nodal levels I-V for manual versus AI contours. Across all physician-generated contours, 82% were rated as usable with stylistic to no edits, and across all AI-generated contours, 92% were rated as usable with stylistic to no edits.

CONCLUSION

An approach to generate clinically acceptable automated contours for cervical lymph node levels in the head and neck was demonstrated. Furthermore, for nodal levels I-V, there was no significant difference in clinical acceptability in manual vs AI contours. Because we were able to generate and validate a model for each lymph node level individually, the output is applicable to a complete range of disease in which cervical lymph nodes are treated.

Natural History and Clinical/Dosimetric Determinants of Osteoradionecrosis in a Large Cohort of Head and Neck Cancer Following Curative Radiotherapy: Debunking the Myth of Decreased Rates of Osteoradionecrosis in the Modern Radiotherapy Era

PURPOSE/OBJECTIVE(S)

Osteoradionecrosis (ORN) of the mandible is the most devastating toxicity following head and neck cancer (HNC) radiotherapy (RT). The rate of ORN occurrence has been debatable in the modern era of advanced RT. We aim to determine the natural history and time to ORN development in a large cohort of HNC.

MATERIALS/METHODS

After IRB approval, we identified HNC patients treated with curative-intent RT between 2005 and 2020 at MD Anderson Cancer Center. Dental oncology notes were reviewed and all dental procedures were recorded. Available dose volume histograms (DVHs) for the segmented mandibular volumes were extracted. Based on our previously published ORN normal tissue complication probability (NTCP) model, any dental procedure pre-RT is a clinical high-risk factor and, therefore, data were coded as (high vs. low clinical risk) accordingly. We also coded the dosimetric risk factors to (high vs. low dosimetric risk) according to our published DVH thresholds (high dosimetric risk if any applies: V45≥40%, V55≥25%, and/or D30 ≥40 Gy). Finally, patients were classified to four groups according to combined clinical and dosimetric risk factors (No, clinical, dosimetric, and both). We used the Kaplan-Meier method to calculate time to ORN development and ORN-free survival. For time to ORN development, any grade ORN occurrence was coded as event and all others were censored. For ORN-free survival, death and ORN were coded as events and all others were censored. Log-rank test was used to compared curves of different risk groups.

RESULTS

One thousand eight hundred sixty-six patients were included. Median follow-up was 38 months (range 4-162). ORN was reported in 252 patients (13.5%). The median time to ORN development was 18.5 months (range 4-145). 95 patients (37.7%) developed ORN after 2-years post-RT. The 1-, 3-, and 5-year ORN rates were 4.7%, 12.7%, and 17.8%, respectively. The 1-, 3-, and 5-year ORN-free survival were 94.3%, 85.5%, and 80.3%, respectively. There were statistically significant differences (P < 0.0001) between ORN-free survival in different clinical/dosimetric risk factors. The patients with no, clinical-only, dosimetric-only, and both clinical and dosimetric risk factors were 35%, 19%, 22%, and 24%, respectively. The 5-year ORN-free survival was 94.3%, 89.8%, 76.3%, and 69.6% for patients with no, clinical-only, dosimetric-only, and both clinical and dosimetric risk factors, respectively. The hazard-ratio (HR) of ORN development in clinical-only, dosimetric-only, and both clinical and dosimetric risk groups was 2.1, 5.4, and 7.5 compared to the no risk group (P<0.05 for all).

CONCLUSION

Our findings indicate that ORN remains a remarkable toxicity hazard for HNC survivors. A prolonged surveillance time is required for the majority of HNC survivor since more than one-third of the ORN events occurred after 2-year follow-up. Patients with combined clinical and dosimetric risk factors have a staggering ORN risk profile and are proper candidates for future prophylactic pharmacotherapy clinical studies.

Longitudinal Monitoring of Quantitative Imaging Kinetics of Primary Tumor and Nodal Volumes Using the MR-Linac Device in Head and Neck Cancer Patients

PURPOSE/OBJECTIVE(S)

We aim to characterize the serial quantitative apparent diffusion coefficient (ADC) changes of the target disease volume using diffusion-weighted imaging (DWI) acquired weekly during radiation therapy (RT) on a 1.5T MR-Linac and correlate these changes with tumor response and oncologic outcomes for head and neck squamous cell carcinoma (HNSCC) patients.

MATERIALS/METHODS

Thirty patients with pathologically confirmed HNSCC and received curative-intent RT at the University of Texas MD Anderson Cancer Center, were included in this prospective study. Baseline and weekly MRIs (weeks 1-6) were obtained, and various ADC parameters (mean, 5th, 10th, 20th, 30th, 40th, 50th, 60th, 70th, 80th, 90th and 95th percentile) were extracted from the target regions of interest (ROIs). Pre-RT and weekly ADC parameters were correlated with response during RT, loco-regional control, and the development of relapse using the Mann-Whitney U test. The Wilcoxon signed-rank test was used to compare the weekly ADC versus baseline values. Weekly volumetric changes (Δvolume) for each ROI were correlated with ΔADC using Spearman's Rho test. Recursive partitioning analysis (RPA) was performed to identify the optimal ΔADC threshold associated with different oncologic outcomes.

