Automatic localization of anatomical landmarks in head cine fluoroscopy images via deep learning.

Background: Fluoroscopy guided interventions (FGIs) pose a risk of prolonged radiation exposure; personalized patient dosimetry is necessary to improve patient safety during these procedures. However, current FGIs systems do not capture the precise exposure regions of the patient, making it challenging to perform patient-procedure-specific dosimetry. Thus, there is a pressing need to develop approaches to extract and use this information to enable personalized radiation dosimetry for interventional procedures.

Generation of fluoroscopy-alike radiographs as alternative datasets for deep learning in interventional radiology.

In fluoroscopy-guided interventions (FGIs), obtaining large quantities of labelled data for deep learning (DL) can be difficult. Synthetic labelled data can serve as an alternative, generated via pseudo 2D projections of CT volumetric data. However, contrasted vessels have low visibility in simple 2D projections of contrasted CT data.

Osteoporosis in Parkinson's Disease: Relevance of Distal Radius Dual-Energy X-Ray Absorptiometry (DXA) and Sarcopenia.

Osteoporotic fractures are common in Parkinson's disease (PD). Standard dual-energy X-ray absorptiometry (DXA) measuring bone mineral density (BMD) at the femoral neck and lumbar spine (central sites) has suboptimal sensitivity in predicting fracture risk in the general population. An association between sarcopenia and osteoporosis in PD has not been studied.

Progressive and accelerated weight and body fat loss in Parkinson's disease: A three-year prospective longitudinal study.

Introduction: Although weight loss is common in Parkinson's disease (PD), longitudinal studies assessing weight and body composition changes are limited.

Methods: In this three-year longitudinal study, 125 subjects (77 PD patients and 48 spousal/sibling controls) underwent clinical, biochemical and body composition assessments using dual-energy X-ray absorptiometry.

Results: Patients were older than controls (65.

Automated plaque classification using computed tomography angiography and Gabor transformations.

Cardiovascular diseases are the primary cause of death globally. These are often associated with atherosclerosis. This inflammation process triggers important variations in the coronary arteries (CA) and can lead to coronary artery disease (CAD).

Personalized administration of contrast medium with high delivery rate in low tube voltage coronary computed tomography angiography.

Background: High delivery rate is an important factor in optimizing contrast medium administration in coronary computed tomography angiography (CCTA). A personalized contrast volume calculation algorithm incorporating high iodine delivery rate (IDR) can reduce total iodine dose (TID) and produce optimal vessel contrast enhancement (VCE) in low tube voltage CCTA. In this study, we developed and validated an algorithm for calculating the volume of contrast medium delivered at a high rate for patients undergoing retrospectively ECG-gated CCTA with low tube voltage protocol.

Low tube voltage prospectively ECG-triggered coronary CT angiography: a systematic review of image quality and radiation dose.

Objective: This study aimed (1) to perform a systematic review on scanning parameters and contrast medium (CM) reduction methods used in prospectively electrocardiography (ECG-triggered low tube voltage coronary CT angiography (CCTA), (2) to compare the achievable dose reduction and image quality and (3) to propose appropriate scanning techniques and CM administration methods.

Methods: A systematic search was performed in PubMed, the Cochrane library, CINAHL, Web of Science, ScienceDirect and Scopus, where 20 studies were selected for analysis of scanning parameters and CM reduction methods.

Results: The mean effective dose (H) ranged from 0.