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Making decisions on capacity requirements in hospital environments has long-term consequences. Sound estimates of expected mid and long-term demand for hospital beds are required to avoid oversupply or deficits. Though in many cases, forecasts of admissions and Length of Stay evolutions for specific pathologies are available, current models rarely model hospital environments on the pathology level, rendering them useless. Additionally, existing models are most often unit type or facility-dependent. This work describes a model to estimate care demand and capacity needs per ward of a generic hospital, in which pathology-specific parameters can be used, and that supports patient stays structurally segmented across multiple wards. The methodology enables an increase in model complexity while explicitly guarding the accuracy of parameter estimates.

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. Head-to-toe PET/CT examinations and raw data from 64 patients were retrospectively retrieved. PET image reconstruction was carried out twice: once optimized for quantification, complying with EARL accreditation requirements, and once optimized for lesion detection, according to GE's Q.Clear reconstruction settings. RESULTS: The two reconstruction protocols showed different NEMA phantom RC values for different sphere sizes. Q.Clear values were always highest and exceeded the EARL accreditation maximum for smaller spheres. Comparison of liver SULmean showed a statistically significant but clinically irrelevant difference between both protocols. Comparison of lesion SULpeak and SULmax showed a statistically significant, and clinically relevant, difference of 1.64 and 4.57, respectively. CONCLUSIONS: For treatment response assessment using PERCIST criteria, the harmonization reconstruction protocol should be used as the lesion detection reconstruction protocol using resolution recovery systematically overestimates true SUL values. ispartof: EJNMMI PHYSICS vol:5 issue:1 ispartof: location:Germany status: published

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. Thereby, ILK plays important roles in cellular attachment, motility, proliferation and survival. To assess the in vivo role of ILK signaling in osteoprogenitors and the osteoblast lineage cells descending thereof, we generated conditional knockout mice using the Osx-Cre:GFP driver strain. Mice lacking functional ILK in osterix-expressing cells and their derivatives showed no apparent developmental or growth phenotype, but by 5 weeks of age they displayed a significantly reduced trabecular bone mass, which persisted into adulthood in male mice. Histomorphometry and serum analysis indicated no alterations in osteoclast formation and activity, but provided evidence that osteoblast function was impaired, resulting in reduced bone mineralization and increased accumulation of unmineralized osteoid. In vitro analyses further substantiated that absence of ILK in osteogenic cells was associated with compromised collagen matrix production and mineralization. Mechanistically, we found evidence for both impaired cytoskeletal functioning and reduced signal transduction in osteoblasts lacking ILK. Indeed, loss of ILK in primary osteogenic cells impaired F-actin organization, cellular adhesion, spreading, and migration, indicative of defective coupling of cell-matrix interactions to the cytoskeleton. In addition, BMP/Smad and Wnt/β-catenin signaling was reduced in the absence of ILK. Taken together, these data demonstrate the importance of integrin-mediated cell-matrix interactions and ILK signaling in osteoprogenitors in the control of osteoblast functioning during juvenile bone mass acquisition and adult bone remodeling and homeostasis. © 2017 American Society for Bone and Mineral Research.

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). Formula-estimated LBMs were calculated using formulas of James (1976 Research on Obesity: a Report of the DHSS/MRC Group (London: HMSO)) and Janmahasatian et al (2005 Clin. Pharmacokinet. 44 1051-65), and body surface area (BSA) was calculated using the DuBois formula (Dubois and Dubois 1989 Nutrition 5 303-11). The CT segmentation method was validated by comparing total patient body weight (BW) to CT-estimated BW (BWCT). LBMCT was compared to formula-based estimates (LBMJames and LBMJanma). SUVs in two healthy reference tissues, liver and mediastinum, were normalized for the aforementioned parameters and compared to each other in terms of variability and dependence on normalization factors and BW. Comparison of actual BW to BWCT shows a non-significant difference of 0.8 kg. LBMJames estimates are significantly higher than LBMJanma with differences of 4.7 kg for female and 1.0 kg for male patients. Formula-based LBM estimates do not significantly differ from LBMCT, neither for men nor for women. The coefficient of variation (CV) of SUV normalized for LBMJames (SUVLBM-James) (12.3%) was significantly reduced in liver compared to SUVBW (15.4%). All SUV variances in mediastinum were significantly reduced (CVs were 11.1-12.2%) compared to SUVBW (15.5%), except SUVBSA (15.2%). Only SUVBW and SUVLBM-James show independence from normalization factors. LBMJames seems to be the only advantageous SUV normalization. No advantage of other SUV normalizations over BW could be demonstrated.

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.Head-to-toe PET/CT examinations were retrospectively retrieved and semiautomatically segmented into tissue types based on thresholding of CT Hounsfield units. LC was obtained by omitting image slices. Image segmentation was validated on the WB CT examinations by comparing CT-estimated BW with actual BW, and LBM estimated from LC images were compared with LBM estimated from WB images. A direct method and an indirect method were developed and validated on an independent data set.Comparing LBM estimated from LC examinations with estimates from WB examinations (LBMWB) showed a significant but limited bias of 1.2 kg (direct method) and nonsignificant bias of 0.05 kg (indirect method).This study demonstrates that LBM can be estimated from LC CT images with no significant difference from LBMWB.

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.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. Tissue type segmentation in DXA was performed via the standard clinical protocol and in CT through different sets of HU ranges. Percent coefficients of variation (%CV) were used to assess precision while % differences of observed masses were tested against zero using the Wilcoxon signed-rank Test.Total mass DXA measurements differ little but significantly (P=0.016) from true mass, while total mass CT measurements based on literature values show non-significant (P=0.69) differences of 1.7% and 2.0%. BT mass estimates with DXA differed more from true mass (median -78.2 to -75.8%) than other tissue types (median -11.3 to -8.1%). Tissue mass estimates with CT and literature HU ranges showed small differences from true mass for every tissue type (median -10.4 to 8.8%).The most suited method for automated tissue segmentation is CT and can become a valuable tool in quantitative nuclear medicine.

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. In this context, four methods to determine LBM are reviewed: bioelectrical impedance analysis, dual-energy X-ray absorptiometry. CT, and magnetic resonance imaging. These methods were selected based on clinical accessibility and are compared in terms of methodology, precision and accuracy. By assessing each method's specific advantages and limitations, a well-considered choice of method can hopefully lead to more accurate SUVLBM values, hence more accurate quantitative assessment of 18F-FDG PET images.