Prognostic significance of pre-treatment neutrophil-to-lymphocyte ratio (NLR) in patients with oropharyngeal cancer treated with radiotherapy.

BACKGROUND: This study aimed to evaluate the prognostic value of pre-treatment NLR in patients with oropharyngeal cancer. METHODS: Patients who completed definitive radiotherapy (RT) for oropharyngeal cancer and had blood counts taken pre-RT from 2002 to 2013 were included. NLR was calculated as total neutrophil/lymphocytes. Survival rates were estimated using the Kaplan-Meier method. Univariable and multivariable analyses were conducted with linear and Cox regression methods. NLR was analysed posteriori and dichotomised on the discovered median. RESULTS: Eight hundred and forty-eight patients were analysed. The median pre-RT NLR was 3. Patients with NLR of <3 had improved overall survival (OS) than those with NLR ≥ 3 (5-year OS 85 vs 74%, p < 0.0001). OS differences remained significant when stratified according to HPV status (HPV-positive p = 0.011; HPV-negative p = 0.003). Freedom from any recurrence (FFR), locoregional control (LRC) and freedom of distant recurrence (FDR) were better in those with NLR < 3. The negative impact of elevated pre-RT NLR on OS (HR = 1.64, p = 0.001), FFR (HR = 1.6, p = 0.006) and LRC (HR = 1.8, p = 0.005) remained significant on multivariable analysis. CONCLUSIONS: Pre-RT NLR is an independent prognostic factor in patients with oropharyngeal cancer regardless of HPV status. Patients with lower NLR had more favourable OS and disease control.

Tobacco exposure as a major modifier of oncologic outcomes in human papillomavirus (HPV) associated oropharyngeal squamous cell carcinoma.

BACKGROUND: The incidence of oropharyngeal squamous cell carcinoma (OPSCC) in the US is rapidly increasing, driven largely by the epidemic of human papillomavirus (HPV)-mediated OPSCC. Although survival for patients with HPV mediated OPSCC (HPV+ OPSCC) is generally better than that of patients with non-virally mediated OPSCC, this effect is not uniform. We hypothesized that tobacco exposure remains a critical modifier of survival for HPV+ OPSCC patients. METHODS: We conducted a retrospective analysis of 611 OPSCC patients with concordant p16 and HPV testing treated at a single institute (2002-2013). Survival analysis was performed using Kaplan-Meier analysis and Cox regression. Recursive partitioning analysis (RPA) was used to define tobacco exposure associated with survival (p < 0.05). RESULTS: Tobacco exposure impacted overall survival (OS) for HPV+ patients on univariate and multivariate analysis (p = 0.002, p = 0.003 respectively). RPA identified 30 pack-years (PY) as a threshold at which survival became significantly worse in HPV+ patients. OS and disease-free survival (DFS) for HPV+ > 30 PY patients didn't differ significantly from HPV- patients (p = 0.72, p = 0.27, respectively). HPV+ > 30 PY patients had substantially lower 5-year OS when compared to their ≤30 PYs counterparts: 78.4% vs 91.6%; p = 0.03, 76% vs 88.3%; p = 0.07, and 52.3% vs 74%; p = 0.05, for stages I, II, and III (AJCC 8th Edition Manual), respectively. CONCLUSIONS: Tobacco exposure can eliminate the survival benefit associated with HPV+ status in OPSCC patients. Until this effect can be clearly quantified using prospective datasets, de-escalation of treatment for HPV + OPSCC smokers should be avoided.

Radiographic retropharyngeal lymph node involvement in HPV-associated oropharyngeal carcinoma: Patterns of involvement and impact on patient outcomes.

