Feasibility of Dark-Field Radiography to Enhance Detection of Nondisplaced Fractures.

Background Many clinically relevant fractures are occult on conventional radiographs and therefore challenging to diagnose reliably. X-ray dark-field radiography is a developing method that uses x-ray scattering as an additional signal source. Purpose To investigate whether x-ray dark-field radiography enhances the depiction of radiographically occult fractures in an experimental model compared with attenuation-based radiography alone and whether the directional dependence of dark-field signal impacts observer ratings. Materials and Methods Four porcine loin ribs had nondisplaced fractures experimentally introduced. Microstructural changes were visually verified using high-spatial-resolution three-dimensional micro-CT. X-ray dark-field radiographs were obtained before and after fracture, with the before-fracture scans serving as control images. The presence of a fracture was scored by three observers using a six-point scale (6, surely; 5, very likely; 4, likely; 3, unlikely; 2, very unlikely; and 1, certainly not). Differences between scores based on attenuation radiographs alone (n = 96) and based on combined attenuation and dark-field radiographs (n = 96) were evaluated by using the DeLong method to compare areas under the receiver operating characteristic curve. The impact of the dark-field signal directional sensitivity on observer ratings was evaluated using the Wilcoxon test. The dark-field data were split into four groups (24 images per group) according to their sensitivity orientation and tested against each other. Musculoskeletal dark-field radiography was further demonstrated on human finger and foot specimens. Results The addition of dark-field radiographs was found to increase the area under the receiver operating characteristic curve to 1 compared with an area under the receiver operating characteristic curve of 0.87 (95% CI: 0.80, 0.94) using attenuation-based radiographs alone (P < .001). There were similar observer ratings for the four different dark-field sensitivity orientations (P = .16-.65 between the groups). Conclusion These results suggested that the inclusion of dark-field radiography has the potential to help enhance the detection of nondisplaced fractures compared with attenuation-based radiography alone. © RSNA, 2024 See also the editorial by Rubin in this issue.

Recommender-based bone tumour classification with radiographs-a link to the past.

OBJECTIVES: To develop an algorithm to link undiagnosed patients to previous patient histories based on radiographs, and simultaneous classification of multiple bone tumours to enable early and specific diagnosis. MATERIALS AND METHODS: For this retrospective study, data from 2000 to 2021 were curated from our database by two orthopaedic surgeons, a radiologist and a data scientist. Patients with complete clinical and pre-therapy radiographic data were eligible. To ensure feasibility, the ten most frequent primary tumour entities, confirmed histologically or by tumour board decision, were included. We implemented a ResNet and transformer model to establish baseline results. Our method extracts image features using deep learning and then clusters the k most similar images to the target image using a hash-based nearest-neighbour recommender approach that performs simultaneous classification by majority voting. The results were evaluated with precision-at-k, accuracy, precision and recall. Discrete parameters were described by incidence and percentage ratios. For continuous parameters, based on a normality test, respective statistical measures were calculated. RESULTS: Included were data from 809 patients (1792 radiographs; mean age 33.73 ± 18.65, range 3-89 years; 443 men), with Osteochondroma (28.31%) and Ewing sarcoma (1.11%) as the most and least common entities, respectively. The dataset was split into training (80%) and test subsets (20%). For k = 3, our model achieved the highest mean accuracy, precision and recall (92.86%, 92.86% and 34.08%), significantly outperforming state-of-the-art models (54.10%, 55.57%, 19.85% and 62.80%, 61.33%, 23.05%). CONCLUSION: Our novel approach surpasses current models in tumour classification and links to past patient data, leveraging expert insights. CLINICAL RELEVANCE STATEMENT: The proposed algorithm could serve as a vital support tool for clinicians and general practitioners with limited experience in bone tumour classification by identifying similar cases and classifying bone tumour entities. KEY POINTS: • Addressed accurate bone tumour classification using radiographic features. • Model achieved 92.86%, 92.86% and 34.08% mean accuracy, precision and recall, respectively, significantly surpassing state-of-the-art models. • Enhanced diagnosis by integrating prior expert patient assessments.

The use of quantitative pupillometry in brain death determination: preliminary findings.

