PURPOSE: In this study the temporal texture differentiation associated with the bone formation properties, around loaded oral implants after Platelet Rich Plasma (PRP) employment, was investigated in Panoramic Radiographs. MATERIALS AND METHODS:Thirty eligible patients are randomly assigned to two groups. The test group received PRP application around new implants, while in the control group no PRP treatment was made. The bone-to-implant contact region was analyzed in a clinical sample of 60 Digitized Panoramic Radiographs, 30 corresponding to immediate implant loading (Class-I) and 30 after an 8 month follow-up period (Class-II). This region was sampled by 1146 circular Regions-of-Interest (ROIs), resulting from a specifically designed segmentation scheme based on Markov-Random-Fields (MRF). From each ROI, 41 textural features were extracted, then reduced to a subset of 4 features due to redundancy and employed as input to Receiver-Operating-Characteristic (ROC) analysis, to assess the textural differentiation between two classes. RESULTS: The selected subset, achieved Area-Under-Curve (AUC) values ranging from 0.77-0.81 in the PRP group, indicating the significant temporal textural differentiation has been made. In the control group, the AUC values ranged from 0.56-0.68 demonstrating lesser osseo integration activity. CONCLUSION: This study provides evidences that PRP application may favor bone formation around loaded dental implants that could modify the dental treatment planning.
RCT Entities:
PURPOSE: In this study the temporal texture differentiation associated with the bone formation properties, around loaded oral implants after Platelet Rich Plasma (PRP) employment, was investigated in Panoramic Radiographs. MATERIALS AND METHODS: Thirty eligible patients are randomly assigned to two groups. The test group received PRP application around new implants, while in the control group no PRP treatment was made. The bone-to-implant contact region was analyzed in a clinical sample of 60 Digitized Panoramic Radiographs, 30 corresponding to immediate implant loading (Class-I) and 30 after an 8 month follow-up period (Class-II). This region was sampled by 1146 circular Regions-of-Interest (ROIs), resulting from a specifically designed segmentation scheme based on Markov-Random-Fields (MRF). From each ROI, 41 textural features were extracted, then reduced to a subset of 4 features due to redundancy and employed as input to Receiver-Operating-Characteristic (ROC) analysis, to assess the textural differentiation between two classes. RESULTS: The selected subset, achieved Area-Under-Curve (AUC) values ranging from 0.77-0.81 in the PRP group, indicating the significant temporal textural differentiation has been made. In the control group, the AUC values ranged from 0.56-0.68 demonstrating lesser osseo integration activity. CONCLUSION: This study provides evidences that PRP application may favor bone formation around loaded dental implants that could modify the dental treatment planning.
Entities:
Keywords:
Markov Random Fields; Platelet Rich Plasma; dental implants; implant segmentation; medical image texture analysis; radiography
Authors: Stuart J Froum; Stephen S Wallace; Dennis P Tarnow; Sang-Choon Cho Journal: Int J Periodontics Restorative Dent Date: 2002-02 Impact factor: 1.840
Authors: A Wojtowicz; S Chaberek; L Kryst; E Urbanowska; K Ciechowicz; K Ostrowski Journal: Int J Oral Maxillofac Surg Date: 2003-02 Impact factor: 2.789
Authors: Yan Huang; Michael M Bornstein; Ivo Lambrichts; Hai-Yang Yu; Constantinus Politis; Reinhilde Jacobs Journal: Int J Oral Sci Date: 2017-03-10 Impact factor: 6.344
Authors: Sameh Attia; Clara Narberhaus; Heidrun Schaaf; Philipp Streckbein; Jörn Pons-Kühnemann; Christian Schmitt; Friedrich Wilhelm Neukam; Hans-Peter Howaldt; Sebastian Böttger Journal: J Clin Med Date: 2020-02-01 Impact factor: 4.241
Authors: Aleshba S Khan; Naauman Zaheer; Abdul M Zaigham; Maliha Shahbaz; Usman Zaheer; Mohammad Khursheed Alam Journal: Biomed Res Int Date: 2021-03-13 Impact factor: 3.411