Myosteatosis in multiple myeloma: a key determinant of survival beyond sarcopenia.

OBJECTIVE: Fatty infiltration of skeletal muscle (Myosteatosis) is associated with increased frailty, decreased muscle and mobility function, which seems fairly prevalent in multiple myeloma (MM) patients. This study aimed to determine the prognostic value of myosteatosis assessed by CT for progression-free survival (PFS) and overall survival (OS). MATERIALS AND METHODS: This IRB-approved cohort study included patients with newly diagnosed MM who were treated at a single university hospital and received CT at baseline. Geriatric assessment was performed via International Myeloma Working Group frailty score and Revised Myeloma Comorbidity Index. Myosteatosis was determined through measurement of paravertebral muscle radiodensity. Statistical analyses included uni- and multivariable Cox proportional hazard models and the Kaplan-Meier-method. RESULTS: A total of 226 newly diagnosed MM patients (median age: 65 years [range: 29-89], 63% males, mean BMI: 25 [14-42]) were analyzed. The prevalence of myosteatosis was 51%. Muscle radiodensity was significantly decreased in individuals with International Staging System stage III vs. I (p < 0.001), indicating higher fatty muscle infiltration in patients with advanced disease. Both PFS and OS were significantly decreased in patients with myosteatosis (PFS: median 32.0 months (95% CI 20.5.5-42.2) vs. 66.4 months without myosteatosis (95% CI 42.5-not reached), p < .001); OS: median 58.6 (95% CI 51.3-90.2) vs. not reached, p < .001). Myosteatosis remained an independent predictor of OS in multivariable analyses (HR: 1.98; 95%-CI: 1.20-3.27). CONCLUSION: Myosteatosis seems fairly prevalent in patients with newly diagnosed MM and associated with impaired overall survival. Prospective clinical trials are required to better understand the role of myosteatosis in MM patients.

MR imaging after patellar MACI and MPFL reconstruction: a comparison of isolated versus combined procedures.

OBJECTIVE: To qualitatively and quantitatively evaluate the 2.5-year MRI outcome after Matrix-associated autologous chondrocyte implantation (MACI) at the patella, reconstruction of the medial patellofemoral ligament (MPFL), and combined procedures. METHODS: In 66 consecutive patients (age 22.8 ± 6.4years) with MACI at the patella (n = 16), MPFL reconstruction (MPFL; n = 31), or combined procedures (n = 19) 3T MRI was performed 2.5 years after surgery. For morphological MRI evaluation WORMS and MOCART scores were obtained. In addition quantitative cartilage T2 and T1rho relaxation times were acquired. Several clinical scores were obtained. Statistical analyses included descriptive statistics, Mann-Whitney-U-tests and Pearson correlations. RESULTS: WORMS scores at follow-up (FU) were significantly worse after combined procedures (8.7 ± 4.9) than after isolated MACI (4.3 ± 3.6, P = 0.005) and after isolated MPFL reconstruction (5.3 ± 5.7, P = 0.004). Bone marrow edema at the patella in the combined group was the only (non-significantly) worsening WORMS parameter from pre- to postoperatively. MOCART scores were significantly worse in the combined group than in the isolated MACI group (57 ± 3 vs 88 ± 9, P < 0.001). Perfect defect filling was achieved in 26% and 69% of cases in the combined and MACI group, respectively (P = 0.031). Global and patellar T2 values were higher in the combined group (Global T2: 34.0 ± 2.8ms) and MACI group (35.5 ± 3.1ms) as compared to the MPFL group (31.1 ± 3.2ms, P < 0.05). T2 values correlated significantly with clinical scores (P < 0.005). Clinical Cincinnati scores were significantly worse in the combined group (P < 0.05). CONCLUSION: After combined surgery with patellar MACI and MPFL reconstruction inferior MRI outcomes were observed than after isolated procedures. Therefore, patients with need for combined surgery may be at particular risk for osteoarthritis.

Biomechanical Effects of Chronic Ankle Instability on the Talar Cartilage Matrix: The Value of T1ρ Relaxation Mapping Without and With Mechanical Loading.

