Publications by authors named "Dapeng Hao"

64 Publications

Resolving the spatial and cellular architecture of lung adenocarcinoma by multiregion single-cell sequencing.

Cancer Discov 2021 May 10. Epub 2021 May 10.

Pulmonary Medicine, UT-MD Anderson Cancer Center.

Little is known of the geospatial architecture of individual cell populations in lung adenocarcinoma (LUAD) evolution. Here, we perform single-cell RNA sequencing of 186,916 cells from 5 early-stage LUADs and 14 multi-region normal lung tissues of defined spatial proximities from the tumors. We show that cellular lineages, states, and transcriptomic features geospatially evolve across normal regions to LUADs. LUADs also exhibit pronounced intratumor cell heterogeneity within single sites and transcriptional lineage-plasticity programs. T regulatory cell phenotypes are increased in normal tissues with proximity to LUAD, in contrast to diminished signatures and fractions of cytotoxic CD8+ T cells, antigen-presenting macrophages and inflammatory dendritic cells. We further find that the LUAD ligand-receptor interactome harbors increased expression of epithelial CD24 which mediates pro-tumor phenotypes. These data provide a spatial atlas of LUAD evolution, and a resource for identification of targets for its treatment.
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http://dx.doi.org/10.1158/2159-8290.CD-20-1285DOI Listing
May 2021

Site percolation on square and simple cubic lattices with extended neighborhoods and their continuum limit.

Phys Rev E 2021 Feb;103(2-1):022126

Center for the Study of Complex Systems and Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan 48109-2800, USA.

By means of extensive Monte Carlo simulation, we study extended-range site percolation on square and simple cubic lattices with various combinations of nearest neighbors up to the eighth nearest neighbors for the square lattice and the ninth nearest neighbors for the simple cubic lattice. We find precise thresholds for 23 systems using a single-cluster growth algorithm. Site percolation on lattices with compact neighborhoods of connected sites can be mapped to problems of lattice percolation of extended objects of a given shape, such as disks and spheres, and the thresholds can be related to the continuum thresholds η_{c} for objects of those shapes. This mapping implies zp_{c}∼4η_{c}=4.51235 in two dimensions and zp_{c}∼8η_{c}=2.7351 in three dimensions for large z for circular and spherical neighborhoods, respectively, where z is the coordination number. Fitting our data for compact neighborhoods to the form p_{c}=c/(z+b) we find good agreement with this prediction, c=2^{d}η_{c}, with the constant b representing a finite-z correction term. We also examined results from other studies using this fitting formula. A good fit of the large but finite-z behavior can also be made using the formula p_{c}=1-exp(-2^{d}η_{c}/z), a generalization of a formula of Koza, Kondrat, and Suszcayński [J. Stat. Mech.: Theor. Exp. (2014) P110051742-546810.1088/1742-5468/2014/11/P11005]. We also study power-law fits which are applicable for the range of values of z considered here.
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http://dx.doi.org/10.1103/PhysRevE.103.022126DOI Listing
February 2021

Magnetic Resonance Imaging-Based Radiomics Nomogram for Prediction of the Histopathological Grade of Soft Tissue Sarcomas: A Two-Center Study.

J Magn Reson Imaging 2021 Jun 18;53(6):1683-1696. Epub 2021 Feb 18.

Department of Sports Medicine, the Affiliated Hospital of Qingdao University, QingDao, Shandong, 266003, China.

Background: Preoperative prediction of soft tissue sarcoma (STS) grade is important for treatment decisions. Therefore, formulation an STS grade model is strongly needed.

Purpose: To develop and test an magnetic resonance imaging (MRI)-based radiomics nomogram for predicting the grade of STS (low-grade vs. high grade).

Study Type: Retrospective POPULATION: One hundred and eighty patients with STS confirmed by pathologic results at two independent institutions were enrolled (training set, N = 109; external validation set, N = 71).

Field Strength/sequence: Unenhanced T1-weighted (T1WI) and fat-suppressed T2-weighted images (FS-T2WI) were acquired at 1.5 T and 3.0 T.

Assessment: Clinical-MRI characteristics included age, gender, tumor-node-metastasis (TNM) stage, American Joint Committee on Cancer (AJCC) stage, progression-free survival (PFS), and MRI morphological features (ie, margin). Radiomics feature extraction were performed on T1WI and FS-T2WI images by minimum redundancy maximum relevance (MRMR) method and least absolute shrinkage and selection operator (LASSO) algorithm. The selected features constructed three radiomics signatures models (RS-T1, RS-FST2, and RS-Combined). Univariate and multivariate logistic regression analysis were applied for screening significant risk factors. Radiomics nomogram was constructed by incorporating the radiomics signature and risk factors.

Statistical Tests: Clinical-MRI characteristics were performed by a univariate analysis. Model performances (discrimination, calibration, and clinical usefulness) were validated in the external validation set. The RS-T1 model, RS-FST2 model, and RS-Combined model had an area under curves (AUCs) of 0.645, 0.641, and 0.829, respectively, in the external validation set. The radiomics nomogram, incorporating significant risk factors and the RS-Combined model had AUCs of 0.916 (95%CI, 0.866-0.966, training set) and 0.879 (95%CI, 0.791-0.967, external validation set), and demonstrated good calibration and good clinical utility.

Data Conclusion: The proposed noninvasive MRI-based radiomics models showed good performance in differentiating low-grade from high-grade STSs.

Level Of Evidence: 3 TECHNICAL EFFICACY STAGE: 2.
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http://dx.doi.org/10.1002/jmri.27532DOI Listing
June 2021

NG-Circos: next-generation Circos for data visualization and interpretation.

NAR Genom Bioinform 2020 Sep 3;2(3):lqaa069. Epub 2020 Sep 3.

Division of Computational Biomedicine, Department of Biological Chemistry, School of Medicine, University of California, Irvine, CA 92697, USA.

Circos plots are widely used to display multi-dimensional next-generation genomic data, but existing implementations of Circos are not interactive with limited support of data types. Here, we developed next-generation Circos (NG-Circos), a flexible JavaScript-based circular genome visualization tool for designing highly interactive Circos plots using 21 functional modules with various data types. To our knowledge, NG-Circos is the most powerful software to construct interactive Circos plots. By supporting diverse data types in a dynamic browser interface, NG-Circos will accelerate the next-generation data visualization and interpretation, thus promoting the reproducible research in biomedical sciences and beyond. NG-Circos is available at https://wlcb.oit.uci.edu/NG-Circos and https://github.com/YaCui/NG-Circos.
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http://dx.doi.org/10.1093/nargab/lqaa069DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7671351PMC
September 2020

A CT-based radiomics nomogram for distinguishing between benign and malignant bone tumours.

Cancer Imaging 2021 Feb 6;21(1):20. Epub 2021 Feb 6.

