Cholesteatoma surgery in the pediatric population: remaining challenges in the era of mastoid obliteration.

PURPOSE: To present the first pediatric study on the safety and efficacy of mastoid obliteration using S53P4 bioactive glass (BAG) for cholesteatoma surgery. METHODS: A single-center retrospective cohort study was conducted. Inclusion criteria were pediatric cases (≤ 18 years) and at least at least one year of follow-up including non-echo planar diffusion-weighted MRI to assess cholesteatoma recidivism. Both canal wall up (CWU) and canal wall down (CWD) procedures were evaluated. RESULTS: A total of 61 cases (56 patients) were included. Most cases had an otologic history before the development of the cholesteatoma. CWU procedure was performed in 18 cases (30%) and CWD procedure in 43 cases (70%). The cholesteatoma recidivism rate was 33% after a mean follow-up period of 58 months. Kaplan-Meier curve estimated a 5-year recidivism rate of 40%. Few complications were seen that were all minor and resolved spontaneously or after local or systemic treatment. Control of the infection (merchant grade 0-1) was achieved in 98% of the cases. Closure of the air-bone gap within 20 dB was achieved in 22% of the cases with complete audiometric evaluation. CONCLUSION: In this MRI-controlled study, we show the safety and efficacy of S53P4 BAG for mastoid obliteration in a pediatric cholesteatoma cohort. Postoperative complications were both rare and minor, and a dry ear was achieved in almost all patients. Nevertheless, persistent hearing loss and the apparent high recidivism rate reflect the challenging nature of pediatric cholesteatoma.

Outcome prediction of head and neck squamous cell carcinoma by MRI radiomic signatures.

OBJECTIVES: Head and neck squamous cell carcinoma (HNSCC) shows a remarkable heterogeneity between tumors, which may be captured by a variety of quantitative features extracted from diagnostic images, termed radiomics. The aim of this study was to develop and validate MRI-based radiomic prognostic models in oral and oropharyngeal cancer. MATERIALS AND METHODS: Native T1-weighted images of four independent, retrospective (2005-2013), patient cohorts (n = 102, n = 76, n = 89, and n = 56) were used to delineate primary tumors, and to extract 545 quantitative features from. Subsequently, redundancy filtering and factor analysis were performed to handle collinearity in the data. Next, radiomic prognostic models were trained and validated to predict overall survival (OS) and relapse-free survival (RFS). Radiomic features were compared to and combined with prognostic models based on standard clinical parameters. Performance was assessed by integrated area under the curve (iAUC). RESULTS: In oral cancer, the radiomic model showed an iAUC of 0.69 (OS) and 0.70 (RFS) in the validation cohort, whereas the iAUC in the oropharyngeal cancer validation cohort was 0.71 (OS) and 0.74 (RFS). By integration of radiomic and clinical variables, the most accurate models were defined (iAUC oral cavity, 0.72 (OS) and 0.74 (RFS); iAUC oropharynx, 0.81 (OS) and 0.78 (RFS)), and these combined models outperformed prognostic models based on standard clinical variables only (p < 0.001). CONCLUSIONS: MRI radiomics is feasible in HNSCC despite the known variability in MRI vendors and acquisition protocols, and radiomic features added information to prognostic models based on clinical parameters. KEY POINTS: • MRI radiomics can predict overall survival and relapse-free survival in oral and HPV-negative oropharyngeal cancer. • MRI radiomics provides additional prognostic information to known clinical variables, with the best performance of the combined models. • Variation in MRI vendors and acquisition protocols did not influence performance of radiomic prognostic models.

Improved high-dimensional prediction with Random Forests by the use of co-data.

