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  • Dong, Qian  (3)
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  • 1
    Online Resource
    Online Resource
    DataSheet_1.pdf
    Frontiers Media SA ; 2022
    In:  Frontiers in Oncology Vol. 12 ( 2022-3-7)
    Details
    In: Frontiers in Oncology, Frontiers Media SA, Vol. 12 ( 2022-3-7)
    Abstract: To explore a new model to predict the prognosis of liver cancer based on MRI and CT imaging data. Methods A retrospective study of 103 patients with histologically proven hepatocellular carcinoma (HCC) was conducted. Patients were randomly divided into training (n = 73) and validation (n = 30) groups. A total of 1,217 radiomics features were extracted from regions of interest on CT and MR images of each patient. Univariate Cox regression, Spearman’s correlation analysis, Pearson’s correlation analysis, and least absolute shrinkage and selection operator Cox analysis were used for feature selection in the training set, multivariate Cox proportional risk models were established to predict disease-free survival (DFS) and overall survival (OS), and the models were validated using validation cohort data. Multimodal radiomics scores, integrating CT and MRI data, were applied, together with clinical risk factors, to construct nomograms for individualized survival assessment, and calibration curves were used to evaluate model consistency. Harrell’s concordance index (C-index) values were calculated to evaluate the prediction performance of the models. Results The radiomics score established using CT and MR data was an independent predictor of prognosis (DFS and OS) in patients with HCC ( p & lt; 0.05). Prediction models illustrated by nomograms for predicting prognosis in liver cancer were established. Integrated CT and MRI and clinical multimodal data had the best predictive performance in the training and validation cohorts for both DFS [(C-index (95% CI): 0.858 (0.811–0.905) and 0.704 (0.563–0.845), respectively)] and OS [C-index (95% CI): 0.893 (0.846–0.940) and 0.738 (0.575–0.901), respectively] . The calibration curve showed that the multimodal radiomics model provides greater clinical benefits. Conclusion Multimodal (MRI/CT) radiomics models can serve as effective visual tools for predicting prognosis in patients with liver cancer. This approach has great potential to improve treatment decisions when applied for preoperative prediction in patients with HCC.
    Type of Medium: Online Resource
    ISSN: 2234-943X
    URL: Article
    URL: Article
    DOI: 10.3389/fonc.2022.745258
    DOI: 10.3389/fonc.2022.745258.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2649216-7
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  • 2
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    Online Resource
    Table_4.doc
    Frontiers Media SA ; 2021
    In:  Frontiers in Oncology Vol. 11 ( 2021-4-21)
    Details
    In: Frontiers in Oncology, Frontiers Media SA, Vol. 11 ( 2021-4-21)
    Abstract: Hepatoblastoma (HB) is the most common malignant tumor in the liver of infants and young children. The incidence rate varies among different populations. However, genetic differences in HB patients with different epidemiological and ancestral backgrounds have not been found. In this study, we aim to analyze data from 16 patients treated at our center and collected published data from whole-exome sequencing studies on HB, and to explore the genetic differences between races. Data from a total of 75 HB patients of three races (24 Asian, 37 Caucasian and 14 Hispanic) were analyzed. We identified 16 genes with recurrent somatic mutations and 7 core pathway modules. Among them, the Wnt/β-catenin pathway had the highest mutation rate, and the mutation frequency in Caucasians and Hispanics was approximately twice as high as that in Asians. In addition, this study compared the characteristics of gene mutations between patients who underwent preoperative chemotherapy and those who did not and found that there was no significant difference in gene mutations between the two groups. We also preliminarily verified the function of cancer-associated candidate genes (CTNNB1 and KMT2D). In conclusion, we found ethnic differences in HB biology at the genomic level, which expands our understanding of the genetics of HB in children.
    Type of Medium: Online Resource
    ISSN: 2234-943X
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fonc.2021.669560
    DOI: 10.3389/fonc.2021.669560.s001
    DOI: 10.3389/fonc.2021.669560.s002
    DOI: 10.3389/fonc.2021.669560.s003
    DOI: 10.3389/fonc.2021.669560.s004
    DOI: 10.3389/fonc.2021.669560.s005
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2649216-7
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  • 3
    Online Resource
    Online Resource
    Standard Liver Volume-Predicting Formulae Derived From Normal Liver Volume in Children Under 18 Years of Age
    Frontiers Media SA ; 2021
    In:  Frontiers in Pediatrics Vol. 9 ( 2021-2-19)
    Details
    In: Frontiers in Pediatrics, Frontiers Media SA, Vol. 9 ( 2021-2-19)
    Abstract: Background: Standard liver volume (SLV) is important in risk assessment for major hepatectomy. We aimed to investigate the growth patterns of normal liver volume with age and body weight (BW) and summarize formulae for calculating SLV in children. Methods: Overall, 792 Chinese children ( & lt;18 years of age) with normal liver were enrolled. Liver volumes were measured using computed tomography. Correlations between liver volume and BW, body height (BH), and body surface area (BSA) were analyzed. New SLV formulae were selected from different regression models; they were assessed by multicentral validations and were compared. Results: The growth patterns of liver volume with age (1 day−18 years) and BW (2–78 kg) were summarized. The volume grows from a median of 139 ml (111.5–153.6 in newborn) to 1180.5 ml (1043–1303.1 at 16–18 years). Liver volume was significantly correlated with BW ( r = 0.95, P & lt; 0.001), BH ( r = 0.92, P & lt; 0.001), and BSA ( r = 0.96, P & lt; 0.001). The effect of sex on liver volume increases with BW, and BW of 20 kg was identified as the optimal cutoff value. The recommended SLV formulae were BW≤20 kg: SLV = 707.12 × BSA 1.09 ; BW & gt;20 kg, males: SLV = 691.90 × BSA 1.06 ; females: SLV = 663.19 × BSA 1.04 . Conclusions: We summarized the growth patterns of liver volume and provided formulae predicting SLV in Chinese children, which is useful in assessing the safety of major hepatectomies.
    Type of Medium: Online Resource
    ISSN: 2296-2360
    URL: Article
    DOI: 10.3389/fped.2021.629645
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2711999-3
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