ライフサイエンスコーパス: diffusion tensor imaging

1 s of apathy, depression, quality of life and diffusion tensor imaging.

2 nalyses included voxel-based morphometry and diffusion tensor imaging.

3 s throughout the brain were obtained through diffusion tensor imaging.

4 sis of fractional anisotropy (FA) in newborn diffusion tensor imaging.

5 ractional anisotropy values, as derived from diffusion tensor imaging.

6 ubjects underwent volumetric T1-weighted and diffusion tensor imaging.

7 linical control subjects were assessed using diffusion tensor imaging.

8 l imaging and fibre tracking with the use of diffusion tensor imaging.

9 f traumatic axonal injury as demonstrated by diffusion tensor imaging.

10 statistics analysis of indices derived from diffusion tensor imaging.

11 identifiable at a single subject level with diffusion tensor imaging.

12 y fractional anisotropy values obtained from diffusion tensor imaging.

13 sured with high-resolution T(1)-weighted and diffusion tensor imaging.

14 on and magnetic resonance imaging, including diffusion tensor imaging.

15 ed functional magnetic resonance imaging and diffusion tensor imaging.

16 ing technique and mean diffusivity (MD) from diffusion tensor imaging.

17 underwent 3T whole brain magnetic resonance diffusion tensor imaging.

18 ructural integrity that were estimated using diffusion tensor imaging.

19 (ACC) to the medial temporal lobe (MTL) with diffusion tensor imaging.

20 nations of white-matter tracts identified by diffusion tensor imaging.

21 g resting-state functional MRI (rs-fMRI) and diffusion tensor imaging.

22 dex measurement of the corpus callosum using diffusion tensor imaging.

23 Diffusion tensor imaging, a translational imaging techni

24 hip among presurgical cognitive performance, diffusion tensor imaging abnormalities and postoperative

25 aumatic brain injury was not associated with diffusion tensor imaging abnormalities detectable with t

26 Diffusion tensor imaging abnormalities in a cohort of 97

27 While the diffusion tensor imaging abnormalities observed in the c

28 ntrolling for general cognitive performance, diffusion tensor imaging abnormalities of the cerebellum

29 Presurgical diffusion tensor imaging abnormalities of the cerebellum

30 matter and white matter atrophy, as well as diffusion-tensor imaging abnormalities (P < .01).

31 However, diffusion tensor imaging alone cannot currently pinpoint

32 Diffusion tensor imaging analysis revealed a significant

33 The diffusion tensor imaging analysis revealed that fraction

34 reas of white matter loss were observed with diffusion tensor imaging analysis, which also demonstrat

35 assessments, and magnetic resonance imaging, diffusion tensor imaging and (18)F-fluorodeoxyglucose po

36 be seizures in temporal lobe epilepsy, using diffusion tensor imaging and automated fibre quantificat

37 Structural networks based on diffusion tensor imaging and cortical thickness were ana

38 Diffusion tensor imaging and fluorescence microscopy stu

39 structural connectivity (SC) as measured by diffusion tensor imaging and frontoparietal functional c

40 More generally, a number of correlations of diffusion tensor imaging and functional connectivity mag

41 also can change white matter as measured by diffusion tensor imaging and increase resting-state midl

42 e to tissue microstructural changes, such as diffusion tensor imaging and magnetization transfer imag

43 haemic changes, all of which can affect both diffusion tensor imaging and magnetization transfer imag

44 roimaging methods-surface-based morphometry, diffusion tensor imaging and network-based statistics-ea

45 Here, we utilize quantitative techniques of diffusion tensor imaging and neurite orientation dispers

46 opontine nucleus structural connectivity via diffusion tensor imaging and performance on cognitive te

47 Structural diffusion tensor imaging and resting-state functional ma

48 (n = 12; age and sex matched), we performed diffusion tensor imaging and structural MRI, polysomnogr

49 e and hippocampal volume were assessed using diffusion tensor imaging and structural MRI, respectivel

50 , anatomical connectivity was examined using diffusion tensor imaging and tract-based spatial statist