PURPOSE: Quantitative pupillometry (QP) has been increasingly applied in neurocritical care as an easy-to-use and reliable technique for evaluating the pupillary light reflex (PLR). Here, we report our preliminary findings on using QP for clinical brain death (BD) determination. MATERIALS: This retrospective study included 17 patients ≥ 18 years (mean age, 57.3 years; standard deviation, 15.8 years) with confirmed BD, as defined by German Guidelines for the determination of BD. The PLR was tested using the NPi®-200 Pupillometer (Neuroptics, Laguna Hill, USA), a handheld infrared device automatically tracking and analyzing pupil dynamics over 3 s. In addition, pupil diameter and neurological pupil index (NPi) were also evaluated. RESULTS: Intracerebral bleeding, subarachnoid hemorrhage, and hypoxic encephalopathy were the most prevalent causes of BD. In all patients, the NPi was 0 for both eyes, indicating the cessation of mid-brain function. The mean diameter was 4.9 mm (± 1.3) for the right pupil and 5.2 mm (±1.2) for the left pupil. CONCLUSIONS: QP is a valuable tool for the BD certification process to assess the loss of PLR due to the cessation of brain stem function. Furthermore, implementing QP before the withdrawal of life-sustaining therapy in brain-injured patients may reduce the rate of missed organ donation opportunities. Further studies are warranted to substantiate the feasibility and potential of this technique in treating patients and identify suitable candidates for this technique during the BD certification process.

The role of sarcopenia in fragility fractures of the pelvis - is sarcopenia an underestimated risk factor?

BACKGROUND: Fragility fractures of the pelvis (FFPs) represent a significant health burden, particularly for the elderly. The role of sarcopenia, an age-related loss of muscle mass and function, in the development and impact of these fractures is not well understood. This study aims to investigate the prevalence and impact of osteoporosis and sarcopenia in patients presenting with FFPs. METHODS: This retrospective study evaluated 140 elderly patients with FFPs. The diagnosis of sarcopenia was assessed by psoas muscle area (PMA) and the height-adjusted psoas muscle index (PMI) measured on computed tomography (CT) scans. Clinical data, radiological findings and functional outcomes were recorded and compared with the presence or absence of sarcopenia and osteoporosis. RESULTS: Our study cohort comprised 119 female (85.0%) and 21 (15.0%) male patients. The mean age at the time of injury or onset of symptoms was 82.26 ± 8.50 years. Sarcopenia was diagnosed in 68.6% (n = 96) patients using PMA and 68.8% (n = 88) using PMI. 73.6% (n = 103) of our study population had osteoporosis and 20.0% (n = 28) presented with osteopenia. Patients with sarcopenia and osteoporosis had longer hospital stays (p < 0.04), a higher rate of complications (p < 0.048) and functional recovery was significantly impaired, as evidenced by a greater need for assistance in daily living (p < 0.03). However, they were less likely to undergo surgery (p < 0.03) and the type of FFP differed significantly (p < 0.04). There was no significant difference in mortality rate, pre-hospital health status, age or gender. CONCLUSION: Our study highlights the important role of sarcopenia in FFPs in terms of the serious impact on health and quality of life in elderly patients especially when osteoporosis and sarcopenia occur together. Identifying and targeting sarcopenia in older patients may be an important strategy to reduce pelvic fractures and improve recovery. Further research is needed to develop effective prevention and treatment approaches that target muscle health in the elderly.

The association of COVID-19 pandemic with the increase of sinogenic and otogenic intracranial infections in children: a 10-year retrospective comparative single-center study.

OBJECTIVE: Otitis media and sinusitis are common childhood infections, typically mild with good outcomes. Recent studies show a rise in intracranial abscess cases in children, raising concerns about a link to COVID-19. This study compares a decade of data on these cases before and after the pandemic. METHODS: This retrospective comparative analysis includes pediatric patients diagnosed with otitis media and sinusitis, who later developed intracranial abscesses over the past decade. We collected comprehensive data on the number of cases, patient demographics, symptoms, treatment, and outcomes. RESULTS: Between January 2013 and July 2023, our center identified 10 pediatric patients (median age 11.1years, range 2.2-18.0 years, 60% male) with intracranial abscesses from otitis media and sinusitis. Of these, 7 cases (70%, median age 9.7 years, range 2.2-18.0 years) occurred since the onset of the COVID-19 pandemic, while the remaining 3 cases (30%, median age 13.3 years, range 9.9-16.7 years) were treated before the pandemic. No significant differences were found in otolaryngological associations, surgical interventions, preoperative symptoms, lab findings, or postoperative antibiotics between the two groups. All patients showed positive long-term recovery. CONCLUSION: This study reveals 5-fold increase of pediatric otogenic and sinogenic intracranial abscess cases in the last three-years since the onset of the COVID-19 pandemic. While further investigation is needed, these findings raise important questions about potential connections between the pandemic and the severity of otitis media and sinusitis complications in children. Understanding these associations can improve pediatric healthcare management during infectious disease outbreaks.

Stereotactic frame-based biopsy of infratentorial lesions via the suboccipital-transcerebellar approach with the Zamorano-Duchovny stereotactic system-a retrospective analysis of 79 consecutive cases.

