Multisource Differential Fusion Driven Monocular Endoscope Hybrid 3-D Tracking for Advanced Endoscopic Navigation Surgery.

Surgical navigation systems involve various technologies of segmentation, calibration, registration, tracking, and visualization. These systems aim to superimpose multisource information in the surgical field and provide surgeons with a composite overlay (augmented-reality) view, improving the operative precision and experience. Surgical 3-D tracking is the key to build these systems. Unfortunately, surgical 3-D tracking is still a challenge to endoscopic and robotic navigation systems and easily gets trapped in image artifacts, tissue deformation, and inaccurate positional (e.g., electromagnetic) sensor measurements. This work explores a new monocular endoscope hybrid 3-D tracking method called spatially constrained adaptive differential evolution that combines two spatial constraints with observation-recall adaptive propagation and observation-based fitness computing for stochastic optimization. Specifically, we spatially constraint inaccurate electromagnetic sensor measurements to the centerline of anatomical tubular structures to keep them physically locating inside the tubes, as well as interpolate these measurements to reduce jitter errors for smooth 3-D tracking. We then propose observation-recall adaptive propagation with fitness computing to precisely fuse the constrained sensor measurements, preoperative images, and endoscopic video sequences for accurate hybrid 3-D tracking. Additionally, we also propose a new marker-free hybrid registration strategy to precisely align positional sensor measurements to preoperative images. Our new framework was evaluated on a large amount of clinical data acquired from various surgical endoscopic procedures, with the experimental results showing that it certainly outperforms current surgical 3-D approaches. In particular, the position and rotation errors were significantly reduced from (6.55, 11.4) to (3.02 mm, 8.54 °).

Competitive Swarm Optimized SVD Clutter Filtering for Ultrafast Power Doppler Imaging.

Ultrafast power Doppler imaging (uPDI) can significantly increase the sensitivity of resolving small vascular paths in ultrasound. While clutter filtering is a fundamental and essential method to realize uPDI, it commonly uses singular value decomposition (SVD) to suppress clutter signals and noise. However, current SVD-based clutter filters using two cutoffs cannot ensure sufficient separation of tissue, blood, and noise in uPDI. This article proposes a new competitive swarm-optimized SVD clutter filter to improve the quality of uPDI. Specifically, without using two cutoffs, such a new filter introduces competitive swarm optimization (CSO) to search for the counterparts of blood signals in each singular value. We validate the CSO-SVD clutter filter on public in vivo datasets. The experimental results demonstrate that our method can achieve higher contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR), and blood-to-clutter ratio (BCR) than the state-of-the-art SVD-based clutter filters, showing a better balance between suppressing clutter signals and preserving blood signals. Particularly, our CSO-SVD clutter filter improves CNR by 0.99 ± 0.08 dB, SNR by 0.79 ± 0.08 dB, and BCR by 1.95 ± 0.03 dB when comparing a spatial-similarity-based SVD clutter filter in the in vivo dataset of rat brain bolus.

Monocular endoscope 6-DoF tracking with constrained evolutionary stochastic filtering.

Monocular endoscopic 6-DoF camera tracking plays a vital role in surgical navigation that involves multimodal images to build augmented or virtual reality surgery. Such a 6-DoF camera tracking generally can be formulated as a nonlinear optimization problem. To resolve this nonlinear problem, this work proposes a new pipeline of constrained evolutionary stochastic filtering that originally introduces spatial constraints and evolutionary stochastic diffusion to deal with particle degeneracy and impoverishment in current stochastic filtering methods. With its application to endoscope 6-DoF tracking and validation on clinical data including more than 59,000 endoscopic video frames acquired from various surgical procedures, the experimental results demonstrate the effectiveness of the new pipeline that works much better than state-of-the-art tracking methods. In particular, it can significantly improve the accuracy of current monocular endoscope tracking approaches from (4.83 mm, 10.2∘) to (2.78 mm, 7.44∘).

Doppler and Pair-Wise Optical Flow Constrained 3D Motion Compensation for 3D Ultrasound Imaging.