51 Diffusion tensor imaging and transverse relaxation time

52 Sixty-direction diffusion-tensor imaging and magnetization-prepared rapi

53 Diffusion-tensor imaging and serial neurocognitive testi

54 Ex vivo diffusion-tensor imaging and TBSS were used to compare C

55 Diffusion-tensor imaging and tract-based spatial statist

56 operties and second-language immersion using diffusion tensor imaging, and (ii) to determine whether

57 connectivity, analysis of white matter using diffusion tensor imaging, and analysis of gray matter us

58 ed networks was probed using high-resolution diffusion tensor imaging, and cellular/regional activati

59 and the medial lemniscus was performed with diffusion tensor imaging, and lesions were classified by

60 of these conditions--in single subjects with diffusion tensor imaging appears to have strong diagnost

61 However, data based primarily on diffusion tensor imaging approaches remain inconclusive.

62 ural MRI, resting--state functional MRI, and diffusion tensor imaging--are highly sensitive to common

63 al connectivity abnormalities, measured with diffusion tensor imaging, as well as the convergent impa

64 microstructural organization using neonatal diffusion tensor imaging, associated with skills importa

65 e-matched healthy control subjects underwent diffusion-tensor imaging at baseline and after a mean fo

66 te matter tract degeneration was assessed on diffusion-tensor imaging at each time-point.

67 We assessed white matter integrity with diffusion tensor imaging-based axial and radial diffusiv

68 ine, neuropsychological, retinal vessel, and diffusion tensor imaging-based cerebral WM evaluations.

69 A high amyloid load does not influence diffusion tensor imaging-based measures of white matter

70 Magnetic resonance imaging (T1-weighted and diffusion tensor imaging-based structural connectome), a

71 a white matter diffusion profile by means of diffusion-tensor imaging-based parameters and constraine

72 in microstructural integrity, as measured by diffusion tensor imaging before surgery, on postoperativ

73 For diffusion tensor imaging, brains were scanned with a dif

74 y and microstructural brain development with diffusion tensor imaging by measuring fractional anisotr

75 However, both clinical and DTI diffusion-tensor imaging changes did not persist beyond

76 opological centrality of nodes in the normal diffusion tensor imaging connectome were generally repli

77 RI (85% sensitivity, 83% specificity) and on diffusion tensor imaging data (88% sensitivity, 92% spec

78 We analyzed diffusion tensor imaging data from 35 patients and 35 he

79 of brain anatomical networks estimated from diffusion tensor imaging data on healthy volunteers (n =

80 Diffusion tensor imaging data were acquired in 63 patien

81 te functional magnetic resonance imaging and diffusion tensor imaging data were acquired.

82 ng and functional magnetic resonance imaging/diffusion tensor imaging data, we also find that variabi

83 tivity matrices calculated from skeletonized diffusion tensor imaging data.

84 lus, as measured by tract-based analysis for diffusion-tensor imaging data.

85 Here, analysing a publicly shared diffusion tensor imaging dataset, we found that, during

86 aging scanner to acquire T1-weighted images, diffusion tensor imaging datasets, and single volume dif

87 We used diffusion tensor imaging derived fractional anisotropy (

88 ility through specialized techniques such as diffusion-tensor imaging, diffusion-weighted (DW) imagin

89 Integrating the biologically realistic diffusion tensor imaging/diffusion spectrum imaging-base

90 e events result in disrupted white matter on diffusion tensor imaging (DT) scans.

91 Diffusion tensor imaging (DTI) allowed us to relate pote

92 tter structure and function were assessed by diffusion tensor imaging (DTI) and (1)H magnetic resonan

93 of the uncinate fasciculus (UF) measured by Diffusion Tensor Imaging (DTI) and anxiety symptoms in a

94 ify a PD-specific MRI pattern using combined diffusion tensor imaging (DTI) and arterial spin labelin

95 actional anisotropy (FA) measure provided by diffusion tensor imaging (DTI) and cross-hemispheric com

96 etest reliability of high spatial resolution diffusion tensor imaging (DTI) and diffusion kurtosis im

97 tions between PC integrity, measured through diffusion tensor imaging (DTI) and fractional anisotropy

98 ng multiple modalities of WM imaging such as diffusion tensor imaging (DTI) and magnetization transfe

99 Metrics of diffusion tensor imaging (DTI) and magnetization transfe

100 ntrols were assessed with magnetic resonance diffusion tensor imaging (DTI) and neuropsychological te

101 ic disorders, and integrated these data with diffusion tensor imaging (DTI) and psychometric measurem

102 ing techniques using magnetic resonance (MR) diffusion tensor imaging (DTI) and resting state functio

103 Diffusion tensor imaging (DTI) and resting-state functio

104 ned longitudinally from 6 to 48 months using diffusion tensor imaging (DTI) and tract-based spatial s

105 and healthy term controls (N = 16) underwent diffusion tensor imaging (DTI) at term equivalent age.

