Multicentric development and validation of a multi-scale and multi-task deep learning model for comprehensive lower extremity alignment analysis

Osteoarthritis of the knee, a widespread cause of knee disability, is commonly treated in orthopedics due to its rising prevalence. Lower extremity misalignment, pivotal in knee injury etiology and management, necessitates comprehensive mechanical alignment evaluation via frequently-requested weight-bearing long leg radiographs (LLR). Despite LLR's routine use, current analysis techniques are error-prone and time-consuming. To address this, we conducted a multicentric study to develop and validate a deep learning (DL) model for fully automated leg alignment assessment on anterior-posterior LLR, targeting enhanced reliability and efficiency. The DL model, developed using 594 patients' LLR and a 60%/10%/30% data split for training, validation, and testing, executed alignment analyses via a multi-step process, employing a detection network and nine specialized networks. It was designed to assess all vital anatomical and mechanical parameters for standard clinical leg deformity analysis and preoperative planning. Accuracy, reliability, and assessment duration were compared with three specialized orthopedic surgeons across two distinct institutional datasets (136 and 143 radiographs). The algorithm exhibited equivalent performance to the surgeons in terms of alignment accuracy (DL: 0.21 ± 0.18°to 1.06 ± 1.3°vs. OS: 0.21 ± 0.16°to 1.72 ± 1.96°), interrater reliability (ICC DL: 0.90 ± 0.05 to 1.0 ± 0.0 vs. ICC OS: 0.90 ± 0.03 to 1.0 ± 0.0), and clinically acceptable accuracy (DL: 53.9%-100% vs OS 30.8%-100%). Further, automated analysis significantly reduced analysis time compared to manual annotation (DL: 22 ± 0.6 s vs. OS; 101.7 ± 7 s, p ≤ 0.01). By demonstrating that our algorithm not only matches the precision of expert surgeons but also significantly outpaces them in both speed and consistency of measurements, our research underscores a pivotal advancement in harnessing AI to enhance clinical efficiency and decision-making in orthopaedics.

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.

Evaluation of Conventional MR Imaging of the Shoulder in the Diagnosis of Lesions of the Biceps Pulley

RATIONALE AND OBJECTIVES

To determine the diagnostic accuracy and reproducibility of conventional MR imaging (MRI) of the shoulder in evaluating biceps pulley lesions using arthroscopy as the standard of reference.

METHODS

In a retrospective study, MR examinations of 68 patients with arthroscopically proven torn or intact biceps pulley were assessed for the presence of pulley lesions by three radiologists. The following criteria were evaluated: displacement of the long head of the biceps tendon (LHBT) relative to the subscapularis tendon (displacement sign), subluxation/dislocation of the LHBT, the integrity of the superior glenohumeral ligament (SGHL) and the coracohumeral ligament (CHL), lesions of the supraspinatus (SSP) and subscapularis (SSC) tendons adjacent to the rotator interval, presence of biceps tendinopathy and subacromial bursitis.

RESULTS

There were 42 patients with pulley lesions in the study group. Conventional MR imaging showed an overall sensitivity of 95.2%, 88.1% and 92.9%, a specificity of 61.5%, 73.1%, and 80.8% and an accuracy of 82.4%, 82.4% and 88.2% in the diagnosis of pulley lesions. Interobserver agreement was substantial (multirater k = 0.75). Biceps tendinopathy (97.6%, 95.2%, 97.6%), defects of the SGHL (86.3%, 81.0%, 88.1%) and the displacement sign (88.1%, 81.0%, 85.7%) were the most sensitive diagnostic criteria. Subluxation/dislocation of the LHBT was insensitive (78.6%, 42.9%, 33.3%), but specific (69.2%, 100,0%, 96.2%).

CONCLUSION

In the diagnosis of pulley lesions, conventional MR imaging is reproducible and shows high sensitivity and accuracy but moderate specificity.

Deep-learning-based image quality enhancement of CT-like MR imaging in patients with suspected traumatic shoulder injury

PURPOSE

To evaluate the diagnostic performance of CT-like MR images reconstructed with an algorithm combining compressed sense (CS) with deep learning (DL) in patients with suspected osseous shoulder injury compared to conventional CS-reconstructed images.

METHODS

Thirty-two patients (12 women, mean age 46 ± 14.9 years) with suspected traumatic shoulder injury were prospectively enrolled into the study. All patients received MR imaging of the shoulder, including a CT-like 3D T1-weighted gradient-echo (T1 GRE) sequence and in case of suspected fracture a conventional CT. An automated DL-based algorithm, combining CS and DL (CS DL) was used to reconstruct images of the same k-space data as used for CS reconstructions. Two musculoskeletal radiologists assessed the images for osseous pathologies, image quality and visibility of anatomical landmarks using a 5-point Likert scale. Moreover, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated.

RESULTS

Compared to CT, all acute fractures (n = 23) and osseous pathologies were detected accurately on the CS only and CS DL images with almost perfect agreement between the CS DL and CS only images (κ 0.95 (95 %confidence interval 0.82-1.00). Image quality as well as the visibility of the fracture lines, bone fragments and glenoid borders were overall rated significantly higher for the CS DL reconstructions than the CS only images (CS DL range 3.7-4.9 and CS only range 3.2-3.8, P = 0.01-0.04). Significantly higher SNR and CNR values were observed for the CS DL reconstructions (P = 0.02-0.03).

CONCLUSION

Evaluation of traumatic shoulder pathologies is feasible using a DL-based algorithm for reconstruction of high-resolution CT-like MR imaging.

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.

Diagnostic Delay in Patients with Osteoid Osteoma

PURPOSE

 To assess diagnostic delay in patients with osteoid osteoma and to analyze influencing factors.

MATERIALS AND METHODS

 All patients treated for osteoid osteoma at our tertiary referral center between December 1997 and February 2021 were retrospectively identified (n = 302). The diagnosis was verified by an expert panel of radiologists and orthopedic surgeons. The exclusion criteria were post-interventional recurrence, missing data on symptom onset, and lack of pretherapeutic CT images. Clinical parameters were retrieved from the local clinical information system. CT and MR images were assessed by a senior specialist in musculoskeletal radiology.

RESULTS

 After all exclusions, we studied 162 patients (mean age: 24 ± 11 years, 115 men). The average diagnostic delay was 419 ± 485 days (median: 275 days; range: 21-4503 days). Gender, patient age, presence of nocturnal pain, positive aspirin test, extent of bone sclerosis, and location of the tumor within bone and relative to joints did not influence diagnostic delay (p > 0.05). It was, however, positively correlated with nidus size (r = 0.26; p < 0.001) and was shorter with affection of long tubular bones compared to all other sites (p = 0.04). If osteoid osteoma was included in the initial differential diagnoses, the diagnostic delay was also shorter (p = 0.007).

