Publications by authors named "Zhaoxiang Ye"

83 Publications

Quantitative breast density measurement based on three-dimensional images: a study on cone-beam breast computed tomography.

Acta Radiol 2021 Jul 14:2841851211027386. Epub 2021 Jul 14.

Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Tianjin, PR China.

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 (=0.890; <0.001) and between the volume measured with CBBCT images and Archimedes method (=0.969; <0.001).

Conclusion: CBBCT images can evaluate breast density reliably on a continuous scale.
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http://dx.doi.org/10.1177/02841851211027386DOI Listing
July 2021

Distinguishing nontuberculous mycobacteria from Mycobacterium tuberculosis lung disease from CT images using a deep learning framework.

Eur J Nucl Med Mol Imaging 2021 Jun 16. Epub 2021 Jun 16.

TCM Key Research Laboratory for Infectious Disease Prevention for State Administration of Traditional Chinese Medicine, Tianjin Institute of Respiratory Diseases, Haihe Hospital, Tianjin University, Tianjin, People's Republic of China.

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.
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http://dx.doi.org/10.1007/s00259-021-05432-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8205608PMC
June 2021

Association of postoperative recurrence with radiological and clinicopathological features in patients with stage IA-IIA lung adenocarcinoma.

Eur J Radiol 2021 Aug 29;141:109802. Epub 2021 May 29.

Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Key Laboratory of Cancer Prevention and Therapy, Huanhuxi Road, Hexi District, Tianjin, 300060, China. Electronic address:

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.
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http://dx.doi.org/10.1016/j.ejrad.2021.109802DOI Listing
August 2021

Cell-Type-Specific Gene Modules Related to the Regional Homogeneity of Spontaneous Brain Activity and Their Associations With Common Brain Disorders.

Front Neurosci 2021 20;15:639527. Epub 2021 Apr 20.

Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China.

Mapping gene expression profiles to neuroimaging phenotypes in the same anatomical space provides opportunities to discover molecular substrates for human brain functional properties. Here, we aimed to identify cell-type-specific gene modules associated with the regional homogeneity (ReHo) of spontaneous brain activity and their associations with brain disorders. Fourteen gene modules were consistently associated with ReHo in the three datasets, five of which showed cell-type-specific expression (one neuron-endothelial module, one neuron module, one astrocyte module and two microglial modules) in two independent cell series of the human cerebral cortex. The neuron-endothelial module was mainly enriched for transporter complexes, the neuron module for the synaptic membrane, the astrocyte module for amino acid metabolism, and microglial modules for leukocyte activation and ribose phosphate biosynthesis. In enrichment analyses of cell-type-specific modules for 10 common brain disorders, only the microglial module was significantly enriched for genes obtained from genome-wide association studies of multiple sclerosis (MS) and Alzheimer's disease (AD). The ReHo of spontaneous brain activity is associated with the gene expression profiles of neurons, astrocytes, microglia and endothelial cells. The microglia-related genes associated with MS and AD may provide possible molecular substrates for ReHo abnormality in both brain disorders.
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http://dx.doi.org/10.3389/fnins.2021.639527DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8093778PMC
April 2021

The morphometry of left cuneus mediating the genetic regulation on working memory.

Hum Brain Mapp 2021 Aug 3;42(11):3470-3480. Epub 2021 May 3.

Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China.

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.
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http://dx.doi.org/10.1002/hbm.25446DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8249898PMC
August 2021

Imaging Biomarkers to Predict and Evaluate the Effectiveness of Immunotherapy in Advanced Non-Small-Cell Lung Cancer.

Front Oncol 2021 19;11:657615. Epub 2021 Mar 19.

Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin, China.

Objective: We aimed to identify imaging biomarkers to assess predictive capacity of radiomics nomogram regarding treatment response status (responder/non-responder) in patients with advanced NSCLC undergoing anti-PD1 immunotherapy.

Methods: 197 eligible patients with histologically confirmed NSCLC were retrospectively enrolled from nine hospitals. We carried out a radiomics characterization from target lesions (TL) approach and largest target lesion (LL) approach on baseline and first follow-up (TP1) CT imaging data. Delta-radiomics feature was calculated as the relative net change in radiomics feature between baseline and TP1. Minimum Redundancy Maximum Relevance (mRMR) and Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression were applied for feature selection and radiomics signature construction.

