ライフサイエンスコーパス: SUV

1 SUV cannot be used to quantify (18)F-fluoromethylcholine

2 SUV corrected for lean body mass (SUL and SULpeak) were

3 SUV is, however, associated with multiple sources of var

4 SUV measurements and rate of glucose uptake values were

5 SUV quantification of (18)F-FLT uptake in glioma had an

6 SUV quantification shows notable differences between (18

7 SUV ratios (affected disk/reference disk) were determine

8 SUV ratios (SUVRs) are used for relative quantification

9 SUV ratios (SUVRs) showed a strong correlation in tracer

10 SUV ratios and GM volumes were compared using regional a

11 SUV(max) was not related to plasma VEGF-A at all scan mo

12 SUVs and target-to-background ratios for the symptomatic

13 SUVs and the number of medullar lesions detected by (64)

14 SUVs at 60 min after tracer injection also correlated (r

15 SUVs for any RR were not significantly different over ti

16 SUVs from 60 to 120 min after injection derived from eac

17 at 6 mo (P = 0.014) and 12 mo (P = 0.0005); SUV maximal percentage change from baseline and clinical

18 6 mo (P = 0.0147) and 6-12 mo (P = 0.0053); SUV change at 6 mo and overall survival (P = 0.018); num

19 with regards to AC-CTref: for (18)F-FET (A)-SUVs as well as volumes of interest (VOIs) defined by a

20 positive/ HER2-negative cancers and absolute SUV(max) after two cycles of chemotherapy for HER2-posit

21 In HER2-positive phenotype, absolute SUV(max) (or SUV(peak)) values at PET imaging after two

22 For an acceptable SUV variability, the lowest bias in SUV was observed usi

23 ICC was excellent (>0.95) for all SUV metrics.

24 s 2.18 (IQR 2.00-2.65), and all cases had an SUV(max) greater than 1.6 (the threshold for defining ca

25 robe PET/CT imaging of HCC70 tumors shows an SUV of 0.32 +/- 0.03 for vehicle-, 0.50 +/- 0.01 for GDC

26 e PET/CT imaging of MDAMB468 tumors shows an SUV of 0.35 +/- 0.02 for vehicle- and 0.73 +/- 0.05 for

27 cm(3) were automatically segmented using an SUV threshold of 15 g/mL.

28 old had no significant influence, whereas an SUV threshold of 2.5 proved optimal for automated lesion

29 nstrated only 3 frontal lobe regions with an SUV estimation bias of 5% or greater (P < 0.05).

30 d contrast and slow renal clearance, with an SUV of 14.1 +/- 6.2.

31 0.03%), parametric maps (28.02%-61.45%), and SUV (45.49%-45.63%) segmentation.

32 0.03%), parametric maps (28.02%-61.45%), and SUV (45.49%-45.63%) segmentation.

33 s a strong correlation in size (r= 0.98) and SUV (r= 0.91) and a moderate correlation in contrast (rh

34 -to-blood-pool SUV ratio was 59% higher, and SUV gradient was 51% higher, with good correlation betwe

35 ce tissue model (SRTM), reference Logan, and SUV ratio (SUVr).

36 h compartmental modeling parametric maps and SUV segmentations using simulations of clinically releva

37 ectral clustering (SC), parametric maps, and SUV segmentation.

38 n adaptive template registration method, and SUV ratio 3D-SSP values were computed using the pons and

39 expressing neuroendocrine tumors (NETs), and SUV measurements are suggested for treatment monitoring.

40 onal T1-weighted volumetric MR sequence, and SUV estimations were compared with CT AC for whole-image

41 Standardized uptake values (SUVs) and SUV gradients as a measure of lesion sharpness were obta

42 binding potential ([Formula: see text]) and SUV ratio ([Formula: see text]) images were compared.

43 account for differences in lesion volume and SUV quantification between reconstruction algorithms.