BACKGROUND: Prediction in high dimensional settings is difficult due to the large number of variables relative to the sample size. We demonstrate how auxiliary 'co-data' can be used to improve the performance of a Random Forest in such a setting. RESULTS: Co-data are incorporated in the Random Forest by replacing the uniform sampling probabilities that are used to draw candidate variables by co-data moderated sampling probabilities. Co-data here are defined as any type information that is available on the variables of the primary data, but does not use its response labels. These moderated sampling probabilities are, inspired by empirical Bayes, learned from the data at hand. We demonstrate the co-data moderated Random Forest (CoRF) with two examples. In the first example we aim to predict the presence of a lymph node metastasis with gene expression data. We demonstrate how a set of external p-values, a gene signature, and the correlation between gene expression and DNA copy number can improve the predictive performance. In the second example we demonstrate how the prediction of cervical (pre-)cancer with methylation data can be improved by including the location of the probe relative to the known CpG islands, the number of CpG sites targeted by a probe, and a set of p-values from a related study. CONCLUSION: The proposed method is able to utilize auxiliary co-data to improve the performance of a Random Forest.

Multiple sclerosis-associated CLEC16A controls HLA class II expression via late endosome biogenesis.

C-type lectins are key players in immune regulation by driving distinct functions of antigen-presenting cells. The C-type lectin CLEC16A gene is located at 16p13, a susceptibility locus for several autoimmune diseases, including multiple sclerosis. However, the function of this gene and its potential contribution to these diseases in humans are poorly understood. In this study, we found a strong upregulation of CLEC16A expression in the white matter of multiple sclerosis patients (n = 14) compared to non-demented controls (n = 11), mainly in perivascular leukocyte infiltrates. Moreover, CLEC16A levels were significantly enhanced in peripheral blood mononuclear cells of multiple sclerosis patients (n = 69) versus healthy controls (n = 46). In peripheral blood mononuclear cells, CLEC16A was most abundant in monocyte-derived dendritic cells, in which it strongly co-localized with human leukocyte antigen class II. Treatment of these professional antigen-presenting cells with vitamin D, a key protective environmental factor in multiple sclerosis, downmodulated CLEC16A in parallel with human leukocyte antigen class II. Knockdown of CLEC16A in distinct types of model and primary antigen-presenting cells resulted in severely impaired cytoplasmic distribution and formation of human leucocyte antigen class II-positive late endosomes, as determined by immunofluorescence and electron microscopy. Mechanistically, CLEC16A participated in the molecular machinery of human leukocyte antigen class II-positive late endosome formation and trafficking to perinuclear regions, involving the dynein motor complex. By performing co-immunoprecipitations, we found that CLEC16A directly binds to two critical members of this complex, RILP and the HOPS complex. CLEC16A silencing in antigen-presenting cells disturbed RILP-mediated recruitment of human leukocyte antigen class II-positive late endosomes to perinuclear regions. Together, we identify CLEC16A as a pivotal gene in multiple sclerosis that serves as a direct regulator of the human leukocyte antigen class II pathway in antigen-presenting cells. These findings are a first step in coupling multiple sclerosis-associated genes to the regulation of the strongest genetic factor in multiple sclerosis, human leukocyte antigen class II.

Noncompliance to guidelines in head and neck cancer treatment; associated factors for both patient and physician.

