Noninvasive technique to evaluate the muscle fiber characteristics using q-space imaging

Background Skeletal muscles include fast and slow muscle fibers. The tibialis anterior muscle (TA) is mainly composed of fast muscle fibers, whereas the soleus muscle (SOL) is mainly composed of slow muscle fibers. However, a noninvasive approach for appropriately investigating the characteristics of muscles is not available. Monitoring of skeletal muscle characteristics can help in the evaluation of the effects of strength training and diseases on skeletal muscles. Purpose The present study aimed to determine whether q-space imaging can distinguish between TA and SOL in in vivo mice. Methods In vivo magnetic resonance imaging of the right calves of mice (n = 8) was performed using a 7-Tesla magnetic resonance imaging system with a cryogenic probe. TA and SOL were assessed. q-space imaging was performed with a field of view of 10 mm x 10 mm, matrix of 48 x 48, and section thickness of 1000 mu m. There were ten b-values ranging from 0 to 4244 s/mm(2), and each b-value had diffusion encoding in three directions. Magnetic resonance imaging findings were compared with immunohistological findings. Results Full width at half maximum and Kurtosis maps of q-space imaging showed signal intensities consistent with immunohistological findings for both fast (myosin heavy chain II) and slow (myosin heavy chain I) muscle fibers. With regard to quantification, both full width at half maximum and Kurtosis could represent the immunohistological findings that the cell diameter of TA was larger than that of SOL (P < 0.01). Conclusion q-space imaging could clearly differentiate TA from SOL using differences in cell diameters. This technique is a promising method to noninvasively estimate the fiber type ratio in skeletal muscles, and it can be further developed as an indicator of muscle characteristics.journal articl

Automatic measurement of the Cobb angle for adolescent idiopathic scoliosis using convolutional neural network

Abstract This study proposes a convolutional neural network method for automatic vertebrae detection and Cobb angle (CA) measurement on X-ray images for scoliosis. 1021 full-length X-ray images of the whole spine of patients with adolescent idiopathic scoliosis (AIS) were used for training and segmentation. The proposed AI algorithm's results were compared with those of the manual method by six doctors using the intraclass correlation coefficient (ICC). The ICCs recorded by six doctors and AI were excellent or good, with a value of 0.973 for the major curve in the standing position. The mean error between AI and doctors was not affected by the angle size, with AI tending to measure 1.7°–2.2° smaller than that measured by the doctors. The proposed method showed a high correlation with the doctors’ measurements, regardless of the CA size, doctors’ experience, and patient posture. The proposed method showed excellent reliability, indicating that it is a promising automated method for measuring CA in patients with AIS

A study on the use of the Osstell apparatus to evaluate pedicle screw stability: An in-vitro study using micro-CT.

Pull-out force and insertion torque have not been generally used as intraoperative measures for the evaluation of pedicle screw stability because of their invasiveness. On the other hand, resonance frequency analysis is a non-invasive and repeatable technique that has been clinically used in dentistry to evaluate implant stability e.g. by the Osstell apparatus. In this study, the characteristics of the implant stability quotient (ISQ) value obtained by the Osstell apparatus in the field of spinal surgery were investigated. Biomechanical test materials simulating human bone were used to provide a comparative platform for evaluating each fixation strength measure, including pull-out force, insertion torque, and the ISQ value. To perform pull-out force measurement and to repeat pedicle screw insertion and removal, loosening was artificially created, and its effect was investigated. The grade of loosening was quantified on a micro-CT image after pedicle screw removal. In the comparison of the 3 fixation strength measures, the correlations of the ISQ value with the pull-out force (R2 = 0.339 p <0.0001) and the insertion torque (R2 = 0.337 p <0.0001) were lower than the correlation between pull-out force and insertion torque (R2 = 0.918 p <0.0001). On a micro-CT study, the material volume of the internal threads disappeared after destruction of its integrity due to repeated pedicle screw insertion and removal. Material integrity destruction of the internal threads decreased only the pull-out force and the insertion torque, but it did not affect the ISQ value. The ISQ value only decreased when the material volume of the internal threads disappeared, probably because the ISQ value reflects the resistance against a force in the perpendicular direction of the screw, unlike the conventional measures of fixation strength, such as pull-out force and insertion torque, which reflect axial load

Sweep Pulse Excitation Method for Enhancing Photoacoustic Elastic Waves at Different Laser Irradiation Parameters

Laser remote sensing using a sweep pulse excitation method, in which a laser beam is irradiated at the same repetition frequency as the natural frequency, for enhancing photoacoustic elastic waves through resonance effect has been studied. The sweep pulse excitation method, which is based on the principle of detecting natural frequency fluctuations, such as hammering tests, can detect natural frequencies in the audible sound region with low average laser power and contribute to the convenience and low cost of an installation strength diagnosis of fastening bolts. In this study, we investigated the dynamics of the swept excitation method for optimization by evaluating the dependence of the laser irradiation conditions (pulse width, spot size, and average power) on different metal disc samples. We discovered that the magnitude of the photoacoustic elastic wave is proportional to the absorption of laser power, and the spatiotemporal dynamics can be explained through thermal diffusion phenomena. These findings contribute to the development of laser-sensing technology based on photoacoustic elastic waves

Machine Learning-Based Diagnosis in Laser Resonance Frequency Analysis for Implant Stability of Orthopedic Pedicle Screws

Evaluation of the initial stability of implants is essential to reduce the number of implant failures of pedicle screws after orthopedic surgeries. Laser resonance frequency analysis (L-RFA) has been recently proposed as a viable diagnostic scheme in this regard. In a previous study, L-RFA was used to demonstrate the diagnosis of implant stability of monoaxial screws with a fixed head. However, polyaxial screws with movable heads are also frequently used in practice. In this paper, we clarify the characteristics of the laser-induced vibrational spectra of polyaxial screws which are required for making L-RFA diagnoses of implant stability. In addition, a novel analysis scheme of a vibrational spectrum using L-RFA based on machine learning is demonstrated and proposed. The proposed machine learning-based diagnosis method demonstrates a highly accurate prediction of implant stability (peak torque) for polyaxial pedicle screws. This achievement will contribute an important analytical method for implant stability diagnosis using L-RFA for implants with moving parts and shapes used in various clinical situations

Reliability of Trapezius Muscle Hardness Measurement: A Comparison between Portable Muscle Hardness Meter and Ultrasound Strain Elastography

Prolonged computer work and smartphone use can cause stiffness of the neck and shoulder muscles, including the trapezius muscle. Hence, muscle hardness quantification is clinically beneficial. The present study aimed to examine the reliability of trapezius muscle hardness measurement using a portable muscle hardness meter and ultrasound strain elastography. Overall, 20 healthy young men participated in this study. Prior to measurement, the participant&rsquo;s subjective symptoms, particularly shoulder muscle stiffness, were rated using an 11-point verbal scale. Furthermore, hardness of the right and left upper trapezius muscles was assessed. In the strain elastography assessment, muscle hardness was evaluated using strain ratio. Results showed that, in quantifying upper trapezius muscle hardness, both portable muscle hardness meter and strain elastography had an excellent intra-tester reliability (&gt;0.9). However, the correlation coefficients between muscle hardness values assessed using a muscle hardness meter and those evaluated with strain elastography did not significantly differ, and the scores for subjective shoulder stiffness did not correspond to muscle hardness values. Therefore, the hardness of the trapezius muscle does not directly reflect the subjective shoulder stiffness. Future studies should thoroughly examine the location of the shoulder stiffness, and check whether it is accompanied by local pain or tenderness