PurposeThe tibial tubercle–trochlear groove distance (TT–TG) is an established measurement to assist diagnosis and treatment of patellofemoral instability. However, little is known about the distribution of TT–TG in osteoarthritic knees. The purpose of the current study is to investigate the TT–TG in a large cohort of osteoarthritic knees and to analyse, in particular, the association of knee alignment and TT–TG. MethodsData from 962 consecutive patients [455 male, 507 female; mean age ± SD 70.8 ± 9.3 (37–96)] who had undergone 3D‐CT and preoperative knee planning with validated commercial 3D planning software before total knee arthroplasty (TKA) were collected prospectively. The TT–TG, coronal hip knee ankle angle (HKA), femoral anteversion (AVF), external tibial torsion (ETT), and femorotibial rotation (Rot FT) were analysed. Pearson correlations were performed to assess correlations between TT–TG, mechanical axis, and rotational parameters (p < 0.05). ResultsHKA showed a strong correlation with TT–TG (r = 0.488; p < 0.001) with 98 (67.1%) and 45 (30.8%) of valgus knees having respective abnormal and pathological TT–TG values. There were no significant correlations between parameters of rotational alignment (AVF, ETT, Rot FT) and TT–TG. Mean TT–TG was 12.9 ± 5.6 mm, ranging from 0.0 to 33.7 mm. 325 (33.8%) of all patients had abnormal (> 15 mm) and 101 (10.5%) had pathological (> 20 mm) values. A varus alignment was present in 716 (74.4%) of the cases (HKA < − 1.5°), a neutral alignment in 100 (10.4%), and a valgus alignment in 146 (15.2%) (HKA > 1.5°). ConclusionA wide variation of TT–TG values in osteoarthritic knees was shown by our results. There was a relevant influence of coronal limb alignment on the TT–TG—the more valgus the higher and more pathological the TT–TG. With the aim of having a more personalised TKA, the individual TT–TG should be taken into account to improve the outcome. Level of clinical evidenceIII. Retrospective cohort study.

Background There is evidence that specific variants of scapular morphology are associated with dynamic and static posterior shoulder instability. To this date, observations regarding glenoid and/or acromial variants were analyzed independently, with two-dimensional imaging or without comparison with a healthy control group. Therefore, the purpose of this study was to analyze and describe the three-dimensional (3D) shape of the scapula in healthy and in shoulders with static or dynamic posterior instability using 3D surface models and 3D measurement methods. Methods In this study, 30 patients with unidirectional posterior instability and 20 patients with static posterior humeral head subluxation (static posterior instability, Walch B1) were analyzed. Both cohorts were compared with a control group of 40 patients with stable, centered shoulders and without any clinical symptoms. 3D surface models were obtained through segmentation of computed tomography images and 3D measurements were performed for glenoid (version and inclination) and acromion (tilt, coverage, height). Results Overall, the scapulae of patients with dynamic and static instability differed only marginally among themselves. Compared with the control group, the glenoid was 2.5° ( P = .032), respectively, 5.7° ( P = .001) more retroverted and 2.9° ( P = .025), respectively, 3.7° ( P = .014) more downward tilted in dynamic, respectively, static instability. The acromial roof of dynamic instability was significantly higher and on average 6.2° ( P = .007) less posterior covering with an increased posterior acromial height of +4.8mm ( P = .001). The acromial roof of static instability was on average 4.8° ( P = .041) more externally rotated (axial tilt), 7.3° ( P = .004) flatter (sagittal tilt), 8.3° ( P = .001) less posterior covered with an increased posterior acromial height of +5.8 mm (0.001). Conclusion The scapula of shoulders with dynamic and static posterior instability is characterized by an increased glenoid retroversion and an acromion that is shorter posterolaterally, higher, and more horizontal in the sagittal plane. All these deviations from the normal scapula values were more pronounced in static posterior instability.

Purpose There is still lack of knowledge regarding the variability of patellofemoral alignment in healthy, non‐osteoarthritic knees, without patellofemoral instability. Therefore, a systematic review of the existing literature was performed to evaluate the variability of patellofemoral alignment. Methods Patellofemoral alignment of the knee was defined by the following parameters: sulcus angle (SA), femoral trochlear depth (FTD), patellar tilt angle (PTA), lateral patellofemoral angle (LPFA), lateral femoral trochlear inclination (LFTI) and tibial tubercle–trochlear groove distance (TT–TG). The electronic databases MEDLINE and EMBASE were searched from database inception to search date (January 11, 2019) and screened for relevant studies. The PRISMA guidelines were followed. Articles reporting PF alignment measurements of healthy knees in patients between 15 years and 47 years were included. Results A total of 15 studies met the inclusion criteria. The studies reported mean values and standard deviations for the SA between 118.7° ± 7 and 168°; for the FTD between 3.4 mm ± 1.1 and 7.1 mm ± 1.8; for the PTA between 0.7° ± 4.99 and 17.05° ± 4.3; for the LPFA between 6.26° ± 4.1 and 11.1° ± 4.0; for the LFTI between 16.3° ± 2.8 and 22.1° ± 1.9; and for the TT–TG between 9.8 mm ± 4.6 and 17.3 mm ± 5.3. Conclusion Patellofemoral alignment in the healthy knee is extremely variable. A more precise knowledge of the complex relationship between the patella and the trochlea may help to better diagnose PF disorders and eventually help in selecting the correct therapy. Furthermore, standardised imaging protocols and measurement techniques for patellofemoral parameters are needed. Level of evidence III.

Purpose Total knee arthroplasty (TKA) designs continuously evolve with the aim of improving patient outcomes. The purpose of the current study was to compare clinical and patient‐reported outcome (PRO) results of a new TKA implant to its predecessor. The hypothesis of this study was that joint awareness and range of motion (ROM) of the newer design would be better than the classic design. Methods One hundred patients undergoing TKA using the newer design (Attune®) were matched by age and gender to 200 patients with the classic design (LCS®). All patients underwent computer‐navigated (Vector Vision, Brain‐Lab, Germany) primary TKA by the same surgeon using the same technique. Data (FJS‐12, WOMAC and ROM) were collected preoperatively and at 12 months follow‐up at our implant registry. Results Compared to preoperative scores, FJS‐12, WOMAC and ROM improved significantly at 12 months follow‐up. In the Attune group, mean FJS‐12 and WOMAC at follow‐up were 67.6 (SD 27.8) and 14.8 (SD 14.9) respectively, compared to 70.8 (SD 33.8) and 15 (SD 17.9) in the LCS group. Mean postoperative ROM was similar in both groups (Attune 120°, range 90°–140°, SD 10.4 and LCS 120°, range 85°–140°, SD 10.3). Conclusion The newer TKA and the predecessor design achieved comparable joint awareness, WOMAC scores and ROM at 1‐year follow‐up. The benefits expected of the newer design could not be observed in early clinical and PROs. The clinical relevance of this study is that it questions the importance of implant design as the single most important factor for patient outcomes. Level of evidence III.