Osteoradionecrosis after postoperative radiotherapy for oral cavity cancer: A retrospective cohort study

Label-free rapid diagnosis of jaw osteonecrosis via the intersection of Raman spectroscopy and deep learning

OBJECTIVES

To establish a precise and efficient diagnostic framework for distinguishing medication-related osteonecrosis of the jaw, radiation-induced osteonecrosis of the jaw, and normal bone tissue, thus enhancing clinical decision-making and enabling targeted therapeutic interventions.

METHODS

Raman spectroscopy was applied to investigate bone mineral composition, organic matrix content, and crystallinity in ninety bone tissue samples (30 MRONJ, 30 ORN, 30 control). Each mandible underwent 10 randomized spectral acquisitions, yielding 900 spectra across 200-2200 cm-1. The raw spectral data were preprocessed using Labspec6 software (Horiba Scientific). Principal component analysis (PCA) and linear discriminant analysis (LDA) were employed for feature extraction and classification. Additionally, a ResNet18 deep learning architecture was employed to enhance diagnostic accuracy. The model's performance was evaluated using precision, recall, and the area under the receiver operating characteristic curve to ensure robustness.

RESULTS

The PCA-LDA integration achieved 90.3 % accuracy in differentiating MRONJ, ORN, and healthy bone， with leave-one-out cross-validation confirming 89.1 % classification robustness. Furthermore, the ResNet18 deep learning model outperformed traditional classification methods, achieving 0.926 ± 0.024 accuracy, 0.924 ± 0.026 precision, 0.926 ± 0.024 recall, and 0.985 ± 0.007 AUROC on the validation set.

SIGNIFICANCE

These findings underscore the significant potential of combining Raman spectroscopy with advanced deep learning techniques as a rapid, noninvasive, and highly reliable diagnostic tool. This approach not only enhances the ability to differentiate between MRONJ and ORN but also offers substantial implications for improving patient management and therapeutic outcomes in clinical practice.

Externally validated digital decision support tool for time-to-osteoradionecrosis risk-stratification using right-censored multi-institutional observational cohorts

BACKGROUND

Existing studies on osteoradionecrosis of the jaw (ORNJ) have primarily used cross-sectional data, assessing risk factors at a single time point. Determining the time-to-event profile of ORNJ has important implications to monitor oral health in head and neck cancer (HNC) long-term survivors.

METHODS

Data were retrospectively obtained for a clinical observational cohort of 1129 patients (198 ORNJ cases) with HNC treated with radiotherapy (RT) at The University of Texas MD Anderson Cancer Center. A Weibull Accelerated Failure Time model was trained on previously identified dosimetric, clinical and demographic predictors. External validation was performed using an independent cohort of 265 patients (92 ORNJ cases) treated at Guy's and St. Thomas' Hospitals. To facilitate clinical implementation of the model, an online graphical user interface (GUI) was developed, including formal stakeholder usability testing.

RESULTS

Our model identified that gender (males), pre-RT dental extractions and D25% were associated with a 38 %, 27 % and 12 % faster onset of ORNJ, respectively, with adjusted time ratios of 0.62 (p = 0.11), 0.73 (p = 0.13) and 0.88 (p < 0.005). The model demonstrated strong internal calibration (integrated Brier score of 0.133, D-calibration p-value 0.998) and optimal discrimination at 72 months (Harrell's C-index of 0.72).

CONCLUSION

This study is the first to demonstrate a direct relationship between radiation dose and the time to ORNJ onset, providing a novel characterization of the impact of delivered dose and patient-related factors not only on the probability of a late effect (ORNJ), but the conditional risk during survivorship.

Impact of Oral Health on the Incidence of Osteoradionecrosis and Oral Mucositis in Tonsil Cancer Patients Treated With Radiotherapy-A Retrospective Cohort Study

OBJECTIVE

To clarify the clinical significance of oral health in the occurrence of oral complications of radiotherapy in patients with tonsil cancer.

STUDY DESIGN

This was a retrospective cohort study in patients with tonsil cancer who received radiotherapy. Oral health status was assessed from dental panoramic tomography images. The associations between age, sex, smoking and alcohol use, and regular glucocorticoid medication and the outcome variables of oral mucositis (OM) and osteoradionecrosis (ORN) were evaluated.

