Current Opinion in Otolaryngology & Head and Neck Surgery最新文献

Purpose of review: To highlight the recent literature on the use of hyperspectral imaging (HSI) for cancer margin evaluation ex vivo, for head and neck cancer pathology and in vivo during head and neck cancer surgery.

Recent findings: HSI can be used ex vivo on unstained and stained tissue sections to analyze head and neck tissue and tumor cells in combination with machine learning approaches to analyze head and neck cancer cell characteristics and to discriminate the tumor border from normal tissue. Data on in vivo applications during head and neck cancer surgery are preliminary and limited. Even now an accuracy of 80% for tumor versus nonneoplastic tissue classification can be achieved for certain tasks, within the current in vivo settings.

Summary: Significant progress has been made to introduce HSI for ex vivo head and neck cancer pathology evaluation and for an intraoperative use to define the tumor margins. To optimize the accuracy for in vivo use, larger HSI databases with annotations for head and neck cancer are needed.

Purpose of review: To summarize the recent literature on epidemiology, clinical findings, treatment, and survival of laryngeal verrucous cell carcinoma (LVC).

Recent findings: Epidemiological studies report that LVC accounts for 1-3% of all laryngeal cancers. The incidence is decreasing, while most patients are male individuals and smokers. LVC are commonly detected in early stages because they are more frequently located in the glottic region. Tobacco, alcohol overuse, and, possibly, human papilloma virus are the main contributing factors. Recent studies confirm that surgery is the primary therapeutic approach with better prognosis when compared with other treatment modalities. Surgery alone is associated with 86.8% disease-free and 80.3% overall survival rates, while metastases are anecdotal.

Summary: LVC presents different clinical, pathological, and survival outcomes when compared with the classic laryngeal squamous cell carcinoma. Biopsies need often to be repeated before getting the most appropriate diagnosis; this supports the need of large-sample biopsy during the tumor diagnosis and staging. The glottic location of most LVC leads to detection of this lesion in its early stages, with ensuing better survival and outcomes after surgery compared with the classic form of squamous cell carcinoma. Future studies are needed to understand the biology of LVC and its related better prognostic outcomes when compared to other laryngeal malignancies.

Purpose of review: This review aims to describe the oncological outcomes of T4b oral squamous cell carcinomas (OSCC) with masticatory space involvement as well as the surgical approaches that are able to achieve compartmental 'en bloc' resection of these lesions.

Recent findings: The masticatory space is subdivided into infra-notch and supra-notch spaces according to the axial plane passing through the mandibular notch between the coronoid process and the condyle neck. Compartmental resection for T4b OSCC with masticatory space invasion can be successfully achieved via purely external approaches or combining external and transnasal endoscopic routes. Infra-notch T4b OSCC showed survival outcomes comparable to T4a OSCC, thus prompting treatment with curative intent.

Summary: Compartmental resection of the masticatory space is technically feasible with comprehensive control of tumour margins. Use of a transnasal endoscopic anterior route within a multiportal approach may provide better control of margins at the level of the pterygo-maxillary fissure. Equivalent survival outcomes between T4a and infra-notch T4b OSCC are reported. Thus, a downstaging of the latter to T4a is advisable and compartmental surgery of such advanced lesions could be considered as a first-line treatment option in selected patients.

Purpose of review: This review critically assesses the current literature and guidelines, aiming to clarify some of the most important factors that impact surgical strategies of head and neck nonmelanoma skin cancers (NMSCs), focusing on squamous, basal, and Merkel cell carcinomas.

Recent findings: Recent developments underscore the complexity of treatment for NMSC, particularly in the head and neck region. There is a lack of high-level evidence for the management of these tumors, especially in advanced stages. The need to tailor the extent of surgical margins and parotid/neck management to different histotypes, considering the varying risk factors for recurrence, is beginning to emerge in the literature. Moreover, the role of immunotherapy and targeted therapies for locally advanced disease, alongside traditional treatment options, is progressively growing.

Summary: NMSCs represent a heterogeneous group of malignancies with varying treatment complexities and prognoses. Management of NMSC is evolving towards an increasingly personalized strategy within a multidisciplinary therapeutic framework.

Purpose of review: The purpose of this review is to present recent advances and limitations in machine learning applied to the evaluation of speech, voice, and swallowing in head and neck cancer.

Recent findings: Novel machine learning models incorporating diverse data modalities with improved discriminatory capabilities have been developed for predicting toxicities following head and neck cancer therapy, including dysphagia, dysphonia, xerostomia, and weight loss as well as guiding treatment planning. Machine learning has been applied to the care of posttreatment voice and swallowing dysfunction by offering objective and standardized assessments and aiding innovative technologies for functional restoration. Voice and speech are also being utilized in machine learning algorithms to screen laryngeal cancer.

Summary: Machine learning has the potential to help optimize, assess, predict, and rehabilitate voice and swallowing function in head and neck cancer patients as well as aid in cancer screening. However, existing studies are limited by the lack of sufficient external validation and generalizability, insufficient transparency and reproducibility, and no clear superior predictive modeling strategies. Algorithms and applications will need to be trained on large multiinstitutional data sets, incorporate sociodemographic data to reduce bias, and achieve validation through clinical trials for optimal performance and utility.