Association between myosteatosis and impaired glucose metabolism: A deep learning whole-body magnetic resonance imaging population phenotyping approach.

BACKGROUND: There is increasing evidence that myosteatosis, which is currently not assessed in clinical routine, plays an important role in risk estimation in individuals with impaired glucose metabolism, as it is associated with the progression of insulin resistance. With advances in artificial intelligence, automated and accurate algorithms have become feasible to fill this gap. METHODS: In this retrospective study, we developed and tested a fully automated deep learning model using data from two prospective cohort studies (German National Cohort [NAKO] and Cooperative Health Research in the Region of Augsburg [KORA]) to quantify myosteatosis on whole-body T1-weighted Dixon magnetic resonance imaging as (1) intramuscular adipose tissue (IMAT; the current standard) and (2) quantitative skeletal muscle (SM) fat fraction (SMFF). Subsequently, we investigated the two measures for their discrimination of and association with impaired glucose metabolism beyond baseline demographics (age, sex and body mass index [BMI]) and cardiometabolic risk factors (lipid panel, systolic blood pressure, smoking status and alcohol consumption) in asymptomatic individuals from the KORA study. Impaired glucose metabolism was defined as impaired fasting glucose or impaired glucose tolerance (140-200 mg/dL) or prevalent diabetes mellitus. RESULTS: Model performance was high, with Dice coefficients of ≥0.81 for IMAT and ≥0.91 for SM in the internal (NAKO) and external (KORA) testing sets. In the target population (380 KORA participants: mean age of 53.6 ± 9.2 years, BMI of 28.2 ± 4.9 kg/m2, 57.4% male), individuals with impaired glucose metabolism (n = 146; 38.4%) were older and more likely men and showed a higher cardiometabolic risk profile, higher IMAT (4.5 ± 2.2% vs. 3.9 ± 1.7%) and higher SMFF (22.0 ± 4.7% vs. 18.9 ± 3.9%) compared to normoglycaemic controls (all P ≤ 0.005). SMFF showed better discrimination for impaired glucose metabolism than IMAT (area under the receiver operating characteristic curve [AUC] 0.693 vs. 0.582, 95% confidence interval [CI] [0.06-0.16]; P < 0.001) but was not significantly different from BMI (AUC 0.733 vs. 0.693, 95% CI [-0.09 to 0.01]; P = 0.15). In univariable logistic regression, IMAT (odds ratio [OR] = 1.18, 95% CI [1.06-1.32]; P = 0.004) and SMFF (OR = 1.19, 95% CI [1.13-1.26]; P < 0.001) were associated with a higher risk of impaired glucose metabolism. This signal remained robust after multivariable adjustment for baseline demographics and cardiometabolic risk factors for SMFF (OR = 1.10, 95% CI [1.01-1.19]; P = 0.028) but not for IMAT (OR = 1.14, 95% CI [0.97-1.33]; P = 0.11). CONCLUSIONS: Quantitative SMFF, but not IMAT, is an independent predictor of impaired glucose metabolism, and discrimination is not significantly different from BMI, making it a promising alternative for the currently established approach. Automated methods such as the proposed model may provide a feasible option for opportunistic screening of myosteatosis and, thus, a low-cost personalized risk assessment solution.

Association Between Body Composition and Survival in Patients With Gastroesophageal Adenocarcinoma: An Automated Deep Learning Approach.

