Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 88
Filtrar
1.
Eur Radiol ; 2021 Sep 03.
Artigo em Inglês | MEDLINE | ID: mdl-34476564

RESUMO

Dedicated breast CT is being increasingly used for breast imaging. This technique provides images with no compression, removal of tissue overlap, rapid acquisition, and available simultaneous assessment of microcalcifications and contrast enhancement. In this second installment in a 2-part review, the current status of clinical applications and ongoing efforts to develop new imaging systems are discussed, with particular emphasis on how to achieve optimized practice including lesion detection and characterization, response to therapy monitoring, density assessment, intervention, and implant evaluation. The potential for future screening with breast CT is also addressed. KEY POINTS: • Dedicated breast CT is an emerging modality with enormous potential in the future of breast imaging by addressing numerous clinical needs from diagnosis to treatment. • Breast CT shows either noninferiority or superiority with mammography and numerical comparability to MRI after contrast administration in diagnostic statistics, demonstrates excellent performance in lesion characterization, density assessment, and intervention, and exhibits promise in implant evaluation, while potential application to breast cancer screening is still controversial. • New imaging modalities such as phase-contrast breast CT, spectral breast CT, and hybrid imaging are in the progress of R & D.

2.
Eur J Radiol ; 142: 109878, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34388626

RESUMO

PURPOSE: To utilize a neural architecture search (NAS) approach to develop a convolutional neural network (CNN) method for distinguishing benign and malignant lesions on breast cone-beam CT (BCBCT). METHOD: 165 patients with 114 malignant and 86 benign lesions were collected by two institutions from May 2012 to August 2014. The NAS method autonomously generated a CNN model using one institution's dataset for training (patients/lesions: 71/91) and validation (patients/lesions: 20/23). The model was externally tested on another institution's dataset (patients/lesions: 74/87), and its performance was compared with fine-tuned ResNet-50 models and two breast radiologists who independently read the lesions in the testing dataset without knowing lesion diagnosis. RESULTS: The lesion diameters (mean ± SD) were 18.8 ± 12.9 mm, 22.7 ± 10.5 mm, and 20.0 ± 11.8 mm in the training, validation, and external testing set, respectively. Compared to the best ResNet-50 model, the NAS-generated CNN model performed three times faster and, in the external testing set, achieved a higher (though not statistically different) AUC, with sensitivity (95% CI) and specificity (95% CI) of 0.727, 80% (66-90%), and 60% (42-75%), respectively. Meanwhile, the performances of the NAS-generated CNN and the two radiologists' visual ratings were not statistically different. CONCLUSIONS: Our preliminary results demonstrated that a CNN autonomously generated by NAS performed comparably to pre-trained ResNet models and radiologists in predicting malignant breast lesions on contrast-enhanced BCBCT. In comparison to ResNet, which must be designed by an expert, the NAS approach may be used to automatically generate a deep learning architecture for medical image analysis.


Assuntos
Aprendizado Profundo , Mama , Tomografia Computadorizada de Feixe Cônico , Humanos , Redes Neurais de Computação , Radiologistas
3.
Eur Radiol ; 2021 Aug 03.
Artigo em Inglês | MEDLINE | ID: mdl-34342694

RESUMO

Dedicated breast CT is an emerging 3D isotropic imaging technology for breast, which overcomes the limitations of 2D compression mammography and limited angle tomosynthesis while providing some of the advantages of magnetic resonance imaging. This first installment in a 2-part review describes the evolution of dedicated breast CT beginning with a historical perspective and progressing to the present day. Moreover, it provides an overview of state-of-the-art technology. Particular emphasis is placed on technical limitations in scan protocol, radiation dose, breast coverage, patient comfort, and image artifact. Proposed methods of how to address these technical challenges are also discussed. KEY POINTS: • Advantages of breast CT include no tissue overlap, improved patient comfort, rapid acquisition, and concurrent assessment of microcalcifications and contrast enhancement. • Current clinical and prototype dedicated breast CT systems differ in acquisition modes, imaging techniques, and detector types. • There are still details to be decided regarding breast CT techniques, such as scan protocol, radiation dose, breast coverage, patient comfort, and image artifact.