Results: Radiomics signature at baseline did not show significant predictive value regarding response status for LL approach ( = 0.10), nor in terms of TL approach ( = 0.27). A combined Delta-radiomics nomogram incorporating Delta-radiomics signature with clinical factor of distant metastasis for target lesions had satisfactory performance in distinguishing responders from non-responders with AUCs of 0.83 (95% CI: 0.75-0.91) and 0.81 (95% CI: 0.68-0.95) in the training and test sets respectively, which was comparable with that from LL approach ( = 0.92, = 0.97). Among a subset of those patients with available pretreatment PD-L1 expression status (n = 66), models that incorporating Delta-radiomics features showed superior predictive accuracy than that of PD-L1 expression status alone (0.001).

Conclusion: Early response assessment using combined Delta-radiomics nomograms have potential advantages to identify patients that were more likely to benefit from immunotherapy, and help oncologists modify treatments tailored individually to each patient under therapy.
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http://dx.doi.org/10.3389/fonc.2021.657615DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8017283PMC
March 2021

CT-Based Radiomics Signature: A Potential Biomarker for Predicting Postoperative Recurrence Risk in Stage II Colorectal Cancer.

Front Oncol 2021 19;11:644933. Epub 2021 Mar 19.

Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Centre of Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.

To evaluate whether a radiomics signature could improve stratification of postoperative risk and prediction of chemotherapy benefit in stage II colorectal cancer (CRC) patients. This retrospective study enrolled 299 stage II CRC patients from January 2010 to December 2015. Based on preoperative portal venous-phase CT scans, radiomics features were generated and selected to build a radiomics score (Rad-score) using the Least Absolute Shrinkage and Selection Operator (LASSO) method. The minority group was balanced by the synthetic minority over-sampling technique (SMOTE). Predictive models were built with the Rad-score and clinicopathological factors, and the area under the curve (AUC) was used to evaluate their performance. A nomogram was also constructed for predicting 3-year disease-free survival (DFS). The performance of the nomogram was assessed with a concordance index (C-index) and calibration plots. Overall, 114 features were selected to construct the Rad-score, which was significantly associated with the 3-year DFS. Multivariate analysis demonstrated that the Rad-score, CA724 level, mismatch repair status, and perineural invasion were independent predictors of recurrence. Results showed that the Rad-score can classify patients into high-risk and low-risk groups in the training cohort (AUC 0.886) and the validation cohort (AUC 0.874). On this basis, a nomogram that integrated the Rad-score and clinical variables demonstrated superior performance (AUC 0.954, 0.906) than the clinical model alone (AUC 0.765, 0.705) in the training and validation cohorts, respectively. The C-index of the nomogram was 0.872, and the performance was acceptable. Our radiomics-based model can reliably predict recurrence risk in stage II CRC patients and potentially provide complementary prognostic value to the traditional clinicopathological risk factors for better identification of patients who are most likely to benefit from adjuvant therapy. The proposed nomogram promises to be an effective tool for personalized postoperative surveillance for stage II CRC patients.
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http://dx.doi.org/10.3389/fonc.2021.644933DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8017337PMC
March 2021

, , and as Prognostic Factors in Head and Neck Squamous Cell Carcinoma Are Involved in the Remodeling of the Tumor Microenvironment.

Front Oncol 2021 22;11:618187. Epub 2021 Feb 22.

Department of Radiology, The First Medical Centre, Chinese PLA General Hospital, Beijing, China.