44 sible tumor uptake of (68)Ga-NOTA-AE105, and SUVs were obtained from tumor lesions by manually drawin

45 ts, previous therapies, pain medication, and SUVs were included in the analysis.

46 PET/CT results and SUVs were compared with prognostic factors such as histo

47 bellar concentrations (SUV ratio [SUVR]) and SUVs.

48 tion of (89)Zr-bevacizumab was quantified as SUVs.

49 retest studies have been performed to assess SUV repeatability, although a comparison of reports is c

50 VpeakW) was compared with that of an average SUV computed from the 40 hottest voxels, irrespective of

51 The performance of an average SUV over a 1-mL-volume sphere within an (18)F-FDG-positi

52 lue within a lesion (SUVmax) and the average SUV within a small volume of interest around the site of

53 to-background ratios; for (68)Ga-DOTANOC (B)-SUVs as well as VOIs defined by a 50% threshold for all

54 Target-to-background SUV ratio and percentage myocardial (18)F-forbetaben ret

55 pool and calculation of target-to-background SUV ratio.

56 asurements and thus offers routine LBM-based SUV quantification in PET/MR.

57 Baseline SUV(max) was higher in lymph nodes than in primary tumor

58 Across patients, the correlation between SUV and apparent diffusion coefficient was weak and nons

59 The patient-specific correlation between SUV obtained with both methods was high (R(2) = 0.9980,

60 Relationships between SUV and clinical as well as pathologic features in patie

61 erature suggests that the difference between SUVs measured before and after treatment can be used to

62 Blood SUV was determined as the mean value of a 3-dimensional

63 ically low intrasubject variability in blood SUV and uptake time and the accordingly small deltaCF va

64 SUR compared with TRVSUVVariability in blood SUV and uptake time has been identified as a causal fact

65 antial for the level of variability in blood SUV and uptake time typically observed in the clinical c

66 computed as the ratio of tumor SUV to blood SUV and were uptake time-corrected to 75 min after injec

67 as to investigate whether the tumor-to-blood SUV ratio (SUR) can improve TRV in tracer uptake.

68 STBPET3 as determined by (2 x blood SUV) + (2 x SD) correlated best with STBHP (Pearson rho

69 sed PET/MR images, and IF-to-BM and SF-to-BM SUV ratios were compared using the Student t test.

70 In order to determine the mean normal bone SUV, initially a 1-cm spheric volume of interest (VOI) w

71 The absolute PD of brain SUV and the VT had similar values.

72 Results: The absolute PD of brain SUV and the VT had similar values.

73 se association was found between whole-brain SUV and reported cigarettes per day (P<0.05), but no sig

74 sed bone compartment reduced the whole-brain SUV estimation bias of Dixon-based PET/MR AC by 95% comp

75 CC values were higher for VTs than for brain SUVs, which were both moderate to high; however, lower I

76 kers and non-smokers differed in whole-brain SUVs (P=0.006) owing to smokers having 16.8% lower value

77 r uptake of [(18)F]6b in the olfactory bulb (SUV of 0.34 at 30 min pi) accompanied by a low uptake in

78 ulation in renal allografts as determined by SUVs on PET and diffusion restriction as determined by a

79 of interest were extracted and quantified by SUVs and by 2-tissue-compartment modeling for calculatio

80 or body weight, which were used to calculate SUV.

81 No significant differences in cerebellar SUVs were found among cases with different amounts or ty

82 -LLP2A and (18)F-FDG demonstrated comparable SUV in the prominent lesions in the femur.

83 d two-sample t test was performed to compare SUV(max).

84 We directly compared SUV estimation between MR-based AC and reference CT AC i

85 From the PET data, regional and composite SUV ratios (SUVRs) with and without PVEC were obtained.

86 The variability of computed SUV(BW) between different software packages is substanti

87 -05270430 was fast, with peak concentration (SUVs of 1.5-1.8 in rhesus monkeys) achieved within 7 min

88 with reference to cerebellar concentrations (SUV ratio [SUVR]) and SUVs.