CONCLUSION

 The diagnostic delay in patients with osteoid osteoma is independent of demographics, clinical parameters, and most imaging parameters. A long average delay of more than one year suggests low awareness of the disease among physicians. Patients with unclear imaging findings should thus be referred to a specialized musculoskeletal center or an expert in the field should be consulted in a timely manner.

KEY POINTS

  · In this retrospective study of 162 patients treated for osteoid osteoma, the median diagnostic delay was 275 days (range: 21-4503 days).. · Gender, age, presence of nocturnal pain, positive aspirin test, extent of bone sclerosis, and location of the tumor did not influence the diagnostic delay (p > 0.05).. · Diagnostic delay was positively correlated with nidus size (r = 0.26; p < 0.001) and was shorter with affection of long tubular bones compared to all other sites (376 ± 485 vs. 560 ± 462 days; p = 0.04)..

Cantharidin increases the force of contraction and protein phosphorylation in isolated human atria

Cantharidin, an inhibitor of protein phosphatase 1 (PP1) and protein phosphatase 2A (PP2A), is known to increase the force of contraction and shorten the time to relaxation in human ventricular preparations. We hypothesized that cantharidin has similar positive inotropic effects in human right atrial appendage (RAA) preparations. RAA were obtained during bypass surgery performed on human patients. These trabeculae were mounted in organ baths and electrically stimulated at 1 Hz. For comparison, we studied isolated electrically stimulated left atrial (LA) preparations and isolated spontaneously beating right atrial (RA) preparations from wild-type mice. Cumulatively applied (starting at 10 to 30 µM), cantharidin exerted a positive concentration-dependent inotropic effect that plateaued at 300 µM in the RAA, LA, and RA preparations. This positive inotropic effect was accompanied by a shortening of the time to relaxation in human atrial preparations (HAPs). Notably, cantharidin did not alter the beating rate in the RA preparations. Furthermore, cantharidin (100 µM) increased the phosphorylation state of phospholamban and the inhibitory subunit of troponin I in RAA preparations, which may account for the faster relaxation observed. The generated data indicate that PP1 and/or PP2A play a functional role in human atrial contractility.

Deep Learning-Based Detection of Bone Tumors around the Knee in X-rays of Children

Even though tumors in children are rare, they cause the second most deaths under the age of 18 years. More often than in other age groups, underage patients suffer from malignancies of the bones, and these mostly occur in the area around the knee. One problem in the treatment is the early detection of bone tumors, especially on X-rays. The rarity and non-specific clinical symptoms further prolong the time to diagnosis. Nevertheless, an early diagnosis is crucial and can facilitate the treatment and therefore improve the prognosis of affected children. A new approach to evaluating X-ray images using artificial intelligence may facilitate the detection of suspicious lesions and, hence, accelerate the referral to a specialized center. We implemented a Vision Transformer model for image classification of healthy and pathological X-rays. To tackle the limited amount of data, we used a pretrained model and implemented extensive data augmentation. Discrete parameters were described by incidence and percentage ratio and continuous parameters by median, standard deviation and variance. For the evaluation of the model accuracy, sensitivity and specificity were computed. The two-entity classification of the healthy control group and the pathological group resulted in a cross-validated accuracy of 89.1%, a sensitivity of 82.2% and a specificity of 93.2% for test groups. Grad-CAMs were created to ensure the plausibility of the predictions. The proposed approach, using state-of-the-art deep learning methodology to detect bone tumors on knee X-rays of children has achieved very good results. With further improvement of the algorithm, enlargement of the dataset and removal of potential biases, this could become a useful additional tool, especially to support general practitioners for early, accurate and specific diagnosis of bone lesions in young patients.

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.

True-to-scale DNA-density maps correlate with major accessibility differences between active and inactive chromatin

Chromatin compaction differences may have a strong impact on accessibility of individual macromolecules and macromolecular assemblies to their DNA target sites. Estimates based on fluorescence microscopy with conventional resolution, however, suggest only modest compaction differences (∼2-10×) between the active nuclear compartment (ANC) and inactive nuclear compartment (INC). Here, we present maps of nuclear landscapes with true-to-scale DNA densities, ranging from <5 to >300 Mbp/μm3. Maps are generated from individual human and mouse cell nuclei with single-molecule localization microscopy at ∼20 nm lateral and ∼100 nm axial optical resolution and are supplemented by electron spectroscopic imaging. Microinjection of fluorescent nanobeads with sizes corresponding to macromolecular assemblies for transcription into nuclei of living cells demonstrates their localization and movements within the ANC and exclusion from the INC.

Baseline cartilage T1ρ and T2 predicted patellofemoral joint cartilage lesion progression and patient-reported outcomes after ACL reconstruction

This study aims to determine if baseline T1ρ and T2 will predict cartilage morphological lesion progression in the patellofemoral joint (PFJ) and patient-reported outcomes at 2-year after anterior cruciate ligament (ACL) reconstruction (ACLR). Thirty-nine ACL-injured patients were studied at baseline and two-year after ACLR. 3 T MR T1ρ and T2 images and Knee Injury and Osteoarthritis Outcome Score (KOOS) were acquired at both time points. Voxel-based relaxometry (VBR) technique was used to detect local cartilage abnormalities. Patients were divided into progression and non-progression groups based on changes of the whole-organ magnetic resonance imaging scoring (WORMS) grading of cartilage in PFJ from baseline to 2-year, and into lower (more pain) and higher (less pain) KOOS pain groups based on 2-year KOOS pain scores, separately. Voxel-based analyses of covariance were used to compare T1ρ and T2 values at baseline between the defined groups. Using VBR analysis, the progression group at 2-year showed higher T1ρ and T2 compared with the non-progression group at baseline, with the medial femoral condyle showing the largest areas with significant differences. At two-year, 56% of patients were able to recover with respect to KOOS pain. The lower KOOS pain group at 2-year showed significantly elevated T1ρ and T2 in the patella at baseline compared with the higher KOOS pain group. In conclusion, baseline T1ρ and T2 mapping, combined with VBR analysis, may help identify ACLR patients at high risk of developing progressive PFJ cartilage lesions and worse clinical symptoms 2-year after surgery.

The 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.

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.

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.

High-performance cavity-dumped Q-switched Alexandrite laser CW diode-pumped in double-pass configuration

We present a high-performance Alexandrite laser for LIDAR applications with repetition rates up to 20 kHz in cavity-dumped Q-switched operation continuous-wave diode-pumped in the red spectral region. With a double-pass pump configuration, short pulses with 2.8 ns duration at repetition frequencies ranging from 1 kHz to 20 kHz could be demonstrated. At 5 kHz a - to our knowledge - record pulse energy of over 500 µJ could be achieved at 755 nm in TEM₀₀. Furthermore, a stability measurement at an energy of around 350 µJ with 5 kHz showed no degradation over 150 Mega-shots. The influence of the crystal temperature on the laser performance is also investigated, first in continuous-wave and secondly in cavity-dumped Q-switched operation.

