This study aimed to investigate the difference that convolutional neural network(CNN) shows in the determining osteoporosis on panoramic radiograph by performing a paired test by inputting the original image and the limited image including the cortical bone of the posterior border of the mandible used by radiologists. On panoramic radiographs of a total of 661 subjects (mean age 66.3 years ± 11.42), the area including the cortical bone of the posterior part of the mandible was divided into the left and right sides, and the ROI was set, and the remaining area was masked in black to form the limited image. For training of VGG-16, panoramic radiographs of 243 osteoporosis subjects (mean age 72.67 years ± 7.97) and 222 normal subjects (mean age 53.21 years ± 2.46) were used, and testing 1 and testing 2 were performed on the original and limited images, respectively, using panoramic radiographs of 51 osteoporosis subjects (mean age 72.78 years ± 8.3) and 47 normal subjects (mean age 53.32 years ± 2.81). The accuracy of VGG-16 for determining osteoporosis was 97%, in the testing 1 and 100% in the testing 2. When determining osteoporosis on the original image, CNN showed sensitivity in a wide range of areas including not only the inferior cortical bone of the mandible but also the maxillary and mandibular cancellous bone, cervical spine, and zygomatic bone. When the same ROI including the lower inferior cortical border of the mandible of the osteoporosis group was applied and the sensitive region was compared between the original image and the limited image, the original image showed wider sensitive region in cancellous bone and cortical bone than on the limited image (p<.05). Since osteoporosis is a disease that affects throughout the skeletal system, this finding seems very valid.

2011년 발생한 동일본대지진의 영향으로 후쿠시마 원자력발전소 폭파사고 이후 국제원자력기구(IAEA)의 방사선비상계획구역(EPZ) 확 대를 권고하였으며, 이에 따라 우리나라에서도 방사선비상계획구역(EPZ, Emergency Planning Zone)를 기존 반경 8~10km에서 20~30km 로 확대를 하였다. 이에 따라 방사선 비상시 대규모 대피에 관한 관심이 높아지며 원활한 대피를 위한 교통운영관리전략 수립이 필요 한 실정이다. 방사선 비상과 같은 대규모 재난이 발생하면 동시다발적인 대피수요가 발생하고 한정된 도로교통망에 차량이 집중되어 극심한 혼잡이 발생할 것으로 예상된다. 따라서, 본 연구에서는 교통분야에서 활용되는 도로운영관리전략 중 방사선비상시 적용 가능 한 전략 및 적용기준을 수립한다. 또한, 선정된 도로운영관리전략의 효과분석을 위하여 TOVA를 활용하였으며, Sub Network 기능으로 대상지역의 네트워크를 추출 후 분석을 시행하였다. 방사선비상시 도로운영관리전략은 도로용량 증대, 통행속도 향상, 교통수요 관리 및 기타 등 네 가지로 구분하여 분류하였다. 이 중 우리나라에 도입되지 않은 역류차로제 전략 도입 효과분석을 수행하였다. 시뮬레이 션 대상지는 고리원자력 발전소의 사고가 발생한 것으로 가정하며, 대피인원은 원자력발전소에서 부산광역시로 이동하는 것으로 설정 하였다. 효과분석 결과, 시행시 120.6%의 교통량(시간당 7,600대)과 117% 속도(30.21km/h → 65.55km/h)가 증가되는 것으로 분석되었다

2011년 일본 후쿠시마 원자력발전소 사고로 인해 130만 톤 이상의 방사능 오염수가 발생하였고, 2023년부터 일본 정부는 다량 의 오염수를 바다로 방류하고 있다. 이 사고는 해양방사능 오염에 대한 우려와 해산물 섭취에 대한 불안감을 증가시켰으며, 특히 수산물 소비량이 높은 우리나라에서 방사선감수성이 높은 어린이와 태아에게 미치는 영향에 대한 걱정 등을 야기시켰다. 이러한 해양 방사능 오 염 사태를 포함한 다양한 해양 방사능 누출 사고에 대비하기 위해 방사선 방호물질에 대한 연구의 필요성이 증대되고 있다. 천연 방사선 방호제는 화학적 방사선방호제에 비해 부작용이 적고 상용화가 용이하다. 따라서 본 연구는 천연 항산화물질인 엽산과 α-토코페롤 혼합 물이 방사선으로부터 생체를 보호하는 기능을 확인하고자 하였다. 실험은 방사선감수성이 높은 태아를 대상으로 하기 위하여 Spraque-Dawley rat (SD rat)을 사용하여 임신을 유도하였으며, 출산 후 2세대의 골격계, 혈액분석, 체중, 비장, 뇌 및 소장을 관찰하였다. 혈 액분석과 소장의 융모길이, 대뇌피질 두께 측정에서 혼합물 투여 후 방사선조사군이 비교군(방사선조사군)에 비해 유의미한 회복(p<0.05) 을 보였으며, 이는 엽산과 α-토코페롤 혼합물이 해양 방사능 오염 환경에서 생체 내 방사선방호에 효과적임을 시사한다.

