Enhancing quality of life in head and neck cancer patients: a comparative analysis of 3D exoscope-assisted surgery vs. traditional approaches.

Introduction: The increasing population of survivors of head and neck carcinomas is becoming more conspicuous. Consequently, the pivotal role of quality of life, particularly elucidated through the assessment of dysphagia and dysphonia, is progressively influencing the decision-making process. The current study aims to assess whether VITOM 3D could offer a comparable post-treatment quality of life to traditional approaches for patients with laryngeal cancer and oro-hypopharyngeal cancer. Methods: A case series of laryngeal cancer and oro-hypopharyngeal cancer patients treated either with an exoscopic-assisted surgical setup and with conventional treatments (transoral microsurgery and radio-chemotherapy) at the Otolaryngology Unit of IRCCS San Martino Hospital, Genoa, is presented. The post-treatment quality of life of the two cohorts were compared through the administration of the University of Washington Quality of Life Questionnaire, Voiceik Handicap Index-10, M.D. Anderson Dysphagia Inventory were administrated to both cohorts of patients. Results: In the laryngeal cancer group, a total of 79 patients were included. Of these, 50.1% underwent transoral exoscope-assisted surgery, while 49.9% underwent primary transoral microscopic-assisted surgical approach. No significant differences were observed in terms of the University of Washington Quality of Life Questionnaire and Voice Handicap Index-10 between the two subgroups. Conversely, in the oro-hypopharyngeal cancer group, 43 patients were included. Of these, 37.2% underwent primary transoral exoscope-assisted surgery, while 62.8% received (chemo)radiotherapy. No notable differences were reported in terms of the University of Washington Quality of Life Questionnaire and M.D. Anderson Dysphagia Inventory between the transoral exoscope-assisted surgery and (chemo)radiotherapy subgroups. Conclusions: Assessments of quality of life, conducted through the University of Washington Quality of Life Questionnaire questionnaire, dysphonia evaluations using the Voice Handicap Index-10, and dysphagia assessments employing the M.D. Anderson Dysphagia Inventory questionnaire, demonstrate analogous outcomes between conventional treatment modalities and transoral interventions utilizing the 3D exoscope.

An automated approach for real-time informative frames classification in laryngeal endoscopy using deep learning.

PURPOSE: Informative image selection in laryngoscopy has the potential for improving automatic data extraction alone, for selective data storage and a faster review process, or in combination with other artificial intelligence (AI) detection or diagnosis models. This paper aims to demonstrate the feasibility of AI in providing automatic informative laryngoscopy frame selection also capable of working in real-time providing visual feedback to guide the otolaryngologist during the examination. METHODS: Several deep learning models were trained and tested on an internal dataset (n = 5147 images) and then tested on an external test set (n = 646 images) composed of both white light and narrow band images. Four videos were used to assess the real-time performance of the best-performing model. RESULTS: ResNet-50, pre-trained with the pretext strategy, reached a precision = 95% vs. 97%, recall = 97% vs, 89%, and the F1-score = 96% vs. 93% on the internal and external test set respectively (p = 0.062). The four testing videos are provided in the supplemental materials. CONCLUSION: The deep learning model demonstrated excellent performance in identifying diagnostically relevant frames within laryngoscopic videos. With its solid accuracy and real-time capabilities, the system is promising for its development in a clinical setting, either autonomously for objective quality control or in conjunction with other algorithms within a comprehensive AI toolset aimed at enhancing tumor detection and diagnosis.

The impact of margins in laryngeal cancer patients treated with transoral laser microsurgery: a systematic review and meta-analysis.

PURPOSE: In laryngeal squamous cell carcinoma (LSCC) treated with transoral laser microsurgery (TOLMS), the status of margins significantly affected local control. When a positive or close margin is present, there is no ubiquitous consensus regarding further treatments. The rationale of the present systematic review and meta-analysis is to investigate the survival impact of the status of the margins in patients affected by LSCC treated with TOLMS. DATA SOURCES: PubMed, EMBASE, and Cochrane Library. METHODS: We performed a systematic search, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Inclusion criteria were: patients affected by LSCC, staged according to the American Joint Committee on Cancer Staging System and treated by TOLMS without any previous treatment; margins status (close, positive, negative) and the adjusted hazard ratios (aHRs) with 95% confidence intervals (CIs) of overall survival, disease-specific survival, and disease-free survival has to be reported. RESULTS: Nine studies were deemed eligible for the qualitative analysis, and 3 for the quantitative analysis to investigate the association between margin status and OS. The cumulative number of patients was 3130. The sample size ranged from 96 to 747 patients. The follow-up period ranged from 0 to 201 months. The meta-analysis results show that positive margins have an aHR of 1.30 yet with CI range (0.56 to 2.97). CONCLUSIONS: Our current meta-analysis results are unable to definitively assess the real impact of resection margins on OS. Few authors provide accurate data regarding position and types of margins. Further prospective or high-quality studies are required.