89 Conclusion: SUV quantification of (18)F-FLT uptake in glioma had an

90 Correcting SUV for uptake time improves sensitivity, but algorithm

91 The key secondary objective was to correlate SUV with the proliferation marker Ki-67 at baseline and

92 e relative differences between corresponding SUV measurements obtained on the 2 d.

93 variable (SUV; 14.5 vs 11.2; P = .05), delta SUV (10.3 vs 5.4; P = .02), and relative delta SUV (0.6

94 V (10.3 vs 5.4; P = .02), and relative delta SUV (0.6 vs 0.4; P = .02) were significantly higher in t

95 emoradiotherapy that demonstrates that delta SUV of less than 45% is associated with patients with re

96 analyses, the initial mean SUV, Deltamaximum SUV, and Deltatumor-to-background ratio demonstrated the

97 e the repeatability of (18)F-NaF PET-derived SUV imaging metrics in individual bone lesions from pati

98 significant differences in (18)F-FDG-derived SUVs were observed between different grades (P = 0.38).

99 etrics of minimum SUV and standard deviation SUV.

100 th SUVmax and STB as determined by different SUV cutoffs for (68)Ga-PSMA PET (STBPET1-6).

101 ility and growth using DMPC-NP-SLBs and DMPC-SUVs, with and without BaP, as their sole carbon source.

102 cles (SUVs) or DMPC-NP-SLBs with excess DMPC-SUVs to support colloidal stability, when added to satur

103 d in 20 lung cancer lesions yielded for each SUV metric its mean value, relative measurement error, a

104 Our study evaluates SUVs in benign prostate tissue and malignant, intraprost

105 using SUVpeak Although changes in (18)F-FLT SUV after treatment cannot be directly interpreted as a

106 ificant associations included the following: SUV and prostate-specific antigen percentage change at 6

107 f SUVmax, the repeatability coefficients for SUV, SUVAUC, and SUVTBR were 26% (ICC, 0.95), 31% (ICC,

108 rmined using the Pearson coefficient (r) for SUV and size and the Spearman rank coefficient (rho) for

109 igorous protocol compliance, but in general, SUV is a highly repeatable imaging biomarker that is ide

110 Blood flow was quantified by (15)O-H2O SUV.

111 er a proprietary software tool can harmonize SUV estimation sufficiently to provide consistent respon

112 F +/- TOF data (PSF +/- TOF.EQ) to harmonize SUVs with the OSEM values.

113 F-FIMX uptake into the human brain was high (SUV = 4-6 in the cerebellum), peaked at about 10 min, an

114 of the liver dome and a significantly higher SUV for lung lesions.

115 etween the tip and the area with the highest SUV within the lesion was measured.

116 of the needle to the focus with the highest SUV, as well as the mean difference between the maximum

117 aft function in one subject, whereas hotspot SUV was unchanged in subjects with stable graft function

118 ceptable SUV variability, the lowest bias in SUV was observed using an 8-min acquisition per bed posi

119 PERCIST suggest a threshold of 30% change in SUV to define partial response and progressive disease.

120 re better correlated with PCR than change in SUV(max) (AUC, 0.78; P = .11) or change in TLG (AUC, 0.6

121 ologic response vary by phenotype: change in SUV(max) or TLG are most adequate for TNBCs and ER-posit

122 e number of malignant lesions and changes in SUV on follow-up Na(18)F PET/CT significantly correlate

123 ting for the absence of group differences in SUV and distribution volume (VT) estimated with an arter

124 tion of the fractional paired differences in SUV and SUR.

125 ess than 1.5 cm showed a greater increase in SUV from GeminiTF to DigitalTF than those lesions 1.5 cm

126 ntom and human scans have shown agreement in SUVs and image quality with the reference scanner.

127 ative methods including percentage change in SUVs, lean body mass-corrected (SUL) SULpeak, SULmax, an

128 Changes in SUVs and lesion number were correlated with prostate-spe

129 ind to the numerous lipid packing defects in SUVs.

