Impact of PET reconstruction protocols on quantification of lesions that fulfil the PERCIST lesion inclusion criteria.

Background: The aim of this study was to compare liver and oncologic lesion standardized uptake values (SUV) obtained through two different reconstruction protocols, GE's newest clinical lesion detection protocol (Q.Clear) and the EANM Research Ltd (EARL) harmonization protocol, and to assess the clinical relevance of potential differences and possible implications for daily clinical practice using the PERCIST lesional inclusion criteria. NEMA phantom recovery coefficients (RC) and SUV normalized for lean body mass (LBM), referred to as SUV normalized for LBM (SUL), of liver and lesion volumes of interest were compared between the two reconstruction protocols.

Patient-specific lean body mass can be estimated from limited-coverage computed tomography images.

Objective: In PET/CT, quantitative evaluation of tumour metabolic activity is possible through standardized uptake values, usually normalized for body weight (BW) or lean body mass (LBM). Patient-specific LBM can be estimated from whole-body (WB) CT images. As most clinical indications only warrant PET/CT examinations covering head to midthigh, the aim of this study was to develop a simple and reliable method to estimate LBM from limited-coverage (LC) CT images and test its validity.

Integrin-Linked Kinase Regulates Bone Formation by Controlling Cytoskeletal Organization and Modulating BMP and Wnt Signaling in Osteoprogenitors.

Cell-matrix interactions constitute a fundamental aspect of skeletal cell biology and play essential roles in bone homeostasis. These interactions are primarily mediated by transmembrane integrin receptors, which mediate cell adhesion and transduce signals from the extracellular matrix to intracellular responses via various downstream effectors, including integrin-linked kinase (ILK). ILK functions as adaptor protein at focal adhesion sites, linking integrins to the actin cytoskeleton, and has been reported to act as a kinase phosphorylating signaling molecules such as GSK-3β and Akt.

Evaluation of CT-based SUV normalization.

The purpose of this study was to determine patients' lean body mass (LBM) and lean tissue (LT) mass using a computed tomography (CT)-based method, and to compare standardized uptake value (SUV) normalized by these parameters to conventionally normalized SUVs. Head-to-toe positron emission tomography (PET)/CT examinations were retrospectively retrieved and semi-automatically segmented into tissue types based on thresholding of CT Hounsfield units (HU). The following HU ranges were used for determination of CT-estimated LBM and LT (LBMCT and LTCT):  -180 to  -7 for adipose tissue (AT), -6 to 142 for LT, and 143 to 3010 for bone tissue (BT).

Preclinical validation of automated dual-energy X-ray absorptiometry and computed tomography-based body composition measurements.

Background: The aim of this study was to determine and validate a set of Hounsfield unit (HU) ranges to segment computed tomography (CT) images into tissue types and to test the validity of dual-energy X-ray absorptiometry (DXA) tissue segmentation on pure, unmixed porcine tissues.

Methods: This preclinical prospective study was approved by the local ethical committee. Different quantities of porcine bone tissue (BT), lean tissue (LT) and adipose tissue (AT) were scanned using DXA and CT.

Review of clinically accessible methods to determine lean body mass for normalization of standardized uptake values.

With the routine use of 2-deoxy-2-[18F]-fluoro-D-glucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) scans, metabolic activity of tumors can be quantitatively assessed through calculation of SUVs. One possible normalization parameter for the standardized uptake value (SUV) is lean body mass (LBM), which is generally calculated through predictive equations based on height and body weight. (Semi-)direct measurements of LBM could provide more accurate results in cancer populations than predictive equations based on healthy populations.