RESULTS

Altogether 107 primary tonsil carcinoma patients were included in the analyses. Most patients (86%) had clinically notable radiation-induced OM. No significant associations were observed between oral health variables and OM occurrence. ORN occurred in 10% of the patients followed for at least 2 years. There was an association between ORN and oral health. Presence of teeth in poor condition was associated with ORN occurrence.

CONCLUSION

Poor oral health is linked to ORN. The association remained even when dental infections were treated before radiotherapy. These findings emphasize the role of oral bacteria and chronic inflammation in ORN. Infection-free dentition and good oral health prevent difficult complications of radiotherapy.

STATEMENT OF CLINICAL RELEVANCE

Infection-free dentition and good oral health prevent difficult complications of radiotherapy.

Identification and management of recurrent oral squamous cell carcinoma in the clinical presentation of osteoradionecrosis: a single-center case series for treatment experience sharing

INTRODUCTION

Radiotherapy is an integral component of the comprehensive and sequential treatment approach for advanced oral squamous cell carcinoma (OSCC). One of the significant complications associated with radiotherapy is osteoradionecrosis (ORN), which most frequently affects the mandible. Differentiating between osteoradionecrosis (ORN) and recurrent oral squamous cell carcinoma (ORSCC) can be challenging when relying solely on clinical and radiologic characteristics. The diagnosis becomes even more difficult when bone necrosis of jaw presents as the first clinical symptom.

OBJECTIVES

This study aims to present the clinical manifestations and treatment processes of patients at our institution who have developed bone necrosis of jaw after radiotherapy and subsequently diagnosed with recurrent oral squamous cell carcinoma (ORSCC).

CASE PRESENTATION

We have collected six patients with recurrent oral squamous cell carcinoma (ORSCC) who developed bone necrosis of jaw after radiotherapy. These patients subsequently underwent surgical repair and reconstruction and were eventually diagnosed with ORSCC. We present a case series reviewing their basic characteristics, radiological reports, surgical treatment, and pathological diagnosis. All six patients initially presented with oral or facial pain and were diagnosed with osteoradionecrosis (ORN) through imaging studies. All patients underwent surgical treatment, with free flaps used to repair postoperative defects. Among them, five patients were diagnosed with tumor recurrence through preoperative or intraoperative frozen biopsy, and one patient was confirmed with recurrence in the osseous resection through postoperative examination.

CONCLUSION

Identified ORSCC in the suspected ORN of the jaw following radiotherapy is relatively rare, yet it poses identification challenges and can significantly impact treatment decisions. Consequently, surgeons must remain vigilant and ensure clear pathological diagnoses for suspicious patients, either before or during surgery.

Postoperative fever following surgery for oral cancer: Incidence, risk factors, and the formulation of a machine learning-based predictive model

BACKGROUND

Postoperative fever (POF) is a common occurrence in patients undergoing major surgery, presenting challenges and burdens for both patients and surgeons yet. This study endeavors to examine the incidence, identify risk factors, and establish a machine learning-based predictive model for POF following surgery of oral cancer.

METHODS

A total of seven hundred and twenty-seven consecutive patients undergoing radical resection of oral cancer were retrospectively investigated. The analysis encompassed 34 parameters, incorporating demographic and clinical characteristics, biochemical and hematological assay results, surgical-related data, hospitalization costs and stay in hospital. Six machine learning models were compared by the area under the receiver operating characteristic curve (AUC). The best-performing models were selected for further analyze, including feature importance evaluation and nomogram analysis, identifying key POF risk factors, and establish a comprehensive prediction model.

RESULTS

A total of 466 patients with surgery for oral cancer met the criteria, with an average age of (54.2 ± 11.1) years, including an POF group (n = 197) and a non-POF group (n = 269). The fever group has greater hospitalization costs, longer lengths of stay, and higher infection biochemical indicators (leucocyte ratio and erythrocyte sedimentation rate). Furthermore, Among the 6 machine learning models, logistic regression models performed best, with the higher AUC and accuracy. In univariate and multivariate logistic analysis showed that age, sex, reoperation, Charlson Comorbidity Index score (CCI), leukocyte, bleeding and blood transfusion were independent risk factors for POF of patients following surgery in oral cancer. Then seven variables were selected to establish the nomogram for predict the probability of POF by nomogram algorithm.

CONCLUSIONS

Postoperative fever patients following radical resection of oral cancer have greater burden. Machine learning algorithms can be effectively used to identify potential risk factors of POF, which may enhance individualized treatment plans in oral cancer patient during perioperative period.

