A Sub-pixel Accurate Quantification of Joint Space Narrowing Progression in Rheumatoid Arthritis

TL;DR

This paper introduces a novel phase-only correlation method for highly sensitive, sub-pixel accurate quantification of joint space narrowing progression in rheumatoid arthritis, surpassing traditional pixel-level techniques.

Contribution

The study presents a new phase spectrum-based approach for measuring joint space narrowing with sub-pixel accuracy, improving early detection of RA progression.

Findings

Mean error reduced to 0.0130mm on phantom radiographs

Standard deviation of 0.0519mm on clinical radiography

Sub-pixel accuracy surpasses manual measurement methods

Abstract

Rheumatoid arthritis (RA) is a chronic autoimmune disease that primarily affects peripheral synovial joints, like fingers, wrist and feet. Radiology plays a critical role in the diagnosis and monitoring of RA. Limited by the current spatial resolution of radiographic imaging, joint space narrowing (JSN) progression of RA with the same reason above can be less than one pixel per year with universal spatial resolution. Insensitive monitoring of JSN can hinder the radiologist/rheumatologist from making a proper and timely clinical judgment. In this paper, we propose a novel and sensitive method that we call partial image phase-only correlation which aims to automatically quantify JSN progression in the early stages of RA. The majority of the current literature utilizes the mean error, root-mean-square deviation and standard deviation to report the accuracy at pixel level. Our work measures JSN progression between a baseline and its follow-up finger joint images by using the phase spectrum in the frequency domain. Using this study, the mean error can be reduced to 0.0130mm when applied to phantom radiographs with ground truth, and 0.0519mm standard deviation for clinical radiography. With its sub-pixel accuracy far beyond manual measurement, we are optimistic that our work is promising for automatically quantifying JSN progression.