Iliopsoas tendonitis after total hip arthroplasty : an improved detection method with applications to preoperative planning.

AIMS: Iliopsoas impingement occurs in 4% to 30% of patients after undergoing total hip arthroplasty (THA). Despite a relatively high incidence, there are few attempts at modelling impingement between the iliopsoas and acetabular component, and no attempts at modelling this in a representative cohort of subjects. The purpose of this study was to develop a novel computational model for quantifying the impingement between the iliopsoas and acetabular component and validate its utility in a case-controlled investigation. METHODS: This was a retrospective cohort study of patients who underwent THA surgery that included 23 symptomatic patients diagnosed with iliopsoas tendonitis, and 23 patients not diagnosed with iliopsoas tendonitis. All patients received postoperative CT imaging, postoperative standing radiography, and had minimum six months' follow-up. 3D models of each patient's prosthetic and bony anatomy were generated, landmarked, and simulated in a novel iliopsoas impingement detection model in supine and standing pelvic positions. Logistic regression models were implemented to determine if the probability of pain could be significantly predicted. Receiver operating characteristic curves were generated to determine the model's sensitivity, specificity, and area under the curve (AUC). RESULTS: Highly significant differences between the symptomatic and asymptomatic cohorts were observed for iliopsoas impingement. Logistic regression models determined that the impingement values significantly predicted the probability of groin pain. The simulation had a sensitivity of 74%, specificity of 100%, and an AUC of 0.86. CONCLUSION: We developed a computational model that can quantify iliopsoas impingement and verified its accuracy in a case-controlled investigation. This tool has the potential to be used preoperatively, to guide decisions about optimal cup placement, and postoperatively, to assist in the diagnosis of iliopsoas tendonitis.Cite this article: Bone Jt Open 2023;4(1):3-12.

Distinct Wrist Patterns Founded on Measurements in Plain Radiographs.

Background In joints, structure dictates function and consequently pathology. Interpreting wrist structure is complicated by the existence of multiple joints and variability in bone shapes and anatomical patterns in the wrist. Previous studies evaluated lunate and capitate shape in the midcarpal joint, and two distinct patterns have been identified. Purpose Our purpose was to further characterize the two wrist patterns in normal wrist radiographs using measurements of joint contact and position. Our hypothesis was that we will find significant differences between the two distinct anatomical patterns. Patients and Methods A database of 172 normal adult wrist posteroanterior (PA) radiographs was evaluated for radial inclination, height, length, ulnar variance, volar tilt, radial-styloid-scaphoid distance, and lunate and capitate types. We measured and calculated percent of capitate facet that articulates with the lunate, scapholunate ligament, scaphoid, and trapezoid. These values were compared between the wrist types and whole population. Results Type-1 wrists (lunate type-1 and spherical proximal capitate) were positively associated with a longer facet between capitate and distal lunate ( p = 0.01), capitate and base of middle metacarpal ( p = 0.004), and shorter facet between the capitate and hamate ( p = 0.004). The odds ratio of having a type-1 wrist when the interface between the capitate and lunate measures >8.5 mm is 2.71 (confidence interval [CI] 1.07, 6.87) and when the line between the capitate and the base of middle metacarpal >9.5 mm is 3.5 (CI 1.38, 9.03). Conclusion We characterized the two-wrist patterns using intracarpal measurements. Translating these differences into three-dimensional contact areas may help in the understanding of biomechanical transfer of forces through the wrist. Level of Evidence This is a Level II, diagnostic study.

Intraprostatic Fiducials Compared with Bony Anatomy and Skin Marks for Image-Guided Radiation Therapy of Prostate Cancer.

Purpose Prostate motion occurs during radiotherapy for localized prostate cancer. We evaluated the input of intraprostatic fiducials for image-guided radiation therapy and compared it with bony anatomy and skin marks. Methods Eleven patients were implanted with three fiducial markers in the prostate. Daily sets of orthogonal kV-kV images were compared with digitally reconstructed radiography. Data were recorded for skin marks, bony anatomy, and fiducial markers. The variations were analyzed along three principal axes (left-right: LR, superoinferior: SI, and anteroposterior: AP). Results A total of 2,417 measures were recorded over 38 fractions of radiotherapy (76 Gy). Fiducial marker movements from bony anatomy were ≤ 5 mm for 84.2% (confidence interval: CI 95%±1.5), 91.3% (CI 95%±1.1), and 99.5% (CI 95%±0.4) of the measures along the AP, SI, and LR axes, respectively. Ninety-five percent of the shifts between a fiducial marker and the bony anatomy were < 8 mm in the AP and SI axes, and < 3 mm in the LR axis. Fiducial marker movements from skin marks were ≤ 5 mm for 64.8% (CI 95%±1.9), 79.2% (CI 95%±1.6), and 87.2% (CI 95%±1.3) of the measures along the AP, SI, and LR axes, respectively. Bony anatomy movements from skin marks were ≤ 5 mm for 84% (CI 95%±1.4), 92% (CI 95%±1.1), and 87% (CI 95%±1.3) of the measurements along the AP, SI, and LR axes, respectively. Conclusion Using fiducial markers provides better accuracy of repositioning of the prostate than using bony anatomy and skin marks for image-guided radiotherapy of prostate cancer.

Physiotherapy assessment of shoulder stiffness and how it influences management.

Common causes of shoulder stiffness include osteoarthritis, trauma, rheumatological conditions and stiffness secondary to soft tissue adaptation. Physiotherapy assessment of the stiff shoulder aims to ascertain the key causative factors of stiffness to inform effective management planning. Identification of whether a patient presents with pain or stiffness as their predominant symptom further guides treatment selection. The current evidence base underpins a management algorithm which has been developed to guide the assessment and management of patients presenting with shoulder stiffness.