Comparison of deep-learning multimodality data fusion strategies in mandibular osteoradionecrosis NTCP modelling using clinical variables and radiation dose distribution volumes

Objective.Normal tissue complication probability (NTCP) modelling is rapidly embracing deep learning (DL) methods, acknowledging the importance of spatial dose information. Finding effective ways to combine information from radiation dose distribution maps (dosiomics) and clinical data involves technical challenges and requires domain knowledge. We propose different multi-modality data fusion strategies to facilitate future DL-based NTCP studies.Approach.Early, joint and late DL multi-modality fusion strategies were compared using clinical and mandibular radiation dose distribution volumes. These were contrasted with single-modality models: a random forest trained on non-image data (clinical, demographic and dose-volume metrics) and a 3D DenseNet-40 trained on image data (mandibular dose distribution maps). The study involved a matched cohort of 92 osteoradionecrosis cases and 92 controls from a single institution.Main results.The late fusion model exhibited superior discrimination and calibration performance, while the join fusion achieved a more balanced distribution of the predicted probabilities. Discrimination performance did not significantly differ between strategies. Late fusion, though less technically complex, lacks crucial inter-modality interactions for NTCP modelling. In contrast, joint fusion, despite its complexity, resulted in a single network training process which included intra- and inter-modality interactions in its model parameter optimisation.Significance.This study is a pioneering effort in comparing different strategies for including image data into DL-based NTCP models in combination with lower dimensional data such as clinical variables. The discrimination performance of such multi-modality NTCP models and the choice of fusion strategy will depend on the distribution and quality of both types of data. Multiple data fusion strategies should be compared and reported in multi-modality NTCP modelling using DL.

External validation of a multimodality deep-learning normal tissue complication probability model for mandibular osteoradionecrosis trained on 3D radiation distribution maps and clinical variables

Background and purpose

While the inclusion of spatial dose information in deep learning (DL)-based normal-tissue complication probability (NTCP) models has been the focus of recent research studies, external validation is still lacking. This study aimed to externally validate a DL-based NTCP model for mandibular osteoradionecrosis (ORN) trained on 3D radiation dose distribution maps and clinical variables.

Methods and materials

A 3D DenseNet-40 convolutional neural network (3D-mDN40) was trained on clinical and radiation dose distribution maps on a retrospective class-balanced matched cohort of 184 subjects. A second model (3D-DN40) was trained on dose maps only and both DL models were compared to a logistic regression (LR) model trained on DVH metrics and clinical variables. All models were externally validated by means of their discriminative ability and calibration on an independent dataset of 82 subjects.

Results

No significant difference in performance was observed between models. In internal validation, these exhibited similar Brier scores around 0.2, Log Loss values of 0.6-0.7 and ROC AUC values around 0.7 (internal) and 0.6 (external). Differences in clinical variable distributions and their effect sizes were observed between internal and external cohorts, such as smoking status (0.6 vs. 0.1) and chemotherapy (0.1 vs. -0.5), respectively.

Conclusion

To our knowledge, this is the first study to externally validate a multimodality DL-based ORN NTCP model. Utilising mandible dose distribution maps, these models show promise for enhancing spatial risk assessment and guiding dental and oncological decision-making, though further research is essential to address overfitting and domain shift for reliable clinical use.

Timing of development of osteoradionecrosis post head and neck radiotherapy: does a safe time interval exist for dental extraction?

INTRODUCTION

Risk factors for developing osteoradionecrosis (ORN) are well known, but less is known about factors influencing the interval between radiotherapy and the onset of ORN. Also, it is unknown whether there is any specific period post-radiotherapy with a reduced probability of ORN when irradiated teeth require extraction.

PURPOSE

The primary aim of this study was to identify factors influencing the interval in developing ORN in the following subgroups of patients: (1) patients who spontaneously developed ORN, (2) surgical-intervention-related ORN with a particular focus on patients after mandibulectomy. The secondary aim was to attempt to identify a possible time for safer dental intervention after primary treatment.

MATERIALS AND METHODS

The authors retrospectively analysed 1608 head and neck cancer (HNC) patients treated in a single centre. Time intervals were measured from the end of radiotherapy to the development of ORN and further analysed in the subgroups listed above.

RESULTS

In all, 141 patients (8.8%) developed intra-oral ORN. Median time from radiotherapy to ORN development in the whole cohort was 9 months. Median interval for spontaneous ORN was 8 months, 6.5 months for intervention-related ORN, and 15 months for patients post-mandibulectomy. In patients who required dental extraction preradiotherapy, median interval of ORN onset was 5 months.