Survival and complications after carotid resection for head and neck squamous cell carcinoma: A systematic review and pooled analysis.

OBJECTIVE: The aim of this study is to analyze oncologic outcomes and complications rate after common or internal carotid artery (CCA/ICA) resection for head and neck squamous cell carcinoma (HNSCC). METHODS: This study was conducted in conformity with the PRISMA statement. A systematic review and pooled analysis was performed for overall survival (OS), disease specific survival (DSS) (primary outcomes), and perioperative death rate (secondary outcome). RESULTS: A total of 276 patients (males: 76.7%, n = 191/249) with a median age of 59 years (n = 239/276; 95% CI 55.0-61.7) who underwent CCA/ICA resection for HNSCC were included. The median follow-up time was 11 months (n = 276). Estimated pooled OS rates (95% CI) at 1 and 2 years were 52.7% (46.9-59.2) and 29.8% (24.3-36.5), respectively. The median OS (95% CI) was 14 months (12-17). Estimated pooled DSS rates (95% CI) at 1 and 2 years were 58.6% (52.7-65.2) and 34.6% (28.5-41.9), respectively. The median DSS (95% CI) was 16 months (14-19). The perioperative death rate was 6.9% (n = 19/276). CONCLUSIONS: CCA/ICA resection should be considered as a treatment option for accurately selected patients. Multicentric prospective studies are recommended to develop a predictive score guiding the decision-making process.

Exploring the landscape of AI-assisted decision-making in head and neck cancer treatment: a comparative analysis of NCCN guidelines and ChatGPT responses.

PURPOSE: Recent breakthroughs in natural language processing and machine learning, exemplified by ChatGPT, have spurred a paradigm shift in healthcare. Released by OpenAI in November 2022, ChatGPT rapidly gained global attention. Trained on massive text datasets, this large language model holds immense potential to revolutionize healthcare. However, existing literature often overlooks the need for rigorous validation and real-world applicability. METHODS: This head-to-head comparative study assesses ChatGPT's capabilities in providing therapeutic recommendations for head and neck cancers. Simulating every NCCN Guidelines scenarios. ChatGPT is queried on primary treatments, adjuvant treatment, and follow-up, with responses compared to the NCCN Guidelines. Performance metrics, including sensitivity, specificity, and F1 score, are employed for assessment. RESULTS: The study includes 68 hypothetical cases and 204 clinical scenarios. ChatGPT exhibits promising capabilities in addressing NCCN-related queries, achieving high sensitivity and overall accuracy across primary treatment, adjuvant treatment, and follow-up. The study's metrics showcase robustness in providing relevant suggestions. However, a few inaccuracies are noted, especially in primary treatment scenarios. CONCLUSION: Our study highlights the proficiency of ChatGPT in providing treatment suggestions. The model's alignment with the NCCN Guidelines sets the stage for a nuanced exploration of AI's evolving role in oncological decision support. However, challenges related to the interpretability of AI in clinical decision-making and the importance of clinicians understanding the underlying principles of AI models remain unexplored. As AI continues to advance, collaborative efforts between models and medical experts are deemed essential for unlocking new frontiers in personalized cancer care.

Depth of Invasion Assessment in Laryngeal Glottic Carcinoma: A Preoperative Imaging Approach for Prognostication.

OBJECTIVE: The prognostic value of depth of invasion (DOI) in oral squamous cell cancer carcinoma and cutaneous melanoma is well established, while there is a lack of reports investigating the role of DOI in laryngeal cancer. This study aims to explore the association of glottic cancer DOI with other established pathological risk factors and nodal metastasis and evaluate the feasibility of measuring DOI preoperatively using tomographic imaging. METHODS: The medical records of glottic cancer patients treated between 2015 and 2020 in a single tertiary referral center were screened retrospectively. Pathologically measured DOI (pDOI) value was also reviewed and registered. Preoperative computer tomography (CT) was used to obtain the radiological DOI (rDOI) measured by two dedicated radiologists. Their inter-rated agreement was assessed and the correlation between pDOI and rDOI was calculated. pDOI association with the main pathology report features was assessed with univariable analysis. Cox univariable and multivariable models were used to explore the role of pDOI on survival. RESULTS: Ninety-one patients had pDOI data available, of which 59 also had rDOI data. A strong concordance between the two radiologists was found (concordance correlation coefficient = 0.96); rDOI and pDOI were highly and significantly correlated (R = 0.85; p < 0.001). pDOI was significantly higher in patients with perineural invasion (PNI; p < 0.001), lymphovascular invasion (LVI; p < 0.001), and nodal metastasis (p < 0.001). pDOI was associated with disease-free survival at univariable analysis (p = 0.04) while it did not show a significant impact (p = 0.10) at multivariable analysis. CONCLUSION: Glottic carcinoma DOI correlates with PNI, LVI, and nodal metastasis and it can be reliably assessed in a preoperative setting using CT imaging. LEVEL OF EVIDENCE: 3 Laryngoscope, 2024.

