MRI-based 3D models of the hip joint enables radiation-free computer-assisted planning of periacetabular osteotomy for treatment of hip dysplasia using deep learning for automatic segmentation

3.0T magnetic resonance imaging-based hip bone models for femoroacetabular impingement syndrome are equivalent to computed tomography-based models

This study aimed to compare three-dimensional (3D) proximal femoral and acetabular surface models generated from 3.0T magnetic resonance imaging (MRI) to the clinical gold standard of computed tomography (CT). Ten intact fresh-frozen cadaveric hips underwent CT and 3.0T MRI scans. The CT- and MRI-based segmented models were superimposed using a validated 3D-3D registration volume-merge method to compare them. The least surface-to-surface distance between the models was calculated by a point-to-surface calculation algorithm using a custom-written program. The variables of interest were the signed and absolute surface-to-surface distance between the paired bone models. One-sample t-tests were performed using a signed and absolute test value of 0.16 mm and 0.37 mm, respectively, based on a previous study that validated 1.5T MRI bone models by comparison with CT bone models. For the femur, the average signed and absolute surface-to-surface distance was 0.18 ± 0.09 mm and 0.30 ± 0.06 mm, respectively. There was no difference in the signed surface-to-surface distance and the 0.16 mm test value (t = 0.650, p = 0.532). However, the absolute surface-to-surface difference was less than the 0.37 mm test value (t = -4.025, p = 0.003). For the acetabulum, the average signed and absolute surface-to-surface distance was -0.06 ± 0.06 mm and 0.26 ± 0.04 mm, respectively. The signed (t = -12.569, p < 0.001) and absolute (t = -8.688, p < 0.001) surface-to-surface difference were less than the 0.16 mm and 0.37 mm test values, respectively. Our data shows that 3.0T MRI bone models are more similar to CT bone models than previously validated 1.5T MRI bone models. This is likely due to the higher resolution of the 3T data.

Ultra-low dose hip CT-based automated measurement of volumetric bone mineral density at proximal femoral subregions

BACKGROUND

Forty to fifty percent of women and 13%-22% of men experience an osteoporosis-related fragility fracture in their lifetimes. After the age of 50 years, the risk of hip fracture doubles in every 10 years. x-Ray based DXA is currently clinically used to diagnose osteoporosis and predict fracture risk. However, it provides only 2-D representation of bone and is associated with other technical limitations. Thus, alternative methods are needed.

PURPOSE

To develop and evaluate an ultra-low dose (ULD) hip CT-based automated method for assessment of volumetric bone mineral density (vBMD) at proximal femoral subregions.

METHODS

An automated method was developed to segment the proximal femur in ULD hip CT images and delineate femoral subregions. The computational pipeline consists of deep learning (DL)-based computation of femur likelihood map followed by shape model-based femur segmentation and finite element analysis-based warping of a reference subregion labeling onto individual femur shapes. Finally, vBMD is computed over each subregion in the target image using a calibration phantom scan. A total of 100 participants (50 females) were recruited from the Genetic Epidemiology of COPD (COPDGene) study, and ULD hip CT imaging, equivalent to 18 days of background radiation received by U.S. residents, was performed on each participant. Additional hip CT imaging using a clinical protocol was performed on 12 participants and repeat ULD hip CT was acquired on another five participants. ULD CT images from 80 participants were used to train the DL network; ULD CT images of the remaining 20 participants as well as clinical and repeat ULD CT images were used to evaluate the accuracy, generalizability, and reproducibility of segmentation of femoral subregions. Finally, clinical CT and repeat ULD CT images were used to evaluate accuracy and reproducibility of ULD CT-based automated measurements of femoral vBMD.