OBJECTIVE: Lesions of the posterior fossa (brainstem and cerebellum) are challenging in diagnosis and treatment due to the fact that they are often located eloquently and total resection is rarely possible. Therefore, frame-based stereotactic biopsies are commonly used to asservate tissue for neuropathological diagnosis and further treatment determination. The aim of our study was to assess the safety and diagnostic success rate of frame-based stereotactic biopsies for lesions in the posterior fossa via the suboccipital-transcerebellar approach. METHODS: We performed a retrospective database analysis of all frame-based stereotactic biopsy cases at our institution since 2007. The aim was to identify all surgical cases for infratentorial lesion biopsies via the suboccipital-transcerebellar approach. We collected clinical data regarding outcomes, complications, diagnostic success, radiological appearances, and stereotactic trajectories. RESULTS: A total of n = 79 cases of stereotactic biopsies for posterior fossa lesions via the suboccipital-transcerebellar approach (41 female and 38 male) utilizing the Zamorano-Duchovny stereotactic system were identified. The mean age at the time of surgery was 42.5 years (± 23.3; range, 1-87 years). All patients were operated with intraoperative stereotactic imaging (n = 62 MRI, n = 17 CT). The absolute diagnostic success rate was 87.3%. The most common diagnoses were glioma, lymphoma, and inflammatory disease. The overall complication rate was 8.7% (seven cases). All patients with complications showed new neurological deficits; of those, three were permanent. Hemorrhage was detected in five of the cases having complications. The 30-day mortality rate was 7.6%, and 1-year survival rate was 70%. CONCLUSIONS: Our data suggests that frame-based stereotactic biopsies with the Zamorano-Duchovny stereotactic system via the suboccipital-transcerebellar approach are safe and reliable for infratentorial lesions bearing a high diagnostic yield and an acceptable complication rate. Further research should focus on the planning of safe trajectories and a careful case selection with the goal of minimizing complications and maximizing diagnostic success.

Role of Hydrogen Bond Defects for Cluster Formation and Distribution in Ionic Liquids by Means of Neutron Diffraction and Molecular Dynamics Simulations.

Defects fundamentally govern the properties of all real materials. Correlating molecular defects to macroscopic quantities remains a challenge, particularly in the liquid phase. Herein, we report the influence of hydrogen bonds (HB) acting as defects in mixtures of non-hydroxyl-functionalized ionic liquids (ILs) with an increasing concentration of hydroxyl-functionalized ILs. We observed two types of HB defects: The conventional HBs between cation and anion (c-a), and the elusive HBs between cations (c-c) despite the repulsive Coulomb forces. We use neutron diffraction with isotopic substitution in combination with molecular dynamics simulations for measuring the geometry, strength, and distribution of mobile OH defects in the IL mixtures. In principle, this procedure allows relating the number and stability of defects to macroscopic properties such as diffusion, viscosity, and conductivity, which are of utmost importance for the performance of electrolytes in batteries and other electrical devices.

SAM-X: sorting algorithm for musculoskeletal x-ray radiography.

OBJECTIVE: To develop a two-phased deep learning sorting algorithm for post-X-ray image acquisition in order to facilitate large musculoskeletal image datasets according to their anatomical entity. METHODS: In total, 42,608 unstructured and pseudonymized radiographs were retrieved from the PACS of a musculoskeletal tumor center. In phase 1, imaging data were sorted into 1000 clusters by a self-supervised model. A human-in-the-loop radiologist assigned weak, semantic labels to all clusters and clusters with the same label were merged. Three hundred thirty-two non-musculoskeletal clusters were discarded. In phase 2, the initial model was modified by "injecting" the identified labels into the self-supervised model to train a classifier. To provide statistical significance, data split and cross-validation were applied. The hold-out test set consisted of 50% external data. To gain insight into the model's predictions, Grad-CAMs were calculated. RESULTS: The self-supervised clustering resulted in a high normalized mutual information of 0.930. The expert radiologist identified 28 musculoskeletal clusters. The modified model achieved a classification accuracy of 96.2% and 96.6% for validation and hold-out test data for predicting the top class, respectively. When considering the top two predicted class labels, an accuracy of 99.7% and 99.6% was accomplished. Grad-CAMs as well as final cluster results underlined the robustness of the proposed method by showing that it focused on similar image regions a human would have considered for categorizing images. CONCLUSION: For efficient dataset building, we propose an accurate deep learning sorting algorithm for classifying radiographs according to their anatomical entity in the assessment of musculoskeletal diseases. KEY POINTS: • Classification of large radiograph datasets according to their anatomical entity. • Paramount importance of structuring vast amounts of retrospective data for modern deep learning applications. • Optimization of the radiological workflow and increase in efficiency as well as decrease of time-consuming tasks for radiologists through deep learning.

Evaluation of a deep learning-based reconstruction method for denoising and image enhancement of shoulder MRI in patients with shoulder pain.

