Assessing Hallux Valgus using Automatically Segmented Weight Bearing CT Datasets: A Case-Control Study. Issue 4 (22nd October 2020)

• Record Type: Journal Article
• Authors: Lintz, Francois; Bernasconi, Alessio; Fernando, Céline; Netto, Cesar de Cesar
• Is Part Of: Foot & ankle orthopaedics. Volume 5:Issue 4(2020)
• Publication Date: 2020-10-22
• Subjects: Forefoot -- Weight Bearing CT -- Hallux Valgus; Foot -- Surgery -- Periodicals; Ankle -- Surgery -- Periodicals; Orthopedics -- Periodicals; 617.584
• DOI: 10.1177/2473011420S00056
• Languages: English
• ISSNs: 2473-0114

Abstract

Category: Bunion; Midfoot/Forefoot Introduction/Purpose: Hallux Valgus (HV) is a complex 3D deformity. Coronal rotation of the first column has been advocated as a key component of its pathophysiology. Cone Beam Weightbearing CT (CB-WBCT) provides 3D images of the foot and ankle bones under physiological load and may provide any absolute or relative measurements. However, the fact that numerous bones and joints are concerned makes analysis time-consuming and results difficult to render and interpret. Artificial Intelligence based Automatic Segmentation (AIAS) is a new tool which allows for volumetric identification and localization of bones. The objective of this study was to use this tool to obtain exhaustive measurements of the whole first column relative to the second and third columns in HV and compare them to the normal population. Methods: Retrospective comparative, level III study including 16 HV cases and 16 controls matched for age, sex and BMI. Bilateral CB-WBCT images performed as standard care were available for each patient. Inclusion criteria were clinically identified HV cases with first intermetatarsal angle (IMA) >10° and HV angles (HVA) >15° as measured on digitally reconstructed radiographs. Patients under 18 years of age, history of trauma or surgery resulting in a potential modification of the forefoot were excluded. Datasets were analyzed using AIAS software which provided: 3D coordinates for spatial position and orientation and angles of the first, second and third metatarsals and cuneiforms, sesamoids, first phalanx of the first ray, navicular, talus, calcaneus. Normality was assessed using a Shapiro-Wilk test and differences between means were calculated using Welch's unequal variances t-test. Results: Mean age and BMI were respectively 57.25 +- 9.65 years and 22.23 +- 2.85 kg.m2; 93.75% (31/32) feet came from women. The mean IMA was 12.9° +- 3° in HV and 8.7° +- 1.4° in controls. In the axial plane, the following measurements were found to be significantly different: IMA (p<0.001), first tarsometatarsal angle (p<0.001) and first-fifth metatarsal angle (p=0.001). In the coronal plane, sesamoid angle (p<0.001), sesamoid shift (p<0.001) and sesamoid rotation (p<0.001) were found significantly different, while first metatarsal torsion was similar in the two groups (p=0.347). Conclusion: The main finding of this study is that AIAS provided an exhaustive series of measurements in the 3 planes of space which were efficient in discriminating between HV and controls with highly significant figures, even when small numerical differences were observed. The introduction of CB-WBCT, which provides images taken during physiological standing stance, followed by the elaboration of data through AIAS (in order to determine absolute or relative positions of bones in space) may help increase efficiency in clinical daily practice.