ライフサイエンスコーパス: mammographic

1 ications, and masses) was evaluated with the mammographic accreditation ACR phantom.

2 --consistent with mammographic data; and the mammographic and (post-operative) pathologic sizes are l

3 radiologists with expertise in interpreting mammographic and CT findings independently reviewed the

4 Imaging Reporting and Data System (BI-RADS) mammographic and magnetic resonance (MR) imaging feature

5 agreement between BPE levels on CE spectral mammographic and MR images and among readers, weighted k

6 aders independently rated BPE on CE spectral mammographic and MR images with the ordinal scale: minim

7 ween readers for BPE detected on CE spectral mammographic and MR images.

8 Mammographic and MR imaging features were retrospectivel

9 ediolateral oblique and craniocaudal digital mammographic and tomosynthesis images of both breasts we

10 f malignancy were determined after biopsy or mammographic and US follow-up at a minimum of 11 months.

11 reading to occur only in women with a denser mammographic background pattern (P = .02).

12 ing necessity of short-interval follow-up of mammographic BI-RADS category 3 findings.

13 Mammographic breast cancer detection in the CEE group wa

14 Percent mammographic breast density (PMD) is a strong heritable

15 nclusion This DL model can be used to assess mammographic breast density at the level of an experienc

16 n requiring radiology facilities to disclose mammographic breast density information to women, often

17 Results Mammographic breast density was inversely associated wit

18 Limitation: Quantitative measures of mammographic breast density were not available for compa

19 erogeneity=0.01) and is also associated with mammographic breast density, a strong risk factor for br

20 Measurements: Mammographic breast density, as clinically recorded usin

21 Conclusion The BI-RADS features of mammographic breast density, calcification morphology, m

22 lop a deep learning (DL) algorithm to assess mammographic breast density.

23 ample shows how to apply a FR method to sort mammographic breast lesion features.

24 50-64 years who were invited to and attended mammographic breast screening from April 1, 2003, to Mar

25 n ADH involves fewer than three foci and all mammographic calcifications have been removed, because t

26 Needle biopsy was performed because of mammographic calcifications in 215 of the 276 lesions (7

27 ates were similar, regardless of whether all mammographic calcifications were removed (seven [17%] of

28 S and benign breast disease that manifest as mammographic calcifications.

29 xteen radiologists independently reviewed 60 mammographic cases: 20 cases with cancer and 40 cases wi

30 umour grows 7-10mm per year--consistent with mammographic data; and the mammographic and (post-operat

31 investigated the concurrent associations of mammographic dense and nondense areas, body mass index (

32 owth spurts starting in early infancy reduce mammographic dense area in adulthood.

33 Mammographic dense area was positively associated with r

34 as tailored to lifetime risk (Gail test) and mammographic density (according to Breast Imaging Report

35 countries in the International Consortium on Mammographic Density (ICMD).

36 has been set at either low or high level of mammographic density (MD) and the organoid models are ex

37 Mammographic density (MD) is one of the strongest breast

38 Mammographic density (MD) phenotypes are strongly associ

39 ted 10-year breast cancer risk score (TCRS), mammographic density (MD), and a 77-single nucleotide po

40 colony organization, at the maximum level of mammographic density (MD), are investigated.

41 icroenvironment is increased to that of high mammographic density (MD).

42 aracteristics (n = 4,091), risk factors, and mammographic density (n = 1,957) were included.

43 = 0.36) became positive after adjustment for mammographic density (odds ratio = 1.28, 95% confidence

44 positive outcome (P > .05), although greater mammographic density (P = .022) and younger age (< 50 ye

45 Percent mammographic density (PMD) adjusted for age and body mas

46 Percent mammographic density adjusted for age and body mass inde

47 High-percent mammographic density adjusted for age and body mass inde

48 We studied the change in mammographic density after a breast cancer diagnosis and

49 Previous studies have linked reductions in mammographic density after a breast cancer diagnosis to

50 A decrease in mammographic density after breast cancer diagnosis appea

51 treatment is associated with a reduction in mammographic density and an improved survival.

52 r evidence of a shared genetic basis between mammographic density and breast cancer and illustrate th

53 uate the strength of the association between mammographic density and breast cancer risk using differ

54 To maximize statistical power in studies of mammographic density and breast cancer, it is advantageo

55 ations of plasma leptin and adiponectin with mammographic density and disease status and assessed the

56 onectin levels were directly associated with mammographic density and HDL cholesterol and negatively

57 Mammographic density and lobular involution are both sig

58 requiring that women be informed about their mammographic density and related adjunct imaging.