OBJECTIVES: To evaluate the diagnostic performance of an automated reconstruction algorithm combining MR imaging acquired using compressed SENSE (CS) with deep learning (DL) in order to reconstruct denoised high-quality images from undersampled MR images in patients with shoulder pain. METHODS: Prospectively, thirty-eight patients (14 women, mean age 40.0 ± 15.2 years) with shoulder pain underwent morphological MRI using a pseudo-random, density-weighted k-space scheme with an acceleration factor of 2.5 using CS only. An automated DL-based algorithm (CS DL) was used to create reconstructions of the same k-space data as used for CS reconstructions. Images were analyzed by two radiologists and assessed for pathologies, image quality, and visibility of anatomical landmarks using a 4-point Likert scale. RESULTS: Overall agreement for the detection of pathologies between the CS DL reconstructions and CS images was substantial to almost perfect (κ 0.95 (95% confidence interval 0.82-1.00)). Image quality and the visibility of the rotator cuff, articular cartilage, and axillary recess were overall rated significantly higher for CS DL images compared to CS (p < 0.03). Contrast-to-noise ratios were significantly higher for cartilage/fluid (CS DL 198 ± 24.3, CS 130 ± 32.2, p = 0.02) and ligament/fluid (CS DL 184 ± 17.3, CS 141 ± 23.5, p = 0.03) and SNR values were significantly higher for ligaments and muscle of the CS DL reconstructions (p < 0.04). CONCLUSION: Evaluation of shoulder pathologies was feasible using a DL-based algorithm for MRI reconstruction and denoising. In clinical routine, CS DL may be beneficial in particular for reducing image noise and may be useful for the detection and better discrimination of discrete pathologies. Assessment of shoulder pathologies was feasible with improved image quality as well as higher SNR using a compressed sensing deep learning-based framework for image reconstructions and denoising. KEY POINTS: • Automated deep learning-based reconstructions showed a significant increase in signal-to-noise ratio and contrast-to-noise ratio (p < 0.04) with only a slight increase of reconstruction time of 40 s compared to CS. • All pathologies were accurately detected with no loss of diagnostic information or prolongation of the scan time. • Significant improvements of the image quality as well as the visibility of the rotator cuff, articular cartilage, and axillary recess were detected.

Assessment of glenoid bone loss and other osseous shoulder pathologies comparing MR-based CT-like images with conventional CT.

OBJECTIVES: To evaluate and compare the diagnostic performance of CT-like images based on a 3D T1-weighted spoiled gradient-echo sequence (T1 GRE), an ultra-short echo time sequence (UTE), and a 3D T1-weighted spoiled multi-echo gradient-echo sequence (FRACTURE) with conventional CT in patients with suspected osseous shoulder pathologies. MATERIALS AND METHODS: Patients with suspected traumatic dislocation of the shoulder (n = 46, mean age 40 ± 14.5 years, 19 women) were prospectively recruited and received 3-T MR imaging including 3D T1 GRE, UTE, and 3D FRACTURE sequences. CT was performed in patients with acute fractures and served as standard of reference (n = 25). Agreement of morphological features between the modalities was analyzed including the glenoid bone loss, Hill-Sachs interval, glenoid track, and the anterior straight-line length. Agreement between the modalities was assessed using Bland-Altman plots, Student's t-test, and Pearson's correlation coefficient. Inter- and intrareader assessment was evaluated with weighted Cohen's κ and intraclass correlation coefficient. RESULTS: All osseous pathologies were detected accurately on all three CT-like sequences (n = 25, κ = 1.00). No significant difference in the percentage of glenoid bone loss was found between CT (mean ± standard deviation, 20.3% ± 8.0) and CT-like MR images (FRACTURE 20.6% ± 7.9, T1 GRE 20.4% ± 7.6, UTE 20.3% ± 7.7, p > 0.05). When comparing the different measurements on CT-like images, measurements performed using the UTE images correlated best with CT. CONCLUSION: Assessment of bony Bankart lesions and other osseous pathologies was feasible and accurate using CT-like images based on 3-T MRI compared with conventional CT. Compared to the T1 GRE and FRACTURE sequence, the UTE measurements correlated best with CT. CLINICAL RELEVANCE STATEMENT: In an acute trauma setting, CT-like images based on a T1 GRE, UTE, or FRACTURE sequence might be a useful alternative to conventional CT scan sparing associated costs as well as radiation exposure. KEY POINTS: • No significant differences were found for the assessment of the glenoid bone loss when comparing measurements of CT-like MR images with measurements of conventional CT images. • Compared to the T1 GRE and FRACTURE sequence, the UTE measurements correlated best with CT whereas the FRACTURE sequence appeared to be the most robust regarding motion artifacts. • The T1 GRE sequence had the highest resolution with high bone contrast and detailed delineation of even small fractures but was more susceptible to motion artifacts.

