Bone quality assessment in patients with healing mandibular fracture sites: a computed tomography investigation.
Erika Antonia Anjos RamosLuciana MunhozBasílio Almeida MilaniEmiko Saito AritaPublished in: General dentistry (2024)
The objective of this retrospective study was to assess the bone quality of healing mandibular fracture sites by measuring the Hounsfield units (HU) on computed tomographic (CT) images obtained presurgery and postsurgery in patients treated with rigid internal fixation (RIF). The HU values of healing fracture sites were compared to those of corresponding nonfractured (control) sites on the opposing side and cervical vertebrae sites in the same patients. In total, 31 patients with 45 mandibular fractures treated with RIF underwent presurgical and postsurgical CT examinations. The scans performed after surgery (1, 3, 6, 12, or 18 months) were taken only when there was a need for radiographic evaluation due to a complaint of discomfort from the patient or when the surgeon needed to verify the postsurgical outcome, and each patient underwent only a single postsurgical CT. At the presurgical CT examination, the HU values were lower in the fracture sites than in the control sites. At 3 months postsurgery, the HU values in the fracture sites had increased as the mandibular bone healed. At 6 months postsurgery, the HU values in the fracture sites were higher than those of the control sites. At 12 and 18 months postsurgery, the HU values of both sites were similar. The HU values of the cervical vertebrae remained constant with time. These results suggest that, in patients who have been treated with RIF for mandibular bone fracture, HU values measured by CT vary across time, expressing the physiologic bone healing process.
Keyphrases
- computed tomography
- dual energy
- image quality
- end stage renal disease
- contrast enhanced
- bone mineral density
- newly diagnosed
- positron emission tomography
- chronic kidney disease
- magnetic resonance imaging
- hip fracture
- peritoneal dialysis
- soft tissue
- magnetic resonance
- case report
- deep learning
- pulmonary tuberculosis
- patient reported outcomes
- cone beam computed tomography
- machine learning