Advancements in craniofacial prosthesis fabrication: A narrative review of holistic treatment

The treatment of craniofacial anomalies has been challenging as a result of technological shortcomings that could not provide a consistent protocol to perfectly restore patient-specific anatomy. In the past, wax-up and impression-based maneuvers were implemented to achieve this clinical end. However, with the advent of computer-aided design and computer-aided manufacturing (CAD/CAM) technology, a rapid and cost-effective workflow in prosthetic rehabilitation has taken the place of the outdated procedures. Because the use of implants is so profound in different facets of restorative dentistry, their placement for craniofacial prosthesis retention has also been widely popular and advantageous in a variety of clinical settings. This review aims to effectively describe the well-rounded and interdisciplinary practice of craniofacial prosthesis fabrication and retention by outlining fabrication, osseointegrated implant placement for prosthesis retention, a myriad of clinical examples in the craniofacial complex, and a glimpse of the future of bioengineering principles to restore bioactivity and physiology to the previously defected tissue.

Conventional versus digital radiographs in detecting artificial voids in root canal filling material

Inappropriate condensation of gutta-percha or improper use of sealer can lead to voids in root canal filling material and consequent failure of the treatment. Timely detection of voids within root canal filling may prevent complications. In this study, we compared the accuracy of digital and conventional radiograph for detecting voids within root canal fillings. The root canals of 50 extracted maxillary permanent incisors were prepared and filled with gutta-percha and sealer. The teeth were then randomly divided into two groups of 25 incisors. The teeth were imaged using the paralleling technique with E-speed film and digital/digital zoomed system. The accuracy of radiographic techniques was evaluated for detecting voids by three independent observers. Presence/absence of voids was recorded and compared with the baseline data. The sensitivity, specificity, accuracy and positive and negative predictive values was recorded. The sensitivity, specificity and accuracy of conventional radiography and digital radiography were 48%, 52%, 50%, and 82.7%, 80% and 81.3%, respectively. The positive and negative predictive value of conventional radiography was 50%. Digital images showed the positive predictive value of 80.3% and negative predictive value of 83.5%. The values of positive and negative predictive were reported as 81.6% and 81.1% in digital zoomed images. Digital and digital zoomed images performed better than conventional radiographs in detecting voids, but there were no differences between the performances of both digital images