57 research outputs found
Motion artifacts in kidney stone imaging using single-source and dual-source dual-energy CT scanners: a phantom study
PURPOSE:
Dual-energy computed tomography (DECT) has shown the capability of differentiating uric acid (UA) from non-UA stones with 90-100% accuracy. With the invention of dual-source (DS) scanners, both low- and high-energy images are acquired simultaneously. However, DECT can also be performed by sequential acquisition of both images on single-source (SS) scanners. The objective of this study is to investigate the effects of motion artifacts on stone classification using both SS-DECT and DS-DECT.
METHODS:
114 kidney stones of different types and sizes were imaged on both DS-DECT and SS-DECT scanners with tube voltages of 80 and 140 kVp with and without induced motion. Postprocessing was conducted to create material-specific images from corresponding low- and high-energy images. The dual-energy ratio (DER) and stone material were determined and compared among different scans.
RESULTS:
For the motionless scans, all stones were correctly classified with SS-DECT, while two cystine stones were misclassified with DS-DECT. When motion was induced, 94% of the stones were misclassified with SS-DECT versus 11% with DS-DECT (P < 0.0001). Stone size was not a factor in stone misclassification under motion. Stone type was not a factor in stone misclassification under motion with SS-DECT, although with DS-DECT, cystine showed higher number of stone misclassification.
CONCLUSIONS:
Motion artifacts could result in stone misclassification in DECT. This effect is more pronounced in SS-DECT versus DS-DECT, especially if stones of different types lie in close proximity to each other. Further, possible misinterpretation of the number of stones (i.e., missing one, or thinking that there are two) in DS-DECT could be a potentially significant problem
Detection of different kidney stone types: an ex vivo comparison of ultrashort echo time MRI to reference standard CT
BACKGROUND AND PURPOSE:
With the development of ultrashort echo time (UTE) sequences, it may now be possible to detect kidney stones by using magnetic resonance imaging (MRI). In this study, kidney stones of varying composition and sizes were imaged using both UTE MRI as well as the reference standard of computed tomography (CT), with different surrounding materials and scan setups.
METHODS:
One hundred and fourteen kidney stones were inserted into agarose and urine phantoms and imaged both on a dual-energy CT (DECT) scanner using a standard renal stone imaging protocol and on an MRI scanner using the UTE sequence with both head and body surface coils. A subset of the stones representing all composition types and sizes was then inserted into the collecting system of porcine kidneys and imaged in vitro with both CT and MRI.
RESULTS:
All of the stones were visible on both CT and MRI imaging. DECT was capable of differentiating between uric acid and nonuric acid stones. In MRI imaging, the choice of coil and large field of view (FOV) did not affect stone detection or image quality. The MRI images showed good visualization of the stones' shapes, and the stones' dimensions measured from MRI were in good agreement with the actual values (R(2)=0.886, 0.895, and 0.81 in the agarose phantom, urine phantom, and pig kidneys, respectively). The measured T2 relaxation times ranged from 4.2 to 7.5ms, but did not show significant differences among different stone composition types.
CONCLUSIONS:
UTE MRI compared favorably with the reference standard CT for imaging stones of different composition types and sizes using body surface coil and large FOV, which suggests potential usefulness of UTE MRI in imaging kidney stones in vivo
Detection of a CMB decrement towards a cluster of mJy radiosources
We present the results of radio, optical and near-infrared observations of
the field of TOC J0233.3+3021, a cluster of milliJansky radiosources from the
TexOx Cluster survey. In an observation of this field with the Ryle Telescope
(RT) at 15 GHz, we measure a decrement in the cosmic microwave background (CMB)
of Jy on the RT's 0.65 k baseline. Using
optical and infrared imaging with the McDonald 2.7-m Smith Reflector, Calar
Alto 3.5-m telescope and UKIRT, we identify the host galaxies of five of the
radiosources and measure magnitudes of , , .