RESULTS

There was an overall significant rise in all ADC parameters during different time points of RT compared to baseline values for both GTV-P & GTV-N. The increased ADC values for GTV-P were statistically significant only for primary tumors achieving CR during RT. RPA identified GTV-P ΔADC 5th percentile >13% at the 3rd week of RT as the most significant parameter associated with CR for GTV-P during RT (p <0.001). Baseline ADC parameters didn't significantly correlate with response to RT or other oncologic outcomes. There was a significant decrease in residual volume of both GTV-P & GTV-N throughout the course of RT. Additionally, a significant negative correlation between mean ΔADC and Δvolume for GTV-P at the 3rd and 4th week of RT was detected (r = -0.39, p = 0.044 & r = -0.45, p = 0.019, respectively).

CONCLUSION

Assessment of ADC kinetics at regular intervals throughout RT is potentially able to predict the response to RT and oncologic outcome. Further studies with larger cohorts and multi-institutional data are needed for validation of our results.

Deep Learning Based Prognostic Prediction in Oropharyngeal Cancer Patients Using Multiparametric MRI Inputs

PURPOSE/OBJECTIVE(S)

While prognostic outcomes for oropharyngeal cancer (OPC) patients have improved in recent years, patients still face a non-negligible risk of disease recurrence or death. Accurately predicting post-therapy prognosis would be highly valuable for risk stratification and treatment guidance for OPC patients. Recent studies using PET/CT data have demonstrated the effectiveness of large-scale, end-to-end image-based deep learning (DL) models for predicting progression-free survival (PFS) in OPC patients. Multiparametric MRI (mpMRI), which combines anatomical and functional MRI sequences, has the potential to offer similar results, and has the added advantage of high-frequency longitudinal imaging capabilities, such as through MR-Linac devices. Therefore, this study aimed to develop a DL model using mpMRI data to predict PFS, and to evaluate the impact of anatomical and functional input channels on model performance.

MATERIALS/METHODS

From a large-scale head and neck cancer database at MD Anderson Cancer Center, treatment-naïve OPC patients with available pre-radiotherapy mpMRI imaging were selected for this study. mpMRI images used for this study included T2-weighted images (T2) and apparent diffusion coefficient (ADC) maps. PFS event status was defined as having either a local, regional, or distant failure, and/or death; data were right censored if an event had not occurred. Images were resampled to the T2 resolution, normalized to a [-1,1] scale, and cropped to the field of view of the ADC image for use in DL models. A DL convolutional neural network model based on the DenseNet121 architecture from the Medical Open Network for AI (MONAI) Python package using a negative log-likelihood loss function was implemented. The model used mpMRI images as input channels and 20 output channels representing the different time intervals of the predicted PFS conditional probabilities of surviving that time interval; final PFS in days was obtained by summing the cumulative probability of surviving each interval times the interval duration. A 5-fold cross validation approach was used for model training and evaluation. Separate models using only T2, only ADC, and T2 + ADC channel inputs were compared. Model performance was measured using the C-index.

RESULTS

Out of 1154 patients, 404 met inclusion criteria. The overall PFS event rate was 16%. Median C-index values from the 5-fold cross validation were 0.62, 0.67, and 0.69 for the ADC, T2, and T2+ADC models, respectively.

CONCLUSION

Using large-scale datasets and open-source DL implementations, we find that OPC PFS prediction models using mpMRI data yield modest but comparable performance to existing models (i.e., state-of-the-art reference performance using PET/CT). Moreover, combining mpMRI channels may increase the performance of models for OPC prognostic prediction. Future work will involve integration of additional timepoints, additional mpMRI images, clinical variables, and saliency maps.

Assessment of Dynamic Contrast Enhanced (DCE) MRI for Detection of Radiotherapy Induced Alteration in Mandibular Vasculature

PURPOSE/OBJECTIVE(S)

We aim to determine the kinetics of DCE-MRI changes in various mandibular risk volumes based on radiation (RT) dose received.