PURPOSE: Body composition (BC) may play a role in outcome prognostication in patients with gastroesophageal adenocarcinoma (GEAC). Artificial intelligence provides new possibilities to opportunistically quantify BC from computed tomography (CT) scans. We developed a deep learning (DL) model for fully automatic BC quantification on routine staging CTs and determined its prognostic role in a clinical cohort of patients with GEAC. MATERIALS AND METHODS: We developed and tested a DL model to quantify BC measures defined as subcutaneous and visceral adipose tissue (VAT) and skeletal muscle on routine CT and investigated their prognostic value in a cohort of patients with GEAC using baseline, 3-6-month, and 6-12-month postoperative CTs. Primary outcome was all-cause mortality, and secondary outcome was disease-free survival (DFS). Cox regression assessed the association between (1) BC at baseline and mortality and (2) the decrease in BC between baseline and follow-up scans and mortality/DFS. RESULTS: Model performance was high with Dice coefficients ≥0.94 ± 0.06. Among 299 patients with GEAC (age 63.0 ± 10.7 years; 19.4% female), 140 deaths (47%) occurred over a median follow-up of 31.3 months. At baseline, no BC measure was associated with DFS. Only a substantial decrease in VAT >70% after a 6- to 12-month follow-up was associated with mortality (hazard ratio [HR], 1.99 [95% CI, 1.18 to 3.34]; P = .009) and DFS (HR, 1.73 [95% CI, 1.01 to 2.95]; P = .045) independent of age, sex, BMI, Union for International Cancer Control stage, histologic grading, resection status, neoadjuvant therapy, and time between surgery and follow-up CT. CONCLUSION: DL enables opportunistic estimation of BC from routine staging CT to quantify prognostic information. In patients with GEAC, only a substantial decrease of VAT 6-12 months postsurgery was an independent predictor for DFS beyond traditional risk factors, which may help to identify individuals at high risk who go otherwise unnoticed.

Odontoid Fracture with Accompanying Severe Atlantoaxial Instability in Elderly Patients-Analysis of Treatment, Adverse Events, and Outcome.

(1) Background: In elderly patients with type II odontoid fractures, accompanying severe atlantoaxial instability (AAI) is discussed as a marker possibly warranting more aggressive surgical therapy. This study aimed to characterize adverse events as well as the radiological and functional outcomes of surgical vs. conservative therapy in patients with odontoid fracture and AAI. (2) Methods: Patients aged 65 years and older with type II odontoid fracture and AAI treated were included. AAI was assumed if the mean subluxation across both atlantoaxial facet joints in the sagittal plane was greater than 50%. Data on demographics, comorbidities, treatment, adverse events, radiological, and functional outcomes were analyzed. (3) Results: Thirty-nine patients were included. Hospitalization time was significantly shorter in conservatively treated patients compared to patients with ventral or dorsal surgery. Adverse events occurred in 11 patients (28.2%), affecting 10 surgically treated patients (35.7%), and 1 conservatively treated patient (9.1%). Moreover, 25 patients were followed-up (64.1%). One secondary dislocation occurred in the conservative group (11.1%) and three in the surgical group (18.8%). (4) Conclusions: Despite the potential for instability in this injury, conservative treatment does not seem to lead to unfavorable short-term results, less adverse events, and a shorter hospital stay and should thus be considered and discussed with patients as a treatment option, even in the presence of severe AAI.

Adverse events after surgery for injuries to the subaxial cervical spine: analysis of incidence and risk factors.

PURPOSE: To determine the incidence of severe surgical adverse events (sSAE) after surgery of patients with subaxial cervical spine injury (sCS-Fx) and to identify patient, treatment, and injury-related risk factors. METHODS: Retrospective analysis of clinical and radiological data of sCS-Fx patients treated surgically between 2010 and 2020 at a single national trauma center. Baseline characteristics of demographic data, preexisting conditions, treatment, and injury morphology were extracted. Incidences of sSAEs within 60 days after surgery were analyzed. Univariate analysis and binary logistic regression for the occurrence of one or more sSAEs were performed to identify risk factors. P-values < .05 were considered statistically significant. RESULTS: Two hundred and ninety-two patients were included. At least one sSAE occurred in 49 patients (16.8%). Most frequent were sSAEs of the surgical site (wound healing disorder, infection, etc.) affecting 29 patients (9.9%). Independent potential risk factors in logistic regression were higher age (OR 1.02 [1.003-1.04], p = .022), the presence of one or more modifiers in the AO Spine Subaxial Injury Classification (OR 2.02 [1.03-3.96], p = .041), and potentially unstable or unstable facet injury (OR 2.49 [1.24-4.99], p = .010). Other suspected risk factors were not statistically significant, among these Injury Severity Score, the need for surgery for concomitant injuries, the primary injury type according to AO Spine, and preexisting medical conditions. CONCLUSION: sSAE rates after treatment of sCS-Fx are high. The identified risk factors are not perioperatively modifiable, but their knowledge should guide intra and postoperative care and surgical technique.

Secondary Dislocations in Type B and C Injuries of the Subaxial Cervical Spine: Risk Factors and Treatment.

