# 3D modeling and fitted sphere analysis-based biotechniques unveil novel indicators for subacromial impingement syndrome

## TL;DR

This paper introduces new diagnostic indicators for subacromial impingement syndrome using 3D modeling and fitted sphere analysis, which could improve diagnosis accuracy.

## Contribution

The study introduces novel diagnostic indicators for subacromial impingement syndrome based on 3D modeling and fitted sphere analysis.

## Key findings

- The humeral head-pseudo-moving domain volume index and pseudo-moving domain abduction angle are effective indicators for subacromial impingement syndrome.
- Combined use of new indicators improves diagnostic accuracy with an AUC of 0.859.
- Some new indicators correlate with existing clinical parameters like Acromion Index and Critical Shoulder Angle.

## Abstract

To investigate the impact and diagnostic value of novel indicators based on 3D modeling and fitted sphere analysis for Subacromial Impingement Syndrome (SIS).

CT data from patients with Subacromial Impingement Syndrome and healthy individuals were imported into a software system to reconstruct a 3D model of the index shoulder. The following parameters were measured: humeral head-pseudo-moving domain volume index, pseudo-moving domain anteversion angle, pseudo-moving domain abduction angle, Critical Shoulder Angle (CSA), Acromion Index (AI), Acromio-humeral Interval (AHI), Lateral Acromial Angle (LAA), Acromion-Greater Tuberosity Impingement Index (ATI), glenoid inclination angle, and glenoid ante/retroversion angle. Influencing factor analysis, Receiver Operating Characteristic curve analysis, and correlation analysis were then performed.

The humeral head-pseudo-moving domain volume index, pseudo-moving domain anteversion angle, and pseudo-moving domain abduction angle were all indicators for SIS (P < 0.05). The humeral head-pseudo-moving domain volume index had high accuracy in predicting SIS (AUC = 0.778, P < 0.001), with an optimal threshold of 0.690, at which sensitivity and specificity were 67.0% and 77.0%, respectively. The pseudo-moving domain anteversion angle had no diagnostic value. The pseudo-moving domain abduction angle had high accuracy in predicting SIS (AUC = 0.728, P < 0.001), with an optimal threshold of 75.012, at which sensitivity and specificity were 62.2% and 72.8%, respectively. When the new indicators were used in combination, the accuracy was higher (AUC = 0.859, P < 0.001), with optimal thresholds of 0.528 or 0.542. The humeral head-pseudo-moving domain volume index had correlation with AI, AHI, LAA, and ATI. The pseudo-moving domain anteversion angle showed no correlation with glenoid anteversion/retroversion. The pseudo-moving domain abduction angle had correlation with critical shoulder angle and glenoid superior inclination.

The new indicators based on 3D modeling and fitted sphere analysis are indicators for SIS. The humeral head-pseudo-moving domain volume index and pseudo-moving domain abduction angle have prognostic value for SIS.