Objective:
To determine the cause and high-risk factors for the development of intestinal fistulas (IFs) after ultrasound-guided microwave ablation (MA) of abdominopelvic lesions, and to identify ...effective prophylactic and therapeutic actions.
Methods:
Clinical data were collected from patients with an IF after ultrasound-guided MA of abdominopelvic lesions in our hospital from January 1, 2010 to December 31, 2018. The cause, diagnosis, and treatment of IFs in these patients were analyzed.
Results:
Among 8,969 patients who underwent ultrasound-guided MA of abdominopelvic lesions, eight patients developed IF after MA, Seven patients were discharged after being cured and one died.
Conclusion:
Abdominopelvic lesions are close to the intestines, so histories of surgery, radiotherapy, and abdominopelvic infection are high-risk factors for IF development after MA of these lesions. Surgical treatment should be provided as soon as an IF is identified.
Anatomically diffused tissues (ADTs) refer to soft tissues containing many anatomical regions that are spatially dispersed and structurally irregular. In magnetic resonance images, ADTs exhibit ...blurred morphology and heterogeneous texture, making the accurate extraction of their 3D anatomy challenging. Center-free fuzzy <inline-formula><tex-math notation="LaTeX">C</tex-math></inline-formula>-means (FCM) can effectively partition nonlinear or nonspherical clusters, providing a promising scheme for ADT segmentation. It solves the uncertainty arising from unreliable center estimation by introducing a similarity criterion. However, the similarity criterion is sensitive to the number of target objects and their adjacent members in the images. Moreover, memberships of the existing algorithms are susceptible to losing real ADT details. To handle these issues, we propose an edge-preserving constrained center-free FCM algorithm for segmenting 3D ADTs in magnetic resonance images. To overcome the sensitivity of the similarity criterion, a novel object-to-cluster similarity measure is first proposed to utilize refined member-to-object adjacency. Specifically, the similarity measure focuses on members in the feature space, which share approximately homogeneous characteristics with each target object. Gradient-domain edge-preserving filtering is then combined with the improved similarity criterion to construct the novel objective function of center-free FCM. With the assistance of the designed image-driven edge-preserving regularization, the gradient information of clusters is constrained, eventually approaching that of ADTs in the guidance image. Experiments are conducted on two public brain datasets and one local intrahepatic vein dataset. The results demonstrate that the proposed algorithm is more effective for ADT segmentation than the state-of-the-art peers, exhibiting superior generalization capability.
Segmenting portal vein (PV) and hepatic vein (HV) from magnetic resonance imaging (MRI) scans is important for hepatic tumor surgery. Compared with single phase-based methods, multiple phases-based ...methods have better scalability in distinguishing HV and PV by exploiting multi-phase information. However, these methods just coarsely extract HV and PV from different phase images. In this paper, we propose a unified framework to automatically and robustly segment 3D HV and PV from multi-phase MR images, which considers both the change and appearance caused by the vascular flow event to improve segmentation performance. Firstly, inspired by change detection, flow-guided change detection (FGCD) is designed to detect the changed voxels related to hepatic venous flow by generating hepatic venous phase map and clustering the map. The FGCD uniformly deals with HV and PV clustering by the proposed shared clustering, thus making the appearance correlated with portal venous flow robustly delineate without increasing framework complexity. Then, to refine vascular segmentation results produced by both HV and PV clustering, interclass decision making (IDM) is proposed by combining the overlapping region discrimination and neighborhood direction consistency. Finally, our framework is evaluated on multi-phase clinical MR images of the public dataset (TCGA) and local hospital dataset. The quantitative and qualitative evaluations show that our framework outperforms the existing methods.
Objective
To evaluate the efficacy and safety of microwave ablation (MWA) for the treatment of symptomatic benign thyroid nodules in children.
Methods
A retrospective study of MWA for the treatment ...of 34 symptomatic benign thyroid nodules in 25 children was conducted. Volume reduction ratio (VRR), technique efficacy, symptom score, cosmetic score, and thyroid function were used to evaluate the efficacy of the technique. The associated complications and side effects were recorded.
Results
The participants were followed for at least 6 months (median 12 months, range 6–48 months). After MWA treatment, the volumes of the targeted nodules decreased gradually (median volume 5.86 mL before MWA and 0.34 mL at the final follow-up assessment), the VRR achieved was up to 85.03% at the final follow-up assessment, and the technical efficacy at this time was 91.2%. The subjective and objective nodule-related symptoms were also ameliorated. The circulating hormone concentrations reflecting thyroid function remained within their normal ranges in all the participants after one month of follow-up. The procedure had no major complications.
Conclusions
MWA seems to be an effective and safe technique for the treatment of symptomatic benign thyroid nodules in pediatric patients.