The CMB decrement is consistent with the Sunyaev-Zel'dovich (SZ) effect of a
massive cluster of galaxies, which if modelled as a spherical King profile of
core radius has a central temperature decrement
of K. The magnitudes and colours of the galaxies are consistent with
those of old ellipticals at . We therefore conclude that TOC
J0233.3+3021 is a massive, high redshift cluster. These observations add to the
growing evidence for a significant population of massive clusters at high
redshift, and demonstrate the effectiveness of combining searches for AGN
`signposts' to clusters with the redshift-independence of the SZ effect.Comment: Six pages; accepted for publication in MNRAS. Version with
full-resolution UV plot available from
http://www.mrao.cam.ac.uk/~garret/MB185.p
Mapping of the SZ effect in the cluster Cl 0016+16 with the Ryle Telescope
We have mapped the high-redshift (z = 0.546) cluster Cl 0016+16 with the Ryle
Telescope at 15 GHz. The Sunyaev-Zel'dovich decrement is clearly detected, and
resolved. We combine our data with an X-ray image from ROSAT, and a gas
temperature from ASCA to estimate the Hubble Constant H0 = 69 +21/-16 km/s/Mpc
for an Omega_M=1.0 cosmology or H0 = 84 +25/-19 km/s/Mpc for Omega_M=0.3 and
Omega_Lambda=0.7.Comment: 10 pages, 2 tables, 6 figures Submitted to MNRA
Physiogenomic analysis of weight loss induced by dietary carbohydrate restriction
BACKGROUND: Diets that restrict carbohydrate (CHO) have proven to be a successful dietary treatment of obesity for many people, but the degree of weight loss varies across individuals. The extent to which genetic factors associate with the magnitude of weight loss induced by CHO restriction is unknown. We examined associations among polymorphisms in candidate genes and weight loss in order to understand the physiological factors influencing body weight responses to CHO restriction. METHODS: We screened for genetic associations with weight loss in 86 healthy adults who were instructed to restrict CHO to a level that induced a small level of ketosis (CHO ~10% of total energy). A total of 27 single nucleotide polymorphisms (SNPs) were selected from 15 candidate genes involved in fat digestion/metabolism, intracellular glucose metabolism, lipoprotein remodeling, and appetite regulation. Multiple linear regression was used to rank the SNPs according to probability of association, and the most significant associations were analyzed in greater detail. RESULTS: Mean weight loss was 6.4 kg. SNPs in the gastric lipase (LIPF), hepatic glycogen synthase (GYS2), cholesteryl ester transfer protein (CETP) and galanin (GAL) genes were significantly associated with weight loss. CONCLUSION: A strong association between weight loss induced by dietary CHO restriction and variability in genes regulating fat digestion, hepatic glucose metabolism, intravascular lipoprotein remodeling, and appetite were detected. These discoveries could provide clues to important physiologic adaptations underlying the body mass response to CHO restriction
Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes.
Although several lung cancer susceptibility loci have been identified, much of the heritability for lung cancer remains unexplained. Here 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated genome-wide association study (GWAS) analysis of lung cancer in 29,266 cases and 56,450 controls. We identified 18 susceptibility loci achieving genome-wide significance, including 10 new loci. The new loci highlight the striking heterogeneity in genetic susceptibility across the histological subtypes of lung cancer, with four loci associated with lung cancer overall and six loci associated with lung adenocarcinoma. Gene expression quantitative trait locus (eQTL) analysis in 1,425 normal lung tissue samples highlights RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer
No evidence that protein truncating variants in BRIP1 are associated with breast cancer risk: implications for gene panel testing.
