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PURPOSE The impact of posterolateral tibial plateau impaction fractures (TPIF) on posttraumatic knee stability in the setting of primary anterior cruciate ligament (ACL) tear is unknown. The main objective was to determine whether increased bone loss of the posterolateral tibial plateau is associated with residual rotational instability and impaired functional outcome after ACL reconstruction. METHODS A cohort was identified in a prospective enrolled study of patients suffering acute ACL injury who underwent preoperative standard radiographic diagnostics and clinical evaluation. Patients were included when scheduled for isolated single-bundle hamstring autograft ACL reconstruction. Exclusion criteria were concurrent anterolateral complex (ALC) reconstruction (anterolateral tenodesis), previous surgery or symptoms in the affected knee, partial ACL tear, multi-ligament injury with an indication for additional surgical intervention, and extensive cartilage wear. On MRI, bony (TPIF, tibial plateau, and femoral condyle morphology) and ligament status (ALC, concomitant collateral ligament, and meniscus injuries) were assessed by a musculoskeletal radiologist. Clinical evaluation consisted of KT-1000, pivot-shift, and Lachman testing, as well as Tegner activity and IKDC scores. RESULTS Fifty-eight patients were included with a minimum follow-up of 12 months. TPIF was identified in 85% of ACL injuries (n = 49). The ALC was found to be injured in 31 of 58 (53.4%) cases. Pearson analysis showed a positive correlation between TPIF and the degree of concomitant ALC injury (p < 0.001). Multiple regression analysis revealed an increased association of high-grade TPIF with increased lateral tibial convexity (p = 0.010). The high-grade TPIF group showed worse postoperative Tegner scores 12 months postoperatively (p = 0.035). CONCLUSION Higher degrees of TPIFs are suggestive of a combined ACL/ALC injury. Moreover, patients with increased posterolateral tibial plateau bone loss showe

OBJECTIVES The aim is to validate the performance of a deep convolutional neural network (DCNN) for vertebral body measurements and insufficiency fracture detection on lumbar spine MRI. METHODS This retrospective analysis included 1000 vertebral bodies in 200 patients (age 75.2 ± 9.8 years) who underwent lumbar spine MRI at multiple institutions. 160/200 patients had ≥ one vertebral body insufficiency fracture, 40/200 had no fracture. The performance of the DCNN and that of two fellowship-trained musculoskeletal radiologists in vertebral body measurements (anterior/posterior height, extent of endplate concavity, vertebral angle) and evaluation for insufficiency fractures were compared. Statistics included (a) interobserver reliability metrics using intraclass correlation coefficient (ICC), kappa statistics, and Bland-Altman analysis, and (b) diagnostic performance metrics (sensitivity, specificity, accuracy). A statistically significant difference was accepted if the 95% confidence intervals did not overlap. RESULTS The inter-reader agreement between radiologists and the DCNN was excellent for vertebral body measurements, with ICC values of > 0.94 for anterior and posterior vertebral height and vertebral angle, and good to excellent for superior and inferior endplate concavity with ICC values of 0.79-0.85. The performance of the DCNN in fracture detection yielded a sensitivity of 0.941 (0.903-0.968), specificity of 0.969 (0.954-0.980), and accuracy of 0.962 (0.948-0.973). The diagnostic performance of the DCNN was independent of the radiological institution (accuracy 0.964 vs. 0.960), type of MRI scanner (accuracy 0.957 vs. 0.964), and magnetic field strength (accuracy 0.966 vs. 0.957). CONCLUSIONS A DCNN can achieve high diagnostic performance in vertebral body measurements and insufficiency fracture detection on heterogeneous lumbar spine MRI. KEY POINTS • A DCNN has the potential for high diagnostic performance in measuring vertebral bodies and detecting insuffic

PURPOSE To investigate the predictive value of talar head edema (THE) in acute ankle sprain for the presence of concomitant ligament injuries. METHODS This retrospective study was approved by the ethics committee and informed consent was obtained. One hundred patients (mean age: 37 years ± 14 [standard deviation], range 13-77 years) with MRI of the ankle after acute trauma were included. The cohort in this matched-pair study consisted of 50 patients with THE (group 1) and 50 patients without THE (group 2). Two readers independently evaluated presence and size of bone marrow edema of the talus head and injuries of the lateral, medial, talonavicular, and spring ligament complex. Statistics included intraclass correlation coefficient (ICC) and Kappa statistics as well as parametric and non-parametric tests. RESULTS On average, patients with THE demonstrated significantly more ligament injuries in comparison to patients without THE (3.7 vs. 1.3, p ≤ 0.01). Also, in patients with THE, the number of injured ligaments was significantly higher at the lateral (p = 0.03), medial (p ≤ 0.01), and talonavicular (p ≤ 0.01) compartment in comparison to patients without THE. The most frequently injured ligaments in patients with THE were the anterior talofibular ligament (60%) and the anterior tibiotalar ligament (42%). There was no significant correlation between edema size and the number of injured ligaments or compartments (p = 0.5). CONCLUSION THE is associated with more extensive ligamentous ankle injury, in particular to the medial and lateral collateral ligament complex, and therefore indicative of severe ankle trauma.

