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1.
J Thorac Imaging ; 35 Suppl 1: S35-S39, 2020 May.
Artigo em Inglês | MEDLINE | ID: mdl-32079905

RESUMO

PURPOSE: The purpose of this study was to validate the accuracy of an artificial intelligence (AI) prototype application in determining bone mineral density (BMD) from chest computed tomography (CT), as compared with dual-energy x-ray absorptiometry (DEXA). MATERIALS AND METHODS: In this Institutional Review Board-approved study, we analyzed the data of 65 patients (57 female, mean age: 67.4 y) who underwent both DEXA and chest CT (mean time between scans: 1.31 y). From the DEXA studies, T-scores for L1-L4 (lumbar vertebrae 1 to 4) were recorded. Patients were then divided on the basis of their T-scores into normal control, osteopenic, or osteoporotic groups. An AI algorithm based on wavelet features, AdaBoost, and local geometry constraints independently localized thoracic vertebrae from chest CT studies and automatically computed average Hounsfield Unit (HU) values with kVp-dependent spectral correction. The Pearson correlation evaluated the correlation between the T-scores and HU values. Mann-Whitney U test was implemented to compare the HU values of normal control versus osteoporotic patients. RESULTS: Overall, the DEXA-determined T-scores and AI-derived HU values showed a moderate correlation (r=0.55; P<0.001). This 65-patient population was divided into 3 subgroups on the basis of their T-scores. The mean T-scores for the 3 subgroups (normal control, osteopenic, osteoporotic) were 0.77±1.50, -1.51±0.04, and -3.26±0.59, respectively. The mean DEXA-determined L1-L4 BMD measures were 1.13±0.16, 0.88±0.06, and 0.68±0.06 g/cm, respectively. The mean AI-derived attenuation values were 145±42.5, 136±31.82, and 103±16.28 HU, respectively. Using these AI-derived HU values, a significant difference was found between the normal control patients and osteoporotic group (P=0.045). CONCLUSION: Our results show that this AI prototype can successfully determine BMD in moderate correlation with DEXA. Combined with other AI algorithms directed at evaluating cardiac and lung diseases, this prototype may contribute to future comprehensive preventative care based on a single chest CT.

2.
J Comput Assist Tomogr ; 43(6): 852-856, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31738204

RESUMO

OBJECTIVE: The objective of this study was to assess renal lesions measuring less than 20 Hounsfield units (HU) on noncontrast computed tomography (NCT). METHODS: Twenty-one (18.1%) of 116 consecutive pathologically proven renal cell carcinomas measured less than 20 HU on NCT and were compared with 40 confirmed benign cysts also measuring less than 20 HU. All lesions were assessed qualitatively (heterogeneous or homogenous) by 3 blinded readers and quantitatively with commercially available textural analysis software. Finally, a combined assessment was performed. RESULTS: Qualitative assessment performed well (sensitivity, 76%-90%; specificity, 70%-88%). Quantitative assessment revealed mean positive pixels as having the highest performance (area under the curve, 0.912; sensitivity, 90%; specificity, 80% at a cutoff value of 21). The combined assessment, using the mean positive pixel cutoff, improved the sensitivity (reader 1, 100%; reader 2, 95%; and reader 3, 95%). CONCLUSION: Qualitative and quantitative assessments have relatively good performance, but the combination can nearly eliminate renal cell carcinomas being missed on NCT.


Assuntos
Carcinoma de Células Renais/diagnóstico por imagem , Neoplasias Renais/diagnóstico por imagem , Interpretação de Imagem Radiográfica Assistida por Computador/métodos , Diagnóstico Diferencial , Feminino , Humanos , Doenças Renais Císticas/diagnóstico por imagem , Masculino , Projetos Piloto , Sensibilidade e Especificidade , Tomografia Computadorizada por Raios X
3.
Artigo em Inglês | MEDLINE | ID: mdl-31615736

RESUMO

OBJECTIVE: To evaluate the feasibility of dual-energy CT (DECT)-based iodine quantification to estimate myocardial extracellular volume (ECV) fraction in patients with and without cardiomyopathy (CM), as well as to assess its ability to distinguish healthy myocardial tissue from cardiomyopathic, with the goal of defining a threshold ECV value for disease detection. METHODS: Ten subjects free of heart disease and 60 patients with CM (mean age 66.4 ±â€¯9.4; 59 males and 11 females; 40 ischemic and 20 non-ischemic CM) underwent late iodine enhanced DECT imaging. Myocardial iodine maps were obtained using 3-material decomposition. ECV of the left ventricle was estimated from hematocrit levels and the iodine maps using the AHA 16-segment model. Receiver operating characteristic curve analysis was performed, with corresponding area under the curve, along with Youden's index assessment, to establish a threshold for CM detection. RESULTS: The median ECV for healthy myocardium, non-ischemic CM, and ischemic CM were 25.4% (22.9-27.3), 38.3% (33.7-43.0), and 36.9% (32.4-41.1), respectively. Healthy myocardium showed significantly lower ECV values compared to ischemic and non-ischemic CM (p < 0.001). From Youden's index analysis, an ECV>29.5% would indicate the presence of CM in the myocardium (sensitivity = 90.3; specificity = 90.3); the AUC for this criterion was 0.950 (p < 0.001). CONCLUSION: The findings of this study resulted in a statistically significant distinction between healthy myocardium and CM ECVs. This led to the establishment of a promising threshold ECV value that could facilitate the differentiation between healthy and diseased myocardium, and highlights the potential of this DECT methodology to detect cardiomyopathic tissue.

