Head and neck target delineation using a novel PET automatic segmentation algorithm

Purpose To evaluate the feasibility and impact of using a novel advanced PET auto-segmentation method in Head and Neck (H&N) radiotherapy treatment (RT) planning. Methods ATLAAS, Automatic decision Tree-based Learning Algorithm for Advanced Segmentation, previously developed and validated on pre-clinical data, was applied to 18F-FDG-PET/CT scans of 20 H&N patients undergoing Intensity Modulated Radiation Therapy. Primary Gross Tumour Volumes (GTVs) manually delineated on CT/MRI scans (GTVpCT/MRI), together with ATLAAS-generated contours (GTVpATLAAS) were used to derive the RT planning GTV (GTVpfinal). ATLAAS outlines were compared to CT/MRI and final GTVs qualitatively and quantitatively using a conformity metric. Results The ATLAAS contours were found to be reliable and useful. The volume of GTVpATLAAS was smaller than GTVpCT/MRI in 70% of the cases, with an average conformity index of 0.70. The information provided by ATLAAS was used to grow the GTVpCT/MRI in 10 cases (up to 10.6 mL) and to shrink the GTVpCT/MRI in 7 cases (up to 12.3 mL). ATLAAS provided complementary information to CT/MRI and GTVpATLAAS contributed to up to 33% of the final GTV volume across the patient cohort. Conclusions ATLAAS can deliver operator independent PET segmentation to augment clinical outlining using CT and MRI and could have utility in future clinical studies

Determinants of physiological uptake of 18F-fluorodeoxyglucose in palatine tonsils

To determine the extent of physiological variation of uptake of 18F-flurodeoxyglucose (FDG) within palatine tonsils. To define normal limits for side-to-side variation and characterize factors affecting tonsillar uptake of FDG.Over a period of 16 weeks 299 adult patients at low risk for head and neck pathology, attending our center for FDG positron emission tomography/computed tomography (PET/CT) scans were identified. The maximum standardized uptake value (SUVmax) was recorded for each palatine tonsil. For each patient age, gender, smoking status, scan indication and prior tonsillectomy status as well as weather conditions were noted.There was a wide variation in palatine tonsil FDG uptake with SUVmax values between 1.3 and 11.4 recorded. There was a strong left to right correlation for tonsillar FDG uptake within each patient (P < .01). The right palatine tonsil showed increased FDG uptake (4.63) compared to the left (4.47) (P < .01). In multivariate analysis, gender, scan indication, and prevailing weather had no significant impact of tonsillar FDG uptake. Lower tonsillar uptake was seen in patients with a prior history of tonsillectomy (4.13) than those without this history (4.64) (P < .01). Decreasing tonsillar FDG uptake was seen with advancing age (P < .01). Significantly lower uptake was seen in current smokers (SUVmax 4.2) than nonsmokers (SUV 4.9) (P = .03).Uptake of FDG in palatine tonsils is variable but shows a strong side-to-side correlation. We suggest the left/ right SUVmax ratio as a guide to normality with a first to 99th percentiles of (0.70–1.36) for use in patients not suspected to have tonsillar pathology

Machine-learned target volume delineation of 18F-FDG PET images after one cycle of induction chemotherapy

Biological tumour volume (GTVPET) delineation on 18F-FDG PET acquired during induction chemotherapy (ICT) is challenging due to the reduced metabolic uptake and volume of the GTVPET. Automatic segmentation algorithms applied to 18F-FDG PET (PET-AS) imaging have been used for GTVPET delineation on 18F-FDG PET imaging acquired before ICT. However, their role has not been investigated in 18F-FDG PET imaging acquired after ICT. In this study we investigate PET-AS techniques, including ATLAAS a machine learned method, for accurate delineation of the GTVPET after ICT. Twenty patients were enrolled onto a prospective phase I study (FiGaRO). PET/CT imaging was acquired at baseline and 3 weeks following 1 cycle of induction chemotherapy. The GTVPET was manually delineated by a nuclear medicine physician and clinical oncologist. The resulting GTVPET was used as the reference contour. The ATLAAS original statistical model was expanded to include images of reduced metabolic activity and the ATLAAS algorithm was re-trained on the new reference dataset. Estimated GTVPET contours were derived using sixteen PET-AS methods and compared to the GTVPET using the Dice Similarity Coefficient (DSC). The mean DSC for ATLAAS, 60% Peak Thresholding (PT60), Adaptive Thresholding (AT) and Watershed Thresholding (WT) was 0.72, 0.61, 0.63 and 0.60 respectively. The GTVPET generated by ATLAAS compared favourably with manually delineated volumes and in comparison, to other PET-AS methods, was more accurate for GTVPET delineation after ICT. ATLAAS would be a feasible method to reduce inter-observer variability in multi-centre trials