59 e genome-wide association studies of percent mammographic density and report an association with rs10

60 At lower levels of MDA, mammographic density and telomere length were inversely

61 s evidence of a J-shaped association between mammographic density and telomere length.

62 n ERBB2 (HER2(+) or HER2(-)) tumor subtypes, mammographic density and tumor grade.

63 e results provide new insights into how high mammographic density arises and why it is associated wit

64 reast cancer are based on questionnaires and mammographic density assessments.

65 The percent mammographic density at the first available mammogram wa

66 ated with a weaker annual decline in percent mammographic density by 0.09% (standard error = 0.03; P

67 We measured mammographic density by a computer assisted method and b

68 However, mammographic density cannot be used as a clinical indica

69 tatistically significant association between mammographic density change and survival.

70 Conversely, mammographic density does not appear to explain the inve

71 However, the extent to which change in mammographic density during adjuvant tamoxifen therapy c

72 Interval breast cancers in women with low mammographic density have the most aggressive phenotype.

73 Background Mammographic density improves the accuracy of breast can

74 We examined the effect of CEE alone on mammographic density in a subsample of the Women's Healt

75 conjugated equine estrogens (CEEs) alone on mammographic density in diverse racial/ethnic population

76 st prominent difference between low and high mammographic density in healthy breast tissue by PARADIG

77 y measured circulating carotenoid levels and mammographic density in the Nurses' Health Study.

78 High mammographic density is a strong breast cancer risk fact

79 Extensive mammographic density is a strong risk factor for breast

80 Increased mammographic density is associated with increased breast

81 In this study, mammographic density is measured by using a fully automa

82 Mammographic density is one of the strongest predictors

83 In this study we examined whether mammographic density is related to blood telomere length

84 investigated whether the level of decline in mammographic density is related to breast cancer risk us

85 Mammographic density is strongly associated with breast

86 n may be an important genetic determinant of mammographic density measure that predicts breast cancer

87 y variants were associated with at least one mammographic density measure.

88 ssociations between reproductive factors and mammographic density measured using processed FFDM image

89 s demonstrate the robustness of quantitative mammographic density measurements across FFDM and film m

90 Mammographic density measurements are associated with ri

91 Mammographic density measures adjusted for age and body

92 They had a total of 6,317 mammographic density measures available from the first 5

93 ociated with both breast cancer risk and the mammographic density measures.

94 Conclusion Mammographic density on FFDM images was positively assoc

95 omere length was not associated with percent mammographic density or dense area, before or after adju

96 ome-wide association studies (GWAS) of three mammographic density phenotypes: dense area, non-dense a

97 dentify etiologic pathways implicated in how mammographic density predicts breast cancer risk.

98 Mammographic density reflects the amount of stromal and

99 e clinical significance of the CEE effect on mammographic density remains to be determined.

100 However, mammographic density significantly modified the associat

101 etween siblings in the Early Determinants of Mammographic Density study (1959-2008; n = 700 women wit

102 spective data from the Early Determinants of Mammographic Density Study (n = 1,108; 1959-2008), we ex

103 spective data from the Early Determinants of Mammographic Density study (United States, 1959-2008, n

104 lation of the epithelium in a mouse model of mammographic density supported a causal relationship bet

105 st but statistically significant increase in mammographic density that is sustained over at least a 2

106 udy, we show that epithelial cells from high mammographic density tissues have more DNA damage signal

107 onse compared with epithelial cells from low mammographic density tissues.

108 s seen in desmoplastic and disease-free high mammographic density tissues.

109 risk for developing cancer, especially high mammographic density tissues.

110 ome-wide association study (GWAS) of percent mammographic density to identify novel genetic loci asso

111 ample of 479 individuals from the Australian Mammographic Density Twins and Sisters was used for disc

112 Interreader agreements for the mammographic density types and CT density grades were de

113 igher for the CT density grades than for the mammographic density types, with 0.79 (95% confidence in

114 0, a single reader reassessed all images for mammographic density using Cumulus software (Sunnybrook

115 .6 years, the mean annual decline in percent mammographic density was 1.1% (standard deviation = 0.1)

116 Change in mammographic density was calculated as percentage change

117 Mammographic density was estimated as the four-category

118 Mammographic density was measured by using a computer-as

119 Mammographic density was measured by using an automated

120 s central), amount of FGT at MR imaging, and mammographic density were assessed on index images.