BACKGROUND: BRCA1 interacting protein C-terminal helicase 1 (BRIP1) is one of the Fanconi Anaemia Complementation (FANC) group family of DNA repair proteins. Biallelic mutations in BRIP1 are responsible for FANC group J, and previous studies have also suggested that rare protein truncating variants in BRIP1 are associated with an increased risk of breast cancer. These studies have led to inclusion of BRIP1 on targeted sequencing panels for breast cancer risk prediction. METHODS: We evaluated a truncating variant, p.Arg798Ter (rs137852986), and 10 missense variants of BRIP1, in 48 144 cases and 43 607 controls of European origin, drawn from 41 studies participating in the Breast Cancer Association Consortium (BCAC). Additionally, we sequenced the coding regions of BRIP1 in 13 213 cases and 5242 controls from the UK, 1313 cases and 1123 controls from three population-based studies as part of the Breast Cancer Family Registry, and 1853 familial cases and 2001 controls from Australia. RESULTS: The rare truncating allele of rs137852986 was observed in 23 cases and 18 controls in Europeans in BCAC (OR 1.09, 95% CI 0.58 to 2.03, p=0.79). Truncating variants were found in the sequencing studies in 34 cases (0.21%) and 19 controls (0.23%) (combined OR 0.90, 95% CI 0.48 to 1.70, p=0.75). CONCLUSIONS: These results suggest that truncating variants in BRIP1, and in particular p.Arg798Ter, are not associated with a substantial increase in breast cancer risk. Such observations have important implications for the reporting of results from breast cancer screening panels.The COGS project is funded through a European Commission's Seventh Framework Programme grant
(agreement number 223175 - HEALTH-F2-2009-223175). BCAC is funded by Cancer Research UK
[C1287/A10118, C1287/A12014] and by the European Community´s Seventh Framework Programme under
grant agreement number 223175 (grant number HEALTH-F2-2009-223175) (COGS). Funding for the iCOGS
infrastructure came from: the European Community's Seventh Framework Programme under grant agreement
n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710,
C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, C8197/A16565), the
National Institutes of Health (CA128978) and Post-Cancer GWAS initiative (1U19 CA148537, 1U19
16
CA148065 and 1U19 CA148112 - the GAME-ON initiative), the Department of Defense (W81XWH-10-1-
0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast
Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer
Research Fund. This study made use of data generated by the Wellcome Trust Case Control consortium.
Funding for the project was provided by the Wellcome Trust under award 076113. The results published here
are in part based upon data generated by The Cancer Genome Atlas Project established by the National Cancer
Institute and National Human Genome Research Institute.This is the author accepted manuscript. The final version is available from BMJ Group at http://dx.doi.org/10.1136/jmedgenet-2015-103529
Breast cancer risk variants at 6q25 display different phenotype associations and regulate ESR1, RMND1 and CCDC170.
We analyzed 3,872 common genetic variants across the ESR1 locus (encoding estrogen receptor α) in 118,816 subjects from three international consortia. We found evidence for at least five independent causal variants, each associated with different phenotype sets, including estrogen receptor (ER(+) or ER(-)) and human ERBB2 (HER2(+) or HER2(-)) tumor subtypes, mammographic density and tumor grade. The best candidate causal variants for ER(-) tumors lie in four separate enhancer elements, and their risk alleles reduce expression of ESR1, RMND1 and CCDC170, whereas the risk alleles of the strongest candidates for the remaining independent causal variant disrupt a silencer element and putatively increase ESR1 and RMND1 expression.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ng.352
Axiomatic Choice Theory Traveling between Mathematical Formalism, Normative Choice Rules and Psychological Measurement, 1944-1956
Cell-type–specific eQTL of primary melanocytes facilitates identification of melanoma susceptibility genes
Most expression quantitative trait locus (eQTL) studies to date have been performed in heterogeneous tissues as opposed to specific cell types. To better understand the cell-type–specific regulatory landscape of human melanocytes, which give rise to melanoma but account for <5% of typical human skin biopsies, we performed an eQTL analysis in primary melanocyte cultures from 106 newborn males. We identified 597,335 cis-eQTL SNPs prior to linkage disequilibrium (LD) pruning and 4997 eGenes (FDR < 0.05). Melanocyte eQTLs differed considerably from those identified in the 44 GTEx tissue types, including skin. Over a third of melanocyte eGenes, including key genes in melanin synthesis pathways, were unique to melanocytes compared to those of GTEx skin tissues or TCGA melanomas. The melanocyte data set also identified trans-eQTLs, including those connecting a pigmentation-associated functional SNP with four genes, likely through cis-regulation of IRF4. Melanocyte eQTLs are enriched in cis-regulatory signatures found in melanocytes as well as in melanoma-associated variants identified through genome-wide association studies. Melanocyte eQTLs also colocalized with melanoma GWAS variants in five known loci. Finally, a transcriptome-wide association study using melanocyte eQTLs uncovered four novel susceptibility loci, where imputed expression levels of five genes (ZFP90, HEBP1, MSC, CBWD1, and RP11-383H13.1) were associated with melanoma at genome-wide significant P-values. Our data highlight the utility of lineage-specific eQTL resources for annotating GWAS findings, and present a robust database for genomic research of melanoma risk and melanocyte biology
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