BACKGROUND: T1ρ mapping has been proposed for the detection of early cartilage degeneration associated with chronic ankle instability (CAI). However, there are limited data surrounding the influence of ankle loading on T1ρ relaxation. PURPOSE: To evaluate T1ρ relaxation times of talar cartilage, as an indicator of early degenerative changes, associated with CAI and to investigate the influence of acute axial in situ loading on T1ρ values in CAI patients and healthy controls. STUDY TYPE: Prospective. SUBJECTS: A total of 9 patients (age = 21.8 ± 2.5 years, male/female = 2/7) with chronic ankle instability and 18 healthy control subjects (age = 22.8 ± 3.6 years, male/female = 5/13). FIELD STRENGTH: 3 T. SEQUENCE: 3D gradient echo fast low-angle shot (FLASH) sequence augmented with a variable spin-lock preparation period. ASSESSMENT: Ankle T1ρ mapping was performed without and with axial loading of 500 N. The talar cartilage was segmented in five coronal slices covering the central talocrural joint. Median talar T1ρ values were separately calculated for the medial and lateral facets. STATISTICAL TESTS: Mann-Whitney U and Wilcoxon signed-rank tests, significance level: P < 0.05. RESULTS: For the combined cohorts, the statistical analysis yielded significantly lower T1ρ values with loading compared to the no-load measurement for both the lateral (no load: [51.0 ± 4.0] msec, load: [49.5 ± 5.4] msec) as well as the medial compartment (no load: [50.0 ± 5.4] msec, load: [47.8 ± 6.8] msec). In the unloaded scans, the CAI patients showed significantly increased talar T1ρ values ([53.0 ± 7.4] mse ) compared to the healthy control subjects ([48.8 ± 4.1] msec) in the medial compartment. DATA CONCLUSION: Increased talar T1ρ relaxation times in CAI patients compared to healthy controls suggest that T1ρ relaxation is a sensitive biomarker for CAI-induced early-stage cartilage degeneration. However, the load-induced T1ρ change did not prove to be a viable marker for the altered biomechanical properties of the hyaline talar cartilage. LEVEL OF EVIDENCE: 2 LEVEL OF EFFICACY: Stage 2.

Application of diffusion microstructure imaging in musculoskeletal radiology - translation from head to shoulders.

OBJECTIVES: Quantitative MRI techniques, such as diffusion microstructure imaging (DMI), are increasingly applied for advanced tissue characterization. We determined its value in rotator cuff (RC) muscle imaging by studying the association of DMI parameters to isometric strength and fat fraction (FF). METHODS: Healthy individuals prospectively underwent 3T-MRI of the shoulder using DMI and chemical shift encoding-based water-fat imaging. RC muscles were segmented and quantitative MRI metrics (V-ISO, free fluid; V-intra, compartment inside of muscle fibers; V-extra, compartment outside of muscle fibers, and FF) were extracted. Isometric shoulder strength was quantified using specific clinical tests. Sex-related differences were assessed with Student's t. Association of DMI-metrics, FF, and strength was tested. A factorial two-way ANOVA was performed to compare the main effects of sex and external/internal strength-ratio and their interaction effects on quantitative imaging parameters ratios of infraspinatus/subscapularis. RESULTS: Among 22 participants (mean age: 26.7 ± 3.1 years, 50% female, mean BMI: 22.6 ± 1.9 kg/m2), FF of the individual RC muscles did not correlate with strength or DMI parameters (all p > 0.05). Subjects with higher V-intra (r = 0.57 to 0.87, p < 0.01) and lower V-ISO (r = -0.6 to -0.88, p < 0.01) had higher internal and external rotation strength. Moreover, V-intra was higher and V-ISO was lower in all RC muscles in males compared to female subjects (all p < 0.01). There was a sex-independent association of external/internal strength-ratio with the ratio of V-extra of infraspinatus/subscapularis (p = 0.02). CONCLUSIONS: Quantitative DMI parameters may provide incremental information about muscular function and microstructure in young athletes and may serve as a potential biomarker. KEY POINTS: • Diffusion microstructure imaging was successfully applied to non-invasively assess the microstructure of rotator cuff muscles in healthy volunteers. • Sex-related differences in the microstructural composition of the rotator cuff were observed. • Muscular microstructural metrics correlated with rotator cuff strength and may serve as an imaging biomarker of muscular integrity and function.

Association of lumbar vertebral bone marrow and paraspinal muscle fat composition with intervertebral disc degeneration: 3T quantitative MRI findings from the population-based KORA study.