The tumor microenvironment (TME) plays a critical role in the initiation and progression of cancer. However, the specific mechanism of its regulation in head and neck squamous cell carcinoma (HNSCC) remains unclear. In this study, we first applied the ESTIMATE method to calculate the immune and stromal scores in patients' tumor tissues from The Cancer Genome Atlas (TCGA) database. GSE41613, GSE30784, and GSE37991 data sets from the Gene Expression Omnibus (GEO) database were recruited for further validation. Differentially expressed genes (DEGs) were identified and then analyzed by Cox regression analysis and protein-protein interaction (PPI) network construction. DEGs significantly associated with prognosis and TME will be identified as hub genes. These genes were also validated at the protein level by immunohistochemical analysis of 10 pairs of primary tumor tissues and the adjacent normal tissues from our institution. The relationship between hub genes expression and immune cell fraction estimated by CIBERSORT software was also examined. 275 DEGs were significantly associated with TME. , and have then identified as hub genes by intersection Cox and PPI analysis. Further investigation revealed that the expression of , and was negatively correlated with clinicopathological characteristics (clinical stage, T stage) and positively associated with survival in HNSCC patients, especially in male patients. The expression of and was lower in males than in females. and were differentially expressed in tumor tissues than normal tissues, and the results were validated at the protein level by immunohistochemistry experiments. Gene set enrichment analysis (GSEA) showed that the high expression groups' hub genes were mainly enriched for immune-related activities. In the low-expression groups, genes were primarily enriched in metabolic pathways. CIBERSORT results showed that the expression of these genes was all negatively correlated with the fraction of memory B cells and positively correlated with the fraction of the other four cells, including naive B cells, resting T cells CD4 memory, T cells follicular helper, and T cells regulatory (Tregs). The results suggest that , and may be responsible for maintaining the immune dominance of TME, thus leading to a better prognosis.
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http://dx.doi.org/10.3389/fonc.2021.618187DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7937936PMC
February 2021

Using arterial spin labeling blood flow and its histogram analysis to distinguish early-stage nasopharyngeal carcinoma from lymphoid hyperplasia.

Medicine (Baltimore) 2021 Feb;100(8):e24955

Department of Radiology.

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.
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http://dx.doi.org/10.1097/MD.0000000000024955DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7909173PMC
February 2021

Exploring the predictive value of additional peritumoral regions based on deep learning and radiomics: A multicenter study.

Med Phys 2021 May 30;48(5):2374-2385. Epub 2021 Mar 30.

CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.

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.
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http://dx.doi.org/10.1002/mp.14767DOI Listing
May 2021

Primary pericardial angiosarcoma: A case report.

J Nucl Cardiol 2021 Feb 8. Epub 2021 Feb 8.

Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China.

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.
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http://dx.doi.org/10.1007/s12350-020-02470-0DOI Listing
February 2021

Study of Brain Structure in HIV Vertically Infected Adolescents.

AIDS Res Hum Retroviruses 2021 Feb 26. Epub 2021 Feb 26.

Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.

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 -tests, with age and sex as nuisance regressors of no interest. Significant effects were identified using voxel-wise  < .001 and cluster-level  < .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.
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http://dx.doi.org/10.1089/AID.2020.0030DOI Listing
February 2021

Multi-Window CT Based Radiological Traits for Improving Early Detection in Lung Cancer Screening.

Cancer Manag Res 2020 27;12:12225-12238. Epub 2020 Nov 27.

Department of Cancer Physiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.

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 ( = 0.009) and from 0.877 to 0.917 ( = 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.
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http://dx.doi.org/10.2147/CMAR.S246609DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7707434PMC
November 2020

Machine Learning-Based Differentiation of Nontuberculous Mycobacteria Lung Disease and Pulmonary Tuberculosis Using CT Images.

Biomed Res Int 2020 29;2020:6287545. Epub 2020 Sep 29.

Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin, China.

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.
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http://dx.doi.org/10.1155/2020/6287545DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7545409PMC
May 2021

Contrast-enhanced cone beam breast CT features of breast cancers: correlation with immunohistochemical receptors and molecular subtypes.

Eur Radiol 2021 Apr 2;31(4):2580-2589. Epub 2020 Oct 2.

Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Huan-Hu-Xi Road, Ti-Yuan-Bei, Hexi District, Tianjin, 300060, People's Republic of China.

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.
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http://dx.doi.org/10.1007/s00330-020-07277-8DOI Listing
April 2021

Neural mechanisms of AVPR1A RS3-RS1 haplotypes that impact verbal learning and memory.

Neuroimage 2020 11 20;222:117283. Epub 2020 Aug 20.

Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin 300052, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China. Electronic address:

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.
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http://dx.doi.org/10.1016/j.neuroimage.2020.117283DOI Listing
November 2020

Contrast-enhanced ultrasound LI-RADS 2017: comparison with CT/MRI LI-RADS.

Eur Radiol 2021 Feb 15;31(2):847-854. Epub 2020 Aug 15.