BACKGROUND: The objective of the current study was to characterize the incidence, pattern, and impact on oncologic outcomes of retropharyngeal lymph node (RPLN) involvement in HPV-associated oropharyngeal cancer (OPC). METHODS: Data regarding patients with HPV-associated OPC who were treated at The University of Texas MD Anderson Cancer Center with intensity-modulated radiotherapy from 2004 through 2013 were analyzed retrospectively. RPLN status was determined by reviewing pretreatment imaging and/or reports. Outcomes analysis was restricted to patients with lymph node-positive (+) disease. Kaplan-Meier survival estimates were generated and survival curves were compared using the log-rank test. Bayesian information criterion assessed model performance changes with the addition of RPLN status to current American Joint Committee on Cancer staging. Competing risk analysis compared modes of disease recurrence. RESULTS: The incidence of radiographic RPLN involvement was 9% (73 of 796 patients) and was found to vary by primary tumor site. The 5-year rates of freedom from distant metastases (FDM) and overall survival were lower in patients with RPLN(+) status compared with those with RPLN-negative (-) status (84% vs 93% [P = .0327] and 74% vs 87% [P = .0078], respectively). RPLN(+) status was not found to be associated with outcomes on multivariate analysis. Bayesian information criterion analysis demonstrated that current American Joint Committee on Cancer staging was not improved with the inclusion of RPLN. Locoregional and distant disease recurrence probabilities for those patients with RPLN(+) status were 8% and 13%, respectively, compared with 10% and 6%, respectively, for those with RPLN(-) status. RPLN(+) status portended worse 5-year FDM in the low-risk subgroup (smoking history of <10 pack-years) and among patients who received concurrent chemotherapy but not induction chemotherapy. CONCLUSIONS: RPLN(+) status was associated with worse overall survival and FDM on univariate but not multivariate analysis. In subgroup analyses, RPLN(+) status was associated with poorer FDM in both patients with a smoking history of <10 pack-years and those who received concurrent chemotherapy, suggesting that RPLN(+) status could be considered an exclusion criteria in treatment deintensification efforts seeking to omit chemotherapy.

Predicting treatment Response based on Dual assessment of magnetic resonance Imaging kinetics and Circulating Tumor cells in patients with Head and Neck cancer (PREDICT-HN): matching 'liquid biopsy' and quantitative tumor modeling.

BACKGROUND: Magnetic resonance imaging (MRI) has improved capacity to visualize tumor and soft tissue involvement in head and neck cancers. Using advanced MRI, we can interrogate cell density using diffusion weighted imaging, a quantitative imaging that can be used during radiotherapy, when diffuse inflammatory reaction precludes PET imaging, and can assist with target delineation as well. Correlation of circulating tumor cells (CTCs) measurements with 3D quantitative tumor characterization could potentially allow selective, patient-specific response-adapted escalation or de-escalation of local therapy, and improve the therapeutic ratio, curing the greatest number of patients with the least toxicity. METHODS: The proposed study is designed as a prospective observational study and will collect pretreatment CT, MRI and PET/CT images, weekly serial MR imaging during RT and post treatment CT, MRI and PET/CT images. In addition, blood sample will be collected for biomarker analysis at those time intervals. CTC assessments will be performed on the CellSave tube using the FDA-approved CellSearch® Circulating Tumor Cell Kit (Janssen Diagnostics), and plasma from the EDTA blood samples will be collected, labeled with a de-identifying number, and stored at - 80 °C for future analyses. DISCUSSION: The primary objective of the study is to evaluate the prognostic value and correlation of weekly tumor response kinetics (gross tumor volume and MR signal changes) and circulating tumor cells of mucosal head and neck cancers during radiation therapy using MRI in predicting treatment response and clinical outcomes. This study will provide landmark information as to the utility of CTCs ('liquid biopsy) and tumor-specific functional quantitative imaging changes during treatment to guide personalization of treatment for future patients. Combining the biological information from CTCs and the structural information from MRI may provide more information than either modality alone. In addition, this study could potentially allow us to determine the optimal time to obtain MR imaging and/ or CTCs during radiotherapy to assess tumor response and provide guidance for patient selection and stratification for future dose escalation or de-escalation strategies. TRIAL REGISTRATION: Clinicaltrials.gov ( NCT03491176 ). Date of registration: 9th April 2018. (retrospectively registered). Date of enrolment of the first participant: 30th May 2017.

