Automatic segmentation of inconstant fractured fragments for tibia/fibula from CT images using deep learning.

Orthopaedic surgeons need to correctly identify bone fragments using 2D/3D CT images before trauma surgery. Advances in deep learning technology provide good insights into trauma surgery over manual diagnosis. This study demonstrates the application of the DeepLab v3+ -based deep learning model for the automatic segmentation of fragments of the fractured tibia and fibula from CT images and the results of the evaluation of the performance of the automatic segmentation. The deep learning model, which was trained using over 11 million images, showed good performance with a global accuracy of 98.92%, a weighted intersection over the union of 0.9841, and a mean boundary F1 score of 0.8921. Moreover, deep learning performed 5-8 times faster than the experts' recognition performed manually, which is comparatively inefficient, with almost the same significance. This study will play an important role in preoperative surgical planning for trauma surgery with convenience and speed.

Feasibility study using multifocal Doppler twinkling artifacts to detect suspicious microcalcifications in ex vivo specimens of breast cancer on US.

Multifocal Doppler twinkling artifact (MDTA) imaging has shown high detection rates of microcalcifications in phantom studies. We aimed to evaluate its performance in detecting suspicious microcalcifications in comparison with mammography by using ex vivo breast cancer specimens. We prospectively included ten women with breast cancer that presented with calcifications on mammography. Both digital specimen mammography and MDTA imaging were performed for ex vivo breast cancer specimens on the day of surgery. Five breast radiologists marked cells that included suspicious microcalcifications (referred to as 'positive cell') on specimen mammographic images using a grid of 5-mm cells. Cells that were marked by at least three readers were considered as 'consensus-positive'. Matched color Doppler twinkling artifact (CDTA) signals were compared between reconstructed US-MDTA projection images and mammographic images. The median detection rate for each case was 74.7% for positive cells and 96.7% for consensus-positive cells. Of the 10 cases, 90% showed a detection rate of ≥ 80%, with 50% of cases showing a 100% detection rate for consensus-positive cells. The proposed MDTA imaging method showed high performance for detecting suspicious microcalcifications in ex vivo breast cancer specimens, and may be a feasible approach for detecting suspicious breast microcalcifications with US.

Real-Time Ultrasound Detection of Breast Microcalcifications Using Multifocus Twinkling Artifact Imaging.

Detecting microcalcifications (MCs) in real time is important in the guidance of many breast biopsies. Due to its capability in visualizing biopsy needles without radiation hazards, ultrasound imaging is preferred over X-ray mammography, but it suffers from low sensitivity in detecting MCs. Here, we present a new nonionizing method based on real-time multifocus twinkling artifact (MF-TA) imaging for reliably detecting MCs. Our approach exploits time-varying TAs arising from acoustic random scattering on MCs with rough or irregular surfaces. To obtain the increased intensity of the TAs from MCs, in MF-TA, acoustic transmit parameters, such as the transmit frequency, the number of focuses and f-number, were optimized by investigating acoustical characteristics of MCs. A real-time MF-TA imaging sequence was developed and implemented on a programmable ultrasound research system, and it was controlled with a graphical user interface during real-time scanning. From an in-house 3D phantom and ex vivo breast specimen studies, the MF-TA method showed outstanding visibility and high-sensitivity detection for MCs regardless of their distribution or the background tissue. These results demonstrated that this nonionizing, noninvasive imaging technique has the potential to be one of effective image-guidance methods for breast biopsy procedures.

Development of a direction-sensitive gamma-ray monitoring system using a gamma camera with a dual-sided collimator: A Monte Carlo study.

Nuclear explosions, sabotage, and dirty bomb materials are considered a security threat. This paper discusses the development of a gamma-ray monitoring system that enables the screening of nuclear materials moving simultaneously on both sides of the system at ports. This direction-sensitive gamma-ray monitoring (DSGM) system consists of a monolithic plastic scintillator surrounded by 28 photomultiplier tubes and dual-sided parallel-hole lead collimators. With Monte Carlo simulation, the monitoring performance of the DSGM system was assessed for static and moving sources. A multilayer perceptron model was employed to estimate the energy-deposited position of the gamma-rays emitted by nuclear materials in the scintillator.