INTRODUCTION: This study analyzed the incidence of secondary dislocations (sDLs) after surgical stabilization of AO Spine type B and C injuries of the subaxial cervical spine (sCS). MATERIALS AND METHODS: Patients treated for injuries of the sCS from 2010 to 2020 were retrospectively analyzed for the incidence of sDL within 60 days after first surgery. A univariate analysis of variables potentially influencing the risk of sDL was performed. Patients with solitary anterior stabilization underwent subgroup analysis. The treatment of sDLs was described. RESULTS: A total of 275 patients were included. sDLs occurred in 4.0% of patients (n = 11) in the total sample, most frequently after solitary anterior stabilization with 8.0% (n = 10, p = 0.010). Only one sDL occurred after combined stabilization and no sDLs after posterior stabilization. In the total sample and the anterior subgroup, variables significantly associated with sDL were older age (p = 0.001) and concomitant unstable facet joint injury (p = 0.020). No neurological deterioration occurred due to sDL and most patients were treated with added posterior stabilization. sDL is frequent after solitary anterior stabilization and rare after posterior or combined stabilization. DISCUSSION: Patients of higher age and with unstable facet joint injuries should be followed up diligently to detect sDLs in time. Neurological deterioration does not regularly occur due to sDL, and most patients can be treated with added posterior stabilization.

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.

Survival and Clinical Outcomes after Unconstrained Total Knee Arthroplasty for Tibial Plateau Fractures-A Retrospective Study with Minimum 4-Year Follow-Up.

This study investigated survival, complications, revisions, and patient-reported outcomes (PROs) for unconstrained total knee arthroplasty (TKA) in posttraumatic osteoarthritis (PTO) caused by intraarticular tibial plateau fractures with minimum four years follow-up. Forty-nine patients (71.4% male; 58.7 years) were included. Kaplan-Meier analysis was performed with failure defined as TKA removal. Patients without failure underwent pre- and postoperative evaluation (range of motion (ROM), Oxford Knee Score (OKS), Knee Society Score (KSS), anatomical femorotibial angle (aFTA), proximal tibial slope (PTS)) and Short Form-12 (SF-12) Physical (PCS) and Mental Component Summary (MCS) assessment at final follow-up. Fifteen (30.6%) patients had a complication, and eight (16.3%) patients underwent prosthesis removal at median 2.5 years. Cumulative survival rate of TKA was 79.6% at 20 years. A total of 32 patients with a mean follow-up of 11.8 years underwent further analyses. ROM (p = 0.028), aFTA (p = 0.044), pPS (p = 0.009), OKS (p < 0.001) and KSS (p < 0.001) improved significantly. SF-12 PCS was 42.3 and MCS was 54.4 at final follow-up. In general, one third of patients suffer a complication, and one in six patients has their prosthesis removed after TKA for PTO due to tibial plateau fractures. In patients who do not fail, TKA significantly improves clinical and radiographic outcomes at long-term follow-up.

Odontoid fracture in geriatric patients - analysis of complications and outcome following conservative treatment vs. ventral and dorsal surgery.

BACKGROUND: Different treatment options are discussed for geriatric odontoid fracture. The aim of this study was to compare the treatment options for geriatric odontoid fractures. METHODS: Included were patients with the following criteria: age ≥ 65 years, identification of seniors at risk (ISAR score ≥ 2), and odontoid fracture type A/B according to Eysel and Roosen. Three groups were compared: conservative treatment, surgical therapy with ventral screw osteosynthesis or dorsal instrumentation. At a follow-up examination, the range of motion and the trabecular bone fracture healing rate were evaluated. Furthermore, demographic patient data, neurological status, length of stay at the hospital and at the intensive care unit (ICU) as well as the duration of surgery and occurring complications were analyzed. RESULTS: A total of 72 patients were included and 43 patients could be re-examined (range: 2.7 ± 2.1 months). Patients with dorsal instrumentation had a better rotation. Other directions of motion were not significantly different. The trabecular bone fracture healing rate was 78.6%. The patients with dorsal instrumentation were hospitalized significantly longer; however, their duration at the ICU was shortest. There was no significant difference in complications. CONCLUSION: Geriatric patients with odontoid fracture require individual treatment planning. Dorsal instrumentation may offer some advantages.