CONCLUSION

In our study, a slightly higher proportion of patients with intervention developed ORN earlier in comparison with spontaneous ORN. The period from 12-18 months after radiotherapy was identified as having the highest probability of developing ORN in patients after mandibulectomy. A time for safer dental intervention after primary treatment was not identified.

Mandibular dose-volume predicts time-to-osteoradionecrosis in an actuarial normal-tissue complication probability (NTCP) model: External validation of right-censored clinico-dosimetric and competing risk application across international multi-institutional observational cohorts and online graphical user interface clinical support tool assessment

Background

Existing studies on osteoradionecrosis of the jaw (ORNJ) have primarily used cross-sectional data, assessing risk factors at a single time point. Determining the time-to-event profile of ORNJ has important implications to monitor oral health in head and neck cancer (HNC) long-term survivors.

Methods

Demographic, clinical and dosimetric data were retrospectively obtained for a clinical observational cohort of 1129 patients with HNC treated with radiotherapy (RT) at The University of Texas MD Anderson Cancer Center. ORNJ was diagnosed in 198 patients (18%). A multivariable logistic regression analysis with forward stepwise variable selection identified significant predictors for ORNJ. These predictors were then used to train a Weibull Accelerated Failure Time (AFT) model, which was externally validated using an independent cohort of 265 patients (92 ORNJ cases and 173 controls) treated at Guy's and St. Thomas' Hospitals.

Findings

Our model identified that each unit increase in D25% is significantly associated with a 12% shorter time to ORNJ (Adjusted Time Ratio [ATR] 0·88, p<0·005); pre-RT dental extractions was associated to a 27% faster (ATR 0·73, p=0·13) onset of ORNJ; male patients experienced a 38% shorter time to ORNJ (ATR 0·62, p = 0·11). The model demonstrated strong internal calibration (integrated Brier score of 0·133, D-calibration p-value 0.998) and optimal discrimination at 72 months (Harrell's C-index of 0·72). The model also showed good generalization to the independent cohort, despite a slight drop in performance.

Interpretation

This study is the first to demonstrate a direct relationship between radiation dose and the time to ORNJ onset, providing a novel characterization of the impact of delivered dose not only on the probability of a late effect (ORNJ), but the conditional risk during survivorship.

Funding

This work was supported by various funding sources including NIH, NIDCR, NCI, NAPT, NASA, BCM, Affirmed Pharma, CRUK, KWF Dutch Cancer Society, NWO ZonMw, and the Apache Corporation.

The incidence of osteoradionecrosis of the jaws in oral cavity cancer patients treated with intensity-modulated radiotherapy: a systematic review and meta-analysis

OBJECTIVE

A systematic review with meta-analysis was conducted to define the incidence of osteoradionecrosis (ORN) in patients with oral cavity cancer (OCC) treated with intensity-modulated radiotherapy (IMRT), and to identify the risk factors influencing its development.

STUDY DESIGN

Six databases were searched systematically. A meta-analysis was performed to determine overall, spontaneous, and dental extraction-attributed incidences of ORN. The Grading of Recommendations Assessment, Development, and Evaluation tool evaluated evidence certainty.

RESULTS

Out of 11 eligible studies, 6 underwent meta-analysis for the overall aggregated ORN incidence in OCC patients receiving IMRT, resulting in an incidence rate of 8% (95% CI: 6%-11%). Regarding development reasons, 2 studies were assessed, revealing an incidence of 36% (95% CI: 1%-98%) for spontaneous ORN, and 17% (95% CI: 5%-44%) ensued from dental extraction exclusively pre-RT. All rates had very low certainty of evidence. Factors significantly correlated with ORN development included postoperative RT use (78%), employment of therapeutic doses above 50 Gy, and mandibular involvement (80.5%).

CONCLUSION

The findings suggest that IMRT alone is not sufficient to decrease ORN rates in OCC patients, underscoring the importance of precisely identifying the involved risk factors. However, further detailed primary studies will be necessary.

Prevalence and Factors Influencing Post-Operative Complications following Tooth Extraction: A Narrative Review

Background

Complications from dental extractions may result in multiple post-operative visits and adversely affect the patient's life. Preventing complications may decrease post-operative morbidity for the individual as well as lower societal costs, such as lost time from work and healthcare costs.