121 We examined whether age-related changes in mammographic density were different for 533 cases and 1,

122 ed breast cancer after adjusting for age and mammographic density were family history of breast cance

123 BPE pattern, MR imaging amount of FGT, and mammographic density were not significantly different be

124 tive would have a greater decline in percent mammographic density with age, compared with less physic

125 se results and to examine the association of mammographic density with age-related chronic disease an

126 The associations of mammographic density with breast cancer and the model fi

127 val breast cancers in dense breasts (> 40.9% mammographic density) were less aggressive than interval

128 breast cancers in nondense breasts (</= 20% mammographic density) were significantly more likely to

129 The associations are independent of BMI, mammographic density, and treatment.

130 within-cohort percentile changes) with adult mammographic density, assessed using a computer-assisted

131 normal breast epithelium of women with high mammographic density, correlated positively with epithel

132 ssion adjusted for age, available prior MRI, mammographic density, examination year, and multiple ris

133 larly, among women in the highest tertile of mammographic density, high levels of circulating alpha-c

134 somatotype at age 18, benign breast disease, mammographic density, polygenic risk score, family histo

135 Percent mammographic density, the proportion of dense breast tis

136 Among women in the highest tertile of mammographic density, total carotenoids were associated

137 le predictors of breast cancer risk, but few mammographic density-associated genetic variants have be

138 orresponds to the collagen component at high mammographic density.

139 in the breast epithelium of women with high mammographic density.

140 breast cancer risk is not fully explained by mammographic density.

141 he SNP most strongly associated with percent mammographic density.

142 associated with both breast cancer risk and mammographic density.

143 d by highest and lowest quartiles of percent mammographic density.

144 signaling has been associated with increased mammographic density.

145 .27 to 0.93) compared with women with stable mammographic density.

146 be partially due to negative confounding by mammographic density.

147 st cancer risk remained after adjustment for mammographic density.

148 n inverse association between involution and mammographic density.

149 wer risk factors, such as polygenic risk and mammographic density.

150 er through a mechanism that includes reduced mammographic density.

151 otect against breast cancer is by decreasing mammographic density.

152 cer risk, particularly among women with high mammographic density.

153 ent to reduce cancer risk in women with high mammographic density.

154 isted thresholding method to measure percent mammographic density.

155 carotenoids and breast cancer risk varies by mammographic density.

156 breast cancer risk through its influence on mammographic density.

157 and breast cancer risk among women with low mammographic density.

158 ng carotenoids are inversely associated with mammographic density.

159 cer risk and, less consistently, with higher mammographic density.

160 ere length and MDA in their association with mammographic density.

161 eafter, unless otherwise indicated, a yearly mammographic evaluation should be performed.

162 alculated for the earliest available digital mammographic examination for each woman.

163 ons were reported on the basis of the second mammographic examination regardless of acquisition metho

164 eral breast cancers were diagnosed in 10 715 mammographic examinations (2.5 cancers per 1000 examinat

165 Diagnostic and screening tomosynthesis mammographic examinations (n = 175; cranial caudal and m

166 age 0-III breast cancer who underwent 33 938 mammographic examinations and 2506 breast MRI examinatio

167 Screening digital mammographic examinations from 240 women (median age, 62

168 A retrospective review of the screening mammographic examinations identified 42.9% (39 of 91) of

169 trospective study included data from digital mammographic examinations in BreastScreen Norway obtaine

170 aminations) compared with 16 cancers in 6916 mammographic examinations in the RTAS group (2.3 cancers

171 d older who underwent at least two screening mammographic examinations less than 36 months apart betw

172 st-BCT protocol, which recommends semiannual mammographic examinations of the ipsilateral breast for

173 Results There were 8818 MR and 6245 mammographic examinations performed in 2463 women.

174 etection performance of radiologists reading mammographic examinations unaided versus supported by an

175 m 2009 to 2014, during which 108 276 digital mammographic examinations were performed (50 062 before

176 All mammographic examinations were performed with DBT.

177 MR imaging examinations and 26 866 screening mammographic examinations were performed.

178 Two hundred mammographic examinations were selected from examination

179 who underwent 10,641 screening or diagnostic mammographic examinations with abnormal results between

180 DBT groups were composed of 9019 and 22 887 mammographic examinations, respectively, in 8170 women (

181 e (91% vs 86%; P = .03) and those with total mammographic experience of fewer than 80 000 cases (88%