Non-invasive monitoring of neoadjuvant radiation therapy response in soft tissue sarcomas by multiparametric MRI and quantification of circulating tumor DNA-A study protocol.

BACKGROUND: Wide resection remains the cornerstone of localized soft-tissue sarcomas (STS) treatment. Neoadjuvant radiation therapy (NRT) may decrease the risk of local recurrences; however, its effectiveness for different histological STS subtypes has not been systematically investigated. The proposed prospective study evaluates the NRT response in STS using liquid biopsies and the correlation of multiparametric magnetic resonance imaging (mpMRI) with histopathology and immunohistochemistry. METHODS: Patients with localized high-grade STS, who qualify for NRT, are included in this study. LIQUID BIOPSIES: Quantification of circulating tumor DNA (ctDNA) in patient blood samples is performed by targeted next-generation sequencing. Soft-tissue sarcoma subtype-specific panel sequencing in combination with patient-specific exome sequencing allows the detection of individual structural variants and point mutations. Circulating free DNA is isolated from peritherapeutically collected patient plasma samples and ctDNA quantified therein. Identification of breakpoints is carried out using FACTERA. Bioinformatic analysis is performed using samtools, picard, fgbio, and the MIRACUM Pipeline. MPMRI: Combination of conventional MRI sequences with diffusion-weighted imaging, intravoxel-incoherent motion, and dynamic contrast enhancement. Multiparametric MRI is performed before, during, and after NRT. We aim to correlate mpMRI data with the resected specimen's macroscopical, histological, and immunohistochemical findings. RESULTS: Preliminary data support the notion that quantification of ctDNA in combination with tumor mass characterization through co-registration of mpMRI and histopathology can predict NRT response of STS. CLINICAL RELEVANCE: The methods presented in this prospective study are necessary to assess therapy response in heterogeneous tumors and lay the foundation of future patient- and tumor-specific therapy concepts. These methods can be applied to various tumor entities. Thus, the participation and support of a wider group of oncologic surgeons are needed to validate these findings on a larger patient cohort.

Development and Evaluation of MR-Based Radiogenomic Models to Differentiate Atypical Lipomatous Tumors from Lipomas.

BACKGROUND: The aim of this study was to develop and validate radiogenomic models to predict the MDM2 gene amplification status and differentiate between ALTs and lipomas on preoperative MR images. METHODS: MR images were obtained in 257 patients diagnosed with ALTs (n = 65) or lipomas (n = 192) using histology and the MDM2 gene analysis as a reference standard. The protocols included T2-, T1-, and fat-suppressed contrast-enhanced T1-weighted sequences. Additionally, 50 patients were obtained from a different hospital for external testing. Radiomic features were selected using mRMR. Using repeated nested cross-validation, the machine-learning models were trained on radiomic features and demographic information. For comparison, the external test set was evaluated by three radiology residents and one attending radiologist. RESULTS: A LASSO classifier trained on radiomic features from all sequences performed best, with an AUC of 0.88, 70% sensitivity, 81% specificity, and 76% accuracy. In comparison, the radiology residents achieved 60-70% accuracy, 55-80% sensitivity, and 63-77% specificity, while the attending radiologist achieved 90% accuracy, 96% sensitivity, and 87% specificity. CONCLUSION: A radiogenomic model combining features from multiple MR sequences showed the best performance in predicting the MDM2 gene amplification status. The model showed a higher accuracy compared to the radiology residents, though lower compared to the attending radiologist.

Multiparametric magnetic resonance imaging for radiation therapy response monitoring in soft tissue sarcomas: a histology and MRI co-registration algorithm.