OBJECTIVE: To assess the association of lumbar bone marrow adipose tissue fat fraction (BMAT-FF) and paraspinal muscle proton density fat fraction (PDFF) and their interplay with intervertebral disc degeneration (IVDD). METHODS: In this retrospective cross-sectional study based on a prospective population-based cohort, BMAT-FF and PDFF of asymptomatic individuals were calculated based on 3T-MRI dual-echo and multi-echo Dixon VIBE sequences. IVDD was assessed at motion segments L1 to L5 and dichotomized based on Pfirrmann grade ≥ 4 and/or presence of other severe degenerative changes or spinal abnormalities at least at one segment. Pearson's correlation coefficients were calculated for BMAT-FF and PDFF. Univariable and multivariable logistic regression models for IVDD were calculated. RESULTS: Among 335 participants (mean age: 56.2 ± 9.0 years, 43.3% female), the average BMI was 27.7 ± 4.5 kg/m2 and the prevalence of IVDD was high (69.9%). BMAT-FF and PDFF were significantly correlated (r = 0.31-0.34; p < 0.001). The risk for IVDD increased with higher PDFF (OR = 1.45; CI 1.03, 2.04) and BMAT-FF (OR = 1.56; CI 1.16, 2.11). Pairwise combinations of PDFF and BMAT-FF quartiles revealed a lower risk for IVDD in individuals in the lowest BMAT-FF and PDFF quartile (OR = 0.21; CI 0.1, 0.48). Individuals in the highest BMAT-FF and PDFF quartile showed an increased risk for IVDD (OR = 5.12; CI 1.17, 22.34) CONCLUSION: Lumbar BMAT-FF and paraspinal muscle PDFF are correlated and represent both independent and additive risk factors for IVDD. Quantitative MRI measurements of paraspinal myosteatosis and vertebral bone marrow fatty infiltration may serve as imaging biomarkers to assess the individual risk for IVDD. KEY POINTS: • Fat composition of the lumbar vertebral bone marrow is positively correlated with paraspinal skeletal muscle fat. • Higher fat-fractions of lumbar vertebral bone marrow and paraspinal muscle are both independent as well as additive risk factors for intervertebral disc degeneration. • Quantitative magnetic resonance imaging measurements of bone marrow and paraspinal muscle may serve as imaging biomarkers for intervertebral disc degeneration.

Bone Stress Injuries at the Ankle and Foot.

Bone stress injuries (BSIs) are a frequent finding in athletes, particularly of the foot and ankle. A BSI is caused by recurring microtrauma to the cortical or trabecular bone exceeding the repair capacity of normal bone. The most frequent fractures at the ankle are low risk, characterized by a low risk for nonunion. These include the posteromedial tibia, the calcaneus, and the metatarsal diaphysis. High-risk stress fractures have a higher risk for nonunion and need more aggressive treatment. Examples are the medial malleolus, navicular bone, and the base of the second and fifth metatarsal bone.Imaging features depend on the primary involvement of cortical versus trabecular bone. Conventional radiographs may remain normal up to 2 to 3 weeks. For cortical bone, early signs of BSIs are a periosteal reaction or the "gray cortex sign," followed by cortical thickening and fracture line depiction. In trabecular bone, a sclerotic dense line may be seen. Magnetic resonance imaging enables early detection of BSIs and can differentiate between a stress reaction and a fracture. We review typical anamnestic/clinical findings, epidemiology and risk factors, imaging characteristics, and findings at typical locations of BSIs at the foot and ankle that may help guide treatment strategy and patient recovery.

Single point imaging with radial acquisition and compressed sensing.

PURPOSE: To accelerate the Pointwise Encoding Time Reduction with Radial Acquisition (PETRA) sequence using compressed sensing while preserving the image quality for high-resolution MRI of tissue with ultra-short T2∗ values. METHODS: Compressed sensing was introduced in the PETRA sequence (csPETRA) to accelerate the time-consuming single point acquisition of the k-space center data. Random undersampling was applied to achieve acceleration factors up to Acc = 32. Phantom and in vivo images of the knee joint of six volunteers were measured at 3T using csPETRA sequence with Acc = 4, 8, 12, 16, 24, and 32. Images were compared against fully sampled PETRA data (Acc = 1) for structural similarity and normalized-mean-square-error. Qualitative and semi-quantitative analyses were performed to assess the effect of the acceleration on image artifacts, image quality, and delineation of anatomical structures at the knee. RESULTS: Even at high acceleration factors of Acc = 16 no aliasing artifacts were observed, and the anatomical details were preserved compared with the fully sampled data. The normalized-mean-square-error was less than 1% for Acc = 16, in which single point imaging acquisition time was reduced from 165 to 10 s, reducing the total scan time from 7.8 to 5.2 min. Semi-quantitative analyses suggest that Acc = 16 yields comparable diagnostic quality as the fully sampled data for knee imaging at a scan time of 5.2 min. CONCLUSION: csPETRA allows for ultra-short T2∗ imaging of the knee joint in clinically acceptable scan times while maintaining the image quality of original non-accelerated PETRA sequence.

Development and evaluation of machine learning models based on X-ray radiomics for the classification and differentiation of malignant and benign bone tumors.