Department of Radiology, The Affiliated Hospital of Qingdao University Qingdao, 16 Jiangsu Road, Qingdao, Shandong, China.

Background: We sought to evaluate the performance of a computed tomography (CT)-based radiomics nomogram we devised in distinguishing benign from malignant bone tumours.

Methods: Two hundred and six patients with bone tumours were spilt into two groups: a training set (n = 155) and a validation set (n = 51). A feature extraction process based on 3D Slicer software was used to extract the radiomics features from unenhanced CT images, and least absolute shrinkage and selection operator logistic regression was used to calculate the radiomic score to generate a radiomics signature. A clinical model comprised demographics and CT features. A radiomics nomogram combined with the clinical model and the radiomics signature was constructed. The performance of the three models was comprehensively evaluated from three aspects: identification ability, accuracy, and clinical value, allowing for generation of an optimal prediction model.

Results: The radiomics nomogram comprised clinical and radiomics signature features. The nomogram model displayed good performance in training and validation sets with areas under the curve of 0.917 and 0.823, respectively. The areas under the curve, decision curve analysis, and net reclassification improvement showed that the radiomics nomogram model could obtain better diagnostic performance than the clinical model and achieve greater clinical net benefits than the clinical and radiomics signature models alone.

Conclusions: We constructed a combined nomogram comprising a clinical model and radiomics signature as a noninvasive preoperative prediction method to distinguish between benign and malignant bone tumours and assist treatment planning.
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http://dx.doi.org/10.1186/s40644-021-00387-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7866630PMC
February 2021

Cisplatin prevents breast cancer metastasis through blocking early EMT and retards cancer growth together with paclitaxel.

Theranostics 2021 1;11(5):2442-2459. Epub 2021 Jan 1.

Cancer Center, Faculty of Health Sciences, University of Macau, Macau SAR, China.

Cancer growth is usually accompanied by metastasis which kills most cancer patients. Here we aim to study the effect of cisplatin at different doses on breast cancer growth and metastasis. We used cisplatin to treat breast cancer cells, then detected the migration of cells and the changes of epithelial-mesenchymal transition (EMT) markers by migration assay, Western blot, and immunofluorescent staining. Next, we analyzed the changes of RNA expression of genes by RNA-seq and confirmed the binding of activating transcription factor 3 (ATF3) to cytoskeleton related genes by ChIP-seq. Thereafter, we combined cisplatin and paclitaxel in a neoadjuvant setting to treat xenograft mouse models. Furthermore, we analyzed the association of disease prognosis with cytoskeletal genes and ATF3 by clinical data analysis. When administered at a higher dose (6 mg/kg), cisplatin inhibits both cancer growth and metastasis, yet with strong side effects, whereas a lower dose (2 mg/kg) cisplatin blocks cancer metastasis without obvious killing effects. Cisplatin inhibits cancer metastasis through blocking early steps of EMT. It antagonizes transforming growth factor beta (TGFβ) signaling through suppressing transcription of many genes involved in cytoskeleton reorganization and filopodia formation which occur early in EMT and are responsible for cancer metastasis. Mechanistically, TGFβ and fibronectin-1 (FN1) constitute a positive reciprocal regulation loop that is critical for activating TGFβ/SMAD3 signaling, which is repressed by cisplatin induced expression of ATF3. Furthermore, neoadjuvant administration of cisplatin at 2 mg/kg in conjunction with paclitaxel inhibits cancer growth and blocks metastasis without causing obvious side effects by inhibiting colonization of cancer cells in the target organs. Thus, cisplatin prevents breast cancer metastasis through blocking early EMT, and the combination of cisplatin and paclitaxel represents a promising therapy for killing breast cancer and blocking tumor metastasis.
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http://dx.doi.org/10.7150/thno.46460DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7797698PMC
January 2021

Single-cell dissection of intratumoral heterogeneity and lineage diversity in metastatic gastric adenocarcinoma.

Nat Med 2021 01 4;27(1):141-151. Epub 2021 Jan 4.

Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Intratumoral heterogeneity (ITH) is a fundamental property of cancer; however, the origins of ITH remain poorly understood. We performed single-cell transcriptome profiling of peritoneal carcinomatosis (PC) from 15 patients with gastric adenocarcinoma (GAC), constructed a map of 45,048 PC cells, profiled the transcriptome states of tumor cell populations, incisively explored ITH of malignant PC cells and identified significant correlates with patient survival. The links between tumor cell lineage/state compositions and ITH were illustrated at transcriptomic, genotypic, molecular and phenotypic levels. We uncovered the diversity in tumor cell lineage/state compositions in PC specimens and defined it as a key contributor to ITH. Single-cell analysis of ITH classified PC specimens into two subtypes that were prognostically independent of clinical variables, and a 12-gene prognostic signature was derived and validated in multiple large-scale GAC cohorts. The prognostic signature appears fundamental to GAC carcinogenesis and progression and could be practical for patient stratification.
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http://dx.doi.org/10.1038/s41591-020-1125-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8074162PMC
January 2021

Integrated genomic profiling and modelling for risk stratification in patients with advanced oesophagogastric adenocarcinoma.

Gut 2020 Dec 17. Epub 2020 Dec 17.

Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA

Objective: Prognosis of patients with advanced oesophagogastric adenocarcinoma (mEGAC) is poor and molecular determinants of shorter or longer overall survivors are lacking. Our objective was to identify molecular features and develop a prognostic model by profiling the genomic features of patients with mEGAC with widely varying outcomes.

Design: We profiled 40 untreated mEGACs (20 shorter survivors <13 months and 20 longer survivors >36 months) with whole-exome sequencing (WES) and RNA sequencing and performed an integrated analysis of exome, transcriptome, immune profile and pathological phenotypes to identify the molecular determinants, developing an integrated model for prognosis and comparison with The Cancer Genome Atlas (TCGA) cohorts.

Results: alterations were exclusively observed in shorter survivors together with high level of intratumour heterogeneity and complex clonal architectures, whereas the APOBEC mutational signatures were significantly enriched in longer survivors. Notably, the loss of heterozygosity in chromosome 4 (Chr4) was associated with shorter survival and 'cold' immune phenotype characterised by decreased B, CD8, natural killer cells and interferon-gamma responses. Unsupervised transcriptomic clustering revealed a shorter survivor subtype with distinct expression features (eg, upregulated druggable targets and ). An integrated model was then built based on clinical variables and the identified molecular determinants, which significantly segregated shorter and longer survivors. All the above features and the integrated model have been validated independently in multiple TCGA cohorts.

Conclusion: This study discovered novel molecular features prognosticating overall survival in patients with mEGAC and identified potential novel targets in shorter survivors.
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http://dx.doi.org/10.1136/gutjnl-2020-322707DOI Listing
December 2020

The Application of Three-Dimensional Technology Combined With Image Navigation in Nasal Skull Base Surgery.

