Interstitial fibrosis and tubular atrophy measurement via hierarchical extractions of kidney and atrophy regions with deep learning method

• Published in: Measurement : journal of the International Measurement Confederation 2022-10, Vol.202, p.111885, Article 111885
• Main Authors: Lai, Yexin, Liu, Xueyu, Wu, Yongfei, Zhou, Daoxiang, Wang, Chen, Niu, Dan, Han, Weixia, Zhou, Xiaoshuang, Chen, Jiayan, Zheng, Wen
• Format: Article
• Language: English
• Subjects: Hierarchical extraction; Instance segmentation; Interstitial fibrosis and tubular atrophy; Quantitative analysis; Salient object detection
• ISSN: 0263-2241; 1873-412X
• DOI: 10.1016/j.measurement.2022.111885

Interstitial fibrosis and tubular atrophy (IFTA) are the most critical characteristics of chronic kidney disease, and it is superior to glomerular pathology in predicting the decrease of glomerular filtration rate (eGFR) for chronic kidney disease (CKD). However, measurement of IFTA usually depends on manual operation, which is laborious and may lead to significant differences among pathologists. Therefore, the long-term focus of chronic kidney disease research has been on the glomerulus with relatively prominent morphological characteristics. There are few types of research on IFTA. We proposed an IFTA measurement method based on hierarchically extracting renal tissue, interstitial fibrosis and tubular atrophy regions. Our proposed method first extracts the whole renal tissue region (cortex and medulla) on WSIs by employing the Kidney Tissue Module and then recognizes the interstitial fibrosis and tubular atrophy regions via Interstitial fibrosis and Tubular atrophy Module. Finally, the proportion of the IFTA area to the entire renal tissue area is calculated to obtain the end-to-end output IFTA ratio. Experimental results confirmed that the proposed method outperforms recently proposed approaches by comparing accuracy in segmenting IFTA area and thus achieved state-of-the-art performance. ITNet also achieved a faster-processing speed in calculating the proportion of IFTA than pathologists. Furthermore, the results showed that our proposed hierarchical extraction method could make full use of feature information, effectively combine the advantages of different scales, and segment IFTA with high accuracy and reasonable acceptability. Quantitative analysis of IFTA by the proposed method can reduce pathologists’ measurement time to diagnose and decrease the assessment difference between different pathologists. Therefore, the proposed method can assist pathologists in improving the efficiency of diagnosis and supplying consistent measurement accuracy. •Proposed an IFTA measurement method based on hierarchically extracting.•Creatively segment renal tissue at low resolution and IFTA at high resolution.•Automatically assessment of IFTA, unify the evaluation criteria of pathologists.•After experiments, it is proved that the proposed method is superior to others.