Prognostic Factors and Outcomes Associated With Neck Lymphedema in Head and Neck Cancer Survivors.

OBJECTIVES: The purpose of this study is to determine the predictors of neck lymphedema and to explore its association with symptoms and patient-reported outcomes (PROs) in Head and Neck Cancer (HNC) patients who underwent non-operative treatment. METHODS: This study involved a cross-sectional secondary analysis of data from patients diagnosed with head and neck squamous cell carcinoma who underwent radiation therapy (±chemotherapy). Patients with visits <6 weeks or >2 years following completion of radiation and those with recurrent or metastatic cancer were excluded. Presence of post-treatment lymphedema, demographics, clinical characteristics, health-related behaviors, and symptoms were collected. PROs were obtained using validated questionnaires that assessed depression, anxiety, swallowing dysfunction, and quality of life (QOL). Multivariable regression models were used to examine the relationship between lymphedema with predictors and symptoms. RESULTS: Of the 203 patients included, 88 (43.4%) developed post-treatment lymphedema. In multivariable analysis, pre-treatment Body Mass Index (BMI) (odds ratio [OR] = 1.07, 95% confidence interval [CI] [1.01, 1.14] p = 0.016) and N stage (OR = 1.96, 95% CI [1.06, 3.66], p = 0.032) were found to be independently associated with lymphedema. Regarding PROs, lymphedema was associated with greater swallowing dysfunction (3.48, 95% CI [0.20, 6.75], p = 0.038), decreased mouth opening (-3.70, 95% CI [-7.31, -0.10], p = 0.044), and increased fatigue (1.88, 95% CI [1.05, 3.38], p = 0.034). CONCLUSION: Higher pre-treatment BMI and greater N stage are identified as independent predictors for lymphedema development in non-operative HNC patients. Additionally, patients experiencing lymphedema reported worsening swallowing dysfunction and increased symptoms related to trismus and fatigue. Recognizing patients at elevated risk for lymphedema allows for early intervention, alleviation of symptom burden, and optimization of health care resources. LEVEL OF EVIDENCE: 4 Laryngoscope, 2024.

Spatially-aware clustering improves AJCC-8 risk stratification performance in oropharyngeal carcinomas.

OBJECTIVE: Evaluate the effectiveness of machine learning tools that incorporate spatial information such as disease location and lymph node metastatic patterns-of-spread, for prediction of survival and toxicity in HPV+ oropharyngeal cancer (OPC). MATERIALS & METHODS: 675 HPV+ OPC patients that were treated at MD Anderson Cancer Center between 2005 and 2013 with curative intent IMRT were retrospectively collected under IRB approval. Risk stratifications incorporating patient radiometric data and lymph node metastasis patterns via an anatomically-adjacent representation with hierarchical clustering were identified. These clusterings were combined into a 3-level patient stratification and included along with other known clinical features in a Cox model for predicting survival outcomes, and logistic regression for toxicity, using independent subsets for training and validation. RESULTS: Four groups were identified and combined into a 3-level stratification. The inclusion of patient stratifications in predictive models for 5-yr Overall survival (OS), 5-year recurrence free survival, (RFS) and Radiation-associated dysphagia (RAD) consistently improved model performance measured using the area under the curve (AUC). Test set AUC improvements over models with clinical covariates, was 9 % for predicting OS, and 18 % for predicting RFS, and 7 % for predicting RAD. For models with both clinical and AJCC covariates, AUC improvement was 7 %, 9 %, and 2 % for OS, RFS, and RAD, respectively. CONCLUSION: Including data-driven patient stratifications considerably improve prognosis for survival and toxicity outcomes over the performance achieved by clinical staging and clinical covariates alone. These stratifications generalize well to across cohorts, and sufficient information for reproducing these clusters is included.

Changes in Apparent Diffusion Coefficient (ADC) in Serial Weekly MRI during Radiotherapy in Patients with Head and Neck Cancer: Results from the PREDICT-HN Study.

