Comparison of Two-Dimensional and Three-Dimensional Radiographs Using Clinically Relevant Parameters.

Area of Science:

• Dentistry
• Radiology
• Oral Imaging

Background:

• Comparison of diagnostic accuracy between 2D (intraoral radiographs - I-O, panoramic radiographs - OPT) and 3D (cone beam computed tomography - CBCT) imaging modalities is crucial for clinical decision-making.
• Evaluating 14 distinct dental and periodontal parameters across different radiographic techniques provides comprehensive insights into their respective strengths and limitations.

Observation:

• A case study involving a 53-year-old female patient with significant dental and periodontal issues was utilized to compare CBCT, I-O, and OPT imaging.
• Two independent examiners assessed 14 predefined clinical parameters using the available radiographic datasets.

Findings:

• Cone beam computed tomography (CBCT) demonstrated superior performance in assessing 10 out of 14 (71%) parameters compared to both intraoral radiographs (I-O) and panoramic radiographs (OPT).
• CBCT showed inferior diagnostic capability for detecting caries and evaluating dental restorations when contrasted with I-O and OPT.
• Intraoral radiographs (I-O) provided more clinically relevant information than panoramic radiographs (OPT) for 10 out of 14 (71%) assessed parameters.
• High agreement was observed between I-O and OPT for assessing dehiscence, fenestration, bone wall count, and root canal cross-sections.
• Maxillary teeth assessments revealed more inter-modality differences than mandibular teeth assessments concerning furcation involvement, root proximity, and root fusion.

Implications:

• CBCT offers enhanced visualization for a majority of dental and periodontal conditions, potentially improving diagnostic accuracy and treatment planning.
• The findings suggest a complementary role for I-O and OPT, particularly for detecting caries and assessing restorations, where CBCT may be less advantageous.
• Understanding the specific strengths of each imaging modality allows for optimized selection based on the clinical question, potentially leading to more efficient and effective patient care.