Volumetric (3D) ultrasound imaging using a 2D matrix array probe is increasingly developed for various clinical procedures. However, 3D ultrasound imaging suffers from motion artifacts due to tissue motions and a relatively low frame rate. Current Doppler-based motion compensation (MoCo) methods only allow 1D compensation in the in-range dimension. In this work, we propose a new 3D-MoCo framework that combines 3D velocity field estimation and a two-step compensation strategy for 3D diverging wave compounding imaging. Specifically, our framework explores two constraints of a round-trip scan sequence of 3D diverging waves, i.e., Doppler and pair-wise optical flow, to formulate the estimation of the 3D velocity fields as a global optimization problem, which is further regularized by the divergence-free and first-order smoothness. The two-step compensation strategy is to first compensate for the 1D displacements in the in-range dimension and then the 2D displacements in the two mutually orthogonal cross-range dimensions. Systematical in-silico experiments were conducted to validate the effectiveness of our proposed 3D-MoCo method. The results demonstrate that our 3D-MoCo method achieves higher image contrast, higher structural similarity, and better speckle patterns than the corresponding 1D-MoCo method. Particularly, the 2D cross-range compensation is effective for fully recovering image quality.

Reamed versus unreamed intramedullary nailing for the treatment of femoral shaft fractures among adults: A meta-analysis of randomized controlled trials.

BACKGROUND: The purpose of this meta-analysis is to compare the merits and drawbacks between reamed intramedullary nailing (RIN) and unreamed intramedullary nailing (URIN) among adults. METHODS: We comprehensively searched PubMed, MEDLINE database through the PubMed search engine, Google Scholar, Cochrane Library, Embase, VIPI (Database for Chinese Technical Periodicals), and CNKI (China National Knowledge Infrastructure) from inception to March 2020. Outcomes of interest included nonunion rates, implant failure rates, secondary procedure rates, blood loss, acute respiratory distress syndrome (ARDS) rates, and pulmonary complications rates. RESULTS: Eight randomized controlled trials were included. The result of nonunion rates shows that the nonunion rate is significantly lower in the RIN group (RR = 0.20, 95% CI = 0.09-0.48, Z = 3.63, P = 0.0003). There were no significant differences for the risk of implant failure rates (RR = 0.55, 95% CI = 0.18-1.69, Z = 1.04, P = 0.30). The secondary procedure rates were significantly lower in the RIN group (RR = 0.28, 95% CI = 0.12-0.66, Z = 2.91, P = 0.004). The result shows that the blood loss of URIN group is significantly lower (RR = 145.52, 95% CI = 39.68-251.36, Z = 2.69, P = 0.007). The result shows that there was no significant difference in the ARDS rates (RR = 1.53, 95% CI = 0.37-6.29, Z = 0.59, P = 0.55) and the pulmonary complications rates between RIN group and URIN group (RR = 1.59, 95% CI = 0.61-4.17, Z = 0.94, P = 0.35). CONCLUSIONS: Reamed intramedullary nailing would lead to lower nonunion rate, secondary procedure rate and more blood loss. Unreamed intramedullary nailing is related to a higher nonunion rate, secondary procedure rate and less blood loss. No significant difference is found in implant failure rate, ARDS rate and pulmonary complication rate between the two groups.

DDA-Net: Unsupervised cross-modality medical image segmentation via dual domain adaptation.

BACKGROUND AND OBJECTIVE: Deep convolutional networks are powerful tools for single-modality medical image segmentation, whereas generally require semantic labelling or annotation that is laborious and time-consuming. However, domain shift among various modalities critically deteriorates the performance of deep convolutional networks if only trained by single-modality labelling data. METHODS: In this paper, we propose an end-to-end unsupervised cross-modality segmentation network, DDA-Net, for accurate medical image segmentation without semantic annotation or labelling on the target domain. To close the domain gap, different images with domain shift are mapped into a shared domain-invariant representation space. In addition, spatial position information, which benefits the spatial structure consistency for semantic information, is preserved by an introduced cross-modality auto-encoder. RESULTS: We validated the proposed DDA-Net method on cross-modality medical image datasets of brain images and heart images. The experimental results show that DDA-Net effectively alleviates domain shift and suppresses model degradation. CONCLUSIONS: The proposed DDA-Net successfully closes the domain gap between different modalities of medical image, and achieves state-of-the-art performance in cross-modality medical image segmentation. It also can be generalized for other semi-supervised or unsupervised segmentation tasks in some other field.