Atraumatic Bone Marrow Edema Involving the Epiphyses.

Bone marrow edema (BME)-like signal intensity involving the epiphyses of tubular bones represents a frequent magnetic resonance imaging finding associated with a wide spectrum of bone and joint disorders. It is important to distinguish this finding from cellular infiltration of bone marrow and to be aware of the differential diagnosis of underlying causes. With a general focus on the adult musculoskeletal system, this article reviews the pathophysiology, clinical presentation, histopathology, and imaging findings of nontraumatic conditions associated with epiphyseal BME-like signal intensity: transient bone marrow edema syndrome, subchondral insufficiency fracture, avascular necrosis, osteoarthritis, arthritis, and bone neoplasms.

Acetabular cartilage delamination: performance of MRI using arthroscopy as the standard of reference.

BACKGROUND: Femoroacetabular impingement (FAI) frequently leads to acetabular chondral delamination. Early identification and treatment of these cases is crucial to prevent further damage to the hip. PURPOSE: To evaluate the accuracy of morphological signs of cartilage acetabular delamination in non-arthrographic magnetic resonance imaging (MRI) using intra-articular arthroscopic findings in patients undergoing FAI surgery. MATERIAL AND METHODS: All hip MRI scans were assessed individually by three independent radiologists. Images were assessed for signs of delamination including the presence of a linear area of bright signal intensity along the acetabular subchondral bone and an area of darker tissue at the surface of the acetabular cartilage. All FAI patients underwent surgery; arthroscopy served as the standard of reference. RESULTS: The mean age of participants was 36.1±10.9 years with 36 (48.6%) women. In the FAI group, arthroscopic surgery showed acetabular chondral delamination in 37 hips. In all hips (including the controls), MRI signs of acetabular cartilage delamination showed an average sensitivity across the three raters of 73.0% with a specificity of 71.0%. In a separate analysis of only the FAI patients, a slightly higher sensitivity (77.7%) but lower specificity (66.7%) was demonstrated. The interrater reliability showed a moderate agreement (average [k]) across the raters (0.450). CONCLUSION: Performance of non-arthrographic MRI in diagnosing acetabular chondral delamination showed good results, yet inter-observer reproducibility among different radiologists was only moderate. Our results suggest that an increased level of awareness, for signs of delamination using MRI, will be helpful for detecting chondral delamination in patients with a history of FAI.

Routine ICU admission after brain tumor surgery: retrospective validation and critical appraisal of two prediction scores.

BACKGROUND: Routine admission to an intensive care unit (ICU) following brain tumor surgery has been a common practice for many years. Although this practice has been challenged by many authors, it has still not changed widely, mainly due to the lack of reliable data for preoperative risk assessment. Motivated by this dilemma, risk prediction scores for postoperative complications following brain tumor surgery have been developed recently. In order to improve the ICU admission policy at our institution, we assessed the applicability, performance, and safety of the two most appropriate risk prediction scores. METHODS: One thousand consecutive adult patients undergoing elective brain tumor resection within 19 months were included. Patients with craniotomy for other causes, i.e., cerebral aneurysms and microvascular decompression, were excluded. The decision for postoperative ICU-surveillance was made by joint judgment of the operating surgeon and the anesthesiologist. All data and features relevant to the scores were extracted from clinical records and subsequent ICU or neurosurgical floor documentation was inspected for any postoperative adverse events requiring ICU admission. The CranioScore derived by Cinotti et al. (Anesthesiology 129(6):1111-20, 5) and the risk assessment score of Munari et al. (Acta Neurochir (Wien) 164(3):635-641, 15) were calculated and prognostic performance was evaluated by ROC analysis. RESULTS: In our cohort, both scores showed only a weak prognostic performance: the CranioScore reached a ROC-AUC of 0.65, while Munari et al.'s score achieved a ROC-AUC of 0.67. When applying the recommended decision thresholds for ICU admission, 64% resp. 68% of patients would be classified as in need of ICU surveillance, and the negative predictive value (NPV) would be 91% for both scores. Lowering the thresholds in order to increase patient safety, i.e., 95% NPV, would lead to ICU admission rates of over 85%. CONCLUSION: Performance of both scores was limited in our cohort. In practice, neither would achieve a significant reduction in ICU admission rates, whereas the number of patients suffering complications at the neurosurgical ward would increase. In future, better risk assessment measures are needed.

Applications of machine learning for imaging-driven diagnosis of musculoskeletal malignancies-a scoping review.