130 substantial test-retest variability (TRV) in SUVs.

131 Baseline PET imaging parameters, including SUV, proliferative volume, or metabolic tumor volume, di

132 h PET/MRI examinations, lead to inconsistent SUV measurements in serial studies, which may affect the

133 Four of the 5 SLNs exhibited increased SUVs of 12.4-139.0 obtained from PET/CT.

134 int-spread function (PSF) modeling increases SUVs significantly in tumors but only moderately in the

135 uantifying heterogeneity, image intensities (SUVs) are typically resampled into a reduced number of d

136 , simplified methods were evaluated-that is, SUVs and tumor-to-blood ratios (TBR)-for several scan in

137 If uptake time is known, SUV correction methods may raise sensitivity to 87%-95%

138 fied as a causal factor in the TRV in lesion SUV.

139 s thoracic organ motion and increases lesion SUV, detectability, and delineation, thus potentially af

140 sponse assessment, the reliability of lesion SUVs, notably their test-retest stability, thus becomes

141 Lesion quantity, mean and maximum lesional SUV, z score, and percentage of affected bone volume are

142 high (SUV 16), and two 2.7-cm liver lesions (SUV 14).

143 Although not without limitations, SUV has emerged as the predominant metric for tumor quan

144 atients with furosemide presented with lower SUV and radioactivity concentration within the urinary b

145 onfirmed the predictive value of baseline LV SUV for subsequent cardiac abnormalities.

146 In HD patients, LV SUV showed a progressive increase during doxorubicin tre

147 In these subjects, pretherapy LV SUV was markedly lower with respect to the remaining pat

148 Tumor maximal SUV (T-SUVmax) and T-SUVmax-to-mediastinum blood-pool (M

149 d for 18 organs in all patients, and maximum SUV and mean SUV were recorded for all the identified ma

150 The association of risk factors and maximum SUV of (64)Cu-DOTATATE was found driven by body mass ind

151 features (metabolic tumor volume and maximum SUV).

152 s up to 34% for peak SUV and 50% for maximum SUV and mean SUV.

153 The percentage change in maximum SUV (%DeltaSUVmax) between FLT1 and FLT2 and FLT3 was ca

154 ss than 5%; 28 parameters, including maximum SUV, showed variation with a COV in the range of 5%-10%.

155 2 representative lesions, the lesion maximum SUV was 36% higher with DigitalTF than with GeminiTF, le

156 MTV, maximum SUV, and 43 textural features were extracted for each tu

157 The errors in reported maximum SUV ranged from -37.8% to 0% for an isolated voxel with

158 The maximum SUV at the location of the aspirating needle tip was sig

159 l as the mean difference between the maximum SUV in the whole lesion and at the needle tip, was calcu

160 The maximum and mean SUV increase of the PET/CT compared with the PET/trigger

161 ns in all patients, and maximum SUV and mean SUV were recorded for all the identified malignant lesio

162 or peak SUV and 50% for maximum SUV and mean SUV.

163 The highest mean SUV of 0.6 +/- 0.2 was observed at 24 h after injection

164 ng-characteristic analyses, the initial mean SUV, Deltamaximum SUV, and Deltatumor-to-background rati

165 ted brain uptake of [(18)F]6b in mouse (mean SUV of 0.04 at 30 min pi).

166 better predictive value for percentage mean SUV (P = 0.02) and similar prediction for peak SUV (P =

167 were drawn on LV myocardium to quantify mean SUV.

168 ivity level, and errors in the reported mean SUV ranged from -1.6% to 100% for a region with controll

169 ation correction was quantified by measuring SUVs in lung lesions.

170 Median SUV(max) was 2.18 (IQR 2.00-2.65), and all cases had an

171 tumor lesions in 22 patients, with a median SUV(max) (maximum standardized uptake value) of 6.9 (ran

172 in the less commonly used metrics of minimum SUV and standard deviation SUV.