MATERIALS/METHODS

Eighty-eight head and neck cancer (HNC) patients (Pts) who underwent definitive RT were enrolled in this prospective study after IRB approval and informed consent. Images were acquired at pre-RT (Baseline), 3 weeks after RT start date (Mid-RT), 3 mos post-RT (PostRT1), and 6 mos post-RT (PostRT2). Manually segmented mandibular volumes on T2-weighted images were propagated to co-registered DCE-MRIs. Planning CTs and dose grids were also co-registered to corresponding baseline T2 images to create 3-D dose subvolumes. These were used to create 3 risk subvolumes; <30 Gy, 30-50 Gy, and >50 Gy ROIs. DCE images of different timepoints (TPs) were deformably co-registered and the dose subvolumes were propagated to each TP. We used the extended-Tofts model to generate the vascular quantitative maps (Ktrans and Ve). Each subvolume histogram parameters were extracted at each TP. Wilcoxon Signed Rank test was used to compare the changes at different TPs compared to baseline. We classified Pts' delta parameters at different TPs -based on our prior extensive QA assessment- into Pts with stable vascular profile (±25% change), Pts with significant increase (>25% change) and Pts with significant decrease (<-25%). Chi-square test was used to assess the change at different TPs.

RESULTS

For <30 Gy subvolumes, there were no significant changes (p > 0.05) in the studied DCE parameters at all TPs except a significant decrease (p < 0.001) in median Ktrans at PostRT2. For 30-50 Gy subvolumes, there was a significant increase in median Ktrans that started at MidRT (p = 0.006) and continued at PostRT1 (p = 0.04) but recovered to baseline values at PostRT2. Median Ve on the other hand only showed significant increase at PostRT1 (p = 0.001), but other TPs were not significantly different compared to baseline. Similarly, subvolumes >50 Gy showed same kinetics as in 30-50 Gy with significant increase of Ktrans at MidRT and PostRT1 and significant increase in Ve in only PostRT1 (P <0.05). For <30 Gy, there was significant increase in the number of Pts with stable or decrease in Ktrans at PostRT2 compared to earlier TPs (70% vs. 60% at PostRT1 and 54% at MidRT p = 0.003). 30-50 Gy subvolumes showed similar profile like <30 Gy with significant increase in the percentage of Pts with recovery at PostRT2. However, for >50 Gy, there was no significant increase in the number of Pts who recovered at PostRT2 (p = 0.3). Ve showed no significant increase in the percentage of Pts with recovery at different TPs (p > 0.05).

CONCLUSION

Results showed that for all dose mandibular subvolumes, there is an acute vascular insult that tends to recover at +6 months post-RT except for a selective group of patients who continue to have persistence of the vascular insult at high dose subvolumes. These findings are of importance for future selection of high risk population for prophylactic intervention against osteoradionecrosis.

Fractionated Stereotactic Radiotherapy in the Management of Dural Recurrence of Olfactory Neuroblastoma

PURPOSE/OBJECTIVE(S)

Treatment protocols for dural recurrence among esthesioneuroblastoma patients have not been standardized. We assess the outcomes of fractionated stereotactic radiotherapy (FSR) for patients with olfactory neuroblastoma (ONB) dura-based recurrences.

MATERIALS/METHODS

We identified ONB patients with dura-based recurrences treated with FSR after prior radiotherapy who were enrolled between 2013 and 2022 in our prospective head and neck reirradiation and skull base registries. In-field tumor control (within 2 cm of prescribed radiotherapy volume) and out-of-field tumor control (non-contiguous or contralateral dura, nodal, or distant metastases) were analyzed.

RESULTS

Thirteen patients with 28 dural lesions were included in this analysis. All patients were initially treated with surgery to their primary paranasal sinus disease; 69% with a craniofacial approach followed by adjuvant radiotherapy to a median dose of 63 Gy (range 60-72.4 Gy) prescribed to the resected tumor bed. Patients re-presented with dural recurrence at median 58.3 months (range 35.0 - 163.0 months) from completion of their initial treatment. Two patients underwent dural resections. On presentation of recurrence, 4 patients had 1 lesion treated, with a median of 2 lesions treated (range 1-4 lesions). All dural based tumors were treated with FSR to a median dose of 27 Gy in 3 fractions delivered QOD. 68Ga-DOTATATE PET/CT was utilized for FSR treatment planning in 31% of cases. The median follow up from FSR was 23.3 months (range: 13.1 - 51.6 months). The 1-year overall survival and progression free survival was 75% and 38%, respectively. The 1- and 2-year in-field control rate was 85% and 75%, respectively. Among treated lesions, 25 of 28 (89%) responded or remained stable following FSR. Two patients (3 lesions) had evidence of in-field radiographic progression at 17 and 9 months, respectively. Five patients (38%) experienced progression in the contralateral or non-contiguous dura, and 5 patients (38%) developed distant metastases. The overall out-of-field progression rate was 58% at 1 year. There was no grade 3 or higher toxicity observed. Three patients (23%) developed asymptomatic changes on MRI consistent with brain necrosis, all of which occurred in a previously irradiated region.

CONCLUSION

In the largest single institution study of FSR reirradiation for ONB dural recurrence to date, high local control rates with minimal toxicity are attainable. However, subsequent out-of-field dural recurrences and/or distant metastases remain problematic.