4.
Acta Radiol ; : 2841851211027386, 2021 Jul 14.
Artigo em Inglês | MEDLINE | ID: mdl-34259021

RESUMO

BACKGROUND: Breast density is an independent predictor of breast cancer risk. Quantitative volumetric breast density (QVBD) is expected to provide more information on the prediction of breast cancer risk. PURPOSE: To evaluate the reliability of QVBD measurements based on cone-beam breast computed tomography (CBBCT) images. MATERIAL AND METHODS: A total of 216 breasts were used to evaluate the stability of QVBD measurements based on CBBCT images and the correlations between this volumetric measurement and visual and area-based measurement methods. The intra- and inter-observer consistency of QVBD measurements were compared. Visual breast density (VBD) was evaluated with Breast Imaging Reporting and Data System (BI-RADS) standard on CBBCT images. The correlation between QVBD and VBD was evaluated by Spearman correlation coefficient. Receiver operating characteristic (ROC) curve was used to assess the sensitivity and specificity of the volumetric method in distinguishing dense and non-dense breasts. The correlation between QVBD and quantitative area-based breast density (QABD) was determined with Pearson correlation coefficient. Then, the breast volume measured with CBBCT images was compared with the breast specimen obtained during nipple-sparing mastectomy (NSM) by Pearson correlation coefficient and linear regression. RESULTS: Excellent intra- and inter-observer consistency was found from QVBD measurements. The volumetric method distinguished dense and non-dense breasts at a cutoff value of 9.5%, with 94.5% sensitivity and 77.1% specificity. Positive correlations were found between QVBD and QABD (r=0.890; P<0.001) and between the volume measured with CBBCT images and Archimedes method (r=0.969; P<0.001). CONCLUSION: CBBCT images can evaluate breast density reliably on a continuous scale.

5.
Eur J Radiol ; 141: 109802, 2021 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-34090112

RESUMO

OBJECTIVES: To retrospectively investigate whether radiological and clinicopathological characteristics were associated with the presence of stage IA-IIA lung adenocarcinoma in patients at high risk for a postoperative recurrence. MATERIALS AND METHODS: Three hundred twelve patients with biopsy-proven node-negative early-stage (IA-IIA) lung adenocarcinoma met the inclusion criteria for this study. Demographics data and histopathological findings were collected from medical records. Computed tomography (CT) performed approximately 1 month before surgery was manually scored using 23 CT descriptors. Univariate analyses were applied to demonstrate an association between clinicopathological and radiological features and 2-/5-year recurrences. Multivariate logistic regression was performed to assess the ability of radiological and clinicopathological features to discriminate low and high-risk factors for recurrence. A ROC curve was used to evaluate prediction performance. RESULTS: Univariate analysis revealed that the 2-year recurrence was associated with six radiological features and two clinicopathological features, while 5-year recurrence was associated with five radiological features and two clinicopathological features. A multivariate logistic regression model of combined clinicopathological and radiological features showed that stage IIA (OR = 2.87), solid texture (solid part > 50 %: OR = 4.81; solid part = 100 %: OR = 3.61), pleural attachment (OR = 3.97) and bronchovascular bundle thickening (OR = 2.16) were associated with the independent predictors of 2-year recurrence, and stage IIA (OR = 3.52), solid texture (solid part > 50 %: OR = 3.56; solid part = 100 %: OR = 2.44) and pleural attachment (OR = 4.57) were associated with 5-year recurrence. Combined radiological and clinicopathological features could be significant indicators of 2- and 5-year recurrences (AUC = 0.784 and AUC = 0.815, respectively). CONCLUSIONS: The combination of radiological and clinicopathological features has the potential to help predict postoperative recurrence in patients with stage IA-IIA lung adenocarcinomas and guide oncologists and patients whether to undergo additional treatment after surgery.


Assuntos
Adenocarcinoma de Pulmão , Adenocarcinoma , Neoplasias Pulmonares , Adenocarcinoma/diagnóstico por imagem , Adenocarcinoma/patologia , Adenocarcinoma/cirurgia , Adenocarcinoma de Pulmão/diagnóstico por imagem , Adenocarcinoma de Pulmão/cirurgia , Humanos , Neoplasias Pulmonares/diagnóstico por imagem , Neoplasias Pulmonares/patologia , Neoplasias Pulmonares/cirurgia , Recidiva Local de Neoplasia/diagnóstico por imagem , Recidiva Local de Neoplasia/patologia , Estadiamento de Neoplasias , Prognóstico , Estudos Retrospectivos
6.
Artigo em Inglês | MEDLINE | ID: mdl-34131803

RESUMO

PURPOSE: To develop and evaluate the effectiveness of a deep learning framework (3D-ResNet) based on CT images to distinguish nontuberculous mycobacterium lung disease (NTM-LD) from Mycobacterium tuberculosis lung disease (MTB-LD). METHOD: Chest CT images of 301 with NTM-LD and 804 with MTB-LD confirmed by pathogenic microbiological examination were retrospectively collected. The differences between the clinical manifestations of the two diseases were analysed. 3D-ResNet was developed to randomly extract data in an 8:1:1 ratio for training, validating, and testing. We also collected external test data (40 with NTM-LD and 40 with MTB-LD) for external validation of the model. The activated region of interest was evaluated using a class activation map. The model was compared with three radiologists in the test set. RESULT: Patients with NTM-LD were older than those with MTB-LD, patients with MTB-LD had more cough, and those with NTM-LD had more dyspnoea, and the results were statistically significant (p < 0.05). The AUCs of our model on training, validating, and testing datasets were 0.90, 0.88, and 0.86, respectively, while the AUC on the external test set was 0.78. Additionally, the performance of the model was higher than that of the radiologist, and without manual labelling, the model automatically identified lung areas with abnormalities on CT > 1000 times more effectively than the radiologists. CONCLUSION: This study shows the efficacy of 3D-ResNet as a rapid auxiliary diagnostic tool for NTB-LD and MTB-LD. Its use can help provide timely and accurate treatment strategies to patients with these diseases.