Background: The PREDICT-HN study aimed to systematically assess the kinetics of imaging MR biomarkers during head and neck radiotherapy. Methods: Patients with intact squamous cell carcinoma of the head and neck were enrolled. Pre-, during, and post-treatment MRI were obtained. Serial GTV and ADC measurements were recorded. The correlation between each feature and the GTV was calculated using Spearman's correlation coefficient. The linear mixed model was used to evaluate the change in GTV over time. Results: A total of 41 patients completed the study. The majority (76%) had oropharyngeal cancer. A total of 36 patients had intact primary tumours that can be assessed on MRI, and 31 patients had nodal disease with 46 nodes assessed. Median primary GTV (GTVp) size was 14.1cc. The rate of GTVp shrinkage was highest between pre-treatment and week 4. Patients with T3-T4 tumours had a 3.8-fold decrease in GTVp compared to T1-T2 tumours. The ADC values correlated with residual GTVp. The median nodal volume (GTVn) was 12.4cc. No clinical features were found to correlate with GTVn reduction. The overall change in ADC for GTVn from pre-treatment was significant for 35th−95th percentiles in weeks 1−4 (p < 0.001). Conclusion: A discrepancy in the trajectory of ADC between primary and nodal sites suggested that they exhibit different treatment responses and should be analysed separately in future studies.

Precision association of lymphatic disease spread with radiation-associated toxicity in oropharyngeal squamous carcinomas.

PURPOSE: To determine whether patient similarity in terms of head and neck cancer spread through lymph nodes correlates significantly with radiation-associated toxicity. MATERIALS AND METHODS: 582 head and neck cancer patients received radiotherapy for oropharyngeal cancer (OPC) and had non-metastatic affected lymph nodes in the head and neck. Affected lymph nodes were segmented from pretreatment contrast-enhanced tomography scans and categorized according to consensus guidelines. Similar patients were clustered into 4 groups according to a graph-based representation of disease spread through affected lymph nodes. Correlation between dysphagia-associated symptoms and patient groups was calculated. RESULTS: Out of 582 patients, 26% (152) experienced toxicity during a follow up evaluation 6 months after completion of radiotherapy treatment. Patient groups identified by our approach were significantly correlated with dysphagia, feeding tube, and aspiration toxicity (p < .0005). DISCUSSION: Our results suggest that structural geometry-aware characterization of affected lymph nodes can be used to better predict radiation-associated dysphagia at time of diagnosis, and better inform treatment guidelines. CONCLUSION: Our work successfully stratified a patient cohort into similar groups using a structural geometry, graph-encoding of affected lymph nodes in oropharyngeal cancer patients, that were predictive of late radiation-associated dysphagia and toxicity.

Radiomics feature stability of open-source software evaluated on apparent diffusion coefficient maps in head and neck cancer.

Radiomics is a promising technique for discovering image based biomarkers of therapy response in cancer. Reproducibility of radiomics features is a known issue that is addressed by the image biomarker standardisation initiative (IBSI), but it remains challenging to interpret previously published radiomics signatures. This study investigates the reproducibility of radiomics features calculated with two widely used radiomics software packages (IBEX, MaZda) in comparison to an IBSI compliant software package (PyRadiomics). Intensity histogram, shape and textural features were extracted from 334 diffusion weighted magnetic resonance images of 59 head and neck cancer (HNC) patients from the PREDICT-HN observational radiotherapy study. Based on name and linear correlation, PyRadiomics shares 83 features with IBEX and 49 features with MaZda, a sub-set of well correlated features are considered reproducible (IBEX: 15 features, MaZda: 18 features). We explore the impact of including non-reproducible radiomics features in a HNC radiotherapy response model. It is possible to classify equivalent patient groups using radiomic features from either software, but only when restricting the model to reliable features using a correlation threshold method. This is relevant for clinical biomarker validation trials as it provides a framework to assess the reproducibility of reported radiomic signatures from existing trials.

Longitudinal characterization of the tumoral microbiome during radiotherapy in HPV-associated oropharynx cancer.