J Craniofac Surg 2020 Nov/Dec;31(8):2304-2309

Department of Otorhinolaryngology Head and Neck Surgery.

Three-dimensional (3D) technology including 3D reconstruction and 3D printing technology, has been widely used in clinical treatment, especially in surgical planning, and image navigation technology, which can make surgical procedures more accurate, now is also increasingly favored by surgeons. But the combination of those 2 technologies was rarely reported. Thus, this study will preliminarily investigate the feasibility and the effect of the combination of 2 technologies in endonasal skull base surgery. Eight patients were involved in this study (from October 2016 to July 2017 at The Affiliated Hospital of Qingdao University), 5 cases of nasal skull base tumors and 3 cases of foreign body perforation. All operations were done under the assistance of 3D technology and image guidance system. Surgical discussion with patient, preoperative planning and clinical teaching were investigated between 2D images and 3D models by voting. For all cases, 3D reconstruction model and 3D printed model were deemed to be more helpful than CT/MRI images in surgical discussion with the patient; surgical simulation on 3D model in preoperative planning was largely deemed to be helpful and very helpful; and in clinical teaching, 3D models combined with image guidance system were deemed to be more helpful in understanding the disease than using 2D images. Besides, all patients recovered well after surgery, no recurrence and complications were found in the follow-up. The combination of 3D technology and electromagnetic image guidance system could improve surgical efficiency and the quality of clinical teaching.
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http://dx.doi.org/10.1097/SCS.0000000000006913DOI Listing
April 2021

An MRI-Based Radiomic Nomogram for Discrimination Between Malignant and Benign Sinonasal Tumors.

J Magn Reson Imaging 2021 01 9;53(1):141-151. Epub 2020 Aug 9.

Huangdao Hospital of Traditional Chinese Medicine, Qingdao, China.

Background: Preoperative discrimination between malignant and benign sinonasal tumors is important for treatment plan selection.

Purpose: To build and validate a radiomic nomogram for preoperative discrimination between malignant and benign sinonasal tumors.

Study Type: Retrospective.

Population: In all, 197 patients with histopathologically confirmed 84 benign and 113 malignant sinonasal tumors.

Field Strength/sequences: Fast-spin-echo (FSE) T -weighted and fat-suppressed FSE T -weighted imaging on a 1.5T and 3.0T MRI.

Assessment: T and fat-suppressed T -weighted images were selected for feature extraction. The least absolute shrinkage selection operator (LASSO) algorithm was applied to establish a radiomic score. Multivariate logistic regression analysis was applied to determine independent risk factors, and the radiomic score was combined to build a radiomic nomogram. The nomogram was assessed in a training dataset (n = 138/3.0T MRI) and tested in a validation dataset (n = 59/1.5T MRI).

Statistical Tests: Independent t-test or Wilcoxon's test, chi-square-test, or Fisher's-test, univariate analysis, LASSO, multivariate logistic regression analysis, area under the curve (AUC), Hosmer-Lemeshow test, decision curve, and the Delong test.

Results: In the validation dataset, the radiomic nomogram could differentiate benign from malignant sinonasal tumors with an AUC of 0.91. There was no significant difference in AUC between the combined radiomic score and radiomic nomogram (P > 0.05), and the radiomic nomogram showed a relatively higher AUC than the combined radiomic score. There was a significant difference in AUC between each two of the following models (the radiomic nomogram vs. the clinical model, all P < 0.001; the combined radiomic score vs. the clinical model, P = 0.0252 and 0.0035, respectively, in the training and validation datasets). The radiomic nomogram outperformed the radiomic scores and clinical model.

Data Conclusion: The radiomic nomogram combining the clinical model and radiomic score is a simple, effective, and reliable method for patient risk stratification.

Level Of Evidence: 4 TECHNICAL EFFICACY STAGE: 2.
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http://dx.doi.org/10.1002/jmri.27298DOI Listing
January 2021

Soft Tissue Sarcoma: Preoperative MRI-Based Radiomics and Machine Learning May Be Accurate Predictors of Histopathologic Grade.

AJR Am J Roentgenol 2020 10 29;215(4):963-969. Epub 2020 Jul 29.

Department of Radiology, The Affiliated Hospital of Qingdao University, Shinan Jiangsu 16 Rd, Qingdao, Shandong 266003, China.

The purpose of this study was to assess the value of radiomics features for differentiating soft tissue sarcomas (STSs) of different histopathologic grades. The T1-weighted and fat-suppressed T2-weighted MR images of 70 STSs of varying grades (35 low-grade [grades 1 and 2], 35 high-grade [grade 3]) formed the primary dataset used to train multiple machine learning algorithms for the construction of models for assigning STS grade. The models were tested with a separate validation dataset. Different machine learning algorithms had different strengths and weaknesses. The best classification algorithm for the prediction of STS grade had a combination of the least absolute shrinkage and selection operator feature selection method and the random forest classification algorithm (AUC, 0.9216; 95% CI, 0.8437-0.9995) in the validation set. The accuracy of the combined methods applied to the validation set was 91.43%; sensitivity, 88.24%; and specificity, 94.44%. Because of tumor heterogeneity, initial biopsy grade may be an underestimate of the final grade identified in extensive histopathologic analysis of surgical specimens. This creates an urgent need to construct an accurate preoperative approach to grading STS. This radiomics study revealed the optimal machine learning approaches for differentiating STS grades. This capability can enhance the precision of preoperative diagnosis.
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http://dx.doi.org/10.2214/AJR.19.22147DOI Listing
October 2020

Computed tomography and magnetic resonance imaging of adenoid cystic carcinoma in the maxillary sinus: a retrospective study with radiologic-histopathologic correlations.

Oral Surg Oral Med Oral Pathol Oral Radiol 2021 Jan 4;131(1):111-121. Epub 2020 Jul 4.

Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.

Objective: The aim of this study was to investigate computed tomography (CT) and magnetic resonance imaging (MRI) findings in adenoid cystic carcinoma (ACC) in the maxillary sinus and their correlations with the tubular, cribriform, and solid histopathologic types of ACC.

Study Design: Twenty cases of histopathologically proven ACC in the maxillary sinus were retrospectively reviewed. CT and MRI findings were correlated with histopathologic results.

Results: On CT, significant differences were discovered among the 3 histopathologic ACC types in range, size, shape, margins, type of bone destruction, and time intensity curve (TIC) (P ≤ .018). Tubular lesions were limited in range, were smaller than the other types, produced small cystic patterns with well-defined margins, and caused a cribriform pattern of bone destruction. All tumors demonstrated heterogeneous intensity signal on T1- and T2-weighted images (T1WI and T2WI) and appeared as hypo- or isointense small cystic lesions on T1WI and hyperintense on T2WI (n = 6). Postcontrast MRI revealed marked heterogeneous enhancement for all lesions. The TIC showed a rapidly enhancing and slow washout pattern in all tubular lesions and a rapidly enhancing and rapid washout pattern in solid tumors.