Differentiating Enchondromas and Atypical Cartilaginous Tumors in Long Bones with Computed Tomography and Magnetic Resonance Imaging

The differentiation between the atypical cartilaginous tumor (ACT) and the enchondromas is crucial as ACTs require a curettage and clinical as well as imaging follow-ups, whereas in the majority of cases enchondromas require neither a treatment nor follow-ups. Differentiating enchondromas from ACTs radiologically remains challenging. Therefore, this study evaluated imaging criteria in a combination of computed tomography (CT) and magnetic resonance (MR) imaging for the differentiation between enchondromas and ACTs in long bones. A total of 82 patients who presented consecutively at our institution with either an ACT (23, age 52.7 ±18.8 years; 14 women) or an enchondroma (59, age 46.0 ± 11.1 years; 37 women) over a period of 10 years, who had undergone preoperative MR and CT imaging and subsequent biopsy or/and surgical removal, were included in this study. A histopathological diagnosis was available in all cases. Two experienced radiologists evaluated several imaging criteria on CT and MR images. Likelihood of an ACT was significantly increased if either edema within the bone (p = 0.049), within the adjacent soft tissue (p = 0.006) or continuous growth pattern (p = 0.077) were present or if the fat entrapment (p = 0.027) was absent on MR images. Analyzing imaging features on CT, the likelihood of the diagnosis of an ACT was significantly increased if endosteal scalloping >2/3 (p < 0.001), cortical penetration (p < 0.001) and expansion of bone (p = 0.002) were present and if matrix calcifications were observed in less than 1/3 of the tumor (p = 0.013). All other imaging criteria evaluated showed no significant influence on likelihood of ACT or enchondroma (p > 0.05). In conclusion, both CT and MR imaging show suggestive signs which can help to adequately differentiate enchondromas from ACTs in long bones and therefore can improve diagnostics and consequently patient management. Nevertheless, these features are rare and a combination of CT and MR imaging features did not improve the diagnostic performance substantially.

From Self-supervised Learning to Transfer Learning with Musculoskeletal Radiographs

Ewing sarcomas are malignant neoplasm entities typically found in children and adolescents. Early detection is crucial for therapy and prognosis. Due to the low incidence the general experience as well as according data is limited. Novel support tools for diagnosis, such as deep learning models for image interpretation, are required. While acquiring sufficient data is a common obstacle in medicine, several techniques to tackle small data sets have emerged. The general necessity of large data sets in addition to a rare disease lead to the question whether transfer learning can solve the issue of limited data and subsequently support tasks such as distinguishing Ewing sarcoma from its main differential diagnosis (acute osteomyelitis) in paediatric radiographs. 42,608 unstructured radiographs from our musculoskeletal tumour centre were retrieved from the PACS. The images were clustered with a DeepCluster, a self-supervised algorithm. 1000 clusters were used for the upstream task (pretraining). Following, the pretrained classification network was applied for the downstream task of differentiating Ewing sarcoma and acute osteomyelitis. An untrained network achieved an accuracy of 81.5%/54.2%, while an ImageNet-pretrained network resulted in 89.6%/70.8% for validation and testing, respectively. Our transfer learning approach surpassed the best result by 4.4%/17.3% percentage points. Transfer learning demonstrated to be a powerful technique to support image interpretation tasks. Even for small data sets, the impact can be significant. However, transfer learning is not a final solution to small data sets. To achieve clinically relevant results, a structured and systematic data acquisition is of paramount importance.

Detection and Segmentation of Heterogeneous Bone Tumours in Limited Radiographs

Bone tumours are a rare and often highly malignant entity. Early clinical diagnosis is the most important step, but the difficulty of detecting and assessing bone malignancies is in its radiological peculiarity and limited experience of non-experts. Since X-ray imaging is the first imaging method of bone tumour diagnostics, the purpose of this study is to develop an artificial intelligence (AI) model to detect and segment the tumorous tissue in a radiograph. We investigated which methods are necessary to cope with limited and heterogeneous data. We collected 531 anonymised radiographs from our musculoskeletal tumour centre. In order to adapt to the complexity of recognizing the malignant tissue and cope with limited data, transfer learning, data augmentation as well as several architectures, some of which were initially designed for medical images, were implemented. Furthermore, dataset size was varied by adding another bone tumour entity. We applied a data split of 72%, 18%, 10% for training, validation and testing, respectively. To provide statistical significance and robustness, we applied a cross-validation and image stratification with respect to tumour pixels present. We achieved an accuracy of 99.72% and an intersection over union of 87.43% for hold-out test data by applying several methods to tackle limited data. Transfer learning and additional data brought the greatest performance increase. In conclusion, our model was able to detect and segment tumorous tissue in radiographs with good performance, although it was trained on a very limited amount of data. Transfer Learning and data augmentation proved to significantly mitigate the issue of limited data samples. However, to accomplish clinical significance, more data has to be acquired in the future. Through minor adjustments, the model could be adapted to other musculoskeletal tumour entities and become a general support tool for orthopaedic surgeons and radiologists.

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.

Artificial Intelligence Resolves Kinetic Pathways of Magnesium Binding to RNA

Magnesium is an indispensable cofactor in countless vital processes. In order to understand its functional role, the characterization of the binding pathways to biomolecules such as RNA is crucial. Despite the importance, a molecular description is still lacking since the transition from the water-mediated outer-sphere to the direct inner-sphere coordination is on the millisecond time scale and therefore out of reach for conventional simulation techniques. To fill this gap, we use transition path sampling to resolve the binding pathways and to elucidate the role of the solvent in the binding process. The results reveal that the molecular void provoked by the leaving phosphate oxygen of the RNA is immediately filled by an entering water molecule. In addition, water molecules from the first and second hydration shell couple to the concerted exchange. To capture the intimate solute-solvent coupling, we perform a committor analysis as the basis for a machine learning algorithm that derives the optimal deep learning model from thousands of scanned architectures using hyperparameter tuning. The results reveal that the properly optimized deep network architecture recognizes the important solvent structures, extracts the relevant information, and predicts the commitment probability with high accuracy. Our results provide detailed insights into the solute-solvent coupling which is ubiquitous for kosmotropic ions and governs a large variety of biochemical reactions in aqueous solutions.

