Publications by authors named "Yoshihiko Furuki"

Fibrosarcoma in the mandible in children is a very rare condition. We present a rare case of central mandibular fibrosarcoma in a child, treated with radical tumor resection, reconstructive surgery, long-term prognostic evaluation, and morphofunctional reconstruction. The patient was an 8-year-old boy.

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Elastofibromatous changes of the oral mucosa, such as an elastofibroma (EF) or an elastofibromatous lesion (EFL), are not well recognized, and the second such case in Japan is reported. A 72-year-old man wearing a complete maxillary denture presented with a small nodule on the hard palate. Histopathological examination showed abundant fibrous tissue with numerous elastic fibers on Elastica van Gieson (EvG) staining.

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The purpose of this retrospective study was to identify risks of postoperative facial nerve injury (FNI) in mandibular condylar fractures. A total of 59 consecutive cases of condyle fracture or plate removal with a retromandibular transparotid approach (RMTA) were divided into FNI and non-FNI groups that were evaluated for associations with age, sex, laterality, fracture type, height, weight, body mass index (BMI), and maxillofacial bone height and width diameters on computed tomography (CT). FNI occurred in 11 of 59 patients (18.

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Article Synopsis
  • The study evaluated how accurately deep learning can determine the relationship between the inferior alveolar canal and mandibular third molars using a dataset of 1279 digital radiographs.
  • The researchers specifically focused on two types of analysis: contact (presence or absence of contact between the molar and canal) and continuity (bone continuity as seen on CT scans).
  • Results showed that the ResNet50v2 model using sharpness-aware minimization (SAM) performed well in contact analysis (accuracy 0.860, AUC 0.890), but the models struggled with continuity analysis, showing limited effectiveness.
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  • * The researchers compared the performance of CNN model VGG16 using both SAM and stochastic gradient descent (SGD) optimizers, with and without a learning rate scheduler over 300 epochs.
  • * Results showed that SAM, particularly with the learning rate scheduler, achieved the highest accuracy (11.2), AUC (0.9328), and reduced overfitting, suggesting its potential for enhancing oral cytological diagnosis.
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Attention mechanism, which is a means of determining which part of the forced data is emphasized, has attracted attention in various fields of deep learning in recent years. The purpose of this study was to evaluate the performance of the attention branch network (ABN) for implant classification using convolutional neural networks (CNNs). The data consisted of 10191 dental implant images from 13 implant brands that cropped the site, including dental implants as pretreatment, from digital panoramic radiographs of patients who underwent surgery at Kagawa Prefectural Central Hospital between 2005 and 2021.

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  • - The study analyzed the rates of hepatitis B (HBV), hepatitis C (HCV), and HIV infections diagnosed through pre-operative screening for patients undergoing elective surgery from April 2014 to March 2022, revealing very low prevalence rates of these infections among a large patient group.
  • - Self-reported infection rates were significantly higher compared to pre-operative screening results, and variations in prevalence were influenced by age and sex, but no link was found between oral diseases and viral infections.
  • - The screening costs per positive diagnosis were notably high, particularly for HIV, indicating that while questionnaires are somewhat helpful, they fall short in accurately screening for infections, which complicates further diagnosis related to oral health.
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Bone-modifying agents (BMA) such as bisphosphonates and denosumab are frequently used for the treatment of bone metastases, osteoporosis, and multiple myeloma. BMA may lead to anti-resorptive agent-related osteonecrosis of the jaw (ARONJ). This study aimed to clarify the risk factors for and probabilities of developing ARONJ after tooth extraction in patients undergoing BMA therapy.

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  • A retrospective study analyzed the success rate of endoscopic endodontic surgeries involving 242 patients, finding a high success rate of 95.3%.
  • The study categorized risk factors influencing surgery outcomes into attributes, general health, anatomy, and surgical factors, with the presence of posts as the most significant predictor.
  • The study calculated correlation coefficients and odds ratios to identify key factors affecting surgical success, highlighting the importance of the presence of posts with an odds ratio of 9.592.
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  • Osteoporosis is a growing global health concern linked to longer life spans but is hard to detect early due to lack of noticeable symptoms.
  • This study explores using deep learning techniques, particularly convolutional neural networks (CNN), to identify osteoporosis from dental panoramic radiographs (X-rays).
  • The research found that incorporating clinical data alongside the radiographic images in an ensemble model significantly enhanced the accuracy of osteoporosis classification.
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Cervicofacial subcutaneous emphysema (SE) is primarily caused by dental treatment introducing gas into the subcutaneous tissue. Air rapidly dissects into the subcutaneous tissue with face and neck swelling, leading to respiratory distress, patient discomfort, and chest pain. Computed tomography (CT) can detect spreading SE patterns.

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Article Synopsis
  • - This study assesses the effectiveness of convolutional neural networks (CNNs) in classifying mandibular third molars using panoramic X-rays according to Pell and Gregory and Winter’s classifications.
  • - Researchers analyzed 1,330 images of third molars and found that single-task learning outperformed multi-task learning in diagnostic accuracy, indicated by significant statistical results (p < 0.05).
  • - The findings suggest that applying these specific classifications through deep learning models can improve the accuracy of identifying the positioning of mandibular third molars, representing a pioneering effort in this area.
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Background : An accessory parotid gland (APG) is a common anatomical structure that occurs in 10%-56% of individuals. Pleomorphic adenomas are the most common benign tumors of the APG, and their ideal treatment is surgical excision, although there is a risk for aesthetic disorders and facial nerve damage due to the site of origin. Moreover, despite being benign, these tumors are known to recur.

