Positron Range Correction Helps Enhance the Image Quality of Cardiac Rb PET/CT.

The image quality and quantitative accuracy of Rb myocardial perfusion imaging (MPI) using PET is challenged by the extensive positron range (PR) effects, with the PR of Rb being about 7 mm in soft tissues. This study explored the feasibility of applying postacquisition PR correction (PRC) to routine Rb PET/CT MPI acquisitions and assessed its impact on diagnostic accuracy and image quality. We implemented a PRC method adjusted to Rb into a vendor-provided reconstruction toolbox, using tissue-specific corrections for soft tissue, bone, and air/lungs.

Development of a comprehensive sustainability index for extractive and mining companies: Integrating the Sustainable Development Goals.

Sustainability in the extractive and mining industry has become a key global concern, necessitating alignment with the United Nations Sustainable Development Goals (SDGs). This research introduces an innovative, scientific index-based assessment methodology designed to quantify the contribution of companies in these sectors to the SDGs. The methodology leverages a metric index scoring system to evaluate and enhance their sustainability performance.

High satisfaction and low conversion rate to total hip arthroplasty after hip arthroscopy for femoroacetabular impingement syndrome and risk factors affecting survival at long-term follow-up.

Purpose: Studies evaluating the long-term survival rate, patient satisfaction, and conversion to total hip arthroplasty (THA) are limited. The aim of this study was to evaluate satisfaction and hip survival at a minimum 10-year follow-up in patients following hip arthroscopy for femoroacetabular impingement syndrome (FAIS).

Methods: A total of 164 patients underwent hip arthroscopy for FAIS between 2007 and 2012; of these, 76 (49 men and 27 women; mean age, 40.

SMART-PET: a Self-SiMilARiTy-aware generative adversarial framework for reconstructing low-count [18F]-FDG-PET brain imaging.

Introduction: In Positron Emission Tomography (PET) imaging, the use of tracers increases radioactive exposure for longitudinal evaluations and in radiosensitive populations such as pediatrics. However, reducing injected PET activity potentially leads to an unfavorable compromise between radiation exposure and image quality, causing lower signal-to-noise ratios and degraded images. Deep learning-based denoising approaches can be employed to recover low count PET image signals: nonetheless, most of these methods rely on structural or anatomic guidance from magnetic resonance imaging (MRI) and fails to effectively preserve global spatial features in denoised PET images, without impacting signal-to-noise ratios.