ライフサイエンスコーパス: lung nodule

1 There were 51 cases with and 49 without lung nodules.

2 was applied to data from 15 subjects with 77 lung nodules.

3 olorectal cancer, and 1 lymphoma) and 7 with lung nodules.

4 o be helpful in the identification of benign lung nodules.

5 se, but possibly treat, malignant peripheral lung nodules.

6 nt and infiltrated macrophages in metastatic lung nodules.

7 ng nodules, including a 28-year-old with >10 lung nodules.

8 bnormal with 16 nodules, 9 normal) to detect lung nodules.

9 Radiologists missed on average 59% of these lung nodules.

10 of the chest should be performed to identify lung nodules.

11 ologically proven datasets: colon polyps and lung nodules.

12 essarily intensive diagnostic evaluations of lung nodules.

13 ed breath to quickly and accurately classify lung nodules.

14 am-based management of incidentally detected lung nodules.

15 (CT)-guided percutaneous tissue sampling of lung nodules.

16 , thus improving the diagnostic accuracy for lung nodules.

17 ng between part-solid (PS) and nonsolid (NS) lung nodules.

18 t with the characterization of indeterminate lung nodules.

19 d left parietal CNS metastasis and enlarging lung nodules.

20 s, including high concentrations in lymphoid lung nodules.

21 OPG and anti-gp100 (HMB45) antibodies in LAM lung nodules.

22 the most frequent cause of disagreement was lung nodules.

23 uted tomographic (CT) volumetric analysis of lung nodules.

24 ated variables involved in the assessment of lung nodules.

25 99 localizes rapidly and specifically to B16 lung nodules.

26 21-89 years old (mean age, 61.3 years) with lung nodules 1.0 cm or smaller underwent CT-guided trans

27 ges from patients with presumed nonmalignant lung nodules (58.7% men; mean [SD] age, 61.9 [5.0] years

28 study included a total of 486 patients with lung nodules (63 years +/- 5.2 [standard deviation], 261

29 Lung nodules (75%, kappa = 0.71) and effusions (100%, ka

30 Thirty-three out of 42 missed lung nodules (78.6%) in 26 patients were rated benign, w

31 LAM lung nodules also produced OPG, as shown by expression o

32 chest CT scans from two public datasets, the Lung Nodule Analysis 2016 (Luna16) (n = 656) and the Rad

33 available medical datasets: (i) Segmentation-LUng Nodule Analysis Challenge, (ii) Regression-RSNA Ped

34 readers on non-thin section chest CT with a lung nodule analysis software followed by extraction of

35 employed in a bakery presented with a single lung nodule and underwent investigations to rule out pul

36 Ts, most frequently liver masses followed by lung nodules and adenopathy.

37 ived by extracting 105 3-D features from 200 lung nodules and by selecting the features with higher a

38 E-cadherin expression persists in metastatic lung nodules and circulating tumor cells (CTCs) in two m

39 y be useful in identifying the derivation of lung nodules and consequently enhances treatment plannin

40 deep learning architectures to characterize lung nodules and early cancers.

41 ease in which LAM cells and fibroblasts form lung nodules and it is hypothesized that LAM nodule-deri

42 ance compared with no AI in the detection of lung nodules and masses on chest radiographs, but user p

43 re 128; Philips Medical Systems) to evaluate lung nodules and pulmonary interstitium (Fig 2).

44 re 128; Philips Medical Systems) to evaluate lung nodules and pulmonary interstitium.

45 Of note, the measured size of lung nodules and renal stones with MBIR was significantl

46 rgent interventions during the evaluation of lung nodules and stage I non-small cell lung cancer.

47 for more evidence on better ways to evaluate lung nodules and to avoid unnecessarily intensive diagno

48 he same year she was diagnosed with multiple lung nodules and underwent pulmonary wedge resection wit

49 ents were enrolled: 5,659 in LDCT, 15,461 in Lung Nodule, and 1,766 in Multidisciplinary Care.

50 lay screening, defer surveillance imaging of lung nodules, and minimize nonurgent interventions durin

51 , and one of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 f

52 1, and 15 of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 f

53 and four of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 f

54 Background: Lung nodules are common incidental findings, and timely

55 The cancer and metastatic lung nodules are estrogen dependent and retain estrogen

56 Hepatic and renal AMLs and noncalcified lung nodules are more common in TSC/LAM, while lymphatic

57 died in lung blood vessels, producing as few lung nodules as B16-FTIII.N cells which lack sialyl Lewi

58 Lung nodules as small as 3 mm in diameter were successfu

59 e metastases, whereas disadvantages exist in lung nodule assessments.

