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Background In this study, we aimed to investigate the value of Diffusion-Weighted Imaging-Alberta Stroke Program Early CT Score (DWI-ASPECTS) in predicting stroke-associated pneumonia (SAP) in patients with acute ischemic stroke. Methods A total of 291 patients who suffered acute cerebral infarction for the first time were included in this retrospective study. DWI-ASPECTS was assessed and clinical data were collected in order to find the risk factors of SAP, and a logistic regression model was used to investigate the effect of predicting SAP. Furthermore, correlation analysis was used to explore the relationship between DWI-ASPECTS and the immume status of the body. Results Among the 291 patients, 74 (25.4%) subjects were diagnosed with SAP. Compared with non-SAP, the patients with SAP were older and had a higher rate of atrial fibrillation (AF), National Institutes of Health Stroke Scale (NIHSS) scores. The SAP group also had a significantly lower DWI-ASPECTS than did the non-SAP group (P P 0.7, 95% CI [0.678–0.800]) had acceptable discriminatory abilities. By the correlation analysis, DWI-ASPECTS was found to be negatively correlated with the count of white blood cell, neutrophils, monocytes, neutrophil-to-monocyte ratio and neutrophil-to-lymphocyte ratio, and positively correlated with the count of lymphocytes. Conclusions DWI-ASPECTS grades could predict stroke-associated pneumonia for patients with acute ischemic stroke, and combining grade with age, AF, or NIHSS could predict SAP events more accurately.

BackgroundSubacromial pain syndrome is one of the most frequent injuries in overhead athletes, and it takes place when the acromiohumeral distance (AHD) is narrowed. Conservative treatment is the first approach to this syndrome, being shoulder taping one of the most used techniques. Although there are quite a few studies that analyse the effect of taping on the AHD, most of them do not include sham tapings. This study aimed to examine if the Relocation of the humeral head (RHH) taping produced an increase in the AHD in healthy recreationally weightlifter males, quantifying the change that may be due to a placebo effect.MethodsThe design of this study was a two-group pretest-posttest, in which eighteen healthy recreationally weightlifter males were measured. in a laboratory of the University of Valencia. RHH using rigid or sham taping was randomly applied to the participants. The AHD was measured and registered before and after the application of the taping for both groups by a blinded examiner using ultrasound.ResultsThere were no significant differences between pre and post measures in the sham group (p= 0.51). The experimental group showed a significant AHD increase of 9.2% (10.75 ± 1.89vs11.74 ± 1.82, respectively, withpp

The sliding-window-based dynamic functional connectivity network (D-FCN) has been becoming an increasingly useful tool for understanding the changes of brain connectivity patterns and the association of neurological diseases with these dynamic variations. However, conventional D-FCN is essentially low-order network, which only reflects the pairwise interaction pattern between brain regions and thus overlooking the high-order interactions among multiple brain regions. In addition, D-FCN is innate with temporal sensitivity issue, i.e., D-FCN is sensitive to the chronological order of its subnetworks. To deal with the above issues, we propose a novel high-order functional connectivity network framework based on the central moment feature of D-FCN. Specifically, we firstly adopt a central moment approach to extract multiple central moment feature matrices from D-FCN. Furthermore, we regard the matrices as the profiles to build multiple high-order functional connectivity networks which further capture the higher level and more complex interaction relationships among multiple brain regions. Finally, we use the voting strategy to combine the high-order networks with D-FCN for autism spectrum disorder diagnosis. Experimental results show that the combination of multiple functional connectivity networks achieves accuracy of 88.06%, and the best single network achieves accuracy of 79.5%.

This study explores the use of a minimally invasive assessment of myocardial infarction (MI) in mice using myocardial contrast echocardiography (MCE). The technique uses existing equipment and software readily available to the average researcher. C57/BL6 mice were randomized to either MI or sham surgery and evaluated using MCE at 1- or 2-weeks post-surgery. Size-isolated microbubbles were injected via retro-orbital catheter where their non-linear characteristics were utilized to produce the two-dimensional parameters of Wash-in-Rate and the Peak Enhancement, indicative of relative myocardial perfusion and blood volume, respectively. Three-dimensional cardiac reconstructions allowed the calculation of the Percent Agent, interpreted as the vascularity of the entire myocardium. These MCE parameters were compared to conventional assessments including M-Mode, strain analysis, and 2,3,5-Triphenyltetrazolium chloride (TTC) staining. Except for the Wash-in-Rate 2-week cohort, all MCE parameters were able to differentiate sham-operated versus MI animals and correlated with TTC staining (P < 0.05). MCE parameters were also able to identify MI group animals which failed to develop infarctions as determined by TTC staining. This study provides basic validation of these MCE parameters to detect MI in mice complementary to conventional methods while providing additional hemodynamic information in vivo.

Artificial intelligence has been emerging as an increasingly important aspect of our daily lives and is widely applied in medical science. One major application of artificial intelligence in medical science is medical imaging. As a major component of artificial intelligence, many machine learning models are applied in medical diagnosis and treatment with the advancement of technology and medical imaging facilities. The popularity of convolutional neural network in dental, oral and craniofacial imaging is heightening, as it has been continually applied to a broader spectrum of scientific studies. Our manuscript reviews the fundamental principles and rationales behind machine learning, and summarizes its research progress and its recent applications specifically in dental, oral and craniofacial imaging. It also reviews the problems that remain to be resolved and evaluates the prospect of the future development of this field of scientific study.

Background Pompe Disease (PD) is a rare inherited metabolic myopathy, caused by lysosomal-α-glucosidase (GAA) deficiency, which leads to glycogen accumulation within the lysosomes, resulting in cellular and tissue damage. Due to the emergence of a disease modifying treatment with recombinant GAA there has been a large increase in studies of late onset Pompe Disease (LOPD) during the last decade. Methods The present study evaluates muscle quality in 10 patients with LOPD receiving treatment with enzyme replacement therapy and in 10 age and gender matched healthy controls applying T1-weighted Dixon MR imaging and isokinetic dynamometry. Muscle quality was determined by muscle strength in relation to muscle size (contractile cross-sectional area, CSA) and to muscle quality (fat fraction). A follow-up evaluation of the patients was performed after 8–12 months. Patient evaluations also included: six-minute walking test (6MWT), forced vital capacity, manual muscle testing and SF-36 questionnaire. Results Fat fraction of knee flexors (0.15 vs 0.07, p p r = 0.86, knee extensors: r = 0.88, hip extensors: r = 0.83, p

Background Merino land sheep are a popular pre-clinical large animal model in research on systemic skeletal diseases such as osteoporosis. Interpretation of studies is difficult because many reference parameters are missing or not established. This study aims to determine the reference parameters of the skeletal system (peak bone mass = PBM, T-Score). A defined standard allows an easier comparison of the study data of the animal model with human studies (T-Score). Materials and methods A total of 116 Dual Energy X-ray Absorptiometry DXA measurements were performed on 74 untreated sheep. The average age of the animals was 57 months. The BMD, BMC, and fat content of the sheep were determined by the relevant human region of interest (ROI). From this, the PBM and from this the T-score for each of the animals were calculated. Results Using 682 DXA measurements BMD and BMC were determined to provide an indication to PBM. For BMD a significant correlation to the age of the animals was observed (p = 0.043). A significant correlation was also seen for BMC (B) (p ≤ 0.001). In the age-dependent analysis, a widespread of values above the linear regression line was measured for both BMD and BMC between the 50th and 90th months of life. From an age of about 90 months, a wider spread of values below the linear regression line was found, although the average values continued to rise. Discussion The evaluation of the 116 DXA measurements allowed the determination of the PBM for merino land sheep. With the help of the PBM, a T-score was calculated for each animal. The statistical analysis shows significant differences in BMD values between the different animal groups in each of the four ROIs investigated. Individual control or sham groups per study are therefore not sufficient. To improve comparability, an independent reference group should be established. Conclusion An independent reference group for PBM and a T-score was established from four to six-year-old animals. The bone density increases with the age of the animals. Around the fourth year of life, a first peak could be observed. Also, after the seventh year of life, a further peak with the beginning plateau phase was observed. When compiling a group of animals for an osteoporosis model, animals from the age of seven years should, therefore, be used.

