Investigating glioma genetics through perfusion MRI: rCBV and rCBF as predictive biomarkers.

Background: Brain tumors exhibit diverse genetic landscapes and hemodynamic properties, influencing diagnosis and treatment outcomes.

Purpose: To explore the relationship between MRI perfusion metrics (rCBV, rCBF), genetic markers, and contrast enhancement patterns in gliomas, aiming to enhance diagnostic accuracy and inform personalized therapeutic strategies. Additionally, other radiological features, such as the T2/FLAIR mismatch sign, are evaluated for their predictive utility in IDH mutations.

Evaluation of a Vendor-Agnostic Deep Learning Model for Noise Reduction and Image Quality Improvement in Dental CBCT.

Background/objectives: To assess the impact of a vendor-agnostic deep learning model (DLM) on image quality parameters and noise reduction in dental cone-beam computed tomography (CBCT) reconstructions.

Methods: This retrospective study was conducted on CBCT scans of 93 patients (41 males and 52 females, mean age 41.2 years, SD 15.

Early Cerebral Microvasculature Impairment and Increased Body Mass Index in Patients with Psoriasis.

Psoriasis induces systemic atherosclerosis, but its impact on cerebrovascular function remains unclear. However, stroke prevention must be considered in psoriasis, as it is commonly comorbid with classic cardiovascular risk factors. Thus, the aim of the study is to assess cerebral microvasculature function and its confounders in patients with psoriasis.

Endodontic Treatment Outcomes in Cone Beam Computed Tomography Images-Assessment of the Diagnostic Accuracy of AI.

The aim of this study was to assess the diagnostic accuracy of the AI-driven platform Diagnocat for evaluating endodontic treatment outcomes using cone beam computed tomography (CBCT) images. A total of 55 consecutive patients (15 males and 40 females, aged 12-70 years) referred for CBCT imaging were included. CBCT images were analyzed using Diagnocat's AI platform, which assessed parameters such as the probability of filling, adequate obturation, adequate density, overfilling, voids in filling, short filling, and root canal number.

Accuracy of Artificial Intelligence for Cervical Vertebral Maturation Assessment-A Systematic Review.

To systematically review and summarize the existing scientific evidence on the diagnostic performance of artificial intelligence (AI) in assessing cervical vertebral maturation (CVM). This review aimed to evaluate the accuracy and reliability of AI algorithms in comparison to those of experienced clinicians. Comprehensive searches were conducted across multiple databases, including PubMed, Scopus, Web of Science, and Embase, using a combination of Boolean operators and MeSH terms.

Comparison of Three Commercially Available, AI-Driven Cephalometric Analysis Tools in Orthodontics.

Cephalometric analysis (CA) is an indispensable diagnostic tool in orthodontics for treatment planning and outcome assessment. Manual CA is time-consuming and prone to variability. This study aims to compare the accuracy and repeatability of CA results among three commercial AI-driven programs: CephX, WebCeph, and AudaxCeph.

Reliability of the AI-Assisted Assessment of the Proximity of the Root Apices to Mandibular Canal.

: This study evaluates the diagnostic accuracy of an AI-assisted tool in assessing the proximity of the mandibular canal (MC) to the root apices (RAs) of mandibular teeth using computed tomography (CT). : This study involved 57 patients aged 18-30 whose CT scans were analyzed by both AI and human experts. The primary aim was to measure the closest distance between the MC and RAs and to assess the AI tool's diagnostic performance.

Evaluating the Diagnostic Accuracy of an AI-Driven Platform for Assessing Endodontic Treatment Outcomes Using Panoramic Radiographs: A Preliminary Study.

The purpose of this preliminary study was to evaluate the diagnostic performance of an AI-driven platform, Diagnocat (Diagnocat Ltd., San Francisco, CA, USA), for assessing endodontic treatment outcomes using panoramic radiographs (PANs). The study included 55 PAN images of 55 patients (15 males and 40 females, aged 12-70) who underwent imaging at a private dental center.