7.
Hum Brain Mapp ; 42(11): 3470-3480, 2021 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-33939221

RESUMO

Working memory is a basic human cognitive function. However, the genetic signatures and their biological pathway remain poorly understood. In the present study, we tried to clarify this issue by exploring the potential associations and pathways among genetic variants, brain morphometry and working memory performance. We first carried out association analyses between 2-back accuracy and 212 image-derived phenotypes from 1141 Human Connectome Project (HCP) subjects using a linear mixed model (LMM). We found a significantly positive correlation between the left cuneus volume and 2-back accuracy (T = 3.615, p = 3.150e-4, Cohen's d = 0.226, corrected using family-wise error [FWE] method). Based on the LMM-based genome-wide association study (GWAS) on the HCP dataset and UK Biobank 33 k GWAS summary statistics, we identified eight independent single nucleotide polymorphisms (SNPs) that were reliably associated with left cuneus volume in both UKB and HCP dataset. Within the eight SNPs, we found a negative correlation between the rs76119478 polymorphism and 2-back accuracy accuracy (T = -2.045, p = .041, Cohen's d = -0.129). Finally, an LMM-based mediation analysis elucidated a significant effect of left cuneus volume in mediating rs76119478 polymorphism on the 2-back accuracy (indirect effect = -0.007, 95% BCa CI = [-0.045, -0.003]). These results were also replicated in a subgroup of Caucasians in the HCP population. Further fine mapping demonstrated that rs76119478 maps on intergene CTD-2315A10.2 adjacent to protein-encoding gene DAAM1, and is significantly associated with L3HYPDH mRNA expression. Our study suggested this new variant rs76119478 may regulate the working memory through exerting influence on the left cuneus volume.

8.
Medicine (Baltimore) ; 100(8): e24955, 2021 Feb 26.
Artigo em Inglês | MEDLINE | ID: mdl-33663135

RESUMO

ABSTRACT: To investigate the feasibility of arterial spin labeling (ASL) blood flow (BF) and its histogram analysis to distinguish early-stage nasopharyngeal carcinoma (NPC) from nasopharyngeal lymphoid hyperplasia (NPLH).Sixty-three stage T1 NPC patients and benign NPLH patients underwent ASL on a 3.0-T magnetic resonance imaging system. BF histogram parameters were derived automatically, including the mean, median, maximum, minimum, kurtosis, skewness, and variance. Absolute values were obtained for skewness and kurtosis (absolute value of skewness [AVS] and absolute value of kurtosis [AVK], respectively). The Mann-Whitney U test, receiver operating characteristic curve, and multiple logistic regression models were used for statistical analysis.The mean, maximum, and variance of ASL BF values were significantly higher in early-stage NPC than in NPLH (all P < 0.0001), while the median and AVK values of early-stage NPC were also significantly higher than those of NPLH (all P < 0.001). No significant difference was found between the minimum and AVS values in early-stage NPC compared with NPLH (P = 0.125 and P = 0.084, respectively). The area under the curve (AUC) of the maximum was significantly higher than those of the mean and median (P < 0.05). The AUC of variance was significantly higher than those of the other parameters (all P < 0.05). Multivariate analysis showed that variance was the only independent predictor of outcome (P < 0.05).ASL BF and its histogram analysis could distinguish early-stage NPC from NPLH, and the variance value was a unique independent predictor.


Assuntos
Circulação Cerebrovascular , Neoplasias de Cabeça e Pescoço/diagnóstico por imagem , Imageamento por Ressonância Magnética/métodos , Carcinoma Nasofaríngeo/diagnóstico por imagem , Estudos de Casos e Controles , Detecção Precoce de Câncer/métodos , Estudos de Viabilidade , Feminino , Humanos , Hiperplasia/diagnóstico por imagem , Doenças Linfáticas/diagnóstico por imagem , Masculino , Estudos Prospectivos , Curva ROC , Sensibilidade e Especificidade
9.
Med Phys ; 48(5): 2374-2385, 2021 May.
Artigo em Inglês | MEDLINE | ID: mdl-33580497