(-)-Gallocatechin gallate from green tea rescues cognitive impairment through restoring hippocampal silent synapses in post-menopausal depression.

Post-menopausal depression (PMD) is a common psychological disorder accompanied by a cognitive deficit, which is caused by a series of uncontrolled emotional disruptions by strong environmental stressors during menopause. To overcome PMD-induced cognitive deficit, Green tea has been suggested as a dietary supplement because of its ameliorating effect on cognitive dysfunction induced by normal aging or neurodegenerative syndromes; however, its clinical use to improve PMD-accompanied cognitive deficit is still limited due to the controversy for the active ingredients and ambiguous mechanism of its action. Here, we developed modified high-temperature-processed green tea extract (HTP-GTE), which showed lower neuronal toxicity than the conventional green tea extract (GTE). We also demonstrated that HTP-GTE administration prevented the development of learned helplessness (LH) in a rat post-menopausal model. Additionally, HTP-GTE improved LH-induced cognitive impairments simultaneously with rescued the long-term synaptic plasticity. This occurred via the restoration of silent synapse formation by increasing the hippocampal BDNF-tyrosine receptor kinase B pathway in the helpless ovariectomized (OVX) rats. Likewise, we also identified that (-)-gallocatechin gallate was the main contributor of the HTP-GTE effect. Our findings suggested that HTP-GTE has a potential as a preventive nutritional supplement to ameliorate cognitive dysfunctions associated with PMD.

3D microcalcification detection using a color Doppler twinkling artifact with optimized transmit conditions: Preliminary results.

PURPOSE: Mammography is the only method that has been proven to detect breast microcalcifications (MCs), but the sensitivity of mammography varies according to breast density. This paper proposes an ultrasound (US) color Doppler twinkling artifact (CDTA) method with optimized transmit conditions to identify breast MCs without ionizing radiation. METHODS: The transmit conditions for US color Doppler imaging (CDI) were optimized to enhance the sensitivity of the twinkling artifact (TA) that arises from random scattering on rough surfaces of breast MCs. To validate the proposed breast MC detection method, a chicken breast phantom with MC particles (groups of particles <400  µ m and <240  µ m ) was fabricated and scanned by a digital mammography system and an US research platform by an L11-5v linear array probe with a three-dimensional (3D) motion tracking system. RESULTS: From the phantom experiment, the proposed 3D CDTA imaging method with optimized transmit conditions (i.e., a center frequency of 5.0 MHz, an f-number of 1.3, and a peak negative pressure of 1.83 MPa) successfully detected all 16 MC particles, comparable to detection with mammography. For a human breast surgical specimen in the ex vivo study, all 10 MC clusters, marked by a radiologist on the mammogram, were identified with the proposed 3D CDTA imaging method. CONCLUSIONS: In the phantom and ex vivo breast specimen studies, the proposed 3D CDTA imaging method successfully detected MCs, and the spatial localization was highly correlated with the mammogram results. These results indicate that the proposed 3D CDTA imaging method has great potential for the detection of MCs without ionizing radiation.

High PRF ultrafast sliding compound doppler imaging: fully qualitative and quantitative analysis of blood flow.