BACKGROUND: Decisions on head and neck squamous cell carcinoma (HNSCC) treatment are widely recognized as being difficult, due to high morbidity, often involving vital functions. Some patients may therefore decline standard, curative treatment. In addition doctors may propose alternative, nonstandard treatments. Little attention is devoted, both in literature and in daily practice, to understanding why and when HNSCC patients or their physicians decline standard, curative treatment modalities. Our objective is to determine factors associated with noncompliance in head and neck cancer treatment for both patients and physicians and to assess the influence of patient compliance on prognosis. METHODS: We did a retrospective study based on the medical records of 829 patients with primary HNSCC, who were eligible for curative treatment and referred to our hospital between 2010 and 2012. We analyzed treatment choice and reasons for nonstandard treatment decisions, survival, age, gender, social network, tumor site, cTNM classification, and comorbidity (ACE27). Multivariate analysis using logistic regression methods was performed to determine predictive factors associated with non-standard treatment following physician or patient decision. To gain insight in survival of the different groups of patients, we applied a Cox regression analysis. After checking the proportional hazards assumption for each variable, we adjusted the survival analysis for gender, age, tumor site, tumor stage, comorbidity and a history of having a prior tumor. RESULTS: 17 % of all patients with a primary HNSCC did not receive standard curative treatment, either due to nonstandard treatment advice (10 %) or due to the patient choosing an alternative (7 %). A further 3 % of all patients refused any type of therapy, even though they were considered eligible for curative treatment. Elderliness, single marital status, female gender, high tumor stage and severe comorbidity are predictive factors. Patients declining standard treatment have a lower overall 3-year survival (34 % vs. 70 %). CONCLUSIONS: Predictive factors for nonstandard treatment decisions in head and neck cancer treatment differed between the treating physician and the patient. Patients who received nonstandard treatment had a lower overall 3-year survival. These findings should be taken into account when counselling patients in whom nonstandard treatment is considered.

Efficacy of S53P4 Bioactive Glass for the Secondary Obliteration of Chronically Discharging Radical Cavities.

Objective: Present the results of the secondary obliteration of chronically discharging radical cavities using S53P4 bioactive glass (BAG). Study Design: Retrospective cohort study. Setting: Single-center study. Methods: A single-center retrospective cohort study was conducted of all patients that underwent secondary obliteration of persistently draining radical cavities using S53P4 BAG between 2011 and 2022. Patients with middle ear cholesteatoma were excluded. The main outcome was postoperative otorrhea, as indicated by Merchant grading. Results: In total, 97 patients were included. The median postoperative follow-up time was 3.9 years (range 0.5-10.4). Average time between the original canal wall down surgery and the secondary obliteration was 25.3 years (SD 11.7, range 2-66). At the most recent follow-up visit, a Merchant grade of 0 to 1 was observed in 95% of the cases. There were no cases of sensorineural hearing loss or facial palsy, one case developed a retro auricular skin defect and 1 patient developed CSF leakage. Minor complications were seen in 10 patients (10%). Ossicular chain reconstruction with a titanium prosthesis was performed in 42 cases, resulting in a median improvement of 11.2 dB in air conduction thresholds. In 9/42 cases (21%), closure of the postoperative air-bone gap to ≤20 dB was achieved. Twenty-five percent of cases could be discharged from out-patient visits. Conclusion: Revision of persistently draining radical cavities with BAG obliteration is feasible and results in a dry and safe ear in 95% of the patients, thereby enabling wearing of a conventional hearing aid. Out-patient visits could be ceased in 25% of the cases.

Magnetic resonance imaging based radiomics prediction of Human Papillomavirus infection status and overall survival in oropharyngeal squamous cell carcinoma.

OBJECTIVES: Human papillomavirus- (HPV) positive oropharyngeal squamous cell carcinoma (OPSCC) differs biologically and clinically from HPV-negative OPSCC and has a better prognosis. This study aims to analyze the value of magnetic resonance imaging (MRI)-based radiomics in predicting HPV status in OPSCC and aims to develop a prognostic model in OPSCC including HPV status and MRI-based radiomics. MATERIALS AND METHODS: Manual delineation of 249 primary OPSCCs (91 HPV-positive and 159 HPV-negative) on pretreatment native T1-weighted MRIs was performed and used to extract 498 radiomic features per delineation. A logistic regression (LR) and random forest (RF) model were developed using univariate feature selection. Additionally, factor analysis was performed, and the derived factors were combined with clinical data in a predictive model to assess the performance on predicting HPV status. Additionally, factors were combined with clinical parameters in a multivariable survival regression analysis. RESULTS: Both feature-based LR and RF models performed with an AUC of 0.79 in prediction of HPV status. Fourteen of the twenty most significant features were similar in both models, mainly concerning tumor sphericity, intensity variation, compactness, and tumor diameter. The model combining clinical data and radiomic factors (AUC = 0.89) outperformed the radiomics-only model in predicting OPSCC HPV status. Overall survival prediction was most accurate using the combination of clinical parameters and radiomic factors (C-index = 0.72). CONCLUSION: Predictive models based on MR-radiomic features were able to predict HPV status with sufficient performance, supporting the role of MRI-based radiomics as potential imaging biomarker. Survival prediction improved by combining clinical features with MRI-based radiomics.