Rationale: To establish a spatially exact co-registration procedure between in vivo multiparametric magnetic resonance imaging (mpMRI) and (immuno)histopathology of soft tissue sarcomas (STS) to identify imaging parameters that reflect radiation therapy response of STS. Methods: The mpMRI-Protocol included diffusion-weighted (DWI), intravoxel-incoherent motion (IVIM), and dynamic contrast-enhancing (DCE) imaging. The resection specimen was embedded in 6.5% agarose after initial fixation in formalin. To ensure identical alignment of histopathological sectioning and in vivo imaging, an ex vivo MRI scan of the specimen was rigidly co-registered with the in vivo mpMRI. The deviating angulation of the specimen to the in vivo location of the tumor was determined. The agarose block was trimmed accordingly. A second ex vivo MRI in a dedicated localizer with a 4 mm grid was performed, which was matched to a custom-built sectioning machine. Microtomy sections were stained with hematoxylin and eosin. Immunohistochemical staining was performed with anti-ALDH1A1 antibodies as a radioresistance and anti-MIB1 antibodies as a proliferation marker. Fusion of the digitized microtomy sections with the in vivo mpMRI was accomplished through nonrigid co-registration to the in vivo mpMRI. Co-registration accuracy was qualitatively assessed by visual assessment and quantitatively evaluated by computing target registration errors (TRE). Results: The study sample comprised nine tumor sections from three STS patients. Visual assessment after nonrigid co-registration showed a strong morphological correlation of the histopathological specimens with ex vivo MRI and in vivo mpMRI after neoadjuvant radiation therapy. Quantitative assessment of the co-registration procedure using TRE analysis of different pairs of pathology and MRI sections revealed highly accurate structural alignment, with a total median TRE of 2.25 mm (histology - ex vivo MRI), 2.22 mm (histology - in vivo mpMRI), and 2.02 mm (ex vivo MRI - in vivo mpMRI). There was no significant difference between TREs of the different pairs of sections or caudal, middle, and cranial tumor parts, respectively. Conclusion: Our initial results show a promising approach to obtaining accurate co-registration between histopathology and in vivo MRI for STS. In a larger cohort of patients, the method established here will enable the prospective identification and validation of in vivo imaging biomarkers for radiation therapy response prediction and monitoring in STS patients via precise molecular and cellular correlation.

Generation of a set of induced pluripotent stem cell lines from two Alzheimer disease patients carrying APOE4 (MLUi007-J; MLUi008-A) and healthy old donors carrying APOE3 (MLUi009-A; MLUi010-B) to study APOE in aging and disease.

Late-onset Alzheimer disease (LOAD) is the most frequent neurodegenerative disease, and the APOE ε4 allele is the most prominent risk factor for LOAD. Four human induced pluripotent stem cell (iPSC) lines MLUi007-J, MLUi008-B, MLUi009-A, and MLUi010-B were generated from LOAD patients and healthy matched donors by reprogramming of B-lymphoblastoid cells (B-LCLs) with episomal plasmids. The application of B-LCLs holds a great promise to model LOAD and other diseases because they can easily be generated from primary peripheral blood mononuclear cells (PBMCs) by infection with the Epstein-Barr virus (EBV).

Associations of myosteatosis with disc degeneration: A 3T magnetic resonance imaging study in individuals with impaired glycaemia.

BACKGROUND: Intervertebral disc degeneration (IVDD) may be linked to dysregulations of skeletal muscle glucose metabolism and fatty alterations of muscle composition (Myosteatosis). Our aim was to evaluate the different associations of magnetic resonance imaging (MRI)-based paravertebral myosteatosis with lumbar disc degeneration in individuals with impaired glucose metabolism and normoglycaemic controls. METHODS: In total, 304 individuals (mean age: 56.3 ± 9.1 years, 53.6% male sex, mean body mass index [BMI]: 27.6 ± 4.7 kg/m2 ) from a population-based cohort study who underwent 3-Tesla whole-body chemical-shift-encoded (six echo times) and T2-weighted single-shot-fast-spin-echo MRI were included. Lumbar disc degeneration was assessed at motion segments L1 to L5, categorized according to the Pfirrmann score and defined as Pfirrmann grade > 2 and/or disc bulging/herniation on at least one segment. Fat content of the autochthonous back muscles and the quadratus lumborum muscle was quantified as proton density fat fraction (PDFFmuscle ). Logistic regression models adjusted for age, sex, BMI and regular physical activity were calculated to evaluate the association between PDFFmuscle and outcome IVDD. RESULTS: The overall prevalence of IVDD was 79.6%. There was no significant difference in the prevalence or severity distribution of IVDD between participants with or without impaired glucose metabolism (77.7% vs. 80.7%, P = 0.63 and P = 0.71, respectively). PDFFmuscle was significantly and positively associated with an increased risk for the presence of IVDD in participants with impaired glycaemia when adjusted for age, sex and BMI (PDFFautochthonous back muscles : odds ratio [OR] 2.16, 95% confidence interval [CI] [1.09, 4.3], P = 0.03; PDFFquadratus lumborum : OR 2.01, 95% CI [1.04, 3.85], P = 0.04). After further adjustment for regular physical activity, the results attenuated, albeit approaching statistical significance (PDFFautochthonous back muscles : OR 1.97, 95% CI [0.97, 3.99], P = 0.06; PDFFquadratus lumborum : OR 1.86, 95% CI [0.92, 3.76], P = 0.09). No significant associations were shown in healthy controls (PDFFautochthonous back muscles : OR 0.62, 95% CI [0.34, 1.14], P = 0.13; PDFFquadratus lumborum : OR 1.06, 95% CI [0.6, 1.89], P = 0.83). CONCLUSIONS: Paravertebral myosteatosis is positively associated with intervertebral disc disease in individuals with impaired glucose metabolism, independent of age, sex and BMI. Regular physical activity may confound these associations. Longitudinal studies will help to better understand the pathophysiological role of skeletal muscle in those with concomitant disturbed glucose haemostasis and intervertebral disc disease, as well as possible underlying causal relationships.