Deep learning-based MRI diagnosis of internal joint derangement is an emerging field of artificial intelligence, which offers many exciting possibilities for musculoskeletal radiology. A variety of investigational deep learning algorithms have been developed to detect anterior cruciate ligament tears, meniscus tears, and rotator cuff disorders. Additional deep learning-based MRI algorithms have been investigated to detect Achilles tendon tears, recurrence prediction of musculoskeletal neoplasms, and complex segmentation of nerves, bones, and muscles. Proof-of-concept studies suggest that deep learning algorithms may achieve similar diagnostic performances when compared to human readers in meta-analyses; however, musculoskeletal radiologists outperformed most deep learning algorithms in studies including a direct comparison. Earlier investigations and developments of deep learning algorithms focused on the binary classification of the presence or absence of an abnormality, whereas more advanced deep learning algorithms start to include features for characterization and severity grading. While many studies have focused on comparing deep learning algorithms against human readers, there is a paucity of data on the performance differences of radiologists interpreting musculoskeletal MRI studies without and with artificial intelligence support. Similarly, studies demonstrating the generalizability and clinical applicability of deep learning algorithms using realistic clinical settings with workflow-integrated deep learning algorithms are sparse. Contingent upon future studies showing the clinical utility of deep learning algorithms, artificial intelligence may eventually translate into clinical practice to assist detection and characterization of various conditions on musculoskeletal MRI exams.

OBJECTIVE To investigate the impact of contrast dispersion pattern/location during lumbar CT-guided transforaminal epidural steroid injection (TFESI) and experience of the performing radiologist on therapeutic outcome. MATERIALS AND METHODS In this single-center retrospective cohort study, two observers analyzed contrast dispersion during CT-guided TFESI of 204 patients (age 61.1 ± 14 years) with discogenic unilateral single-level L4 or L5 radiculopathy. The contrast dispersion pattern was classified as "focal," "linear," or "tram-track"; the location was divided into "extraforaminal," "foraminal," or "recessal." Pain was assessed before and 4 weeks after treatment using a numerical rating scale (0, no pain; 10, intolerable pain). Additionally, the patient global impression of change (PGIC) was assessed. The TFESI was performed by musculoskeletal radiologists (experience range: first year of musculoskeletal fellowship training to 19 years). Contrast pattern/location and radiologist's experience were compared between "good responder" (≥ 50% pain reduction) and "poor responder" (< 50%). A p-value < 0.05 was considered to be statistically significant. RESULTS Overall, CT-guided TFESI resulted in a substantial pain reduction in 46.6% of patients with discogenic radiculopathy. The contrast dispersion pattern and location had no effect on pain relief (p = 0.75 and p = 0.09) and PGIC (p = 0.70 and p = 0.21) 4 weeks after TFESI. Additionally, the experience of the radiologist had no influence on pain reduction (p = 0.92) or PGIC (p = 0.75). Regarding pre-interventional imaging findings, both the location and grading of nerve compression had no effect on pain relief (p = 0.91 and p = 0.85) and PGIC (p = 0.18 and p = 0.31). CONCLUSION Our results indicate that neither contrast agent dispersion/location nor the experience of the radiologist allows predicting the therapeutic outcome 4 weeks after the procedure.

OBJECTIVES To compare ultra-low-dose CT (ULD-CT) of the osseous pelvis with tin filtration to standard clinical CT (CT), and to assess the quality of computed virtual pelvic radiographs (VRs). METHODS CT protocols were optimized in a phantom and three pelvic cadavers. Thirty prospectively included patients received both standard CT (automated tube voltage selection and current modulation) and tin-filtered ULD-CT of the pelvis (Sn140kV/50mAs). VRs of ULD-CT data were computed using an adapted cone beam-based projection algorithm and were compared to digital radiographs (DRs) of the pelvis. CT and DR dose parameters and quantitative and qualitative measures (1 = worst, 4 = best) were compared. CT and ULD-CT were assessed for osseous pathologies. RESULTS Dose reduction of ULD-CT was 84% compared to CT, with a median effective dose of 0.38 mSv (quartile 1-3: 0.37-0.4 mSv) versus 2.31 mSv (1.82-3.58 mSv; p < .001), respectively. Mean dose of DR was 0.37 mSv (± 0.14 mSv). The median signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of bone were significantly higher for CT (64.3 and 21.5, respectively) compared to ULD-CT (50.4 and 18.8; p ≤ .01), while ULD-CT was significantly more dose efficient (figure of merit (FOM) 927.6) than CT (FOM 167.6; p < .001). Both CT and ULD-CT were of good image quality with excellent depiction of anatomy, with a median score of 4 (4-4) for both methods (p = .1). Agreement was perfect between both methods regarding the prevalence of assessed osseous pathologies (p > .99). VRs were successfully calculated and were equivalent to DRs. CONCLUSION Tin-filtered ULD-CT of the pelvis at a dose equivalent to standard radiographs is adequate for assessing bone anatomy and osseous pathologies and had a markedly superior dose efficiency than standard CT. KEY POINTS Ultra-low-dose pelvic CT with tin filtration (0.38 mSv) can be performed at a dose of digital radiographs (0.37 mSv), with a dose reduction of 84% compared to standard CT (2.31 mS