Automatic segmentation of head and neck primary tumors on MRI using a multi-view CNN.

BACKGROUND : Accurate segmentation of head and neck squamous cell cancer (HNSCC) is important for radiotherapy treatment planning. Manual segmentation of these tumors is time-consuming and vulnerable to inconsistencies between experts, especially in the complex head and neck region. The aim of this study is to introduce and evaluate an automatic segmentation pipeline for HNSCC using a multi-view CNN (MV-CNN). METHODS: The dataset included 220 patients with primary HNSCC and availability of T1-weighted, STIR and optionally contrast-enhanced T1-weighted MR images together with a manual reference segmentation of the primary tumor by an expert. A T1-weighted standard space of the head and neck region was created to register all MRI sequences to. An MV-CNN was trained with these three MRI sequences and evaluated in terms of volumetric and spatial performance in a cross-validation by measuring intra-class correlation (ICC) and dice similarity score (DSC), respectively. RESULTS: The average manual segmented primary tumor volume was 11.8±6.70 cm3 with a median [IQR] of 13.9 [3.22-15.9] cm3. The tumor volume measured by MV-CNN was 22.8±21.1 cm3 with a median [IQR] of 16.0 [8.24-31.1] cm3. Compared to the manual segmentations, the MV-CNN scored an average ICC of 0.64±0.06 and a DSC of 0.49±0.19. Improved segmentation performance was observed with increasing primary tumor volume: the smallest tumor volume group (<3 cm3) scored a DSC of 0.26±0.16 and the largest group (>15 cm3) a DSC of 0.63±0.11 (p<0.001). The automated segmentation tended to overestimate compared to the manual reference, both around the actual primary tumor and in false positively classified healthy structures and pathologically enlarged lymph nodes. CONCLUSION: An automatic segmentation pipeline was evaluated for primary HNSCC on MRI. The MV-CNN produced reasonable segmentation results, especially on large tumors, but overestimation decreased overall performance. In further research, the focus should be on decreasing false positives and make it valuable in treatment planning.

Mastoid Obliteration Using S53P4 Bioactive Glass in Cholesteatoma Surgery: A 10-Year Single-Center Experience in 173 Adult Patients with Long-Term Magnetic Resonance Imaging Controlled Follow-up.

OBJECTIVE: To present the long-term outcomes of mastoid obliteration in cholesteatoma surgery using S53P4 bioactive glass (BAG) in an adult population. STUDY DESIGN: Retrospective cohort study. SETTING: Single-center study. PATIENTS: All 173 adult patients who underwent primary or revision surgery for cholesteatoma with mastoid obliteration using S53P4 BAG with at least 1 year of follow-up including nonecho planar diffusion-weighted magnetic resonance imaging (MRI) (non-EP DWI MRI) and/or second-look surgery to evaluate recidivism. Both canal wall up (CWU) and canal wall down (CWD) procedures were included. INTERVENTIONS: Patients underwent CWU or CWD mastoidectomy using S53P4 BAG. MAIN OUTCOME AND MEASURES: Cholesteatoma recidivism, postoperative complications, Merchant grade, hearing outcome. RESULTS: Cholesteatoma recidivism was assessed by MRI in 97% of all cases and second-look surgery look surgery in 3% of cases. After a mean follow-up period of 53 months, cholesteatoma recidivism was seen in 10% of the cases (n = 18). Using the Kaplan-Meier curve to extrapolate, a 5-year recidivism rate of 12% was estimated. Only minor complications occurred, all resolving spontaneously or after minor treatment. Merchant grade of 0 to 1 was achieved 95% of the patients, no persistently wet ears were observed. Closure of the air-bone gap within 20 dB was possible in 32%. CONCLUSION: In this long-term (up to 10 yr) follow-up study, we demonstrated the safety of S53P4 BAG. Minimal and only minor postoperative complications were observed. The effectiveness of BAG was indicated by the low rate of recidivism, even when using non-EP DWI MRI, a sensitive and specific noninvasive technique to detect cholesteatoma recidivism.