RESUMO

PURPOSE: The present study assessed the predictive value of peritumoral regions on three tumor tasks, and further explored the influence of peritumors with different sizes. METHODS: We retrospectively collected 333 samples of gastrointestinal stromal tumors from the Second Affiliated Hospital of Zhejiang University School of Medicine, and 183 samples of gastrointestinal stromal tumors from Tianjin Medical University Cancer Hospital. We also collected 211 samples of laryngeal carcinoma and 233 samples of nasopharyngeal carcinoma from the First Affiliated Hospital of Jinan University. The tasks of three tumor datasets were risk assessment (gastrointestinal stromal tumor), T3/T4 staging prediction (laryngeal carcinoma), and distant metastasis prediction (nasopharyngeal carcinoma), respectively. First, deep learning and radiomics were respectively used to construct peritumoral models, to study whether the peritumor had predictive value on three tumor datasets. Furthermore, we defined different sizes peritumors including fixed size (not considering tumor size) and adaptive size (according to average tumor radius) to explore the influence of peritumor of different sizes and types of tumors. Finally, we visualized the deep learning and radiomic models to observe the influence of the peritumor in three datasets. RESULTS: The performance of intra-peritumors are better than intratumors alone in three datasets. Specifically, the comparisons of area under receiver operating characteristic curve in the testing set between intra-peritumoral and intratumoral models are: 0.908 vs 0.873 (P value: 0.037) in gastrointestinal stromal tumor datasets, 0.796 vs 0.756 (P value: 0.188) in laryngeal carcinoma datasets and 0.660 vs 0.579 (P value: 0.431) in nasopharyngeal carcinoma datasets. Furthermore, for gastrointestinal stromal tumor datasets, deep learning is more stable to learn peritumors with both fixed and adaptive size than radiomics. For laryngeal carcinoma datasets, the intra-peritumoral radiomic model could make model performance more balanced. For nasopharyngeal carcinoma datasets, radiomics is also more suitable for modeling peritumors than deep learning. The size of the peritumor is critical in this task, and only the performance of 1.5 mm-4.5 mm peritumors is stable. CONCLUSIONS: Our results indicate that peritumors have additional predictive value in three tumor datasets through deep learning or radiomics. The definitions of the peritumoral region and artificial intelligence method also have great influence on the performance of the peritumor.


Assuntos
Aprendizado Profundo , Inteligência Artificial , Humanos , Curva ROC , Estudos Retrospectivos
10.
J Nucl Cardiol ; 2021 Feb 08.
Artigo em Inglês | MEDLINE | ID: mdl-33559092

RESUMO

Primary pericardial angiosarcoma is a rare malignant cardiac neoplasm with early metastasis and poor prognosis. There are currently no guidelines or effective therapeutic strategies. Here we report a case of a 22-year-old man who presented with chest pain, suffocation and transient syncope over the course of 4 months. Further workup showed a large mass in the right pericardium, histopathologic examination revealed angiosarcoma. The patient subsequently received a total of 8 cycles of chemotherapy (paclitaxel and doxorubicin). This patient has an overall survival of 1 year to date. The current examination methods and reported cases revealed that early detection of primary pericardial angiosarcoma with imaging examinations is critical for prognosis.

11.
AIDS Res Hum Retroviruses ; 37(9): 647-656, 2021 09.
Artigo em Inglês | MEDLINE | ID: mdl-33430682

RESUMO

Neuroimaging studies have focused mainly on human immunodeficiency virus (HIV)-infected adults or younger children, showing abnormal brain structures. In this study, we used voxel-based morphometry to investigate the brain integrity of HIV vertically infected adolescents. Twenty-five HIV vertically infected (HIV+) adolescents and 33 HIV-exposed, but uninfected (HIV-) and demographically matched controls participated in this study. T1 high-resolution anatomical magnetic resonance imaging images were obtained and segmented into gray matter (GM) and white matter (WM) segments. Then, population templates were derived from the entire imaging dataset using the diffeomorphic anatomical registration through exponentiated lie algebra (DARTEL) technique. Between-group GM and WM maps were contrasted using independent two-sample t-tests, with age and sex as nuisance regressors of no interest. Significant effects were identified using voxel-wise p < .001 and cluster-level p < .05 with a family-wise error correction. Whole brain volume between the groups did not demonstrate a significant difference. Relative to HIV- controls, the HIV+ adolescents demonstrated less GM in the bilateral cerebellum, right pallidum, right calcarine, left anterior cingulate cortex (ACC), and right superior occipital lobe. HIV+ adolescents also demonstrated less WM volume in the bilateral cerebellum, right brainstem, and left occipital lobe. Furthermore, the volume of the ACC was positively correlated with the Mini-Mental State Examination (MMSE) and the CD4 cell counts in the HIV+ adolescents. The age of highly active antiretroviral therapy (HAART) onset was positively correlated with GM volume in the right temporal lobe, left occipital lobe, and left precentral gyrus. In HIV+ adolescents, a pattern of less WM density and altered GM and WM volume suggests that early HIV infection combined with neurotoxicity effect of early HAART, a lack of viral control may have a significant effect on the brain structural integrity. The process of corpus callosum formation in the corpus callosum and the frontal WM is more susceptible to HIV infection. Altered ACC integrity may represent a promising biomarker of cognitive dysfunction following HIV infection.