106 d the processing and statistical analyses of diffusion tensor imaging (DTI) data across sites and met

107 time positron emission tomography (PET) and diffusion tensor imaging (DTI) data of a SCA animal mode

108 Diffusion tensor imaging (DTI) data of two sets of 40 he

109 Diffusion tensor imaging (DTI) data were acquired from 2

110 monemia-associated astrocytic changes, while diffusion tensor imaging (DTI) demonstrates changes in n

111 Diffusion tensor imaging (DTI) enables comprehensive who

112 Diffusion tensor imaging (DTI) enables in-vivo quantific

113 encing a first episode of psychosis received diffusion tensor imaging (DTI) exams, clinical assessmen

114 While diffusion tensor imaging (DTI) failed to distinguish sim

115 INTRODUCTION: Discrepancies between diffusion tensor imaging (DTI) findings and functional r

116 Diffusion tensor imaging (DTI) harnesses the power of co

117 Diffusion tensor imaging (DTI) has been used to evaluate

118 included using both T1-weighted imaging and diffusion tensor imaging (DTI) in a cross-sectional samp

119 Diffusion tensor imaging (DTI) is a derivative MRI techn

120 Diffusion tensor imaging (DTI) is a unique in vivo imagi

121 Diffusion tensor imaging (DTI) is highly sensitive in de

122 In addition, diffusion tensor imaging (DTI) is sensitive to disruptio

123 tructural changes in white matter (WM) using diffusion tensor imaging (DTI) may be a useful outcome m

124 Diffusion tensor imaging (DTI) may detect subtle white m

125 ted white matter abnormalities of ASPD using diffusion tensor imaging (DTI) measures: fractional anis

126 We extracted tract-specific diffusion tensor imaging (DTI) metrics to assess changes

127 fer measurements), myelin water fraction and diffusion tensor imaging (DTI) metrics, in addition to p

128 pecific structural connectivity derived from diffusion tensor imaging (DTI) of 22 individuals with le

129 Diffusion tensor imaging (DTI) of brain development in f

130 Structural connectivity was defined by diffusion tensor imaging (DTI) of white matter tract mic

131 Diffusion tensor imaging (DTI) offers a method of assess

132 Diffusion tensor imaging (DTI) provides a window for vis

133 Diffusion tensor imaging (DTI) provides us an insight in

134 on structural magnetic resonance imaging and diffusion tensor imaging (DTI) scanning.

135 ks) underwent magnetic resonance imaging and diffusion tensor imaging (DTI) scans, early in life (pos

136 Diffusion tensor imaging (DTI) studies consistently repo

137 Diffusion tensor imaging (DTI) studies have detected whi

138 Diffusion tensor imaging (DTI) studies in the related co

139 Cross-sectional diffusion tensor imaging (DTI) studies indicate that, af

140 We review diffusion tensor imaging (DTI) studies that investigate

141 a psychiatric disorder (controls) underwent diffusion tensor imaging (DTI) studies.

142 This investigation was a cross-sectional diffusion tensor imaging (DTI) study at an outpatient ac

143 A recent diffusion tensor imaging (DTI) study showed that trainin

144 We used diffusion tensor imaging (DTI) to assess the integrity o

145 impact of brief exposure to hyperoxia using diffusion tensor imaging (DTI) to identify axonal injury

146 The aim of this study was to use MR diffusion tensor imaging (DTI) to identify brain microst

147 l imaging of PET and (18)F-FDG combined with diffusion tensor imaging (DTI) to investigate the associ

148 Thirty-three MMT patients underwent diffusion tensor imaging (DTI) twice - at the start of t

149 3-Tesla, 15-direction diffusion tensor imaging (DTI) was acquired from 90 pret