Development and Validation of a Novel and Rapid Molecular Detection Method for High-Risk Human Papillomavirus in Formalin-Fixed, Paraffin-Embedded Tumor Tissue.

The most widely applied algorithm for human papillomavirus (HPV) detection in formalin-fixed, paraffin-embedded (FFPE) specimens of oropharyngeal head and neck squamous cell carcinoma (HNSCC) consists of p16INK4A immunostaining followed by PCR-based detection of high-risk HPV DNA on p16INK4A-immunopositive samples. However, in nonoropharyngeal HNSCC this algorithm fails, hampering correct interpretation of the prevalence and prognosis of HPV in these cases. In this study, we developed and validated a molecular HPV detection method for FFPE specimens of oropharyngeal and nonoropharyngeal HNSCC. Sectioning of FFPE blocks was circumvented by using punch biopsies from tumor-enriched regions of FFPE tissue blocks, and combined extraction was applied to obtain high-quality DNA and RNA from the punch biopsy. Next, PCR-based detection of HPV DNA was performed for 15 high-risk HPV types with subsequent detection of E6 mRNA for validation. The combined DNA/RNA FFPE test of tissue cores was assessed in well-characterized cohorts with known HPV status based on earlier work, that is, a cohort of oropharyngeal HNSCC (n = 80) and oral cavity HNSCC (n = 25), and reached an accuracy of 97% and 100%, respectively. In conclusion, our method is rapid, simple, and shows an excellent diagnostic performance for detection of HPV type 16. Ultimately, it can be applied for large cohort studies to determine the etiologic fraction and prognostic implication of HPV in nonoropharyngeal HNSCC.

Comprehensive multiparameter genetic analysis improves circulating tumor DNA detection in head and neck cancer patients.

INTRODUCTION: Tumor-specific genetic aberrations in cell-free DNA (cfDNA) from plasma are promising biomarkers for diagnosis of recurrent head and neck squamous cell carcinoma (HNSCC). However, the sensitivity when using somatic mutations only in cfDNA is suboptimal. Here, we combined detection of copy number aberrations (CNAs), human papillomavirus (HPV) DNA and somatic mutations in a single sequencing workflow. METHODS: Pretreatment plasmas of 40 patients and 20 non-cancer controls were used for analysis. Plasma DNA underwent low-coverage whole genome sequencing (lcWGS) to detect both CNAs and HPV-DNA, and deep sequencing to detect mutations in 12 frequently altered cancer driver genes in HNSCC using the same sequencing library. A specific analysis pipeline line was developed for data mining. The corresponding tumors were analyzed using slightly adapted protocols. RESULTS: Using the developed method, somatic mutations and CNAs were detected in plasma DNA of HNSCC patients in 67% and 52%, respectively. HPV-DNA in plasma was detected in 100% of patients with HPV-positive tumors, and not in plasma of patients with HPV-negative tumors or non-cancer controls. Combined analysis increased the detection rate of tumor DNA in plasma to 78%. The detection rate was significantly associated with the stage of disease of the tumor. Neither HPV status nor location of the primary tumor influenced detection of CNAs or somatic mutations in plasma. CONCLUSIONS: This study demonstrates that the combined analysis of CNAs, HPV and somatic mutations in plasma of HNSCC patients is feasible and contributes to a higher sensitivity of the assay compared to single modality analyses.