Clinical relevance statement
Microwave ablation is a safe and effective method to treat symptomatic benign thyroid nodules in pediatric patients. This treatment may be selected if the patient or parents are not suitable or refuse to undergo surgery.
Key Points
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Microwave ablation is effective in reducing the volume of benign thyroid nodules and ameliorating nodule-related symptoms in pediatric patients.
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Microwave ablation is a safe method in children, with low complications.
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Microwave ablation does not affect the circulating thyroid hormone concentrations of children.
Purpose
The liver segments divided by Couinaud classification method are used to understand the functional anatomy of liver, which is significant in hepatic resection surgery. In Couinaud ...classification method, each third‐order branch of the portal vein (PV) defines the supplied territory of a corresponding liver segment. However, the accuracies of the reconstruction and classification of PV are affected by the complicated structure of the vein. The purpose of this paper is to develop a separation and classification method that can accurately extract the liver segments.
Methods
In this paper, a multiple feature‐based method is proposed to obtain liver segments. Because the portal and hepatic veins usually connect in the vessel segmentation result, the PV is first completely separated based on the different strategies for minimal node cut using fused features of topology and appearance. Meanwhile, all bifurcation nodes of PV are detected. The bifurcation nodes are initial ordered through their linkages to classify the branches. Then, the feature of the vascular topology is used to refine the orders of bifurcation nodes. The bifurcation nodes with the refined orders classify the branches between them, and the third‐order branches of PV are obtained. The liver segments are eventually obtained through the third‐order branches.
Results
The separation and classification in the proposed method are evaluated on the CT and MR datasets. The average values of Dice, Jaccard, Recall, and Precision obtained by the proposed method are 93.00%, 87.90%, 93.47%, and 93.19%, respectively. Compared with the state‐of‐the‐art methods, the separation results obtained by the proposed method are more accurate. The branches of PV are classified based on the separation result. According to the third‐order branches, eight liver segments correspond to the different functional areas are precisely extracted.
Conclusions
The proposed method achieves a high accuracy for the liver segment extraction. And the extracted liver segments are significant for the preplanning of resection surgery.
Microwave ablation (MWA) is a minimally invasive procedure for the treatment of liver tumor. Accumulating clinical evidence has considered the minimal ablative margin (MAM) as a significant predictor ...of local tumor progression (LTP). In clinical practice, MAM assessment is typically carried out through image registration of pre- and post-MWA images. However, this process faces two main challenges: non-homologous match between tumor and coagulation with inconsistent image appearance, and tissue shrinkage caused by thermal dehydration. These challenges result in low precision when using traditional registration methods for MAM assessment. In this paper, we present a local contractive nonrigid registration method using a biomechanical model (LC-BM) to address these challenges and precisely assess the MAM. The LC-BM contains two consecutive parts: 1) local contractive decomposition (LC-part), which reduces the incorrect match between the tumor and coagulation and quantifies the shrinkage in the external coagulation region, and 2) biomechanical model constraint (BM-part), which compensates for the shrinkage in the internal coagulation region. After quantifying and compensating for tissue shrinkage, the warped tumor is overlaid on the coagulation, and then the MAM is assessed. We evaluated the method using prospectively collected data from 36 patients with 47 liver tumors, comparing LC-BM with 11 state-of-the-art methods. LTP was diagnosed through contrast-enhanced MR follow-up images, serving as the ground truth for tumor recurrence. LC-BM achieved the highest accuracy (97.9%) in predicting LTP, outperforming other methods. Therefore, our proposed method holds significant potential to improve MAM assessment in MWA surgeries.
•We propose a method to correct the noisy label based on the strong supervision signal and use the corrected label to guide the supervised learning.•The proposed model can predict the ablation time ...closer to that in the non-relapse after microwave ablation for liver cancer, providing a helpful reference for physicians.
Percutaneous microwave ablation is an essential and safe method for the treatment of liver cancer. As one therapeutic dose, ablation time is crucial to the treatment effect determined by the physicians. However, due to the different experiences of physicians and the significant individual differences of patients, the final treatment effect is also different, which makes it difficult for the ablation time recorded in the electronic health records (EHRs) to follow the same pattern. To solve this problem, we propose a data mining method based on historical treatment data recorded in EHR, which uses a robust relapse risk as strong supervision to correct the ablation time. The prediction results of this method are closer to the situation of patients without relapse, which can provide physicians with reference.
In the proposed method, we introduce the optimization method to iteratively minimize the postoperative relapse risk and utilize gradient propagation between the risk and ablation time during iteration to correct the latter. We also apply a self-attention mechanism to find the global dependencies between each feature in EHR to improve the final prediction performance of the model.