150 unger and 28 older healthy adults by linking diffusion tensor imaging (DTI) with functional magnetic

151 Here, we applied diffusion tensor imaging (DTI), a modality of magnetic r

152 brain magnetic resonance imaging, including diffusion tensor imaging (DTI), and cognitive assessment

153 unctional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), and electroencephalograp

154 1) who underwent magnetic resonance imaging, diffusion tensor imaging (DTI), and positron emission to

155 such as single voxel spectroscopy (MRS) and diffusion tensor imaging (DTI), in children with X-linke

156 tients by using magnetic resonance (MRI) and diffusion tensor imaging (DTI), unbiased stereology and

157 ns, including T2-weighted imaging (T2WI) and diffusion tensor imaging (DTI), were performed one day p

158 ment effects on white matter integrity using diffusion tensor imaging (DTI).

159 M) in multiple sclerosis (MS) patients using diffusion tensor imaging (DTI).

160 quantitative magnetic resonance imaging and diffusion tensor imaging (DTI).

161 monstrated using fiber tractography based on diffusion tensor imaging (DTI).

162 ting transsexuals and healthy controls using diffusion tensor imaging (DTI).

163 the thalamus and less thalamic fiber loss by diffusion tensor imaging (DTI).

164 The latter can be addressed with diffusion tensor imaging (DTI).

165 itching, in a sample of 84 adolescents using diffusion tensor imaging (DTI).

166 ween FTLD-TAU and FTLD-TDP during life using diffusion tensor imaging (DTI).

167 ine motor skill assessment and scanning with diffusion tensor imaging (DTI).

168 tion and can be assessed non-invasively with diffusion tensor imaging (DTI).

169 th improvements in cognitive function, using diffusion tensor imaging (DTI).

170 ond the motor pathways, can be visualised by diffusion tensor imaging (DTI).

171 ed magnetic resonance (MR) imaging, with two diffusion-tensor imaging (DTI) acquisitions and arterial

172 Purpose To determine the changes of diffusion-tensor imaging (DTI) and tractography in the d

173 Magnetic resonance (MR) neurography with diffusion-tensor imaging (DTI) was performed in all stud

174 l DWI, diffusion kurtosis imaging (DKI), and diffusion-tensor imaging (DTI) with quantitative histopa

175 Stability of diffusion tensor imaging findings was verified by repeat

176 Diffusion-tensor imaging findings were correlated with s

177 n of cortical thickness and surface area and diffusion tensor imaging for quantification of the quali

178 ow low white matter integrity, measured with diffusion tensor imaging, for both disorders.

179 Whole-brain and regional diffusion tensor imaging fractional anisotropy were used

180 r quantification of brain connectivity using diffusion tensor imaging, functional connectivity, and g

181 betic and nondiabetic participants underwent diffusion tensor imaging, functional magnetic resonance

182 l ganglia volumetry; white matter integrity (diffusion tensor imaging); gray matter density (voxel-ba

183 nected through white matter (WM) tracts, and diffusion tensor imaging has provided compelling evidenc

184 atter microstructural changes detected using diffusion tensor imaging have been reported in bipolar d

185 Connectomic approaches using diffusion tensor imaging have contributed to our underst

186 Although diffusion tensor imaging holds promise for in vivo chara

187 m as quickly as possible with concurrent 3T diffusion tensor imaging in 164 participants (57.1% fema

188 ctivity) between the abnormal GM regions via diffusion tensor imaging in 48 marijuana users and 62 ag

189 te functional magnetic resonance imaging and diffusion tensor imaging in a group of 32 healthy subjec

190 , we modeled the structural connectome using diffusion tensor imaging in a sample of 949 youths (aged

191 udy compared white-matter organization using diffusion tensor imaging in early- and late-trained musi

192 ssessed via fractional anisotropy [FA]) with diffusion tensor imaging in patients with BD (n=26), una

193 ffusion properties of white matter tracts by diffusion tensor imaging in the presence of cerebrospina

194 rostructural integrity of white matter using diffusion tensor imaging in two healthy control samples

195 and to evaluate white matter integrity with diffusion-tensor imaging in patients who are recovering

196 ic white matter (WM) tracts as detected with diffusion-tensor imaging in the absence of clinically di

197 d mean diffusivity were measured by means of diffusion-tensor imaging in the white matter adjacent to

198 sonance imaging [MRI], resting-state MRI, or diffusion tensor imaging) in combination with multivaria

199 ical structural connectivity, as measured by diffusion tensor imaging, in a cohort of 28 participants

200 dial diffusivity in this region, measured by diffusion tensor imaging, inversely predicted thickness.

