APPLICATION OF THE CONE BEAM COMPUTED TOMOGRAPHY (CBCT) MODALITY WITH WEIGHT BEARING TECHNIQUE TO IDENTIFY OSTEOARTHRITIS (OA) IN THE KNEE JOINT - IM Dwitya Surya Wrddhi Putra; Sudiyono Sudiyono; Kasimin Kasimin (Politeknik Kesehatan Kementerian Kesehatan Semarang, 2022)
ABSTRACTBackground : Osteoarthritis (OA) is a degenerative joint disease that causes inflammation of the cartilage due to the load that is often received by the joints. The knee joint is a part that is often affected by OA. Radiographic and CT examinations can be used to check for OA of the knee. Radiographic examination has the advantage of optimally displaying OA because the examination is carried out under weight bearing conditions, and CT is superior in displaying anatomical details due to cross sectional and 3D reconstruction. Technological developments present Cone Beam CT (CBCT) weight bearings that combine the advantages of radiographic and CT examinations. The purpose of this study is to determine the role and benefits of CBCT weight bearing on knee joint image information in cases of OA.Method : This type of research is literature review research with a narrative review approach. The databases used in the review articles include Science Direct, ProQuest, PubMed, DOAJ, Google Scholar, Wiley Online Library, ISI Web of Knowledge, and the Oxford Journal. The articles that have been obtained will be processed in tabulated form for later extraction.Result : The results of this study indicate that weight bearing is able to assess degeneration causing internal rotation in the range of +/- 2.8-3.1o, lateral patellar shift up to +/- 0.4 mm, joint space width (JSW) up to +/- 0.5 mm, meniscal extrusion (ME) up to +/- 10.2 mm. Conclusion : CBCT is used to obtain volumetric and cross sectional 3D knee images, in order to obtain images with high spatial resolution with low doses, detailed bone structure images, short scan times, visualization of narrowing and progression of OA in JSW clearly, visualization of OA in the menisci, as well as visualizing the complexity of the joint and soft tissue images so that OA is easily identified.