Evolution of the MOMENTUM Study for Evidence-Based Implementation of MR-Guided Radiotherapy Using the 1.5 Tesla MR-Linac

PURPOSE/OBJECTIVE(S)

The international prospective 'Multiple Outcome Evaluation of Radiation Therapy Using the MR-Linac' (MOMENTUM) study (NCT04075305) was initiated in 2019 by seven hospitals and industry partner precision radiation medicine company, with the aim to facilitate evidence-based implementation of magnetic resonance (MR) guided radiotherapy using the 1.5 Tesla (T) MR-linear accelerator (Linac). Over the last four years, MOMENTUM has expanded to other institutions and the design and organization of MOMENTUM have evolved. Herein, we give an overview of the current status of MOMENTUM and study innovations that have been implemented to accelerate development and assessment of the 1.5T MR-Linac.

MATERIALS/METHODS

We summarized operational outputs of MOMENTUM, including site participation, data aggregation, academic output, and study design elements that have been introduced since 2019.

RESULTS

As of January 2023, 17 sites have joined and 10 sites are actively enrolling patients in MOMENTUM. The MOMENTUM infrastructure, which consists of prospectively collected clinical and technical patient data and patient reported outcomes, is increasingly being used for predicate studies, technical development studies, safety and early clinical evaluation, and hypothesis testing studies according to R-IDEAL. Over 3500 patients who received treatment for 33 different tumor sites have provided informed consent for using their data for scientific research and product development. The technical database currently includes over 190.000 items, including approximately 98,000 MRI scans and 33,800 dose plans. A total of 38 data requests have been accepted (2019: n = 1; 2020: n = 5; 2021: n = 10; 2022: n = 22), including technical studies focused on algorithmic development. The MOMENTUM infrastructure is also hosting prospective clinical studies, including the randomized HERMES trial (NCT04595019) and prospective UNITED study (NCT04726397). Recently, the 'Trials within Cohorts' (TwiCs) design has been implemented, which is well suited to perform pragmatic randomized trials. MOMENTUM has partnered with Kaiku Health, an electronic patient-reported outcomes application, to facilitate collection of patient reported toxicity.

CONCLUSION

Over the past four years, the MOMENTUM study has evolved into a unique platform, whose infrastructure is increasingly being used by clinicians, researchers, physicists and industry. Continuous efforts are being made to encourage the participation of new sites and the development of innovative tools to facilitate the conduct of well-designed trials that are expected to transform daily clinical practice.

Multi-Specialty Physician Performance in Predicting Radiographic Extranodal Extension in Nodal Metastases of Oropharyngeal Squamous Carcinoma

PURPOSE/OBJECTIVE(S)

The presence of extranodal extension (ENE) in oropharyngeal (OPC) cancer patients is an important prognostic factor and can be used to determine the optimal course of treatment; however, currently, the gold standard method for ENE assessment is performed pathologically, which can only be done in a post-hoc fashion after surgical treatment has already been performed. Anatomic imaging features are being explored as a possible method for the pre-therapeutic determination of ENE, but there is currently no objective standard for the assessment of ENE from radiographic images. In this study we recruited expert clinicians, including surgeons, radiation oncologists, and radiologists, across multiple institutions to individually evaluate the presence of ENE from CT scans in order to assess the performance of radiographic ENE evaluation in human experts across different specialties.

MATERIALS/METHODS

Pre-therapy contrast-enhanced CT scans were collected from 25 OPC patients with lymph node metastasis that were pathologically evaluated for ENE after surgical resection. 5 scans were randomly chosen to be duplicated and left/right inverted, resulting in a total of 30 scans of which 21 had pathologically-confirmed ENE. To hide the inversion, all images were cropped to only show the oropharynx region. 34 expert head and neck cancer physicians, comprised of 12 surgeons, 11 radiation oncologists, and 11 radiologists, then separately evaluated the 30 CT scans using 3D Slicer for ENE presence or absence with their prediction confidence. For each physician, discriminative performance metrics were measured by calculating the accuracy, sensitivity, specificity, area under the receiver-operating characteristic curve (AUC), and Brier score, a measure of the probabilistic prediction accuracy calculated from their confidence where a lower Brier score is better. Statistical tests were performed using the Mann Whitney U test.

RESULTS

The median (interquartile) study results are shown in Table 1. There was no statistically significant difference among groups for accuracy or AUC, but significant differences among groups for Brier score, sensitivity, and specificity.

CONCLUSION

In this study we provide evidence that expert physicians, regardless of specialty, show poor performance in assessing the presence of ENE from CT scans in OPC patients. These results agree with conclusions from previous literature, and suggest the need for further research in the automated analysis of radiographic ENE.