RESULTS

Dice scores of accuracy (n = 20), reproducibility (n = 5), and generalizability (n = 12) of ULD CT-based automated subregion segmentation were 0.990, 0.982, and 0.977, respectively, for the femoral head and 0.941, 0.970, and 0.960, respectively, for the femoral neck. ULD CT-based regional vBMD showed Pearson and concordance correlation coefficients of 0.994 and 0.977, respectively, and a root-mean-square coefficient of variation (RMSCV) (%) of 1.39% with the clinical CT-derived reference measure. After 3-digit approximation, each of Pearson and concordance correlation coefficients as well as intraclass correlation coefficient (ICC) between baseline and repeat scans were 0.996 with RMSCV of 0.72%. Results of ULD CT-based bone analysis on 100 participants (age (mean ± SD) 73.6 ± 6.6 years) show that males have significantly greater (p < 0.01) vBMD at the femoral head and trochanteric regions than females, while females have moderately greater vBMD (p = 0.05) at the medial half of the femoral neck than males.

CONCLUSION

Deep learning, combined with shape model and finite element analysis, offers an accurate, reproducible, and generalizable algorithm for automated segmentation of the proximal femur and anatomic femoral subregions using ULD hip CT images. ULD CT-based regional measures of femoral vBMD are accurate and reproducible and demonstrate regional differences between males and females.

Deep learning-based workflow for hip joint morphometric parameter measurement from CT images

Objective.Precise hip joint morphometry measurement from CT images is crucial for successful preoperative arthroplasty planning and biomechanical simulations. Although deep learning approaches have been applied to clinical bone surgery planning, there is still a lack of relevant research on quantifying hip joint morphometric parameters from CT images.Approach.This paper proposes a deep learning workflow for CT-based hip morphometry measurement. For the first step, a coarse-to-fine deep learning model is designed for accurate reconstruction of the hip geometry (3D bone models and key landmark points). Based on the geometric models, a robust measurement method is developed to calculate a full set of morphometric parameters, including the acetabular anteversion and inclination, the femoral neck shaft angle and the inclination, etc. Our methods were validated on two datasets with different imaging protocol parameters and further compared with the conventional 2D x-ray-based measurement method.Main results. The proposed method yields high bone segmentation accuracies (Dice coefficients of 98.18% and 97.85%, respectively) and low landmark prediction errors (1.55 mm and 1.65 mm) on both datasets. The automated measurements agree well with the radiologists' manual measurements (Pearson correlation coefficients between 0.47 and 0.99 and intraclass correlation coefficients between 0.46 and 0.98). This method provides more accurate measurements than the conventional 2D x-ray-based measurement method, reducing the error of acetabular cup size from over 2 mm to less than 1 mm. Moreover, our morphometry measurement method is robust against the error of the previous bone segmentation step. As we tested different deep learning methods for the prerequisite bone segmentation, our method produced consistent final measurement results, with only a 0.37 mm maximum inter-method difference in the cup size.Significance. This study proposes a deep learning approach with improved robustness and accuracy for pelvis arthroplasty planning.

3D Printing Technology in Pediatric Orthopedics: a Primer for the Clinician

PURPOSE OF REVIEW

This article reviews the basics of 3D printing and provides an overview of current and future applications of this emerging technology in pediatric orthopedic surgery.

RECENT FINDINGS

Both preoperative and intraoperative utilization of 3D printing technology have enhanced clinical care. Potential benefits include more accurate surgical planning, shortening of a surgical learning curve, decrease in intraoperative blood loss, less operative time, and fluoroscopic time. Furthermore, patient-specific instrumentation can be used to improve the safety and accuracy of surgical care. Patient-physician communication can also benefit from 3D printing technology. 3D printing is rapidly advancing in the field of pediatric orthopedic surgery. It has the potential to increase the value of several pediatric orthopedic procedures by enhancing safety and accuracy while saving time. Future efforts in cost reduction strategies, making patient-specific implants including biologic substitutes and scaffolds, will further increase the relevance of 3D technology in the field of pediatric orthopedic surgery.

[Innovative image-based planning in musculoskeletal surgery]

BACKGROUND

For the preparation of surgical procedures in orthopedics and trauma surgery, precise knowledge of imaging and the three-dimensional imagination of the surgeon are of outstanding importance. Image-based, preoperative two-dimensional planning is the gold standard in arthroplasty today. In complex cases, further imaging such as computed tomography (CT) or magnetic resonance imaging is also performed, generating a three-dimensional model of the body region and helping the surgeon in the planning of the surgical treatment. Four-dimensional, dynamic CT studies have also been reported and are available as a complementary tool.