Meniscal Root Tears and Extrusion Are Significantly Associated with the Development of Accelerated Knee Osteoarthritis: Data from the Osteoarthritis Initiative

OBJECTIVE

To identify joint structural risk factors, measured using quantitative compositional and semiquantitative magnetic resonance imaging (MRI) scoring, associated with the development of accelerated knee osteoarthritis (AKOA) compared with a more normal rate of knee osteoarthritis (OA) development.

DESIGN

From the Osteoarthritis Initiative we selected knees with no radiographic OA (Kellgren-Lawrence grade [KL] 0/1) that developed advanced-stage OA (KL 3/4; AKOA) within a 4-year timeframe and a comparison group with a more normal rate of OA development (KL 0/1 to KL 2 in 4 years). MRIs at the beginning of the 4-year timeframe were assessed for cartilage T2 values and structural abnormalities using a modified Whole-Organ Magnetic Resonance Imaging Score (WORMS). Associations of MRI findings with AKOA versus normal OA were assessed using multivariable logistic regression models.

RESULTS

A total of 106 AKOA and 168 subjects with normal OA development were included. Mean cartilage T2 values were not significantly associated with AKOA (odds ratio [OR] 1.06; 95% confidence interval [CI] 0.82-1.36). Risk factors for AKOA development included higher meniscus maximum scores (OR 1.37; 95% CI 1.11-1.68), presence of meniscal extrusion (OR 6.30; 95% CI 2.57-15.49), presence of root tears (OR 4.64; 95% CI 1.61-13.34), and higher medial tibia cartilage lesion scores (OR 1.96; 95% CI 1.19-3.24).

CONCLUSIONS

We identified meniscal damage, especially meniscal extrusion and meniscal root tears as risk factors for AKOA development. These findings contribute to identifying subjects at risk of AKOA at an early stage when preventative measures targeting modifiable risk factors such as meniscal repair surgery could still be effective.

Ultrasound-based evaluation revealed reliable postoperative knee stability after combined acute ACL and MCL injuries

Purpose

Anterior cruciate ligament (ACL) injuries are often combined with lesions of the medial collateral ligament (MCL). The aim of this study was to evaluate treatment outcome of combined acute ACL and MCL lesions using functional US and clinical examination.

Methods

Patients aged > 18 years undergoing primary ACL reconstruction with concomitant operative (group 1) or non-operative treatment of the MCL (group 2) between 2014 and 2019 were included after a minimum follow-up of 12 months. Grade II MCL injuries with dislocated tibial or femoral avulsions and grade III MCL ruptures underwent ligament repair whereas grade II injuries without dislocated avulsions were treated non-operatively. Radiological outcome was assessed with functional US examinations. Medial knee joint width was determined in a supine position at 0° and 30° of knee flexion in unloaded and standardized loaded (= 15 Dekanewton) conditions using a fixation device. Clinical examination was performed and patient-reported outcomes were assessed by the use of the subjective knee form (IKDC), Lysholm score, and the Tegner activity scale.

Results

A total of 40 patients (20 per group) met inclusion criteria. Mean age of group 1 was 40 ± 12 years (60% female) with a mean follow-up of 33 ± 17 months. Group 2 showed a mean age of 33 ± 8 years (20% female) with a mean follow-up of 34 ± 15 months. Side-to-side differences in US examinations were 0.4 ± 1.5 mm (mm) in 0° and 0.4 ± 1.5 mm in 30° knee flexion in group 1, and 0.9 ± 1.1 mm in 0° and 0.5 ± 1.4 mm in 30° knee flexion in group 2, with no statistically significant differences between both groups. MCL repair resulted in lower Lysholm scores (75 ± 19 versus 86 ± 15; p < 0.05). No significant differences could be found for subjective IKDC or Tegner activity scores among the two groups.

Conclusion

A differentiated treatment concept in combined ACL and MCL injuries based on injury patterns leads to reliable postoperative ligamentous knee stability in US-based and clinical examinations. However, grade II and III MCL lesions with subsequent operative MCL repair (group 1) result in slightly poorer subjective outcome scores.

Level of evidence

Retrospective cohort study; Level III

Tackling Tumour Cell Heterogeneity at the Super-Resolution Level in Human Colorectal Cancer Tissue

Simple Summary

Tumour cell heterogeneity is the most fundamental problem in cancer diagnosis and therapy. Micro-diagnostic technologies able to differentiate the heterogeneous molecular, especially metastatic, potential of single cells or cell clones already within early primary tumours of carcinoma patients would be of utmost importance. Single molecule localisation microscopy (SMLM) has recently allowed the imaging of subcellular features at the nanoscale. However, the technology has mostly been limited to cultured cell lines only. We introduce a first-in-field approach for quantitative SMLM-analysis of chromatin nanostructure in individual cells in resected, routine-pathology colorectal carcinoma patient tissue sections, illustrating, as a first example, changes in nuclear chromatin nanostructure and microRNA intracellular distribution within carcinoma cells as opposed to normal cells, chromatin accessibility and microRNAs having been shown to be critical in gene regulation and metastasis. We believe this technology to have an enormous potential for future differential diagnosis between individual cells in the tissue context.

Abstract

Tumour cell heterogeneity, and its early individual diagnosis, is one of the most fundamental problems in cancer diagnosis and therapy. Single molecule localisation microscopy (SMLM) resolves subcellular features but has been limited to cultured cell lines only. Since nuclear chromatin architecture and microRNAs are critical in metastasis, we introduce a first-in-field approach for quantitative SMLM-analysis of chromatin nanostructure in individual cells in resected, routine-pathology colorectal carcinoma (CRC) patient tissue sections. Chromatin density profiles proved to differ for cells in normal and carcinoma colorectal tissues. In tumour sections, nuclear size and chromatin compaction percentages were significantly different in carcinoma versus normal epithelial and other cells of colorectal tissue. SMLM analysis in nuclei from normal colorectal tissue revealed abrupt changes in chromatin density profiles at the nanoscale, features not detected by conventional widefield microscopy. SMLM for microRNAs relevant for metastasis was achieved in colorectal cancer tissue at the nuclear level. Super-resolution microscopy with quantitative image evaluation algorithms provide powerful tools to analyse chromatin nanostructure and microRNAs of individual cells from normal and tumour tissue at the nanoscale. Our new perspectives improve the differential diagnosis of normal and (metastatically relevant) tumour cells at the single-cell level within the heterogeneity of primary tumours of patients.

Three-dimensional nanothermometry below the diffraction limit

Lanthanide-doped nanothermometers are used to measure temperature through changes in their emission characteristic with sensitivities of up to a few %/K. In contrast to their sensitivity, their spatial resolution, which is of critical importance for various applications, has not been thoroughly studied and optimized. We numerically investigated the improvement in spatial resolution of nanothermometers with a stimulated emission depletion microscopy approach. Fundamental relationships between spatial and temperature resolution were identified by using different beam parameters for the excitation and depletion beams. Our simulations predict contactless temperature measurement below the diffraction limit with temperature resolution of ±1.25K. We further studied the influence of sample thickness and position on both temperature and spatial resolution and showed the potential of three-dimensional measurements.