60 The largest remaining lung nodule at 1.4 cm showed no metabolic activity.

61 Accordingly, 42 lung nodules (average size +/- SD, 3.9 +/- 1.3 mm; range

62 , consolidation, mediastinal and hilar mass, lung nodule) based on the corresponding CT results (grou

63 magnetic navigational bronchoscopy (ENB) for lung nodule biopsy has been used for decades without a s

64 Histologically, CD44v6 was present in LAM lung nodules, but not in normal vascular smooth muscle c

65 he prevalence and size distribution of solid lung nodules by age and sex in a nonsmoking population.

66 In lung nodules, cathepsin K immunoreactivity predominantly

67 Lung nodule characteristics were reviewed through direct

68 The lungs, nodules, chest wall, and mediastinum were filled

69 lung cancer screening low-dose CT scans for lung nodule classification with annotations performed in

70 l EID CT, with better diagnostic quality and lung nodule CNR.

71 Two large lung nodules collected from culled wild South African el

72 mography of the chest demonstrated bibasilar lung nodules consistent with septic emboli.

73 attenuation, noise power spectrum (NPS), and lung nodule contrast-to-noise ratio (CNR).

74 e-matched smokers or individuals with benign lung nodules correctly classified 95% of patients (AUCs

75 By contrast, the SUVs of benign lung nodules decreased slightly over time (-6.3% +/- 8.1

76 in Marshfield, Wisconsin, with an incidental lung nodule detected between January 1, 2005, and Decemb

77 ce of focal tracer uptake was noted for each lung nodule detected on (18)F-FDG PET/CT and (18)F-FDG P

78 System (Lung-RADS) classifications of solid lung nodules detected at lung cancer screening using man

79 to accurately estimate the probability that lung nodules detected on baseline screening low-dose CT

80 hould affect the management of indeterminant lung nodules detected on screening CT scans.

81 mine factors predicting the probability that lung nodules detected on the first screening low-dose CT

82 n of a positive result and the management of lung nodules detected on the scans.

83 3, P < .01 for group 2), with higher CNR for lung nodule detection (12.1 +/- 1.7 vs 10.0 +/- 1.8, P <

84 Seven lung nodule detection algorithms were validated on chest

85 performed conventional chest radiography for lung nodule detection and determination of case manageme

86 terventions, and artificial intelligence for lung nodule detection and risk stratification are key op

87 gmentation in magnetic resonance imaging and lung nodule detection in computed tomography, demonstrat

88 With an automated lung nodule detection method, a large fraction (84%, 32

89 age prediction based on hand radiographs and lung nodule detection on chest radiographs.

90 Reducing image size leads to decreased lung nodule detection on CT scans viewed at a fixed dist

91 rch, recognition and acceptance, and overall lung nodule detection rate can be studied with eye track

92 e effectiveness), and overall sensitivity of lung nodule detection were measured.

93 For lung nodule detection, the area under the receiver opera

94 haracterization of thoracic malignancies and lung nodules, determination of extent of disease, and as

95 rofile of persons with incidentally detected lung nodules differs from that of screening-eligible per

96 ancer screening and modify the evaluation of lung nodules due to the added risks from potential expos

97 cancer screening programs and patients with lung nodules during the COVID-19 pandemic.

98 within the GV gaze volume s, the fraction of lung nodules encompassed within each GV gaze volume (sea

99 Absence of significant lung nodule enhancement (< or = 15 HU) at CT is strongly

100 Rates of guideline-concordant lung nodule evaluation are low, and the risk of delayed

101 n) as the comparator, 2 other intensities of lung nodule evaluation were defined.

102 how social determinants of health influence lung nodule evaluation, 3) studying approaches to improv

103 al applications of lung cancer screening and lung nodule evaluation, the policy statement outlines ca

104 delines related to lung cancer screening and lung nodule evaluation.

105 of interventions to mitigate disparities in lung nodule evaluation.

106 ed to interventions to reduce disparities in lung nodule evaluation.

107 ecommendations for lung cancer screening and lung nodule evaluation.

108 g, comparing two diagnostic CT protocols for lung nodule evaluation.

109 Whether guideline-concordant lung nodule evaluations lead to better outcomes remains

110 Out of 134 lung nodules found on (18)F-FDG PET/CT, (18)F-FDG PET/MR

111 radiology resident retrospectively measured lung nodules from screening CT scans obtained between Se

112 ttin 2.5F and FDG were able to differentiate lung nodules from the surrounding tissues.

113 lung nodules greater than 300 mm(3), and new lung nodules greater than 200 mm(3), should be managed i

114 eening approach; that non-calcified baseline lung nodules greater than 300 mm(3), and new lung nodule

115 llelic ablation of floxed Ago2 inhibited KPC lung nodule growth while reducing proliferative index an

116 lcified lung nodules <1 cm, 12 patients with lung nodules > or =1 cm, 24 patients with infiltrates, 7

117 ng nodules (>=30 mm(3)), clinically relevant lung nodules (>=100 mm(3)), and actionable nodules (>=30

118 The prevalence and size of lung nodules (>=30 mm(3)), clinically relevant lung nodu

119 showed that the right ureteral mass and all lung nodules had regressed or disappeared (Figs 2B, 3B).