Pediatric cervical spine injuries-results of the German multicenter CHILDSPINE study.

OBJECTIVES: The aim of this study was to provide epidemiological data of pediatric patients suffering from cervical spinal trauma in Germany, in order to integrate these data in future decision-making processes concerning diagnosis and therapy. MATERIALS AND METHODS: Retrospective multicenter study includes all patients up to 16 years suffering from cervical spine injuries who were treated in six German spine centers between 01/2010 and 12/2016. The clinical databases were screened for specific trauma mechanism, level of injury as well as accompanying injuries. Diagnostic imaging and the chosen therapy were analyzed. Patients were divided into three age groups for further evaluation: age group I (0-6 years), age group II (7-9 years), age group III (10-16 years). RESULTS: A total of 214 children with 265 cervical spine injuries were included during the mentioned period. The mean age at the time of injury was 11.9 (± 3.9) years. In age group I, 24 (11.2%) patients were included, age group II consisted of 22 patients (10.3%), and 168 patients belonged to age group III (78.5%). Girls and boys were equally affected. In all age groups, falls and traffic accidents were the most common causes of cervical spine injuries. A total of 180 patients (84.1%) were treated conservatively, while 34 (15.9%) children underwent surgery. Distorsion/whiplash injury was the most common entity (n = 165; 68.2%). Children aged 0-9 years had significantly (p < 0.001) more frequent injuries of the upper cervical spine (C0-C2) compared to older age groups. Patients of age group III were more likely to suffer from injuries in subaxial localizations. Neurological deficits were rarely seen in all age groups. Head injuries did represent the most common accompanying injuries (39.8%, n = 92). CONCLUSIONS: The upper cervical spine was more frequently affected in young children. Older children more often suffered from subaxial pathologies. The majority of cervical spinal column injuries were treated conservatively. Nevertheless, 15% of the hospitalized children had to be treated surgically.

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.

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.

Individualized Mini-Panel Sequencing of ctDNA Allows Tumor Monitoring in Complex Karyotype Sarcomas.

Soft tissue sarcomas (STS) are rare tumors of mesenchymal origin with high mortality. After curative resection, about one third of patients suffer from distant metastases. Tumor follow-up only covers a portion of recurrences and is associated with high cost and radiation burden. For metastasized STS, only limited inferences can be drawn from imaging data regarding therapy response. To date there are no established and evidence-based diagnostic biomarkers for STS due to their rarity and diversity. In a proof-of-concept study, circulating tumor DNA (ctDNA) was quantified in (n = 25) plasma samples obtained from (n = 3) patients with complex karyotype STS collected over three years. Genotyping of tumor tissue was performed by exome sequencing. Patient-individual mini-panels for targeted next-generation sequencing were designed encompassing up to 30 mutated regions of interest. Circulating free DNA (cfDNA) was purified from plasma and ctDNA quantified therein. ctDNA values were correlated with clinical parameters. ctDNA concentrations correlated with the tumor burden. In case of full remission, no ctDNA was detectable. Patients with a recurrence at a later stage showed low levels of ctDNA during clinical remission, indicating minimal residual disease. In active disease (primary tumor or metastatic disease), ctDNA was highly elevated. We observed direct response to treatment, with a ctDNA decline after tumor resections, radiotherapy, and chemotherapy. Quantification of ctDNA allows for the early detection of recurrence or metastases and can be used to monitor treatment response in STS. Therapeutic decisions can be made earlier, such as the continuation of a targeted adjuvant therapy or the implementation of extended imaging to detect recurrences. In metastatic disease, therapy can be adjusted promptly in case of no response. These advantages may lead to a survival benefit for patients in the future.