An exact a posteriori correction for hydrogen bond population correlation functions and other reversible geminate recombinations obtained from simulations with periodic boundary conditions. Liquid water as a test case

The kinetics of breaking and re-formation of hydrogen bonds (HBs) in liquid water is a prototype of reversible geminate recombination. HB population correlation functions (HBPCFs) are a means to study the HB kinetics. The long-time limiting behavior of HBPCFs is controlled by translatoric diffusion and shows a t^-3/2 time-dependence, which can be described by analytical expressions based on the HB acceptor density and the donor-acceptor inter-diffusion coefficient. If the trajectories are not properly "unwrapped," the presence of periodic boundary conditions (PBCs) can perturb this long-time limiting behavior. Keeping the trajectories "wrapped," however, allows for a more efficient calculation of HBPCFs. We discuss the consequences of PBCs in combination with "wrapped" trajectories following from the approximations according to Luzar-Chandler and according to Starr, each deviating in a different fashion from the true long-time limiting behavior, but enveloping the unperturbed function. A simple expression is given for estimating the maximum time up to which the computed HBPCFs reliably describe the long-time limiting behavior. In addition, an exact a posteriori correction for systems with PBCs for "wrapped" trajectories is derived, which can be easily computed and which is able to fully recover the true t^-3/2 long-time behavior. For comparison, HBPCFs are computed from MD simulations of TIP4P/2005 model water for varying system sizes and temperatures of 273 and 298 K using this newly introduced correction. Implications for the computations of HB lifetimes and the effect of the system-size are discussed.

Hydrogen Bonds between Ions of Opposite and Like Charge in Hydroxyl-Functionalized Ionic Liquids: an Exhaustive Examination of the Interplay between Global and Local Motions and Intermolecular Hydrogen Bond Lifetimes and Kinetics

Hydroxyl-functionalized ionic liquids (ILs) represent a new interesting class of ILs where hydrogen bonds (HBs) play an important role: here, "typical" HBs between cations and anions (ca) are competing with "atypical" HBs connecting pairs of cations (cc). We study the equilibrium and kinetics of (cc) and (ca) HBs in 1-(n-hydroxyalkyl)-pyridinium bis(trifluoromethlysulfonyl)imide [HOC_nPy][NTf₂] ILs by means of molecular dynamics simulations. (cc) HBs are found to be between 0.96 and 3.76 kJ mol^-1 stronger than their (ca) counterparts, depending on the alkyl chain length. HB lifetimes and kinetics are analyzed by means of HB population and reactive flux correlation functions. Essentially, four different HB lifetimes have to be considered, spanning about 3 orders of magnitude, each valid in its own right and each associated with different aspects of HB breaking and HB reformation. The long-time limiting behavior of the HB population correlation function is controlled by diffusion of the ions and can be quantitatively described by analytical expressions. The short-time HB behavior is tied to the localized dynamics of the hydroxyl group exploring its local solvation environment. A minimalist kinetic two-domain model is introduced to realistically describe the time evolution of the HB population correlation function for both (ca) and (cc) HBs over 5 orders of magnitude. By employing the reactive flux method, we determine the kinetics of HB breaking, unaffected by diffusion processes. We determine both, the ultrafast upper boundary and the average rate of HB breaking, allowing recrossing-events during the transient relaxation time period. For sufficiently long alkyl chains, all those computed HB lifetimes indicate a higher kinetic stability of (cc) HBs over (ca) HBs; for short chains, it is vice-versa.

Prognostic Assessment in High-Grade Soft-Tissue Sarcoma Patients: A Comparison of Semantic Image Analysis and Radiomics

BACKGROUND

In patients with soft-tissue sarcomas of the extremities, the treatment decision is currently regularly based on tumor grading and size. The imaging-based analysis may pose an alternative way to stratify patients' risk. In this work, we compared the value of MRI-based radiomics with expert-derived semantic imaging features for the prediction of overall survival (OS).

METHODS

Fat-saturated T2-weighted sequences (T2FS) and contrast-enhanced T1-weighted fat-saturated (T1FSGd) sequences were collected from two independent retrospective cohorts (training: 108 patients; testing: 71 patients). After preprocessing, 105 radiomic features were extracted. Semantic imaging features were determined by three independent radiologists. Three machine learning techniques (elastic net regression (ENR), least absolute shrinkage and selection operator, and random survival forest) were compared to predict OS.

RESULTS

ENR models achieved the best predictive performance. Histologies and clinical staging differed significantly between both cohorts. The semantic prognostic model achieved a predictive performance with a C-index of 0.58 within the test set. This was worse compared to a clinical staging system (C-index: 0.61) and the radiomic models (C-indices: T1FSGd: 0.64, T2FS: 0.63). Both radiomic models achieved significant patient stratification.

CONCLUSIONS

T2FS and T1FSGd-based radiomic models outperformed semantic imaging features for prognostic assessment.

Meniscal ramp lesions: frequency, natural history, and the effect on knee cartilage over 2 years in subjects with anterior cruciate ligament tears

PURPOSE

(i) To investigate the frequency and natural evolution of meniscal ramp lesions (MRLs) on MRI in subjects with acute ACL tear and (ii) to compare knee cartilage compositional degeneration between subjects with MRLs and subjects without meniscal pathology over 2 years.

MATERIALS AND METHODS

Fifty-seven subjects with ACL tears (32 females; age 32.6 ± 8.3 years; BMI 24.5 ± 3.5 kg/m²) from a prospective study were screened for the presence of MRLs. Morphological (high-resolution 3D fast spin-echo) and compositional (T1ρ and T2 mapping) MRI was performed prior to and 2 years after ACL reconstruction. Follow-up MR images were assessed for changes in the signal intensity of the MRLs and the presence of meniscal tears. Differences of compositional parameters were compared between subjects with MRLs and without meniscal lesions using independent samples t tests.

RESULTS

MRLs were found in 16% (9/56) of the subjects with ACL tears at baseline. Only one subject with MRLs developed a posterior horn meniscal tear over 2 years. In 12 knees, no meniscal tears were found, which were defined as controls. Most interestingly, cartilage ∆T1ρ of the medial femur and medial tibia increased significantly more in subjects with MRLs compared with controls (mean difference, MF = 6.0 ± 0.8 vs. 2.3 ± 0.6, p = 0.004, and MT = 4.4 ± 1.4 vs. 0.4 ± 0.6, p = 0.027) and medial femur ∆T2 over 2 years increased significantly more in MRL than in control knees (5.1 ± 2.5 ms vs. 2.2 ± 1.9 ms, p = 0.012).