As the number of households with pets has increased worldwide, there is a growing trend of accepting pets as family members. Consequently, the pet food market has seen the emergence of concepts such as “human-grade,” “raw (PMR and BARF),” and “no synthetic additives” pet food. These concepts not only fulfill essential nutrients but also consider the health and habits of pets, a crucial aspect that should be at the forefront of our work. However, these types of pet food are prone to microbial contamination and component alterations caused by heat. Current studies and products have recently been developed overseas to apply non-thermal sterilization technologies to pet food commonly used in the food industry. In contrast, the domestic standards for non-thermal sterilization in pet food are insufficient. Therefore, a comprehensive review of non-thermal sterilization technologies, such as high-pressure processing (HPP), radiation, and plasma predominantly applied in the international pet food market, is deemed necessary. This review is expected to provide guidelines for non-thermal sterilization standards in domestic pet food, thereby laying the foundation for the safe production of raw pet food.

중재 시술의 발전으로, 노출된 방사선으로 인한 의료 방사선 중재 시술자에 미치는 건강 위협이 증대됨에 따라 시술 중 방사선 노출을 최소화하기 위한 관심과 노력이 요구되고 있다. 이에 대한췌장담도학회에서는 투시 장비를 이용한 중재 시술 중 의료 방사선 중재 시술자에게 미치는 방사선 노출을 최소화하기 위한 권고안을 개발하였다. 본 권고안은 방사선 차폐, 방사선 투시기와 방사선량의 관리, 방사선 노출 선량 한도 및 감시, 임신과 출산 총 4가지 분야로 나누어 중재 시술자에게 방사선 노출의 위험을 이해하기 위한 지식을 전달하고 실질적으로 수행해야 하는 권고사항을 명확히 제시하여 불필요한 방사선 노출을 피하기 위한 실용적인 접근이 가능하도록 구성되었다. 본 권고안을 통해 의료 방사선 중재시술자의 방사선 노출을 최소화하여 안전하고 효과적인 중재 시술이 이루어질 수 있기를 기대한다.

Previous researches have revealed that dental panoramic radiographs routinely taken in dental clinics can be useful to diagnose low bone density. The purpose of this study is to investigate the prevalence, awareness and treatment rate of low bone density of females utilizing dental panoramic images. Four-hundred-and-fifteen female patients(mean age 70.4 yrs ± 11.4 yrs) between the age of 50s to 90s, at Chonnam National University Dental Hospital were randomly selected for this study. The panoramic radiographs taken from the patients were reviewed for the purpose of interpreting suspected low bone density(SLBD) on the basis of mandibular cortex index. Awareness and treatment rates of osteoporosis were investigated based on electronic records using the past medical history. As a result, the prevalence rate was 42.17%(175 in 415), the osteoporosis-awareness rate 22.3%(39 in 175), and the treatment rate 87%(34 in 39), showing that the osteoporosis-awareness rate was low, but the treatment rate was relatively high. In conclusion, it can be suggested that osteoporosis-awareness rate by diagnosing SLBD with dental panoramic radiographs be increased to help patients to receive proper treatment.

본 연구에서는 자기공명영상검사실 방사선사의 환자안전 문화 인식을 분석하고자 하였다. 수도권 자기공명영상검사 실에서 근무하는 방사선사 109명을 대상으로 일반적인 특성, 실태조사, 환자안전 문화 인식에 대해 설문 조사하였 다. 의료종사자들을 대상으로 개발된 한국형 환자안전문화 측정 도구에서 최상위 리더십을 경영진으로, 부서장이라 는 단어를 파트장으로 수정하였고 전문가 5인에게 내용 타당도를 검증받았다. 결과적으로 자기공명영상검사실에서 근무하는 방사선사의 환자안전 문화 인식 점수는 평균 3.97로 높았지만, 안전사고경험 비율이 65.1%로 높게 나타났 다. 따라서 정기적으로 이루어지고 있는 자기공명영상검사 안전교육의 효율성 제고를 위한 연구가 필요하며 본 연구 가 기초자료를 제공할 것이라 사료된다.