PURPOSE: To describe the baseline and serial tumor microbiome in HPV-associated oropharynx cancer (OPC) over the course of radiotherapy (RT). METHODS: Patients with newly diagnosed HPV-associated OPC treated with definitive radiotherapy +/- concurrent chemotherapy were enrolled in this prospective study. Using 16S rRNA gene sequencing, dynamic changes in the tumor site microbiome during RT were investigated. Surface tumor samples were obtained before RT and at week 1, 3 and 5 of RT. Radiological primary tumor response at mid-treatment was categorized as complete (CR) or partial (PR). RESULTS: Ten patients were enrolled, but 9 patients were included in the final analysis. Mean age was 62 years (range: 51-71). As per AJCC 8th Ed, 56%, 22% and 22% of patients had stage I, II and III, respectively. At 4-weeks, 6 patients had CR and 3 patients had PR; at follow-up imaging post treatment, all patients had CR. The baseline diversity of the tumoral versus buccal microbiome was not statistically different. For the entire cohort, alpha diversity was significantly decreased over the course of treatment (p = 0.04). There was a significant alteration in the bacterial community within the first week of radiation. Baseline tumor alpha diversity of patients with CR was significantly higher than those with PR (p = 0.03). While patients with CR had significant reduction in diversity over the course of radiation (p = 0.01), the diversity remained unchanged in patients with PR. Patients with history of smoking had significantly increased abundance of  Kingella (0.05) and lower abundance of Stomatobaculum (p = 0.03) compared to never smokers. CONCLUSIONS: The tumor microbiome of HPV-associated OPC exhibits reduced alpha diversity and altered taxa abundance over the course of radiotherapy. The baseline bacterial profiles of smokers vs. non-smokers were inherently different. Baseline tumor alpha diversity of patients with CR was higher than patients with PR, suggesting that the microbiome deserves further investigation as a biomarker of radiation response.

Outcomes after salvage for HPV-positive recurrent oropharyngeal cancer treated with primary radiation.

PURPOSE: HPV-positive oropharyngeal squamous cell carcinoma (OPSCC) carries a favorable prognosis for patients, yet nearly 30% of patients will experience disease relapse. We sought to detail patterns of failure, associated salvage therapy, and outcomes for patients with recurrent HPV-positive OPSCC. METHODS AND MATERIALS: This is a single institution retrospective study of patients with recurrent HPV-positive OPSCC irradiated from 2002 to 2014. The primary study outcome was overall survival (OS, calculated using the Kaplan-Meier method). Secondary aims included patterns of first failure with descriptive details of salvage therapy. Solitary recurrences were defined as initial presentation of recurrence in a single site (primary, neck or oligometastatic), and multi-site was defined as local and regional and/or multiple sites of distant recurrence. Survival outcomes were compared using the log-rank test. RESULTS: The cohort consisted of 132 patients. The median follow-up was 59 months for surviving patients. Estimated 2-year and 5-year OS rates were 47% and 32%, respectively. Comparative 2-year and 5-year OS rates were 65% and 46% versus 19% and 9% for the solitary group and multi-site group, respectively (p < .001). CONCLUSIONS: Patients with recurrent HPV-positive OPSCC experience 5-year survival of approximately 32%. However, patients with a "solitary" recurrence including disease at the primary site, neck or oligometastatic site have more favorable long-term outcomes.

18FDG positron emission tomography mining for metabolic imaging biomarkers of radiation-induced xerostomia in patients with oropharyngeal cancer.