DIGITAL AIDS

Furthermore, digital aids should generate an improved representation of the pathology to be treated and optimize the surgeon's imagination. The finite element method allows patient-specific and implant-specific parameters to be taken into account in preoperative surgical planning. Intraoperatively, relevant information can be provided by augmented reality without significantly influencing the surgical workflow.

Deep-Learning-Based Segmentation of the Shoulder from MRI with Inference Accuracy Prediction

Three-dimensional (3D)-image-based anatomical analysis of rotator cuff tear patients has been proposed as a way to improve repair prognosis analysis to reduce the incidence of postoperative retear. However, for application in clinics, an efficient and robust method for the segmentation of anatomy from MRI is required. We present the use of a deep learning network for automatic segmentation of the humerus, scapula, and rotator cuff muscles with integrated automatic result verification. Trained on N = 111 and tested on N = 60 diagnostic T1-weighted MRI of 76 rotator cuff tear patients acquired from 19 centers, a nnU-Net segmented the anatomy with an average Dice coefficient of 0.91 ± 0.06. For the automatic identification of inaccurate segmentations during the inference procedure, the nnU-Net framework was adapted to allow for the estimation of label-specific network uncertainty directly from its subnetworks. The average Dice coefficient of segmentation results from the subnetworks identified labels requiring segmentation correction with an average sensitivity of 1.0 and a specificity of 0.94. The presented automatic methods facilitate the use of 3D diagnosis in clinical routine by eliminating the need for time-consuming manual segmentation and slice-by-slice segmentation verification.

[Preoperative MR imaging for hip dysplasia : Assessment of associated deformities and intraarticular pathologies]

BACKGROUND

Developmental dysplasia of the hip (DDH) is a known reason for hip pain for adolescents and young adults. Preoperative imaging is increasingly recognized as an important factor due to the recent advances in MR imaging.

OBJECTIVES

The aim of this article is to give an overview of preoperative imaging for DDH. The acetabular version and morphology, associated femoral deformities (cam deformity, valgus and femoral antetorsion) and intraarticular pathologies (labrum and cartilage damage) and cartilage mapping are described.

METHODS

After an initial evaluation with AP radiographs, CT or MRI represent the methods of choice for the preoperative evaluation of the acetabular morphology and cam deformity, and for the measurement of femoral torsion. Different measurement techniques and normal values should be considered, especially for patients with increased femoral antetorsion because this could lead to misinterpretation and misdiagnosis. MRI allows analysis of labrum hypertrophy and subtle signs for hip instability. 3D MRI for cartilage mapping allows quantification of biochemical cartilage degeneration and yields great potential for surgical decision-making. 3D-CT and, increasingly, 3D MRI of the hip to generate 3D pelvic bone models and subsequent 3D impingement simulation can help to detect posterior extraarticular ischiofemoral impingement.

RESULTS AND DISCUSSION

Acetabular morphology can be divided in anterior, lateral and posterior hip dysplasia. Combined osseous deformities are common, such as hip dysplasia combined with cam deformity (86%). Valgus deformities were reported in 44%. Combined hip dysplasia and increased femoral antetorsion can occur in 52%. Posterior extraarticular ischiofemoral impingement between the lesser trochanter and the ischial tuberosity can occur in patients with increased femoral antetorsion. Typically, labrum damage and hypertrophy, cartilage damage, subchondral cysts can occur in hip dysplasia. Hypertrophy of the muscle iliocapsularis is a sign for hip instability. Acetabular morphology and femoral deformities (cam deformity and femoral anteversion) should be evaluated before surgical therapy for patients with hip dysplasia, considering the different measurement techniques and normal values of femoral antetorsion.