Deep learning driven colorectal lesion detection in gastrointestinal endoscopic and pathological imaging.

Colorectal cancer has the second highest incidence of malignant tumors and is the fourth leading cause of cancer deaths in China. Early diagnosis and treatment of colorectal cancer will lead to an improvement in the 5-year survival rate, which will reduce medical costs. The current diagnostic methods for early colorectal cancer include excreta, blood, endoscopy, and computer-aided endoscopy. In this paper, research on image analysis and prediction of colorectal cancer lesions based on deep learning is reviewed with the goal of providing a reference for the early diagnosis of colorectal cancer lesions by combining computer technology, 3D modeling, 5G remote technology, endoscopic robot technology, and surgical navigation technology. The findings will supplement the research and provide insights to improve the cure rate and reduce the mortality of colorectal cancer.

A deep learning model for detection and tracking in high-throughput images of organoid.

Organoid, an in vitro 3D culture, has extremely high similarity with its source organ or tissue, which creates a model in vitro that simulates the in vivo environment. Organoids have been extensively studied in cell biology, precision medicine, drug toxicity, efficacy tests, etc., which have been proven to have high research value. Periodic observation of organoids in microscopic images to obtain morphological or growth characteristics is essential for organoid research. It is difficult and time-consuming to perform manual screens for organoids, but there is no better solution in the prior art. In this paper, we established the first high-throughput organoid image dataset for organoids detection and tracking, which experienced experts annotate in detail. Moreover, we propose a novel deep neural network (DNN) that effectively detects organoids and dynamically tracks them throughout the entire culture. We divided our solution into two steps: First, the high-throughput sequential images are processed frame by frame to detect all organoids; Second, the similarities of the organoids in the adjacent frames are computed, and the organoids on the adjacent frames are matched in pairs. With the help of our proposed dataset, our model achieves organoids detection and tracking with fast speed and high accuracy, effectively reducing the burden on researchers. To our knowledge, this is the first exploration of applying deep learning to organoid tracking tasks. Experiments have demonstrated that our proposed method achieved satisfactory results on organoid detection and tracking, verifying the great potential of deep learning technology in this field.

ApodNet: Learning for High Frame Rate Synthetic Transmit Aperture Ultrasound Imaging.

Two-way dynamic focusing in synthetic transmit aperture (STA) beamforming can benefit high-quality ultrasound imaging with higher lateral spatial resolution and contrast resolution. However, STA requires the complete dataset for beamforming in a relatively low frame rate and transmit power. This paper proposes a deep-learning architecture to achieve high frame rate STA imaging with two-way dynamic focusing. The network consists of an encoder and a joint decoder. The encoder trains a set of binary weights as the apodizations of the high-frame-rate plane wave transmissions. In this respect, we term our network ApodNet. The decoder can recover the complete dataset from the acquired channel data to achieve dynamic transmit focusing. We evaluate the proposed method by simulations at different levels of noise and in-vivo experiments on the human biceps brachii and common carotid artery. The experimental results demonstrate that ApodNet provides a promising strategy for high frame rate STA imaging, obtaining comparable lateral resolution and contrast resolution with four-times higher frame rate than conventional STA imaging in the in-vivo experiments. Particularly, ApodNet improves contrast resolution of the hypoechoic targets with much shorter computational time when compared with other high-frame-rate methods in both simulations and in-vivo experiments.

Comparison of treatment results between surgical and conservative treatment of distal radius fractures in adults: A meta-analysis of randomized controlled trials.

