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OBJECTIVES: Head and neck squamous cell carcinoma (HNSCC) is a complex malignancy that requires a multidisciplinary tumor board approach for individual treatment planning. In recent years, artificial intelligence tools have emerged to assist healthcare professionals in making informed treatment decisions. This study investigates the application of the newly published LLM Claude 3 Opus compared to the currently most advanced LLM ChatGPT 4.0 for the diagnosis and therapy planning of primary HNSCC. The results were compared to that of a conventional multidisciplinary tumor board; (2) Materials and Methods: We conducted a study in March 2024 on 50 consecutive primary head and neck cancer cases. The diagnostics and MDT recommendations were compared to the Claude 3 Opus and ChatGPT 4.0 recommendations for each patient and rated by two independent reviewers for the following parameters: clinical recommendation, explanation, and summarization in addition to the Artificial Intelligence Performance Instrument (AIPI); (3) Results: In this study, Claude 3 achieved better scores for the diagnostic workup of patients than ChatGPT 4.0 and provided treatment recommendations involving surgery, chemotherapy, and radiation therapy. In terms of clinical recommendations, explanation and summarization Claude 3 scored similar to ChatGPT 4.0, listing treatment recommendations which were congruent with the MDT, but failed to cite the source of the information; (4) Conclusion: This study is the first analysis of Claude 3 for primary head and neck cancer cases and demonstrates a superior performance in the diagnosis of HNSCC than ChatGPT 4.0 and similar results for therapy recommendations. This marks the advent of a newly launched advanced AI model that may be superior to ChatGPT 4.0 for the assessment of primary head and neck cancer cases and may assist in the clinical diagnostic and MDT setting.
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Background: Cervical fibrosis (CF) as a late consequence in patients after radiotherapy significantly impacts the long-term symptoms, functionality, and quality of life of these cancer patients due to a hardening process of different histological tissues. Modern Shear Wave Ultrasound Elastography now enables a differentiated analysis of the changes in various tissue types. In this study, tissue-specific changes in CF induced by radiation therapy in head and neck (ENT) cancer patients were quantified and correlated with cervical range of motion (CROM). Materials and Methods: 16 patients after radiation of the cervical lymphatic drainage were selected as the observation group (OG). Further, 16 people without radiation in the head and neck region were matched by gender, age, and BMI as the control group (CG). Stiffness measurements in kilopascal (kPa; 1 Pa = 1 N m-2) were performed using shear wave elastography (SWE) to assess the elasticity of muscle, fascia, and subcutaneous tissue within and surrounding the sternocleidomastoid muscle (SCM). Specific parameters of the OG were compared to the CG and correlated with functional parameters and quality of life (QoL). Results: The OG exhibited significantly higher stiffness values (Emean, Emax, Emin) across all tissue types than the CG, suggesting a tangible effect of radiation therapy on tissue stiffness. Muscle compartment analysis revealed the most significant stiffness differences. Thickness measurements indicated changes in the muscle and skin but not in the subcutaneous tissue. CROM measurements within the OG fell within normal ranges, suggesting a possible homogenizing effect of radiation treatment on CROM variability. Strong correlations were observed between age and specific stiffness measures, particularly in the OG group, indicating a broader impact of aging or radiation therapy on physiological measures. Significant correlations between tissue stiffness and CROM were found. Conclusion: CF after radiotherapy occurs primarily in the muscle tissue and its fascia, with the hardening being about twice as pronounced as in the average population and becoming more pronounced with increasing age and correlates with CROM.
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Background: Head and neck squamous cell carcinoma (HNSCC) is a complex malignancy that requires a multidisciplinary approach in clinical practice, especially in tumor board discussions. In recent years, artificial intelligence has emerged as a tool to assist healthcare professionals in making informed decisions. This study investigates the application of ChatGPT 3.5 and ChatGPT 4.0, natural language processing models, in tumor board decision-making. Methods: We conducted a pilot study in October 2023 on 20 consecutive head and neck cancer patients discussed in our multidisciplinary tumor board (MDT). Patients with a primary diagnosis of head and neck cancer were included. The MDT and ChatGPT 3.5 and ChatGPT 4.0 recommendations for each patient were compared by two independent reviewers and the number of therapy options, the clinical recommendation, the explanation and the summarization were graded. Results: In this study, ChatGPT 3.5 provided mostly general answers for surgery, chemotherapy, and radiation therapy. For clinical recommendation, explanation and summarization ChatGPT 3.5 and 4.0 scored well, but demonstrated to be mostly an assisting tool, suggesting significantly more therapy options than our MDT, while some of the recommended treatment modalities like primary immunotherapy are not part of the current treatment guidelines. Conclusions: This research demonstrates that advanced AI models at the moment can merely assist in the MDT setting, since the current versions list common therapy options, but sometimes recommend incorrect treatment options and in the case of ChatGPT 3.5 lack information on the source material.
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PURPOSE: To assess the robustness of prognostic biomarkers and molecular tumour subtypes developed for patients with head and neck squamous cell carcinoma (HNSCC) on cell-line derived HNSCC xenograft models, and to develop a novel biomarker signature by combining xenograft and patient datasets. MATERIALS AND METHODS: Mice bearing xenografts (nâ¯=â¯59) of ten HNSCC cell lines and a retrospective, multicentre patient cohort (nâ¯=â¯242) of the German Cancer Consortium-Radiation Oncology Group (DKTK-ROG) were included. All patients received postoperative radiochemotherapy (PORT-C). Gene expression analysis was conducted using GeneChip Human Transcriptome Arrays. Xenografts were stratified based on their molecular subtypes and previously established gene classifiers. The dose to control 50â¯% of tumours (TCD50) was compared between these groups. Using differential gene expression analyses combining xenograft and patient data, a gene signature was developed to define risk groups for the primary endpoint loco-regional control (LRC). RESULTS: Tumours of mesenchymal subtype were characterized by a higher TCD50 (xenografts, pâ¯<â¯0.001) and lower LRC (patients, pâ¯<â¯0.001) compared to the other subtypes. Similar to previously published patient data, hypoxia- and radioresistance-related gene signatures were associated with high TCD50 values. A 2-gene signature (FN1, SERPINE1) was developed that was prognostic for TCD50 (xenografts, pâ¯<â¯0.001) and for patient outcome in independent validation (LRC: pâ¯=â¯0.007). CONCLUSION: Genetic prognosticators of outcome for patients after PORT-C and subcutaneous xenografts after primary clinically relevant irradiation show similarity. The identified robust 2-gene signature may help to guide patient stratification, after prospective validation. Thus, xenografts remain a valuable resource for translational research towards the development of individualized radiotherapy.