Sustained-Drug-Release, Strong, and Anti-Swelling Water-Lipid Biphasic Hydrogels Prepared via Digital Light Processing 3D Printing for Protection against Osteoarthritis: Demonstration in a Porcine Model.

Osteoarthritis is a serious disease affecting joint cartilage. Owing to poor blood supply, the meniscus and acetabular labrum of joints heal poorly after injury. However, the development of artificial alternatives to these components that have similar mechanical properties and cartilage-protection ability is challenging. In this study, a strong hydrogel with a biomimetic microstructure is prepared with an emulsion-type photosensitive resin, where both hydrophilic and hydrophobic monomers, photo-initiator, and drugs can be adopted. In this system, the hydrophobic monomer forms uniformly dispersed aggregates after curing, improving the mechanical properties of the hydrogel significantly. Furthermore, the coordination bonds between nontoxic Zr4+ cations and sulfonic acid groups prevent hydrogel swelling. In addition, the water-oil biphasic hydrogel ink enables the loading of water- and lipid-soluble drugs, yielding hydrogel scaffolds with sustained dual-drug release ability. Crucially, hydrogel scaffolds having excellent mechanical properties, low swelling, and sustained biphasic drug release ability can be prepared using digital light processing 3D printing technology, owing to the high curing rate of the hydrophobic photo-initiator. These hydrogel scaffolds are applied as meniscal and labral replacements in a porcine model and show great promise for the prevention of secondary osteoarthritis, demonstrating the broad potential clinical applications of this material.

Contextual Features and Information Bottleneck-Based Multi-Input Network for Breast Cancer Classification from Contrast-Enhanced Spectral Mammography.

In computer-aided diagnosis methods for breast cancer, deep learning has been shown to be an effective method to distinguish whether lesions are present in tissues. However, traditional methods only classify masses as benign or malignant, according to their presence or absence, without considering the contextual features between them and their adjacent tissues. Furthermore, for contrast-enhanced spectral mammography, the existing studies have only performed feature extraction on a single image per breast. In this paper, we propose a multi-input deep learning network for automatic breast cancer classification. Specifically, we simultaneously input four images of each breast with different feature information into the network. Then, we processed the feature maps in both horizontal and vertical directions, preserving the pixel-level contextual information within the neighborhood of the tumor during the pooling operation. Furthermore, we designed a novel loss function according to the information bottleneck theory to optimize our multi-input network and ensure that the common information in the multiple input images could be fully utilized. Our experiments on 488 images (256 benign and 232 malignant images) from 122 patients show that the method's accuracy, precision, sensitivity, specificity, and f1-score values are 0.8806, 0.8803, 0.8810, 0.8801, and 0.8806, respectively. The qualitative, quantitative, and ablation experiment results show that our method significantly improves the accuracy of breast cancer classification and reduces the false positive rate of diagnosis. It can reduce misdiagnosis rates and unnecessary biopsies, helping doctors determine accurate clinical diagnoses of breast cancer from multiple CESM images.

A Universal and Simple Method to Obtain Hydrogels with Combined Extreme Mechanical Properties and Their Application as Tendon Substitutes.

With the development of biomedical engineering, the preparation of hydrogels with combined extreme mechanical properties similar to those of some biological hydrogels becomes an important research topic for scientists. In this work, a single-network hydrogel with combined extreme mechanical properties is prepared through a simple and universal method, wherein the strength, elongation at break, toughness, and fracture energy of the hydrogel WPU-3PAAm-6PAN are achieved at 24.7 MPa, 544.0%, 68.9 MJ m-3, and 37.2 kJ m-2, respectively. Herein, a series of photosensitive resins in emulsion form are synthesized, and due to the water-oil diphasic characteristic, hydrophobic monomers and high-efficient hydrophobic photo-initiators are adopted into the resins, which can significantly improve the mechanical properties of the hydrogels due to the hydrophobic association effect and solve the biggest barrier of low curing rate in digital light processing (DLP) fabrication of hydrogels, respectively. Moreover, the simple and facile method to obtain robust and tough hydrogels can be universally applied to other polymer systems. Combined with the excellent mechanical properties and printing ability, the hydrogels with optimized structures are fabricated through DLP printing technology and applied as tendon substitutes. The tendon substitutes exhibit superior performance for mechanical connection and regeneration of collagen fibers. Although further clinical research is required, the hydrogels have great potential applications in various biological areas.

Mesenchymal Stem Cells From Different Sources in Meniscus Repair and Regeneration.