Ursolic acid and luteolin-7-glucoside improves rat plasma lipid profile and increases liver glycogen content through glycogen synthase kinase-3

In the present study, two phytochemicals - ursolic acid (UA) and luteolin-7-glucoside (L7G) - were assessed in vivo in healthy rats regarding effects on plasma glucose and lipid profile (total cholesterol, HDL and LDL), as well as liver glycogen content, in view of their importance in the aetiology of diabetes and associated complications. Both UA and L7G significantly decreased plasma glucose concentration. UA also significantly increased liver glycogen levels accompanied by phosphorylation of glycogen synthase kinase-3 (GSK3). The increase in glycogen deposition induced by UA (mediated by GSK3) could have contributed to the lower plasma glucose levels observed. Both compounds significantly lowered total plasma cholesterol and low-density lipoprotein levels, and, in addition, UA increased plasma high-density lipoprotein levels. Our results show that UA particularly may be useful in preventable strategies for people at risk of developing diabetes and associated cardiovascular complications by improving plasma glucose levels and lipid profile, as well as by promoting liver glycogen deposition.MFA and CMS were supported by the Foundation for Science and Technology, Portugal, through the grants SFRH/BD/12527/2003 and SFRH/BD/42566/2007, respectively. This work was supported by the Foundation for Science and Technology, Portugal, research grant POCI/AGR/62040/2004

Inhibitory Activities of Cyanidin and Its Glycosides and Synergistic Effect with Acarbose against Intestinal α-Glucosidase and Pancreatic α-Amylase

Cyanidin and its glycosides are naturally dietary pigments which have been indicated as promising candidates to have potential benefits to humans, especially in the prevention and treatment of diabetes mellitus. We investigated the structure activity relationships of cyanidin and its glycosides to inhibit intestinal α-glucosidases and pancreatic α-amylase in vitro. The results found that cyanidin and its glycosides are more specific inhibitors of intestinal sucrase than intestinal maltase. Cyanidin-3-galactoside and cyanidin-3-glucoside were the most potent inhibitors against intestinal sucrase and pancreatic α-amylase with IC50 values of 0.50 ± 0.05 and 0.30 ± 0.01 mM, respectively. Our findings indicate that the structural difference between glucose and galactose at the 3-O-position of cyanidin was an important factor for modulating the inhibition of intestinal sucrase and pancreatic α-amylase. The combination of cyandin-3-glucoside, cyanidin-3- galactoside or cyanidin-3,5-diglucosides with a low concentration of acarbose showed synergistic inhibition on intestinal maltase and sucrase. The synergistic inhibition was also found for a combination of cyanidin or cyanidin-3-glucoside with a low concentration of acarbose. The findings could provide a new insight into a use for the naturally occurring intestinal α-glucosidase and pancreatic α-amylase inhibitors for the prevention and treatment of diabetes and its complications

On the microstructure and tensile behaviour of nanostructured NiTi alloy produced by electroplastic rolling

Electroplastic rolling was employed to produce nanostructured (NS), near-equiatomic NiTi alloy from a coarse grained NiTi nugget (ingot), which was produced using vacuum induction melting, followed by quenching in water from a temperature of 800°C. The microstructure of NS NiTi was characterized using X-ray Diffraction (XRD) and transmission electron microscopy (TEM). XRD analysis revealed that the NS NiTi is predominantly martensitic at room temperature, with less than ≈10 % of the austenite phase. The NS NiTi alloy has an average grain size of ≈36 nm. TEM investigation confirmed the presence of grains that are less than 10 nm in size and no amorphous zones were detected. The NS martensitic NiTi alloy specimens were tested in tension at two different strain rates (10−2 and 10−1 s−1). In contrast to a stress-strain profile expected in a martensitic NiTi alloy, the stress-strain curves show conventional tensile behaviour. The observed UTS was high, around ≈1800 MPa, with a less than usual elongation to failure of ≈6 %. The presence of dimples on the fracture surfaces can be seen in scanning electron microscopy (SEM) images, which is indicative of ductile fracture. The role of grain size in the observed deformation and fracture features is also discussed