Musculoskeletal malignancies are a rare type of cancer. Consequently, sufficient imaging data for machine learning (ML) applications is difficult to obtain. The main purpose of this review was to investigate whether ML is already having an impact on imaging-driven diagnosis of musculoskeletal malignancies and what the respective reasons for this might be. A scoping review was conducted by a radiologist, an orthopaedic surgeon and a data scientist to identify suitable articles based on the PRISMA statement. Studies meeting the following criteria were included: primary malignant musculoskeletal tumours, machine/deep learning application, imaging data or data retrieved from images, human/preclinical, English language and original research. Initially, 480 articles were found and 38 met the eligibility criteria. Several continuous and discrete parameters related to publication, patient distribution, tumour specificities, ML methods, data and metrics were extracted from the final articles. For the synthesis, diagnosis-oriented studies were further examined by retrieving the number of patients and labels and metric scores. No significant correlations between metrics and mean number of samples were found. Several studies presented that ML could support imaging-driven diagnosis of musculoskeletal malignancies in distinct cases. However, data quality and quantity must be increased to achieve clinically relevant results. Compared to the experience of an expert radiologist, the studies used small datasets and mostly included only one type of data. Key to critical advancement of ML models for rare diseases such as musculoskeletal malignancies is a systematic, structured data collection and the establishment of (inter)national networks to obtain substantial datasets in the future. KEY POINTS: • Machine learning does not yet significantly impact imaging-driven diagnosis for musculoskeletal malignancies compared to other disciplines such as lung, breast or CNS cancer. • Research in the area of musculoskeletal tumour imaging and machine learning is still very limited. • Machine learning in musculoskeletal tumour imaging is impeded by insufficient availability of data and rarity of the disease.

Deep learning-based acceleration of Compressed Sense MR imaging of the ankle.

OBJECTIVES: To evaluate a compressed sensing artificial intelligence framework (CSAI) to accelerate MRI acquisition of the ankle. METHODS: Thirty patients were scanned at 3T. Axial T2-w, coronal T1-w, and coronal/sagittal intermediate-w scans with fat saturation were acquired using compressed sensing only (12:44 min, CS), CSAI with an acceleration factor of 4.6-5.3 (6:45 min, CSAI2x), and CSAI with an acceleration factor of 6.9-7.7 (4:46 min, CSAI3x). Moreover, a high-resolution axial T2-w scan was obtained using CSAI with a similar scan duration compared to CS. Depiction and presence of abnormalities were graded. Signal-to-noise and contrast-to-noise were calculated. Wilcoxon signed-rank test and Cohen's kappa were used to compare CSAI with CS sequences. RESULTS: The correlation was perfect between CS and CSAI2x (κ = 1.0) and excellent for CS and CSAI3x (κ = 0.86-1.0). No significant differences were found for the depiction of structures between CS and CSAI2x and the same abnormalities were detected in both protocols. For CSAI3x the depiction was graded lower (p ≤ 0.001), though most abnormalities were also detected. For CSAI2x contrast-to-noise fluid/muscle was higher compared to CS (p ≤ 0.05), while no differences were found for other tissues. Signal-to-noise and contrast-to-noise were higher for CSAI3x compared to CS (p ≤ 0.05). The high - resolution axial T2-w sequence specifically improved the depiction of tendons and the tibial nerve (p ≤ 0.005). CONCLUSIONS: Acquisition times can be reduced by 47% using CSAI compared to CS without decreasing diagnostic image quality. Reducing acquisition times by 63% is feasible but should be reserved for specific patients. The depiction of specific structures is improved using a high-resolution axial T2-w CSAI scan. KEY POINTS: • Prospective study showed that CSAI enables reduction in acquisition times by 47% without decreasing diagnostic image quality. • Reducing acquisition times by 63% still produces images with an acceptable diagnostic accuracy but should be reserved for specific patients. • CSAI may be implemented to scan at a higher resolution compared to standard CS images without increasing acquisition times.

Diagnosis of joint invasion in patients with malignant bone tumors: value and reproducibility of direct and indirect signs on MR imaging.