Objectives

This narrative review aims to assess the prevalence and factors influencing post-operative complications following tooth extraction, helping clinicians minimise the risk. Data Sources. Cross-sectional studies. Study Eligibility and Participants. Patients undergoing dental extractions. Our exclusion criteria included in vitro studies, animal studies, terminally ill patients, and tooth loss not due to dental extraction. Literature was collected from "PubMed" and "Web of Science" through search criteria based on the "PICO" framework. Twenty articles were used to formulate a prevalence table, and 156 articles were included for the factors influencing complications. Study Appraisal and Synthesis Methods. This narrative review was reported using the SANRA (a scale for the quality assessment of narrative review articles) checklist. Due to the scope of our narrative review and its associated objectives, the quality of cross-sectional studies (AXIS) will be conducted from the studies outlining the prevalence.

Results

Alveolar osteitis appears to be the most prevalent post-operative complication following tooth extraction. Predisposing factors can be significant in their ability to alter the risk of postoperative complications, and clinicians should provide patient-centred care to mitigate this risk. Limitations. Due to the breadth of context, a systematic review was not feasible, as it may have introduced heterogeneity.

Conclusion

This narrative review has highlighted an array of factors which can influence the prevalence of post-operative complications. Future research would benefit from individually reporting post-operative complications, reducing the heterogeneity in definitions of the complications, and including greater detail on the predisposing factors studied.

Osteoradionecrosis - an old problem with new consequences

PURPOSE OF REVIEW

Osteoradionecrosis (ORN) is a devasting complication of radiation therapy (RT), especially in head and neck cancers (HNC), and is still poorly understood. The aim of this review is to report its incidence and consider the risk factors associated with ORN to highlight prevention strategies to decrease its incidence.

RECENT FINDINGS

The average incidence of ORN is between 2% and 23%, with incidence decreasing in more recent years with the introduction of modern RT technology and better oral health care. Smoking, diabetes mellitus, oropharyngeal and oral cavity cancers, pre- and post-RT dental extractions and a total radiation dose of over 60 Gy were all identified as risk factors for ORN. In prevention, strategies were mainly structured around minimising risk factors or targeting possible mechanisms of ORN's pathophysiology.

SUMMARY

At present, the controversy surrounding the risk factors and pathogenesis of ORN makes it difficult to establish a set of prevention guidelines for its incidence. In order to achieve this, more research examining its aetiology must be conducted as well as a universal staging system within which ORN may be classified.

A Patient with a History of Tonsillar Cancer Presents for Evaluation of Exposed Alveolar Bone in the Mouth

Osteoradionecrosis (ORN) is a rare but serious late complication of head and neck radiation therapy. The mandible, proximity of the primary tumor to the jawbones, radiation dose, poor oral hygiene, and smoking history are risk factors of ORN. ORN manifests as a chronic infection with exposed jawbone, which typically occurs in the first 3 years after radiotherapy; however, the risk for ORN development occurring in the patients who have undergone head and neck radiation therapy may be indefinite. Surgery has an important role in the management of cases of ORN, ranging from sequestrectomy, debridement, and extensive extirpative procedures with reconstructive surgery.

The added values of 18F-FDG PET/CT in differentiating cancer recurrence and osteoradionecrosis of mandible in patients with treated oral squamous cell carcinoma

BACKGROUND

Osteoradionecrosis (ORN) of the jaw requires a differential diagnosis to exclude cancer recurrence. Here, we sought to develop a scoring system comprising ¹⁸F-FDG PET/CT parameters for distinguishing between the two conditions in patients with oral squamous cell carcinoma (OSCC).

METHODS

The study consisted of 103 OSCC patients with suspected ORN of the jaw. All participants underwent ¹⁸F-FDG PET/CT imaging within 6 months of diagnostic histopathology. Following extraction of PET parameters, we identified clinical and imaging predictors of mandibular recurrence-free survival (MRFS) using receiver operating characteristic curve analysis and multivariate Cox regression models.

RESULTS

The results of histopathology revealed mandibular cancer recurrence in 24 patients (23.3%). Multivariate Cox regression analyses identified an age at diagnosis ≤ 52 years (P = 0.013), a location of the SUVmax voxel with soft tissue predominance (P = 0.019), and mandibular total lesion glycolysis (TLG) > 62.68 g (P < 0.001) as independent risk factors for MRFS. A scoring system was devised with scores from 0 (no risk factor) to 3 (presence of all three risk factors). High-risk patients with a score of 2-3 compared with score of 0-1 had a significantly higher likelihood of mandibular cancer recurrence (hazard ratio: 32.50, 95% confidence interval: 8.51-124.18, P < 0.001). The scoring system had a sensitivity of 87.50%, a specificity of 82.28%, and an accuracy of 83.50% for identifying mandibular cancer recurrence.