182 The size and predominant mammographic feature of the cancer were recorded, as was

183 Stratus method and computer-aided detection mammographic features (density, masses, microcalcificati

184 The mammographic features (masses, architectural distortions

185 genetic predisposition to breast cancer and mammographic features among women with a family history

186 with false-positive findings and in whom the mammographic features changed over time had a highly inc

187 Mammographic features influence breast cancer risk and a

188 Understanding how genetics influence mammographic features is important because the mechanism

189 investigation of common loci associated with mammographic features is warranted to better understand

190 Previous mammographic features might yield useful information for

191 The mammographic features of 131 NLCs with reduced E-cadheri

192 nsity have relied on one assessment, yet the mammographic features of the breast that constitute brea

193 Women in whom mammographic features showed changes in subsequent false

194 The heritability of mammographic features such as dense area (MD), microcalc

195 ancers missed at FFDM tend to have different mammographic features than those missed at SFM.

196 reduced E-cadherin expression appear to have mammographic features that make them difficult to detect

197 Cancers were classified as missed or true, mammographic features were described, percentages were c

198 Conclusion By combining three mammographic features, differences in the left and right

199 ts according to radiologic classification of mammographic features.

200 rics of breast density on full-field digital mammographic (FFDM) images as predictors of future breas

201 Breast microcalcifications are a common mammographic finding.

202 s (age, family history, and hormone use) and mammographic findings (described using the established l

203 rate was 0% for all US findings and for all mammographic findings except pure clustered microcalcifi

204 Among the 122 DBT examinations, 74 mammographic findings had final histologic findings, inc

205 We imaged 4 women with mammographic findings highly suggestive of breast cancer

206 For mammographic findings other than pure clustered microcal

207 and use of hormone replacement therapy) and mammographic findings recorded in the Breast Imaging Rep

208 board-approved study, 205 patients with 216 mammographic findings suspicious for cancer were schedul

209 PPV of mammographic findings was evaluated in a prospective coh

210 ue-positive rates, false-positive rates, and mammographic findings were assessed by using confidence

211 men (age range, 50-64 years) with discordant mammographic findings were discussed at consensus meetin

212 Mammographic findings were matched with a state cancer r

213 MR and mammographic findings were reviewed.

214 in five additional patients on the basis of mammographic findings, and malignancy was detected in th

215 BT according to volumetric density, age, and mammographic findings.Materials and MethodsFrom November

216 early breast clinical examination and yearly mammographic follow-up to detect an eventual cancer in i

217 All 275 women underwent one mammographic follow-up, 205 (74.5%) underwent a second m

218 ic follow-up, 205 (74.5%) underwent a second mammographic follow-up, and 147 (53.5%) underwent a thir

219 Excluding initial mammographic follow-up, there were 8234 examinations.

220 follow-up, and 147 (53.5%) underwent a third mammographic follow-up.

221 esigned a deep fusion learning framework for mammographic image classification.

222 ay be important, as standard two-dimensional mammographic images are increasingly being replaced by s

223 p neural network, further information in the mammographic images can be considered.

224 c and enhancement imaging features on MR and mammographic images in screening and prior examinations.

225 nal treatment, breast density on CE spectral mammographic images, and amount of fibroglandular tissue

226 dress the recognition of abnormalities among mammographic images, in this study we apply the deep fus

227 or in reducing recall recommendations during mammographic interpretation.

228 esian networks may help radiologists improve mammographic interpretation.

229 differentiation between malignant and benign mammographic lesions was better than that with the lesio

230 tracer (SUV ratio > 1.1) coinciding with the mammographic location of the lesion, whereas the other 3

231 ake of tracer (SUVR>1.1) coinciding with the mammographic location of the lesion.

232 15 of the 276 lesions (77.9%) and because of mammographic masses in 35 (12.7%).

233 arriers (MR imaging median size = 12.5 mm vs mammographic median size = 6 mm; P = .067); the differen

234 agnostic criterion to rule out malignancy in mammographic microcalcifications at breast MR imaging.

235 hanced MR imaging was used for assessment of mammographic microcalcifications that were assigned Brea

236 r diagnosis of malignancy in BI-RADS 3 and 5 mammographic microcalcifications, but can be considered

237 cations, but can be considered for BI-RADS 4 mammographic microcalcifications.