The Predictive Value of Early Postoperative MRI-Based Bone Marrow Parameters for Mid-Term Outcome after MACI with Autologous Bone Grafting at the Knee.

OBJECTIVE: The aim of this study was to longitudinally determine the prognostic value of early postoperative quantitative 3T-MRI (magnetic resonance imaging) parameters of subchondral bone marrow for 2-year clinical and MRI outcome after matrix-associated autologous chondrocyte implantation (MACI) with autologous bone grafting (ABG) at the knee. DESIGN: Consecutive subjects who received MACI with ABG for treatment of focal osteochondral defects received MRI follow-up 3, 6, 12, and 24 months postoperatively. Quantitative MRI included bone marrow edema-like lesion (BMEL) volume measurements and single-voxel magnetic resonance spectroscopy (MRS; n = 9) of the subchondral bone marrow. At 2-year follow-up, morphological MRI outcome included MOCART (magnetic resonance observation of cartilage repair tissue) 2.0 scores. Clinical outcomes were assessed using Lysholm scores. RESULTS: Among a total of 18 subjects (mean age: 28.7 ± 8.4 years, n = 14 males) with defects at the medial or lateral (n = 15 and n = 3, respectively) condyle, mean BMEL volume decreased from 4.9 cm3 at 3 months to 2.0 cm3 at 2-year follow-up (P = 0.040). MRS-based bone marrow water T2 showed a decrease from 20.7 ms at 1-year follow-up to 16.8 ms at 2-year follow-up (P = 0.040). Higher BMEL volume at 6 months correlated with lower 2-year Lysholm (R = -0.616, P = 0.015) and MOCART 2.0 scores (R = -0.567, P = 0.027). Larger early postoperative BMEL volumes at 3 months (R = -0.850, P = 0.007) and 6 months (R = -0.811, P = 0.008) correlated with lower MRS-based unsaturated lipid fractions at 2-year follow-up. Furthermore, patients with early postoperative bony defects showed worse MOCART 2.0 (P = 0.044) and Lysholm scores (P = 0.017) after 24 months. CONCLUSION: Low subchondral BMEL volume and optimal restoration of the subchondral bone at early postoperative time points predict better 2-year clinical and MRI outcomes after MACI with ABG.

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.

Development and first application testing of a new protocol for CT-based stability evaluation of the injured upper cervical spine.

PURPOSE: For trauma surgeons, the evaluation of the stability of the upper cervical spine may be demanding. The aim of this study was to develop a protocol for decision-making on upper cervical spine stability in trauma patients based on established parameters obtained by CT imaging as well as testing the protocol by having it applied by trauma surgeons. METHODS: A structured literature search on upper cervical spine stability was performed. The best evaluated instability criteria in CT imaging were determined. Based on these parameters a protocol for stability evaluation of the injured upper cervical spine was developed. A first application testing was performed. In addition to the assessment of instability, the time required for the assessment was analyzed. RESULTS: A protocol for CT-based stability evaluation of the injured upper cervical spine based on the current literature was developed and displayed in a flow chart. Testing of the protocol found the stability of the cervical spine was correctly assessed in 55 of 56 evaluations (98.2%). In one test run, a stable upper cervical spine was judged to be unstable. Further analysis showed that this case was based on a measurement error. The assessment time of CT-images decreased significantly during repeat application of the protocol (p < 0.0001), from 336 ± 108 s (first case) to 180 ± 30 s (fourth case). CONCLUSION: The protocol can be applied quickly and safely by non-specialized trauma surgeons. Thus, the protocol can support the decision-making process in CT-based evaluation of the stability of the injured upper cervical spine.