Automated Sarcopenia Assessment and Outcomes in Head and Neck Cancer with Deep Learning Analysis of Cervical Neck Skeletal Muscle

PURPOSE/OBJECTIVE(S)

Sarcopenia is an established prognostic factor in patients diagnosed with head and neck cancers (HNC), typically measured by the skeletal muscle index (SMI) from abdominal muscle mass at L3. While sarcopenia assessment could inform HNC management, it remains impractical, time- and labor-intensive, and operator-dependent. To overcome these challenges, we developed an automated deep learning (DL) platform to calculate SMI at L3 by quantifying cross-sectional cervical skeletal muscle area (SMA) at C3 through auto-segmentation, externally validated it, and evaluated associations with clinical outcomes.

MATERIALS/METHODS

Eight hundred twenty-one patients diagnosed with HNC from multiple institutes from 1999-2013, treated with definitive chemoradiation with baseline pre-treatment CT scans, were included for model development (335 training, 96 tuning) and for independent testing (48 internal, and 342 external). Ground truth single-slice segmentations of SM at the mid-C3 vertebral level were manually annotated by radiation oncologists using an established protocol. A multi-stage DL pipeline was developed, with a 2D DenseNet to select the middle slice of C3 section and a 2D UNet to segment the SM, from which SMA was calculated. The model was evaluated using the Dice Similarity Coefficient (DC) for the internal test set, and human acceptability testing on the external test set was performed by two radiation oncologists not involved in annotations. SMI was calculated from C3 SMA based on prior literature, and sarcopenia was defined by an established, sex-specific SMI cutoff. Sarcopenia associations with overall survival (OS) and toxicities were assessed on the external dataset with Cox and logistic multivariable regressions, as indicated.

RESULTS

Model DC on the internal test set as 0.90 [95% CI: 0.90-0.91], with an intra-class coefficient of 0.96 for SMA. Human acceptability testing showed a pass rate of 94.4%. Of the 342 patients in the clinical analysis, 261 (76.3%) patients had sarcopenia. Five-year survival was 84.4% in patients without sarcopenia vs 73.1% in patients with sarcopenia (HR 2.21, p = 0.028) (median f/u: 44 mo (IQR: 25 - 66 mo)). On multivariable regression, sarcopenia (HR 2.06, p = 0.037), ACE-27 score 2+ (HR 2.25, p = 0.001), non-oropharynx diagnosis (HR 3.96, p<0.001), and T3-4 stage (HR 2.37, p<0.001) were associated with worse OS. Sarcopenia was associated with longer PEG tube duration on multivariable analysis (HR 1.59, p = 0.003), along with ACE-27 score (HR 1.20, p = 0.012) and non-oropharynx primary site (HR 1.46, p = 0.034). Sarcopenia was associated with higher risk of having PEG tube at last follow up (OR 2.25, p = 0.046). An observed increase in risk of hospitalization <3 months after RT was non-significant (OR 2.18, p = 0.117).

CONCLUSION

We developed and externally validated a fully-automated platform for sarcopenia assessment that can be used on routine HNC imaging. This algorithm is positioned for prospective testing to determine if use will inform HNC management.

Operational Ontology for Radiation Oncology (OORO): A Professional Society-Based, Multi-Stakeholder Consensus Driven Informatics Standard Supporting Clinical and Research Use of Real-World Data

PURPOSE/OBJECTIVE(S)

There is a critical need for large-scale, multi-institutional "real-world" data to evaluate patient, diagnosis and treatment factors affecting oncology patient outcomes. However, lack of data standardization undermines the potential for automated learning from the vast amount of information routinely archived in electronic health records (EHRs), Radiation Oncology Information Systems and other cancer care databases. As next step to promote data standardization beyond the American Association of Physicists in Medicine (AAPM)'s TG-263 guidance for radiotherapy (RT) nomenclature, the AAPM's Big Data Subcommittee (BDSC) has led an international RT professional society collaboration to develop the Operational Ontology for Radiation Oncology (OORO).

MATERIALS/METHODS

Initiated July 2019 to explore issues that typically compromise formation of large inter- and intra- institutional databases from EHRs, the AAPM's BDSC membership includes representatives from the AAPM, American Society of Radiation Oncology (ASTRO), Canadian Organization of Medical Physicists (COMP), Canadian Association of Radiation Oncology (CARO), European Society of Therapeutic Radiation Oncology (ESTRO) and clinical trials experts from NRG Oncology. Multiple external stakeholders were engaged, including government agencies, vendors and RT community members through the iterative and consensus-driven approach to OORO development.

RESULTS

The OORO includes 42 key elements, 359 attributes, 144 value sets, and 155 relationships, ranked for priority of implementation based on clinical significance, likelihood of availability in EHRs, or ability to modify routine clinical processes to permit aggregation. The initial version of OORO includes many disease-site independent concepts common for all cancer patients and a smaller set specific for prostate cancer. The OORO development methodology is currently being applied/adapted to include additional disease site-specific concepts beginning with head and neck cancers.