This study aimed to investigate which areas AI is sensitive when inputting panoramic radiographs with dental area masked and when inputting unmasked ones. Therefore, the null hypothesis of this study was that masking dental area would not make a difference in the sensitive areas of osteoporosis determination of AI. For this study 1165 female(average age 48.4 ± 23.9 years) from whom panoramic radiographs were taken were selected. Either osteoporosis or normal should be clearly defined by oral and maxillofacial radiologists. The panoramic radiographs from the female were classified as either osteoporosis or normal according to the mandibular inferior cortex shape. VGG-16 model was used to get training, validating, and testing to determine between osteoporosis or normal. Two experiments were performed; one using unmasked images of panoramic radiographs, and the other using panoramic radiographs with dental region masked. In two experiments, accuracy of VGG-16 was 97.9% with unmasked images and 98.6% with dental-region-masked images. In the osteoporosis group, the sensitive areas identified with unmasked images included cervical vertebrae, maxillary and mandibular cancellous bone, dental area, zygomatic bone, mandibular inferior cortex, and cranial base. The osteoporosis group shows sensitivity on mandibular cancellous bone, cervical vertebrae, and mandibular inferior cortex with masked images. In the normal group, when unmasked images were input, only dental region was sensitive, while with masked images, only mandibular cancellous bone was sensitive. It is suggestive that when dental influence of panoramic radiographs was excluded, AI determined osteoporosis on the mandibular cancellous bone more sensitively.

The purpose of this study was to verify the sensitive areas when the AI determines osteoporosis for the entire area of the panoramic radiograph. Panoramic radiographs of a total of 1,156 female patients(average age of 49.0±24.0 years) were used for this study. The panoramic radiographs were diagnosed as osteoporosis and the normal by Oral and Maxillofacial Radiology specialists. The VGG16 deep learning convolutional neural network(CNN) model was used to determine osteoporosis and the normal from testing 72 osteoporosis(average age of 73.7±8.0 years) and 93 normal(average age of 26.4±5.1 years). VGG16 conducted a gradient-weighted class activation mapping(Grad-CAM) visualization to indicate sensitive areas when determining osteoporosis. The accuracy of CNN in determining osteoporosis was 100%. Heatmap image from 72 panoamic radiographs of osteoporosis revealed that CNN was sensitive to the cervical vertebral in 70.8%(51/72), the cortical bone of the lower mandible in 72.2%(52/72), the cranial base area in 30.6%(22/72), the cancellous bone of the mandible in 33.3%(24/72), the cancellous bone of the maxilla in 20.8%(15/72), the zygoma in 8.3%(6/72), and the dental area in 5.6%(4/72). Consideration: it was found that the cervical vertebral area and the cortical bone of the lower mandible were sensitive areas when CNN determines osteoporosis in the entire area of panoramic radiographs.

The aim of this study was to investigate radiographic features of osteosclerosis on digital panoramic radiographs. Osteoscleosis was diagnosed with its radiographic features of amorphous non- expansible radiopacity with unknown etiology. In diagosing osteosclerosis, differential diagnosis is needed from periapical cemental dysplasia, osteoma, benign cementoblastoma, and anatomic structures. Fifty-eight osteosclerosis on digital panoramic radiopgraphs from 46 patients with osteoscleosis were selected for this study. All of the osteosclerosis were found in the mandible. Among them, 53(91.4%) occurred on the posterior region. The mean diameter was 9.1㎜. The internal structure was radiopaque in 39(67.2%) and mixed radiolucent and radiopaque in 19(35.3%). There was no specific effect on the surrounding structures. In 16(27.6%), partial or complete radiolucent margin was noted which might be digital image artifact by enhancement.