Ultrafast compound Doppler imaging based on plane-wave excitation (UCDI) can be used to evaluate cardiovascular diseases using high frame rates. In particular, it provides a fully quantifiable flow analysis over a large region of interest with high spatio-temporal resolution. However, the pulse-repetition frequency (PRF) in the UCDI method is limited for high-velocity flow imaging since it has a tradeoff between the number of plane-wave angles (N) and acquisition time. In this paper, we present high PRF ultrafast sliding compound Doppler imaging method (HUSDI) to improve quantitative flow analysis. With the HUSDI method, full scanline images (i.e. each tilted plane wave data) in a Doppler frame buffer are consecutively summed using a sliding window to create high-quality ensemble data so that there is no reduction in frame rate and flow sensitivity. In addition, by updating a new compounding set with a certain time difference (i.e. sliding window step size or L), the HUSDI method allows various Doppler PRFs with the same acquisition data to enable a fully qualitative, retrospective flow assessment. To evaluate the performance of the proposed HUSDI method, simulation, in vitro and in vivo studies were conducted under diverse flow circumstances. In the simulation and in vitro studies, the HUSDI method showed improved hemodynamic representations without reducing either temporal resolution or sensitivity compared to the UCDI method. For the quantitative analysis, the root mean squared velocity error (RMSVE) was measured using 9 angles (-12° to 12°) with L of 1-9, and the results were found to be comparable to those of the UCDI method (L = N = 9), i.e. ⩽0.24 cm s-1, for all L values. For the in vivo study, the flow data acquired from a full cardiac cycle of the femoral vessels of a healthy volunteer were analyzed using a PW spectrogram, and arterial and venous flows were successfully assessed with high Doppler PRF (e.g. 5 kHz at L = 4). These results indicate that the proposed HUSDI method can improve flow visualization and quantification with a higher frame rate, PRF and flow sensitivity in cardiovascular imaging.

Texture Analysis of Supraspinatus Ultrasound Image for Computer Aided Diagnostic System.

OBJECTIVES: In this paper, we proposed an algorithm for recognizing a rotator cuff supraspinatus tendon tear using a texture analysis based on a histogram, gray level co-occurrence matrix (GLCM), and gray level run length matrix (GLRLM). METHODS: First, we applied a total of 57 features (5 first order descriptors, 40 GLCM features, and 12 GLRLM features) to each rotator cuff region of interest. Our results show that first order statistics (mean, skewness, entropy, energy, smoothness), GLCM (correlation, contrast, energy, entropy, difference entropy, homogeneity, maximum probability, sum average, sum entropy), and GLRLM features are helpful to distinguish a normal supraspinatus tendon and an abnormal supraspinatus tendon. The statistical significance of these features is verified using a t-test. The support vector machine classification showed accuracy using feature combinations. Support Vector Machine offers good performance with a small amount of training data. Sensitivity, specificity, and accuracy are used to evaluate performance of a classification test. RESULTS: From the results, first order statics features and GLCM and GLRLM features afford 95%, 85%, and 100% accuracy, respectively. First order statistics and GLCM and GLRLM features in combination provided 100% accuracy. Combinations that include GLRLM features had high accuracy. GLRLM features were confirmed as highly accurate features for classified normal and abnormal. CONCLUSIONS: This algorithm will be helpful to diagnose supraspinatus tendon tear on ultrasound images.

Continuous monitoring of arthritis in animal models using optical imaging modalities.

Given the several difficulties associated with histology, including difficulty in continuous monitoring, this study aimed to investigate the feasibility of optical imaging modalities­cross-polarization color (CPC) imaging, erythema index (EI) imaging, and laser speckle contrast (LSC) imaging­for continuous evaluation and monitoring of arthritis in animal models. C57BL/6 mice, used for the evaluation of arthritis, were divided into three groups: arthritic mice group (AMG), positive control mice group (PCMG), and negative control mice group (NCMG). Complete Freund's adjuvant, mineral oil, and saline were injected into the footpad for AMG, PCMG, and NCMG, respectively. LSC and CPC images were acquired from 0 through 144 h after injection for all groups. EI images were calculated from CPC images. Variations in feet area, EI, and speckle index for each mice group over time were calculated for quantitative evaluation of arthritis. Histological examinations were performed, and the results were found to be consistent with those from optical imaging analysis. Thus, optical imaging modalities may be successfully applied for continuous evaluation and monitoring of arthritis in animal models.