Femoral impingement in maximal hip flexion is anterior-inferior distal to the cam deformity in femoroacetabular impingement patients with femoral retroversion : implications for hip arthroscopy

AIMS

Femoroacetabular impingement (FAI) patients report exacerbation of hip pain in deep flexion. However, the exact impingement location in deep flexion is unknown. The aim was to investigate impingement-free maximal flexion, impingement location, and if cam deformity causes hip impingement in flexion in FAI patients.

METHODS

A retrospective study involving 24 patients (37 hips) with FAI and femoral retroversion (femoral version (FV) < 5° per Murphy method) was performed. All patients were symptomatic (mean age 28 years (SD 9)) and had anterior hip/groin pain and a positive anterior impingement test. Cam- and pincer-type subgroups were analyzed. Patients were compared to an asymptomatic control group (26 hips). All patients underwent pelvic CT scans to generate personalized CT-based 3D models and validated software for patient-specific impingement simulation (equidistant method).

RESULTS

Mean impingement-free flexion of patients with mixed-type FAI (110° (SD 8°)) and patients with pincer-type FAI (112° (SD 8°)) was significantly (p < 0.001) lower compared to the control group (125° (SD 13°)). The frequency of extra-articular subspine impingement was significantly (p < 0.001) increased in patients with pincer-type FAI (57%) compared to cam-type FAI (22%) in 125° flexion. Bony impingement in maximal flexion was located anterior-inferior at femoral four and five o'clock position in patients with cam-type FAI (63% (10 of 16 hips) and 37% (6 of 10 hips)), and did not involve the cam deformity. The cam deformity did not cause impingement in maximal flexion.

CONCLUSION

Femoral impingement in maximal flexion was located anterior-inferior distal to the cam deformity. This differs to previous studies, a finding which could be important for FAI patients in order to avoid exacerbation of hip pain in deep flexion (e.g. during squats) and for hip arthroscopy (hip-preservation surgery) for planning of bone resection. Hip impingement in flexion has implications for daily activities (e.g. putting on shoes), sports, and sex.Cite this article: Bone Joint Res 2023;12(1):22-32.

Efficient cascaded V-net optimization for lower extremity CT segmentation validated using bone morphology assessment

Semantic segmentation of bone from lower extremity computerized tomography (CT) scans can improve and accelerate the visualization, diagnosis, and surgical planning in orthopaedics. However, the large field of view of these scans makes automatic segmentation using deep learning based methods challenging, slow and graphical processing unit (GPU) memory intensive. We investigated methods to more efficiently represent anatomical context for accurate and fast segmentation and compared these with state-of-the-art methodology. Six lower extremity bones from patients of two different datasets were manually segmented from CT scans, and used to train and optimize a cascaded deep learning approach. We varied the number of resolution levels, receptive fields, patch sizes, and number of V-net blocks. The best performing network used a multi-stage, cascaded V-net approach with 128³ -64³ -32³ voxel patches as input. The average Dice coefficient over all bones was 0.98 ± 0.01, the mean surface distance was 0.26 ± 0.12 mm and the 95th percentile Hausdorff distance 0.65 ± 0.28 mm. This was a significant improvement over the results of the state-of-the-art nnU-net, with only approximately 1/12th of training time, 1/3th of inference time and 1/4th of GPU memory required. Comparison of the morphometric measurements performed on automatic and manual segmentations showed good correlation (Intraclass Correlation Coefficient [ICC] >0.8) for the alpha angle and excellent correlation (ICC >0.95) for the hip-knee-ankle angle, femoral inclination, femoral version, acetabular version, Lateral Centre-Edge angle, acetabular coverage. The segmentations were generally of sufficient quality for the tested clinical applications and were performed accurately and quickly compared to state-of-the-art methodology from the literature.