Department of Gastroenterology and Hepatology, Tianjin Institute of Hepatobiliary Disease, Tianjin Key Laboratory of Artificial Cell, Artificial Cell Engineering Technology Research Center of Public Health Ministry, Tianjin Third Central Hospital, Tianjin, 300170, China.

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.
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http://dx.doi.org/10.1007/s00330-020-07159-zDOI Listing
February 2021

Right Posterior Insula and Putamen Volume Mediate the Effect of Oxytocin Receptor Polygenic Risk for Autism Spectrum Disorders on Reward Dependence in Healthy Adults.

Cereb Cortex 2021 Jan;31(2):746-756

Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China.

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.
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http://dx.doi.org/10.1093/cercor/bhaa198DOI Listing
January 2021

Deep learning-based pulmonary nodule detection: Effect of slab thickness in maximum intensity projections at the nodule candidate detection stage.

Comput Methods Programs Biomed 2020 Nov 20;196:105620. Epub 2020 Jun 20.

Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.

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 F 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.
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http://dx.doi.org/10.1016/j.cmpb.2020.105620DOI Listing
November 2020

Assessment of the aggressiveness of rectal cancer using quantitative parameters derived from dual-energy computed tomography.

Clin Imaging 2020 Dec 17;68:136-142. Epub 2020 Jun 17.

Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, China. Electronic address:

Purpose: To evaluate the value of quantitative parameters derived from dual-energy computed tomography (DECT) in assessing the aggressiveness of rectal cancer.

Materials And Methods: Seventy-eight patients with rectal cancers confirmed by pathology underwent contrasted DECT scans. The normalized iodine concentration (NIC) and normalized water concentration (NWC) of the tumor against artery and tumor sizes were measured. The quantitative parameters were compared and statistically analyzed between subgroups based on the following prognostic factors: pretreatment carcinoembryonic antigen (CEA) levels, mesorectal fascia (MRF) status, T stage (T1,2 and T3,4), N stage (N0 and N1,2), tumor differentiation grade (poor differentiation, poor-moderate differentiation, moderate differentiation, moderate-well differentiation, well differentiation), and extramural venous invasion.

Results: The differences of NIC values between MRF-free and MRF-invaded groups (P = 0.042), between T2 and T3-4 stage groups (P = 0.044), between N0 and N+ (N1, 2) groups (P = 0.036), between poor differentiation group and other differentiated groups (P < 0.05)were respectively significant. No significant differences of NIC values existed between CEA level or extramural venous invasion subgroups. For NWC values and tumor sizes, there were no significant differences between subgroups based on the prognostic factors above all.

Conclusions: Higher NIC value is associated with a more aggressive tumor character. NIC value may have the potential to become an imaging biomarker of tumor aggressiveness.
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http://dx.doi.org/10.1016/j.clinimag.2020.06.028DOI Listing
December 2020

A CT-based Radiomics Model for Prediction of Lymph Node Metastasis in Early Stage Gastric Cancer.

Acad Radiol 2021 06 2;28(6):e155-e164. Epub 2020 Jun 2.

Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, Huanhuxi Road, Hexi District, Tianjin 300060, China; National Clinical Research Center for Cancer, Tianjin, China; Tianjin's Clinical Research Center for Cancer, Tianjin, China; The Key Laboratory of Cancer Prevention and Therapy, Tianjin, China. Electronic address:

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.
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http://dx.doi.org/10.1016/j.acra.2020.03.045DOI Listing
June 2021

MRI-Based Radiomics Signature: A Potential Biomarker for Identifying Glypican 3-Positive Hepatocellular Carcinoma.

J Magn Reson Imaging 2020 12 3;52(6):1679-1687. Epub 2020 Jun 3.

Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.

Background: Glypican 3 (GPC3) expression has proved to be a critical risk factor related to prognosis in hepatocellular carcinoma (HCC) patients.

Purpose: To investigate the performance of MRI-based radiomics signature in identifying GPC3-positive HCC.

Study Type: Retrospective.

Population: An initial cohort of 293 patients with pathologically confirmed HCC was involved in this study, and patients were randomly divided into training (195) and validation (98) cohorts.

Field Strength/sequences: Contrast-enhanced T -weight MRI was performed with a 1.5T scanner.