173 calculated as the percentage mean myocardial SUV change between 0 and 5 min and 15 and 20 min after r

174 uptake in the pituitary gland was observed (SUV of 0.7 at 30 min pi).

175 nalyses were conducted for the assessment of SUV variations between PETA and PETBImage artifacts were

176 The association of SUV with DAS28, C-reactive protein, and CD4+CD28- T-cell

177 orrection for uptake time the correlation of SUV measures and TLG between the 60- and 90-min data sig

178 The influence of SUV threshold and Hounsfield unit thresholds was analyze

179 mproved when characterized by SUR instead of SUV.

180 ifacts that may influence the reliability of SUV.

181 The optimum threshold of SUV to discriminate positive and negative lesions for bo

182 Quantitative accuracy of SUVs was clinically acceptable for UTE- and BD-AC for gr

183 with background uptake, the average bias of SUVs in background volumes of interest was 2.4% +/- 2.5%

184 pituitary gland; and for (18)F-FDG (C)-RD of SUVs of the whole brain and 10 anatomic regions segmente

185 elf at 40 min, resulting in several types of SUVs: SUV, SUVAUC, and SUVTBR The test-retest repeatabil

186 R2-positive phenotype, absolute SUV(max) (or SUV(peak)) values at PET imaging after two cycles of che

187 t group differences in pseudoreference VT or SUV, excepting whole-brain VT, which was higher in cLBP

188 Furthermore, ovarian SUVs in young women around the time of ovulation (midcyc

189 Mean ovarian SUVs (3.08 +/- 0.7) were comparable to brain levels and

190 or that converts individual ratios of paired SUVs into corresponding SURs.

191 tative (18)F-fluoromethylcholine parameters (SUV, MTV, and total uptake in the lesion) were approxima

192 V (P = 0.02) and similar prediction for peak SUV (P = 0.04).

193 timates for SFS-RR images up to 34% for peak SUV and 50% for maximum SUV and mean SUV.

194 a change of >/=30% decrease in (18)F-FDG PET SUV given a true decrease of 40%) and specificity (proba

195 ptake were also quantified as target-to-pons SUV ratios in 12 regions of interest (ROIs).

196 lTF than with GeminiTF, lesion-to-blood-pool SUV ratio was 59% higher, and SUV gradient was 51% highe

197 4 h after injection, but tumor-to-blood-pool SUV ratios increased with time after injection (P = 0.04

198 at motile bacteria could successfully propel SUVs and LUVs with a velocity of 28 mum s(-1) and 13 mum

199 A published SUV correction based on local linearity of uptake-time d

200 Quantitative (SUV) analysis of (68)Ga-PSMA PET was not able to discrim

201 (18)F-T807 in gray matter peaked quickly (SUV > 2 at approximately 5 min).

202 correction (AC), and inaccurate radiotracer SUV estimation can limit future PET/MR clinical applicat

203 %CI, 0.97-0.99; Delta = 0.44), and reference SUV (spleen: ICC, 0.81; Delta = 1.10; liver: ICC, 0.79;

204 Regional SUV averaged from 60 to 120 min after injection in brain

205 ake measurements can be reduced by replacing SUV with SUR as the uptake measure.

206 5.6% and 6.6%, respectively, and scan-rescan SUV variations were within +/-20% in 95% of the cases.

207 In a response assessment setting, SUV reductions of more than 25% and increases of more th

208 Lesion size, SUV and characterization correlate strongly between the

209 ith full kinetic analysis than does standard SUV.

210 of SUVAUC was comparable to that of standard SUV.

211 n distribution volume ratio (DVR) and static SUV ratio (SUVR) using the cerebellum as a reference tis

212 of the studies are analyzed using the static SUV ratio (SUVR) approach because of its simplicity.

213 mplementary information compared with static SUV images.

