京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第20248号 / 医博第4207号 / 新制||医||1020(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 鈴木 実, 教授 別所 和久, 教授 大森 孝一 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

Medical imaging is a key tool used in healthcare to diagnose and prognose patients by aiding the detection of a variety of diseases and conditions. In practice, medical image screening must be performed by clinical practitioners who rely primarily on their expertise and experience for disease diagnosis. The ability of convolutional neural networks (CNNs) to extract hierarchical features and determine classifications directly from raw image data makes CNNs a potentially useful adjunct to the medical image analysis process. A common challenge in successfully implementing CNNs is optimizing hyperparameters for training. In this study, we propose a method which utilizes scheduled hyperparameters and Bayesian optimization to classify cancerous and noncancerous tissues (i.e., segmentation) from head and neck computed tomography (CT) and positron emission tomography (PET) scans. The results of this method are compared using CT imaging with and without PET imaging for 2D and 3D image segmentation models.

Background: Patient-reported outcomes (PRO) assess disease burden and indicate unmet needs. Home-based electronic PRO measures (ePROMs) can support tumor aftercare (TAC). Creating an ePROM is the next step after implementing the software “OncoFunction” to assess PROs during TAC of head- and neck-cancer patients (HNC). Therefore, internet use and perception on ePROMs of ENT and TAC patients were evaluated. Methods: From May–July 2020, ENT patients at a high- volume outpatient department aged >18 without need for emergency treatment were invited to complete a questionnaire concerning internet use and access, hardware, and opinion on the chances, requirements, and designs of ePROMs. Results: 415 questionnaires were evaluated; 46.3% of the respondents visited the common consultation hour (CCH) and 44.3% TAC; 71.9% were internet users, being younger than non-internet users; and 36.4% of TAC patients were non-internet users and 16.3% of them were without a web-enabled device. Significant differences existed in age and assessment of future perspectives between internet-/non-internet users and TAC/CCH patients, respectively. Regarding the design of ePROMs, patients preferred quarterly and short surveys. Data safety and feedback were important. Conclusions: ePROMs are not suitable for everyone because of missing internet access and experience. A tailored approach to implement ePROMs in TAC is needed

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Background Compared with other malignancies, head and neck cancer (HNC) increases the risk of not returning to work (RTW). Methods Within a cross-sectional study, patients with HNC filled out the OncoFunction questionnaire, a version of the International Classification of Functioning Core Sets for HNC. In 231 patients below 65 years of age, associations of sociodemographic, clinical, functional, and psychological factors with employment and participation in rehabilitation program were explored. Results Unemployed patients reported more swallowing difficulties and speaking problems. Being unemployed was associated with higher levels of depressive and anxiety symptoms, fatigue, and lower global health. Rehabilitation participation was not significantly associated with any of the assessed factors except for smoking. Conclusions Unemployed patients with HNC are more burdened than employed patients with HNC regarding clinical, psychological, and functional factors. These differences are more evident later in recovery. Rehabilitation participation was not associated with psychological and functional burden which indicates the need for tailored HNC rehabilitation programs.

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The full text will be available at the end of the embargo: 30th July 2026

During prosthetic rehabilitation after tumor therapy in the head and neck region, the dentist must assess whether the prognosis of the remaining teeth is sufficiently good or whether implants should be used to anchor dentures. Thus, the aim of the present study was to compare the survival rate of teeth and implants after and to evaluate factors potentially influencing implant survival. One hundred fifteen patients (male: 70.3%; mean age: 63.2 12.4 years) having received dental treatment before and after at the Martin Luther University Halle-Wittenberg were enrolled in the study. Clinical examination including assessment of dental status and stimulated salivary flow rate was performed. Information about disease progression and therapy was retrieved from medical records. After from a total of 1262 teeth, 27.2% had to be extracted. Of 308 implants inserted after 7.0% were lost. Teeth exhibited lower 5-year survival probability (76.8%) than implants (89.9%; p = 0.001). The risk of loss (RL) of implants increased with age, nicotine use, intraoral defects, and RCT. Radiotherapy did not independently increase the RL. Thus, implants seem to be a reliable treatment option in case of progressive tooth decay after, particularly after RT.