With the novel coronavirus disease 2019 (COVID-19) pandemic, the need for radiologic procedures is increasing for the effective diagnosis and follow-up of pulmonary diseases. There is an immense load on the radiographers’ shoulders to cope with all the challenges associated with the pandemic. However, amidst this crisis, Lebanese radiographers are also suffering from a socioeconomic crisis and record hyperinflation that have posed additional challenges. A cross-sectional study was conducted among registered Lebanese radiographers to assess the general, workplace conditions, health and safety, mental/psychologic, financial, and skill/knowledge development impacts. Despite applying an adapted safety protocol, institutions are neither providing free RT-PCR testing to their staff nor showing adequate support for infected staff members, thus causing distress about contracting the virus from the workplace. Aggravated by the deteriorating economic situation that affected the radiographers financially, they additionally suffer from severe occupational physical and mental burnout. Regardless of that, they used their free time during the lockdown for skill/knowledge development and have performed many recreational activities. This cross-sectional study highlighted the different ways the pandemic has impacted the radiographers: physically, psychologically, and financially. It aimed to shed light on what these frontline heroes are passing through in the midst of all these unprecedented crises.

While tactile sensation plays an essential role in interactions with the surroundings, relatively little is known about the neural processes involved in the perception of tactile information. In particular, it remains unclear how different intensities of tactile hardness are represented in the human brain during object manipulation. This study aims to investigate neural responses to various levels of tactile hardness using functional magnetic resonance imaging while people grasp objects to perceive hardness intensity. We used four items with different hardness levels but otherwise identical in shape and texture. A total of Twenty-five healthy volunteers participated in this study. Before scanning, participants performed a behavioral task in which they received a pair of stimuli and they were to report the perceived difference of hardness between them. During scanning, without any visual information, they were randomly given one of the four objects and asked to grasp it. We found significant blood oxygen-level-dependent (BOLD) responses in the posterior insula in the right hemisphere (rpIns) and the right posterior lobe of the cerebellum (rpCerebellum), which parametrically tracked hardness intensity. These responses were supported by BOLD signal changes in the rpCerebellum and rpIns correlating with tactile hardness intensity. Multidimensional scaling analysis showed similar representations of hardness intensity among physical, perceptual, and neural information. Our findings demonstrate the engagement of the rpCerebellum and rpIns in perceiving tactile hardness intensity during active object manipulation.

Background Prostate cancer is one of the most common cancers worldwide. Currently, convolution neural networks (CNNs) are achieving remarkable success in various computer vision tasks, and in medical imaging research. Various CNN architectures and methodologies have been applied in the field of prostate cancer diagnosis. In this work, we evaluate the impact of the adaptation of a state-of-the-art CNN architecture on domain knowledge related to problems in the diagnosis of prostate cancer. The architecture of the final CNN model was optimised on the basis of the Prostate Imaging Reporting and Data System (PI-RADS) standard, which is currently the best available indicator in the acquisition, interpretation, and reporting of prostate multi-parametric magnetic resonance imaging (mpMRI) examinations. Methods A dataset containing 330 suspicious findings identified using mpMRI was used. Two CNN models were subjected to comparative analysis. Both implement the concept of decision-level fusion for mpMRI data, providing a separate network for each multi-parametric series. The first model implements a simple fusion of multi-parametric features to formulate the final decision. The architecture of the second model reflects the diagnostic pathway of PI-RADS methodology, using information about a lesion’s primary anatomic location within the prostate gland. Both networks were experimentally tuned to successfully classify prostate cancer changes. Results The optimised knowledge-encoded model achieved slightly better classification results compared with the traditional model architecture (AUC = 0.84 vs. AUC = 0.82). We found the proposed model to achieve convergence significantly faster. Conclusions The final knowledge-encoded CNN model provided more stable learning performance and faster convergence to optimal diagnostic accuracy. The results fail to demonstrate that PI-RADS-based modelling of CNN architecture can significantly improve performance of prostate cancer recognition using mpMRI.

Background We assessed median nerve travel and deformation concurrently to better understand the influence of occupational risk factors on carpal tunnel dynamics, including forceful chuck gripping and deviated wrist positions. Methods Fourteen healthy right-hand dominant participants performed a chuck grip in 6 experimental conditions: two relative force levels (10% and 40% of maximum voluntary effort); three wrist positions (15° radial deviation, 0° neutral, 30° ulnar deviation). Chuck grip forces were measured with a load cell while the transverse cross-section of the carpal tunnel was imaged via ultrasound at the distal wrist crease. Images of the median nerve were analyzed in ImageJ to assess cross-sectional area, circularity, width, and height as well as travel in the anterior-posterior and medial-lateral axes. Results We found a main effect of deviated wrist position on both anterior-posterior and medial-lateral travel, with the greatest nerve travel occurring in 30° ulnar deviation. There was also a significant interaction between chuck grip force and deviated wrist position on cross-sectional area. Specifically, the area decreased with 40% vs. 10% chuck grip force when the wrist was in 30° ulnar deviation; however, there were no changes in 0° neutral and 15° radial deviation. Discussion Overall, we demonstrated that forceful chuck gripping in deviated wrist positions influenced carpal tunnel dynamics, resulting in both migratory and morphological changes to the median nerve. These changes may, in turn, increase local strain and stress with adjacent structures in the carpal tunnel. Future studies mapping contact stress between structures may further elucidate injury development of work-related carpal tunnel syndrome.

We studied by conventional and speckle-tracking echocardiography, the response of the left ventricle (LV) to a three-week continuous infusion of isoproterenol (Iso), a non-specific beta-adrenergic receptor agonist in male and female C57Bl6/J mice. Before and after Iso (30 mg/kg/day), we characterized LV morphology and function as well as global and segmental strain. We observed that Iso reduced LV ejection in both male (−8.7%) and female (−14.7%) mice. Several diastolic function parameters were negatively regulated in males and females such as E/A, E/E′, isovolumetric relaxation time. Global longitudinal (GLS) and circumferential (GCS) strains were reduced by Iso in both sexes, GLS by 31% and GCS by about 20%. For the segmental LV analysis, we measured strain, strain rate, reverse strain rate, peak speckle displacement and peak speckle velocity in the parasternal long axis. We observed that radial strain of the LV posterior segments were more severely modulated by Iso than those of the anterior wall in males. In females, on the other hand, both posterior and anterior wall segments were negatively impacted by Iso. Longitudinal strain showed similar results to the radial strain for both sexes. Strain rate, on the other hand, was only moderately changed by Iso. Reverse strain rate measurements (an index of diastolic function) showed that posterior LV segments were negatively regulated by Iso. We then studied the animals 5 and 17 weeks after Iso treatment. Compared to control mice, LV dilation was still present in males. Ejection fraction was decreased in mice of both sex compared to control animals. Diastolic function parameters, on the other hand, were back to normal. Taken together, our study indicates that segmental strain analysis can identify LV regions that are more negatively affected by a cardiotoxic agent such as Iso. In addition, cessation of Iso was not accompanied with a complete restoration of cardiac function after four months.