Conclusions: Different histologic patterns of ACCs have distinctive radiologic features, which can facilitate accurate preoperative diagnosis.
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http://dx.doi.org/10.1016/j.oooo.2020.06.019DOI Listing
January 2021

Efficacy of venetoclax in high risk relapsed mantle cell lymphoma (MCL) - outcomes and mutation profile from venetoclax resistant MCL patients.

Am J Hematol 2020 06 17;95(6):623-629. Epub 2020 Apr 17.

Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.

Venetoclax is effective in relapsed patients with mantle cell lymphoma (MCL). Mechanisms of resistance to venetoclax in MCL are poorly understood. We describe the clinical outcomes and genomic characteristics of 24 multiply relapsed patients (median of five prior lines of therapy) who received venetoclax-based therapies; 67% had progressed on BTK inhibitors (BTKi) and 54% had blastoid or pleomorphic histology. Median follow up after venetoclax treatment was 17 months. The overall response rate was 50% and complete response (CR) rate was 21%, 16 patients had progressed and 15 died. The median progression free, overall and post venetoclax survival were 8, 13.5 and 7.3 months respectively. Whole-exome sequencing (WES) was performed on samples collected from seven patients (including five pairs; before starting venetoclax and after progression on venetoclax). The SMARCA4 and BCL2 alterations were noted only after progression, while TP53, CDKN2A, KMT2D, CELSR3, CCND1, NOTCH2 and ATM were altered 2-4-fold more frequently after progression. In two patients with serial samples, we demonstrated clonal evolution of novel SMARCA4 and KMT2C/D mutations at progression. Mutation dynamics in venetoclax resistant MCL is demonstrated. Our data indicates that venetoclax resistance in MCL is predominantly associated with non-BCL2 gene mutations. Further studies are ongoing in MCL patients to evaluate the efficacy of venetoclax in combination with other agents and understand the biology of venetoclax resistance in MCL.
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http://dx.doi.org/10.1002/ajh.25796DOI Listing
June 2020

Preoperative MRI-Based Radiomic Machine-Learning Nomogram May Accurately Distinguish Between Benign and Malignant Soft-Tissue Lesions: A Two-Center Study.

J Magn Reson Imaging 2020 09 29;52(3):873-882. Epub 2020 Feb 29.

Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.

Background: Preoperative differentiation between malignant and benign soft-tissue masses is important for treatment decisions.

Purpose/hypothesis: To construct/validate a radiomics-based machine method for differentiation between malignant and benign soft-tissue masses.

Study Type: Retrospective.

Population: In all, 206 cases.

Field Strength/sequence: The T sequence was acquired with the following range of parameters: relaxation time / echo time (TR/TE), 352-550/2.75-19 msec. The T sequence was acquired with the following parameters: TR/TE, 700-6370/40-120 msec. The data were divided into a 3.0T training cohort, a 1.5T MR validation cohort, and a 3.0T external validationcohort.

Assessment: Twelve machine-learning methods were trained to establish classification models to predict the likelihood of malignancy of each lesion. The data of 206 cases were separated into a training set (n = 69) and two validation sets (n = 64, 73, respectively).

Statistical Tests: 1) Demographic characteristics: a one-way analysis of variance (ANOVA) test was performed for continuous variables as appropriate. The χ test or Fisher's exact test was performed for comparing categorical variables as appropriate. 2) The performance of four feature selection methods (least absolute shrinkage and selection operator [LASSO], Boruta, Recursive feature elimination [RFE, and minimum redundancy maximum relevance [mRMR]) and three classifiers (support vector machine [SVM], generalized linear models [GLM], and random forest [RF]) were compared for selecting the likelihood of malignancy of each lesion. The performance of the radiomics model was assessed using area under the receiver-operating characteristic curve (AUC) and accuracy (ACC) values.

Results: The LASSO feature method + RF classifier achieved the highest AUC of 0.86 and 0.82 in the two validation cohorts. The nomogram achieved AUCs of 0.96 and 0.88, respectively, in the two validation sets, which was higher than that of the radiomic algorithm in the two validation sets and clinical model of the validation 1 set (0.92, 0.88 respectively). The accuracy, sensitivity, and specificity of the radiomics nomogram were 90.5%, 100%, and 80.6%, respectively, for validation set 1; and 80.8%, 75.8%, and 85.0% for validation set 2.

Data Conclusion: A machine-learning nomogram based on radiomics was accurate for distinguishing between malignant and benign soft-tissue masses.

Evidence Level: 3 TECHNICAL EFFICACY: Stage 2 J. Magn. Reson. Imaging 2020;52:873-882.
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http://dx.doi.org/10.1002/jmri.27111DOI Listing
September 2020

Benign or Malignant Characterization of Soft-Tissue Tumors by Using Semiquantitative and Quantitative Parameters of Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

Can Assoc Radiol J 2020 Feb 24;71(1):92-99. Epub 2020 Jan 24.

Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China.

Purpose: To evaluate the efficacy of the semiquantitative and quantitative parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in differentiating between benign and malignant soft-tissue tumors.

Methods: A total of 45 patients with pathologically confirmed soft-tissue tumors (15 benign and 30 malignant tumors) underwent DCE-MRI. The semiquantitative parameters assessed were as follows: time to peak (TTP), maximum concentration (MAX Conc), area under the curve of time-concentration curve (AUC-TC), and maximum rise slope (MAX Slope). Quantitative DCE-MRI was analyzed with the extended Tofts-Kety model to assess the following quantitative parameters: volume transfer constant (Ktrans), microvascular permeability reflux constant (Kep), and distribute volume per unit tissue volume (Ve). Data were evaluated using the independent test or Mann-Whitney test and receiver operating characteristic (ROC) curves.

Results: The TTP ( = .0035), MAX Conc ( = .0018), AUC-TC ( = .0018), MAX Slope ( = .0018), Ktrans ( = .0018), and Kep ( = .0035) were significantly different between the benign and malignant soft-tissue tumors. The AUC of the ROC curve demonstrated the diagnostic potential of TTP (0.778), MAX Conc (0.849), AUC-TC (0.831), MAX Slope (0.847), Ktrans (0.836), Kep (0.778), and Ve (0.638).

Conclusions: The use of semiquantitative and quantitative parameters of DCE-MRI enabled differentiation between benign and malignant soft-tissue tumors. The values of TTP were lower, while those of MAX Conc, AUC-TC, MAX Slope, Ktrans, and Kep were higher in malignant than in benign tumors.
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http://dx.doi.org/10.1177/0846537119888409DOI Listing
February 2020

Reactive versus Constitutive: Reconcile the Controversial Results about the Prognostic Value of PD-L1 Expression in cancer.

Int J Biol Sci 2019 21;15(9):1933-1941. Epub 2019 Jul 21.

Faculty of Health Sciences, University of Macau, Macau, China.