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Rationale: Bone lid surgery (BLS) is minimally invasive surgery that removes the cortical bone and returns it to original position after removing lesions. However, jawbone lesions are completely covered with cortical bone, and it can be difficult to accurately determine the lesion position from the outside.

Patient Concerns: A 24-year-old Japanese woman, identified as having an impacted maxillary canine, was referred to our department.

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: A few deep learning studies have reported that combining image features with patient variables enhanced identification accuracy compared with image-only models. However, previous studies have not statistically reported the additional effect of patient variables on the image-only models. This study aimed to statistically evaluate the osteoporosis identification ability of deep learning by combining hip radiographs with patient variables.

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In this retrospective observational study, we evaluated the relationship between perioperative oral bacterial counts and postoperative complications in cardiovascular disease (CVD) patients. From April 2012 to December 2018, all patients scheduled for surgery received perioperative oral management (POM) by oral specialists at a single center. Tongue dorsum bacterial counts were measured on the pre-hospitalization day, preoperatively, and postoperatively.

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The purpose of this study was to investigate the bone healing properties and histological environment of a u-HA/PLLA/PGA (u-HA-uncalcined and unsintered hydroxyapatite, PLLA-Poly L-lactic acid, PGA-polyglycolic acid) composite device in humans, and to understand the histological dynamics of using this device for maxillofacial treatments. Twenty-one subjects underwent pre-implant maxillary alveolar ridge augmentation with mandibular cortical bone blocks using u-HA/PLLA or u-HA/PLLA/PGA screws for fixation. Six months later, specimens of these screws and their adjacent tissue were retrieved.

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  • * Researchers analyzed 9,767 dental implant images from 12 different brands and stages, using five deep convolutional neural network (CNN) models to evaluate classification performance.
  • * Results showed that deeper networks with more parameters improved classification accuracy, and multi-task learning enhanced brand classification and significantly boosted metrics for treatment phase classification.
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This study considers the use of deep learning to diagnose osteoporosis from hip radiographs, and whether adding clinical data improves diagnostic performance over the image mode alone. For objective labeling, we collected a dataset containing 1131 images from patients who underwent both skeletal bone mineral density measurement and hip radiography at a single general hospital between 2014 and 2019. Osteoporosis was assessed from the hip radiographs using five convolutional neural network (CNN) models.

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Purpose : Antiresorptive agents, such as bisphosphonates, are useful for the prevention of the recurrence of hip fractures. However, their administration has a risk of antiresorptive agent-related osteonecrosis of the jaw (ARONJ), and risk factors include poor oral hygiene. It is difficult for an orthopedic surgeon to examine a patient's oral condition thoroughly.

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A retrospective observational study using an oral bacteria counter was conducted to evaluate the trends in the number of oral bacteria in the perioperative period of lung cancer patients and to verify the relationship between oral health status and postoperative fever. All patients received perioperative oral management (POM) by oral specialists between April 2012 and December 2018 at Kagawa Prefectural Central Hospital, Kagawa, Japan prior to lung cancer surgery. Bacteria counts from the dorsum of the tongue were measured on the day of pre-hospitalization, pre-operation, and post-operation, and background data were also collected retrospectively.

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Background: This study was conducted to compare the histological diagnostic accuracy of conventional oral-based cytology and liquid-based cytology (LBC) methods.

Methods: Histological diagnoses of 251 cases were classified as negative (no malignancy lesion, inflammation, or mild/moderate dysplasia) and positive [severe dysplasia/carcinoma in situ (CIS) and squamous cell carcinoma (SCC)]. Cytological diagnoses were classified as negative for intraepithelial lesion or malignancy (NILM), oral low-grade squamous intraepithelial lesion (OLSIL), oral high-grade squamous intraepithelial lesion (OHSIL), or SCC.

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A novel head-mounted display offers high quality of endoscopic imagery in front of the eyes, irrespective of the head position. We present an application of the head-mounted display system as a personal integrated multi-image monitoring system in endoscopically assisted periradicular surgery. Our head-mounted display system displayed multiple forms of information as integrated, sharp, high-definition endoscope, biological monitor, and X-ray image (such as panoramic and computed tomography images) synchronously using a picture in picture.

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Osteosynthesis resorbable materials made of uncalcined and unsintered hydroxyapatite (u-HA) particles, poly-L-lactide (PLLA), are bioresorbable, and these materials have feasible bioactive/osteoconductive capacities. However, their strength and stability for fixation in mandibular condylar head fractures remain unclear. This in vitro study aimed to assess the biomechanical strength of u-HA/PLLA screws after the internal fixation of condylar head fractures.

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Article Synopsis
  • The study focused on using panoramic X-ray images to assess the accuracy of various dental implant brands through deep convolutional neural networks (CNNs) using transfer learning techniques.
  • A total of 8,859 implant images from 11 different implant systems were analyzed, sourced from patients who received dental implants at a hospital in Japan between 2005 and 2019.
  • Among five evaluated CNN models, the finely tuned VGG16 model achieved the best classification performance for dental implants, followed by the finely tuned VGG19, indicating their effectiveness in distinguishing between the different implant systems.
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