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A Fully Automatic System to Assess Foot Collapse on Lateral Weight-bearing Foot Radiographs
Poster Title: A Fully Automatic System to Assess Foot Collapse on Lateral Weight-bearing Foot Radiographs
Submitted on 30 Oct 2020
Author(s): Dr Joshua Lauder, Dr Jonathan Harris, Dr Benjamin Layton, Dr Priam Heire, Dr Alan Sorani, Max DeSancha, Dr Camilla Sammut-Powell, Dr Claudia Lindner
Affiliations: The University of Manchester, Salford Royal NHS Foundation Trust
This poster was presented at BIR Congress
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Poster Information
Abstract: ABSTRACT

Foot collapse is primarily diagnosed and monitored using lateral weight bearing foot x-ray images. There are several well validated measurements which aid assessment, however these are subject to inter and intra-user variability.
To develop and validate a software system for the fully automatic assessment of radiographic changes associated with foot collapse; automatically generating measurements for calcaneal tilt, cuboid height and Meary’s angle.
Materials and Methods
This retrospective study was approved by the Health Research Authority (IRAS 244852). The system was developed using 200 lateral weight-bearing foot x-ray images from 79 subjects (mean age: 56.4 years ±12.9 SD, 30/49 females/males), and evaluated against manual measurements from five clinical experts. The system has two main components: (i) a Random Forest-based point-finder to outline the bones of interest; and (ii) a geometry-calculator to generate the measurements based on the point positions from the point-finder. The performance of the point-finder was assessed using the point-to-point error (i.e. the mean absolute distance between each found point and the equivalent ground truth point, averaged over all points per image). For assessing the performance of the geometry-calculator, linear mixed models were fitted to estimate clinical inter-observer agreement as well as to compare the performance of the software system to that of the clinical experts.
There was good agreement among the five clinical experts with intraclass correlation estimates between 0.78 and 0.86. The point-finder achieved a median point-to-point error of 2.2mm. There was no significant difference between the clinical and automatically generated measurements using the point-finder results (p=0.29, p=0.23, p=0.32). The results suggest that the fully automatically obtained measurements are in agreement with the manually obtained measurements.
The proposed software system can be used to support and automate radiographic image assessment for diagnosing and managing foot collapse, saving clinician time and improving patient outcomes.
Summary: 1. This automated system can accurately reproduce measurements for Meary’s angle, calcaneal tilt and cuboid height on lateral weight bearing foot xrays in the context of foot collapse.References: 1. Schmidt BM, Holmes CM. Updates on diabetic foot, charcot osteopathic arthropathy. Current Diabetes Reports 2018;18(10):74.
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