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  • Ovid Technologies (Wolters Kluwer Health)  (2)
  • 2020-2024  (2)
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  • Ovid Technologies (Wolters Kluwer Health)  (2)
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  • 2020-2024  (2)
Year
  • 1
    In: Medicine, Ovid Technologies (Wolters Kluwer Health), Vol. 101, No. 10 ( 2022-03-11), p. e28972-
    Abstract: To evaluate the performance of polymerase chain reaction (PCR)-free whole genome sequencing (WGS) for clinical diagnosis, and thereby revealing how experimental parameters affect variant detection. Five NA12878 samples were sequenced using MGISEQ-2000. NA12878 samples underwent WGS with differing deoxyribonucleic acid (DNA) input and library preparation protocol (PCR-based vs PCR-free protocols for library preparation). The depth of coverage and genotype quality of each sample were compared. The performance of each sample was measured for sensitivity, coverage of depth and breadth of coverage of disease-related genes, and copy number variants. We also developed a systematic WGS pipeline (PCR-free) for the analysis of 11 clinical cases. In general, NA12878-2 (PCR-free WGS) showed better depth of coverage and genotype quality distribution than NA12878-1 (PCR-based WGS). With a mean depth of ∼40×, the sensitivity of homozygous and heterozygous single nucleotide polymorphisms (SNPs) of NA12878-2 showed higher sensitivity ( 〉 99.77% and 〉 99.82%) than NA12878-1, and positive predictive value exceeded 99.98% and 99.07%. The sensitivity and positive predictive value of homozygous and heterozygous indels for NA12878-2 (PCR-free WGS) showed great improvement than NA128878-1. The breadths of coverage for disease-related genes and copy number variants are slightly better for samples with PCR-free library preparation protocol than the sample with PCR-based library preparation protocol. DNA input also influences the performance of variant detection in samples with PCR-free WGS. All the 19 previously confirmed variants in 11 clinical cases were successfully detected by our WGS pipeline (PCR free). Different experimental parameters may affect variant detection for clinical WGS. Clinical scientists should know the range of sensitivity of variants for different methods of WGS, which would be useful when interpreting and delivering clinical reports.
    Type of Medium: Online Resource
    ISSN: 0025-7974 , 1536-5964
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2022
    detail.hit.zdb_id: 2049818-4
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  • 2
    In: International Journal of Surgery, Ovid Technologies (Wolters Kluwer Health)
    Abstract: Preoperative evaluation of the metastasis status of lateral lymph nodes (LNs) in papillary thyroid cancer (PTC) is challenging. Strategies for using deep learning (DL) to diagnosis of lateral LN metastasis require additional development and testing. This study aimed to build a DL-based model to distinguish benign lateral LNs from metastatic lateral LNs in PTC and test the model’s diagnostic performance in a real-world clinical setting. Methods: This was a prospective diagnostic study. An ensemble model integrating a three-dimensional residual network (ResNet) algorithm with clinical risk factors available before surgery was developed based on CT images of lateral LNs in an internal dataset and validated in two external datasets. The diagnostic performance of the ensemble model was tested and compared with the results of fine-needle aspiration (FNA) (used as the standard reference method) and the diagnoses made by two senior radiologists in 113 suspicious lateral LNs in patients enrolled prospectively. Results: The area under the receiver operating characteristic curve of the ensemble model for diagnosing suspicious lateral LNs was 0.824 (95% CI, 0.738-0.911). The sensitivity and specificity of the ensemble model were 0.839 (95% CI, 0.762-0.916) and 0.769 (95% CI, 0.607-0.931), respectively. The diagnostic accuracy of the ensemble model was 82.3%. With FNA results as the criterion standard, the ensemble model had excellent diagnostic performance ( P =0.115), similar to that of the two senior radiologists ( P =1.000 and P =0.392, respectively). Conclusion: A three-dimensional ResNet-based ensemble model was successfully developed for diagnostic assessment of suspicious lateral LNs and achieved diagnostic performance similar to that of FNA and senior radiologists. The model appears promising for clinical application.
    Type of Medium: Online Resource
    ISSN: 1743-9159
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2023
    detail.hit.zdb_id: 2201966-2
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