CONCLUSION

The first of its kind in radiation oncology, the OORO is a professional society-based, multi-stakeholder, consensus driven informatics standard. The iterative and collaborative approach to ontology development and refinement aims to ensure that OORO serves as a « living » guidance document, facilitating incremental expansion of data elements over time, as disease site-specific standards are set and RT concepts evolve. Supporting construction of comprehensive "real-world" datasets and application of advanced analytic techniques, including artificial intelligence (AI), OORO holds the potential to revolutionize patient management and improve outcomes.

Development and Standardization of a Classification System for Osteoradionecrosis: Implementation of a Risk-Based Model

Purpose

Osteoradionecrosis of the jaw (ORN) can manifest in varying severity. The aim of this study is to identify ORN risk factors and develop a novel classification to depict the severity of ORN.

Methods

Consecutive head-and-neck cancer (HNC) patients treated with curative-intent IMRT (≥ 45Gy) in 2011-2018 were included. Occurrence of ORN was identified from in-house prospective dental and clinical databases and charts. Multivariable logistic regression model was used to identify risk factors and stratify patients into high-risk and low-risk groups. A novel ORN classification system was developed to depict ORN severity by modifying existing systems and incorporating expert opinion. The performance of the novel system was compared to fifteen existing systems for their ability to identify and predict serious ORN event (jaw fracture or requiring jaw resection).

Results

ORN was identified in 219 out of 2732 (8%) consecutive HNC patients. Factors associated with high-risk of ORN were: oral-cavity or oropharyngeal primaries, received IMRT dose ≥60Gy, current/ex-smokers, and/or stage III-IV periodontal disease. The ORN rate for high-risk vs low-risk patients was 12.7% vs 3.1% (p<0.001) with an area-under-the-receiver-operating-curve (AUC) of 0.71. Existing ORN systems overclassified serious ORN events and failed to recognize maxillary ORN. A novel ORN classification system, RadORN, was proposed based on vertical extent of bone necrosis and presence/absence of exposed bone/fistula. This system detected serious ORN events in 5.7% of patients and statistically outperformed existing systems.

Conclusion

We identified risk factors for ORN, and proposed a novel ORN classification system based on vertical extent of bone necrosis and presence/absence of exposed bone/fistula. It outperformed existing systems in depicting the seriousness of ORN, and may facilitate clinical care and clinical trials.

DASS Good: Explainable Data Mining of Spatial Cohort Data

Developing applicable clinical machine learning models is a difficult task when the data includes spatial information, for example, radiation dose distributions across adjacent organs at risk. We describe the co-design of a modeling system, DASS, to support the hybrid human-machine development and validation of predictive models for estimating long-term toxicities related to radiotherapy doses in head and neck cancer patients. Developed in collaboration with domain experts in oncology and data mining, DASS incorporates human-in-the-loop visual steering, spatial data, and explainable AI to augment domain knowledge with automatic data mining. We demonstrate DASS with the development of two practical clinical stratification models and report feedback from domain experts. Finally, we describe the design lessons learned from this collaborative experience.

Improving Prediction of Late Symptoms using LSTM and Patient-reported Outcomes for Head and Neck Cancer Patients

Patient-Reported Outcomes (PRO) are collected directly from the patients using symptom questionnaires. In the case of head and neck cancer patients, PRO surveys are recorded every week during treatment with each patient's visit to the clinic and at different follow-up times after the treatment has concluded. PRO surveys can be very informative regarding the patient's status and the effect of treatment on the patient's quality of life (QoL). Processing PRO data is challenging for several reasons. First, missing data is frequent as patients might skip a question or a questionnaire altogether. Second, PROs are patient-dependent, a rating of 5 for one patient might be a rating of 10 for another patient. Finally, most patients experience severe symptoms during treatment which usually subside over time. However, for some patients, late toxicities persist negatively affecting the patient's QoL. These long-term severe symptoms are hard to predict and are the focus of this study. In this work, we model PRO data collected from head and neck cancer patients treated at the MD Anderson Cancer Center using the MD Anderson Symptom Inventory (MDASI) questionnaire as time series. We impute missing values with a combination of K nearest neighbor (KNN) and Long Short-Term Memory (LSTM) neural networks, and finally, apply LSTM to predict late symptom severity 12 months after treatment. We compare performance against clinical and ARIMA models. We show that the LSTM model combined with KNN imputation is effective in predicting late-stage symptom ratings for occurrence and severity under the AUC and F1 score metrics.