The Impact of AI on Metal Artifacts in CBCT Oral Cavity Imaging.

Objective: This study aimed to assess the impact of artificial intelligence (AI)-driven noise reduction algorithms on metal artifacts and image quality parameters in cone-beam computed tomography (CBCT) images of the oral cavity.

Materials And Methods: This retrospective study included 70 patients, 61 of whom were analyzed after excluding those with severe motion artifacts. CBCT scans, performed using a Hyperion X9 PRO 13 × 10 CBCT machine, included images with dental implants, amalgam fillings, orthodontic appliances, root canal fillings, and crowns.

Dual-Energy and Photon-Counting Computed Tomography in Vascular Applications-Technical Background and Post-Processing Techniques.

The field of computed tomography (CT), which is a basic diagnostic tool in clinical practice, has recently undergone rapid technological advances. These include the evolution of dual-energy CT (DECT) and development of photon-counting computed tomography (PCCT). DECT enables the acquisition of CT images at two different energy spectra, which allows for the differentiation of certain materials, mainly calcium and iodine.

Beyond conventional imaging: Advancements in MRI for glioma malignancy prediction and molecular profiling.

This review examines the advancements in magnetic resonance imaging (MRI) techniques and their pivotal role in diagnosing and managing gliomas, the most prevalent primary brain tumors. The paper underscores the importance of integrating modern MRI modalities, such as diffusion-weighted imaging and perfusion MRI, which are essential for assessing glioma malignancy and predicting tumor behavior. Special attention is given to the 2021 WHO Classification of Tumors of the Central Nervous System, emphasizing the integration of molecular diagnostics in glioma classification, significantly impacting treatment decisions.

Periapical Lesions in Panoramic Radiography and CBCT Imaging-Assessment of AI's Diagnostic Accuracy.

: Periapical lesions (PLs) are frequently detected in dental radiology. Accurate diagnosis of these lesions is essential for proper treatment planning. Imaging techniques such as orthopantomogram (OPG) and cone-beam CT (CBCT) imaging are used to identify PLs.

Noise-Optimized CBCT Imaging of Temporomandibular Joints-The Impact of AI on Image Quality.

Temporomandibular joint disorder (TMD) is a common medical condition. Cone beam computed tomography (CBCT) is effective in assessing TMD-related bone changes, but image noise may impair diagnosis. Emerging deep learning reconstruction algorithms (DLRs) could minimize noise and improve CBCT image clarity.

Analysis of IVIM Perfusion Fraction Improves Detection of Pancreatic Ductal Adenocarcinoma.

The purpose of this study was to evaluate whether intravoxel incoherent motion (IVIM) parameters can enhance the diagnostic performance of MRI in differentiating normal pancreatic parenchyma from solid pancreatic adenocarcinomas. This study included 113 participants: 66 patients diagnosed with pancreatic adenocarcinoma and 47 healthy volunteers. An MRI was conducted at 1.

Texture analysis of chest X-ray images for the diagnosis of COVID-19 pneumonia.

Purpose: Medical imaging is one of the main methods of diagnosing COVID-19, along with real-time reverse trans-cription-polymerase chain reaction (RT-PCR) tests. The purpose of the study was to analyse the texture parameters of chest X-rays (CXR) of patients suspected of having COVID-19.

Material And Methods: Texture parameters of the CXRs of 70 patients with symptoms typical of COVID-19 infection were analysed using LIFEx software.

Magnetic resonance imaging in patients with implanted cardiac electrotherapy devices: a statement from experts of the Polish Medical Society of Radiology, the Polish Society of Cardiology, and the Polish Society of Electroradiology.

