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Artificial intelligence (AI) can be considered the real revolution of the 21st century [...]

Monte Carlo Path Tracing (MCPT) provides highly realistic visualization of biomedical volumes, but its computational cost limits real-time interaction. The Advanced Realistic Rendering Technique (AR2T) adapts MCPT to enable interactive exploration through coarse images generated at low sample counts. This study explores the application of deep learning models for denoising in the early iterations of the AR2T to enable higher-quality interaction with biomedical data. We evaluate five deep learning architectures, both pre-trained and trained from scratch, in terms of denoising performance. A comprehensive evaluation framework, combining metrics such as PSNR and SSIM for image fidelity and tPSNR and LDR-FLIP for temporal and perceptual consistency, highlights that models trained from scratch on domain-specific data outperform pre-trained models. Our findings challenge the conventional reliance on large, diverse datasets and emphasize the importance of domain-specific training for biomedical imaging. Furthermore, subjective clinical assessments through expert evaluations underscore the significance of aligning objective metrics with clinical relevance, highlighting the potential of the proposed approach for improving interactive visualization for analysis of bones, joints, and vessels in clinical and research environments.

Augmented reality (AR) is an innovative system that enhances the real world by superimposing virtual objects on reality. The aim of this study was to analyze the application of AR in medicine and which of its technical solutions are the most used. We carried out a scoping review of the articles published between 2019 and February 2022. The initial search yielded a total of 2649 articles. After applying filters, removing duplicates and screening, we included 34 articles in our analysis. The analysis of the articles highlighted that AR has been traditionally and mainly used in orthopedics in addition to maxillofacial surgery and oncology. Regarding the display application in AR, the Microsoft HoloLens Optical Viewer is the most used method. Moreover, for the tracking and registration phases, the marker-based method with a rigid registration remains the most used system. Overall, the results of this study suggested that AR is an innovative technology with numerous advantages, finding applications in several new surgery domains. Considering the available data, it is not possible to clearly identify all the fields of application and the best technologies regarding AR.

Objectives: A panoramic radiograph (PAN) is the most frequently diagnostic imaging technique carried out in dentistry and oral surgery. The correct performance of image acquisition is crucial to obtain adequate image quality. The aim of the present study is to (i) review the principles of PAN image acquisition and (ii) describe positioning errors and artefacts that may affect PAN image quality. Methods: Articles regarding PAN acquisition principles, patient’s positioning errors, artefacts, and image quality were retrieved from the literature. Results: Head orientation is of the utmost importance in guaranteeing correct image acquisition. Symmetry, occlusal plane inclination, mandibular condyles localization, cervical spine position, aspect of upper teeth root apexes, exposure parameters, and metal and motion artefacts are factors that greatly affect the image quality of a successful PAN. Conclusions: Several factors are the basis for PAN performance; therefore, a systematic approach that takes into account correct patient positioning and preparation is strongly suggested to improve overall examination quality.

The latest (4th) edition of the World Health Organization (WHO) Classification of Head and Neck Tumours, published in January 2017, has reclassified keratocystic odontogenic tumour as odontogenic keratocyst. Therefore, odontogenic keratocysts (OKCs) are now considered benign cysts of odontogenic origin that account for about 10% of all odontogenic cysts. OKCs arise from the dental lamina and are characterised by a cystic space containing desquamated keratin with a uniform lining of parakeratinised squamous epithelium. The reported age distribution of OKCs is considerably wide, with a peak of incidence in the third decade of life and a slight male predominance. OKCs originate in tooth-bearing regions and the mandible is more often affected than the maxilla. In the mandible, the most common location is the posterior sextant, the angle or the ramus. Conversely, the anterior sextant and the third molar region are the most common sites of origin in the maxilla. OKCs are characterised by an aggressive behaviour with a relatively high recurrence rate, particularly when OKCs are associated with syndromes. Multiple OKCs are typically associated with the nevoid basal cell carcinoma syndrome (NBCCS), an autosomal dominant multisystemic disease. Radiological imaging, mainly computed tomography (CT) and, in selected cases, magnetic resonance imaging (MRI), plays an important role in the diagnosis and management of OKCs. Therefore, the main purpose of this pictorial review is to present the imaging appearance of OKCs underlining the specific findings of different imaging modalities and to provide key radiologic features helping the differential diagnoses from other cystic and neoplastic lesions of odontogenic origin.Key Points• Panoramic radiography is helpful in the preliminary assessment of OKCs.• CT is considered the tool of choice in the evaluation of OKCs.• MRI with DWI or DKI can help differentiate OKCs from other odontogenic lesions.• Ameloblastoma, dentigerous and radicular cysts should be considered in the differential diagnosis.• The presence of multiple OKCs is one of the major criteria for the diagnosis of NBCCS.