CONCLUSION

Subjects with ACL tear presented MRLs in 16% of cases. Compared with controls without meniscal lesions, knees with MRLs demonstrated accelerated degeneration of cartilage composition in the medial knee compartment over 2 years.

Role of Cardiac A2A Receptors Under Normal and Pathophysiological Conditions

This review presents an overview of cardiac A2A-adenosine receptors The localization of A2A-AR in the various cell types that encompass the heart and the role they play in force regulation in various mammalian species are depicted. The putative signal transduction systems of A2A-AR in cells in the living heart, as well as the known interactions of A2A-AR with membrane-bound receptors, will be addressed. The possible role that the receptors play in some relevant cardiac pathologies, such as persistent or transient ischemia, hypoxia, sepsis, hypertension, cardiac hypertrophy, and arrhythmias, will be reviewed. Moreover, the cardiac utility of A2A-AR as therapeutic targets for agonistic and antagonistic drugs will be discussed. Gaps in our knowledge about the cardiac function of A2A-AR and future research needs will be identified and formulated.

Kinetics of Hydrogen Bonding between Ions with Opposite and Like Charges in Hydroxyl-Functionalized Ionic Liquids

Hydrogen-bonded structures and their lifetimes in ionic liquids (ILs) are governed by the subtle balance between Coulomb interactions, hydrogen bonding, and dispersion forces. Despite the dominant Coulomb interaction, local and directional hydrogen bonds (HBs) can play an important role in the behavior of ILs. Compared to water, the archetype of hydrogen-bonded liquids, ILs have larger constituents and higher viscosities but are typically lacking a three-dimensional HB network. Hydroxyl-functionalized ionic liquids are even more special: regular HBs between cations and anions (ca) are accompanied by HBs between pairs of cations (cc). Recently, infrared (IR) measurements have suggested that the (cc) HBs are even stronger than their (ca) counterparts and their strength can be controlled via the hydroxyalkyl chain length. In this paper, we show by means of molecular dynamics (MD) simulations that the presence of HBs has a profound effect on the molecular mobility of the ions. We investigate the kinetic mechanism of hydrogen bonding in ILs and show that the lifetimes and hence the stability of (cc) HBs increase with the chain length, making them more stable than the respective (ca) HBs. The observed HB equilibrium can explain the peculiar chain length dependence of the relative molecular mobilities of the ions by a direct comparison between hydroxyl-functionalized ILs with their nonfunctionalized counterparts.

A comprehensive study of the sorption mechanism and thermodynamics of f-element sorption onto K-feldspar

The mobility of heavy metal contaminants and radionuclides in the environment is directly controlled by their interactions with charged mineral surfaces, hence an assessment of their potential toxicity, e.g. in the context of radioactive waste disposal sites, requires understanding of sorption processes on the molecular level. Here, we investigate the sorption of a variety of rare earth elements (REE) and trivalent actinides (Am, Cm) on K-feldspar using batch sorption, time-resolved laser-induced fluorescence spectroscopy (TRLFS), and a surface complexation model. Initially, a reliable pK_a for K-feldspar's surface deprotonation reaction was determined as 2.5 ± 0.02 by column titration experiments, in excellent agreement with a measured pH_IEP of 2.8. Batch sorption experiments over a broad range of experimental conditions in terms of mineral grain size, pH, [M³⁺], ionic radius, solid/liquid ratio, ionic strength, and equilibration procedures were carried out to quantify macroscopic retention. The trivalent d-block element Y, early, mid, and late lanthanides (La, Eu, Nd, Lu), as well as two minor actinides (Am, Cm) were used for batch sorption experiments and showed similar pH dependent uptake behavior, underlining their chemical analogy. In parallel, spectroscopic investigations provided insight into surface speciation. Cm TRLFS spectra indicate the formation of three inner-sphere sorption complexes with increasing hydrolysis. Additionally, a ternary K-feldspar/Cm/silicate complex was found for pH > 10, and batch and spectroscopic data at low pH (<4) point to small amounts of outer sphere sorption complexes. Based on TRLFS data, batch sorption, and titration data, a generic geochemical sorption model was developed, that describes sorption edges for all investigated M³⁺/K-feldspar systems satisfactorily. The derived stability constants for the binary sorption complexes (logK_1-4 = -3.6, -7.7, -11.5, and -17.4, respectively) could successfully be used to reproduce literature data. The stability constants obtained for the surface complexes were included into the database for the Smart K_d-concept, which will further improve the safety assessment of potential repositories for radioactive waste.

Multibiomarker model to discriminate Type 1 and Type 2 myocardial infarction

Background

The discrimination of patients with type 1 myocardial infarction (T1MI) from patients with type 2 MI (T2MI) is often challenging in the emergency department. Earlier we presented a discrimination model, which based on clinical variables, as well as on troponin concentrations. In the present analyses we sought to investigate the discriminative power of 28 biomarkers in patients with T1MI and T2MI.

Methods

Patients presenting to the emergency department with symptoms suggestive of MI were recruited. The final diagnosis of all patients was adjudicated by two physicians in a blinded fashion and based on the fourth universal definition of MI. For the present analyses only patients with T1MI and T2MI were used. In total 28 biomarkers were measured in blood samples collected directly at admission. A multivariable logistic regression model for T1MI vs T2MI as the dependent variable was used and the predictors were chosen via backward step-down selection.

Results

In total 138 patients (107 T1MI and 31 T2MI) were available for the analyses. The median age of the study population was 65 years and 66.7% were males. Hypertension was present in 77.4% and dyslipidemia in 41.3%. In the multivariable model four biomarkers (apolipoprotein A-II, n-terminal prohormone of brain natriuretic peptide, copeptin and high-sensitivity troponin I) were significant discriminators between T1MI and T2MI (Table 1). Internal validation of the model via bootstrap shows a for overoptimism corrected area under the curve of 0.82.

Conclusion

Using a multibiomarker approach discrimination between T1MI and T2MI could be improved. External validation of our findings is warranted.

Funding Acknowledgement

Type of funding source: Public grant(s) – National budget only. Main funding source(s): Research fellowship by the Deutsche Forschungsgemeinschaft

Usefulness of troponin in selecting patients for invasive coronary angiography after cardiac surgery

Background

Great uncertainty exists about the indication for invasive coronary angiography (ICA) in patients with suspected acute coronary syndrome following cardiac surgery.

Aim

The aim of this study was to define clinical criteria that best identify patients who benefit from ICA after cardiac surgery.