Background The rabbit VX-2 tumor model is a commonly used transplanted tumor model and is widely used in surgical, radiological, and interventional studies. Most of the known tumor models for each site are single solid tumors. This study aimed to establish an accurate and stable intramuscular dual tumor model guided by computed tomography (CT). Methods In this study, we compared three different inoculation methods to select the most appropriate dual tumor model. Six New Zealand White rabbits were used as tumor-carrying rabbits for tumor harvesting. Thirty rabbits were divided into three groups as experimental rabbits. Group A applied the tumor cell suspension method, in which the suspension was injected into the designated location with a syringe under CT guidance. Groups B and C used tumor tissue strips obtained in vivo or under direct in vitro vision. The tumor tissue strips were implanted into the designated locations using a guide needle under CT guidance. The differences in tumorigenic rate, the size difference between bilateral tumors, and metastasis between the three methods were compared. Results It was found that group A obtained a 100% tumor survival rate, but the size of the tumor was more variable, and needle tract implantation metastasis occurred in 5 cases. In group B, tumor tissue strips were taken in vivo for implantation, in which one case failed to survive. Tumor tissue strips in group C were obtained in vitro under direct vision. The tumor tissue strips obtained in vitro by puncture using a biopsy needle in group C had a 100% tumorigenicity rate and stable tumor size. No significant needle tract implantation metastases were found in either group B or C. The variance of tumor size obtained in group A was significantly higher than in groups B and C. The variance of tumor size in group C was the smallest. Group C had high tumorigenicity and a more stable size and morphology of the formed tumors. Conclusion The results showed that the method of obtaining tumor tissue strips using in vitro direct vision puncture and implanting them into the muscle with CT guidance and guide needles can establish an accurate and stable dual tumor model. This dual tumor model can provide substantial support for relevant preclinical studies.

Background The locus coeruleus (LC) is the major noradrenergic source in the central nervous system. Structural alterations in the LC contribute to the pathophysiology of different neuropsychiatric disorders, which may increase to a variable extent the likelihood of developing neurodegenerative conditions. The characterization of such alterations may therefore help to predict progression to neurodegenerative disorders. Despite the LC cannot be visualized with conventional magnetic resonance imaging (MRI), specific MRI sequences have been developed to infer its structural integrity. Methods We quantified LC signal Contrast Ratios (LCCRs) in late-life major depressive disorder (MDD) (n = 37, 9 with comorbid aMCI), amnestic Mild Cognitive Impairment (aMCI) (n = 21, without comorbid MDD), and healthy controls (HCs) (n = 31), and also assessed the putative modulatory effects of comorbidities and other clinical variables. Results LCCRs were lower in MDD compared to aMCI and HCs. While no effects of aMCI comorbidity were observed, lower LCCRs were specifically observed in patients taking serotonin/norepinephrine reuptake inhibitors (SNRIs). Conclusion Our results do not support the hypothesis that lower LCCRs characterize the different clinical groups that may eventually develop a neurodegenerative disorder. Conversely, our results were specifically observed in patients with late-life MDD taking SNRIs. Further research with larger samples is warranted to ascertain whether medication or particular clinical features of patients taking SNRIs are associated with changes in LC neurons.

Background Pain, a major symptom of osteonecrosis of the femoral head (ONFH), is a complex sensory and emotional experience that presents therapeutic challenges. Pain can cause neuroplastic changes at the cortical level, leading to central sensitization and difficulties with curative treatments; however, whether changes in structural and functional plasticity occur in patients with ONFH remains unclear. Methods A total of 23 ONFH inpatients who did not undergo surgery (14 males, nine females; aged 55.61 ± 13.79 years) and 20 controls (12 males, eight females; aged 47.25 ± 19.35 years) were enrolled. Functional indices of the amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and a structural index of tract-based spatial statistics (TBSS) were calculated for each participant. The probability distribution of fiber direction was determined according to the ALFF results. Results ONFH patients demonstrated increased ALFF in the bilateral dorsolateral superior frontal gyrus, right medial superior frontal gyrus, right middle frontal gyrus, and right supplementary motor area. In contrast, ONFH patients showed decreased ReHo in the left superior parietal gyrus and right inferior temporal gyrus. There were no significant differences in TBSS or probabilistic tractography. Conclusion These results indicate cerebral pain processing in ONFH patients. It is advantageous to use functional magnetic resonance imaging to better understand pain pathogenesis and identify new therapeutic targets in ONFH patients.

Previous research has shown the potential value of Bayesian methods in fMRI (functional magnetic resonance imaging) analysis. For instance, the results from Bayes factor-applied second-level fMRI analysis showed a higher hit rate compared with frequentist second-level fMRI analysis, suggesting greater sensitivity. Although the method reported more positives as a result of the higher sensitivity, it was able to maintain a reasonable level of selectivity in term of the false positive rate. Moreover, employment of the multiple comparison correction method to update the default prior distribution significantly improved the performance of Bayesian second-level fMRI analysis. However, previous studies have utilized the default prior distribution and did not consider the nature of each individual study. Thus, in the present study, a method to adjust the Cauchy prior distribution based on a priori information, which can be acquired from the results of relevant previous studies, was proposed and tested. A Cauchy prior distribution was adjusted based on the contrast, noise strength, and proportion of true positives that were estimated from a meta-analysis of relevant previous studies. In the present study, both the simulated images and real contrast images from two previous studies were used to evaluate the performance of the proposed method. The results showed that the employment of the prior adjustment method resulted in improved performance of Bayesian second-level fMRI analysis.

Background Mapping techniques using cardiac magnetic resonance imaging have significantly improved the diagnostic accuracy for myocarditis with focal myocardial injuries. The aim of our study was to determine whether T1 and T2 mapping techniques could identify diffuse myocardial injuries in “normal-appearing” myocardium in pediatric patients with clinically suspected myocarditis and to evaluate the associations between diffuse myocardial injuries and cardiac function parameters. Methods Forty-six subjects were included in this study: 20 acute myocarditis patients, 11 subacute/chronic myocarditis patients and 15 control children. T2 values, native T1 values and the extracellular volume (ECV) of “normal-appearing” myocardium were compared among the three groups of patients. Associations between diffuse myocardial injuries and cardiac function parameters were also evaluated. Results The ECV of “normal-appearing” myocardium was significantly higher in the subacute/chronic myocarditis group than in the control group (30.1 ± 0.9 vs 27.0 ± 0.6, P =0.004). No significant differences in T1 and T2 values between the acute myocarditis and control groups were found. In the subacute/chronic myocarditis group, a significant association between ECV and left ventricle ejection fraction was found (P=0.03). Conclusions Diffuse myocardial injuries are likely to occur in subacute/chronic myocarditis patients with prolonged inflammatory responses. Mapping techniques have great value for the diagnosis and monitoring of myocarditis.