214 Substantial SUV variations were seen mainly for scan-rescan examinat

215 40 min, resulting in several types of SUVs: SUV, SUVAUC, and SUVTBR The test-retest repeatability of

216 t level that, after docking of the templated-SUVs to supported lipid bilayers (SBL), one to two pairs

217 igation of simplified approaches showed that SUV curves normalized to patient weight, and injected tr

218 It has been shown that SUV normalized to the area under the blood activity conc

219 The SUV from target regions (cLBP study, thalamus; ALS study

220 The SUV increase or decrease depended on the type of metal a

221 The SUV of each segment was measured, and median values were

222 The SUV ratio (SUVR) for each RR was calculated by dividing

223 The SUV ratio (SUVR) is widely used for quantification, but

224 injection and image acquisition) affects the SUV measured for tumors in (18)F-FDG PET images.

225 thods were evaluated: (1) R(D), dividing the SUV range into D equally spaced bins, where the intensit

226 efining an appropriate 20-min window for the SUV ratio (SUVR).

227 The clinical data showed an increase in the SUV estimates for SFS-RR images up to 34% for peak SUV a

228 tation of the PET/CT scan and influences the SUV.

229 ng parameters were assessed by measuring the SUV and coefficient of variation in different regions (a

230 subjects with elevated 95% percentile of the SUV (SUV95) were more likely to develop symptomatic RP (

231 reflect treatment effects than those of the SUV, and accordingly there is a need to compute parametr

232 35), which was significantly higher than the SUV, 2.7 (interquartile range, 1.6-3.8), of the thyroid

233 t was a standardized static uptake time (the SUV from 60 to 65 min was selected for all scans), the s

234 The best repeatability was found using the SUV metrics of the averaged PERCIST target lesions (repe

235 y, precentral gyrus) was normalized with the SUV from candidate pseudoreference regions (i.e., occipi

236 BtPI-PLC interactions with the SUV surface are transient with a lifetime of 379 +/- 49

237 The SUVs of a 49-y-old male HAB and MAB were 1.03 +/- 0.14 a

238 The SUVs of the detected lesions with PSF were substantially

239 We compared the SUVs of the PET image obtained after attenuation correct

240 static imaging protocol for determining the SUVs can be applied to assess ERbeta levels.

241 minimum, mean, and standard deviation of the SUVs for each ROI.

242 Comparison of the SUVs showed that (S)-[(18)F]FAMPe had higher tumor to br

243 .3-cm subcutaneous nodule in the left thigh (SUV 16), and two 2.7-cm liver lesions (SUV 14).

244 LINDE to blood cells and peripheral tissues, SUV is not a sufficient surrogate of VT from 2-tissue-co

245 UR by an RTRV factor of 0.9 in comparison to SUV.

246 the reduction in the TRV in SUR relative to SUV.

247 ty coefficients (RCs) of the log-transformed SUV differences.

248 ion in chromaffin cells nor Ca(2+)-triggered SUV-GUV fusion was restored by the Syt1 mutants.

249 High baseline tumor SUV(max) was associated with longer time to progression.

250 erferon-alpha induced a mean change in tumor SUV(max) of -47.0% (range, -84.7 to +20.0%; P < 0.0001)

251 The maximum tumor SUV ranged from no to minimal uptake in 3 patients to a

252 SURs were computed as the ratio of tumor SUV to blood SUV and were uptake time-corrected to 75 mi

253 ed with careful attention to protocol, tumor SUV has a within-subject coefficient of variation of app

254 Normalizing the tumor SUV data with reference to a background region improved

255 re subjectively expected to affect the tumor SUV.

256 Tumor SUVs and related parameters were measured at a central l

257 Results: RCs for tumor SUVs were 22.5% (SUVmean_30%), 23.8% (SUVmean_gradient),

258 RCs for tumor SUVs were 22.5% (SUVmean_30%), 23.8% (SUVmean_gradient),

259 th dissimilar uptake times, changes in tumor SUVs will be under- or overestimated.