Assessment: A total of 853 radiomic features were extracted from the volume imaging. Univariate analysis and Fisher scoring were utilized for feature reduction. Subsequently, forward stepwise feature selection and radiomics signature building were performed based on a support vector machine (SVM). Incorporating independent risk factors, a combined nomogram was developed by multivariable logistic regression modeling.

Statistical Tests: The predictive performance of the nomogram was calculated using the area under the receive operating characteristic curve (AUC). Decision curve analysis (DCA) was applied to estimate the clinical usefulness.

Results: The radiomics signature consisting of 10 selected features achieved good prediction efficacy (training cohort: AUC = 0.879, validation cohort: AUC = 0.871). Additionally, the combined nomogram integrating independent clinical risk factor α-fetoprotein (AFP) and radiomics signature showed improved calibration and prominent predictive performance with AUCs of 0.926 and 0.914 in the training and validation cohorts, respectively.

Data Conclusion: The proposed MR-based radiomics signature is strongly related to GPC3-positive. The combined nomogram incorporating AFP and radiomics signature may provide an effective tool for noninvasive and individualized prediction of GPC3-positive in patients with HCC. J. MAGN. RESON. IMAGING 2020;52:1679-1687.
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http://dx.doi.org/10.1002/jmri.27199DOI Listing
December 2020

Nasopharyngeal carcinoma perfusion MRI: Comparison of arterial spin labeling and dynamic contrast-enhanced MRI.

Medicine (Baltimore) 2020 May;99(22):e20503

Department of Radiology.

To investigate the feasibility of 3D arterial spin labeling (ASL) as an alternative to dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for the qualitative and quantitative evaluation of nasopharyngeal carcinoma (NPC) perfusion.Fifty-two newly diagnosed NPC patients underwent 3D ASL and DCE-MRI scans on a 3.0-T MRI system. The visual qualitative evaluation of the NPC perfusion level was scored from 0 to 3 (0 = no contrast to normal peripheral soft tissue, 3 = pronounced contrast to normal peripheral soft tissue). The visual evaluation of the NPC outline was scored from 0 to 2 (0 = very vague outline, 2 = clear outline). Comparisons of the ASL-derived blood flow (BF) with the DCE-MRI-derived positive enhancement integral, maximum slope of increase, maximum slope of decrease, and time to peak (TTP) were conducted between NPC and non-NPC areas with independent samples t-tests. The diagnostic performance of these parameters was assessed by receiver operating characteristic curve analysis. The correlations between ASL BF and DCE parameters were assessed by Spearman correlation analysis.There was no difference in the visual scores of the NPC perfusion level between the 2 perfusion methods (P= .963). ASL had a lower visual score for describing the outline of NPC than DCE-MRI (P < .001). The ASL and DCE parameters of the NPC areas were significantly different from those of the non-NPC areas (P < .001). The ASL BF showed the largest area under the receiver operating characteristic curve (AUC) of 0.936 for identifying NPC. When all NPC and non-NPC areas were taken into account, significant correlations were observed between the ASL BF and the DCE parameters positive enhancement integral (r = 0.503, P < .001), maximum slope of increase (r = 0.616, P < .001), maximum slope of decrease (r = 0.380, P < .001), and TTP (r = -0.601, P < .001).3D ASL could reveal the hyperperfusion of NPC in a qualitative and quantitative manner without using contrast agent. Additionally, the ASL BF correlated significantly with the semiquantitative DCE-MRI parameters.
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http://dx.doi.org/10.1097/MD.0000000000020503DOI Listing
May 2020

Combination of diffusion-weighted imaging and arterial spin labeling at 3.0 T for the clinical staging of nasopharyngeal carcinoma.

Clin Imaging 2020 Oct 15;66:127-132. Epub 2020 May 15.

Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China. Electronic address:

Purpose: To probe the utility of diffusion-weighted imaging (DWI) and 3D arterial spin labeling (ASL) in assessing the clinical stage of nasopharyngeal carcinoma (NPC).

