The use of artificial intelligence (AI) in the radiological field has been extensively investigated from the radiologists’ perspective. Existing studies have primarily focused on AI’s contribution to diagnostic processes and on how its introduction has transformed—and continues to transform—radiologists’ professional practice. The perspectives of radiographers remain underrepresented in the literature, despite their central role in image acquisition and their position as the primary “on-the-ground” operators and managers of imaging technologies. The objective of this study was to analyze the perceptions, attitudes, and expectations of Italian radiographers regarding the introduction of AI, and to provide insights to inform professional training and organizational strategies within healthcare systems. A cross-sectional survey study with qualitative enhancement was adopted as the study design. A survey was administered to a convenience sample, comprising 222 respondents. The findings reveal a high level of familiarity with AI in everyday life, accompanied by an almost complete absence of cultural resistance, suggesting a workforce that is both receptive and ready to evolve. Nevertheless, this individual readiness is contrasted with a substantial institutional and operational gap, characterized by the lack of standardized protocols, regulatory uncertainty, and an uneven distribution of technological resources. The effective integration of AI therefore requires a comprehensive and coordinated approach. Educational reform is necessary to integrate AI and radiomics into university curricula and continuing professional development programs, encompassing not only technical competencies but also ethical, deontological and communication skills. Finally, national and European regulatory frameworks must evolve to clearly define radiographers’ responsibilities within AI-assisted workflows, to establish robust guidelines for data governance and the management of algorithmic outputs.

This narrative review provides a contemporary synthesis of lateral cephalometric radiography (LCR), addressing both its foundational principles and the impact of technological integration, with a focus on enhancing diagnostic reliability. A structured literature search (PubMed, up to September 2025) was conducted around five domains: LCR’s diagnostic role, acquisition methods, positioning errors, comparisons with cone-beam computed tomography (CBCT), and Artificial Intelligence (AI)-driven quality control. Precise patient positioning—maintaining symmetry and a horizontal Frankfort plane—is paramount, as common errors (tilting, rotation, nodding) introduce quantifiable inaccuracies in key measurements. While digital innovation, particularly deep learning models for automated landmark detection and error flagging, improves the consistency of workflow, current AI tools require validation and human oversight to manage limitations in generalizability. When contextualized against three-dimensional imaging, LCR maintains a favorable balance of diagnostic utility and lower radiation dose, supporting its selective, indication-based use in contemporary practice. Ultimately, this review suggests that adherence to a meticulous acquisition technique remains the cornerstone of reliable LCR analysis, even as AI and digital tools evolve to augment the clinician’s role.

Purpose of Review: This study aimed to investigate the potential of Cone Beam Computed Tomography (CBCT) parameters to identify primary osteoporosis in jawbones. Recent Findings: Early diagnosis of osteoporosis is crucial but challenging. Dual X-ray Absorptiometry (DXA) is the gold standard to measure bone density, nevertheless it has limitations including cost, radiation dose, and 2D imaging. CBCT is a volumetric imaging technique commonly used in dentistry that showed promise as an alternative tool due to its high spatial resolution and excellent analysis of bone structures. Summary: Mandibular and maxillary CBCT indices showed a strong correlation with Bone Mineral Density (BMD) assessed by DXA. Regional indices (Anterior, Molar, and Posterior), quantitative indices (Computed Tomography Mandibular Index, Computed Tomography Index Superior and Inferior), Radiographic Density, Fractal Dimension, and the qualitative index named Computed Tomography Cortical Index seemed appropriate for the detection of primary osteoporosis. Morphometric parameters for trabecular bone did not show differences between osteoporotic and non-osteoporotic patients. Future studies should assess diagnostic accuracy of such CBCT indices and formulate standardized measurement protocols.

Objective: Medication-related osteonecrosis of the jaws (MRONJ) is a progressive and debilitating condition that lacks specific clinical symptoms in its early phase. The recognition of stage 0 MRONJ, defined by clinical signs without bone exposure, may improve prognosis and reduce the risk of disease progression. The aim of this systematic review was to evaluate the early imaging features of MRONJ using panoramic radiography (PAN), cone beam CT (CBCT), multislice CT (MSCT), and MRI. Methods: A literature review was conducted in accordance with PRISMA guidelines using PubMed, Embase, Web of Science, and Scopus databases. Original studies in English language published by October 1, 2025, and focusing on imaging techniques in early-stage MRONJ were selected. Results: Osteosclerosis was found in 50.0%, 75.0%, and 87.5% of the studies with PAN, CBCT, and MSCT respectively. Osteolysis was identified in 66.7% of the studies with PAN and 25.0% of the studies with both CBCT and MSCT. Additional features observed less frequently were lamina dura thickening, bone sequestration, nonspecific bone alterations, and lack of post-extraction bone healing. On MRI, the non-exposed affected bone showed low T1 signal intensity, high T2 STIR signal intensity, and an increased apparent diffusion coefficient compared with healthy subjects. Conclusions: Osteosclerosis was the most frequently observed sign, although no imaging technique proved specific features for stage 0 MRONJ. Further studies with larger cohorts together with a standardization of imaging findings and a revaluation of the definition of MRONJ will be needed to identify such disease in its early stages.