Assuntos
Infecções por HIV , Substância Branca , Adolescente , Encéfalo/diagnóstico por imagem , Substância Cinzenta , Infecções por HIV/complicações , Humanos , Imageamento por Ressonância Magnética
12.
Cereb Cortex ; 31(2): 746-756, 2021 Jan 05.
Artigo em Inglês | MEDLINE | ID: mdl-32710107

RESUMO

Much evidence indicates the influence of the oxytocin receptor (OXTR) gene on autism spectrum disorders (ASDs), a set of disorders characterized by a range of deficits in prosocial behaviors, which are closely related to the personality trait of reward dependence (RD). However, we do not know the effect of the OXTR polygenic risk score for ASDs (OXTR-PRSASDs) on RD and its underlying neuroanatomical substrate. Here, we aimed to investigate associations among the OXTR-PRSASDs, gray matter volume (GMV), and RD in two independent datasets of healthy young adults (n = 450 and 540). We found that the individuals with higher OXTR-PRSASDs had lower RD and significantly smaller GMV in the right posterior insula and putamen. The GMV of this region showed a positive correlation with RD and a mediation effect on the association between OXTR-PRSASDs and RD. Moreover, the correlation map between OXTR-PRSASDs and GMV showed spatial correlation with OXTR gene expression. All results were highly consistent between the two datasets. These findings highlight a possible neural pathway by which the common variants in the OXTR gene associated with ASDs may jointly impact the GMV of the right posterior insula and putamen and further affect the personality trait of RD.

13.
Eur Radiol ; 31(2): 847-854, 2021 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-32803416

RESUMO

OBJECTIVE: To compare the classification based on contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) with that of contrast-enhanced CT and MRI (CECT/MRI) LI-RADS for liver nodules in patients at high risk of hepatocellular carcinoma. METHODS: Two hundred thirty-nine patients with 273 nodules were enrolled in this retrospective study. Each nodule was categorized according to the CEUS LI-RADS version 2017 and CECT/MRI LI-RADS version 2017. The diagnostic performance of CEUS and CECT/MRI was compared. The reference standard was histopathology diagnosis. Inter-modality agreement was assessed with Cohen's kappa. RESULTS: The inter-modality agreement for CEUS LI-RADS and CECT/MRI LI-RADS was fair with a kappa value of 0.319 (p < 0.001). The positive predictive values (PPVs) of hepatocellular carcinoma (HCC) in LR-5, LR-4, and LR-3 were 98.3%, 60.0%, and 25.0% in CEUS, and 95.9%, 65.7%, and 48.1% in CECT/MRI, respectively. The sensitivities and specificities of LR-5 for diagnosing HCC were 75.6% and 93.8% in CEUS, and 83.6% and 83.3% in CECT/MRI, respectively. The positive predictive values of non-HCC malignancy in CEUS LR-M and CECT/MRI LR-M were 33.9% and 93.3%, respectively. The sensitivity, specificity, and accuracy for diagnosing non-HCC malignancy were 90.9%, 84.5%, and 85.0% in CEUS LR-M and 63.6%, 99.6%, and 96.7% in CECT/MRI LR-M, respectively. CONCLUSIONS: The inter-modality agreement of the LI-RADS category between CEUS and CECT/MRI is fair. The positive predictive values of HCCs in LR-5 of the CEUS and CECT/MRI LI-RADS are comparable. CECT/MRI LR-M has better diagnostic performance for non-HCC malignancy than CEUS LR-M. KEY POINTS: • The inter-modality agreement for the final LI-RADS category between CEUS and CECT/MRI is fair. • The LR-5 of CEUS and CECT/MRI LI-RADS corresponds to comparable positive predictive values (PPVs) of HCC. For LR-3 and LR-4 nodules categorized by CECT/MRI, CEUS examination should be performed, at least if they can be detected on plain ultrasound. • CECT/MRI LR-M has better diagnostic performance for non-HCC malignancy than CEUS LR-M. For LR-M nodules categorized by CEUS, re-evaluation by CECT/MRI is necessary.