CONCLUSIONS

The scoring system of our study is clinically useful for identifying mandibular cancer recurrence in patients with suspected ORN of the jaw.

Considerations for radiotherapy planning with MV photons using dose-to-medium

Background and purpose

Radiotherapy planning considerations were developed for the previous calculation algorithms yielding dose to water-in-water (D_w,w). Advanced algorithms improve accuracy, but their dose values in terms of dose to medium-in-medium (D_m,m) depend on the medium considered. This work aimed to show how mimicking D_w,w planning with D_m,m can introduce new issues.

Materials and methods

A head and neck case involving bone and metal heterogeneities outside the CTV was considered. Two different commercial algorithms were used to obtain D_m,m and D_w,w distributions. First, a plan was optimised to irradiate the PTV uniformly and get a homogeneous D_w,w distribution. Second, another plan was optimised to achieve homogeneous D_m,m. Both plans were calculated with D_w,w and D_m,m, and the differences between their dose distributions, clinical impact, and robustness were evaluated.

Results

Uniform irradiation produced D_m,m cold spots in bone (-4%) and implants (-10%). Uniform D_m,m compensated them by increasing fluence but, when recalculated in D_w,w, the fluence compensations produced higher doses that affected homogeneity. Additionally, doses were 1% higher for the target, and + 4% for the mandible, thus increasing toxicity risk. Robustness was impaired when increased fluence regions and heterogeneities mismatched.

Conclusion

Planning with D_m,m as with D_w,w can impact clinical outcome and impair robustness. In optimisation, uniform irradiation instead of homogeneous D_m,m distributions should be pursued when media with different D_m,m responses are involved. However, this requires adapting evaluation criteria or avoiding medium effects. Regardless of the approach, there can be systematic differences in dose prescription and constraints.

Dual-Functional Nanoplatform Based on Bimetallic Metal-Organic Frameworks for Synergistic Starvation and Chemodynamic Therapy

Tumor microenvironment (TME)-responsive chemodynamic therapy (CDT) mediated by nanozymes has been extensively studied in oral squamous cell carcinoma. However, the low catalytic efficiency due to insufficient H₂O₂ in the TME is still a major challenge for its clinical translation. Herein, we present an antitumor nanoplatform based on a Mn-Co organometallic framework material (MnCoMOF), which shows peroxidase-like (POD-like) activity, loaded with glucose oxidase (GOx@MnCoMOF), demonstrating the ability of H₂O₂ self-supply and H₂O₂ conversion to toxic hydroxyl radicals. The encapsulated GOx efficiently catalyzes glucose into gluconic acid and H₂O₂ at the tumor site, which can cut off the energy supply to inhibit tumor growth and produce a large amount of H₂O₂ and acid to compensate for their lack in the tumor microenvironment. The POD-like activity of MnCoMOF can convert H₂O₂ into hydroxyl radicals and eliminate tumor cells. The nanoplatform exhibits enhanced tumor cell cytotoxicity in a high-glucose medium compared with a low-glucose medium, illustrating sufficient generation of H₂O₂ from glucose by GOx. The in vivo results indicate that GOx@MnCoMOF has excellent antitumor efficacy and can remodel the immune-suppressive tumor microenvironment. In conclusion, the GOx@MnCoMOF nanoplatform possesses dual enzymatic activities, i.e., POD-like and glucose oxidase, to achieve improved tumor-suppressive efficiency through synergistic starvation and chemodynamic therapy, thus providing a new strategy for the clinical treatment of oral cancer.