260 ; however, (18)F-FETrp showed higher tumoral SUV than (11)C-AMT in all 3 tumor types tested.

261 The biodistribution and tumoral SUVs for both tracers were compared.

262 nkey revealed moderate initial brain uptake (SUV, 1.9 at 1 min after injection) with a rapid washout.

263 rats revealed moderate initial brain uptake (SUV, approximately 1.5 at 1 min after injection) and rap

264 ll measures of carotid artery/plaque uptake (SUV) and greater than 0.6 in almost all measures of targ

265 mors showed focal (89)Zr-bevacizumab uptake (SUVs at 144 h after injection were 1.0-6.7), whereas no

266 iple sources of variability, and to best use SUV for response assessment, an understanding of the rep

267 FDG uptake and diffusion were measured using SUV and apparent diffusion coefficient, and correlation

268 5-point score) or semiquantitatively (using SUV and DeltaSUV) predicted both PFS and OS (P < 0.01 fo

269 Tracer uptake was quantified using SUVs.

270 ruction using the standardized uptake value (SUV) and the metabolic volume as metrics for quantificat

271 ine profiles, and standardized uptake value (SUV) in focally avid lesions.

272 miscalculation of standardized uptake value (SUV) in PET images can be caused by inappropriate attenu

273 Change in hotspot standardized uptake value (SUV) predicted loss of graft function in one subject, wh

274 24-mo florbetapir standardized uptake value (SUV) ratio (SUVR) changes; to relate those changes to 24

275 The blood standardized uptake value (SUV) was determined by manually delineating the aorta in

276 methods, such as standardized uptake value (SUV), was assessed.

277 (6 x 5 cm with a standardized uptake value [SUV] of 14), a 1.3-cm subcutaneous nodule in the left th

278 form of maximum standardized uptake values (SUV(max)) and uptake volumes before and after treatment

279 The maximum standardised uptake values (SUV(max)) were measured in the plaque area.

280 re obtained, and standardized uptake values (SUV) were calculated for major organs including brain, h

281 Standardized uptake values (SUVs) and SUV gradients as a measure of lesion sharpness

282 ivity curves and standardized uptake values (SUVs) between 60 and 90 min.

283 Standardized uptake values (SUVs) from the 2 devices were compared using linear corr

284 early change in standardized uptake values (SUVs) of 3'deoxy-3'-(18)F-fluorothymidine ((18)F-FLT) us

285 maximum and mean standardized uptake values (SUVs) were calculated in 5 arterial segments.

286 Whole-brain standardized uptake values (SUVs) were determined, and analysis of variance was perf

287 The mean standardized uptake values (SUVs) were recorded for 18 organs in all patients, and m

288 The mean prestandardized uptake variable (SUV; 14.5 vs 11.2; P = .05), delta SUV (10.3 vs 5.4; P =

289 Small unilamellar lipid vesicles (SUVs) that contained the v-SNARE Synaptobrevin2 and Syt1

290 L-serine] (DOPS) small unilamellar vesicles (SUVs) dramatically enhances the aggregation rate of alph

291 C in the form of small unilamellar vesicles (SUVs) or DMPC-NP-SLBs with excess DMPC-SUVs to support c

292 mall, large, and giant unilamellar vesicles (SUVs, LUVs, and GUVs).

293 The most common reasons for failure were SUV outside specifications, incomplete submission, and u

294 ion, we have established ranges beyond which SUV differences are likely due to legitimate biologic ef

295 arameters derived from kinetic analysis with SUV ratio (SUVR) calculated over different imaging time

296 There was a significant association with SUV(max) and C-reactive protein (r=0.58, p=0.04) and qua

297 Compared with SUV, the 3-tissue model adds information about kinetics

298 Absolute AFP values did not correlate with SUV parameters (P = 0.055).

299 tatic scans as the percentage of voxels with SUVs more than 3 SDs from the mean values obtained for s

300 In most published work, SUV has been used for this purpose.