Assuntos
Carcinoma Hepatocelular , Neoplasias Hepáticas , Carcinoma Hepatocelular/diagnóstico por imagem , Meios de Contraste , Humanos , Neoplasias Hepáticas/diagnóstico por imagem , Imageamento por Ressonância Magnética , Estudos Retrospectivos , Tomografia Computadorizada por Raios X
14.
Eur Radiol ; 31(4): 2580-2589, 2021 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-33009590

RESUMO

OBJECTIVES: To investigate the association of contrast-enhanced cone beam breast CT (CE-CBBCT) features, immunohistochemical (IHC) receptors, and molecular subtypes in breast cancer. METHODS: In this retrospective study, patients who underwent preoperative CE-CBBCT and received complete IHC results were analyzed. CE-CBBCT features were evaluated by two radiologists. Observer reproducibility and feature reliability were assessed. The association between CE-CBBCT features, IHC receptors, and molecular subtypes was analyzed using the chi-square, Mann-Whitney, and Kruskal-Wallis tests. Multivariate logistic regression was performed to assess the ability of combined imaging features to discriminate molecular subtypes. ROC curve was used to evaluate prediction performance. RESULTS: A total of 240 invasive cancers identified in 211 women were enrolled. Molecular subtypes of breast cancer were significantly associated with focality number of lesions, lesion type, tumor size, lesion density, internal enhancement pattern, degree of lesion enhancement (ΔHU), mass shape, spiculation, calcifications, calcification distribution, and increased peripheral vascularity of lesion (all p < 0.005), some of which also helped to differentiate IHC receptor status. A multivariate logistic regression model showed that tumor size (odds ratio, OR = 1.244), mass shape (OR = 0.311), spiculation (OR = 0.159), and internal enhancement pattern (OR = 0.227) were associated with differentiation between luminal and non-luminal subtypes (AUC = 0.809). Combined CE-CBBCT features, including lesion type (OR = 0.118), calcifications (OR = 0.181), and ΔHU (OR = 0.962), could be significant indicators of triple-negative versus HER-2-enriched subtypes (AUC = 0.913). CONCLUSIONS: CE-CBBCT features have the potential to help predict IHC receptor status and distinguish molecular subtypes of breast cancer, which could in turn help to develop individual treatment decisions and prognosis predictions. KEY POINTS: • A total of 11 CE-CBBCT features were associated with molecular subtypes, some of which also helped to differentiate IHC receptor status. • Tumor size, irregular mass shape, spiculation, and internal enhancement pattern could help identify luminal subtype. • Lesion type, calcification, and ΔHU could be significant indicators of HER-2- enriched versus triple-negative breast cancers.


Assuntos
Neoplasias da Mama , Mama/diagnóstico por imagem , Neoplasias da Mama/diagnóstico por imagem , Tomografia Computadorizada de Feixe Cônico , Feminino , Humanos , Mamografia , Receptor ErbB-2 , Reprodutibilidade dos Testes , Estudos Retrospectivos
15.
Acad Radiol ; 28(6): e155-e164, 2021 06.
Artigo em Inglês | MEDLINE | ID: mdl-32507613

RESUMO

RATIONALE AND OBJECTIVES: To develop and validate a CT-based radiomics model for preoperative prediction of lymph node metastasis (LNM) in early stage gastric cancer (EGC). MATERIALS AND METHODS: Four hundred and sixty-three consecutive EGC patients were enrolled in this retrospective study. Radiomics features were extracted from portal venous phase CT scans. A radiomics signature was built based on highly reproducible features using the least absolute shrinkage and selection operator method. The predictive performance of radiomics signature was tested in the training and testing cohorts. Multivariate logistic regression analysis was conducted to build a radiomics-based model combined radiomics signature and lymph node status according to CT. Performance of the model was determined by its discrimination, calibration, and clinical usefulness. RESULTS: The radiomics signature comprised six robust features showed significant association with LNM in both cohorts. A radiomics model that incorporated radiomics signature and CT-reported lymph node status showed good calibration and discrimination in the training cohort (AUC = 0.91) and testing cohort (AUC = 0.89). Decision curve analysis confirmed the clinical utility of this model. CONCLUSION: The CT-based radiomics model showed favorable accuracy for prediction of LNM in EGC and may help to improve clinical decision-making.


Assuntos
Neoplasias Gástricas , Humanos , Linfonodos/diagnóstico por imagem , Metástase Linfática/diagnóstico por imagem , Estudos Retrospectivos , Neoplasias Gástricas/diagnóstico por imagem , Tomografia Computadorizada por Raios X
16.
Acad Radiol ; 28(1): 36-45, 2021 01.
Artigo em Inglês | MEDLINE | ID: mdl-32151538