Real-Time Laryngeal Cancer Boundaries Delineation on White Light and Narrow-Band Imaging Laryngoscopy with Deep Learning.

OBJECTIVE: To investigate the potential of deep learning for automatically delineating (segmenting) laryngeal cancer superficial extent on endoscopic images and videos. METHODS: A retrospective study was conducted extracting and annotating white light (WL) and Narrow-Band Imaging (NBI) frames to train a segmentation model (SegMENT-Plus). Two external datasets were used for validation. The model's performances were compared with those of two otolaryngology residents. In addition, the model was tested on real intraoperative laryngoscopy videos. RESULTS: A total of 3933 images of laryngeal cancer from 557 patients were used. The model achieved the following median values (interquartile range): Dice Similarity Coefficient (DSC) = 0.83 (0.70-0.90), Intersection over Union (IoU) = 0.83 (0.73-0.90), Accuracy = 0.97 (0.95-0.99), Inference Speed = 25.6 (25.1-26.1) frames per second. The external testing cohorts comprised 156 and 200 images. SegMENT-Plus performed similarly on all three datasets for DSC (p = 0.05) and IoU (p = 0.07). No significant differences were noticed when separately analyzing WL and NBI test images on DSC (p = 0.06) and IoU (p = 0.78) and when analyzing the model versus the two residents on DSC (p = 0.06) and IoU (Senior vs. SegMENT-Plus, p = 0.13; Junior vs. SegMENT-Plus, p = 1.00). The model was then tested on real intraoperative laryngoscopy videos. CONCLUSION: SegMENT-Plus can accurately delineate laryngeal cancer boundaries in endoscopic images, with performances equal to those of two otolaryngology residents. The results on the two external datasets demonstrate excellent generalization capabilities. The computation speed of the model allowed its application on videolaryngoscopies simulating real-time use. Clinical trials are needed to evaluate the role of this technology in surgical practice and resection margin improvement. LEVEL OF EVIDENCE: III Laryngoscope, 134:2826-2834, 2024.

Transoral robotic surgery in oropharyngeal squamous cell carcinoma: A comparative study between da Vinci Single-Port and da Vinci Xi systems.

BACKGROUND: The recently developed da Vinci single-port (SP) system offers potential advantages in maneuverability within narrower surgical spaces. This study aims to compare intra- and post-operative outcomes, technical advantages, and limitations of transoral resections using the da Vinci SP and da Vinci Xi systems for oropharyngeal squamous cell carcinoma (OPSCC). METHODS: A single-center retrospective cohort study included patients with OPSCC who underwent transoral robotic surgery (TORS) after neoadjuvant chemotherapy (NCT). Data on pre-operative variables, intraoperative data, postoperative complications, and functional outcomes were collected. RESULTS: A total of 209 patients (males: 175; mean age: 59.0 ± 9.3) were included (SP: n = 136; Xi: n = 73). A significantly lower docking time was measured for the SP group (5.7 ± 2.5 min vs. 10.0 ± 4.4 min; p <.001). Similarly, the console time was reduced for the SP group though not reaching statistical significance (76.3 ± 30.7 min vs. 88.1 ± 36.9 min; p =.06). A greater proportion of patients showed wide negative resection margins in the SP group (71 % vs. 56 %; p =.10), although not statistically significant. No significant differences were observed in complication rates or postoperative functional outcomes. DISCUSSION: This study demonstrates the safety and efficacy of the da Vinci SP system in oropharyngeal surgery, with potential advantages in terms of reduced docking and console times. The findings suggest that the SP system offers improved maneuverability and instrument placement compared to the da Vinci Xi system.

Development of machine learning models for the prediction of long-term feeding tube dependence after oral and oropharyngeal cancer surgery.

