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一种用于新生儿筛查中干血斑大小和质量评估的计算机视觉方法。

A computer vision approach to the assessment of dried blood spot size and quality in newborn screening.

作者信息

Flynn Nick, Moat Stuart J, Hogg Sarah L

机构信息

Biochemical Genetics Unit, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.

Department of Medical Biochemistry, Immunology & Toxicology, University Hospital Wales, Cardiff, UK; School of Medicine, Cardiff University, Cardiff, Wales, UK.

出版信息

Clin Chim Acta. 2023 Jul 1;547:117418. doi: 10.1016/j.cca.2023.117418. Epub 2023 Jun 3.

DOI:10.1016/j.cca.2023.117418
PMID:37276944
Abstract

BACKGROUND

Dried blood spot (DBS) size and quality affect newborn screening (NBS) test results. Visual assessment of DBS quality is subjective.

METHODS

We developed and validated a computer vision (CV) algorithm to measure DBS diameter and identify incorrectly applied blood in images from the Panthera DBS puncher. We used CV to assess historical trends in DBS quality and correlate DBS diameter to NBS analyte concentrations in 130,620 specimens.

RESULTS

CV estimates of DBS diameter were precise (percentage coefficient of variation < 1.3%) and demonstrated excellent agreement with digital calipers with a mean (standard deviation) difference of 0.23 mm (0.18 mm). An optimised logistic regression model showed a sensitivity of 94.3% and specificity of 96.8% for detecting incorrectly applied blood. In a validation set of images (n = 40), CV agreed with an expert panel in all acceptable specimens and identified all specimens rejected by the expert panel due to incorrect blood application or DBS diameter > 14 mm. CV identified a reduction in unsuitable NBS specimens from 25.5% in 2015 to 2% in 2021. Each mm decrease in DBS diameter decreased analyte concentrations by up to 4.3%.

CONCLUSIONS

CV can aid assessment of DBS size and quality to harmonize specimen rejection both within and between laboratories.

摘要

背景

干血斑(DBS)的大小和质量会影响新生儿筛查(NBS)的检测结果。对DBS质量进行视觉评估具有主观性。

方法

我们开发并验证了一种计算机视觉(CV)算法,用于测量DBS直径,并识别来自Panthera DBS打孔器图像中不正确涂抹的血液。我们使用CV评估DBS质量的历史趋势,并将DBS直径与130,620份标本中的NBS分析物浓度相关联。

结果

CV对DBS直径的估计精确(变异系数百分比<1.3%),与数字卡尺显示出极好的一致性,平均(标准差)差异为0.23毫米(0.18毫米)。一个优化的逻辑回归模型在检测不正确涂抹的血液时,灵敏度为94.3%,特异性为96.8%。在一组验证图像(n = 40)中,CV在所有可接受的标本中与专家小组意见一致,并识别出所有因血液涂抹不正确或DBS直径>14毫米而被专家小组拒收的标本。CV发现不合适的NBS标本比例从2015年的25.5%降至2021年的2%。DBS直径每减小1毫米,分析物浓度最多降低4.3%。

结论

CV有助于评估DBS的大小和质量,以统一各实验室内部和之间的标本拒收标准。

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引用本文的文献

1
Consistency in the Assessment of Dried Blood Spot Specimen Size and Quality in U.K. Newborn Screening Laboratories.英国新生儿筛查实验室干血斑样本大小和质量评估的一致性
Int J Neonatal Screen. 2024 Sep 5;10(3):60. doi: 10.3390/ijns10030060.