RESUMO

RATIONALE AND OBJECTIVES: To describe the rational and design of a population-based comparative study. The objective of the study is to assess the screening performance of volume-based management of CT-detected lung nodule in comparison to diameter-based management, and to improve the effectiveness of CT screening for chronic obstructive pulmonary disease (COPD) and cardiovascular disease (CVD), in addition to lung cancer, based on quantitative measurement of CT imaging biomarkers in a Chinese screening setting. MATERIALS AND METHODS: A population-based comparative study is being performed, including 10,000 asymptomatic participants between 40 and 74 years old from Shanghai urban population. Participants in the intervention group undergo a low-dose chest and cardiac CT scan at baseline and 1 year later, and are managed according to NELCIN-B3 protocol. Participants in the control group undergo a low-dose chest CT scan according to the routine CT protocol and are managed according to the clinical practice. Epidemiological data are collected through questionnaires. In the fourth year from baseline, the diagnosis of the three diseases will be collected. RESULTS: The unnecessary referral rate will be compared between NELCIN-B3 and standard protocol for managing early-detected lung nodules. The effectiveness of quantitative measurement of CT imaging biomarkers for early detection of lung cancer, COPD and CVD will be evaluated. CONCLUSION: We expect that the quantitative assessment of the CT imaging biomarkers will reduce the number of unnecessary referrals for early detected lung nodules, and will improve the early detection of COPD and CVD in a Chinese urban population. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03988322. Registered on 14 June 2019.


Assuntos
Doenças Cardiovasculares , Neoplasias Pulmonares , Doença Pulmonar Obstrutiva Crônica , Adulto , Idoso , Doenças Cardiovasculares/diagnóstico por imagem , Doenças Cardiovasculares/epidemiologia , China/epidemiologia , Detecção Precoce de Câncer , Humanos , Neoplasias Pulmonares/diagnóstico por imagem , Neoplasias Pulmonares/epidemiologia , Pessoa de Meia-Idade , Doença Pulmonar Obstrutiva Crônica/diagnóstico por imagem , Doença Pulmonar Obstrutiva Crônica/epidemiologia , Tomografia Computadorizada por Raios X
17.
Cancer Manag Res ; 12: 12225-12238, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33273859

RESUMO

Rationale and Objectives: Evaluate ability of radiological semantic traits assessed on multi-window computed tomography (CT) to predict lung cancer risk. Materials and Methods: A total of 199 participants were investigated, including 60 incident lung cancers and 139 benign positive controls. Twenty lung window features and 2 mediastinal window features were extracted and scored on a point scale in three screening rounds. Multivariate logistic regression analysis was used to explore the association of these radiological traits with the risk of developing lung cancer. The areas under the receiver operating characteristic curve (AUROC), sensitivity, specificity, and positive predictive value (PPV) were computed to evaluate the best predictive model. Results: Combining mediastinal window-specific features with the lung window features-based model significantly improves performance compared to individual window features. Model performance is consistent both at baseline and the first follow-up scan, with an AUROC increased from 0.822 to 0.871 (p = 0.009) and from 0.877 to 0.917 (p = 0.008), respectively, for single to multi-window feature models. We also find that the multi-window CT based model showed better specificity and PPV, with PPV at the second follow-up scan improved to 0.953. Conclusion: We find combining window semantic features improves model performance in identifying cancerous nodules. We also find that lung window features are more informative compared to mediastinal features in predicting malignancy.

18.
Biomed Res Int ; 2020: 6287545, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33062689

RESUMO

An increasing number of patients infected with nontuberculous mycobacteria (NTM) are observed worldwide. However, it is challenging to identify NTM lung diseases from pulmonary tuberculosis (PTB) due to considerable overlap in classic manifestations and clinical and radiographic characteristics. This study quantifies both cavitary and bronchiectasis regions in CT images and explores a machine learning approach for the differentiation of NTM lung diseases and PTB. It involves 116 patients and 103 quantitative features. After the selection of informative features, a linear support vector machine performs disease classification, and simultaneously, discriminative features are recognized. Experimental results indicate that bronchiectasis is relatively more informative, and two features are figured out due to promising prediction performance (area under the curve, 0.84 ± 0.06; accuracy, 0.85 ± 0.06; sensitivity, 0.88 ± 0.07; and specificity, 0.80 ± 0.12). This study provides insight into machine learning-based identification of NTM lung diseases from PTB, and more importantly, it makes early and quick diagnosis of NTM lung diseases possible that can facilitate lung disease management and treatment planning.