Molecular Characterization of Locally Relapsed Head and Neck Cancer after Concomitant Chemoradiotherapy.

PURPOSE: To investigate the pathobiological origin of local relapse after chemoradiotherapy, we studied genetic relationships of primary tumors (PT) and local relapses (LR) of patients treated with chemoradiotherapy. EXPERIMENTAL DESIGN: First, low-coverage whole genome sequencing was performed on DNA from 44 biopsies of resected head and neck squamous cell carcinoma (HNSCC) specimens (median 3 biopsies/tumor) to assess suitability of copy number alterations (CNAs) as biomarker for genetic relationships. CNAs were compared within and between tumors and an algorithm was developed to assess genetic relationships with consideration of intratumor heterogeneity. Next, this CNA-based algorithm was combined with target enrichment sequencing of genes frequently mutated in HNSCC to assess the genetic relationships of paired tumors and LRs of patients treated with chemoradiotherapy. RESULTS: Genetic relationship analysis using CNAs could accurately (96%) predict tumor biopsy pairs as patient-matched or independent. However, subsequent CNA analysis of PTs and LRs after chemoradiotherapy suggested genetic relationships in only 20% of cases, and absence in 80%. Target enrichment sequencing for mutations confirmed absence of any genetic relationship in half of the paired PTs and LRs. CONCLUSIONS: There are minor variations in CNA profiles within different areas of HNSCC tumors and many between independent tumors, suggesting that CNA profiles could be exploited as a marker of genetic relationship. Using CNA profiling and mutational analysis of cancer driver genes, relapses after chemoradiotherapy appear to be partially genetically related to the corresponding PTs, but seem often genetically unrelated. This remarkable observation warrants further studies and will impact therapeutic innovations and prognostic modeling when using index tumor characteristics.

Prognostic modeling of oral cancer by gene profiles and clinicopathological co-variables.

Accurate staging and outcome prediction is a major problem in clinical management of oral cancer patients, hampering high precision treatment and adjuvant therapy planning. Here, we have built and validated multivariable models that integrate gene signatures with clinical and pathological variables to improve staging and survival prediction of patients with oral squamous cell carcinoma (OSCC). Gene expression profiles from 249 human papillomavirus (HPV)-negative OSCCs were explored to identify a 22-gene lymph node metastasis signature (LNMsig) and a 40-gene overall survival signature (OSsig). To facilitate future clinical implementation and increase performance, these signatures were transferred to quantitative polymerase chain reaction (qPCR) assays and validated in an independent cohort of 125 HPV-negative tumors. When applied in the clinically relevant subgroup of early-stage (cT1-2N0) OSCC, the LNMsig could prevent overtreatment in two-third of the patients. Additionally, the integration of RT-qPCR gene signatures with clinical and pathological variables provided accurate prognostic models for oral cancer, strongly outperforming TNM. Finally, the OSsig gene signature identified a subpopulation of patients, currently considered at low-risk for disease-related survival, who showed an unexpected poor prognosis. These well-validated models will assist in personalizing primary treatment with respect to neck dissection and adjuvant therapies.

Applications of molecular diagnostics for personalized treatment of head and neck cancer: state of the art.

Squamous cell carcinomas of the head and neck are the sixth most frequent tumors worldwide. Risk factors are carcinogenic exposure, infection with the human papillomavirus (HPV) and genetic predisposition. Lymph node metastasis in the neck and HPV status are major prognostic factors. There are several important clinical challenges that determine the research agenda in head and neck cancer. The first is more accurate staging, particularly of occult metastatic lymph nodes in the neck. A second challenge is the lack of biomarkers for personalized therapy. There are a number of treatment modalities that can be employed both single and in combination, but at present only site and stage of the tumor are used for treatment planning. Provided here is an overview of the successes and failures of molecular diagnostic approaches that have been and are being evaluated to address these clinical challenges.