March 1, 2023

1:30 pm / 3:00 pm

TITLE: Capillary Adaptation in Right Heart Failure

DATE: Wednesday, 1 March 2023

TIME: 1:30–3:00 PM

INVESTIGATORS:

Kenzo Ichimura (1, 2, 3)

Ross Metzger (3)

Edda Spiekerkoetter (1, 2, 3)

(1) Pulmonary, Allergy and Critical Care Medicine

(2) Cardiovascular Institute

(3) Vera Moulton Wall Center for Pulmonary Vascular Disease

LOCATION: Conference Room X399, Medical School Office Building, 1265 Welch Road, Stanford, CA

WEBPAGE: https://dbds.stanford.edu/data-studio/

ABSTRACT

The Data Studio Workshop brings together a biomedical investigator with a group of experts for an in-depth session to solicit advice about statistical and study design issues that arise while planning or conducting a research project. This week, the investigator(s) will discuss the following project with the group.

INTRODUCTION

Right ventricular (RV) function is the primary determinant of functional status and survival in various cardiovascular diseases characterized by an increased RV afterload. Despite the importance of the RV function in diseases such as pulmonary hypertension (PH), the mechanism of RV failure is not well understood which limits the development of RV-targeted therapies.

Capillary rarefaction due to vessel loss or insufficient growth of the capillaries is one of the proposed structural hallmarks of RV failure. Multiple studies using rodent models of PH have shown that capillary numbers and density decrease at the stage of decompensated RV failure. Furthermore, some human studies corroborated these findings and reported that the capillary density was decreased in PH patients with end-stage RV failure. However, most of the studies documenting capillary rarefaction in the RV were performed on thin sections using conventional two-dimensional (2D) imaging which limits the evaluation of the architectural changes of the three-dimensional (3D) microvascular network of the heart.

Developments in 3D deep tissue imaging have added significant depth to our knowledge of complex microstructures such as the central nervous system and blood vessels of the heart. Deep tissue imaging can be used not only to visualize 3D tubular networks such as the vasculature, but allows for quantification of network properties such as length, diameter, orientation angle, straightness, number of branching points, number of segments, and capillary volume.

By using a mouse model of pressure overload-induced RV failure (i.e., pulmonary artery banding, PAB), we developed a 3D deep-tissue imaging and analysis method to visualize and quantify the capillary network in the RV and its relation with the cardiomyocytes (capillary-cardiomyocyte contact area). We also applied this method to human heart tissue which was obtained either from patients undergoing heart transplantation or from control cases without RV failure.

HYPOTHESES

  1. In PAB model, the capillary architecture changes over the disease time course.
  2. In PAB model, the capillary-cardiomyocyte contact area is preserved throughout the disease time course, except for the areas of fibrosis.
  3. In PAB, males and females have different capillary properties at baseline and in response to RV pressure overload.
  4. In patients with end-stage RV failure, capillary architectural change is associated with etiology and disease duration.
  5. ) cases have a different capillary architecture compared to other PAH cases.

DATASET

This study has two parts, an analysis of a mouse model of RV failure (i.e., PAB), and an analysis of samples obtained from patients with end-stage RV failure due to PH.

For the PAB mouse model, parameters of the capillary structure (length, diameter, orientation angle, straightness, number of branching points, number of segments, capillary volume), fibrosis (fibrotic tissue volume), RV tissue volume, as well as cardiomyocytes (cardiomyocyte size, capillary-cardiomyocyte contact area) were obtained from several timepoints after PAB (week 1, week 4, week 7) from male and female mice, and compared to Sham animals. N=5–7 each.

For the patient samples, parameters of the capillary structure (length, diameter, orientation angle, straightness, number of branching points, number of segments, capillary volume), fibrosis (fibrotic tissue volume), RV tissue volume, as well as clinical information (etiology, hemodynamic parameters, disease duration) were obtained. N=7 PAH cases (all female), N=4 control cases (3 males and 1 female).

For the capillary parameters, each sample has 10,000–15,000 observations, as all capillary segments have their own measurements (i.e., length, diameter, orientation angle, and straightness). Likewise, all cardiomyocytes have their own measurements (cardiomyocyte size, capillary-cardiomyocyte contact area) of around 30 observations/sample. Other parameters are unique to each sample (i.e., only one observation for “numbers of branching points” as it is the number of branches/sample).

STATISTICAL ISSUES

(1) How to do a power calculation for multiple endpoints (length, diameter, etc.) that have different SD.

(2) What is the best statistical method to compare the parameters of the capillary structures and cardiomyocytes in PAB mice? Two-way ANOVA? Mixed-effect model?

(3) How can we associate the changes in the capillary structure with etiology, hemodynamic parameters, and disease duration in patient samples? Principal component analysis? tSNE?

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