OBJECTIVES: To evaluate the performance and reproducibility of MR imaging features in the diagnosis of joint invasion (JI) by malignant bone tumors. METHODS: MR images of patients with and without JI (n = 24 each), who underwent surgical resection at our institution, were read by three radiologists. Direct (intrasynovial tumor tissue (ITT), intraarticular destruction of cartilage/bone, invasion of capsular/ligamentous insertions) and indirect (tumor size, signal alterations of epiphyseal/transarticular bone (bone marrow replacement/edema-like), synovial contrast enhancement, joint effusion) signs of JI were assessed. Odds ratios, sensitivity, specificity, PPV, NPV, and reproducibilities (Cohen's and Fleiss' κ) were calculated for each feature. Moreover, the diagnostic performance of combinations of direct features was assessed. RESULTS: Forty-eight patients (28.7 ± 21.4 years, 26 men) were evaluated. All readers reliably assessed the presence of JI (sensitivity = 92-100 %; specificity = 88-100%, respectively). Best predictors for JI were direct visualization of ITT (OR = 186-229, p < 0.001) and destruction of intraarticular bone (69-324, p < 0.001). Direct visualization of ITT was also highly reliable in assessing JI (sensitivity, specificity, PPV, NPV = 92-100 %), with excellent reproducibility (κ = 0.83). Epiphyseal bone marrow replacement and synovial contrast enhancement were the most sensitive indirect signs, but lacked specificity (29-54%). By combining direct signs with high specificity, sensitivity was increased (96 %) and specificity (100 %) was maintained. CONCLUSION: JI by malignant bone tumors can reliably be assessed on preoperative MR images with high sensitivity, specificity, and reproducibility. Particularly direct visualization of ITT, destruction of intraarticular bone, and a combination of highly specific direct signs were valuable, while indirect signs were less predictive and specific. KEY POINTS: • Direct visualization of intrasynovial tumor was the single most sensitive and specific (92-100%) MR imaging sign of joint invasion. • Indirect signs of joint invasion, such as joint effusion or synovial enhancement, were less sensitive and specific compared to direct signs. • A combination of the most specific direct signs of joint invasion showed best results with perfect specificity and PPV (both 100%) and excellent sensitivity and NPV (both 96 %).

Evaluation of MR-derived simulated CT-like images and simulated radiographs compared to conventional radiography in patients with shoulder pain: a proof-of-concept study.

BACKGROUND: To evaluate the diagnostic value of MR-derived CT-like images and simulated radiographs compared with conventional radiographs in patients with suspected shoulder pathology. METHODS: 3 T MRI of the shoulder including a 3D T1-weighted gradient echo sequence was performed in 25 patients (mean age 52.4 ± 18 years, 13 women) with suspected shoulder pathology. Subsequently a cone-beam forward projection algorithm was used to obtain intensity-inverted CT-like images and simulated radiographs. Two radiologists evaluated the simulated images separately and independently using the conventional radiographs as the standard of reference, including measurements of the image quality, acromiohumeral distance, critical shoulder angle, degenerative joint changes and the acromial type. Additionally, the CT-like MR images were evaluated for glenoid defects, subcortical cysts and calcifications. Agreement between the MR-derived simulated radiographs and conventional radiographs was calculated using Cohen's Kappa. RESULTS: Measurements on simulated radiographs and conventional radiographs overall showed a substantial to almost perfect inter- and intra-rater agreement (κ = 0.69-1.00 and κ = 0.65-0.85, respectively). Image quality of the simulated radiographs was rated good to excellent (1.6 ± 0.7 and 1.8 ± 0.6, respectively) by the radiologists. A substantial agreement was found regarding diagnostically relevant features, assessed on Y- and anteroposterior projections (κ = 0.84 and κ = 0.69 for the measurement of the CSA; κ = 0.95 and κ = 0.60 for the measurement of the AHD; κ = 0.77 and κ = 0.77 for grading of the Samilson-Prieto classification; κ = 0.83 and κ = 0.67 for the grading of the Bigliani classification, respectively). CONCLUSION: In this proof-of-concept study, clinically relevant features of the shoulder joint were assessed reliably using MR-derived CT-like images and simulated radiographs with an image quality equivalent to conventional radiographs. MR-derived CT-like images and simulated radiographs may provide useful diagnostic information while reducing the amount of radiation exposure.

Interrater reliability in the assessment of physiotherapy students.

BACKGROUND: Reliable and objective assessment of psychomotor skills in physiotherapy students' education is essential for direct feedback and skill improvement. The aim of this study is to determine the interrater reliability in the assessment process of physiotherapy students and to analyse the assessment behaviour of the examiners. METHODS: Physiotherapy teachers from two different schools assessed students from two different schools performing proprioceptive neuromuscular facilitation (PNF) patterns. An evaluation sheet with a 6-point rating scale and 20 evaluation criteria including an overall rating was used for assessment. The interrater reliability was determined calculating an intraclass-correlation coefficient (ICC) and Krippendorff's alpha. The assessment behaviour of the examiners was further analysed calculating the location parameters and showing the item response distribution over item in form of a Likert plot. RESULTS: The ICC estimates were mostly below 0.4, indicating poor interrater reliability. This was confirmed by Krippendorff's alpha. The examiners showed a certain central tendency and intergroup bias. DISCUSSION AND CONCLUSION: The interrater reliability in this assessment format was rather low. No difference between the two physiotherapy schools concerning the interrater reliability could be identified. Despite certain limitations of this study, there is a definite need for improvement of the assessment process in physiotherapy education to provide the students with reliable and objective feedback and ensure a certain level of professional competence in the students. TRIAL REGISTRATION: The study was approved by the ethics committee of the Medical Faculty RWTH Aachen University (EK 340/16).