OBJECTIVE To evaluate the prevalence, morphology, and clinical significance of a repeatedly observed yet not examined circumscript osseous defect at the anteroinferior aspect of the femoral head, termed femoral head defect. MATERIALS AND METHODS Retrospective study with approval of the institutional review board. There was informed consent by all individuals. Magnetic resonance imaging (MRI) hip examinations of 970 individuals (age 15 to 55) were analyzed for femoral head defect. Patients with femoral head defect were matched for age and gender with patients without defect. Two readers independently assessed MRI images regarding presence, location, and morphology of the defect. MR images and radiographs were analyzed for findings of femoroacetabular impingement (FAI). Femoral torsion was measured. Independent t test and chi-square test were used for statistics. RESULTS Sixty-eight (7%) of 970 MRI examinations exhibited a femoral head defect in an anteroinferior location of the femoral head (29/400 men, 7.3%; 39/570 women, 6.8%; p = 0.8). The most frequent morphology of femoral head defect was type I, dent-like (34; 50%), followed by type II, crater-like (27; 40%), and III, cystic (7; 10%). Femoral head defect was slightly more common on the right hip (39 individuals; 57%) compared to left (29 individuals; 43%), non-significantly (p = 0.115). There was no association between FAI or its subtypes and the presence of femoral head defect (p = 0.890). Femoral antetorsion was reduced in patients with femoral head defect (12.9° ± 8.6) compared to patients without defect (15.2° ± 8.5), without statistical significance (p = 0.121). CONCLUSION The femoral head defect is a common finding in MRI examinations of the hip and is situated in the anteroinferior location. There was no association with FAI yet a non-significant trend towards lower femoral antetorsion in patients with femoral head defects.

BACKGROUND External snapping hip syndrome (ESH) is postulated to be one of the causes of greater trochanteric pain syndrome, which also includes greater trochanteric bursitis and tendinopathy or tears of the hip abductor mechanism. However, it was not yet described what kind of bony morphology can cause the snapping and whether symptomatic and asymptomatic individuals have different imaging features. PURPOSE It was the purpose of this study to look for predisposing morphological factors for ESH and to differentiate between painful and asymptomatic snapping. METHODS A consecutive cohort with ESH and available magnetic resonance imaging (MRI) between 2014 and 2019 was identified. The control group consisted of patients that underwent corrective osteotomies around the knee for mechanical axis correction and never complained of hip symptoms nor had undergone previous hip procedures. The following parameters were blindly assessed for determination of risk factors for ESH: CCD (corpus collum diaphysis) angle; femoral and global offset; femoral antetorsion; functional femoral antetorsion; translation of the greater trochanter (GT); posterior tilt of the GT; pelvic width/anterior pelvic length; intertrochanteric width. Hip and pelvic offset indexes were calculated as ratios of femoral/global offset and intertrochanteric/pelvic width, respectively. For the comparison of symptomatic and asymptomatic snapping, the following soft-tissue signs were investigated: presence of trochanteric bursitis or gluteal tendinopathy; presence of surface bony irregularities on trochanter major and ITB (Iliotibial band) thickness. RESULTS A total of 31 hips with ESH were identified. The control group (n = 29) consisted of patients matched on both age (± 1) and gender. Multiple regression analysis determined an increased hip offset index to be independent predictor of ESH (r = + 0.283, p = 0.025), most likely due to the higher femoral offset in the ESH group (p = 0.031). Pearson correlation ana