Background Static changes in local brain activity in patients suffering from amyotrophic lateral sclerosis (ALS) have been studied. However, the dynamic characteristics of local brain activity are poorly understood. Whether dynamic alterations could differentiate patients with ALS from healthy controls (HCs) remains unclear. Methods A total of 54 patients with ALS (mean age = 48.71 years, male/female = 36/18) and 54 (mean age = 48.30 years, male/female = 36/18) HCs underwent magnetic resonance imaging scans. To depict static alterations in cortical activity, amplitude of low-frequency fluctuations (ALFF) which measures the total power of regional activity was computed. Dynamic ALFF (d-ALFF) from all subjects was calculated using a sliding-window approach. Statistical differences in ALFF and d-ALFF between both groups were used as features to explore whether they could differentiate ALS from HC through support vector machine method. Results In contrast with HCs, patients with ALS displayed increased ALFF in the right inferior temporal gyrus and bilateral frontal gyrus and decreased ALFF in the left middle occipital gyrus and left precentral gyrus. Furthermore, patients with ALS demonstrated lower d-ALFF in widespread regions, including the right lingual gyrus, left superior temporal gyrus, bilateral precentral gyrus, and left paracentral lobule by comparison with HCs. In addition, the ALFF in the left superior orbitofrontal gyrus had a tendency of correlation with ALSFRS-R score and disease progression rate. The classification performance in distinguishing ALS was higher with both features of ALFF and d-ALFF than that with a single approach. Conclusions Decreased dynamic brain activity in the precentral gyrus, paracentral gyrus, lingual gyrus, and temporal regions was found in the ALS group. The combined ALFF and d-ALFF could distinguish ALS from HCs with a higher accuracy than ALFF and d-ALFF alone. These findings may provide important evidence for understanding the neuropathology underlying ALS.

Stem cells are primitive and precursor cells with the potential to reproduce into diverse mature and functional cell types in the body throughout the developmental stages of life. Their remarkable potential has led to numerous medical discoveries and breakthroughs in science. As a result, stem cell–based therapy has emerged as a new subspecialty in medicine. One promising stem cell being investigated is the induced pluripotent stem cell (iPSC), which is obtained by genetically reprogramming mature cells to convert them into embryonic-like stem cells. These iPSCs are used to study the onset of disease, drug development, and medical therapies. However, functional studies on iPSCs involve the analysis of iPSC-derived colonies through manual identification, which is time-consuming, error-prone, and training-dependent. Thus, an automated instrument for the analysis of iPSC colonies is needed. Recently, artificial intelligence (AI) has emerged as a novel technology to tackle this challenge. In particular, deep learning, a subfield of AI, offers an automated platform for analyzing iPSC colonies and other colony-forming stem cells. Deep learning rectifies data features using a convolutional neural network (CNN), a type of multi-layered neural network that can play an innovative role in image recognition. CNNs are able to distinguish cells with high accuracy based on morphologic and textural changes. Therefore, CNNs have the potential to create a future field of deep learning tasks aimed at solving various challenges in stem cell studies. This review discusses the progress and future of CNNs in stem cell imaging for therapy and research.

Study Objective To assess the adequacy of clinical information with reference to the Ottawa Ankle Rules (OAR) in X-ray referrals for adults with traumatic ankle injury in the ED of a South Australian tertiary hospital and report upon referring trends between emergency department clinicians. Methods A retrospective clinical audit of adult ankle X-ray referrals in the emergency department was conducted. Eligible referrals were screened for their adherence to the OAR, patient details, clinical history and referrer. A logistic regression was used to determine the influence of these factors on the likelihood of being referred for X-rays despite not meeting the OAR criteria. Sensitivity, specificity, positive and negative likelihood ratios and their associated confidence intervals were calculated to assess the diagnostic accuracy of the OAR for those referred. Results Out of the 262 eligible referrals, 163 were deemed to have met the criteria for the OAR. Physiotherapists showed the highest OAR compliance of 77.3% and were the most accurate in their use of the rules, with a sensitivity of 0.86. Medical officers, registrars and interns were 2.5 times more likely to still refer a patient for X-ray if they did not meet the OAR criteria, compared to physiotherapists as the baseline. Patient age, duration of injury etc. were not significantly associated with likelihood of referral (even when they did not meet OAR criteria). The overall sensitivity, specificity, positive and negative likelihood ratios of the OAR were 0.59 (95% CI [0.47–0.71]), 0.37 (95% CI [0.30–0.44]), 0.93 (95% CI [0.76–1.16]) and 1.10 (95% CI [0.82–1.48]) respectively. Conclusion The results of this audit demonstrated poor sensitivity and moderate compliance by referrers with the rule. Reasonable evidence exists for the implementation of individual and/or institutional-based change strategies to improve clinician compliance and accuracy with use of the OAR.

Portable chest X-ray (pCXR) has become an indispensable tool in the management of Coronavirus Disease 2019 (COVID-19) lung infection. This study employed deep-learning convolutional neural networks to classify COVID-19 lung infections on pCXR from normal and related lung infections to potentially enable more timely and accurate diagnosis. This retrospect study employed deep-learning convolutional neural network (CNN) with transfer learning to classify based on pCXRs COVID-19 pneumonia (N = 455) on pCXR from normal (N = 532), bacterial pneumonia (N = 492), and non-COVID viral pneumonia (N = 552). The data was randomly split into 75% training and 25% testing, randomly. A five-fold cross-validation was used for the testing set separately. Performance was evaluated using receiver-operating curve analysis. Comparison was made with CNN operated on the whole pCXR and segmented lungs. CNN accurately classified COVID-19 pCXR from those of normal, bacterial pneumonia, and non-COVID-19 viral pneumonia patients in a multiclass model. The overall sensitivity, specificity, accuracy, and AUC were 0.79, 0.93, and 0.79, 0.85 respectively (whole pCXR), and were 0.91, 0.93, 0.88, and 0.89 (CXR of segmented lung). The performance was generally better using segmented lungs. Heatmaps showed that CNN accurately localized areas of hazy appearance, ground glass opacity and/or consolidation on the pCXR. Deep-learning convolutional neural network with transfer learning accurately classifies COVID-19 on portable chest X-ray against normal, bacterial pneumonia or non-COVID viral pneumonia. This approach has the potential to help radiologists and frontline physicians by providing more timely and accurate diagnosis.

Background The traditional treatment for osteoid osteoma is the nidus’ surgical resection, which was difficult to eradicate with more invasive and complications because of osteosclerosis surrounding the nidus. This study aimed to analyze the efficacy and safety of percutaneous CT-guided cryoablation of osteoid osteoma at different sites (especially refractory sites such as the spine). Methods Fifteen patients with osteoid osteoma who underwent cryoablation at our institution were analyzed retrospectively on their imaging data and clinical visual analog scale (VAS) pain scores before and after the procedure. Fifty-three patients underwent surgical resection during the period were also included in this study as a control group. Treatment efficacy was assessed primarily by comparing the differences in VAS scores at different time points in each group of patients by paired-sample t-test. Differences in length of hospital stay and complications between the two groups were also compared. Results The technical success rate was 100% in both the cryoablation and surgical resection group. Cryoablation had a significantly shorter hospitalization time than surgery (p = 0.001). Clinically, the post-operative VAS scores were all significantly improved compared to the pre-operative period, and the clinical cure was achieved in both groups. Surgical operations had more complications than cryoablation, although there was no significant difference. In the group of cryoablation, only one patient had mild numbness of the left lower extremity, which relieved itself; two patients had mild post-operative pain. No patients in the cryoablation group experienced recurrence during the follow-up period. In the surgery group, three of the patients experienced massive bleeding (>500 ml), and two underwent transfusion therapy. Only one patient in the surgical resection group experienced a recurrence at 29 months postoperatively and underwent a second resection. All patients had local scars on the skin after surgical resection. Conclusion Cryoablation is a minimally invasive, safe, and effective treatment strategy for osteoid osteoma, and is fully comparable to surgical resection.

