Clinical Relevance of Computationally Derived Attributes of Arteries and Arterioles in focal segmental glomerulosclerosis and minimal change disease

Background The current semi-qualitative methods used to score sclerosis and hyalinosis in arteries and arterioles in clinical practice are limited in standardization and reproducibility. We developed a computational pipeline designed to accurately and consistently quantify prognostic arterial and arteriolar characteristics in digital kidney biopsies of patients with focal segmental glomerulosclerosis (FSGS) and minimal change disease (MCD) through segmentation and pathomic feature extraction.

We utilized one trichrome-stained WSI from 225 participants in the NEPTUNE/CureGN studies, comprising 127 cases of focal segmental glomerulosclerosis (FSGS) and 98 cases of minimal change disease (MCD). We developed, validated, and quality-controlled deep learning models to segment muscular vessels and their internal compartments (lumen, intima, media, and hyalinosis), including (i) arcuate arteries, (ii) interlobular arteries, and (iii) arterioles with two muscle layers. Arterioles, interlobular, and arcuate arteries were visually scored for sclerosis and hyalinosis on a scale of 0 to 3. Area- and thickness-based pathomic feature extraction was performed on each compartment (lumen, intima, media, and hyalinosis) through radial sampling and ray casting. A correlation study was performed between pathomic and visual semiquantitative visual scores, and the association of both visual scores and pathomic features with disease progression (40% eGFR decline or renal failure) was assessed. Summary statistics (maximum, median, and 75th percentile) were computed for each WSI and analyzed using LASSO-regularized Cox proportional hazards models, adjusted for clinical and demographic factors.

A total of 1,499 arterioles, 686 interlobular arteries, and 131 arcuate arteries were segmented. Statistically significant correlations were found between pathologists visual scores and the average intima-media thickness ratio (Spearman ρ = 0.27, p < 0.001 for arterioles; ρ = 0.69, p < 0.001 for interlobular arteries; and ρ = 0.80, p < 0.001 for arcuate arteries) and arteriolar hyalinosis (ρ = 0.46, p < 0.001). Incorporating pathomic features from trichrome-stained WSIs improved the prediction of disease progression, enhancing the concordance index from 0.70 to 0.75 in arterioles and from 0.69 to 0.74 in arcuate arteries, compared to using demographics and clinical characteristics alone.

Our computational approach offers a novel and reliable method for segmenting and analyzing the pathomic features of sclerosis and hylalinosis in arteries and arterioles. This technique has demonstrated potential as a valuable tool for enhancing the clinical assessment performed by pathologists. Key Points A computational pipeline was developed and validated to segment arteries and arterioles and to quantify lumen, intima, media, and hyalinosis in kidney biopsies from patients with FSGS and MCD. Pathomic features, such as intima-media thickness ratio and hyalinosis area, significantly correlated with pathologists’ semi-quantitative sclerosis and hyalinosis scores. Integrating pathomic features into clinical models improved disease progression prediction accuracy Competing Interest Statement JH, KL, AJ, LB have received financial support from NIH funding list in the acknowledgement. LM has received financial support from NIDDK and NCATS for the submitted work and received grants from Boehringer-Ingelheim, Travere Therapeutics, Reliant Glycosciences, HiBio and Takeda Pharmaceuticals. LM has also received consulting fee from Novartis, Calliditas and Travere and payment for educational events from WebMD/Medscape and MedLive/PlatformQ. LBH has received grants from NIDDK CureGN-Penn PCC, NIDDK Nephrotic Syndrome Rare Disease Clinical Research Network III and NIDDK Computational Pathology for Proteinuric Glomerulopathies. Additionally, LBH holds a leadership role in the Scientific Advisory Board of NephCure Kidney International. JH has received grants from NIH and Department of Defense and received funds from NovoNordisk, Astra Zeneca, Gilead, and Janssen. LB has received grants from NIH fundings listed in Acknowledgment, Nephcure and Haller Foundation. LB has also participated on a Data Safety Monitoring Board or Advisory Board for Vertex and holds a leadership role in the International Society of Glomerular Diseases. Funding Statement 1) the National Institute of Health (NIH) under the following awards: i) by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) under the award number 2R01DK118431; U01DK114907 and National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) under the award number R01AR080668. 2) The Nephrotic Syndrome Study Network (NEPTUNE) is part of the Rare Diseases Clinical Research Network (RDCRN), which is funded by the National Institutes of Health (NIH) and led by the National Center for Advancing Translational Sciences (NCATS) through its Division of Rare Diseases Research Innovation (DRDRI). NEPTUNE is funded under grant number U54DK083912 as a collaboration between NCATS and the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). Additional funding and/or programmatic support is provided by the University of Michigan, NephCure Kidney International, Alport Syndrome Foundation, and the Halpin Foundation. RDCRN consortia are supported by the RDCRN Data Management and Coordinating Center (DMCC), funded by NCATS and the National Institute of Neurological Disorders and Stroke (NINDS) under U2CTR002818. 3) Additional support was also provided by NephCure and the Henry E. Haller, Jr. Foundation. 4) Funding for the CureGN consortium is provided by U24DK100845, U01DK100846, U01DK100876, U01DK100866, and U01DK100867 from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). Patient recruitment is supported by NephCure. Dates of funding for first phase of CureGN was 9/16/2013-5/31/2019. Dates of funding for the second phase of CureGN was 6/1/2019 - 5/31/2024. Patient recruitment is supported by NephCure. Dates of funding for first phase of CureGN was 9/16/2013-5/31/2019. Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The Institutional Review Board of Duke University gave ethical approval for this work (ID: Pro00108417) I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data Availability All data produced in the present work are contained in the manuscript