The prognostic value of programmed death-ligand 1 (PD-L1) has been controversial in recent studies. PD-L1 is known to play a major role in suppressing the immune response, yet increasing studies have reported that PD-L1 expression has a favorable prognostic value for cancer patients. This raises the concern about how to understand PD-L1 expression: merely an immune inhibitory signal, or more likely a reactive process to T-cell response that indicates cytotoxic T lymphocyte (CTL) level in a tumor? To solve this dilemma, an integrative investigation is required. We compared the PD-L1 expression between tumor cells and immune cells, and characterized the inter- and intra-tumor correlation between CTL and PD-L1 expression. The prognostic values between PD-L1 and CTL is compared across 15 solid cancers and 11 independent cohorts of ovarian cancer. PD-L1 and PD-L1-adjusted CTL are analyzed in immunotherapy dataset receiving nivolumab. We observed unexpected high concordance between the prognostic value of PD-L1 and CTL across different cancers and cohorts. We found primarily reactive rather than constitutive PD-L1 expression in most tumors. We revealed that PD-L1-adjusted CTL level, rather than the expression of PD-L1, effectively predicts the responders to immune checkpoint inhibitors. This study highlights the importance of PD-L1 expression, as primarily a signature of reacting efficiency of pre-existing anti-tumor immunity, in balancing the tumor microenvironment. Importantly, it suggests that the reactive efficiency of PD-L1 is more useful to predict the response to immunotherapy.
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http://dx.doi.org/10.7150/ijbs.33297DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6743303PMC
April 2020

A CT-based radiomics nomogram for differentiation of renal angiomyolipoma without visible fat from homogeneous clear cell renal cell carcinoma.

Eur Radiol 2020 Feb 10;30(2):1274-1284. Epub 2019 Sep 10.

Urology Department, The Affiliated Hospital of Qingdao University, No. 16, Jiangsu Road, Qingdao, 266005, Shandong, China.

Objectives: To develop and validate a radiomics nomogram for preoperative differentiating renal angiomyolipoma without visible fat (AML.wovf) from homogeneous clear cell renal cell carcinoma (hm-ccRCC).

Methods: Ninety-nine patients with AML.wovf (n = 36) and hm-ccRCC (n = 63) were divided into a training set (n = 80) and a validation set (n = 19). Radiomics features were extracted from corticomedullary phase and nephrographic phase CT images. A radiomics signature was constructed and a radiomics score (Rad-score) was calculated. Demographics and CT findings were assessed to build a clinical factors model. Combined with the Rad-score and independent clinical factors, a radiomics nomogram was constructed. Nomogram performance was assessed with respect to calibration, discrimination, and clinical usefulness.

Results: Fourteen features were used to build the radiomics signature. The radiomics signature showed good discrimination in the training set (AUC [area under the curve], 0.879; 95%; confidence interval [CI], 0.793-0.966) and the validation set (AUC, 0.846; 95% CI, 0.643-1.000). The radiomics nomogram showed good calibration and discrimination in the training set (AUC, 0.896; 95% CI, 0.810-0.983) and the validation set (AUC, 0.949; 95% CI, 0.856-1.000) and showed better discrimination capability (p < 0.05) compared with the clinical factor model (AUC, 0.788; 95% CI, 0.683-0.893) in the training set. Decision curve analysis demonstrated the nomogram outperformed the clinical factors model and radiomics signature in terms of clinical usefulness.

Conclusions: The CT-based radiomics nomogram, a noninvasive preoperative prediction tool that incorporates the Rad-score and clinical factors, shows favorable predictive efficacy for differentiating AML.wovf from hm-ccRCC, which might assist clinicians in tailoring precise therapy.

Key Points: • Differential diagnosis between AML.wovf and hm-ccRCC is rather difficult by conventional imaging modalities. • A radiomics nomogram integrated with the radiomics signature, demographics, and CT findings facilitates differentiation of AML.wovf from hm-ccRCC with improved diagnostic efficacy. • The CT-based radiomics nomogram might spare unnecessary surgery for AML.wovf.
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http://dx.doi.org/10.1007/s00330-019-06427-xDOI Listing
February 2020

Large-scale integrated analysis of ovarian cancer tumors and cell lines identifies an individualized gene expression signature for predicting response to platinum-based chemotherapy.

Cell Death Dis 2019 09 10;10(9):661. Epub 2019 Sep 10.

School of Ophthalmology & Optometry and Eye Hospital, School of Biomedical Engineering, Wenzhou Medical University, Wenzhou, 325027, P. R. China.

Heterogeneity in chemotherapeutic response is directly associated with prognosis and disease recurrence in patients with ovarian cancer (OvCa). Despite the significant clinical need, a credible gene signature for predicting response to platinum-based chemotherapy and for guiding the selection of personalized chemotherapy regimens has not yet been identified. The present study used an integrated approach involving both OvCa tumors and cell lines to identify an individualized gene expression signature, denoted as IndividCRS, consisting of 16 robust chemotherapy-responsive genes for predicting intrinsic or acquired chemotherapy response in the meta-discovery dataset. The robust performance of this signature was subsequently validated in 25 independent tumor datasets comprising 2215 patients and one independent cell line dataset, across different technical platforms. The IndividCRS was significantly correlated with the response to platinum therapy and predicted the improved outcome. Moreover, the IndividCRS correlated with homologous recombination deficiency (HRD) and was also capable of discriminating HR-deficient tumors with or without platinum-sensitivity for guiding HRD-targeted clinical trials. Our results reveal the universality and simplicity of the IndividCRS as a promising individualized genomic tool to rapidly monitor response to chemotherapy and predict the outcome of patients with OvCa.
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http://dx.doi.org/10.1038/s41419-019-1874-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6737147PMC
September 2019

Radiomics and Machine Learning With Multiparametric Preoperative MRI May Accurately Predict the Histopathological Grades of Soft Tissue Sarcomas.

J Magn Reson Imaging 2020 03 5;51(3):791-797. Epub 2019 Sep 5.

Department of Radiology, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.

Background: Preoperative prediction of the grade of soft tissue sarcomas (STSs) is important because of its effect on treatment planning.

Purpose: To assess the value of radiomics features in distinguishing histological grades of STSs.

Study Type: Retrospective.

Population: In all, 113 patients with pathology-confirmed low-grade (grade I), intermediate-grade (grade II), or high-grade (grade III) soft tissue sarcoma were collected.

Field Strength/sequence: The 3.0T axial T -weighted imaging (T WI) with 550 msec repetition time (TR); 18 msec echo time (TE), 312 × 312 matrix, fat-suppressed fast spin-echo T WI with 4291 msec TR, 85 msec TE, 312 × 312 matrix.

Assessment: Multiple machine-learning methods were trained to establish classification models for predicting STS grades. Eighty STS patients (18 low-grade [grade I]; 62 high-grade [grades II-III]) were enrolled in the primary set and we tested the model with a validation set with 33 patients (7 low-grade, 26 high-grade).