Effect of Early vs Standard Approach to Tracheostomy on Functional Outcome at 6 Months Among Patients With Severe Stroke Receiving Mechanical Ventilation: The SETPOINT2 Randomized Clinical Trial.

Importance: Many patients with severe stroke have impaired airway protective reflexes, resulting in prolonged invasive mechanical ventilation. Objective: To test whether early vs standard tracheostomy improved functional outcome among patients with stroke receiving mechanical ventilation. Design, Setting, and Participants: In this randomized clinical trial, 382 patients with severe acute ischemic or hemorrhagic stroke receiving invasive ventilation were randomly assigned (1:1) to early tracheostomy (≤5 days of intubation) or ongoing ventilator weaning with standard tracheostomy if needed from day 10. Patients were randomized between July 28, 2015, and January 24, 2020, at 26 US and German neurocritical care centers. The final date of follow-up was August 9, 2020. Interventions: Patients were assigned to an early tracheostomy strategy (n = 188) or to a standard tracheostomy (control group) strategy (n = 194). Main Outcomes and Measures: The primary outcome was functional outcome at 6 months, based on the modified Rankin Scale score (range, 0 [best] to 6 [worst]) dichotomized to a score of 0 (no disability) to 4 (moderately severe disability) vs 5 (severe disability) or 6 (death). Results: Among 382 patients randomized (median age, 59 years; 49.8% women), 366 (95.8%) completed the trial with available follow-up data on the primary outcome (177 patients [94.1%] in the early group; 189 patients [97.4%] in the standard group). A tracheostomy (predominantly percutaneously) was performed in 95.2% of the early tracheostomy group in a median of 4 days after intubation (IQR, 3-4 days) and in 67% of the control group in a median of 11 days after intubation (IQR, 10-12 days). The proportion without severe disability (modified Rankin Scale score, 0-4) at 6 months was not significantly different in the early tracheostomy vs the control group (43.5% vs 47.1%; difference, -3.6% [95% CI, -14.3% to 7.2%]; adjusted odds ratio, 0.93 [95% CI, 0.60-1.42]; P = .73). Of the serious adverse events, 5.0% (6 of 121 reported events) in the early tracheostomy group vs 3.4% (4 of 118 reported events) were related to tracheostomy. Conclusions and Relevance: Among patients with severe stroke receiving mechanical ventilation, a strategy of early tracheostomy, compared with a standard approach to tracheostomy, did not significantly improve the rate of survival without severe disability at 6 months. However, the wide confidence intervals around the effect estimate may include a clinically important difference, so a clinically relevant benefit or harm from a strategy of early tracheostomy cannot be excluded. Trial Registration: ClinicalTrials.gov Identifier: NCT02377167.

CT-Navigated Spinal Instrumentations-Three-Dimensional Evaluation of Screw Placement Accuracy in Relation to a Screw Trajectory Plan.

Background and Objectives: In the literature, spinal navigation and robot-assisted surgery improved screw placement accuracy, but the majority of studies only qualitatively report on screw positioning within the vertebra. We sought to evaluate screw placement accuracy in relation to a preoperative trajectory plan by three-dimensional quantification to elucidate technical benefits of navigation for lumbar pedicle screws. Materials and Methods: In 27 CT-navigated instrumentations for degenerative disease, a dedicated intraoperative 3D-trajectory plan was created for all screws. Final screw positions were defined on postoperative CT. Trajectory plans and final screw positions were co-registered and quantitatively compared computing minimal absolute differences (MAD) of screw head and tip points (mm) and screw axis (degree) in 3D-space, respectively. Differences were evaluated with consideration of the navigation target registration error. Clinical acceptability of screws was evaluated using the Gertzbein−Robbins (GR) classification. Results: Data included 140 screws covering levels L1-S1. While screw placement was clinically acceptable in all cases (GR grade A and B in 112 (80%) and 28 (20%) cases, respectively), implanted screws showed considerable deviation compared to the trajectory plan: Mean axis deviation was 6.3° ± 3.6°, screw head and tip points showed mean MAD of 5.2 ± 2.4 mm and 5.5 ± 2.7 mm, respectively. Deviations significantly exceeded the mean navigation registration error of 0.87 ± 0.22 mm (p < 0.001). Conclusions: Screw placement was clinically acceptable in all screws after navigated placement but nevertheless, considerable deviation in implanted screws was noted compared to the initial trajectory plan. Our data provides a 3D-quantitative benchmark for screw accuracy achievable by CT-navigation in routine spine surgery and suggests a framework for objective comparison of screw outcome after navigated or robot-assisted procedures. Factors contributing to screw deviations should be considered to assure optimal surgical results when applying navigation for spinal instrumentation.