120 ed participants with a presumed nonmalignant lung nodule in the NLST between January 1, 2002, and Dec

121 The growth rates of 123 lung nodules in 59 patients who had undergone lung cance

122 CT of the chest revealed multiple cavitating lung nodules in both lungs.

123 Purpose To determine whether the pattern of lung nodules in children with metastatic hepatoblastoma

124 ence of EGFR-driver lung adenocarcinomas and lung nodules in germline carriers supports effort to ide

125 surement of subcutaneous tumors, of counting lung nodules in metastasis models, and the indirect natu

126 In recent years, the identification of lung nodules in non-high-risk populations, scanned for c

127 little is known about the presence of solid lung nodules in the Northern European nonsmoking populat

128 computer-aided diagnostic (CAD) research for lung nodules in thoracic computed tomography (CT), the N

129 Some of the difficulties in detecting lung nodules include the various types and shapes of lun

130 ulti-region exome sequencing of 116 resected lung nodules including AAH (n = 22), AIS (n = 27), MIA (

131 omputed tomography (CT) imaging and nine had lung nodules, including a 28-year-old with >10 lung nodu

132 s distributed nonuniformly across four small lung nodules, including high levels of EEHV6, lower leve

133 The prevalence of lung nodules increased from age 45-49.9 years (male part

134 Background Percutaneous CT-guided biopsy of lung nodules is an established method with high diagnost

135 Thus, detection of small lung nodules is important for appropriate staging of lun

136 The radiologic pattern of subtle lung nodules is poorly simulated by nodule phantoms with

137 1998 and 2001, 128 patients with peripheral lung nodules < or = 3 cm in size with suspected NSCLC we

138 These included 53 patients with noncalcified lung nodules <1 cm, 12 patients with lung nodules > or =

139 CRD42023437509 Keywords: Lung Nodule, Lung Cancer, Lung Cancer Screening, MRI, CT

140 ules include the various types and shapes of lung nodules, lung nodules near other lung structures, a

141 Of these, 42.0% (n = 4377) had at least one lung nodule (male participants, 47.5% [2149 of 4523]; fe

142 taining high sensitivity is challenging with lung nodule malignancy prediction.

143 The proposed 3D-MCN architecture predicted lung nodule malignancy with a high accuracy of 93.12%, s

144 proaches to identify factors associated with lung nodule management disparities, 2) limited data eval

145 A consistent feature of many lung nodule management guidelines is the recommendation

146 bute to the broader discussion on optimizing lung nodule management in screening programs.

147 et up to oversee technical standards; that a lung nodule management pathway should be established and

148 ial determinants of health on disparities in lung nodule management, 3) a lack of certainty regarding

149 re on volumetry and volume doubling times in lung nodule management, outlining their benefits and dra

150 ning studies and current recommendations for lung nodule management.

151 been a dramatic increase in the detection of lung nodules, many of which are preneoplasia atypical ad

152 Chest Radiograph, Conventional Radiography, Lung Nodule, Mass Detection(C) RSNA, 2023.

153 Lymph node enlargement and parenchymal lung nodules may not indicate metastatic disease.

154 st CT detected an additional 125 parenchymal lung nodules (mean size, 3.4 +/- 1.6 mm; range, 1-9 mm)

155 rs registered the presence and size of solid lung nodules measuring 30 mm(3) or greater using semiaut

156 ting the performance of MRI for diagnosis of lung nodules measuring 4 mm or larger, with CT as refere

157 y was to evaluate the outcome of these small lung nodules missed by (18)F-FDG PET/MRI.

158 Although most small lung nodules missed on (18)F-FDG PET/MRI were found to b

159 = 2), surveillance of a previously detected lung nodule (n = 5), evaluation of intermediate and high

160 5), evaluation of intermediate and high-risk lung nodules (n = 4), and management of clinical stage I

161 he various types and shapes of lung nodules, lung nodules near other lung structures, and similar vis

162 wed, and information was collected regarding lung nodule number, size, laterality, timing of resoluti

163 Synthetic lung nodules of four different diameters (3.2, 4.8, 6.4,

164 ively analyzed the CT images of 95 malignant lung nodules of the adenocarcinoma spectrum using BRODER

165 radiographs (60 normal and 60 abnormal with lung nodules of varying subtlety) were used.