Statistical Tests: 1) Student's t-tests were applied for continuous variables and the χ test were applied for categorical variables between low-grade STS and high-grade STS groups. 2) For feature subset selection, either no subset selection or recursive feature elimination was performed. This technology was combined with random forest and support vector machine-learning methods. Finally, to overcome the disparity in the frequencies of the STS grades, each machine-learning model was trained i) without subsampling, ii) with the synthetic minority oversampling technique, and iii) with random oversampling examples, for a total of 12 combinations of machine-learning algorithms that were assessed, trained, and tested in the validation cohort.

Results: The best classification model for the prediction of STS grade was a combination of features selected by recursive feature elimination and random forest classification algorithms with a synthetic minority oversampling technique, which had an area under the curve of 0.9615 (95% confidence interval 0.8944-1.0) in the validation set.

Data Conclusion: Radiomics feature-based machine-learning methods are useful for distinguishing STS grades.

Level Of Evidence: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:791-797.
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http://dx.doi.org/10.1002/jmri.26901DOI Listing
March 2020

Non-classical estrogen signaling in ovarian cancer improves chemo-sensitivity and patients outcome.

Theranostics 2019 31;9(13):3952-3965. Epub 2019 May 31.

Cancer Center, Faculty of health Sciences, University of Macau, Macau, SAR of the People's Republic of China.

Deficiency in homologous recombination repair (HRR) is frequently associated with hormone-responsive cancers, especially the epithelial ovarian cancer (EOC) which shows defects of HRR in up to half of cases. However, whether there are molecular connections between estrogen signaling and HRR deficiency in EOC remains unknown. : We analyzed the estrogen receptor α (ERα) binding profile in EOC cell lines and investigated its association with genome instability, HRR deficiency and sensitivity to chemotherapy using extensive public datasets and / experiments. : We found an inverse correlation between estrogen signaling and HRR activity in EOC, and the genome-wide collaboration between ERα and the co-repressor CtBP. Though the non-classical AP-1-mediated ERα signaling, their targets were highly enriched by HRR genes. We found that depleting ERα in EOC cells up-regulates HRR activity and HRR gene expression. Consequently, estrogen signaling enhances the sensitivity of ovarian cancer cells to chemotherapy agents and . Large-scale analyses further indicate that estrogen replacement and ESR1 expression are associated with chemo-sensitivity and the favorable survival of EOC patients. : These findings characterize a novel role of ERα in mediating the molecular connection between hormone and HRR in EOC and encourage hormone replacement therapy for EOC patients.
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http://dx.doi.org/10.7150/thno.30814DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6587348PMC
September 2020

miR-211 facilitates platinum chemosensitivity by blocking the DNA damage response (DDR) in ovarian cancer.

Cell Death Dis 2019 06 24;10(7):495. Epub 2019 Jun 24.

Department of Pathology, Harbin Medical University, Harbin, 150081, China.

The DNA damage response (DDR) is one of the most important mechanisms of platinum resistance in ovarian cancer. Some miRNAs have been identified to be involved in the regulatory network of DDR, thus the abnormal expression of miRNAs might affect platinum chemosensitivity in ovarian cancer. In this study, by assessing miRNAs simultaneously targeting a set of DDR genes that exhibited response to platinum, we found that miR-211 inhibited most of those genes, and proposed that miR-211 might affect the sensitivity of ovarian cancer cells to platinum by targeting multiple DDR genes and thereby determine the prognosis of ovarian cancer. To verify the hypothesis, we analyzed the association between miR-211 level and clinical prognosis, assessed the effect of miR-211 on DDR and platinum chemosensitivity, and explored the possible molecular mechanism. We revealed that miR-211 enhanced platinum chemosensitivity and was positively correlated with favorable outcomes in ovarian cancer patients. Many DDR genes including TDP1 were identified as targets of miR-211. In contrast, TDP1 suppressed DNA damage and platinum chemosensitivity. Moreover, the miR-211 level in tissues was shown to be associated with the good outcome of neoadjuvant chemotherapy and negatively correlated with the expression of TDP1. Conclusively, we demonstrated that miR-211 improves the prognosis of ovarian cancer patients by enhancing the chemosensitivity of cancer cells to platinum via inhibiting DDR gene expression, which provides an essential basis to identify novel treatment targets to block DDR effectively and improve chemosensitivity in ovarian cancer.
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http://dx.doi.org/10.1038/s41419-019-1715-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6591289PMC
June 2019

Radiomics nomogram for differentiating between benign and malignant soft-tissue masses of the extremities.

J Magn Reson Imaging 2020 01 6;51(1):155-163. Epub 2019 Jun 6.

Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.

Background: Preoperative differentiation between malignant and benign tumors is important for treatment decisions.

Purpose/hypothesis: To investigate/validate a radiomics nomogram for preoperative differentiation between malignant and benign masses.

Study Type: Retrospective.

Population: Imaging data of 91 patients.

Field Strength/sequence: T -weighted images (570 msec repetition time [TR]; 17.9 msec echo time [TE], 200-400 mm field of view [FOV], 208-512 × 208-512 matrix), fat-suppressed fast-spin-echo (FSE) T -weighted images (T WIs) (4331 msec TR; 87.9 msec TE, 200-400 mm FOV, 312 × 312 matrix), slice thickness 4 mm, and slice spacing 1 mm.

Assessment: Fat-suppressed FSE T WIs were selected for extraction of features. Radiomics features were extracted from fat-suppressed T WIs. A radiomics signature was generated from the training dataset using least absolute shrinkage and selection operator algorithms. Independent risk factors were identified by multivariate logistic regression analysis and a radiomics nomogram was constructed. Nomogram capability was evaluated in the training dataset and validated in the validation dataset. Performance of the nomogram, radiomics signature, and clinical model were compared.

Statistical Tests: 1) Independent t-test or Mann-Whitney U-test: for continuous variables. Fisher's exact test or χ test: comparing categorical variables between two groups. Univariate analysis: evaluating associations between clinical/morphological characteristics and malignancy. 2) Least absolute shrinkage and selection operator (LASSO)-logistic regression model: selection of malignancy features. 3) Significant clinical/morphological characteristics and radiomics signature were input variables for multiple logistic regression analysis. Area under the curve (AUC): evaluation of ability of the nomogram to identify malignancy. Hosmer-Lemeshow test and decision curve: evaluation and validation of nomogram results.

Results: The radiomics nomogram was able to differentiate malignancy from benignity in the training and validation datasets with an AUC of 0.94. The nomogram outperformed both the radiomics signature and clinical model alone.

Data Conclusion: This radiomics nomogram is a noninvasive, low-cost preoperative prediction method combining the radiomics signature and clinical model.

