TabMixer: Noninvasive Estimation of the Mean Pulmonary Artery Pressure via Imaging and Tabular Data Mixing

TL;DR

This paper introduces TabMixer, a novel deep learning module that effectively combines imaging and tabular data to noninvasively estimate mean Pulmonary Artery Pressure, potentially improving diagnosis of Pulmonary Hypertension.

Contribution

The paper presents the first use of Multilayer Perceptrons to integrate imaging and tabular data in vision models for medical prediction tasks.

Findings

TabMixer improves performance of CNNs, 3D-MLP, and Vision Transformers in mPAP estimation.

The approach is competitive with existing methods for multimodal data integration.

It enhances noninvasive diagnosis of Pulmonary Hypertension.

Abstract

Right Heart Catheterization is a gold standard procedure for diagnosing Pulmonary Hypertension by measuring mean Pulmonary Artery Pressure (mPAP). It is invasive, costly, time-consuming and carries risks. In this paper, for the first time, we explore the estimation of mPAP from videos of noninvasive Cardiac Magnetic Resonance Imaging. To enhance the predictive capabilities of Deep Learning models used for this task, we introduce an additional modality in the form of demographic features and clinical measurements. Inspired by all-Multilayer Perceptron architectures, we present TabMixer, a novel module enabling the integration of imaging and tabular data through spatial, temporal and channel mixing. Specifically, we present the first approach that utilizes Multilayer Perceptrons to interchange tabular information with imaging features in vision models. We test TabMixer for mPAP estimation and show that it enhances the performance of Convolutional Neural Networks, 3D-MLP and Vision Transformers while being competitive with previous modules for imaging and tabular data. Our approach has the potential to improve clinical processes involving both modalities, particularly in noninvasive mPAP estimation, thus, significantly enhancing the quality of life for individuals affected by Pulmonary Hypertension. We provide a source code for using TabMixer at https://github.com/SanoScience/TabMixer.