PURPOSE: Head and neck cancers radiotherapy (RT) is associated with inevitable injury to parotid glands and subsequent xerostomia. We investigated the utility of SUV derived from 18FDG-PET to develop metabolic imaging biomarkers (MIBs) of RT-related parotid injury. METHODS: Data for oropharyngeal cancer (OPC) patients treated with RT at our institution between 2005 and 2015 with available planning computed tomography (CT), dose grid, pre- & first post-RT 18FDG-PET-CT scans, and physician-reported xerostomia assessment at 3-6 months post-RT (Xero 3-6 ms) per CTCAE, was retrieved, following an IRB approval. A CT-CT deformable image co-registration followed by voxel-by-voxel resampling of pre & post-RT 18FDG activity and dose grid were performed. Ipsilateral (Ipsi) and contralateral (contra) parotid glands were sub-segmented based on the received dose in 5 Gy increments, i.e. 0-5 Gy, 5-10 Gy sub-volumes, etc. Median and dose-weighted SUV were extracted from whole parotid volumes and sub-volumes on pre- & post-RT PET scans, using in-house code that runs on MATLAB. Wilcoxon signed-rank and Kruskal-Wallis tests were used to test differences pre- and post-RT. RESULTS: 432 parotid glands, belonging to 108 OPC patients treated with RT, were sub-segmented & analyzed. Xero 3-6 ms was reported as: non-severe (78.7%) and severe (21.3%). SUV- median values were significantly reduced post-RT, irrespective of laterality (p = 0.02). A similar pattern was observed in parotid sub-volumes, especially ipsi parotid gland sub-volumes receiving doses 10-50 Gy (p < 0.05). Kruskal-Wallis test showed a significantly higher mean RT dose in the contra parotid in the patients with more severe Xero 3-6mo (p = 0.03). Multiple logistic regression showed a combined clinical-dosimetric-metabolic imaging model could predict the severity of Xero 3-6mo; AUC = 0.78 (95%CI: 0.66-0.85; p < 0.0001). CONCLUSION: We sought to quantify pre- and post-RT 18FDG-PET metrics of parotid glands in patients with OPC. Temporal dynamics of PET-derived metrics can potentially serve as MIBs of RT-related xerostomia in concert with clinical and dosimetric variables.

Computed Tomography Radiomics Kinetics as Early Imaging Correlates of Osteoradionecrosis in Oropharyngeal Cancer Patients.

Osteoradionecrosis (ORN) is a major side-effect of radiation therapy in oropharyngeal cancer (OPC) patients. In this study, we demonstrate that early prediction of ORN is possible by analyzing the temporal evolution of mandibular subvolumes receiving radiation. For our analysis, we use computed tomography (CT) scans from 21 OPC patients treated with Intensity Modulated Radiation Therapy (IMRT) with subsequent radiographically-proven ≥ grade II ORN, at three different time points: pre-IMRT, 2-months, and 6-months post-IMRT. For each patient, radiomic features were extracted from a mandibular subvolume that developed ORN and a control subvolume that received the same dose but did not develop ORN. We used a Multivariate Functional Principal Component Analysis (MFPCA) approach to characterize the temporal trajectories of these features. The proposed MFPCA model performs the best at classifying ORN vs. Control subvolumes with an area under curve (AUC) = 0.74 [95% confidence interval (C.I.): 0.61-0.90], significantly outperforming existing approaches such as a pre-IMRT features model or a delta model based on changes at intermediate time points, i.e., at 2- and 6-month follow-up. This suggests that temporal trajectories of radiomics features derived from sequential pre- and post-RT CT scans can provide markers that are correlates of RT-induced mandibular injury, and consequently aid in earlier management of ORN.

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.

Simultaneously spatial and temporal Higher-Order Total Variations for noise suppression and motion reduction in DCE and IVIM.

In many applications based on kinetic evaluation analysis and model fitting, quantitative mapping retrieved on data series from modalites such as MRI is completed on a voxel-by-voxel basis, where motion and low signal to noise ratio (SNR) would considerably degenerate the reliability of estimations. The coherence of image series in space and time can be used as prior knowledge to mitigate this occurrence. In this study, spatial and temporal higher-order total variations (HOTVs) are applied on a data series of MRI signal (e.g. dynamic contrast-enhanced (DCE) MRI and intravoxel incoherent motion (IVIM) MRI) to exploit the coherence of signal in space and time to minimize the variabilities caused by motion as well as improving quality of images with low SNR while retaining the physical details of original data properly. Simultaneously applying spatial and temporal HOTVs on images is non-trivial in implementation since it is a non-smooth optimization problem with multiple regularizers. Therefore, we use the proximal gradient method as well as a primal-dual split proximal mechanism to address the problem properly. In addition to increase the reliability of quantitative parametric map estimations, this preprocessing procedure can be included into many existing map estimation algorithms and pipelines effortlessly. We demonstrate our method on the parametric maps estimation for DCE MRI and IVIM MRI.