OBJECTIVES: To develop and validate machine learning models to distinguish between benign and malignant bone lesions and compare the performance to radiologists. METHODS: In 880 patients (age 33.1 ± 19.4 years, 395 women) diagnosed with malignant (n = 213, 24.2%) or benign (n = 667, 75.8%) primary bone tumors, preoperative radiographs were obtained, and the diagnosis was established using histopathology. Data was split 70%/15%/15% for training, validation, and internal testing. Additionally, 96 patients from another institution were obtained for external testing. Machine learning models were developed and validated using radiomic features and demographic information. The performance of each model was evaluated on the test sets for accuracy, area under the curve (AUC) from receiver operating characteristics, sensitivity, and specificity. For comparison, the external test set was evaluated by two radiology residents and two radiologists who specialized in musculoskeletal tumor imaging. RESULTS: The best machine learning model was based on an artificial neural network (ANN) combining both radiomic and demographic information achieving 80% and 75% accuracy at 75% and 90% sensitivity with 0.79 and 0.90 AUC on the internal and external test set, respectively. In comparison, the radiology residents achieved 71% and 65% accuracy at 61% and 35% sensitivity while the radiologists specialized in musculoskeletal tumor imaging achieved an 84% and 83% accuracy at 90% and 81% sensitivity, respectively. CONCLUSIONS: An ANN combining radiomic features and demographic information showed the best performance in distinguishing between benign and malignant bone lesions. The model showed lower accuracy compared to specialized radiologists, while accuracy was higher or similar compared to residents. KEY POINTS: • The developed machine learning model could differentiate benign from malignant bone tumors using radiography with an AUC of 0.90 on the external test set. • Machine learning models that used radiomic features or demographic information alone performed worse than those that used both radiomic features and demographic information as input, highlighting the importance of building comprehensive machine learning models. • An artificial neural network that combined both radiomic and demographic information achieved the best performance and its performance was compared to radiology readers on an external test set.

The Lodwick classification for grading growth rate of lytic bone tumors: a decision tree approach.

The estimation of growth rate of lytic bone tumors based on conventional radiography has been extensively studied. While benign tumors exhibit slow growth, malignant tumors are more likely to show fast growth. The most frequently used algorithm for grading of growth rate on conventional radiography was published by Gwilym Lodwick. Based on the evaluation of the four descriptors (1) type of bone destruction (including the subdescriptor "margin" for geographic lesions), (2) penetration of cortex, (3) presence of a sclerotic rim, and (4) expanded shell, an overall growth grade (IA, IB, IC, II, III) can be assigned, with higher grade representing faster tumor growth. In this article, we provide an easy-to-use decision tree of Lodwick's original grading algorithm, suitable for teaching of students and residents. Subtleties of the grading algorithm and potential pitfalls in clinical practice are explained and illustrated. Exemplary conventional radiographs provided for each descriptor in the decision tree may be used as a guide and atlas for assisting in evaluation of individual features in daily clinical practice.

Patellar instability MRI measurements are associated with knee joint degeneration after reconstruction of the medial patellofemoral ligament.

OBJECTIVE: To qualitatively and quantitatively evaluate the 2-year magnetic resonance imaging (MRI) outcome after MPFL reconstruction at the knee and to assess MRI-based risk factors that predispose for inferior clinical and imaging outcomes. MATERIALS AND METHODS: A total of 31 patients with MPFL reconstruction were included (22 ± 6 years, 10 female). MRI was performed preoperatively in 21/31 patients. Two-year follow-up MRI included quantitative cartilage T2 and T1rho relaxation time measurements at the ipsilateral and contralateral knee. T2relative was calculated as T2patellofemoral/T2femorotibial. Morphological evaluation was conducted via WORMS scores. Patellar instability parameters and clinical scores were obtained. Statistical analyses included descriptive statistics, t-tests, multivariate regression models, and correlation analyses. RESULTS: Two years after MPFL reconstruction, all patellae were clinically stable. Mean total WORMS scores improved significantly from baseline to follow-up (mean difference ± SEM, - 4.0 ± 1.3; P = 0.005). As compared to patients with no worsening of WORMS subscores over time (n = 5), patients with worsening of any WORMS subscore (n = 16) had lower trochlear depth, lower facetal ratio, higher tibial-tuberosity to trochlear groove (TTTG) distance, and higher postoperative lateral patellar tilt (P < 0.05). T2relative was higher at the ipsilateral knee (P = 0.010). T2relative was associated with preoperatively higher patellar tilt (P = 0.021) and higher TTTG distance (P = 0.034). TTTG distance, global T2 values, and WORMS progression correlated with clinical outcomes (P < 0.05). CONCLUSION: MPFL reconstruction is an optimal treatment strategy to restore patellar stability. Still, progressive knee joint degeneration and patellofemoral cartilage matrix degeneration may be observed, with patellar instability MRI parameters representing particular risk factors.

Multitask Deep Learning for Segmentation and Classification of Primary Bone Tumors on Radiographs.