Meniscus damage is a common trauma that often arises from sports injuries or menisci tissue degeneration. Current treatment methods focus on the repair, replacement, and regeneration of the meniscus to restore its original function. The advance of tissue engineering provides a novel approach to restore the unique structure of the meniscus. Recently, mesenchymal stem cells found in tissues including bone marrow, peripheral blood, fat, and articular cavity synovium have shown specific advantages in meniscus repair. Although various studies explore the use of stem cells in repairing meniscal injuries from different sources and demonstrate their potential for chondrogenic differentiation, their meniscal cartilage-forming properties are yet to be systematically compared. Therefore, this review aims to summarize and compare different sources of mesenchymal stem cells for meniscal repair and regeneration.

Improving the classification ability of network utilizing fusion technique in contrast-enhanced spectral mammography.

PURPOSE: Contrast-enhanced spectral mammography (CESM) is an effective tool for diagnosing breast cancer with the benefit of its multiple types of images. However, few models simultaneously utilize this feature in deep learning-based breast cancer classification methods. To combine multiple features of CESM and thus aid physicians in making accurate diagnoses, we propose a hybrid approach by taking advantages of both fusion and classification models. METHODS: We evaluated the proposed method on a CESM dataset obtained from 95 patients between ages ranging from 21 to 74 years, with a total of 760 images. The framework consists of two main parts: a generative adversarial network based image fusion module and a Res2Net-based classification module. The aim of the fusion module is to generate a fused image that combines the characteristics of dual-energy subtracted (DES) and low-energy (LE) images, and the classification module is developed to classify the fused image into benign or malignant. RESULTS: Based on the experimental results, the fused images contained complementary information of the images of both types (DES and LE), whereas the model for classification achieved accurate classification results. In terms of qualitative indicators, the entropy of the fused images was 2.63, and the classification model achieved an accuracy of 94.784%, precision of 95.016%, recall of 95.912%, specificity of 0.945, F1_score of 0.955, and area under curve of 0.947 on the test dataset, respectively. CONCLUSIONS: We conducted extensive comparative experiments and analyses on our in-house dataset, and demonstrated that our method produces promising results in the fusion of CESM images and is more accurate than the state-of-the-art methods in classification of fused CESM.

Flat-Tunnel Technique With Independently Tensioned Bundles Better Restores Rotational Stability Than Round-Tunnel Technique in Anatomic Anterior Cruciate Ligament Reconstruction Using Hamstring Graft: A Cadaveric Biomechanical Study.

PURPOSE: To investigate the kinematics differences between round-tunnel (ROT) and flat-tunnel (FLT) techniques in anterior cruciate ligament (ACL) reconstruction when using hamstring graft. METHODS: Nine matched pairs of fresh-frozen cadaveric knees were evaluated for the kinematics of intact, ACL-sectioned, and either ROT or FLT reconstructed knees. The graft bundles for FLT technique were separately tensioned. A 6 degrees of freedom robotic system was used to assess knee laxity: (1) 134-N anterior tibial load at 0°, 15°, 30°, 60°, and 90°of knee flexion; (2) 10 Nm of valgus torque followed by 5 Nm of internal rotation torque simulates a pivot-shift test at 15° and 30°; (3) 5-Nm internal and external rotation torques at 0°, 15°, 30°, 60°, and 90°; (4) 10-Nm varus and valgus torques at 15° and 30°. RESULTS: Significant differences were found for ROT versus FLT techniques in terms of the simulated pivot-shift test at 15° (2.5 mm vs 1.4 mm, respectively, difference from intact; P =.039) and the internal rotation test at 15° (2.5° vs 0.5°, respectively, difference from intact; P =.034) and 30° (2.0° vs 0.4°, respectively, difference from intact; P =.014). No significant differences were found between groups during 134-N anterior tibial load, external rotation and valgus/varus rotation. Neither technique was able to reproduce the intact state during an anterior tibial load and simulated pivot-shift test. CONCLUSIONS: The FLT technique with independently tensioned bundles shows the same anterior control as the ROT technique but better restores rotational stability in terms of the simulated pivot-shift test and the internal rotation test in anatomic ACL reconstruction at time zero. CLINICAL RELEVANCE: The FLT technique with independently tensioned bundles of ACL reconstruction appears to be a viable, more anatomic technique than the ROT technique in mimicking flat anatomy and rotational stability of native ACL.

Feasibility and accuracy of orthopaedic surgical robot system for intraoperative navigation to locate bone tunnel in anterior cruciate ligament reconstruction.

BACKGROUND: The combination of navigational system and robotics has the potential to accurately identify and drill bone tunnels in anterior cruciate ligament (ACL) reconstruction. This study explores the feasibility and accuracy of bone tunnel positioning using the TiRobot, an orthopaedic surgical robot. METHODS: The experiment was divided into two groups. In group A, the bone tunnels were positioned using the TiRobot surgical robot (n = 8). In group B, handheld locators were used for positioning (n = 8). RESULTS: TiRobot can be used for positioning the ACL bone tunnel. The accuracy of positioning the femoral tunnel in group A and B was 1.00 ± 0.20 and 3.10 ± 0.59 mm, respectively (t = -9.49, P < 0.001). As for tibial tunnel, the accuracy was 1.02 ± 0.20 and 2.64 ± 0.14 mm, respectively (t = -18.54, P < 0.001). CONCLUSIONS: The bone tunnel drilling precision using TiRobot for ACL reconstruction surgery was more accurate than traditional surgical techniques.