201 Diffusion tensor imaging is sensitive in detecting the w

202 Further, we show that diffusion tensor imaging is sensitive to these cellular

203 Diffusion Tensor Imaging is the most advanced imaging te

204 This study evaluates whether diffusion tensor imaging magnetic resonance neurography

205 Diffusion tensor imaging maps were calculated and transf

206 atosus with past NPSLE, significantly higher diffusion tensor imaging mean and radial diffusivities w

207 egional measures of TSPO using [11C]DPA-713, diffusion tensor imaging measures of regional white matt

208 gned to (i) evaluate the influence of age on diffusion tensor imaging measures of white matter assess

209 Diffusion tensor imaging measures properties of water di

210 Diffusion tensor imaging measures recovery of axonal inj

211 Correlations among clinical, structural and diffusion tensor imaging measures were calculated.

212 sted with control subjects (n = 26) with the diffusion tensor imaging measures: fractional anisotropy

213 h/without past NPSLE and healthy controls on diffusion tensor imaging metrics and on diffusion coeffi

214 measurement of cord cross-sectional area and diffusion tensor imaging metrics in the GM and posterior

215 Brain white matter diffusion tensor imaging metrics were assessed using who

216 s from C2-3 to T2-3 level were measured, and diffusion tensor imaging metrics, i.e. fractional anisot

217 nd slow wave parameters were associated with diffusion tensor imaging metrics; white matter fractiona

218 ealthy controls using the magnetic resonance diffusion tensor imaging, myocardial tagging, and biomec

219 y) and volume of axon pathways using in vivo diffusion tensor imaging of fronto-frontal, fronto-tempo

220 e protocol allows the acquisition of in vivo diffusion tensor imaging of the mouse brainstem and cerv

221 sms of local versus distal acupuncture using diffusion tensor imaging of white matter microstructure

222 Diffusion-tensor imaging of the knee was performed at 3.

223 Using diffusion tensor imaging on a subset of patients, we als

224 stigated the association between presurgical diffusion tensor imaging parameters of brain microstruct

225 Group comparisons on tissue volume and diffusion tensor imaging parameters were made between DM

226 hy control subjects in postural sway and DTI diffusion-tensor imaging parameters (P < .05).

227 balance impairment was correlated with worse diffusion-tensor imaging parameters along the cerebellar

228 y, to correlate force platform measures with diffusion-tensor imaging parameters and regional gray ma

229 iance were performed to evaluate whether DTI diffusion-tensor imaging parameters significantly change

230 with streamline tractography; values of DTI diffusion-tensor imaging parameters were then obtained f

231 res: Quantitative neurologic examination and diffusion tensor imaging performed 1 to 3 times through

232 temperament, magnetic resonance imaging, and diffusion tensor imaging phenotypes.

233 connectivity magnetic resonance imaging and diffusion tensor imaging probabilistic tractography to s

234 MRI using diffusion tensor imaging provides structural information

235 Using diffusion tensor imaging, recent studies suggest that wh

236 Diffusion tensor imaging revealed extensive white matter

237 Diffusion tensor imaging revealed reduced reorientation

238 Diffusion tensor imaging revealed that trait anxiety pre

239 ond time-point, they also underwent a second diffusion tensor imaging scan.

240 volunteers between 8 and 26 years underwent diffusion tensor imaging scanning and completed a delay-

241 used as seeds for tractographic analysis of diffusion tensor imaging scans acquired in the same subj

242 Presurgical diffusion tensor imaging scans of 136 older (>/=70 years

243 For n = 376 individuals, diffusion tensor imaging scans were also available.

244 magnetic resonance imaging (MRI) including a diffusion tensor imaging sequence to assess microstructu

245 quence, a T1-weighted volume sequence, and a diffusion-tensor imaging sequence.

