ABSTRAKPada penelitian sebelumnya diketahui bahwa aplikasi patch gingiva mukoadesif β-carotene berfungsi sebagai bahan proteksi efek paparan radiografi panoramik pada hewan coba kelinci New Zealand. Peningkatan jumlah mikronukleus akibat paparan radiografi panoramik dapat dihambat dengan aplikasi patch β-carotene. Sebagai kelanjutan dari penelitian, dilakukan uji klinis terhadap manusia untuk melihat efek proteksi patch tersebut. Sebanyak 20 orang subjek yang akan dipapar radiografi panoramik dimasukkan secara random dalam 2 kelompok. Kelompok I adalah subjek tanpa aplikasi patch gingiva mukoadesif β-carotene dan Kelompok II adalah subjek yang diaplikasi patch sebelum paparan. Setiap subjek dilakukan apusan pada mukosa gingiva anterior rahang atas sebelum dan 10 hari setelah paparan radiografi panoramik. Apusan diwarnai dengan metode modifikasi Feulgen-Rossenbeck. Efek lain dari aplikasi juga dilihat mengenai lama waktu bertahan patch dan hasil radiograf yang dihasilkan. Hasil penelitian menunjukkan bahwa terdapat penurunan jumlah mikronukleus pada kelompok II walaupun tidak berbeda bermakna (p>0,05) terhadap kelompok I. Lama waktu bertahan patch gingiva mukoadesif β-carotene dapat mencapai lebih dari 10 jam dan dilaporkan terasa mengganjal pada awal pemakaian. Hasil analisis gray scale antara radiograf dengan dan tanpa aplikasi tidak menunjukkan perbedaan yang bermakna (p>0,05). Kesimpulan dari penelitian ini adalah aplikasi patch gingiva mukoadesif β-carotene dapat menurunkan jumlah mikronukleus namun tidak secara signifikan.Maj Ked Gi Ind. Desember 2015; 1(2): 186 -192 Kata Kunci: Patch gingiva mukoadesif β-carotene, mikronukleus, paparan radiografi panoramik manusia Abstract: Effect of β-carotene Gingival Mucoadhesive Patch Application at Panoramic Radiography Exposure.According to previous research, β-carotene gingival mucoadhesive patch has a radiation protection effect on New Zealand Rabbits. The increase in micronucleus after panoramic radiography exposure is avoided because of β-carotene gingival mucoadhesive patch application. In order to continue that research, we try the application of β-carotene gingival mucoadhesive patch into human. Twenty subjects who requested to take panoramic radiography were divided into two groups randomly. Group I was without β-carotene gingival mucoadhesive patch application and Group II was given the application before radiography exposure. Each of the subjects was swabbed on anterior maxillary gingiva before radiography exposure and the 10th day after the exposure. The swab was stained using modified Feulgen Rossenbeck method. The adhesive time and the effect of radiograph were also observed. The result shows that there was a decrease in micronucleus number after β-carotene gingival mucoadhesive patch application but there was no significant difference (p>0,05) between Grup I and II. The adhesive time was more than 10 hours and there was uncomfortable taste in the first time application. Gray scale analysis shows no significant difference (P>0,05) between panoramic rad...

Background: Dental digital radiography is more practical and requires fewer doses of radiation than conventional radiography. Because ionizing radiation has a biological effect on exposed tissue, concerns regarding its stochastic effect merit greater attention. In a previous study, it was found that biological changes and increases in the micronucleus occurred after conventional panoramic exposure to gingival crevicular fluid (GCF). Purpose: The purpose of this study is to investigate the difference in biological effects

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Purpose To analyze the quality of mandibular trabecular structure in postmenopausal women using periapical radiographs. Postmenopausal women are subjected to low bone quality; hence, early detection methods are needed. In addition to bone mineral density (BMD), trabecular architecture must be assessed to determine bone quality. The mandible represents bone quality and allows the assessment of trabecular structure from periapical radiographs. Material and Methods Lumbar (BMDL) and femoral BMD (BMDF) examinations were performed using dual-energy X-ray absorptiometry (DXA) in 31 postmenopausal women and divided into normal, osteopenia, and osteoporotic groups. Periapical radiographs were taken at both posterior sites of the mandible. The region of interest was taken 2 mm from the apical root of the first molar. Trabecular parameters consisting of trabecular thickness (Tb.Th) and bone percentage (BA/TA) were measured using BoneJ. Results Both trabecular parameters were significantly correlated with BMDF [BA/TA ​​(r = 0.3796; p < 0.05) and Tb.Th (r = 0.508; p < 0.05)]. BA/TA and Tb.Th were significantly different between the osteoporosis and normal groups (p < 0.05) contrast to osteopenia and normal groups (p > 0.05). Conclusion Changes in mandibular trabeculae structure in postmenopausal women can be assessed using periapical radiographs.

Objectives: This narrative review is written to describe the accuracy of caries detection and find out the clinical implications and future prospects of using Convolutional Neural Network (CNN) to determine radio-diagnosis of dental caries in bitewing and periapical radiographs. Review: The databases used for literature searching in this narrative review were PubMed, Google Scholar, and Science Direct. The inclusion criteria were original article, case report, and textbook written in English and Bahasa Indonesia, published within 2011-2021. The exclusion criteria were articles that the full text could not be accessed, research article that did not provide the methods used, and duplication articles. In this narrative review, a total of 33 literatures consisting of 30 articles and three textbooks reviewed, including four original articles on CNN for caries detection. Conclusion: Results of the review reveal that GoogLeNet produces the best detection compared to Fully Convolutional Network (FCN) and U-Net for caries detection in bitewing and periapical radiographs. Nonetheless, the positive predictive value (PPV), recall, negative predictive value (NPV), specificity, F1-score, and accuracy values in these architectures indicate good performance. The differences of each CNN’s performances to detect caries are determined by the number of trained datasets, the architecture’s layers, and the complexity of the CNN architectures. The conclusion of this review is CNN can be used as an alternative to detect caries, increasing the diagnostic accuracy and time efficiency as well as preventing errors due to dentist fatigue. Yet the CNN is not able to substitute the expertise of a radiologist. Therefore, it is need to be revalidated by the radiologist to avoid diagnostic errors.