Background: Ameloblastoma are benign but locally invasive neoplasms that represent 10% of all odontogenic tumors. Despite its benign characteristics, ameloblastoma has a high recurrence rate after treatment with a recurrence rate of 55-90%. It is important to identify the risk factors of recurrence to improve patient’s quality of life in oral and maxillofacial surgery. Methods: Patients who underwent surgery at the Department of Oral and Maxillofacial Surgery at Pusan National University Dental Hospital for 5 years from 2017-2021 and were diagnosed with ameloblastoma as a result of postoperative histological examination were included. The patients were divided into two groups, recurrent and non-recurrent, and comparative analysis was performed according to various factors. Results: First, when the lesion was involved with the inferior alveolar nerve (IAN), recurrence was more likely than when it was not. Next, recurrence occurs more often when cortical bone perforation is observed than when it is not. In particular, when resorption is shown on the lingual cortical bone, a remarkable tendency of recurrence is shown. Moreover, in radiographic characteristics, the multicystic type showed a higher recurrence tendency than the unicystic type. Conclusion: When the lesion is multicystic, perforating the cortical bone, infiltrating the adjacent soft tissue, or involving the IAN, a high recurrence rate is shown. The results of this retrospective analysis of the recurrence trend of ameloblastoma over a 5 years period are to contribute significantly to insight and reduction of recurrence rates in treatment for polymorphic lesion in oral and maxillofacial area.

본 연구를 통해 국내 주요 한약재인 복령의 유해물질에 대한 안전성 확립과 허용기준치 설정의 기초자료를 제공하고자 한다. 국내 유통 중인 복령 10건(국내산 5건, 중국 산 5건)에 대한 잔류농약(321종), 중금속(7종), 방사능(3종), 회분 함량을 분석하였다. 잔류농약은 국내산 1건에서만 농약 성분인 cypermethrin 0.03mg/kg이 검출되었으나 기준치 이하로 나타났다. cypermethrin은 과수 및 원예농업에서 해충 방제의 살 충제로 사용되는 성분이다. 중금속은 Hg를 제외한 Zn, Pb, Ni, Cu, Hg, Cr가 모든 시료에서 검출됐지만 기준치 이하로 나타났다. Cd는 중국산 1건에서 0.011 mg/kg이 검출되었다. 방사능 농도도 모든 시료에서 MDA값 이하로 나타나 불검출 수준이었으며, 회분 함량도 모든 시료에서 기준치인 1.0% 이하로 나타났다. 이번 조사에서 국내에 유통 중인 복령의 유해물질에 대한 위해성은 안전하게 나타났다. 일반적으로 버섯류는 중금속 함량이 높다고 알려져 있다. 복령은 토양 속에서 생장하는 재배 특성상 유해물질에 항시 노출되어 있으므로 재배, 저장, 유통 등 생산단계 전반에 대한 지속적인 모니터링과 체계적인 관리기준 설정이 필요할 것으로 보인다.

This study was performed as a part of serial experiments of applying convolutional neural network(CNN) in determining osteoporosis on panoramic radiograph. The purpose of this study was to investigate how sensitively CNN determine osteoporosis on cropped panoramic radiograph. Panoramic radiographs from 1268 female patients(mean age 45.2 ± 21.1 yrs) were selected for this study. For the osteoporosis group, 633(mean age 72.2 ± 8.5 yrs) were selected, while for the normal group 635(mean age 28.3 ± 7.0 yrs). AlexNet was utilized as CNN in this study. A multiple-column CNN was designed with two rectangular regions of interest on the mandible inferior area. An occluding method was used to analyze the sensitive area in determining osteoporosis on AlexNet. Testing of AlexNet showed accuracy of 99% in determining osteoporosis on panoramic radiographs. AlexNet was sensitive at the area of cortical and cancellous bone of the mandible inferior area including adjacent soft tissue.

Deep convolutional network is a deep learning approach to optimize image recognition. This study aimed to apply DCNN to the reading of mandibular cortical thinning in digital panoramic radiographs. Digital panoramic radiographs of 1,268 female dental patients (age 45.2 ± 21.1yrs) were used in the reading of the mandibular cortical bone by two maxillofacial radiologists. Among the subjects, 535 normal subject’s panoramic radiographs (age 28.6 ±7.4 yrs) and 533 those of osteoporosis pationts (age 72.1 ± 8.7 yrs) with mandibular cortical thinning were used for training DCNN. In the testing of mandibular cortical thinning, 100 panoramic radiographs of normal subjects (age 26.6 ± 4.5 yrs) and 100 mandibular cortical thinning (age 72.5 ± 7.2 yrs) were used. The sensitive area of DCNN to mandibular cortical thinning was investigated by occluding analysis. The readings of DCNN were compared by two maxillofacial radiologists. DCNN showed 97.5% accuracy, 96% sensitivity, and 99% specificity in reading mandibular cortical thinning. DCNN was sensitively responded on the cancellous and cortical bone of the mandibular inferior area. DCNN was effective in diagnosing mandibular cortical thinning.