Materials And Methods: This prospective study included sixty-five newly diagnosed NPC patients who underwent DWI and 3D ASL scans on a 3.0-T magnetic resonance imaging (MRI) system. The apparent diffusion coefficient (ADC) and the tumor blood flow (TBF) of NPC were measured. Tumors were classified as low or high T, N and American Joint Committee on Cancer (AJCC) stages. Student's t-test was used to evaluate the differences between tumors with low and high clinical stages. Pearson correlation analyses were performed to determine the correlation between MRI parameters and clinical stages. Receiver operating characteristic (ROC) curves were then used to evaluate diagnostic capability.

Results: High T stage (T3/4) NPC showed significantly lower ADC (P = 0.000) and higher TBF (P = 0.003) and TBF (P = 0.008) values than low T stage (T1/2) NPC. High N stage (N2/3) NPC showed significantly lower ADC values (P = 0.023) than low N stage (N0/1) NPC. High AJCC stage (III/IV) NPC showed significantly lower ADC (P = 0.000) and higher TBF (P = 0.005) and TBF (P = 0.011) values than low AJCC stage (I/II) NPC. ADC values showed moderate negative correlations with T stage (r = -0.512, P = 0.000), N stage (r = -0.281, P = 0.023), and AJCC stage (r = -0.494, P = 0.000). TBF values showed moderate positive correlations with T stage (r = 0.369, P = 0.003) and AJCC stage (r = 0.346, P = 0.005). Compared with ADC and TBF alone, the combination of ADC and TBF improved the accuracy from 72.3% and 75.4% to 78.5%, respectively, for T staging, as well as from 72.3% and 69.2% to 83.1% for AJCC staging.

Conclusions: ADC and TBF values in patients with NPC could help evaluate clinical stages. ADC and TBF values combined could clearly improve the accuracy in the assessment of AJCC stage.
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http://dx.doi.org/10.1016/j.clinimag.2020.05.007DOI Listing
October 2020

A radiomics-based model for prediction of lymph node metastasis in gastric cancer.

Eur J Radiol 2020 Aug 18;129:109069. Epub 2020 May 18.

Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, Huanhuxi Road, Hexi District, Tianjin 300060, China; National Clinical Research Center for Cancer, Huanhuxi Road, Hexi District, Tianjin 300060, China; Tianjin's Clinical Research Center for Cancer, Huanhuxi Road, Hexi District, Tianjin 300060, China; The Key Laboratory of Cancer Prevention and Therapy, Huanhuxi Road, Hexi District, Tianjin 300060, China. Electronic address:

Purpose: To develop and validate a radiomics-based model for preoperative prediction of lymph node metastasis (LNM) in gastric cancer (GC).

Method: A total of 768 GC patients were enrolled in this retrospective study. Radiomics features were extracted from portal venous phase computed tomography (CT) scans. A radiomics signature was built with highly reproducible features using the least absolute shrinkage and selection operator (LASSO) method in the training cohort (n = 486). The signature was further validated in internal validation (n = 240) and external testing cohorts (n = 42). Multivariate logistic regression analysis was conducted to build a model that combined radiomics signature, serum biomarkers, and lymph node status according to CT. Performance of the model was determined by its discrimination, calibration, and clinical usefulness. The predictive value of the model was also evaluated in early stage GC (EGC) subgroup.

Results: The radiomics signature comprised 7 robust features showed favorable prediction efficacy in all cohorts. A radiomics-based model that incorporated radiomics signature, serum CA72-4, and CT-reported lymph node status had good calibration and discrimination in training cohort [AUC, 0.92; 95% confidence interval (CI), 0.89-0.95] and validation cohort (AUC 0.86; 95% CI, 0.81-0.91). The model also showed a favorable predictive performance for EGC patients with an AUC of 0.85 (95% CI, 0.76-0.94). Decision curve analysis confirmed the clinical utility of this model.

Conclusions: The radiomics-based model showed favorable accuracy for prediction of LNM in GC. The model may also serve as a noninvasive tool for preoperative evaluation of LNM in EGC.
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http://dx.doi.org/10.1016/j.ejrad.2020.109069DOI Listing
August 2020

A CT-based radiomics signature for evaluating tumor infiltrating Treg cells and outcome prediction of gastric cancer.

Ann Transl Med 2020 Apr;8(7):469

Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China.

Background: Tumor infiltrating regulatory T (TITreg) cells are highly infiltrated in gastric cancer (GC) and associated with worse prognosis of GC patients. We aim to develop and validate a radiomics signature for evaluation of TITreg cells and outcome prediction of GC patients.