Clustering of Largely Right-Censored Oropharyngeal Head and Neck Cancer Patients for Discriminative Groupings to Improve Outcome Prediction.

Clustering is the task of identifying groups of similar subjects according to certain criteria. The AJCC staging system can be thought as a clustering mechanism that groups patients based on their disease stage. This grouping drives prognosis and influences treatment. The goal of this work is to evaluate the efficacy of machine learning algorithms to cluster the patients into discriminative groups to improve prognosis for overall survival (OS) and relapse free survival (RFS) outcomes. We apply clustering over a retrospectively collected data from 644 head and neck cancer patients including both clinical and radiomic features. In order to incorporate outcome information into the clustering process and deal with the large proportion of censored samples, the feature space was scaled using the regression coefficients fitted using a proxy dependent variable, martingale residuals, instead of follow-up time. Two clusters were identified and evaluated using cross validation. The Kaplan Meier (KM) curves between the two clusters differ significantly for OS and RFS (p-value < 0.0001). Moreover, there was a relative predictive improvement when using the cluster label in addition to the clinical features compared to using only clinical features where AUC increased by 5.7% and 13.0% for OS and RFS, respectively.

Precision toxicity correlates of tumor spatial proximity to organs at risk in cancer patients receiving intensity-modulated radiotherapy.

PURPOSE: Using a 200 Head and Neck cancer (HNC) patient cohort, we employ patient similarity based on tumor location, volume, and proximity to organs at risk to predict radiation-associated dysphagia (RAD) in a new patient receiving intensity modulated radiation therapy (IMRT). MATERIAL AND METHODS: All patients were treated using curative-intent IMRT. Anatomical features were extracted from contrast-enhanced tomography scans acquired pre-treatment. Patient similarity was computed using a topological similarity measure, which allowed for the prediction of normal tissues' mean doses. We performed feature selection and clustering, and used the resulting groups of patients to forecast RAD. We used Logistic Regression (LG) cross-validation to assess the potential toxicity risk of these groupings. RESULTS: Out of 200 patients, 34 patients were recorded as having RAD. Patient clusters were significantly correlated with RAD (p < .0001). The area under the receiver-operator curve (AUC) using pre-established, baseline features gave a predictive accuracy of 0.79, while the addition of our cluster labels improved accuracy to 0.84. CONCLUSION: Our results show that spatial information available pre-treatment can be used to robustly identify groups of RAD high-risk patients. We identify feature sets that considerably improve toxicity risk prediction beyond what is possible using baseline features. Our results also suggest that similarity-based predicted mean doses to organs can be used as valid predictors of risk to organs.

Accuracy of deformable image registration techniques for alignment of longitudinal cholangiocarcinoma CT images.