OBJECTIVE In total hip arthroplasty (THA), surgeons attempt to achieve a physiological antetorsion. However, postoperative antetorsion of the femoral stem is known to show large variabilities. The purpose of this study was to assess whether postoperative antetorsion is influenced by stem design or cementation. MATERIALS AND METHODS This retrospective study included 227 patients with a hip prosthesis with five different stem designs (S1: short curved, S2 and S3: standard straight, S4: standard straight collared, S5: cemented straight), who had metal suppressed 1.5T-MRI of the hip between February 2015 and October 2019. Measurement of femoral antetorsion was done independently by two fellowship-trained radiologists on axial images by measuring the angle between the long axis of the femoral neck and the posterior condylar tangent of the knee. Measured angles in the different groups were compared using the t test for independent samples. RESULTS The cementless collared stem S4 showed the highest antetorsion with 18.1° (± 10.5°; range -10°-45°), which was significantly higher than the antetorsion of the collarless S3 with 13.3° (± 8.4°; - 4°-29°) and the cemented S5 with 12.7° (± 7.7°; - 3°-27°) with p = 0.012 and p = 0.007, respectively. S1 and S2 showed an antetorsion of 14.8° (± 10.0°; 1°-37°) and 14.1° (± 12.2°; - 20°-41°). The torsional variability of the cementless stems (S1-4) was significantly higher compared with that of the cemented S5 with a combined standard deviation of 10.5° and 7.7° (p = 0.019). CONCLUSION Prosthesis design impacts the postoperative femoral antetorsion, with the cementless collared stem showing the highest antetorsion. Cemented stems demonstrated significantly lower variability, suggesting the lowest rate of inadvertent malrotation.

OBJECTIVE To clinically validate a fully automated deep convolutional neural network (DCNN) for detection of surgically proven meniscus tears. MATERIALS AND METHODS One hundred consecutive patients were retrospectively included, who underwent knee MRI and knee arthroscopy in our institution. All MRI were evaluated for medial and lateral meniscus tears by two musculoskeletal radiologists independently and by DCNN. Included patients were not part of the training set of the DCNN. Surgical reports served as the standard of reference. Statistics included sensitivity, specificity, accuracy, ROC curve analysis, and kappa statistics. RESULTS Fifty-seven percent (57/100) of patients had a tear of the medial and 24% (24/100) of the lateral meniscus, including 12% (12/100) with a tear of both menisci. For medial meniscus tear detection, sensitivity, specificity, and accuracy were for reader 1: 93%, 91%, and 92%, for reader 2: 96%, 86%, and 92%, and for the DCNN: 84%, 88%, and 86%. For lateral meniscus tear detection, sensitivity, specificity, and accuracy were for reader 1: 71%, 95%, and 89%, for reader 2: 67%, 99%, and 91%, and for the DCNN: 58%, 92%, and 84%. Sensitivity for medial meniscus tears was significantly different between reader 2 and the DCNN (p = 0.039), and no significant differences existed for all other comparisons (all p ≥ 0.092). The AUC-ROC of the DCNN was 0.882, 0.781, and 0.961 for detection of medial, lateral, and overall meniscus tear. Inter-reader agreement was very good for the medial (kappa = 0.876) and good for the lateral meniscus (kappa = 0.741). CONCLUSION DCNN-based meniscus tear detection can be performed in a fully automated manner with a similar specificity but a lower sensitivity in comparison with musculoskeletal radiologists.

The article "Deep convolutional neural network-based detection of meniscus tears: comparison with radiologists and surgery as standard of reference.

OBJECTIVES: This study was conducted in order to determine the predictive value of MR arthrography findings for pain relief after glenohumeral corticosteroid injection. METHODS: This study prospectively enrolled 212 patients (mean age 51.4 years; range 15-90) who underwent fluoroscopy-guided glenohumeral corticosteroid injection. All patients received MR arthrography of the shoulder less than 3 months prior to the infiltration and returned questionnaires which assessed patients' shoulder pain using the 11-point numeric rating scale (NRS), covering a 1-month follow-up period. MR arthrograms were retrospectively assessed for abnormalities of the rotator cuff, long biceps tendon, glenohumeral bone, cartilage, and labrum as well as for synovitis, bursitis, and signs of adhesive capsulitis. MR arthrography findings were compared to patients' NRS change using the Mann-Whitney U and Kruskal-Wallis tests for univariate analysis and multiple linear regression for multivariate analysis. RESULTS: Pain reduction of ≥ 2 points was considered to represent clinically relevant improvement, which was seen in 71% of patients 1 week and in 74% of patients 1 month after glenohumeral injection. Univariate analysis of MR findings showed that signs of adhesive capsulitis and an intact labrum were associated with significantly higher NRS reductions after 1 month in comparison to patients without these findings (median 4 vs. 3, p = 0.007 and 4 vs. 2, p = 0.003, respectively). Multivariate analysis proved both factors to be independent predictors of improved outcome after 1 month (beta = 0.176, p = 0.039 and beta = 0.212, p = 0.001, respectively). CONCLUSIONS: Glenohumeral corticosteroid injections for pain relief have a high success rate with 74% of patients reporting clinically relevant improvement after 1 month. Signs of adhesive capsulitis and an intact labrum on MR arthrography are independent predictors of a better outcome. KEY POINTS • Seventy-four percent of patients report clinicall