Background An artificial intelligence model that assesses primary bone tumors on radiographs may assist in the diagnostic workflow. Purpose To develop a multitask deep learning (DL) model for simultaneous bounding box placement, segmentation, and classification of primary bone tumors on radiographs. Materials and Methods This retrospective study analyzed bone tumors on radiographs acquired prior to treatment and obtained from patient data from January 2000 to June 2020. Benign or malignant bone tumors were diagnosed in all patients by using the histopathologic findings as the reference standard. By using split-sample validation, 70% of the patients were assigned to the training set, 15% were assigned to the validation set, and 15% were assigned to the test set. The final performance was evaluated on an external test set by using geographic validation, with accuracy, sensitivity, specificity, and 95% CIs being used for classification, the intersection over union (IoU) being used for bounding box placements, and the Dice score being used for segmentations. Results Radiographs from 934 patients (mean age, 33 years ± 19 [standard deviation]; 419 women) were evaluated in the internal data set, which included 667 benign bone tumors and 267 malignant bone tumors. Six hundred fifty-four patients were in the training set, 140 were in the validation set, and 140 were in the test set. One hundred eleven patients were in the external test set. The multitask DL model achieved 80.2% (89 of 111; 95% CI: 72.8, 87.6) accuracy, 62.9% (22 of 35; 95% CI: 47, 79) sensitivity, and 88.2% (67 of 76; CI: 81, 96) specificity in the classification of bone tumors as malignant or benign. The model achieved an IoU of 0.52 ± 0.34 for bounding box placements and a mean Dice score of 0.60 ± 0.37 for segmentations. The model accuracy was higher than that of two radiologic residents (71.2% and 64.9%; P = .002 and P < .001, respectively) and was comparable with that of two musculoskeletal fellowship-trained radiologists (83.8% and 82.9%; P = .13 and P = .25, respectively) in classifying a tumor as malignant or benign. Conclusion The developed multitask deep learning model allowed for accurate and simultaneous bounding box placement, segmentation, and classification of primary bone tumors on radiographs. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Carrino in this issue.

Prospective and longitudinal evolution of postoperative periprosthetic findings on metal artifact-reduced MR imaging in asymptomatic patients after uncemented total hip arthroplasty.

OBJECTIVE: To prospectively assess the evolution of postoperative MRI findings in asymptomatic patients after total hip arthroplasty (THA) over 24 months (mo). METHODS: This prospective cohort study included 9 asymptomatic patients (56.7 ± 15.0 years) after THA. Metal artifact-reduced 1.5-T MRI was performed at 3, 6, 12, and 24 mo after surgery. The femoral stem and acetabular cup were assessed by two readers for bone marrow edema (BME), periprosthetic bone resorption, and periosteal edema in addition to periarticular soft tissue edema and joint effusion. RESULTS: BME was common around the femoral stem in all Gruen zones after 3 mo (range: 50-100%) and 6 mo (range: 33-100%) and in the acetabulum in DeLee and Charnley zone II after 3 mo (100%) and 6 mo (33%). BME decreased substantially after 12 mo (range: 0-78%) and 24 mo (range: 0-50%), may however persist in particular in Gruen zones 1 + 7. Periosteal edema along the stem was common 3 mo postoperatively (range: 63-75%) and rare after 24 mo: 13% only in Gruen zones 2 and 5. Twelve months and 24 mo postoperatively, periprosthetic bone resorption was occasionally present around the femoral stem (range: 11-33% and 13-38%, respectively). Soft tissue edema occurred exclusively along the surgical access route after 3 mo (100%) and 6 mo (89%) and never at 12 mo or 24 mo (0%). CONCLUSION: Around the femoral stem, BME (33-100%) and periosteal edema (0-75%) are common until 6 mo after THA, decreasing substantially in the following period, may however persist up to 24 mo (BME: 0-50%; periosteal edema: 0-13%) in few non-adjoining Gruen zones. Soft tissue edema along the surgical access route should have disappeared 12 mo after surgery.

Development and Validation of a Multitask Deep Learning Model for Severity Grading of Hip Osteoarthritis Features on Radiographs.