Limited Hip Flexion and Internal Rotation Resulting From Early Hip Impingement Conflict on Anterior Metaphysis of Patients With Untreated Severe SCFE Using 3D Modelling

INTRODUCTION

Slipped capital femoral epiphysis (SCFE) is the most common hip disorder in adolescent patients that can result in complex 3 dimensional (3D)-deformity and hip preservation surgery (eg, in situ pinning or proximal femoral osteotomy) is often performed. But there is little information about location of impingement.Purpose/Questions: The purpose of this study was to evaluate (1) impingement-free hip flexion and internal rotation (IR), (2) frequency of impingement in early flexion (30 to 60 degrees), and (3) location of acetabular and femoral impingement in IR in 90 degrees of flexion (IRF-90 degrees) and in maximal flexion for patients with untreated severe SCFE using preoperative 3D-computed tomography (CT) for impingement simulation.

METHODS

A retrospective study involving 3D-CT scans of 18 patients (21 hips) with untreated severe SCFE (slip angle>60 degrees) was performed. Preoperative CT scans were used for bone segmentation of preoperative patient-specific 3D models. Three patients (15%) had bilateral SCFE. Mean age was 13±2 (10 to 16) years and 67% were male patients (86% unstable slip, 81% chronic slip). The contralateral hips of 15 patients with unilateral SCFE were evaluated (control group). Validated software was used for 3D impingement simulation (equidistant method).

RESULTS

(1) Impingement-free flexion (46±32 degrees) and IRF-90 degrees (-17±18 degrees) were significantly ( P <0.001) decreased in untreated severe SCFE patients compared with contralateral side (122±9 and 36±11 degrees).(2) Frequency of impingement was significantly ( P <0.001) higher in 30 and 60 degrees flexion (48% and 71%) of patients with severe SCFE compared with control group (0%).(3) Acetabular impingement conflict was located anterior-superior (SCFE patients), mostly 12 o'clock (50%) in IRF-90 degrees (70% on 2 o'clock for maximal flexion). Femoral impingement was located on anterior-superior to anterior-inferior femoral metaphysis (between 2 and 6 o'clock, 40% on 3 o'clock and 40% on 5 o'clock) in IRF-90 degrees and on anterior metaphysis (40% on 3 o'clock) in maximal flexion and frequency was significantly ( P <0.001) different compared with control group.

CONCLUSION

Severe SCFE patients have limited hip flexion and IR due to early hip impingement using patient-specific preoperative 3D models. Because of the large variety of hip motion, individual evaluation is recommended to plan the osseous correction for severe SCFE patients.

LEVEL OF EVIDENCE

Level III.

Biocompatibility of 3D-printed PLA, PEEK and PETG: Adhesion of Bone Marrow and Peritoneal Lavage Cells

Samples in the form of cylindrical plates, additively manufactured using the fused deposition modelling (or filament freeform fabrication, FDM/FFF) technology from polylactide (PLA), polyethylene terephthalate glycol (PETG) and polyetheretherketone (PEEK), were studied in series of in-vitro experiments on the adhesion of rat bone-marrow cells and rat peritoneal cells. Methods of estimation of the absolute number of cells and polymer samples’ mass change were used for the evaluation of cells adhesion, followed by the evaluation of cell-culture supernatants. The results of experiments for both types of cells demonstrated a statistically significant change in the absolute number of cells (variation from 44 to 119%) and the weight of the polymer samples (variation from 0.61 to 2.18%), depending on roughness of sample surface, controlled by a nozzle diameter of a 3D printer as well as printing layer height. It was found that more cells adhere to PLA samples with a larger nozzle diameter and layer height. For PETG samples, the results did not show a clear relationship between cell adhesion and printing parameters. For PEEK samples, on the contrary, adhesion to samples printed with a lower nozzle diameter (higher resolution) is better than to samples printed with a larger nozzle diameter (lower resolution). The difference in results for various polymers can be explained by their chemical structure.

Automated measurement of alpha angle on 3D-magnetic resonance imaging in femoroacetabular impingement hips: a pilot study

BACKGROUND

Femoroacetabular impingement (FAI) syndrome is an established pre-osteoarthritic condition. Diagnosis is based on both clinical and radiographic parameters. An abnormal manually calculated alpha angle in magnetic resonance imaging (MRI) is traditionally utilized to diagnose abnormal femoral head-neck offset. This pilot study aimed to assess the feasibility of automated alpha angle measurements in patients with FAI syndrome, and to compare automated with manual measurements data with regard to the time and effort needed in each method.