OBJECTIVE: This meta-analysis study aims to determine the efficacy and safety of surgical and conservative treatments for distal radius fractures (DRFs) in adults. METHODS: Reports of randomized controlled trials were retrieved from the Web of Science, Pubmed, Google Scholar, EMBASE, Cochrane Library, Medline, Ovid, and BIOSIS for studies that met the eligibility criteria. The search was limited to human subjects and had no language limits. The search strategy was check by two independent reviewers. If there was any dispute, a third reviewer was consulted. Primary outcomes were: (1) the active wrist range of motion including flexion, extension, pronation, supination, radial, and ulnar deviation; (2) the Disabilities of the Arm, Shoulder, and Hand (DASH) score; and (3) radiological outcomes including radial inclination and ulnar variance. Secondary outcomes were the number of complications including non-infectious and infectious. Quality assessment was performed using the Cochrane Risk of Bias Tool provided by the Cochrane Review Manager 5.3. RESULTS: A total of 10 randomized controlled trials were included. The meta-analysis detected no statistically significant difference in pooled data for complications not included infection (MD 0.64, CI: 0.33 to 1.23, Z=1.34, p=0.18). Surgical treatment achieved a better range of motion (MD 3.76, CI: 1.58 to 5.95, Z=3.37, p=0.0007), DASH score (MD -6.57, CI: -9.08 to -4.06, Z=5.12, p<0.00001), and radiographic outcomes (MD 3.75, CI: 2.75 to 4.74, Z=7.37, p<0.00001) compared with conservative treatment. In contrast, the conservative treatment achieved less infection rate compared with surgical treatment (MD 4.09, CI: 1.18 to 14.21, Z=2.21, p=0.03). CONCLUSION: Findings of this study reveal that when compared with conservative treatment, surgical treatment can ensure better clinical and radiological results for the treatment of DRFs in adults. Although similar complication rates can be encountered with both treatment modalities, it should be taken into account that the rate of infection may be higher in surgical treatment. LEVEL OF EVIDENCE: Level I, Therapeutic Study.

Diagnostic value of bronchoalveolar lavage fluid cryptococcal antigen-lateral flow immunochromatographic assay for pulmonary cryptococcosis in non-HIV patients.

BACKGROUND: The aim of this study was to investigate the diagnostic value of cryptococcal antigen-lateral flow immunochromatographic assay (CrAg-LFA) in bronchoalveolar lavage fluid (BALF) of patients with pulmonary cryptococcosis (PC). METHODS: A total of 308 patients were divided into the PC group (n = 72) and the non-PC group (n = 236). The clinical data, pathogen detection, radiological imaging, and the detection of the cryptococcal antigen in blood and BALF samples were analyzed. RESULTS: The sensitivity, specificity, positive, and negative predicted values of CrAg-LFA in the serum were 75.0%, 99.6%, 98.2%, and 92.9%, respectively, while those in the BALF were 93.1%, 100.0%, 100.0%, and 97.9%, respectively. The sensitivity of the CrAg-LFA in BALF was significantly higher than that in the serum of the patients in the PC group (P < 0.05). CONCLUSION: CrAg-LFA has a higher diagnostic value for PC when analyzing BALF samples compared to serum samples.

D-Dimer Combined with Fibrinogen Predicts the Risk of Venous Thrombosis in Fracture Patients.

OBJECTIVE: While D-dimer can successfully diagnose venous thrombosis due to its excellent negative predictive value (NPV), it cannot be used to detect venous thromboembolism (VTE) because of its low positive predictive value (PPV). This study aims to investigate if a combination of using D-dimer and fibrinogen can improve PPV in the VTE diagnosis. METHODS: We retrospectively analyzed various data including D-dimer, fibrinogen, C-reactive protein, ultrasound, and others collected from 10775 traumatic fracture patients and categorized them into two groups of VTE and non-VTE. By comparing the difference between the two groups, we employ multiple logistic regression to find risk factors that are useful to detect VTE. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic yield of using fibrinogen, D-dimer, and their combination, respectively. Also, these data were classified into quartiles by patient age. We perform the same analysis on the quartiles and find if the patient's age has an impact on diagnosing VTE. RESULTS: The univariate analysis demonstrated that five factors of age, D-dimer, fibrinogen, C-reactive protein, and high-density lipoprotein cholesterol were significant to predict VTE. ROC showed that D-dimer was more useful than fibrinogen for the diagnosis of VTE, while the area under the curve (AUC) was 0.7296 for D-dimer and 0.5209 for fibrinogen. The cutoff point of D-dimer and fibrinogen was 424.89 ng/ml and 3.543 g/L, respectively. The specificity of fibrinogen was 0.777 which was better than D-dimer, while the sensitivity of fibrinogen was lower than that of D-dimer. Both PPV and NPV were similar in D-dimer and fibrinogen. The PPV of combining D-dimer and fibrinogen in ages Q3 (60 < age ≤ 70) and Q4 (age > 70) was better than using either D-dimer or fibrinogen. CONCLUSIONS: Fibrinogen is a promising strategy for the diagnosis of subclinical VTE and postoperative VTE. In particular, a combination of D-dimer and fibrinogen can improve the PPV to successfully diagnose VTE in traumatic fracture patients who are more than 60 years old. Levels of Evidence. This assay is a diagnostic test at level II.