The Progress in Reconstruction of Mandibular Defect Caused by Osteoradionecrosis

Osteoradionecrosis (ORN) is described as a disease with exposed, nonviable bone that fails to heal spontaneously or by means of conservative treatment after radiotherapy in at least 3 months. Though traditional theories in the early stage including hypoxic-hypocellular-hypovascular and fibro-atrophic in addition to new findings such as ferroptosis were put forward to explain the mechanisms of the osteoradionecrosis, the etiology of ORN is still unclear. With the high rate of occurrence in the head and neck area, especially in the mandible, this disease can disrupt the shape and function of the irradiated area, leading to a clinical presentation ranging from stable small areas of asymptomatic exposed bone to severe progressive necrosis. In severe cases, patients may experience pain, xerostomia, dysphagia, facial fistulas, and even a jaw defect. Consequently, sequence therapy and sometimes extensive surgery and reconstructions are needed to manage these sequelae. Treatment options may include pain medication, antibiotics, the removal of sequesters, hyperbaric oxygen therapy, segmental resection of the mandible, and free flap reconstruction. Microanastomosed free-flaps are considered to be promising choice for ORN reconstruction in recent researches, and new methods including three-dimensional (3-D) printing, pentoxifylline, and amifostine are used nowadays in trying increase the success rates and improve quality of the reconstruction. This review summarizes the main research progress in osteoradionecrosis and reconstruction treatment of osteoradionecrosis with mandibular defect.

Osteoradionecrosis After Mandibulotomy and Marginal Mandibulectomy in Patients With Oral Cancer

Objectives Osteoradionecrosis is one of the most severe complications in patients with head and neck cancer, which is characterized by persistent exposed and devitalized bone without proper healing after radiation. The extent to which mandibulotomy and marginal mandibulectomy influence the occurrence of osteoradionecrosis remains unclear. This study evaluated the incidence and risk factors for developing osteoradionecrosis of the mandible after oral cancer treatments. Methods A retrospective study was performed to analyze medical records of patients who underwent surgery and postoperative radiotherapy for oral cancers from 2009 to 2019 at a tertiary care hospital. Patient characteristics, incidence, and risk factors for developing osteoradionecrosis were reviewed. Comparisons between continuous and categorical data were performed using t-test and Chi-squared test. Cox regression analysis was used to assess the association between factors and the development of osteoradionecrosis. Results Among the 61 patients included in the study, osteoradionecrosis of the mandible occurred in 9 of 32 (28.1%) patients who underwent mandibular surgery during oral cancer resection (marginal mandibulectomy and/or mandibulotomy) and 2 of 29 (6.9%) patients without mandibular surgery. The development of osteoradionecrosis was significantly associated with performing mandibular surgery (hazard ratio 4.64, 95% confidence interval: 1.002, 21.5) and HIV infection (hazard ratio 8.53, 95% confidence interval: 2.2, 33.3). In the subgroup analysis of mandibular surgery, the development of osteoradionecrosis significantly increased in patients undergoing mandibulotomy (hazard ratio 6.62, 95% confidence interval: 1.3, 34.8) but not in patients undergoing marginal mandibulectomy (hazard ratio 3.56, 95% confidence interval: 0.6, 22.0). The analysis also showed that concurrent chemoradiation, radiation doses ≥ 60 Gy, and smoking were potential risk factors for the development of osteoradionecrosis, but none of these factors were statistically significant. Conclusion Our findings suggest that mandibular surgery is a significant risk factor for the development of osteoradionecrosis in patients with oral cancer. Further studies including larger population sizes are required to verify these findings.

Association between radiotherapy for surgically treated oral cavity cancer and secondary lung cancer

Background

There is limited research on the incidence of secondary lung cancer (SLC) after radiotherapy (RT) for oral cavity cancer (OCC). Therefore, we investigated the association between RT for OCC and the risk of SLC and the overall survival of these patients.

Methods

Patients diagnosed with OCC between 1975 and 2015 were selected from the Surveillance, Epidemiology, and End Results database. The cumulative incidence of SLC, relative risk (RR) of RT vs. no RT (NRT), standardized incidence ratios (SIR), and survival outcomes were assessed.

Results

A total of 10,936 patients with OCC were included. Of these, 429 (3.92%) patients developed SLC, where 136 (5.02%) received RT and 293 (3.56%) did not. The cumulative incidence of SLC during follow-up was 6.89% and 4.84% in the RT and NRT patients, respectively. RT was associated with a higher risk of SLC. In the subset analysis, the results showed that a higher risk of developing SLC among patients with index OCC in most subgroups. Dynamic RR and SIR revealed a decreased risk of SLC with increasing latency time. No difference was observed in the 10-year survival rates for patients with SLC who received RT or not or compared with primary lung cancer.

Conclusion

RT was associated with a higher risk of SLC, and patients diagnosed with OCC could be followed for 5-10 years after diagnosis.