Comparative experimental results show that compared with other baseline model, the proposed model achieves better performance on R-square, MAE, and MSE metric. The results of ablation experiments show that the integration of label correction and self-attention mechanism can improve the model performance.
We using relapse risk as strong supervision related to the ablation time can effectively correct the deviation of the ablation time as weak supervision. The self-attention mechanism in the proposed model can significantly improve the prediction performance.
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Energy management plays a crucial role in achieving extended endurance for solar-powered Unmanned Aerial Vehicles (UAVs). Current studies in energy management primarily focus on natural energy ...harvesting and task-oriented path planning. This paper aims to optimize energy consumption during the climb and glide stages by exploring variable climb speeds and glide powers. To achieve this, fitness functions are established for both the climb and glide stages, taking into account the maximum climb speed and glide power limits of the aircraft. The particle swarm optimization (PSO) algorithm is employed to solve the problem, resulting in significant energy savings of over 68% in the climb stage and 4.8% in the glide stage. Based on an analysis of the optimization trends, this study proposes an energy-management strategy to fulfill the demand for long-endurance flights. The findings of this study can serve as a valuable reference for high-altitude missions that require extended flight times.
This study aims to assess the relationship between spontaneous oscillations in changes in cerebral tissue oxyhemoglobin concentrations (Delta HbO2) and arterial blood pressure (ABP) signals in ...healthy elderly subjects during the resting state using wavelet coherence analysis. Continuous recordings of near-infrared spectroscopy (NIRS) and ABP signals were obtained from simultaneous measurements in 33 healthy elderly subjects (age: 70.7±7.9years) and 27 young subjects (age: 25.2±3.7years) during the resting state. The coherence between Delta HbO2 and ABP oscillations in six frequency intervals (I, 0.4–2Hz; II, 0.15–0.4Hz; III, 0.05–0.15Hz; IV, 0.02–0.05Hz, V, 0.005–0.0095Hz and VI, 0.005–0.0095Hz) was analyzed using wavelet coherence analysis. In elderly subjects, the Delta HbO2 and ABP oscillations were significantly wavelet coherent in interval I, and wavelet phase coherent in intervals I, II and IV. The wavelet coherence in interval I was significantly higher (p=0.040), in elderly subjects than in young subjects whereas that in interval V significantly lower (p=0.015). In addition, the wavelet phase coherence in interval IV was significantly higher in elderly subjects than in young subjects (p=0.028). The difference in the wavelet coherence of the elderly subjects and the young subjects indicates an altered cerebral autoregulation caused by aging. This study provides new insight into the dynamics of Delta HbO2 and ABP oscillations and may be useful in identifying the risk for dynamic cerebral autoregulation processes.
•Delta (HbO2) and arterial blood pressure signals were measured simultaneously.•Wavelet coherence in cardiac activity was higher in elderly than in young subjects.•Wavelet coherence in metabolic activity was lower in elderly than in young subjects.•Phase coherence in neurogenic activity was higher in elderly than in young subjects.•Difference in coherence indicates an altered cerebral autoregulation due to aging.
•Phase coherence between cerebral Delta HbO2 and blood pressure was analyzed.•Sit-to-stand change induces low wavelet phase coherence in elderly subjects.•Stand-to-sit change induces high wavelet ...phase coherence (WPCO) in elderly subjects.•Difference in WPCO indicates an altered cerebral autoregulation due to aging.
This study aims to assess the dynamic cerebral autoregulation (dCA) in response to posture change using wavelet phase coherence (WPCO) of cerebral tissue oxyhemoglobin concentrations (Delta HbO2) and arterial blood pressure (ABP) signals in healthy elderly subjects. Continuous recordings of near-infrared spectroscopy (NIRS) and ABP signals were obtained from simultaneous measurements in 16 healthy elderly subjects (age: 68.9±7.1 years) and 19 young subjects (age: 24.9±3.2 years). The phase coherence between Delta HbO2 and ABP oscillations in six frequency intervals (I, 0.6–2Hz; II, 0.15–0.6Hz; III, 0.05–0.15Hz; IV, 0.02–0.05Hz, V, 0.0095–0.02Hz and VI, 0.005–0.0095Hz) was analyzed using WPCO. The sit-to-stand posture change induces significantly lower WPCO in interval III (F=5.50 p=0.025) in the elderly subjects than in the young subjects. However, the stand-to-sit posture change induces higher WPCO in intervals II (F=5.25 p=0.028) and V (F=6.22 p=0.018) in the elderly subjects than in the young subjects. The difference of WPCO in response to posture change between the elderly and the young subjects indicates an altered CA due to aging. This study provides new insight into the dynamics of CA and may be useful in identifying the risk for dCA processes.
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