PURPOSE: To predict the necessity of enteral nutrition at 28 days after surgery in patients undergoing major head and neck oncologic procedures for oral and oropharyngeal cancers. MATERIAL AND METHODS: Data from 193 patients with oral cavity and oropharyngeal squamous cell carcinoma were retrospectively collected at two tertiary referral centers to train (n = 135) and validate (n = 58) six supervised machine learning (ML) models for binary prediction employing 29 clinical variables available pre-operatively. RESULTS: The accuracy of the six ML models ranged between 0.74 and 0.88, while the measured area under the curve (AUC) between 0.75 and 0.87. The ML algorithms showed high specificity (range 0.87-0.96) and moderate sensitivity (range: 0.31-0.77) in detecting patients with ≥28 days feeding tube dependence. Negative predictive value was higher (range: 0.81-0.93) compared to positive predictive value (range: 0.40-0.71). Finally, the F1 score ranged between 0.35 and 0.74. CONCLUSIONS: Classification performance of the ML algorithms showed optimistic accuracy in the prediction of enteral nutrition at 28 days after surgery. Prospective studies are mandatory to define the clinical benefit of a ML-based pre-operative prediction of a personalized nutrition protocol.

Predicting the need for prophylactic gastrostomy in major head and neck cancer surgery: The PEG score.

BACKGROUND: To elaborate a preoperative score to predict the necessity of enteral nutrition at 28 days postoperatively in patients undergoing head and neck surgery. METHODS: A total of 424 patients with oral cavity, oropharyngeal, laryngeal, and hypopharyngeal carcinoma were retrospectively enrolled and analyzed to identify preoperative predictors of prolonged postsurgical enteral feeding which were used to create a prediction model with an easy-to-use nomogram. RESULTS: Five preoperative variables (body mass index, previous radiotherapy, preoperative dysphagia, type of surgery, flap reconstruction) were found to be independent predictive factors and were used to create a prediction model named PEG score together with the related nomogram. Accuracy, F1, and the area under the curve (AUC) were 0.74, 0.83, and 0.74. Different decision thresholds can be used to vary the sensitivity and specificity. CONCLUSIONS: The PEG score showed high prediction performances for modeling the need for enteral nutrition at 28 days postoperatively. Prospective studies are needed to define a personalized nutrition protocol.

Neo-adjuvant chemotherapy and transoral robotic surgery in locoregionally advanced oropharyngeal cancer.

PURPOSE: To analyze the oncological outcomes and patterns of recurrence of patients with locoregionally advanced oropharyngeal squamous cell carcinoma (OPSCC) who underwent neo-adjuvant chemotherapy (NCT) with subsequent transoral robotic surgery (TORS). METHODS: A single-center retrospective cohort study was performed, including 198 patients (mean age: 58.6, SD: 9.2). The primary outcome was disease-free survival (DFS). RESULTS: The median follow-up time was 26.5 months (IQR: 16.0-52.0). Estimated DFS rates (95 % CI) at 1 and 3 years were 86.6 % (81.9-91.7), and 81.4 % (75.7-87.6), respectively. Estimated DSS rates (95 % CI) at 1 and 3 years were 96.7 % (94.1-99.3), and 92.6 % (88.4-97.0), respectively. Estimated OS rates (95 % CI) at 1 and 3 years were 96.2 % (93.4-99.0), and 88.7 % (83.4-94.2), respectively. A total of 31 (15.6 %) patients showed a disease relapse after a median time of 8 months (IQR: 4.0-12.0), but only 12 (6 %) patients died of the disease during the study period. CONCLUSIONS: This study demonstrates that NCT and TORS can obtain excellent tumor control and survival in locoregionally advanced OPSCC. NCT might reduce the need for adjuvant treatments, and randomized clinical trials should be conducted to better define this aspect.

Functional outcomes of soft palate reconstruction after oncologic surgery: a systematic review and meta-analysis.

OBJECTIVE: The aim of this study is to analyze functional outcomes of soft palate reconstruction after oncologic surgery. METHODS: This study was conducted in conformity with the PRISMA statement. A single arm meta-analysis was performed for feeding tube dependence (FTD) (primary outcome), velopharyngeal insufficiency (VPI) and hypernasality (HN) (secondary outcomes) incidences. RESULTS: A total of 510 patients (males: 77.75%, n = 353/454) with a median age of 58 years (n = 480/510; 95% CI 57.0-61.0) who underwent soft palate surgical resection with primary reconstruction were included. Overall, the cumulative FTD rate was 1.55% (n = 28/510; 95% CI 0.24-3.96%), the VPI rate was 22.18% (n = 119/379; 95% CI 12.99-33.02%), and the HN rate was 33.01% (n = 88/234; 95% CI 19.03-46.61%). CONCLUSIONS: Soft palate reconstruction results in a low incidence of FTD, and most patients resume a full oral diet. Both obturators, primary closure, local and free flaps seem good reconstructive options. Nevertheless, more specific postoperative functional deficiencies like VPI and HN owns higher incidences, potentially affecting the quality of the swallowing and speaking function and the patient's quality of life.