166 ariations surrounding and overlying a subtle lung nodule on a chest radiograph that are created by th

167 ccessful non-conscious processes that detect lung nodules on chest CT examinations even when not cons

168 d Diagnostic error rates for detecting small lung nodules on chest CT scans remain high at 50%, despi

169 al assessment of a CT examination can detect lung nodules on chest CTs even when conscious recognitio

170 The detection of subtle lung nodules on chest radiographs is limited by anatomic

171 an readers, four AI algorithms for detecting lung nodules on chest radiographs showed improved perfor

172 diologists' performance for the detection of lung nodules on chest radiographs, even when baseline pe

173 can assist radiologists in the detection of lung nodules on chest radiographs.

174 valuation of CAD methods in the detection of lung nodules on CT scans.

175 rove diagnostic accuracy in the detection of lung nodules on digital radiographs.

176 future use in the diagnosis of indeterminate lung nodules or lung cancer.

177 es or masses depicted at PET, 13 (93%) of 14 lung nodules or masses, 20 (65%) of 31 mediastinal lymph

178 for known or suspected focal liver lesions, lung nodules, or kidney stones.

179 ng prevalence and size distribution of solid lung nodules originates from lung cancer screening studi

180 the utility of percutaneous localization of lung nodules performed in conjunction with video-assiste

181 None of the missed lung nodules presented with focal tracer uptake on basel

182 LDCT and Lung Nodule Programs are complementary, expanding access

183 Implementing Lung Nodule Programs may alleviate emerging disparities

184 Guideline-concordant management of lung nodules promotes early lung cancer diagnosis, but t

185 Lung nodule response assessment, by chest computed tomog

186 Accurate and reliable lung nodule segmentation in computed tomography (CT) ima

187 l attention-based architecture, for improved lung nodule segmentation in low-dose CT images.

188 Accurate lung nodule segmentation is fundamental for the early de

189 To address these problems, we propose a new lung nodule segmentation model, abbreviated as MCAT-Net.

190 With the rapid development of deep learning, lung nodule segmentation models based on the encoder-dec

191 nd thoracic radiology fellow) each performed lung nodule segmentation.

192 ET/MRI than (18)F-FDG PET/CT regarding small lung nodules should be considered in the staging of mali

193 LAM lung nodules showed reactivities to antibodies to tumor

194 Integration of biomarkers with lung nodule size has the potential to help guide the man

195 screening CT scans depends on measurement of lung nodule size.

196 The other patient had a solitary lung nodule suggestive of primary lung carcinoma and ele

197 e investigative group included patients with lung nodules suggestive of primary lung malignant neopla

198 fected HT1080 cells formed fewer and smaller lung nodules than vector control cells.

199 LAM cells and fibroblasts form lung nodules that also contain mast cells, although thei

200 tion], 261 female patients), 448 of whom had lung nodules that were subsequently classified as benign

201 ve detection and characterization of smaller lung nodules, thus increasing the chances of positive tr

202 lgorithm that predicts malignancy in current lung nodules using LDCT images (Lung Cancer Prediction C

203 can College of Radiology recommendations for lung nodules, version 1.1 (Lung-RADS).

204 For accurate measurement of lung nodule volume, it is critical to select a section t

205 Lung nodule volumetry is used for nodule diagnosis, as w

206 The accuracy of FDG-PET for diagnosing lung nodules was extremely heterogeneous.

207 A maximum of 10 lung nodules was identified for each patient on baseline

208 , and LNCaP cells, however the volume of the lung nodules was less than 1 mm3 in all of the cases.

209 A database of 38 low-dose CT scans with 50 lung nodules was obtained from a lung cancer screening p

210 mputed tomography (CT)-guided RF ablation of lung nodules was performed 48 hours after SPACE.

211 Individuals with presumed nonmalignant lung nodules were hypothetically assigned annual vs bien

212 r after baseline scanning, 2,244 uncalcified lung nodules were identified in 1,000 participants (66%)

213 ive annual CT examinations, 3356 uncalcified lung nodules were identified in 1118 (74%) participants.

214 (CD) that emulated subtle tissue-equivalent lung nodules were numerically superimposed at the center

215 0.7 cm+/-0.1 and continuing until metastatic lung nodules were observed.

216 Clinically relevant lung nodules were present in 11.1% (1155 of 10 431) of p

217 Conclusion Lung nodules were present in a substantial proportion of

218 Two hundred forty indeterminate lung nodules were prospectively studied at four institut

219 ignificantly enhanced antimetastatic effect: lung nodules were reduced by 7- to 24-fold by Cellax tre

220 16 radiographs that showed confirmed subtle lung nodules were selected.

221 Five hundred fifty lung nodules were studied.

222 Data from 311 consecutive patients with lung nodules who underwent (18)F-FDG PET/CT and CT-guide

223 etric measurement error in the assessment of lung nodules with CT would be a first step toward the de

224 lume (search effectiveness), the fraction of lung nodules within the GV gaze volume detected by the r