Inconsistent Partitioning and Unproductive Feature Associations Yield Idealized Radiomic Models

Background Radiomics is the extraction of predefined mathematic features from medical images for the prediction of variables of clinical interest. While some studies report superlative accuracy of radiomic machine learning (ML) models, the published methodology is often incomplete, and the results are rarely validated in external testing data sets. Purpose To characterize the type, prevalence, and statistical impact of methodologic errors present in radiomic ML studies. Materials and Methods Radiomic ML publications were reviewed for the presence of performance-inflating methodologic flaws. Common flaws were subsequently reproduced with randomly generated features interpolated from publicly available radiomic data sets to demonstrate the precarious nature of reported findings. Results In an assessment of radiomic ML publications, the authors uncovered two general categories of data analysis errors: inconsistent partitioning and unproductive feature associations. In simulations, the authors demonstrated that inconsistent partitioning augments radiomic ML accuracy by 1.4 times from unbiased performance and that correcting for flawed methodologic results in areas under the receiver operating characteristic curve approaching a value of 0.5 (random chance). With use of randomly generated features, the authors illustrated that unproductive associations between radiomic features and gene sets can imply false causality for biologic phenomenon. Conclusion Radiomic machine learning studies may contain methodologic flaws that undermine their validity. This study provides a review template to avoid such flaws. © RSNA, 2022 Supplemental material is available for this article. See also the editorial by Jacobs in this issue.

Factors Associated With Open Access Publishing Costs in Oncology Journals: Cross-sectional Observational Study

BACKGROUND

Open access (OA) publishing represents an exciting opportunity to facilitate the dissemination of scientific information to global audiences. However, OA publishing is often associated with significant article processing charges (APCs) for authors, which may thus serve as a barrier to publication.

OBJECTIVE

In this observational cohort study, we aimed to characterize the landscape of OA publishing in oncology and, further, identify characteristics of oncology journals that are predictive of APCs.

METHODS

We identified oncology journals using the SCImago Journal & Country Rank database. All journals with an OA publication option and APC data openly available were included. We searched journal websites and tabulated journal characteristics, including APC amount (in US dollars), OA model (hybrid vs full), 2-year impact factor (IF), H-index, number of citable documents, modality/treatment specific (if applicable), and continent of origin. All APCs were converted to US-dollar equivalents for final analyses. Selecting variables with significant associations in the univariable analysis, we generated a multiple regression model to identify journal characteristics independently associated with OA APC amount. An audit of a random 10% sample of the data was independently performed by 2 authors to ensure data accuracy, precision, and reproducibility.

RESULTS

Of 367 oncology journals screened, 251 met the final inclusion criteria. The median APC was US $2957 (IQR 1958-3450). The majority of journals (n=156, 62%) adopted the hybrid OA publication model and were based in Europe (n=119, 47%) or North America (n=87, 35%). The median (IQR) APC for all journals was US $2957 (1958-3540). Twenty-five (10%) journals had APCs greater than US $4000. There were 10 (4%) journals that offered OA publication with no publication charge. Univariable testing showed that journals with a greater number of citable documents (P<.001), higher 2-year IF (P<.001), higher H-index (P<.001), and those using the hybrid OA model (P<.001), or originating in Europe or North America (P<.001) tended to have higher APCs. In our multivariable model, the number of citable documents (β=US $367, SD US $133; P=.006), 2-year IF (US $1144, SD US $177; P<.001), hybrid OA publishing model (US $991, SD US $189; P<.001), and North American origin (US $838, SD US $186; P<.001) persisted as significant predictors of processing charges.

CONCLUSIONS

OA publication costs are greater in oncology journals that publish more citable articles, use the hybrid OA model, have a higher IF, and are based in North America or Europe. These findings may inform targeted action to help the oncology community fully appreciate the benefits of open science.

Dysphagia and shortness-of-breath as markers for treatment failure and survival in oropharyngeal cancer after radiation

BACKGROUND

Post-treatment symptoms are a focal point of follow-up visits for head and neck cancer patients. While symptoms such as dysphagia and shortness-of-breath early after treatment may motivate additional work up, their precise association with disease control and survival outcomes is not well established.

METHODS

This prospective data cohort study of 470 oropharyngeal cancer patients analyzed patient-reported swallowing, choking and shortness-of-breath symptoms at 3-to-6 months following radiotherapy to evaluate their association with overall survival and disease control. Associations between the presence of moderate-to-severe swallowing, choking and mild-to-severe shortness-of-breath and treatment outcomes were analyzed via Cox regression and Kaplan-Meier. The main outcome was overall survival (OS), and the secondary outcomes were local, regional, and distant disease control.

RESULTS

The majority of patients (91.3%) were HPV-positive. Median follow-up time was 31.7 months (IQR: 21.9-42.1). Univariable analysis showed significant associations between OS and all three symptoms of swallowing, choking, and shortness-of-breath. A composite variable integrating scores of all three symptoms was significantly associated with OS on multivariable Cox regression (p = 0.0018). Additionally, this composite symptom score showed the best predictive value for OS (c-index = 0.75). Multivariable analysis also revealed that the composite score was significantly associated with local (p = 0.044) and distant (p = 0.035) recurrence/progression. Notably, the same significant associations with OS were seen for HPV-positive only subset analysis (p < 0.01 for all symptoms).