Level Of Evidence: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:155-163.
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http://dx.doi.org/10.1002/jmri.26818DOI Listing
January 2020

Correlations of Twist Expression with Pathological and Computed Tomography (CT) Characteristics and Prognosis of Non-Small Cell Lung Cancer (NSCLC).

Med Sci Monit 2019 Feb 4;25:977-983. Epub 2019 Feb 4.

Department of Radiology, Shengli Oilfield Central Hospital, Dongying, Shandong, China (mainland).

BACKGROUND The aim of this study was to assess the correlations of Twist expression with pathological and computed tomography (CT) characteristics and prognosis of non-small cell lung cancer (NSCLC). MATERIAL AND METHODS We enrolled 120 patients with lung cancer who underwent CT examination. The Twist protein expression level was detected in 120 cases of cancer tissues and a control group using immunohistochemical method. The survival curve was plotted using the Kaplan-Meier method and analyzed via log-rank test. RESULTS The Twist expression was associated with tumor stage, differentiation degree, and presence or absence of lymph node metastasis, but had no correlations with sex, age, or histological type. Grade-3 bronchial involvement, pleural indentation, and hilar and mediastinal lymph node enlargement occurred more frequently in the high-expression Twist group compared with the low-expression Twist group. The overall survival rate of patients with Twist overexpression was significantly lower than that of patients with normal Twist expression. The mean survival time was 69.8 months in Twist protein expression-negative patients and 45.8 months in Twist protein expression-positive patients. Finally, the positive expression of Twist protein was significantly correlated with the long-term survival and prognosis of patients. CONCLUSIONS The Twist gene might be involved in the occurrence and development of NSCLC, which is correlated with patient prognosis.
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http://dx.doi.org/10.12659/MSM.912674DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371739PMC
February 2019

An Analysis of the Expression and Association with Immune Cell Infiltration of the cGAS/STING Pathway in Pan-Cancer.

Mol Ther Nucleic Acids 2019 Mar 20;14:80-89. Epub 2018 Nov 20.

Department of Pathology, Harbin Medical University, Harbin 150081, China; North China Translational Medicine Research and Cooperation Center (NTMRC), Harbin 150081, China. Electronic address:

Recent evidence shows that cyclic GMP-AMP synthase (cGAS)/stimulator of interferon (IFN) genes (STING) signaling is essential for antitumor immunity by inducing the production of type I IFN and thus activating both innate and adaptive immunity based on gene knockout mouse models. However, the extensive detection of the expression of cGAS/STING signaling in human cancer and mining the roles of this signaling pathway in human cancer immunity have not been performed until now. In this study, we revealed that four key molecules (cGAS, STING, TANK binding kinase 1 [TBK1], and IFN regulatory factor 3 [IRF3]) in the cGAS/STING signaling are highly expressed in cancer tissues, and the expression levels of these genes are negatively correlated with their methylation levels in most of the detected cancer types. We also showed that highly upregulated cGAS/STING signaling is negatively correlated with the infiltration of immune cells in some tumor types, and consistent with these findings, we showed that a high level of cGAS/STING signaling predicts a poor prognosis in patients with certain cancers. This study suggests that it is necessary to deeply and fully evaluate the function of cGAS/STING signaling in cancer immunity and cancer progression before the application of the STING agonist-based anticancer immune therapy in the clinic.
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http://dx.doi.org/10.1016/j.omtn.2018.11.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6305687PMC
March 2019

CtBP promotes metastasis of breast cancer through repressing cholesterol and activating TGF-β signaling.

Oncogene 2019 03 15;38(12):2076-2091. Epub 2018 Nov 15.

Cancer Center, Faculty of Health Sciences, University of Macau, Macau, China.

Metastasis is the process through which the primary cancer cells spread beyond the primary tumor and disseminate to other organs. Most cancer patients die of metastatic disease. EMT is proposed to be the initial event associated with cancer metastasis and how it occurred is still a mystery. CtBP is known as a co-repressor abundantly expressed in many types of cancer and regulates genes involved in cancer initiation, progression, and metastasis. We found that CtBP regulates intracellular cholesterol homeostasis in breast cancer cells by forming a complex with ZEB1 and transcriptionally repressing SREBF2 expression. Importantly, CtBP repression of intracellular cholesterol abundance leads to increased EMT and cell migration. The reason is that cholesterol negatively regulates the stability of TGF-β receptors on the cell membrane. Interestingly, TGF-β is also capable of reducing intracellular cholesterol relying on the increased recruitment of ZEB1 and CtBP complex to SREBF2 promoter. Thus, we propose a feedback loop formed by CtBP, cholesterol, and TGF-β signaling pathway, through which TGF-β triggers the cascade that mobilizes the cancer cells for metastasis. Consistently, the intravenous injection of breast cancer cells with ectopically CtBP expression show increased lung metastasis depending on the reduction of intracellular cholesterol. Finally, we analyzed the public breast cancer datasets and found that CtBP expression negatively correlates with SREBF2 and HMGCR expressions. High expression of CtBP and low expression of SREBF2 and HMGCR significantly correlates with high EMT of the primary tumors.
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http://dx.doi.org/10.1038/s41388-018-0570-zDOI Listing
March 2019

MRI Findings of Early Myositis Ossificans without Calcification or Ossification.

Biomed Res Int 2018 3;2018:4186324. Epub 2018 Sep 3.

Department of Radiology, The Affiliated Hospital of Qingdao University Qingdao, Shandong, China.

Purpose: To characterize and evaluate the MR imaging features of early myositis ossificans (MO) without calcification or ossification.

Methods: The MRI manifestations of seven patients with pathologically proven early MO were retrospectively analyzed with regard to tumor location, size, margins, signal intensity, and enhancement appearance in MR images. Additionally, the surrounding soft-tissue edema and adjacent bone change were assessed.

Results: All cases (n=7) had intramuscular tumor-like masses without calcifications. The lesions appeared as isointense in T1-weighted images (T1-WI) and inhomogeneous hyperintense in T2-weighted MR images (T2-WI). On T2-WI and postcontrast T1-WI, the heterogeneously high signal intensity in the expanded muscle interspersed with a few hypointense linear structures consistent with intact muscle fibers showed "striate pattern" in the plane parallel with muscle fibers. The relatively hypointense areas with geometrical pattern consistent with the bundles of intact muscle fibers are found within the lesion with diffuse high signal intensity, displaying the "checkerboard-like pattern" in the plane vertical to muscle fibers. A "striate pattern" (n = 7) and "checkerboard-like pattern" (n = 3) in the lesion appeared in T2-WI. In contrast-enhanced MRI images, all cases showed diffuse "striate pattern" enhancement. Among them, one case demonstrated "checkerboard-like pattern" enhancement. All cases had diffuse and prominent muscle edema that preserved the muscle fascicles. For two lesions located in the deep muscle group, the adjacent bone showed bone marrow edema.