246 Diffusion tensor imaging showed converging imaging abnor

247 Diffusion-tensor imaging shows the columnar microstructu

248 l magnetic resonance imaging marker based on diffusion tensor imaging, skeletonization of white matte

249 We report here a meta-analysis of diffusion tensor imaging studies in these conditions.

250 Findings from diffusion tensor imaging studies of white matter integri

251 or the interpretation of the human and mouse diffusion tensor-imaging studies upon which it is based.

252 Here we present a diffusion tensor imaging study that examined white matte

253 Regression data incorporating diffusion tensor imaging suggest that microstructural pr

254 In the present study, we used a novel diffusion tensor imaging technique to obtain high resolu

255 19 healthy control subjects (sample 1) with diffusion tensor imaging, the Intra-Extra Dimensional Se

256 s underwent multimodal MR imaging, including diffusion-tensor imaging, three-dimensional (3D) T1-weig

257 The authors used diffusion tensor imaging to assess white matter integrit

258 Follow-up MRI included diffusion tensor imaging to assess white matter integrit

259 We used diffusion tensor imaging to characterize putative white

260 ng structural magnetic resonance imaging and diffusion tensor imaging to determine neuroanatomic diff

261 Here, we used diffusion tensor imaging to examine the effects of BDNF

262 We used diffusion tensor imaging to explore differences in fract

263 We used voxel-based morphometry (VBM) and diffusion tensor imaging to identify structural and conn

264 The present study used diffusion tensor imaging to investigate whether military

265 We used diffusion tensor imaging to quantify structural connecti

266 We used diffusion tensor imaging to study the white matter in sp

267 Here we use diffusion tensor imaging to test whether changes in whit

268 Diffusion tensor imaging tractography demonstrates a clo

269 Diffusion tensor imaging tractography revealed increased

270 uantitative tract-specific measures based on diffusion tensor imaging tractography to examine both di

271 ctural networks were built using whole-brain diffusion tensor imaging tractography, and analysed usin

272 which we conducted whole-brain deterministic diffusion tensor imaging tractography.

273 le (ALIC) in MDD and diabetic subjects using diffusion tensor imaging tractography.

274 We performed diffusion tensor imaging, using two complimentary approa

275 olume and thickness reduction or grey matter diffusion tensor imaging values alterations were observe

276 Diffusion tensor imaging was applied in healthy particip

277 l white matter mean diffusivity derived from diffusion tensor imaging was compared between groups in

278 Brain grey and white matter volume and diffusion tensor imaging was compared between survivor g

279 Diffusion tensor imaging was performed in 296 healthy su

280 Diffusion tensor imaging was performed to measure fracti

281 Dual heart-phase diffusion tensor imaging was successfully performed in 9

282 In this study, diffusion tensor imaging was used to evaluate white matt

283 Diffusion tensor imaging was used to model white matter

284 Fractional anisotropy (measured using diffusion tensor imaging) was the primary outcome measur

285 ity between SN/VTA and striatum, measured by diffusion tensor imaging, was tightly coupled to inter-i

286 strength of white matter connectivity using diffusion tensor imaging, we characterize a left frontal

287 Using diffusion tensor imaging, we defined fractional anisotro

288 Using functional and diffusion tensor imaging, we present a comprehensive neu

289 hensive voxelwise analyses of volumetric and diffusion tensor imaging, we used an unsupervised machin

290 g functional magnetic resonance imaging, and diffusion tensor imaging were assessed before and 2 mont

291 utive function task, and structural MRI with diffusion tensor imaging were conducted.

292 Structural magnetic resonance imaging and diffusion tensor imaging were performed with 157 nonseda

293 usion-weighted imaging, MR spectroscopy, and diffusion-tensor imaging) were performed.

294 n magnetic resonance imaging data, including diffusion tensor imaging, were acquired in 16 patients w

295 On diffusion tensor imaging, white matter injury was promin

296 This hypothesis was tested by combining diffusion tensor imaging with a multistep decision task

297 We did so combining diffusion tensor imaging with diffusion-weighted magneti

298 Finally, diffusion tensor imaging with multivariate analysis of 3

299 We introduce a new method that combines diffusion tensor imaging with probabilistic tractography

300 racts within the human brain (measured using diffusion tensor imaging) with data from a large sample