Methods

We performed a retrospective analysis of all patients who underwent cardiac surgery between January 2009 and May 2019 at our center. Exclusion criteria included pediatric patients as well as pacemaker, TAVR and LVAD implantation and heart transplantation procedures. The primary outcome was usefulness of ICA as defined by consequent PCI or re-operation due to ICA findings. ECG changes (ST-elevations) and high-sensitivity Troponin I (hsTrop I) were analyzed.

Results

48,136 patients were screened and after applying exclusion criteria 29,359 patients were finally included in the analysis (mean age 67.8±11.0 years, 31.1% females, Euroscore II 5.14±8.9%). A total of 1,171 patients (4%) underwent post-op ICA. The primary outcome occurred in 440 patients (1.5%) of which 290 underwent consequent PCI and 214 underwent consequent re-operation. Baseline characteristics are shown in table 1. Unadjusted analyses did not identify significant differences in the level of cardiac biomarkers between useful-ICA and unuseful-ICA groups.

In multivariate regression analysis, only ST-elevation on ECG predicted the primary outcome (OR 1.33, 95% CI 1.003–1.76).

Dichotomizing hsTrop I concentrations by applying the guideline-specified cut-off (&gt;70x URL) resulted in correct classification of useful-ICA patients in 95.7%. However, the false-positive rate was also extremely high (83.6%) with a positive predictive value (PPV) of 1.6% and a negative predictive value (NPV) of 99.6% (accuracy 17.5%).

Using area under the curve (ROC) analysis following optimal cut-off values for hsTrop I were identified: in CABG patients a cut-off value of &gt;650x URL (corresponding absolute value 17000 ng/L) was defined with a corresponding sensitivity of 83.3%, specificity of 83.6%, PPV of 8.9% and NPV of 99.6% (accuracy 83.6%). In non-CABG patients (i.e. valve or aortic procedures), the cut-off was about twice as high as that for CABG patients (1,350x URL or 35,000 ng/L) with a corresponding sensitivity of 84.1%, specificity of 89.2%, PPV of 5.9% and NPV of 99.9% (accuracy 89.1%).

Conclusion

Our study demonstrates that currently recommended cut-off concentrations of high-sensitivity troponin are not useful for guiding clinical decision-making in patients with suspected acute coronary syndrome following cardiac surgery, while substantially higher cut-off values might be useful. Those cut-off values critically depend on the type of cardiac surgery performed (CABG vs. non-CABG).

Troponin_Curves post-op

Funding Acknowledgement

Type of funding source: None

Discrimination of myocardial infarction and myocardial injury using a multibiomarker approach

Background

In the Universal Definition of Myocardial Infarction (MI) myocardial injury was introduced as a specific diagnosis in patients with elevated troponin concentrations, but without evidence of acute myocardial ischemia. However, their differentiation within the acute setting might be challenging. Therefore, we sought to investigate a multibiomarker panel in these patients and determine the discriminative capacity to differentiation MI from myocardial injury.

Methods

We use a cohorts of acute patients presenting to the emergency department. All final diagnoses were adjudicated by two physicians in a blinded fashion and based on the fourth universal definition of MI. In case of disagreement a third physician referred. For the present analyses only patients diagnosed with MI or myocardial injury were used. A panel of 28 biomarkers was measured in blood samples collected directly at admission. Spearman correlations were calculated. A multivariable logistic regression model using MI as the dependent variable was used and the predictors were chosen via backward step-back selection. Odds ratios (OR) were calculated for each predictor.

Results

We included 359 patients; 138 were diagnosed as having MI and 221 has having myocardial injury. The median age of the study population was 73 years and 59.1% were males. Hypertension was diagnosed in 80.4%, dyslipidemia in 45.4% and diabetes in 19.0%.The biomarker panel showed a wide range of correlations (Figure 1). In the multivariable model five logarithmized biomarkers (N-terminal prohormone of brain natriuretic peptide [OR 0.62], pulmonary and activation-regulated chemokine [OR 0.51], tumor-necrosis-factor-receptor 2 [OR 2.22], copeptin [OR 1.59] and high-sensitivity troponin I [OR 1.80]) were significant discriminators between MI and myocardial injury. Internal validation of the model via bootstrap shows a for overoptimism corrected area under the curve of 0.84.

Conclusion

In the multivariable model five biomarkers were discriminators between MI and myocardial injury.

Spearman correlations

Funding Acknowledgement

Type of funding source: Public grant(s) – National budget only. Main funding source(s): Research fellowship by the Deutsche Forschungsgemeinschaft

Experimental and numerical study of interlock requirements for high-power EYDFAs

In this work, we studied the interlock requirements in a seed failure scenario for Er³⁺:Yb³⁺ doped fiber amplifiers (EYDFAs) pumped with high intensities in the MWcm^-2 range at 9XX nm. We fed a time-dependent FEM-tool with the data from backwards directed amplified spontaneous emission (ASE) transients of different commercially available core-pumped single-mode fibers. In the FEM-tool, the Er³⁺:Yb³⁺ system is defined as a bi-directional energy transfer process and described by the corresponding rate equations. The power evolution of the pump, seed, and ASE signal is computed by differential equations taking into account the transient population densities of the relevant energy levels. With the model, we computed the temporal evolution of the corresponding energy levels after a seeder failure to take place within tens to hundreds of µs and calculated the associated gain. The fibers under test provide a critical total gain of 30 dB after ∼ 80 µs within the Yb³⁺ band and after ∼300 µs within the Er³⁺ band. This time decreases with increasing pump power and doping concentration. The results can be extrapolated to high-power cladding-pumped EYDFAs to meet the challenging requirements of engineering-level systems.

Associations Between Vitamins C and D Intake and Cartilage Composition and Knee Joint Morphology Over 4 Years: Data From the Osteoarthritis Initiative

OBJECTIVE

To determine the cross-sectional and longitudinal associations of vitamin C and D intake with magnetic resonance imaging (MRI) measures of cartilage composition (T2) and joint structure (cartilage, meniscus, and bone marrow) using data from the Osteoarthritis Initiative (OAI) cohort.

METHODS

A total of 1,785 subjects with radiographic Kellgren/Lawrence knee grades 0-3 in the right knee were selected from the OAI database. Vitamins C and vitamin D intake (diet, supplements, and total) were assessed using the Block Brief 2000 Food Frequency Questionnaire at baseline. The MRI analysis protocol included 3T cartilage T2 quantification and semiquantitative joint morphology gradings (Whole-Organ Magnetic Resonance Imaging Score [WORMS]) at baseline and 4 years. Linear regression was used to assess the association between standardized baseline vitamin intake and both baseline WORMS scores and standardized cartilage T2 values.