Optic disc and optic cup segmentation based on anatomy guided cascade network.

BACKGROUND AND OBJECTIVE: Glaucoma, a worldwide eye disease, may cause irreversible vision damage. If not treated properly at an early stage, glaucoma eventually deteriorates into blindness. Various glaucoma screening methods, e.g. Ultrasound Biomicroscopy (UBM), Optical Coherence Tomography (OCT), and Heidelberg Retinal Scanner (HRT), are available. However, retinal fundus image photography examination, because of its low cost, is one of the most common solutions used to diagnose glaucoma. Clinically, the cup-to-disk ratio is an important indicator in glaucoma diagnosis. Therefore, precise fundus image segmentation to calculate the cup-to-disk ratio is the basis for screening glaucoma. METHODS: In this paper, we propose a deep neural network that uses anatomical knowledge to guide the segmentation of fundus images, which accurately segments the optic cup and the optic disc in a fundus image to accurately calculate the cup-to-disk ratio. Optic disc and optic cup segmentation are typical small target segmentation problems in biomedical images. We propose to use an attention-based cascade network to effectively accelerate the convergence of small target segmentation during training and accurately reserve detailed contours of small targets. RESULTS: Our method, which was validated in the MICCAI REFUGE fundus image segmentation competition, achieves 93.31% dice score in optic disc segmentation and 88.04% dice score in optic cup segmentation. Moreover, we win a high CDR evaluation score, which is useful for glaucoma screening. CONCLUSIONS: The proposed method successfully introduce anatomical knowledge into segmentation task, and achieve state-of-the-art performance in fundus image segmentation. It also can be used for both automatic segmentation and semiautomatic segmentation with human interaction.

Automatic and Accurate Epilepsy Ripple and Fast Ripple Detection via Virtual Sample Generation and Attention Neural Networks.

About 1% of the population around the world suffers from epilepsy. The success of epilepsy surgery depends critically on pre-operative localization of epileptogenic zones. High frequency oscillations including ripples (80-250 Hz) and fast ripples (250-500 Hz) are commonly used as biomarkers to localize epileptogenic zones. Recent literature demonstrated that fast ripples indicate epileptogenic zones better than ripples. Thus, it is crucial to accurately detect fast ripples from ripples signals of magnetoencephalography for improving outcome of epilepsy surgery. This paper proposes an automatic and accurate ripple and fast ripple detection method that employs virtual sample generation and neural networks with an attention mechanism. We evaluate our proposed detector on patient data with 50 ripples and 50 fast ripples labeled by two experts. The experimental results show that our new detector outperforms multiple traditional machine learning models. In particular, our method can achieve a mean accuracy of 89.3% and an average area under the receiver operating characteristic curve of 0.88 in 50 repeats of random subsampling validation. In addition, we experimentally demonstrate the effectiveness of virtual sample generation, attention mechanism, and architecture of neural network models.

Correction to: Telmisartan attenuates kidney apoptosis and autophagy-related protein expression levels in an intermittent hypoxia mouse model.

In the article that appeared on Page: 341-348, Vol 23 (15 September 2018) of the Sleep and breathing [1], one error was discovered in Figure 3. The picture of Normoxia and CIH in 100X is the same one. The corrected version of Figure 3 is presented here.

Sodium Tanshinone IIA Sulfonate Attenuates Tumor Oxidative Stress and Promotes Apoptosis in an Intermittent Hypoxia Mouse Model.