Background Medical imaging is an important approach for the diagnosis of hepatocellular carcinoma (HCC), a common life threaten disease, however, the diagnostic efficiency is still not optimal. Developing a novel method to improve diagnosis is necessary. The aim of this project was to formulate a material that can combine with GPC3 of HCC for targeted enhanced ultrasound. Methods A material of sulfur hexafluoride (SF6) filled liposome microbubbles and conjugated with synthesized peptide (LSPMbs) was prepared and assessed in vitro and vivo. Liposome microbubbles were made of DPPC, DPPG, DSPE-PEG2000,and SF6, using thin film method to form shell, followed filling SF6, and conjugating peptide. A carbodiimide method was used for covalent conjugation of peptide to LSMbs. Results The prepared LSPMbs appeared round shaped, with size of 380.9 ± 176.5 nm, and Zeta potential of −51.4 ± 10.4mV. LSPMbs showed high affinity to Huh-7 cells in vitro, presented good enhanced ultrasound effects, did not show cytotoxicity, and did not exhibit targeted fluorescence and enhanced ultrasound in animal xenograft tumors. Conclusion Extravascular contrast-enhanced ultrasound targeted GPC3 on HCC may not be realized, and the reason may be that targeted contrast agents of microbubbles are hard to access and accumulate in the tumor stroma and matrix.

Background Radiation exposure of the thorax is associated with a greatly increased risk of cardiac morbidity and mortality even after several decades of advancement in the field. Although many studies have demonstrated the damaging influence of ionizing radiation on cardiac fibroblast (CF) structure and function, myocardial fibrosis, the molecular mechanism behind this damage is not well understood. miR-21, a small microRNA, promotes the activation of CFs, leading to cardiac fibrosis. miR-21 is overexpressed after irradiation; however, the relationship between increased miR-21 and myocardial fibrosis after irradiation is unclear. This study was conducted to investigate gene expression after radiation-induced CF damage and the role of miR-21 in this process in rats. Methods We sequenced irradiated rat CFs and performed weighted correlation network analysis (WGCNA) combined with differentially expressed gene (DEG) analysis to observe the effect on the expression profile of CF genes after radiation. Results DEG analysis showed that the degree of gene changes increased with the radiation dose. WGCNA revealed three module eigengenes (MEs) associated with 8.5-Gy-radiation—the Yellow, Brown, Blue modules. The three module eigengenes were related to apoptosis, G2/M phase, and cell death and S phase, respectively. By blocking with the cardiac fibrosis miRNA miR-21, we found that miR-21 was associated with G2/M blockade in the cell cycle and was mainly involved in regulating extracellular matrix-related genes, including Grem1, Clu, Gdf15, Ccl7, and Cxcl1. Stem-loop quantitative real-time PCR was performed to verify the expression of these genes. Five genes showed higher expression after 8.5 Gy-radiation in CFs. The target genes of miR-21 predicted online were Gdf15 and Rsad2, which showed much higher expression after treatment with antagomir-miR-21 in 8.5-Gy-irradiated CFs. Thus, miR-21 may play the role of fibrosis and G2/M blockade in regulating Grem1, Clu, Gdf15, Ccl7, Cxcl1, and Rsad2 post-irradiation.

Objectives The objective of this study was to compare maxillary dimensions and growth in newborns with Complete Unilateral Cleft Lip and Palate (UCLP) to healthy newborns before and after cheiloplasty. Additionally, a palatal growth curve is constructed to give more information about the natural growth before surgical intervention. Methods Twenty-eight newborns with complete UCLP were enrolled in this study. Multiple plaster-casts of each child during their first year were collected and grouped in before and after cheiloplasty. A previous developed semi-automatic segmentation tool was used to assess the maxillary dimensions and were compared to a healthy control group. Z-scores were calculated to indicate differences between the two populations and if cheiloplasty had influence on maxillary growth. Furthermore, the prediction model created in a previous study was used to indicate differences between predictions and the outcome in UCLP measurements. The analysis was tested for inter- and intra-observer variability. Results Results show differences in alveolar and palatal shape in UCLP patients in comparison with healthy controls. Prior to cheiloplasty an increased width and alveolar length was observed while the palatal depth was decreased. After cheiloplasty the widths moved towards normal but were still significantly larger. Conclusion Infants with unilateral cleft lip and palate show a wider maxillary arch in comparison with the control population. Initial treatment has most influence on the width of the arch, which decreased towards normal.

BackgroundMalocclusion characteristics vary across different ethnic groups and populations. Limited data are available regarding the characteristics of Syrian adolescents with Class II division 1 (Class II-1) malocclusion, and the recent inflow of Syrian refugees and immigrants into Europe and many areas worldwide demonstrate the need for updated studies to discover the craniofacial characteristics of these new immigrants.ObjectivesThe present compound cephalometric and tooth-size study sought to assess the dentofacial morphology, upper-airway dimensions, and tooth-size characteristics of Syrian adolescents with Class II-1 malocclusion and compare the results with established Syrian population norms.Materials and MethodsThe study sample consisted of 43 Syrian patients including 24 females and 19 males with Class II-1 malocclusion (age: 14.3 (±1.5) years, mean (±SD)). Cephalometric radiographs and orthodontic casts were analyzed using special orthodontic software (OnyxCeph3™) and a universal digital caliper, respectively. Statistics were calculated using the SPSS software.ResultsIn Syrian adolescents with Class II-1 malocclusion, the position of the mandible relative to the nasion perpendicular (mean (95% confidence interval)) was −11.01 (−12.45, −9.57) mm. Facial axis angle showed a negative value: −6.25 (−7.65, −4.85) degrees. An obtuse nasolabial angle was observed: 104.05 (101.77, 106.33) degrees. The average width of the upper pharynx was 11.50 (10.53, 12.47) mm; however, there was no prevalence of an upper-pharyngeal width of 5 mm or less. The average value of the anterior tooth-size ratio was 80.69 (79.85, 81.53) percent. In total, 39.5% of the investigated subjects had anterior ratios outside two standard deviations from Bolton’s norm, while 25.6% of the investigated subjects had anterior ratios outside two standard deviations from Syrian population norm.ConclusionsIn this study, the inter-maxillary discrepancy of Class II-1 Syrian adolescents was a consequence of their hyperdivergent facial pattern. The observed small pharyngeal widths were not clinically significant, while the anterior tooth-size discrepancy might be clinically relevant.

Background Biomarkers of neurodegeneration, e.g. MRI brain atrophy and [18F]FDG-PET hypometabolism, are often evaluated in patients suspected of neurodegenerative disease. Objective Our primary objective was to investigate prognostic properties of atrophy and hypometabolism. Methods From March 2015-June 2016, 149 patients referred to a university hospital memory clinic were included. The primary outcome was progression/stable disease course as assessed by a clinician at 12 months follow-up. Intracohort defined z-scores of baseline MRI automatic quantified volume and [18F]FDG-PET standardized uptake value ratios were calculated for all unilaterally defined brain lobes and dichotomized as pronounced atrophy (+A)/ pronounced hypometabolism (+H) at z-score z-score dichotomization at −0.1 and −0.5 and dichotomization regarding number of lobes affected at one and three lobes was done. Results Median follow-up time was 420 days [IQR: 387-461 days] and 50 patients progressed. Patients with two or more lobes affected by the pattern +A/+H compared to patients with 0–1 lobes affected had a statistically significant increased risk of progression (odds ratio, 95 % confidence interval: 4.33, 1.90–9.86) in a multivariable model. The model was partially robust to the applied sensitivity analysis. Conclusion Combined atrophy and hypometabolism as assessed by MRI and [18F]FDG-PET in patients under suspicion of neurodegenerative disease predicts progression over 1 year.