RESULTS

Higher vitamin C intake was associated with lower average cartilage T2 values, medial tibia T2 values, and medial tibia WORMS scores (standardized coefficient range -0.07 to -0.05, P < 0.05). Higher vitamin D intake was associated with a lower cartilage WORMS sum score and medial femur WORMS score (standardized coefficient range -0.24 to -0.09, P < 0.05). Consistent use of vitamin D supplements of 400 IU at least once a week over 4 years was associated with significantly less worsening of cartilage, meniscus, and bone marrow abnormalities (odds ratio range 0.40-0.56, P < 0.05).

CONCLUSION

Supplementation with vitamin D over 4 years was associated with significantly less progression of knee joint abnormalities. Given the observational nature of this study, future longitudinal randomized controlled trials of vitamin D supplementation are warranted.

THU0053 CONTRIBUTION OF DEFECTIVE NON-APOPTOTIC FAS SIGNALING TO IMMUNE DYSREGULATION IN AUTOIMMUNE LYMPHOPROLIFERATIVE SYNDROME (ALPS)

Background:

ALPS patients show impaired generation of humoral memory for T independent antigens whereas they generate memory for self-antigens due to impaired FAS-dependent removal of autoreactive germinal center B cells. It is known that FAS signaling via caspase activation results in cell apoptosis. However, FAS ligation may also initiate or modulate non-apoptotic signaling as shown for example by its ability to activate NF-κB. Recent data implicate a regulatory role of FAS in the modulation of mTOR signaling in ALPS double-negative T cells. Moreover, a recently described C194V FAS mutation disturbs its post-translational modification leading to impaired apoptosis induction while non-apoptotic signalling is still intact. Consequently, C194V FAS protects from the autoimmune phenotype in the murine ALPS system. This supports the view that FAS may prevent autoimmunity with other mechanisms than inducing apoptosis.

Objectives:

We hypothesize that FAS mutations impair this modulatory signaling, leading to hyper-activation of B cells. Therefore we aim to investigate non apoptotic FAS signaling in B cells derived from healthy individuals and ALPS patients.

Methods:

We studied resting and activated B cells in ALPS patients in presence or absence of FAS ligand by flow cytometry analysing relevant molecules to the CD40 signaling pathway. We used mass cytometry to perform functional phenotyping of B cells isolated from secondary lymphoid organs. Proteomic studies were performed to identify potential signaling circuits and RNA sequencing to study the consequences of FAS signaling on B cell fate.

Results:

In CD40L activated B cells, FAS signaling results in specific modulation of the mTOR signaling pathway. This modulation is absent in ALPS derived B cells. In line with these data germinal center B cells and plasmablast from secondary lymphoid organs of ALPS patients show hyperactive mTOR signaling pathway. Proteomic studies identify a circuit that links FAS to the phosphatase PTEN via DAXX and the deubiquitinase USP7.

Conclusion:

We describe a new role of FAS in the regulation of B cell activation. Defects in FAS signaling in ALPS contribute to dysregulation of the mTOR signaling pathway and disturbed B cell development.

Disclosure of Interests:

None declared

Extracting Voxel-Based Cartilage Relaxometry Features in Hip Osteoarthritis Subjects Using Principal Component Analysis

BACKGROUND

MRI-based relaxation time measurements provide quantitative assessment of cartilage biochemistry. Identifying distinctive relaxometry features in hip osteoarthritis (OA) might provide important information on regional disease variability.

PURPOSE

First, to incorporate fully automatic voxel-based relaxometry (VBR) with principal component analysis (PCA) to extract distinctive relaxometry features in subjects with radiographic hip OA and nondiseased controls. Second, to use the identified features to further distinguish subjects with cartilage compositional abnormalities.

STUDY TYPE

Cross-sectional.

SUBJECTS

Thirty-three subjects with radiographic hip OA (20 males; age, 50.2 ± 13.3 years) and 55 controls participated (28 males; 41.3 ± 12.0 years).

SEQUENCE

A 3.0T scanner using 3D SPGR, combined T_1ρ /T₂ , and fast spin echo sequences.

ASSESSMENT

Pelvic radiographs, patients' self-reported symptoms, physical function, and cartilage morphology were analyzed. Cartilage relaxation times were quantified using traditional regions of interest and VBR approaches. PCA was performed on VBR data to identify distinctive relaxometry features, and were subsequently used to identify a subgroup of subjects from the controls that exhibited compositional abnormalities.

STATISTICAL TESTS

Chi-square and independent t-tests were used to compare group characteristics. Logistic regression models were used to identify the possible principal components (PCs) that were able to predict OA vs. control classification.

RESULTS

In T_1ρ assessment, OA subjects demonstrated higher T_1ρ values in the posterior hip region and deep cartilage layer when compared with controls (P = 0.012 and 0.001, respectively). In T₂ assessment, OA subjects exhibited higher T₂ values in the posterior hip region (P < 0.001). Based on the PC score classification, 16 subjects without radiographic evidence of OA demonstrated relaxometry patterns similar to OA subjects, and exhibited worse physical function (P = 0.003) and cartilage lesions (P = 0.009-0.032) when compared with the remaining controls.

DATA CONCLUSION

The study identified distinctive cartilage relaxometry features that were able to discriminate subjects with and without radiographic hip OA effectively.

LEVEL OF EVIDENCE

1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1708-1719.

Cartilage degeneration post-meniscectomy performed for degenerative disease versus trauma: data from the Osteoarthritis Initiative

OBJECTIVE

To compare the extent of cartilage deterioration in knees with prior meniscal resection related to trauma versus knees with resection related to degenerative disease, and to compare cartilage deterioration in knees with meniscal surgery to knees without meniscal surgery, controlling for prior knee trauma.

MATERIALS AND METHODS

In this cross-sectional study, we assessed cartilage deterioration in right knees of Osteoarthritis Initiative participants: (i) with meniscal surgery due to injury (n = 79); (ii) matched control knees with a prior injury but without meniscal surgery (n = 79); (iii) with meniscal surgery but without preceding injury (n = 36); and (iv) matched control knees without meniscal surgery or prior knee injury (n = 36). Cartilage composition was measured using T2 measurements derived using semi-automatic cartilage segmentation of the right. Linear regression analysis was used to compare compartmental values of T2 between groups.

RESULTS

Comparing the mean T2 values in surgical cases with and without injury our results did not show significant differences (group i vs. iii, p > 0.05). However, knees with previous meniscal surgery showed significantly (p < 0.001) higher mean T2 values across all compartments (i.e., global T2) when compared to those without meniscal surgery for both knees with a history of trauma (group i vs. ii) and knees without prior trauma (group iii vs. iv). Similar results were obtained when analyzing the compartments separately.

CONCLUSIONS

Cartilage deterioration, assessed by T2, is similar in knees undergoing meniscal surgery after trauma and for degenerative conditions. Both groups demonstrated greater cartilage deterioration than nonsurgical knees, controlling for prior knee injury.