Background A multitask deep learning model might be useful in large epidemiologic studies wherein detailed structural assessment of osteoarthritis still relies on expert radiologists' readings. The potential of such a model in clinical routine should be investigated. Purpose To develop a multitask deep learning model for grading radiographic hip osteoarthritis features on radiographs and compare its performance to that of attending-level radiologists. Materials and Methods This retrospective study analyzed hip joints seen on weight-bearing anterior-posterior pelvic radiographs from participants in the Osteoarthritis Initiative (OAI). Participants were recruited from February 2004 to May 2006 for baseline measurements, and follow-up was performed 48 months later. Femoral osteophytes (FOs), acetabular osteophytes (AOs), and joint-space narrowing (JSN) were graded as absent, mild, moderate, or severe according to the Osteoarthritis Research Society International atlas. Subchondral sclerosis and subchondral cysts were graded as present or absent. The participants were split at 80% (n = 3494), 10% (n = 437), and 10% (n = 437) by using split-sample validation into training, validation, and testing sets, respectively. The multitask neural network was based on DenseNet-161, a shared convolutional features extractor trained with multitask loss function. Model performance was evaluated in the internal test set from the OAI and in an external test set by using temporal and geographic validation consisting of routine clinical radiographs. Results A total of 4368 participants (mean age, 61.0 years ± 9.2 [standard deviation]; 2538 women) were evaluated (15 364 hip joints on 7738 weight-bearing anterior-posterior pelvic radiographs). The accuracy of the model for assessing these five features was 86.7% (1333 of 1538) for FOs, 69.9% (1075 of 1538) for AOs, 81.7% (1257 of 1538) for JSN, 95.8% (1473 of 1538) for subchondral sclerosis, and 97.6% (1501 of 1538) for subchondral cysts in the internal test set, and 82.7% (86 of 104) for FOS, 65.4% (68 of 104) for AOs, 80.8% (84 of 104) for JSN, 88.5% (92 of 104) for subchondral sclerosis, and 91.3% (95 of 104) for subchondral cysts in the external test set. Conclusion A multitask deep learning model is a feasible approach to reliably assess radiographic features of hip osteoarthritis. © RSNA, 2020 Online supplemental material is available for this article.

MRI with state-of-the-art metal artifact reduction after total hip arthroplasty: periprosthetic findings in asymptomatic and symptomatic patients.

OBJECTIVES: To assess the spectrum of periprosthetic MRI findings after primary total hip arthroplasty (THA). METHODS: This multi-center cohort study analyzed 31 asymptomatic patients (65.7 ± 12.7 years) and 27 symptomatic patients (62.3 ± 11.9 years) between 6 months and 2 years after THA. 1.5-T MRI was performed using Compressed Sensing SEMAC and high-bandwidth sequences. Femoral stem and acetabular cup were assessed for bone marrow edema, osteolysis, and periosteal reaction in Gruen zones and DeLee and Charnley zones. Student t test and Fisher's exact test were performed. RESULTS: The asymptomatic and symptomatic groups showed different patterns of imaging findings. Bone marrow edema was seen in 19/31 (61.3%) asymptomatic and 22/27 (81.5%) symptomatic patients, most commonly in Gruen zones 1, 7, and 8 (p ≥ 0.18). Osteolysis occurred in 14/31 (45.2%) asymptomatic and 14/27 (51.9%) symptomatic patients and was significantly more common in Gruen zone 7 in the symptomatic group (8/27 (29.6%)) compared to the asymptomatic group (2/31 (6.5%)) (p = 0.03). Periosteal reaction was present in 4/31 asymptomatic (12.9%) and 9/27 symptomatic patients (33.3%) and more common in Gruen zones 5 and 6 in the symptomatic group (p = 0.04 and 0.02, respectively). In the acetabulum, bone marrow edema pattern was encountered in 3/27 (11.1%) symptomatic patients but not in asymptomatic patients (p ≥ 0.21). Patient management was altered in 8/27 (29.6%) patients based on MRI findings. CONCLUSIONS: Periprosthetic bone marrow edema is common after THA both in asymptomatic and symptomatic patients. Osteolysis and periosteal reaction are more frequent in symptomatic patients. MRI findings led to altered patient management in 29.6% of patients. KEY POINTS: • Bone marrow edema pattern was frequent in both asymptomatic and symptomatic patients after THA, particularly around the proximal femoral stem in Gruen zones 1, 7, and 8. • Osteolysis was significantly more frequent in symptomatic patients in Gruen zone 7. • Periosteal reaction occurred more frequently in symptomatic patients in Gruen zones 5 and 6.

Reliable semiquantitative whole-joint MRI score for the shoulder joint: The shoulder osteoarthritis severity (SOAS) score.