METHODS

Alpha angles were measured with manual and automated techniques, using postprocessing software in nineteen hip MRIs of FAI syndrome patients. Two observers conducted manual measurements. Intra- and inter-observer reproducibility and correlation of manual and automated alpha angle measurements were calculated using intra-class correlation (ICC) analysis. Both techniques were compared regarding the time taken (in minutes) and effort required, measured as the amount of mouse button presses performed.

RESULTS

The first observer's intra-observer reproducibility was good (ICC 0.77; p < 0.001) while the second observer's was good-to-excellent (ICC 0.93; p < 0.001). Inter-observer reproducibility between both observers in the first (ICC 0.45; p < 0.001) and second (ICC 0.56; p < 0.001) manual alpha angle assessment was moderate. The intra-class correlation coefficients between manual and automated alpha angle measurements were ICC = 0.24 (p = 0.052; observer 1, 1st measurement), ICC = 0.32 (p = 0.015; observer 1, 2nd measurement), ICC = 0.50 (p < 0.001; observer 2, 1st measurement), and ICC = 0.45 (p < 0.001; observer 2, 2nd measurement). Average runtime for automatic processing of the image data for the automated assessment was 16.6 ± 1.9 min. Automatic alpha angle measurements took longer (time difference: 14.6 ± 3.9 min; p < 0.001) but required less effort (difference in button presses: 231 ± 23; p < 0.001). While the automatic processing is running, the user can perform other tasks.

CONCLUSIONS

This pilot study demonstrates that objective and reliable automated alpha angle measurement of MRIs in FAI syndrome hips is feasible. Trial registration The Ethics Committee of the University of Düsseldorf approved our study (Registry-ID: 2017084398).

MRI-- and CT--based metrics for the quantification of arthroscopic bone resections in femoroacetabular impingement syndrome

The purpose of this in vitro study was to quantify the bone resected from the proximal femur during hip arthroscopy using metrics generated from magnetic resonance imaging (MRI) and computed tomography (CT) reconstructed three-dimensional (3D) bone models. Seven cadaveric hemi-pelvises underwent both a 1.5 T MRI and CT scan before and following an arthroscopic proximal femoral osteochondroplasty. The images from MRI and CT were segmented to generate 3D proximal femoral surface models. A validated 3D--3D registration method was used to compare surface--to--surface distances between the 3D models before and following surgery. The new metrics of maximum height, mean height, surface area and volume, were computed to quantify bone resected during osteochondroplasty. Stability of the metrics across imaging modalities was established through paired sample t--tests and bivariate correlation. Bivariate correlation analyses indicated strong correlations between all metrics (r = 0.728--0.878) computed from MRI and CT derived models. There were no differences in the MRI- and CT-based metrics used to quantify bone resected during femoral osteochondroplasty. Preoperative- and postoperative MRI and CT derived 3D bone models can be used to quantify bone resected during femoral osteochondroplasty, without significant differences between the imaging modalities.

Combined abnormalities of femoral version and acetabular version and McKibbin Index in FAI patients evaluated for hip preservation surgery