A Versatile Surgical Method for Studying Meniscus Implantation in a Rabbit Model.

Meniscus injury is a health problem that greatly affects people's quality of life. In recent years, the number of diagnosed meniscus injury is increasing year by year. If not treated in time and correctly, it causes severe damages to the cartilage. Owing to the meniscus' limited healing ability, synthetic/tissue-engineered meniscus has emerged as a new treatment modality in recent years. Rabbit models, which have been proved to be a feasible animal model, have been extensively used to study meniscus implantation. However, there is not a unified and minimally invasive surgical method for meniscus implantation in rabbits, and the current surgical methods have unsolved problems, such as long incisions, patella valgus, and cutting of the medial collateral ligament. Therefore, the goal of this study is to provide a minimally invasive and versatile meniscus implantation method. Compared with the control group, our study showed less trauma to the animal model, and we believe that it has the application significance on tissue-engineered meniscus implantation. Impact statement Meniscal injury is a central area of sports medicine research because of the high and increasing global rate. With its profound potential implications for patients' functions and the subsequent development of arthritis, there is a great need for the synthetic/tissue-engineered menisci. Animal meniscus implantation models allow studying meniscus implantation with synthetic/tissue-engineered meniscus, and the rabbit model is a gold method for meniscus implantation in the laboratory. However, there has not yet been a minimally invasive and versatile surgical technique describing this surgery method. This article, therefore, provides a detailed description of the rabbit meniscus implantation method, including step-by-step surgical instructions and accompanying pictures.

Comparison of three different acidic solutions in tendon decellularized extracellular matrix bio-ink fabrication for 3D cell printing.

Decellularized extracellular matrix (dECM) hydrogels are being increasingly investigated for use in bio-inks for three-dimensional cell printing given their good cytocompatibility and biomimetic properties. The osmotic pressure and stiffness of bio-ink are important factors affecting the biological functions of printed cells. However, little attention has been given to the osmotic pressure and stiffness of the dECM bio-inks. Here, we compared three types of commonly used acidic solutions in the bio-fabrication of a tendon derived dECM bio-ink for 3D cell printing (0.5 M acetic acid, 0.1 M hydrochloric acid and 0.02 M hydrochloric acid). We found that low pH value of 0.1 M hydrochloric acid could accelerate the digestion process for dECM powders. This could lead to a much softer dECM hydrogel with storage modulus less than 100 Pa. This soft dECM hydrogel facilitated the spreading and proliferation of stem cells encapsulated within it. It also showed better tendon-inducing ability compared with two others much stiffer dECM hydrogels. However, this over-digested dECM hydrogel was more unstable as it could shrink with the culture time going on. For 0.5 M acetic acid made dECM bio-ink, the hyperosmotic state of the bio-ink led to much lower cellular viability rates. Postprocess (Dilution or dialysis) to tailor the osmotic pressure of hydrogels could be a necessary step before mixed with cells. Thus, kindly choosing the type and concentration of acidic solution is necessary for dECM bio-ink preparation. And a balance should be made between the digestion period, strength of acidic solution, as well as the size and concentration of the dECM powders. STATEMENT OF SIGNIFICANCE: The dECM bio-ink has been widely used in 3D cell printing for tissue engineering and organ modelling. In this study, we found that different types of acid have different digestion and dissolution status for the dECM materials. A much softer tendon derived dECM hydrogel with lower stiffness could facilitate the cellular spreading, proliferation and tendon differentiation. We also demonstrated that the osmotic pressure should be taken care of in the preparation of dECM bio-ink with 0.5 M acetic acid. Thus, kindly choosing the type and concentration of acidic solution is necessary for dECM bio-ink preparation.

Multiview multimodal network for breast cancer diagnosis in contrast-enhanced spectral mammography images.

PURPOSE: CESM (contrast-enhanced spectral mammography) is an efficient tool for detecting breast cancer because of its image characteristics. However, among most deep learning-based methods for breast cancer classification, few models can integrate both its multiview and multimodal features. To effectively utilize the image features of CESM and thus help physicians to improve the accuracy of diagnosis, we propose a multiview multimodal network (MVMM-Net). METHODS: The experiment is carried out to evaluate the in-house CESM images dataset taken from 95 patients aged 21-74 years with 760 images. The framework consists of three main stages: the input of the model, image feature extraction, and image classification. The first stage is to preprocess the CESM to utilize its multiview and multimodal features effectively. In the feature extraction stage, a deep learning-based network is used to extract CESM images features. The last stage is to integrate different features for classification using the MVMM-Net model. RESULTS: According to the experimental results, the proposed method based on the Res2Net50 framework achieves an accuracy of 96.591%, sensitivity of 96.396%, specificity of 96.350%, precision of 96.833%, F1_score of 0.966, and AUC of 0.966 on the test set. Comparative experiments illustrate that the classification performance of the model can be improved by using multiview multimodal features. CONCLUSION: We proposed a deep learning classification model that combines multiple features of CESM. The results of the experiment indicate that our method is more precise than the state-of-the-art methods and produces accurate results for the classification of CESM images.