BACKGROUND: Shoulder osteoarthritis causes severe pain and functional disability. Preventive surgical procedures aiming to halt the progression of degenerative changes are increasingly applied. However, no MRI-based score exists that may be applied for scoring of osteoarthritic changes and their progression. PURPOSE: To establish a semiquantitative MRI-based shoulder osteoarthritis severity (SOAS) evaluation system and to test its reliability. STUDY TYPE: Retrospective. SUBJECTS: A total of N = 60 patients (73.2 ± 7.3 years; 30/60 female) was included; n = 15 subjects for each of the four radiographic grades of osteoarthritis (Samilson score 0 to 3). ASSESSMENT: Based on the MRIs of the shoulder, the SOAS scoring system was created. All MRIs were assessed by six readers. The severity of degeneration was evaluated for: rotator cuff, labral-bicipital-complex, cartilage, osseous findings, joint capsule, and acromion. The total SOAS score ranged between 0 (absence of osteoarthritis) and 100 (most severe osteoarthritis). SOAS scores were correlated with radiographic Samilson, Hamada and Kellgren-Lawrence (KL) gradings. STATISTICS: Pearson correlations, t-tests, receiver operating characteristics (ROC) and interclass correlation coefficients (ICC). RESULTS: Intra- (ICC = 0.99) and interreader agreement (ICC 0.96-0.98) for the total SOAS score was excellent. The range of SOAS scores was from 1 to 88. SOAS correlated significantly with radiographic Samilson and KL scores (R = 0.82, P < 0.001), but not with Hamada scores (R = -0.07, P = 0.60). The highest correlations with Samilson scores were found for cartilage (R = 0.82, P < 0.001) and osseous findings (R = 0.86, P < 0.001). SOAS scores were significantly different between different Samilson grades (Samilson 0, 13.4 ± 7.6; Samilson 1, 26.0 ± 9.1; Samilson 2, 38.2 ± 19.2; Samilson 3, 65.5 ± 13.0; P < 0.05). The ability of the SOAS score to predict incident radiographic shoulder OA (KL grade ≥2) was excellent (AUC = 0.91; P < 0.001). DATA CONCLUSION: The newly developed semiquantitative MRI-based SOAS score represents the severity of global shoulder OA and structure-specific shoulder degeneration with excellent reliability in a standardized manner and may therefore be helpful in MRI research studies of the shoulder. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Vertebrae, Vertebral End Plates, and Disks: Concepts and Specific Pathologies.

Vertebral end plates cover the osseous vertebral body. The integrity of the cartilaginous end plates is of great importance for the entire vertebral segment because the vascularized end plate provides the nutrition for the avascular disk. Yet several pathologies may occur at these end plates at the embryonic stage, in childhood to adolescence (e.g., ossification and segmentation disorders of the spine, persistent notochord, slippage of the growth plate), as well as in the mature spine of an adult (degenerative disk disease), that may impact the integrity of the cartilaginous end plate and therefore lead to severe diseases of the spine. This article reviews specific congenital, developmental, and degenerative disorders of the vertebral end plate as well as both established and newly introduced imaging techniques, such as ultrashort echo time imaging based on magnetic resonance imaging, that are suitable for imaging of the end plate.

Cartilage repair surgery prevents progression of knee degeneration.

PURPOSE: To investigate, whether cartilage repair surgery for focal osteochondral defects at the knee results in less degenerative changes over 6 years in a MR imaging follow-up than morphologically initially identical defects in non-operated control subjects from the osteoarthritis initiative (OAI). METHODS: A total of 32 individuals received baseline and follow-up MRI. In n = 16 patients with cartilage repair [osteochondral autograft transfer system (OATS), n = 12; spongiosa-augmented matrix-associated autologous chondrocyte implantation (MACI), n = 4] MRI was performed preoperatively and after 5.7 ± 2.3 year follow-up. Baseline MRIs of non-operated subjects from the OAI were screened for initially identical cartilage defects (n = 16). Morphological knee abnormalities were assessed using WORMS, AMADEUS and MOCART scores. A sagittal 2D MSME sequence was implemented for quantitative cartilage T2 relaxation time measurements in all (0, 2, 4, 6 and 8-years) follow-ups from the OAI and in the postoperative MRI protocol. RESULTS: For both groups, focal osteochondral defects were located at the femoral condyle in 8/16 cases (5 medial, 3 lateral) and at the patella in 8/16 cases. At baseline, the mean cartilage defect size ± SD was 1.4 ± 1.3 cm2 for the control group and 1.3 ± 1.2 cm2 for the cartilage repair group (n.s.). WORMS scores were not significantly different between the cartilage repair group and the control group at baseline [mean difference ± SEM (95%CI); 0.5 ± 2.5 (- 4.7, 5.7), n.s.]. During identical follow-up times, the progression of total WORMS scores [19.9 ± 2.3 (15.0, 24.9), P < 0.001] and of cartilage defects scores in the affected (P < 0.001) and in the opposing (P = 0.029) compartment was significantly more severe in non-operated individuals (P < 0.05). In non-operated subjects, T2 values increased continuously from baseline to the 8-year follow-up (P = 0.001). CONCLUSIONS: Patients with cartilage repair showed less progression of degenerative MRI changes at 6-year follow-up than a control cohort from the OAI with initially identical osteochondral defects. Patients with focal cartilage defects may profit from cartilage repair surgery since it may prevent progression of early osteoarthritis at the knee joint. LEVEL OF EVIDENCE: Prognostic study, Level II.