Conclusion: MR imaging has unique advantages for diagnosis of early MO without calcification or ossification: the "striate pattern" and "checkerboard-like pattern" appearance shown in T2-WI and contrast-enhanced MRI images can be helpful for differential diagnosis. MRI can delineate the extent of the tumor and provides accurate anatomical information, which is important in diagnosis, treatment, and follow-up.
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http://dx.doi.org/10.1155/2018/4186324DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6140134PMC
January 2019

The rotating stretched curved planar reconstruction of 3D-FIESTA MR imaging for evaluating the anterior cruciate ligament of the knee joint.

Magn Reson Imaging 2019 01 14;55:46-51. Epub 2018 Sep 14.

The Department of Radiology, Qingdao Municipal Hospital, Qingdao 266003, China.

Purpose: To determine the feasibility of the rotating stretched curved planar reconstruction (CPR) of three-dimensional fast imaging with steady-state acquisition magnetic resonance imaging (3D-FIESTA MRI) for evaluating the anterior cruciate ligament of the knee joint.

Materials And Methods: MRI of 40 knee joints in healthy volunteers was performed on a 3.0-T MR scanner and a phased-array extremity coil. The protocol consisted of oblique sagittal spin echo (SE) T1WI, coronal FS-PDWI, axial FS-FSE-T2WI, and 3D-FIESTA sequences. The rotating stretched curved planar reconstructions (CPR) of the ACL at angles of 0°, 30°, 60°, 90°, 120°, 150°, and 180° were generated from images of 3D-FIESTA sequences. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of the 3D-FIESTA were compared with those of the oblique sagittal SE T1WI sequence. The presence of the tibial attachment, midportion, femoral attachment, and double bundles of the ACL on the oblique sagittal SE T1WI and CPR of 3D-FIESTA MR imaging were divided into two categories: visible and not visible.

Results: The ACL SNR efficiency of 3D-FIESTA sequences was significantly higher than that of oblique sagittal SE T1WI sequence (P < 0.05). The 3D-FIESTA sequences produced images with a significantly higher CNR between ACL and synovial fluid than did the oblique sagittal SE T1WI sequence (P < 0.05). CPR of 3D-FIESTA MRI generated an excellent visualization of the ACL. The CPR of 3D-FIESTA MRI was rated superior to oblique sagittal SE T1WI sequence in 60% and 65% of cases with regard to the tibial attachment and midportion of ACL, respectively (P < 0.05). CPR of 3D-FIESTA MR imaging was rated superior to oblique sagittal SE T1WI sequence in 80% and 85% of cases with regard to femoral attachment and double bundles of ACL, respectively (P < 0.05).

Conclusion: The rotating stretched curved planar reconstruction of 3D-FIESTA sequences is significantly better than that of conventional 2D-MRI in evaluating the native ACL and its components, AM bundle and PL bundle, in healthy volunteers.
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http://dx.doi.org/10.1016/j.mri.2018.09.013DOI Listing
January 2019

Clinical significance of the immune microenvironment in ovarian cancer patients.

Mol Omics 2018 10;14(5):341-351

College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.

Ovarian cancer is one of the leading causes of death from gynecologic malignancy in women. High-grade serous carcinomas, low-grade serous carcinomas, endometrioid carcinomas, clear cell carcinomas, and mucinous carcinomas with distinct pathological and clinical characteristics are the main histological subtypes of ovarian cancer. The majority of ovarian cancer patients are diagnosed at an advanced stage due to a lack of suitable screening tests for early detection and specific early symptoms. Despite progress in therapy improvements in ovarian cancer, most patients develop a recurrence within months or years after initial treatment. Given that the presence of tumor infiltrating lymphocytes is associated with prognosis and ovarian cancer is among the first cancers with an established association of immune cell infiltration, identification of the immune microenvironment in ovarian cancer is thought to be promising. In this study, to increase the understanding of tumor immune cell interactions, we undertook a study of tumor infiltrating lymphocytes in a large group of ovarian cancer patients. Our results suggested that tumor immune infiltrates of ovarian cancer were quite cohort and subtype dependent, and activated CD4+ T and CD8+ T tumor infiltrating lymphocytes were associated with good overall survival in the high-grade serous tumors. We found that high expression levels of the immune-related genes were associated with good prognosis in high-grade serous carcinomas. In addition, two different groups of prognostic genes were found in the high-grade and low-grade serous carcinomas, indicating that these two subtypes of serous carcinomas were two biologically and clinically different cancer types.
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http://dx.doi.org/10.1039/c8mo00128fDOI Listing
October 2018

Computed Tomography and Magnetic Resonance Imaging Manifestations of Spinal Monostotic Fibrous Dysplasia.

J Clin Imaging Sci 2018 18;8:23. Epub 2018 Jun 18.

Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China.

Aim: The purpose of the study was to analyze and summarize the computed tomography (CT) and magnetic resonance imaging (MRI) findings of spinal monostotic fibrous dysplasia (MFD) as well as evaluate the clinical value of CT and MRI in MFD diagnosis.

Materials And Methods: CT ( = 4) and MRI ( = 5) images of six patients with pathologically confirmed spinal MFD were examined. The assessed image features included location, shape, rib involvement, vertebral collapse, margin, attenuation, and sclerotic rim on CT, as well as signal intensity, dark signal rim, and enhancement pattern on MRI.

Results: In total, four of six patients underwent CT scanning. The most common findings on CT scanning were expansile lesions ( = 4), sclerotic rims ( = 4), and ground-glass opacity (GGO) ( = 4). In total, five of six patients underwent MRI. The lesions were low-signal intensity ( = 2), low-to-isointense signal intensity ( = 1), and low-signal intensity with several isointense portions ( = 2) on T1-weighted imaging (T1WI). The lesions were low-signal intensity ( = 1), isointense to high intensity ( = 1), and isointense signal intensity with several high portions ( = 3) on T2WI. A dark signal rim was found in most cases on T1WI and T2WI ( = 4). The lesions ( = 2) showed obvious enhancement.

Conclusions: The CT and MRI manifestations of spinal MFD have the following characteristics: expansile lesion, GGO, sclerotic rim, and no obvious soft-tissue mass. The combined use of CT and MRI examinations is necessary for patients with suspected spinal MFD.
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http://dx.doi.org/10.4103/jcis.JCIS_20_18DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6029006PMC
June 2018

Primary Intraosseous Hemangioma of the Foreman Rotundum Area.

J Craniofac Surg 2018 Jul;29(5):e522-e525

Department of Radiology, The Affiliated Hospital of Qingdao University.

The primary intraosseous hemangioma is extremely rare in foreman rotundum area. However, it is very important for radiologists and otolaryngologists to be aware of it, in order to be able to provide accurately diagnosis as well choose the best treatment plan. The purpose of this article is to describe imaging features of this kind of tumor.
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http://dx.doi.org/10.1097/SCS.0000000000004582DOI Listing
July 2018