Noncontrast Computed Tomography (NCCT) of the brain has been the first-line diagnosis for emergency evaluation of acute stroke, so a rapid and automated detection, localization, and/or segmentation of ischemic lesions is of great importance. We provide the state-of-the-art review of methods for automated detection, localization, and/or segmentation of ischemic lesions on NCCT in human brain scans along with their comparison, evaluation, and classification. Twenty-two methods are (1) reviewed and evaluated; (2) grouped into image processing and analysis-based methods (11 methods), brain atlas-based methods (two methods), intensity template-based methods (1 method), Stroke Imaging Marker-based methods (two methods), and Artificial Intelligence-based methods (six methods); and (3) properties of these groups of methods are characterized. A new method classification scheme is proposed as a 2 × 2 matrix with local versus global processing and analysis, and density versus spatial sampling. Future studies are necessary to develop more efficient methods directed toward deep learning methods as well as combining the global methods with a high sampling both in space and density for the merged radiologic and neurologic data.

Background B-mode ultrasound is one of the most commonly used imaging techniques for evaluating thyroid nodules due to its noninvasive property and excellent performance in terms of discriminating between benign and malignant nodules. However, the accuracy of differential diagnosis strongly depends on the experience of ultrasonographers. In addition to B-mode ultrasound, the elastic mode and contrast-enhanced mode have shown complimentary value in the diagnosis of thyroid nodules. The combination of multiple modes in ultrasonic techniques may effectively undermine diagnostic subjectiveness and improve accuracy. In this study, we evaluated the diagnostic value of combining the three ultrasonic modes for differentiating thyroid cancers. Methods In this retrospective study, we analyzed a total of 196 thyroid nodules with suspected malignancies from 185 patients who gave informed consent. Xi’an Jiaotong University granted ethical approval (No. 2018200) to carry out the study within its facilities. All the patients received ultrasonic examinations with the B mode, elastic mode and contrast-enhanced mode, followed by histopathological confirmation by fine-need aspiration or surgery. A predictive multivariate logistic regression model was selected to integrate the variety of data obtained from the three modes. Results The combination of three ultrasonic techniques for differentiating malignant from benign thyroid nodules showed the highest diagnostic accuracy of 0.985 compared to the B mode alone (0.841) and the two-mode combination. The accuracy of the B mode combined with the elastic technique was 0.954, and the accuracy of the B mode combined with the contrast-enhanced technique was 0.960. Discussion Multimode ultrasonic techniques should be recommended to patients with suspected malignant thyroid nodules in routine clinical practice.

Background: A better understanding of the neural changes associated with paresis in stroke patients could have important implications for therapeutic approaches. Dynamic Causal Modeling (DCM) for functional magnetic resonance imaging (fMRI) is commonly used for analyzing effective connectivity patterns of brain networks due to its significant property of modeling neural states behind fMRI signals. We applied this technique to analyze the differences between motor networks (MNW) activated by continuous passive movement (CPM) of paretic and non-paretic ankles in subacute stroke patients. This study aimed to identify CPM induced connectivity characteristics of the primary sensory area (S1) and the differences in extrinsic directed connections of the MNW and to explain the hemodynamic differences of brain regions of MNW. Methods: For the network analysis, we used ten stroke patients’ task fMRI data collected under CPMs of both ankles. Regions for the MNW, the primary motor cortex (M1), the premotor cortex (PM), the supplementary motor area (SMA) and the S1 were defined in a data-driven way, by independent component analysis. For the network analysis of both CPMs, we compared twelve models organized into two model-families, depending on the S1 connections and input stimulus modeling. Using DCM, we evaluated the extrinsic connectivity strengths and hemodynamic parameters of both stimulations of all patients. Results: After a statistical comparison of the extrinsic connections and their modulations of the “best model”, we concluded that three contralateral self-inhibitions (cM1, cS1 and cSMA), one contralateral inter-regional connection (cSMA→cM1), and one interhemispheric connection (cM1→iM1) were significantly different. Our research shows that hemodynamic parameters can be estimated with the Balloon model using DCM but the parameters do not change with stroke. Conclusions: Our results confirm that the DCM-based connectivity analyses combined with Bayesian model selection may be a useful technique for quantifying the alteration or differences in the characteristics of the motor network in subacute stage stroke patients and in determining the degree of MNW changes. CA extern

Objective Bone age (BA) is a crucial indicator for revealing the growth and development of children. This study tested the performance of a fully automated artificial intelligence (AI) system for BA assessment of Chinese children with abnormal growth and development. Materials and Methods A fully automated AI system based on the Greulich and Pyle (GP) method was developed for Chinese children by using 8,000 BA radiographs from five medical centers nationwide in China. Then, a total of 745 cases (360 boys and 385 girls) with abnormal growth and development from another tertiary medical center of north China were consecutively collected between January and October 2018 to test the system. The reference standard was defined as the result interpreted by two experienced reviewers (a radiologist with 10 years and an endocrinologist with 15 years of experience in BA reading) through consensus using the GP atlas. BA accuracy within 1 year, root mean square error (RMSE), mean absolute difference (MAD), and 95% limits of agreement according to the Bland-Altman plot were statistically calculated. Results For Chinese pediatric patients with abnormal growth and development, the accuracy of this new automated AI system within 1 year was 84.60% as compared to the reference standard, with the highest percentage of 89.45% in the 12- to 18-year group. The RMSE, MAD, and 95% limits of agreement of the AI system were 0.76 years, 0.58 years, and −1.547 to 1.428, respectively, according to the Bland-Altman plot. The largest difference between the AI and experts’ BA result was noted for patients of short stature with bone deformities, severe osteomalacia, or different rates of maturation of the carpals and phalanges. Conclusions The developed automated AI system could achieve comparable BA results to experienced reviewers for Chinese children with abnormal growth and development.

Convolutional neural networks (CNNs) trained on natural images are extremely successful in image classification and localization due to superior automated feature extraction capability. In extending their use to biomedical recognition tasks, it is important to note that visual features of medical images tend to be uniquely different than natural images. There are advantages offered through training these networks on large scale medical common modality image collections pertaining to the recognition task. Further, improved generalization in transferring knowledge across similar tasks is possible when the models are trained to learn modality-specific features and then suitably repurposed for the target task. In this study, we propose modality-specific ensemble learning toward improving abnormality detection in chest X-rays (CXRs). CNN models are trained on a large-scale CXR collection to learn modality-specific features and then repurposed for detecting and localizing abnormalities. Model predictions are combined using different ensemble strategies toward reducing prediction variance and sensitivity to the training data while improving overall performance and generalization. Class-selective relevance mapping (CRM) is used to visualize the learned behavior of the individual models and their ensembles. It localizes discriminative regions of interest (ROIs) showing abnormal regions and offers an improved explanation of model predictions. It was observed that the model ensembles demonstrate superior localization performance in terms of Intersection of Union (IoU) and mean Average Precision (mAP) metrics than any individual constituent model.