4.
Am J Cardiol ; 124(9): 1340-1348, 2019 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-31481177

RESUMO

This study investigated the impact of coronary CT angiography (cCTA)-derived plaque markers and machine-learning-based CT-derived fractional flow reserve (CT-FFR) to identify adverse cardiac outcome. Data of 82 patients (60 ± 11 years, 62% men) who underwent cCTA and invasive coronary angiography (ICA) were analyzed in this single-center retrospective, institutional review board-approved, HIPAA-compliant study. Follow-up was performed to record major adverse cardiac events (MACE). Plaque quantification of lesions responsible for MACE and control lesions was retrospectively performed semiautomatically from cCTA together with machine-learning based CT-FFR. The discriminatory value of plaque markers and CT-FFR to predict MACE was evaluated. After a median follow-up of 18.5 months (interquartile range 11.5 to 26.6 months), MACE was observed in 18 patients (21%). In a multivariate analysis the following markers were predictors of MACE (odds ratio [OR]): lesion length (OR 1.16, p = 0.018), low-attenuation plaque (<30 HU) (OR 4.59, p = 0.003), Napkin ring sign (OR 2.71, p = 0.034), stenosis ≥50% (OR 3.83, p 0.042), and CT-FFR ≤0.80 (OR 7.78, p = 0.001). Receiver operating characteristics analysis including stenosis ≥50%, plaque markers and CT-FFR ≤0.80 (Area under the curve 0.94) showed incremental discriminatory power over stenosis ≥50% alone (Area under the curve 0.60, p <0.0001) for the prediction of MACE. cCTA-derived plaque markers and machine-learning CT-FFR demonstrate predictive value to identify MACE. In conclusion, combining plaque markers with machine-learning CT-FFR shows incremental discriminatory power over cCTA stenosis grading alone.

5.
Eur J Radiol ; 117: 69-74, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31307655

RESUMO

PURPOSE: To investigate the protective effect of oral Vitamin C on DNA double-strand breaks (DSBs) after abdominal contrast-enhanced CT examination. MATERIALS AND METHODS: Sixty patients undergoing abdominal multiphase contrast-enhanced CT were divided into control group (n = 30) and prevention group (n = 30). Patients in the prevention group were orally administered 1 g Vitamin C 30-120 minutes prior to CT examination. Blood samples were obtained prior to and 5 min following CT examination for each subject. γ-H2AX foci representing DSBs in the nucleus of lymphocytes were marked by fluorescent markers. Change in γ-H2AX foci/cell was compared through Student t-tests or ANOVA testing. The relationship between physical parameters and increase in γ-H2AX foci was analyzed through Pearson or Spearman correlation analysis. RESULTS: The mean increase in γ-H2AX was 0.49 foci /cell in the control group and 0.19 foci/cell in the prevention group (p < 0.001), corresponding to a 61% reduction in the mean increase in γ-H2AX foci in the prevention group compared to the control group. In the prevention group, increase in γ-H2AX foci/cell positively correlated with dose length product and volume CT dose index (r = 0.449 and 0.403, respectively; both p < 0.05). No difference in the increase in γ-H2AX foci/cell was found between the different time interval subgroups of 30, 60, and 120 min between Vitamin C administration and CT examination (p > 0.05). CONCLUSION: Oral Vitamin C can significantly reduce the level of DSBs after abdominal contrast-enhanced CT examination and is a simple and effective method to decrease DNA damage.


Assuntos
Ácido Ascórbico/administração & dosagem , Ácido Ascórbico/farmacologia , Quebras de DNA de Cadeia Dupla/efeitos da radiação , Profilaxia Pré-Exposição , Radiografia Abdominal/efeitos adversos , Tomografia Computadorizada por Raios X/efeitos adversos , Idoso , Antioxidantes/administração & dosagem , Antioxidantes/farmacologia , Dano ao DNA , Relação Dose-Resposta à Radiação , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Projetos Piloto , Adulto Jovem
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