Computed tomography (CT) and other advanced diagnostic imaging techniques are gaining popularity in forensic pathology. This paper aims to define and offer complete and easily accessible “state of the art” for post-mortem computed tomography (PMCT), by reviewing the latest international literature. The proposed format answers the “five Ws” that follows: (1) What: We report the different kinds of CT scan and settings generally used in post-mortem imaging. The machine most employed is a 8/16-slice spiral CT, usually without contrast enhancement. The introduction of some variables, such as CT-guided biopsies, post-mortem ventilation, and PMCT angiography is becoming increasingly useful. (2) Why: Literature highlights the many advantages of PMCT. Limitations can be partly overcome by modern imaging techniques and combined evaluation with traditional autopsy. (3) Who: Most authors agree that collaboration between different specialists, i.e., radiologists and pathologists, is the best scenario, since radiologic, anatomic, and forensic skills are needed simultaneously. The most important human factor is “teamwork”. (4) When: Literature provides no absolute limits for performing PMCT. Some authors have tested PMCT as a replacement for conventional autopsy but found some limitations. Others evaluated PMCT as a guide or screening tool for traditional autopsy. (5) Where: Many research groups around the world have performed studies on the use of PMCT. Although few countries adopt PMCT in routine practice, its use is rapidly spreading.

Benign neoplasms and tumor-like lesions of the tongue are relatively rare entities, encompassing a heterogeneous spectrum of morphological alterations. The recent literature focusing on benign tumors and tumor-like lesions of the tongue is relatively limited, which may lead to a gap in understanding their specific imaging characteristics. Most benign tongue tumors usually appear as submucosal bulges located in the deep portion of the tongue. Both computed tomography (CT) and magnetic resonance imaging (MRI) are essential for the comprehensive diagnostic evaluation of these entities. Cross-sectional imaging plays a pivotal role in narrowing the differential diagnosis and, in selected cases, may suggest a specific histopathological entity. The benign tumors and tumor-like lesions included in this review comprise schwannoma, lipoma, angiomyolipoma, hemangioma, vascular malformations, dermoid cysts, and thyroglossal duct remnants (including cystic formations and ectopic thyroid tissue). Additionally, certain non-neoplastic conditions—such as lingual abscesses, infectious mononucleosis complicated by lingual tonsillitis, and fatty atrophy of the tongue—can mimic neoplastic processes and present as mass-like lesions; these have also been addressed in this pictorial essay. The purpose of this work is to illustrate the key CT and MRI features of the aforementioned benign lingual lesions, with the aim of improving diagnostic confidence and accuracy.

Background The mechanisms underlying airflow obstruction in COPD cannot be distinguished by standard spirometry. We ascertain whether mathematical modeling of airway biomechanical properties, as assessed from spirometry, could provide estimates of emphysema presence and severity, as quantified by computed tomography (CT) metrics and CT-based radiomics. Methods We quantified presence and severity of emphysema by standard CT metrics (VIDA) and co-registration analysis (ImbioLDA) of inspiratory-expiratory CT in 194 COPD patients who underwent pulmonary function testing. According to percentages of low attenuation area below − 950 Hounsfield Units (%LAA -950insp ) patients were classified as having no emphysema (NE) with %LAA -950insp  < 6, moderate emphysema (ME) with %LAA -950insp  ≥ 6 and < 14, and severe emphysema (SE) with %LAA -950insp  ≥ 14. We also obtained stratified clusters of emphysema CT features by an automated unsupervised radiomics approach (CALIPER). An emphysema severity index (ESI), derived from mathematical modeling of the maximum expiratory flow-volume curve descending limb, was compared with pulmonary function data and the three CT classifications of emphysema presence and severity as derived from CT metrics and radiomics. Results ESI mean values and pulmonary function data differed significantly in the subgroups with different emphysema degree classified by VIDA, ImbioLDA and CALIPER ( p  < 0.001 by ANOVA). ESI differentiated NE from ME/SE CT-classified patients (sensitivity 0.80, specificity 0.85, AUC 0.86) and SE from ME CT-classified patients (sensitivity 0.82, specificity 0.87, AUC 0.88). Conclusions Presence and severity of emphysema in patients with COPD, as quantified by CT metrics and radiomics can be estimated by mathematical modeling of airway function as derived from standard spirometry.

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(1) To investigate correlations between different types of FAI and the ratio of acetabular volume (AV) to femoral head volume (FV) on MR arthrography. (2) To assess 2D/3D measurements in identifying different types of FAI by means of cut-off values of AV/FV ratio (AFR).Materials and methodsAlpha angle, cranial acetabular version, acetabular depth, lateral center edge angle, AV, and FV of 52 hip MR arthrography were measured. ANOVA test correlated different types of FAI with AFR. ROC curves classified FAI by cut-off values of AFR. Accuracy of 2D/3D measurements was calculated.ResultsANOVA test showed a significant difference of AFR (p value < 0.001) among the three types of FAI. The mean values of AFR were 0.64, 0.74, and 0.89 in cam, mixed, and pincer types, respectively. Cut-off values of AFR were 0.70 to distinguish cam types from mixed and pincer types, and 0.79 to distinguish pincer types from cam and mixed types. Cut-off values identified 100%, 73.9%, and 55.6% of pincer, cam, and mixed types. 2D and 3D classifications of FAI showed accuracy of 40.4% and 73.0%.Conclusions3D measurements were clearly more accurate than 2D measurements. Distinct cut-off values of AFR discriminated cam types from pincer types and identified pincer types in all cases. Cam and mixed types were not accurately recognized.