Frequencies of combined abnormalities of femoral version (FV) and acetabular version (AV) and of abnormalities of the McKibbin index are unknown. To investigate the prevalence of combined abnormalities of FV and AV and of abnormalities of the McKibbin index in symptomatic patients with femoroacetabular impingement (FAI), a retrospective, Institutional Review Board (IRB)-approved study of 333 symptomatic patients (384 hips) that were presented with hip pain and FAI was performed. The computed tomography/magnetic resonance imaging based measurement of central AV, cranial AV and FV was compared among five subgroups with distinguished FAI subgroups and patients that underwent a hip preservation surgery. The allocation to each subgroup was based on AP radiographs. Normal AV and FV were 10–25°. The McKibbin index is the sum of central AV and FV. Of patients that underwent a hip preservation surgery, 73% had a normal McKibbin index (20–50°) but 27% had an abnormal McKibbin index. Of all patients, 72% had a normal McKibbin index, but 28% had abnormal McKibbin index. The prevalence of combined abnormalities of FV and AV varied among subgroups: a higher prevalence of decreased central AV combined with decreased FV of patients with acetabular-retroversion group (12%) and overcoverage (11%) was found compared with mixed-type FAI (5%). Normal AV combined with normal FV was present in 41% of patients with cam-type FAI and in 34% of patients with overcoverage. Patients that underwent a hip preservation surgery had normal mean FV (17 ± 11°), central AV (19 ± 7°), cranial AV (16 ± 10°) and McKibbin index (36 ± 14°). Frequency of combined abnormalities of AV and FV differs between subgroups of FAI patients. Aggravated and compensated McKibbin index was prevalent in FAI patients. This has implications for open hip preservation surgery (surgical hip dislocation or femoral derotation osteotomy) or hip arthroscopy or non-operative treatment.

[Imaging in joint-preserving hip surgery]

Instabilität und Impingement stellen die Hauptpathomechanismen dar, die bereits bei jungen Patienten durch erhöhten mechanischen Stress zu chondrolabralen Schäden, schmerzhafter Bewegungseinschränkung und frühzeitiger Coxarthrose führen können. Ziele der gelenkerhaltenden Chirurgie an der Hüfte sind die Korrektur der knöchernen Deformitäten und chondrolabraler Schäden sowie die Wiederherstellung der Gelenkfunktion. Voraussetzung dafür ist die Identifikation der ursächlichen Pathologien an der Hüfte, welche zudem in Kombination auftreten können. Die dezidierte Röntgen- und Magnetresonanzbildgebung der knöchernen Morphologie und der degenerativen Gelenkbinnenläsionen liefern einen essenziellen Beitrag für die Behandlungsindikation und die Behandlungsplanung. Der vorliegende Artikel soll einen kurzen Überblick über die Hüftdeformitäten mit deren Prävalenz, Pathomechanismus und indizierter Therapie sowie detaillierte Empfehlungen über die spezifische radiologische Abklärung geben.

Magnetic Resonance Imaging Versus Computed Tomography for Three-Dimensional Bone Imaging of Musculoskeletal Pathologies: A Review

Magnetic resonance imaging (MRI) is increasingly utilized as a radiation‐free alternative to computed tomography (CT) for the diagnosis and treatment planning of musculoskeletal pathologies. MR imaging of hard tissues such as cortical bone remains challenging due to their low proton density and short transverse relaxation times, rendering bone tissues as nonspecific low signal structures on MR images obtained from most sequences. Developments in MR image acquisition and post‐processing have opened the path for enhanced MR‐based bone visualization aiming to provide a CT‐like contrast and, as such, ease clinical interpretation. The purpose of this review is to provide an overview of studies comparing MR and CT imaging for diagnostic and treatment planning purposes in orthopedic care, with a special focus on selective bone visualization, bone segmentation, and three‐dimensional (3D) modeling. This review discusses conventional gradient‐echo derived techniques as well as dedicated short echo time acquisition techniques and post‐processing techniques, including the generation of synthetic CT, in the context of 3D and specific bone visualization. Based on the reviewed literature, it may be concluded that the recent developments in MRI‐based bone visualization are promising. MRI alone provides valuable information on both bone and soft tissues for a broad range of applications including diagnostics, 3D modeling, and treatment planning in multiple anatomical regions, including the skull, spine, shoulder, pelvis, and long bones.

Diagnosis of acetabular retroversion: Three signs positive and increased retroversion index have higher specificity and higher diagnostic accuracy compared to isolated positive cross over sign

Objectives

The crossover-sign (COS) is a radiographic sign for diagnosis of acetabular-retroversion(AR) in patients with femoroacetabular-impingement (FAI) but overestimates AR. Three signs combined with retroversion-index (RI) could potentially improve diagnostic-accuracy.