PURPOSE: Response assessment of radiotherapy for the treatment of intrahepatic cholangiocarcinoma (IHCC) across longitudinal images is challenging due to anatomical changes. Advanced deformable image registration (DIR) techniques are required to correlate corresponding tissues across time. In this study, the accuracy of five commercially available DIR algorithms in four treatment planning systems (TPS) was investigated for the registration of planning images with posttreatment follow-up images for response assessment or re-treatment purposes. METHODS: Twenty-nine IHCC patients treated with hypofractionated radiotherapy and with pretreatment and posttreatment contrast-enhanced computed tomography (CT) images were analyzed. Liver segmentations were semiautomatically generated on all CTs and the posttreatment CT was then registered to the pretreatment CT using five commercially available algorithms (Demons, B-splines, salient feature-based, anatomically constrained and finite element-based) in four TPSs. This was followed by an in-depth analysis of 10 DIR strategies (plus global and liver-focused rigid registration) in one of the TPSs. Eight of the strategies were variants of the anatomically constrained DIR while the two were based on a finite element-based biomechanical registration. The anatomically constrained techniques were combinations of: (a) initializations with the two rigid registrations; (b) two similarity metrics - correlation coefficient (CC) and mutual information (MI); and (c) with and without a controlling region of interest (ROI) - the liver. The finite element-based techniques were initialized by the two rigid registrations. The accuracy of each registration was evaluated using target registration error (TRE) based on identified vessel bifurcations. The results were statistically analyzed with a one-way analysis of variance (ANOVA) and pairwise comparison tests. Stratified analysis was conducted on the inter-TPS data (plus the liver-focused rigid registration) using treatment volume changes, slice thickness, time between scans, and abnormal lab values as stratifying factors. RESULTS: The complex deformation observed following treatment resulted in average TRE exceeding the image voxel size for all techniques. For the inter-TPS comparison, the Demons algorithm had the lowest TRE, which was significantly superior to all the other algorithms. The respective mean (standard deviation) TRE (in mm) for the Demons, B-splines, salient feature-based, anatomically constrained, and finite element-based algorithms were 4.6 (2.0), 7.4 (2.7), 7.2 (2.6), 6.3 (2.3), and 7.5 (4.0). In the follow-up comparison of the anatomically constrained DIR, the strategy with liver-focused rigid registration initialization, CC as similarity metric and liver as a controlling ROI had the lowest mean TRE - 6.0 (2.0). The maximum TRE for all techniques exceeded 10 mm. Selection of DIR strategy was found to be a statistically significant factor for registration accuracy. Tumor volume change had a significant effect on TRE for finite element-based registration and B-splines DIR. Time between scans had a substantial effect on TRE for all registrations but was only significant for liver-focused rigid, finite element-based and salient feature-based DIRs. CONCLUSIONS: This study demonstrates the limitations of commercially available DIR techniques in TPSs for alignment of longitudinal images of liver cancer presenting complex anatomical changes including local hypertrophy and fibrosis/necrosis. DIR in this setting should be used with caution and careful evaluation.

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.

Quantitative Dynamic Contrast-Enhanced MRI Identifies Radiation-Induced Vascular Damage in Patients With Advanced Osteoradionecrosis: Results of a Prospective Study.

PURPOSE: We aim to characterize the quantitative dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) parameters associated with advanced mandibular osteoradionecrosis (ORN) compared with the contralateral normal mandible. METHODS AND MATERIALS: Patients with a diagnosis of advanced ORN after curative-intent radiation treatment of head and neck cancer were prospectively enrolled after institutional review board approval and study-specific informed consent were obtained. Quantitative maps generated with the Tofts and extended Tofts pharmacokinetic models were used for analysis. Manual segmentation of advanced ORN 3-dimensional volume was done using anatomic sequences to create ORN volumes of interest (VOIs). Subsequently, normal mandibular VOIs were segmented on the contralateral healthy mandible of similar volume and anatomic location to create control VOIs. Finally, anatomic sequences were coregistered to DCE sequences, and contours were propagated to the respective parameter maps. RESULTS: Thirty patients were included. The median time to ORN diagnosis after completion of IMRT was 38 months (range, 6-184 months), whereas median time to ORN progression to advanced grade after initial diagnosis was 5.6 months (range, 0-128 months). There were statistically significant higher Ktrans and Ve in ORN-VOIs compared with controls (0.23 vs 0.07 min-1, and 0.34 vs 0.15; P < .0001 for both). The average relative increase of Ktrans in ORN-VOIs was 3.2-fold higher than healthy mandibular control VOIs. Moreover, the corresponding rise of Ve in ORN-VOIs was 2.7-fold higher than in the controls. Using combined Ktrans and Ve parameters, 27 patients (90%) had at least a 200% increase of either of the studied parameters in the ORN-VOIs compared with their healthy mandible VOIs. CONCLUSIONS: Our results confirm that there is a quantitatively significant higher degree of leakiness in the mandibular vasculature as measured using DCE-MRI parameters of areas with advanced ORN versus healthy mandible.