Purpose One of the main pathophysiological mechanisms of chronic obstructive pulmonary disease is inflammation, which has been associated with lymphadenopathy. Intrapulmonary lymph nodes can be identified on CT as perifissural nodules (PFN). We investigated the association between the number and size of PFNs and measures of COPD severity. Materials and Methods CT images were obtained from COPDGene. 50 subjects were randomly selected per GOLD stage (0 to 4), GOLD-unclassified, and never-smoker groups and allocated to either “Healthy,” “Mild,” or “Moderate/severe” groups. 26/350 (7.4%) subjects had missing images and were excluded. Supported by computer-aided detection, a trained researcher prelocated non-calcified opacities larger than 3 mm in diameter. Included lung opacities were classified independently by two radiologists as either “PFN,” “not a PFN,” “calcified,” or “not a nodule”; disagreements were arbitrated by a third radiologist. Ordinal logistic regression was performed as the main statistical test. Results A total of 592 opacities were included in the observer study. A total of 163/592 classifications (27.5%) required arbitration. A total of 17/592 opacities (2.9%) were excluded from the analysis because they were not considered nodular, were calcified, or all three radiologists disagreed. A total of 366/575 accepted nodules (63.7%) were considered PFNs. A maximum of 10 PFNs were found in one image; 154/324 (47.5%) contained no PFNs. The number of PFNs per subject did not differ between COPD severity groups (p = 0.50). PFN short-axis diameter could significantly distinguish between the Mild and Moderate/severe groups, but not between the Healthy and Mild groups (p = 0.021). Conclusions There is no relationship between PFN count and COPD severity. There may be a weak trend of larger intrapulmonary lymph nodes among patients with more advanced stages of COPD.

Objectives Remote photoplethysmography (rPPG) is a promising non-contact measurement technique for assessing numerous physiological parameters: pulse rate, pulse rate variability (PRV), respiratory rate, pulse wave velocity, blood saturation, blood pressure, etc. To justify its use in ultra-short-term (UST) PRV analysis, which is of great benefit for several healthcare applications, the agreement between rPPG- and PPG-derived UST-PRV metrics was studied. Approach Three time-domain metrics—standard deviation of normal-to-normal (NN) intervals (SDNN), root mean square of successive NN interval differences (RMSSD), and the percentage of adjacent NN intervals that differ from each other by more than 50 ms (pNN50)—were extracted from 56 video recordings in a publicly available data set. The selected metrics were calculated on the basis of three groups of 10 s recordings and their average, two groups of 30 s recordings and their average, and a group of 60 s recordings taken from the full-length recordings and then compared with metrics derived from the corresponding reference (PPG) pulse waveform signals by using correlation and effect size parameters, and Bland–Altman plots. Main results The results show there is stronger agreement as the recording length increases for SDNN and RMSSD, yet there is no significant change for pNN50. The agreement parameters reach r = 0.841 (p < 0.001), r = 0.529 (p < 0.001), and r = 0.657 (p < 0.001), estimated median bias −1.52, −2.28 ms and −1.95% and a small effect size for SDNN, RMSSD, and pNN50 derived from the 60 s recordings, respectively. Significance Remote photoplethysmography-derived UST-PRV metrics manage to capture UST-PRV metrics derived from reference (PPG) recordings well. This feature is highly desirable in numerous applications for the assessment of one’s health and well-being. In future research, the validity of rPPG-derived UST-PRV metrics compared to the gold standard electrocardiography recordings is to be assessed.

Background Altered cerebral blood flow (CBF) and amplitude of low-frequency fluctuation (ALFF) have been reported in hemodialysis patients. However, neurovascular coupling impairments, which provide a novel insight into the human brain, have not been reported in hemodialysis patients. Methods We combined arterial spin labeling (ASL) and blood oxygen level dependent (BOLD) techniques to investigate neurovascular coupling alterations and its relationships with demographic and clinical data in 46 hemodialysis patients and 47 healthy controls. To explore regional neuronal activity, ALFF was obtained from resting-state functional MRI. To measure cerebral vascular response, CBF was calculated from ASL. The across-voxel CBF–ALFF correlations for global neurovascular coupling and CBF/ALFF ratio for regional neurovascular coupling were compared between hemodialysis patients and healthy controls. Two-sample t-tests were used to compare the intergroup differences in CBF and ALFF. Multiple comparisons were corrected using a voxel-wise false discovery rate (FDR) method (P < 0.05). Results All hemodialysis patients and healthy controls showed significant across-voxel correlations between CBF and ALFF. Hemodialysis patients showed a significantly reduced global CBF–ALFF coupling (P = 0.0011) compared to healthy controls at the voxel-level. Of note, decreased CBF/ALFF ratio was exclusively located in the bilateral amygdala involved in emotional regulation and cognitive processing in hemodialysis patients. In hemodialysis patients, the decreased CBF (right olfactory cortex, anterior cingulate gyrus and bilateral insula) and ALFF (bilateral precuneus and superior frontal gyrus) were mainly located in the default mode network and salience network-related regions as well as increased CBF in the bilateral thalamus. Conclusions These novel findings reveal that disrupted neurovascular coupling may be a potential neural mechanism in hemodialysis patients.

Purpose To investigate whether multi-view convolutional neural networks can improve a fully automated lymph node detection system for pelvic MR Lymphography (MRL) images of patients with prostate cancer. Methods A fully automated computer-aided detection (CAD) system had been previously developed to detect lymph nodes in MRL studies. The CAD system was extended with three types of 2D multi-view convolutional neural networks (CNN) aiming to reduce false positives (FP). A 2D multi-view CNN is an efficient approximation of a 3D CNN, and three types were evaluated: a 1-view, 3-view, and 9-view 2D CNN. The three deep learning CNN architectures were trained and configured on retrospective data of 240 prostate cancer patients that received MRL images as the standard of care between January 2008 and April 2010. The MRL used ferumoxtran-10 as a contrast agent and comprised at least two imaging sequences: a 3D T1-weighted and a 3D T2*-weighted sequence. A total of 5089 lymph nodes were annotated by two expert readers, reading in consensus. A first experiment compared the performance with and without CNNs and a second experiment compared the individual contribution of the 1-view, 3-view, or 9-view architecture to the performance. The performances were visually compared using free-receiver operating characteristic (FROC) analysis and statistically compared using partial area under the FROC curve analysis. Training and analysis were performed using bootstrapped FROC and 5-fold cross-validation. Results Adding multi-view CNNs significantly (p p Conclusion Multi-view convolutional neural networks significantly reduce false positives in a lymph node detection system for MRL images, and three orthogonal views are sufficient. At the achieved level of performance, CAD for MRL may help speed up finding lymph nodes and assessing them for potential metastatic involvement.

Background Measuring the thickness of the palatal mucosa at the planning of the surgical procedure is an important step in order to obtain the maximum width and thickness of the graft from the appropriate area. The aim of this study is to determine whether there is a relationship between palatal angle (PA) or palatal depth (PD) and palatal mucosa thickness (PMT) or palatal neurovascular bundle distance (PNBD). Methods PMT, PNBD, PD and PA were measured on cone-beam computed tomography (CBCT) images of maxillary posterior region of 200 male and 200 female patients. The mean of all parameters according to gender was compared and the significance of the difference detected between groups was evaluated. Potential relationship between PMT or PNBD and PA or PD was also evaluated. Results In females, the palatal mucosa was significantly thinner at all tooth regions (p p p ≤ 0.001). Discussion Consistent with previous studies, it was observed that the thickest mucosa in the palatal region was located in the region of the premolar teeth, and women had thinner palatal mucosa. In addition, in patients with a deeper palate vault, the palatal mucosa was thinner, but the palatal neurovascular bundle was more distant from the cemento-enamel junction.