238 density categorization may vary by screening mammographic modality, and this effect appears to vary b

239 cal mechanisms regulating the role played by mammographic nondense area and body fat on breast cancer

240 Mammographic nondense area was inversely associated with

241 DM images and any additional two-dimensional mammographic or US images.

242 Conclusion Radiomic phenotypes capture mammographic parenchymal complexity beyond conventional

243 Purpose To identify phenotypes of mammographic parenchymal complexity by using radiomic fe

244 ontralateral breast parenchyma to assess the mammographic parenchymal patterns.

245 Mammographic PD was estimated with software.

246 Use of CEE resulted in mean increase in mammographic percent density of 1.6 percentage points (9

247 The effect of CEE on mammographic percent density was determined over 1 and 2

248 by using about 22% of the dose for a single mammographic projection.

249 Number of mammographic readings per year was positively related wi

250 For individuals with more than 5000 mammographic readings per year, JAFROC values were posit

251 factor in individuals with a high volume of mammographic readings.

252 ogists with annual volumes of less than 1000 mammographic readings.

253 Widespread mammographic screening and effective systemic therapies

254 orted that their cancer had been detected by mammographic screening and half that they or their clini

255 We aimed to estimate the effect of mammographic screening at ages 40-48 years on breast can

256 Digital mammographic screening beginning at ages 25, 30, 35, and

257 The landscape of mammographic screening continuously evolves, and differe

258 Adding annual MR imaging to annual mammographic screening cost $69125 for each additional Q

259 data were linked to prescription refill and mammographic screening databases.

260 ars who underwent 789 481 full-field digital mammographic screening examinations during 2004-2012 was

261 -74.9 years) who underwent from one to seven mammographic screening examinations from September 2010

262 mors account for a substantial proportion of mammographic screening failure.

263 compared the effect of invitation to annual mammographic screening from age 40 years with commenceme

264 general practice, in a 1:2 ratio, to yearly mammographic screening from the year of inclusion in the

265 Here, using mammographic screening history and detailed questionnair

266 l rate for suspicious microcalcifications at mammographic screening increased during the past 2 decad

267 Mammographic screening is impractical in most of the wor

268 creening continuously evolves, and different mammographic screening modalities may result in differen

269 st cancer and all breast cancers in the U.S. mammographic screening population, with screening of wom

270 the four authors of this article each set up mammographic screening programs and independently develo

271 Mammographic screening sensitivity, specificity, and pos

272 The widespread use of mammographic screening will increase the number of patie

273 Age-specific effects of mammographic screening, and the timing of such effects,

274 (n = 102) was more likely to be detected on mammographic screening, had smaller median size, and les

275 In regions of the world that lack mammographic screening, the routine use of clinical brea

276 , including clinical breast examinations and mammographic screening, were introduced in Brazil in 200

277 Conclusion Consensus review of discordant mammographic screening-detected abnormalities remains a

278 cer and cancer diagnosis are associated with mammographic screening.

279 cer screening, dense breast tissue decreases mammographic sensitivity.

280 Microcalcifications are an early mammographic sign of breast cancer and a target for ster

281 Microcalcifications are an early mammographic sign of breast cancer and frequent target f

282 A total of 1 333 541 mammographic studies (hereafter called "mammograms") ove

283 Whether mammographic surveillance after BCS occurs and by whom i

284 Decisions on mammographic surveillance should also incorporate whethe

285 nnual interval is preferable for ipsilateral mammographic surveillance, allowing detection of a signi

286 d to evaluate image quality for all types of mammographic systems.

287 rs were assigned to evaluate images from two mammographic systems.

288 Mean mammographic target to reflector distance was 0.3 cm.

289 an increased risk of breast cancer and lower mammographic tumor detectability.

290 Average mammographic tumor size of missed cancers manifesting as

291 The median difference from baseline mammographic tumor size to surgery was 0 cm (8.6 cm smal

292 n density readings was similar regardless of mammographic types paired (67.3%-71.0%).

293 Purpose To review mammographic, ultrasonographic (US), and magnetic resona

294 ty of breast cancers at DM versus DBT and by mammographic view, craniocaudal (CC) versus mediolateral

295 cancer conspicuity between DM and DBT or by mammographic view.

296 ime without CAD increased with the number of mammographic views (P < .0001).

297 calcified lesions compared with supplemental mammographic views.

298 ith tomosynthesis and once with supplemental mammographic views; both modes included the mediolateral

299 of the early development of mammography and mammographic wire localizations.

300 The digital mammograms were displayed on mammographic workstations and printed on film according