Early Recoil After Balloon Angioplasty of Erection-Related Arteries in Patients With Arteriogenic Erectile Dysfunction.

PURPOSE: To evaluate the incidence of elastic recoil in patients presenting with erectile dysfunction (ED) undergoing endovascular revascularization of the pudendal or penile arteries. METHODS: A consecutive series of 21 ED patients (mean age 58.3±9.3 years) undergoing minimally invasive revascularization of 31 arteries was analyzed. ED lesions included the pudendal arteries (n=27) and the penile artery (n=4). Mean lesion length was 20.6±13.9 mm. Minimal lumen diameter (MLD) measurements were assessed at baseline, immediately after balloon angioplasty, and 10 minutes thereafter. Early recoil was defined as an MLD reduction >10%. Elastic recoil with >10% lumen compromise was treated with drug-coated balloons, while severe elastic recoil (>30%) required drug-eluting stents (DES). The International Index of Erectile Function (IIEF-15) score was obtained prior to and 3 months after the procedure to obtain information on functional outcomes subsequent to angioplasty. RESULTS: Mean MLD at baseline was 0.9±0.6 mm, which improved to 2.0±0.9 mm immediately after balloon dilation. At 10 minutes after dilation, the MLD was 1.7±1.0 mm. Elastic recoil was observed in all 31 lesions and resulted in a mean lumen compromise of 21.2%. Severe (>30%) recoil was observed in 14 arteries, which underwent DES therapy. The IIEF-15 score improved from 31.3±11.2 at baseline to 49.8±16.8 (p<0.001) at the 3-month follow-up. CONCLUSION: Endovascular revascularization constitutes a safe and feasible treatment modality to restore erectile function in patients with arteriogenic ED and ineffective conservative management. Early elastic recoil is very frequent subsequent to balloon dilation of small-caliber erection-related arteries. Thus, mechanical scaffolding with DES is required in a high subset of ED patients to provide favorable early angiographic and clinical results.

Multidetector Computed Tomography Imaging: Effect of Sparse Sampling and Iterative Reconstruction on Trabecular Bone Microstructure.

Multidetector computed tomography-based trabecular bone microstructure analysis ensures promising results in fracture risk prediction caused by osteoporosis. Because multidetector computed tomography is associated with high radiation exposure, its clinical routine use is limited. Hence, in this study, we investigated in 11 thoracic midvertebral specimens whether trabecular texture parameters are comparable derived from (1) images reconstructed using statistical iterative reconstruction (SIR) and filtered back projection as criterion standard at different exposures (80, 150, 220, and 500 mAs) and (2) from SIR-based sparse sampling projections (12.5%, 25%, 50%, and 100%) and equivalent exposures as criterion standard. Twenty-four texture features were computed, and those that showed similar values between (1) filtered back projection and SIR at the different exposure levels and (2) sparse sampling and equivalent exposures and reconstructed with SIR were identified. These parameters can be of equal value in determining trabecular bone microstructure with lower radiation exposure using sparse sampling and SIR.

Advances in MRI around metal.

The prevalence of orthopedic metal implants is continuously rising in the aging society. Particularly the number of joint replacements is increasing. Although satisfying long-term results are encountered, patients may suffer from complaints or complications during follow-up, and often undergo magnetic resonance imaging (MRI). Yet metal implants cause severe artifacts on MRI, resulting in signal-loss, signal-pileup, geometric distortion, and failure of fat suppression. In order to allow for adequate treatment decisions, metal artifact reduction sequences (MARS) are essential for proper radiological evaluation of postoperative findings in these patients. During recent years, developments of musculoskeletal imaging have addressed this particular technical challenge of postoperative MRI around metal. Besides implant material composition, configuration and location, selection of appropriate MRI hardware, sequences, and parameters influence artifact genesis and reduction. Application of dedicated metal artifact reduction techniques including high bandwidth optimization, view angle tilting (VAT), and the multispectral imaging techniques multiacquisition variable-resonance image combination (MAVRIC) and slice-encoding for metal artifact correction (SEMAC) may significantly reduce metal-induced artifacts, although at the expense of signal-to-noise ratio and/or acquisition time. Adding advanced image acquisition techniques such as parallel imaging, partial Fourier transformation, and advanced reconstruction techniques such as compressed sensing further improves MARS imaging in a clinically feasible scan time. This review focuses on current clinically applicable MARS techniques. Understanding of the main principles and techniques including their limitations allows a considerate application of these techniques in clinical practice. Essential orthopedic metal implants and postoperative MR findings around metal are presented and highlighted with clinical examples. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:972-991.