Background To provide insight into bone turnover, quantitative measurements of bone remodeling are required. Radionuclide studies are widely used in clinical care, but have been rarely used in the exploration of the bone in preclinical studies. We describe a bone planar scintigraphy method for frequent assessment of bone activity in mice across the growing period. Since repeated venous radiotracer injections are hardly feasible in mice, we investigated the subcutaneous route. Methods Repeated 99mTc-hydroxymethylene diphosphonate (HMDP) tracer bone planar scintigraphy studies of the knee region and µCT to measure femur growth rate were performed in eight mice between week 6 and week 27 of life, i.e., during their growth period. Three independent investigators assessed the regions of interest (ROI). An index was calculated based on the counts in knees ROI (normalized by pixels and seconds), corrected for the activity administered, the decay between administration and imaging, and individual weights. Results A total of 93 scintigraphy studies and 85 µCT were performed. Repeated subcutaneous tracer injections were well tolerated and allowed for adequate radionuclide studies. Mean scintigraphic indexes in the knees ROI decreased from 87.4 ± 2.6 × 10−6 counts s−1 pixel−1 MBq−1 g−1 at week 6 to 15.0 ± 3.3 × 10−6 counts s−1 pixel−1 MBq−1 g−1 at week 27. The time constant of the fitted exponential decay was equal to 23.5 days. As control mean femur length assessed by µCT increased from 12.2 ± 0.8 mm at week 6 to 15.8 ± 0.2 mm at week 22. The time constant of the fitted Gompertz law was equal to 26.7 days. A correlation index of −0.97 was found between femur growth and decrease of bone tracer activity count between week 6 and 24. Conclusion This methodological study demonstrates the potential of repeated bone planar scintigraphy in growing mice, with subcutaneous route for tracer administration, for quantitative assessment of bone remodeling.

Background Postoperative pulmonary complications (PPCs) after thoracoscopic surgery are common. This retrospective study aimed to develop a nomogram to predict PPCs in thoracoscopic surgery. Methods A total of 905 patients who underwent thoracoscopy were randomly enrolled and divided into a training cohort and a validation cohort at 80%:20%. The training cohort was used to develop a nomogram model, and the validation cohort was used to validate the model. Univariate and multivariable logistic regression were applied to screen risk factors for PPCs, and the nomogram was incorporated in the training cohort. The discriminative ability and calibration of the nomogram for predicting PPCs were assessed using C-indices and calibration plots. Results Among the patients, 207 (22.87%) presented PPCs, including 166 cases in the training cohort and 41 cases in the validation cohort. Using backward stepwise selection of clinically important variables with the Akaike information criterion (AIC) in the training cohort, the following seven variables were incorporated for predicting PPCs: American Society of Anesthesiologists (ASA) grade III/IV, operation time longer than 180 min, one-lung ventilation time longer than 60 min, and history of stroke, heart disease, chronic obstructive pulmonary disease (COPD) and smoking. With incorporation of these factors, the nomogram achieved good C-indices of 0.894 (95% confidence interval (CI) [0.866–0.921]) and 0.868 (95% CI [0.811–0.925]) in the training and validation cohorts, respectively, with well-fitted calibration curves. Conclusion The nomogram offers good predictive performance for PPCs after thoracoscopic surgery. This model may help distinguish the risk of PPCs and make reasonable treatment choices.

Background This work aimed to explore the association of cerebral microvascular perfusion and diffusion dynamics measured by intravoxel incoherent motion (IVIM) imaging with initial neurological function and clinical outcome in acute stroke. Methods In total, 39 patients were assessed with admission National Institutes of Health Stroke Scale (NIHSS) and day-90 modified Rankin Scale (mRS). The parametrical maps of IVIM were obtained, including apparent diffusion coefficient (ADC), pseudo-diffusion coefficient (D*), true diffusion coefficient (D) and perfusion fraction (f). The fD* was the product of f and D*. Moreover, the ratios of lesioned/contralateral parameters (rADC, rD, rD*, rf and rfD*) were also obtained. The differences of these parameters between the poor outcome group and good outcome group were evaluated. Partial correlation analysis was used to evaluate the correlations between the admission NIHSS/day-90 mRS and each parameter ratio, with lesion volumes controlled. Results The ADC, D, D*, f and fD* values of lesions were significantly reduced than those of the contralateral regions. The rADC and rD were significantly decreased in the poor outcome group than good outcome group (all p < 0.01). With lesion volume controlled, rADC showed a weak negative correlation (r = −0.340, p = 0.037) and a notable negative correlation (r = −0.688, p < 0.001) with admission NIHSS score and day-90 mRS score, respectively. In addition, rD showed a strong negative correlation (r = −0.731, p < 0.001) with day-90 mRS score. Conclusion Significant negative correlations were revealed between IVIM derived diffusion dynamics parameters and initial neurological function as well as clinical outcome for patients with acute ischemic stroke. IVIM can be therefore suggested as an effective non-invasive method for evaluating the acute ischemic stroke.

Objective To investigate the effect of resin infiltrant on resistance of sound permanent enamel surfaces to demineralization. Method Eighty healthy premolars were sectioned to obtain enamel blocks from the buccal surface. Specimens with baseline surface microhardness values of 320–370 were selected. The experimental group were treated with resin infiltrant, while the control group was not. Specimens from each group were artificially demineralized and the surface microhardness values were measured again. Confocal laser scanning microscopy was used to measure the depth of demineralization and detect the penetration ability of the resin infiltrant. The specimens were subjected to a simulated toothbrushing abrasion test. Scanning electron microscopy was used to observe changes in the surface morphology of specimens after each of these procedures. Results No significant differences between the experimental and control groups were observed in the baseline microhardness values or in the experimental group after resin infiltration compared with the baseline conditions. After artificial demineralization, the microhardness value in the control group was significantly lower than that in the experimental group (266.0 (±34.5) compared with 304.0 (±13.0), P = 0.017). Confocal laser scanning microscopy results showed that the demineralization depth in the control group was significantly deeper than that in the experimental group (97.9 (±22.8) µm vs. 50.4 (±14.3) µm, P < 0.001), and that resin infiltrant completely penetrated the acid-etched demineralized area of the tooth enamel with a mean penetration depth of 31.6 (±9.0) µm. Scanning electron microscopy showed that the surface morphology was more uniform and smoother after simulated toothbrushing. The enamel surface structure was more severely destroyed in the control group after artificial demineralization compared with that of the experimental group. Conclusion Resin infiltrant can completely penetrate an acid-etched demineralized enamel area and improve resistance of sound enamel surfaces to demineralization. Our findings provide an experimental basis for preventive application of resin infiltrant to sound enamel surfaces to protect tooth enamel against demineralization.

Background The aim of this study was to detect the optimal values for Age, Body Mass Index (BMI) and HOMA-IR of obese patients prior to surgery that results in a maximal decrease of visceral fat mass 6 months after bariatric surgery. Method In this study, 33 experimental set-ups were designed. This study was approved by Baskent University Medical and Health Sciences Research Board (Approval number: KA16/281). The study data consisted of 40 obese patients who lost weight through the bariatric surgery between February 2015 and December 2016. The values of BMI, Age and HOMA for the obese patients who lost weight through the bariatric surgery were evaluated in three categories and at three levels; the response variable was determined as the Change in Epicardial Fat Thickness (ΔEFT). Results As a result of CCD analysis, the optimum ΔEFT = 2.571 was determined when Age = 30.52, BMI = 45.30, and HOMA = 34.62. As a result of the BBD analysis, the optimum ΔEFT = 3.756 was determined, when Age = 38.36, BMI = 63.18, and HOMA = 14.95. The optimum ΔEFT was modeled with Contour and Response Surface plots. Conclusion Based on the two surface response models used in our study, the maximal decrease of visceral fat mass as assessed by measuring echography images of epicardial fat thickness can be obtained by bariatric surgery of persons who are between 31 and 38 year old, have a BMI between 45 and 63 kg/m2 and have a HOMA-IR 34 between 15 and 35. Central Composite Design and a Box-Behnken Design of suitable patient data predicted 35 optimal settings of independent variables for the maximal clinical response of an intervention.