Assuntos
Interpretação de Imagem Assistida por Computador/métodos , Aprendizado de Máquina , Infecções por Mycobacterium não Tuberculosas/diagnóstico por imagem , Tomografia Computadorizada por Raios X/métodos , Tuberculose Pulmonar/diagnóstico por imagem , Adulto , Idoso , Bronquiectasia/diagnóstico por imagem , Bronquiectasia/patologia , Feminino , Humanos , Pulmão/diagnóstico por imagem , Masculino , Pessoa de Meia-Idade , Infecções por Mycobacterium não Tuberculosas/classificação , Infecções por Mycobacterium não Tuberculosas/patologia , Micobactérias não Tuberculosas , Sensibilidade e Especificidade , Tuberculose Pulmonar/classificação , Tuberculose Pulmonar/patologia
19.
Neuroimage ; 222: 117283, 2020 11 15.
Artigo em Inglês | MEDLINE | ID: mdl-32828928

RESUMO

Converging evidence from both human and animal studies has highlighted the pervasive role of the neuropeptide arginine vasopressin (AVP), which is mediated by arginine vasopressin receptor 1A (AVPR1A), in both social and nonsocial learning and memory. However, the effect of genetic variants in AVPR1A on verbal learning and memory is unknown. The hippocampus is a heterogeneous structure that consists of several anatomically and functionally distinct subfields, and it is the principal target structure for the memory-enhancing effect of AVP. We tested the hypothesis that genetic variants in the RS3 and RS1 repeat polymorphisms may influence verbal learning and memory performance evaluated by the California Verbal Learning Test-II (CVLT-II) by modulating the gray matter volume (GMV) and resting-state functional connectivity (rsFC) of whole hippocampus and its subfields in a large cohort of young healthy subjects (n = 1001). Using a short/long classification scheme for the repeat length of RS3 and RS1, we found that the individuals carrying more short alleles of RS3-RS1 haplotypes had poorer learning and memory performance compared to that of those carrying more long alleles. We also revealed that individuals carrying more short alleles exhibited a significantly smaller GMV in the left cornu ammonis (CA)2/3 and weaker rsFC of the left CA2/3-bilateral thalamic (primarily in medial prefrontal subfields) compared to those carrying more long alleles. Furthermore, multiple mediation analysis confirmed that these two hippocampal imaging measures jointly and fully mediated the relationship between the genetic variants in AVPR1A RS3-RS1 haplotypes and the individual differences in verbal learning and memory performance. Our results suggest that genetic variants in AVPR1A RS3-RS1 haplotypes may affect verbal learning and memory performance in part by modulating the left hippocampal CA2/3 structure and its rsFC with the thalamus.


Assuntos
Aprendizagem/fisiologia , Memória/fisiologia , Receptores de Vasopressinas/genética , Adolescente , Adulto , Feminino , Genótipo , Hipocampo/fisiologia , Humanos , Masculino , Polimorfismo Genético/genética , Regiões Promotoras Genéticas/genética , Aprendizagem Verbal/fisiologia , Adulto Jovem
20.
Comput Methods Programs Biomed ; 196: 105620, 2020 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-32615493

RESUMO

BACKGROUND AND OBJECTIVE: To investigate the effect of the slab thickness in maximum intensity projections (MIPs) on the candidate detection performance of a deep learning-based computer-aided detection (DL-CAD) system for pulmonary nodule detection in CT scans. METHODS: The public LUNA16 dataset includes 888 CT scans with 1186 nodules annotated by four radiologists. From those scans, MIP images were reconstructed with slab thicknesses of 5 to 50 mm (at 5 mm intervals) and 3 to 13 mm (at 2 mm intervals). The architecture in the nodule candidate detection part of the DL-CAD system was trained separately using MIP images with various slab thicknesses. Based on ten-fold cross-validation, the sensitivity and the F2 score were determined to evaluate the performance of using each slab thickness at the nodule candidate detection stage. The free-response receiver operating characteristic (FROC) curve was used to assess the performance of the whole DL-CAD system that took the results combined from 16 MIP slab thickness settings. RESULTS: At the nodule candidate detection stage, the combination of results from 16 MIP slab thickness settings showed a high sensitivity of 98.0% with 46 false positives (FPs) per scan. Regarding a single MIP slab thickness of 10 mm, the highest sensitivity of 90.0% with 8 FPs/scan was reached before false positive reduction. The sensitivity increased (82.8% to 90.0%) for slab thickness of 1 to 10 mm and decreased (88.7% to 76.6%) for slab thickness of 15-50 mm. The number of FPs was decreasing with increasing slab thickness, but was stable at 5 FPs/scan at a slab thickness of 30 mm or more. After false positive reduction, the DL-CAD system, utilizing 16 MIP slab thickness settings, had the sensitivity of 94.4% with 1 FP/scan. CONCLUSIONS: The utilization of multi-MIP images could improve the performance at the nodule candidate detection stage, even for the whole DL-CAD system. For a single slab thickness of 10 mm, the highest sensitivity for pulmonary nodule detection was reached at the nodule candidate detection stage, similar to the slab thickness usually applied by radiologists.


Assuntos
Aprendizado Profundo , Neoplasias Pulmonares , Nódulo Pulmonar Solitário , Humanos , Neoplasias Pulmonares/diagnóstico por imagem , Interpretação de Imagem Radiográfica Assistida por Computador , Sensibilidade e Especificidade , Nódulo Pulmonar Solitário/diagnóstico por imagem
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA
...