Advertisement for orthosearch.org.uk
Results 1 - 3 of 3
Results per page:
Bone & Joint Open
Vol. 5, Issue 4 | Pages 335 - 342
19 Apr 2024
Athavale SA Kotgirwar S Lalwani R

Aims

The Chopart joint complex is a joint between the midfoot and hindfoot. The static and dynamic support system of the joint is critical for maintaining the medial longitudinal arch of the foot. Any dysfunction leads to progressive collapsing flatfoot deformity (PCFD). Often, the tibialis posterior is the primary cause; however, contrary views have also been expressed. The present investigation intends to explore the comprehensive anatomy of the support system of the Chopart joint complex to gain insight into the cause of PCFD.

Methods

The study was conducted on 40 adult embalmed cadaveric lower limbs. Chopart joint complexes were dissected, and the structures supporting the joint inferiorly were observed and noted.


Bone & Joint Open
Vol. 3, Issue 3 | Pages 268 - 274
21 Mar 2022
Krishnan H Eldridge JD Clark D Metcalfe AJ Stevens JM Mandalia V

Recognized anatomic variations that lead to patella instability include patella alta and trochlea dysplasia. Lateralization of the extensor mechanism relative to the trochlea is often considered to be a contributing factor; however, controversy remains as to the degree this contributes to instability and how this should be measured. As the tibial tuberosity-trochlear groove (TT-TG) is one of most common imaging measurements to assess lateralization of the extensor mechanism, it is important to understand its strengths and weaknesses. Care needs to be taken while interpreting the TT-TG value as it is affected by many factors. Medializing tibial tubercle osteotomy is sometimes used to correct the TT-TG, but may not truly address the underlying anatomical problem. This review set out to determine whether the TT-TG distance sufficiently summarizes the pathoanatomy, and if this assists with planning of surgery in patellar instability. Cite this article: Bone Jt Open 2022;3(3):268–274


Bone & Joint Open
Vol. 2, Issue 10 | Pages 879 - 885
20 Oct 2021
Oliveira e Carmo L van den Merkhof A Olczak J Gordon M Jutte PC Jaarsma RL IJpma FFA Doornberg JN Prijs J

Aims

The number of convolutional neural networks (CNN) available for fracture detection and classification is rapidly increasing. External validation of a CNN on a temporally separate (separated by time) or geographically separate (separated by location) dataset is crucial to assess generalizability of the CNN before application to clinical practice in other institutions. We aimed to answer the following questions: are current CNNs for fracture recognition externally valid?; which methods are applied for external validation (EV)?; and, what are reported performances of the EV sets compared to the internal validation (IV) sets of these CNNs?

Methods

The PubMed and Embase databases were systematically searched from January 2010 to October 2020 according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The type of EV, characteristics of the external dataset, and diagnostic performance characteristics on the IV and EV datasets were collected and compared. Quality assessment was conducted using a seven-item checklist based on a modified Methodologic Index for NOn-Randomized Studies instrument (MINORS).