OBJECTIVE: Intermittent hypoxia, a significant feature of obstructive sleep apnea, has pro-tumorigenic effects. Here, we investigated the effect of sodium tanshinone IIA sulfonate on oxidative stress and apoptosis in a mouse model of Lewis lung carcinoma with intermittent hypoxia. METHODS: Mice were randomly assigned to normoxia (control), normoxia plus sodium tanshinone IIA sulfonate (control + sodium tanshinone IIA sulfonate), intermittent hypoxia, and intermittent hypoxia + sodium tanshinone IIA sulfonate groups. Intermittent hypoxia administration lasted 5 weeks in the intermittent hypoxia groups. Lewis lung carcinoma cells were injected into the right flank of each mouse after 1 week of intermittent hypoxia exposure. Sodium tanshinone IIA sulfonate was injected intraperitoneally in the control + sodium tanshinone IIA sulfonate and intermittent hypoxia + sodium tanshinone IIA sulfonate groups. Tumor oxidative stress was evaluated by detection of malondialdehyde and superoxide dismutase. The apoptosis of tumor cells was evaluated by the terminal deoxynucleotidyl transferase dUTP nick-end labeling assay as well as by Western blot analysis of B-cell lymphoma 2-associated X protein and cleaved caspase-3 expression. Additionally, the expression of hypoxia-induced factor-1α, nuclear factor erythroid 2-related factor 2, and nuclear factor kappa B was also evaluated by Western blot. RESULTS: Compared with the control group, the intermittent hypoxia treatment significantly increased Lewis lung carcinoma tumor growth and oxidative stress (serum malondialdehyde) but decreased serum levels of SOD and pro-apoptotic markers (terminal deoxynucleotidyl transferase dUTP nick-end labeling staining, B-cell lymphoma 2-associated X protein, and cleaved caspase-3). These changes were significantly attenuated by intraperitoneal injection of sodium tanshinone IIA sulfonate. Lower nuclear factor erythroid 2-related factor 2 and higher nuclear factor kappa B levels in the intermittent hypoxia group were clearly reversed by sodium tanshinone IIA sulfonate treatment. In addition, sodium tanshinone IIA sulfonate administration decreased the high expression of hypoxia-induced factor-1α induced by intermittent hypoxia. CONCLUSION: Intermittent hypoxia treatment resulted in high oxidative stress and low apoptosis in Lewis lung carcinoma-implanted mice, which could be attenuated by sodium tanshinone IIA sulfonate administration possibly through a mechanism mediated by the nuclear factor erythroid 2-related factor 2/nuclear factor kappa B signaling pathway.

Differential expression of microRNAs in xenografted Lewis lung carcinomas subjected to intermittent hypoxia: a next-generation sequence analysis.

BACKGROUND: Obstructive sleep apnea (OSA) is associated with increased cancer mortality, but the underlying mechanism remains poorly understood. MicroRNAs (miRNAs) are confirmed to be involved in tumorigenesis and tumor progression. However, whether miRNAs have any differential expressions in OSA population needs to be elucidated. The aim of this experimental study was to determine the alterations of various miRNAs in xenograft mice exposed to chronic intermittent hypoxia (IH) which is considered a hallmark of OSA. METHODS: Sequencing was applied to screen the miRNAs of tumor tissues in xenograft mice exposed to IH and normoxia (control, CTL), respectively. Most differentially expressed miRNAs were verified by the quantitative real-time polymerase chain reaction (qRT-PCR). Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway were performed to reveal the functional enrichment of the target genes regulated by the miRNAs. RESULTS: A total of 485 miRNAs (259 novel miRNAs and 226 known miRNAs) were differentially expressed between the IH and CTL groups. 154 miRNAs were upregulated and 331 miRNAs were downregulated among them. The top 5 differentially expressed known (miR-767, miR-466f-5p, miR-5122, miR-124-3p and miR-590-3p) and novel (miR-140, miR-130, miR-301, miR-177 and miR-90) miRNAs were validated by qRT-PCR. MiR-767, miR-124-3p, miR-590-3p and all novel miRNAs were upregulated while miR-466f-5p and miR-5122 were downregulated in IH-induced xenograft mice. In addition, GO and KEGG pathway analysis demonstrated that the predicted target genes, which were regulated by differentially expressed miRNAs were markedly enriched in related biological processes and pathways, including biological processes, cell metabolic and biosynthetic processes and molecular functions. CONCLUSIONS: Several altered miRNAs were detected in xenograft mice exposed to IH. The differentially expressed miRNAs in IH indicates that these miRNAs might involve in the molecular mechanism of tumorigenesis and tumor progression in OSA. Further studies are required to determinate the exact intermediation of certain miRNAs between IH and tumor progression.