Antibiotic-loaded bone cement spacer usage combined with membrane induction in infected gap non-unions: A case series.

OBJECTIVE: To explore the clinical effects upon gap nonunion of antibiotic-loaded bone cement spacer combined with membrane induction on infected bone defects. METHODS: The data of 16 patients with infected bone defects admitted in General Hospital of Shenyang Military Area Command from January 2009 to January 2011 were analyzed retrospectively. There were 12 males and 4 females aged between 24-63 years age (average 43.1 ± 9.7) who had received antibiotic laiden bone cement spacer treatment. Stage-1, debridement and anti-biotic treatment with intraoperative preparation of customized bone cement spacers (antibiotics and bone cement spacer) with or without internal or external fixation Stage-2, removal of spacer and repair of bone defects using membrane-induced technique and internal fixation at bone defects site. RESULTS: Sixteen patients were followed up for 39-98 months, (67.2 ± 20.4) on average. All patients with infected bone defects were healed. X-ray showed that fractures had healed and the new bone formed at graft site was more radio opaque than that of adjacent bone segments. The healing time was 6 to 10 months, (7.4 ± 1.1) on average. There was no recurrence of infection or deformity. CONCLUSION: The antibiotic-loaded cement spacer can control the local infection while maintaining the limb length and increasing the stability, reducing the contracture of bone and soft tissue, creating conditions for subsequent repair and reducing the infection rate of bone defects.

T and N Staging of Gastric Cancer Using Dual-Source Computed Tomography.

AIM: This study is aimed at comparing gastric cancer T and N staging between virtual monochromatic energy images and fusion images generated by dual-source computed tomography (DSCT) dual-energy mode data acquisition prospectively while measuring the iodine concentration of gastric cancer and lymph nodes at different T and N stages from iodine map retrospectively. METHODS: A total of 71 patients (50 males and 21 females; mean age: 59 ± 11 years) confirmed with gastric cancer by endoscopic biopsy with no neoadjuvant chemotherapy were enrolled for the CT examination before surgeries. The preoperative T and N staging results were compared between groups with pathological results as the gold standard. The iodine concentrations of the gastric lesions and LNs were measured on the iodine-based material decomposition images. All iodine concentration values were normalized against those in the abdominal aorta and defined as normalized iodine concentration (nIC) values. The short axis length of LNs and nIC values were statistically analyzed. RESULTS: Group A was better than group B for T3 and T4 staging. No statistically significant difference in the overall accuracies for N staging was found between groups. For the late arterial and delayed phases, T3 and T4 nIC values of the extraserosal adipose tissue showed statistically significant differences. The nIC values between N0 and Nm (N1-N3) showed statistically significant differences in the portal phase only. CONCLUSIONS: T3 and T4 nIC values of the extraserosal adipose tissue showed statistically significant differences. Hence, dual-source CT may be helpful in the differential diagnosis between T3 and T4.

Radiation dose study of 64-slice spiral CT coronary angiography: a paired design.

To compare image noise and radiation dose differences between prospective and retrospective ECG-gated computed tomography (CT) coronary artery imaging with 64-slice spiral CT (64-MSCT) in a paired design. Prospective and retrospective ECG-gated CT coronary angiography was performed among 20 out-patients with suspected coronary artery diseases. If one protocol failed, chose the other instead. The differences in effective dose (ED), image noise, contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) between the two scan protocols were compared. Usual causes of failures were analysed for each. The average ED of retrospective and prospective protocol was 21.6±2 and 6.0±1.2 mSv, respectively. There was a significant statistical difference in the two protocols (p < 0.05 and 6.16e(-14)). The image noise and SNR between the two protocols made no differences (p=0.71, 0.26, >0.05). The average image noise and SNR of retrospective and prospective protocol were (27.95±2.82, 28.66±2.9) and (12.15±1.83, 10.9±1.17). The CNR of retrospective and prospective protocol was (14.52±1.59) and (17.3±2.09), respectively. There was a statistical difference (p < 0.05 and 0.045). The prospective protocol can lower the ED of 64-MSCT a lot than the retrospective protocol. The image noise and SNR made no differences, whereas the prospective protocol gave a better CNR result.