The year 2023 marks 60 years since the first pacemaker was implanted in Poland. The number of implantable cardiac electrotherapy devices (CIEDs), including pacemakers, cardioverter-defibrillators, and resynchronization therapy systems, has been systematically increasing in the subsequent decades. It is estimated that nearly 500,000 Poles have an implanted cardiac electrotherapy device, making optimal diagnostic imaging with the use of magnetic resonance imaging (MRI) a clinically and epidemiologically important issue.

Enhanced visualization in endoleak detection through iterative and AI-noise optimized spectral reconstructions.

To assess the image quality parameters of dual-energy computed tomography angiography (DECTA) 40-, and 60 keV virtual monoenergetic images (VMIs) combined with deep learning-based image reconstruction model (DLM) and iterative reconstructions (IR). CT scans of 28 post EVAR patients were enrolled. The 60 s delayed phase of DECTA was evaluated.

Predicting clinical progression and cognitive decline in patients with relapsing-remitting multiple sclerosis: a 6-year follow-up study.

Introduction: Cognitive impairment occurs from the earliest stages of multiple sclerosis (MS) and progresses over time. The introduction of disease modifying therapies (DMTs) has changed the prognosis for MS patients, offering a potential opportunity for improvement in the cognitive arena as well.

Material And Methods: 41 patients with relapsing-remitting multiple sclerosis (MS) were recruited to the study.

AI in Orthodontics: Revolutionizing Diagnostics and Treatment Planning-A Comprehensive Review.

The advent of artificial intelligence (AI) in medicine has transformed various medical specialties, including orthodontics. AI has shown promising results in enhancing the accuracy of diagnoses, treatment planning, and predicting treatment outcomes. Its usage in orthodontic practices worldwide has increased with the availability of various AI applications and tools.

Skeletal facial asymmetry: reliability of manual and artificial intelligence-driven analysis.

Objectives: To compare artificial intelligence (AI)-driven web-based platform and manual measurements for analysing facial asymmetry in craniofacial CT examinations.

Methods: The study included 95 craniofacial CT scans from patients aged 18-30 years. The degree of asymmetry was measured based on AI platform-predefined anatomical landmarks: sella (S), condylion (Co), anterior nasal spine (ANS), and menton (Me).

Review of Clinical Applications of Dual-Energy CT in Patients after Endovascular Aortic Repair.

Abdominal aortic aneurysms (AAAs) are a significant cause of mortality in developed countries. Endovascular aneurysm repair (EVAR) is currently the leading treatment method for AAAs. Due to the high sensitivity and specificity of post-EVAR complication detection, CT angiography (CTA) is the reference method for imaging surveillance in patients after EVAR.

Correlation Analysis of Nasal Septum Deviation and Results of AI-Driven Automated 3D Cephalometric Analysis.

The nasal septum is believed to play a crucial role in the development of the craniofacial skeleton. Nasal septum deviation (NSD) is a common condition, affecting 18-65% of individuals. This study aimed to assess the prevalence of NSD and its potential association with abnormalities detected through cephalometric analysis using artificial intelligence (AI) algorithms.

The value of metal artifact reduction and iterative algorithms in dual energy CT angiography in patients after complex endovascular aortic aneurysm repair.

Rationale And Objectives: Evaluation of the diagnostic value of linearly blended (LB) and virtual monoenergetic images (VMI) reconstruction techniques with and without metal artifacts reduction (MAR) and of adaptive statistical iterative reconstructions (ASIR) in the assessment of target vessels after branched/fenestrated endovascular aortic repair (f/brEVAR) procedures.

Materials And Methods: CT scans of 28 patients were used in this study. Arterial phase of examination was obtained using a dual-energy fast-kVp switching scanner.

Lung ultrasound in a nutshell. Lines, signs, some applications, and misconceptions from a radiologist's point of view.

In recent years, lung ultrasound (LUS) has developed rapidly, and it is growing in popularity in various scenarios. It has become especially popular among clinicians. There are constant attempts to introduce it in new fields, with quite a strong resistance in the radiological community.