Aims

(1)

To calculate central acetabular-version (AV, CT/MRI) in patients with isolated positive COS and in patients with three radiographic signs for AR on radiographs (AP).

(2)

To calculate diagnostic performance of positive COS and of three signs combined with retroversion-index (RI) > 30% on radiographs (AP) to detect global AR (AV < 10°, CT/MRI).

Methods

A retrospective, IRB-approved, controlled diagnostic study comparing radiographic signs for AR (AP radiographs) with MRI/CT-based measurement of central AV was performed. 462 symptomatic patients (538 hips) with FAI or hip-dysplasia were compared to control-group (48 hips). Three signs for AR(on radiographs) were analyzed: COS, posterior-wall-sign and ischial-spine-sign. RI (synonym cross-over-index) quantifies overlap of anterior and posterior wall in case of positive COS. Diagnostic performance for COS and for three signs combined with RI > 30% to detect central AV < 10° (global AR) was calculated.

Results

(1)

Central AV was significantly (p < 0.001) decreased (13 ± 6°, CT/MRI) in patients with three signs for AR and RI > 30% on radiographs compared to patients with positive COS (18 ± 7°).

(2)

Sensitivity and specificity of three signs combined with RI > 30% on radiographs was 85% and 63% (87% and 23% for COS). Negative-predictive-value (NPV) was 94% (93% for COS) to rule out global AR (AV < 10°, CT/MRI). Diagnostic accuracy increased significantly (p < 0.001) from 31% (COS) to 68% using three signs.

Conclusion

Improved specificity and diagnostic accuracy for diagnosis of global AR can help to avoid misdiagnosis. Global AR can be ruled out with a probability of 94% (NPV) in the absence of three radiographic signs combined with retroversion-index < 30% (e.g. isolated COS positive).

Real-world analysis of artificial intelligence in musculoskeletal trauma

Musculoskeletal trauma accounts for a large percentage of emergency room visits and is amongst the top causes of unscheduled patient visits to the emergency room. Musculoskeletal trauma results in expenditure of billions of dollars and protracted losses of quality-adjusted life years. New and innovative methods are needed to minimise the impact by ensuring quick and accurate assessment. However, each of the currently utilised radiological procedures, such as radiography, ultrasonography, computed tomography, and magnetic resonance imaging, has resulted in implosion of medical imaging data. Deep learning, a recent advancement in artificial intelligence, has demonstrated the potential to analyse medical images with sensitivity and specificity at par with experts. In this review article, we intend to summarise and showcase the various developments which have occurred in the dynamic field of artificial intelligence and machine learning and how their applicability to different aspects of imaging in trauma can be explored to improvise our existing reporting systems and improvise on patient outcomes.

3D MRI Models of the Musculoskeletal System

Computed tomography (CT) is most commonly used to produce three-dimensional (3D) models for evaluating bone and joint morphology in clinical practice. However, 3D models created from magnetic resonance imaging (MRI) data can be equally effective for comprehensive and accurate assessment of osseous and soft tissue structure morphology and pathology. The quality of 3D MRI models has steadily increased over time, with growing potential to replace 3D CT models in various musculoskeletal (MSK) applications. In practice, a single MRI examination for two-dimensional and 3D assessments can increase the value of MRI and simplify the pre- and postoperative imaging work-up. Multiple studies have shown excellent performance of 3D MRI models in shoulder injuries, in the hip in the setting of femoroacetabular impingement, and in the knee for the creation of bone surface models. Therefore, the utility of 3D MRI postprocessed models is expected to continue to rise and broaden in applications. Computer-based and artificial intelligence-assisted postprocessing techniques have tremendous potential to improve the efficiency of 3D model creation, opening many research avenues to validate the applicability of 3D MRI and establish 3D-specific quantitative assessment criteria. We provide a practice-focused overview of 3D MRI acquisition strategies, postprocessing techniques for 3D model creation, MSK applications of 3D MRI models, and an illustration of cases from our daily clinical practice.