Neoadjuvant chemotherapy and transoral robotic surgery for the posterior pharyngeal wall carcinoma.

BACKGROUND: The squamous cell carcinoma (SCC) of the posterior pharyngeal wall (PPW) is associated with poor oncological outcomes based on current literature data. We reported the preliminary outcomes of a potential new treatment protocol based on neoadjuvant chemotherapy (NCT) and transoral robotic surgery (TORS). METHODS: A retrospective single-center case series was performed including a total of 20 patients diagnosed with a SCC of the PPW between October 2010 and September 2021. All patients successfully completed TORS with neck dissection after NCT. Adjuvant treatment was performed in the presence of adverse pathologic features. Loco-regional control (LRC), overall survival (OS), and disease-specific survival (DSS) were defined as the time from surgery to tumor recurrence or death, as appropriate. Survival estimates were calculated by Kaplan-Meier analysis. Surgical data and post-operative functional outcomes were also reported. RESULTS: Estimated 3-year LRC, OS, and DSS rates (95% Confidence interval) were 59.7% (39.7-89.6), 58.6% (38.7-88.8), and 69.4% (49.9-96.6). The median hospital stay was 21 days (IQR 17.0-23.5). Oral diet and decannulation were achieved after a median of 14 days (IQR 12.0-15.0). Feeding tube and tracheostomy dependence after 6 months was observed in 3 (15%) and 2 (10%) patients, respectively. CONCLUSIONS: The use of NCT followed by TORS for PPW SCC treatment appears to have good oncological and functional outcomes for both early and locally advanced cancers. Further randomized trials and site-specific guidelines are needed.

Compartmental Transoral Robotic Lateral Oropharyngectomy with the da Vinci Single-Port System: Surgical Technique.

BACKGROUND: Transoral robotic surgery (TORS) has renovated the surgical management of oropharyngeal squamous cell carcinoma (OPSCC), allowing a minimally invasive surgical approach with optimal oncological outcomes. The recent introduction of the da Vinci Single Port (SP) system resulted in a considerable improvement of TORS technique. METHODS: In this video, we illustrate the transoral robotic lateral oropharyngectomy performed with the da Vinci SP system in a 50-year-old male patient suffering from a p16+ oropharyngeal squamous cell carcinoma cT4N1M0. RESULTS: The transoral robotic lateral oropharyngectomy is illustrated step by step. The structures encountered during the resection are described, and the surgical margins are defined based on anatomical landmarks. The most critical regions encountered during resection are pointed out, and the tip and tricks of this surgery are reported. CONCLUSIONS: A step-by-step transoral lateral oropharyngectomy is described to increase its reproducibility. The da Vinci SP system owns various benefits for performing transoral lateral oropharyngectomy due to the increased maneuverability in the narrower oral cavity working spaces.

Instance segmentation of upper aerodigestive tract cancer: site-specific outcomes.

Objective: To achieve instance segmentation of upper aerodigestive tract (UADT) neoplasms using a deep learning (DL) algorithm, and to identify differences in its diagnostic performance in three different sites: larynx/hypopharynx, oral cavity and oropharynx. Methods: A total of 1034 endoscopic images from 323 patients were examined under narrow band imaging (NBI). The Mask R-CNN algorithm was used for the analysis. The dataset split was: 935 training, 48 validation and 51 testing images. Dice Similarity Coefficient (Dsc) was the main outcome measure. Results: Instance segmentation was effective in 76.5% of images. The mean Dsc was 0.90 ± 0.05. The algorithm correctly predicted 77.8%, 86.7% and 55.5% of lesions in the larynx/hypopharynx, oral cavity, and oropharynx, respectively. The mean Dsc was 0.90 ± 0.05 for the larynx/hypopharynx, 0.60 ± 0.26 for the oral cavity, and 0.81 ± 0.30 for the oropharynx. The analysis showed inferior diagnostic results in the oral cavity compared with the larynx/hypopharynx (p < 0.001). Conclusions: The study confirms the feasibility of instance segmentation of UADT using DL algorithms and shows inferior diagnostic results in the oral cavity compared with other anatomic areas.