Endoscopic Vision Augmentation Using Multiscale Bilateral-Weighted Retinex for Robotic Surgery.

Endoscopic vision plays a significant role in minimally invasive surgical procedures. The visibility and maintenance of such direct in situ vision is paramount not only for safety by preventing inadvertent injury but also to improve precision and reduce operating time. Unfortunately, the endoscopic vision is unavoidably degraded due to the illumination variations during surgery. This paper aims to restore or augment such degraded visualization and quantitatively evaluate it during robotic surgery. A multiscale bilateral-weighted retinex method is proposed to remove non-uniform and highly directional illumination and enhance surgical vision, while an objective no-reference image visibility assessment method is defined in terms of sharpness, naturalness, and contrast, to quantitatively and objectively evaluate the endoscopic visualization on surgical video sequences. The methods were validated on surgical data, with the experimental results showing that our method outperforms existent retinex approaches. In particular, the combined visibility was improved from 0.81 to 1.06, while three surgeons generally agreed that the results were restored with much better visibility.

Endoscopic video defogging using luminance blending.

Endoscopic video sequences provide surgeons with direct surgical field or visualisation on anatomical targets in the patient during robotic surgery. Unfortunately, these video images are unavoidably hazy or foggy to prevent surgeons from clear surgical vision due to typical surgical operations such as ablation and cauterisation during surgery. This Letter aims at removing fog or smoke on endoscopic video sequences to enhance and maintain a direct and clear visualisation of the operating field during robotic surgery. The authors propose a new luminance blending framework that integrates contrast enhancement with visibility restoration for foggy endoscopic video processing. The proposed method was validated on clinical endoscopic videos that were collected from robotic surgery. The experimental results demonstrate that their method provides a promising means to effectively remove fog or smoke on endoscopic video images. In particular, the visual quality of defogged endoscopic images was improved from 0.5088 to 0.6475.

Telmisartan attenuates kidney apoptosis and autophagy-related protein expression levels in an intermittent hypoxia mouse model.

PURPOSE: Obstructive sleep apnea (OSA) is associated with renal impairs. As a novel pathophysiological hallmark of OSA, chronic intermittent hypoxia (CIH) enhances apoptosis and autophagy. The present study aims to evaluate the effect of telmisartan on CIH-induced kidney apoptosis and autophagy in a mouse model of OSA. MATERIALS AND METHODS: Mice were randomly allocated to normoxia, CIH, and CIH+telmisartan groups (n = 12 in each group). The CIH exposure duration was 12 weeks. Mice in the CIH+telmisartan group received telmisartan administration. The terminal deoxynucleotidyl transferase dUTP nick-end labeling (TUNEL) assay and western blotting of Bax and cleaved caspase-3 were conducted for evaluating apoptosis in kidney tissue. While the autophagy-related proteins, beclin-1 and LC3, were also observed via western blotting. RESULTS: The percentage of apoptotic cell in the CIH group was significantly higher than that of normoxia group; meanwhile, Bax and cleaved caspase-3 protein levels were increased in the CIH group than those of normoxia group (all p < 0.05). Compared with the normoxia group, mice in the CIH group had greater autophagy-related proteins (beclin-1 and LC3) expression. When compared to the CIH group, both the renal apoptosis and autophagy in the CIH+telmisartan group were decreased. CONCLUSION: The CIH accelerates renal apoptosis and autophagy levels. Telmisartan ameliorating those levels suggests that it might prevent renal impairs from the CIH in OSA patients.