CONCLUSIONS

Quantitative patient-reported measures of dysphagia and shortness-of-breath 3-to-6 months post-treatment are significant predictors of OS and disease recurrence/progression in OPC patients and in HPV-positive OPC only.

Early detection of mandible osteoradionecrosis risk in a high comorbidity veteran population

OBJECTIVE

Osteoradionecrosis (ORN) of the mandible is a devastating complication of external beam radiation therapy (EBRT) for head and neck squamous cell carcinoma (HNSCC). We sought to ascertain ORN risk in a Veteran HNSCC population treatment with definitive or adjuvant EBRT and followed prospectively.

STUDY DESIGN

Retrospective analysis of prospective cohort.

SETTING

Tertiary care Veterans Health Administration (VHA) medical center.

METHODS

Patients with HNSCC who initiated treatment at the Michael E. DeBakey Veterans Affairs Medical Center (MEDVAMC) are prospectively tracked for quality of care purposes through the end of the cancer surveillance period (5 years post treatment completion). We retrospectively analyzed this patient cohort and extracted clinical and pathologic data for 164 patients with SCC of the oral cavity, oropharynx, larynx, and hypopharynx who received definitive or adjuvant EBRT (2016-2020).

RESULTS

Most patients were dentate and 80 % underwent dental extractions prior to EBRT of which 16 (16 %) had complications. The rate of ORN was 3.7 % for oral cavity SCC patients and 8.1 % for oropharyngeal SCC patients. Median time to ORN development was 156 days and the earliest case was detected at 127 days post EBRT completion. All ORN patients were dentate and underwent extraction prior to EBRT start.

CONCLUSION

ORN development can occur early following EBRT in a Veteran population with significant comorbid conditions but overall rates are in line with the general population. Prospective tracking of HNSCC patients throughout the post-treatment surveillance period is critical to early detection of this devastating EBRT complication.

The contemporary management of cancers of the sinonasal tract in adults

Sinonasal malignancies make up <5% of all head and neck neoplasms, with an incidence of 0.5-1.0 per 100,000. The outcome of these rare malignancies has been poor, whereas significant progress has been made in the management of other cancers. The objective of the current review was to describe the incidence, causes, presentation, diagnosis, treatment, and recent developments of malignancies of the sinonasal tract. The diagnoses covered in this review included sinonasal undifferentiated carcinoma, sinonasal adenocarcinoma, sinonasal squamous cell carcinoma, and esthesioneuroblastoma, which are exclusive to the sinonasal tract. In addition, the authors covered malignances that are likely to be encountered in the sinonasal tract-primary mucosal melanoma, NUT (nuclear protein of the testis) carcinoma, and extranodal natural killer cell/T-cell lymphoma. For the purpose of keeping this review as concise and focused as possible, sarcomas and malignancies that can be classified as salivary gland neoplasms were excluded.

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

6578

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.

Differences between planned and delivered dose for head and neck cancer, and their consequences for normal tissue complication probability and treatment adaptation

BACKGROUND AND PURPOSE

Anatomical changes induce differences between planned and delivered dose. Adaptive radiotherapy (ART) may reduce these differences but the optimal implementation is insufficiently clear. The aims of this study were to quantify the difference between planned and delivered dose in HNC patients, assess the consequential difference in normal tissue complication probability (ΔNTCP) and to explore the value of ΔNTCP as an objective selection strategy for ART.

MATERIALS AND METHODS

For 52 patients, daily doses were accumulated to estimate the delivered dose. The difference from planned dose was analyzed for CTVs and 9 organs-at-risk (OAR). ΔNTCP was calculated for xerostomia, dysphagia, parotid gland dysfunction and tube feeding dependency at 6 months. ART was deemed necessary if ΔNTCP was >5%. The positive predicted value (PPV) was calculated for identification of ART-patients by clinical judgement, and ΔNTCP at fraction 10 and 15.

RESULTS

ΔNTCP >5% was seen five times for dysphagia and twice for the other toxicities. Only 5/9 patients with any ΔNTCP >5% clinically received ART, although ART had been done for 13/52 patients (PPV: 0.38). PPV was 0.86 and 0.75 for accumulated dose at fraction 10 and 15, respectively, using a ΔNTCP cut-off for the allocation of ART of 5%. Using other ΔNTCP cut-offs did not substantially improve PPV. With this cut-off the negative predictive value was 0.93 for ΔNTCP method of fraction 10 and fraction 15, and 0.90 for clinical judgement.

CONCLUSION

To identify patients accurately for ART, NTCP calculations based on the dose differences between planned and delivered dose at fraction 10 are superior to clinical judgement.