Methods: A total of 165 GC patients from three independent cohorts were enrolled in this retrospective study. The abundance of TITreg cells were evaluated by using multispectral immunohistochemical analysis and CIBERSORT algorithm. The radiomics features were extracted by using PyRadiomics software and the radiomics signature was generated by using the least absolute shrinkage and selection operator (LASSO) logistic regression model. The receiver operator characteristic (ROC) curves were applied to assess the performance of radiomics signature for estimating TITreg cells. Univariable and multivariable Cox regression analysis were used for identifying risk factor of overall survival (OS). The prognostic value of the radiomics signature and the TITreg cells were evaluated by using the Kaplan-Meier method and log-rank test.

Results: Six robust features were selected for building the radiomics signature. The radiomics signature showed good ability for estimating TITreg in the training, validation and testing cohort, with area under the curve (AUC) of 0.884, 0.869 and 0.847, respectively. Multivariable Cox regression analysis showed that the radiomics signature was an independent risk factor of unfavorable OS of GC patients.

Conclusions: The proposed CT-based radiomics signature is a promising non-invasive biomarker of TITreg cells and outcome prediction of GC patients.
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http://dx.doi.org/10.21037/atm.2020.03.114DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7210140PMC
April 2020

Optimization of CT windowing for diagnosing invasiveness of adenocarcinoma presenting as sub-solid nodules.

Eur J Radiol 2020 Jul 25;128:108981. Epub 2020 Apr 25.

Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Centre of Cancer, Key Laboratory of Cancer Prevention and Therapy, Department of Radiology, Tianjin, People's Republic of China. Electronic address:

Purpose: To evaluate the optimal window setting to diagnose the invasiveness of lung adenocarcinoma in sub-solid nodules (SSNs).

Methods: We retrospectively included 437 SSNs and randomly divided them 3:1 into a training group (327) and a testing group (110). The presence of a solid component was regarded as indicator of invasiveness. At fixed window level (WL) of 35 Hounsfield Units (HU), two readers adjusted the window width (WW) in the training group and recorded once a solid component appeared or disappeared on CT images acquired at 120 kVp. The optimal WW cut-off value to differentiate between invasive and pre-invasive lesions, based on the receiver operating characteristic (ROC) curve, was defined as "core" WW. The diagnostic performances of the mediastinal window setting (WW/WL, 350/35 HU) and core window setting were then compared in the testing group.

Results: Of the 437 SSNs, 88 were pre-invasive [17 atypical adenomatous hyperplasia (AAH) and 71 adenocarcinoma in situ (AIS)], 349 were invasive [233 minimally invasive adenocarcinoma (MIA), 116 invasive adenocarcinoma (IA)]. In training group, the core WW of 1175 HU was the optimal cut-off to detect solid components of SSNs (AUC:0.79). In testing group, the sensitivity, specificity, positive, negative predictive value, and diagnostic accuracy for SSN invasiveness were 49.4%, 90.5%, 95.7%, 29.7%, and 57.3% for mediastinal window setting, and 87.6%, 76.2%, 91.6%, 76.2%, and 85.5% for core window setting.

Conclusion: At 120 kVp, core window setting (WW/WL, 1175/35 HU) outperformed the traditional mediastinal window setting to diagnose the invasiveness of SSNs.
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http://dx.doi.org/10.1016/j.ejrad.2020.108981DOI Listing
July 2020

Clinical characteristics and work-up of small to intermediate-sized pulmonary nodules in a Chinese dedicated cancer hospital.

Cancer Biol Med 2020 02;17(1):199-207

Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China.

To evaluate the characteristics and work-up of small to intermediate-sized pulmonary nodules in a Chinese dedicated cancer hospital. Patients with pulmonary nodules 4-25 mm in diameter detected computed tomography (CT) in 2013 were consecutively included. The analysis was restricted to patients with a histological nodule diagnosis or a 2-year follow-up period without nodule growth confirming benign disease. Patient information was collected from hospital records. Among the 314 nodules examined in 299 patients, 212 (67.5%) nodules in 206 (68.9%) patients were malignant. Compared to benign nodules, malignant nodules were larger (18.0 mm 12.5 mm, 0.001), more often partly solid (16.0% 4.7%, 0.001) and more often spiculated (72.2% 41.2%, 0.001), with higher density in contrast-enhanced CT (67.0 HU . 57.5 HU, = 0.015). Final diagnosis was based on surgery in 232 out of 314 (73.9%) nodules, 166 of which were identified as malignant [30 (18.1%) stage III or IV] and 66 as benign. In 36 nodules (11.5%), diagnosis was confirmed by biopsy and the remainder verified based on stability of nodule size at follow-up imaging ( = 46, 14.6%). Among 65 nodules subjected to gene (EGFR) mutation analyses, 28 (43.1%) cases (EGFR19 = 13; EGFR21 = 15) were identified as EGFR mutant and 37 (56.9%) as EGFR wild-type. Prior to surgery, the majority of patients [ = 194 (83.6%)] received a contrast-enhanced CT scan for staging of both malignant [ = 140 (84.3%)] and benign [ = 54 (81.8%)] nodules. Usage of positron emission tomography (PET)-CT was relatively uncommon [ = 38 (16.4%)]. CT-derived nodule assessment assists in diagnosis of small to intermediate- sized malignant pulmonary nodules. Currently, contrast-enhanced CT is commonly used as the sole diagnostic confirmation technique for pre-surgical staging, often resulting in surgery for late-stage disease and unnecessary surgery in cases of benign nodules.
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http://dx.doi.org/10.20892/j.issn.2095-3941.2019.0028DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7142837PMC
February 2020

A Subsolid Nodules Imaging Reporting System (SSN-IRS) for Classifying 3 Subtypes of Pulmonary Adenocarcinoma.

Clin Lung Cancer 2020 07 6;21(4):314-325.e4. Epub 2020 Feb 6.

Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Centre of Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, The People's Republic of China. Electronic address:

Objectives: To develop an imaging reporting system for the classification of 3 adenocarcinoma subtypes of computed tomography (CT)-detected subsolid pulmonary nodules (SSNs) in clinical patients.

Methods: Between November 2011 and October 2017, 437 pathologically confirmed SSNs were retrospectively identified. SSNs were randomly divided 2:1 into a training group (291 cases) and a testing group (146 cases). CT-imaging characteristics were analyzed using multinomial univariable and multivariable logistic regression analysis to identify discriminating factors for the 3 adenocarcinoma subtypes (pre-invasive lesions, minimally invasive adenocarcinoma, and invasive adenocarcinoma). These factors were used to develop a classification and regression tree model. Finally, an SSN Imaging Reporting System (SSN-IRS) was constructed based on the optimized classification model. For validation, the classification performance was evaluated in the testing group.

Results: Of the CT-derived characteristics of SSNs, qualitative density (nonsolid or part-solid), core (non-core or core), semantic features (pleural indentation, vacuole sign, vascular invasion), and diameter of solid component (≤6 mm or >6 mm), were the most important factors for the SSN-IRS. The total sensitivity, specificity, and diagnostic accuracy of the SSN-IRS was 89.0% (95% confidence interval [CI], 84.8%-92.4%), 74.6% (95% CI, 70.8%-78.1%), and 79.4% (95% CI, 76.5%-82.0%) in the training group and 84.9% (95% CI, 78.1%-90.3%), 68.5% (95% CI, 62.8%-73.8%), and 74.0% (95% CI, 69.6%-78.0%) in the testing group, respectively.

Conclusions: The SSN-IRS can classify 3 adenocarcinoma subtypes using CT-based characteristics of subsolid pulmonary nodules. This classification tool can help clinicians to make follow-up recommendations or decisions for surgery in clinical patients with SSNs.
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http://dx.doi.org/10.1016/j.cllc.2020.01.014DOI Listing
July 2020

Computed Tomography Screening for Early Lung Cancer, COPD and Cardiovascular Disease in Shanghai: Rationale and Design of a Population-based Comparative Study.

Acad Radiol 2021 01 6;28(1):36-45. Epub 2020 Mar 6.

Changzheng Hospital, Second Military Medical University, Department of Radiology, No. 415 Fengyang Rd, Shanghai 200003, The People's Republic of China. Electronic address:

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.
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http://dx.doi.org/10.1016/j.acra.2020.01.020DOI Listing
January 2021
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