Cardiovascular diseases such as coronary arteriosclerosis are widespread and constitute severe health and welfare problems for both farmed and wild salmonid fish. However, effective tools for rapid ...screening and analysing heart diseases in fish do not currently exist. Electrocardiogram (ECG) recordings are widely used for screening and diagnosing numerous cardiac pathologies in humans, but the use of ECG techniques to diagnose and characterize cardiac abnormalities in fish is still in its infancy. In this study, we induced myocardial ischemia in anaesthetized rainbow trout by surgical coronary artery ligation. Additionally, we experimentally manipulated the fish's heart rate and environmental oxygen availability by altering gill water flow and oxygen saturation (i.e., no flow, normoxic flow and hyperoxic flow), and analyzed changes in the ECG profile in detail. The main ECG abnormalities observed in fish with ligated coronaries in normoxia were atrioventricular blocks, prolonged QRS duration, reduced QRS amplitude and changes in the ST-segment such as the presence of early repolarization pattern. Furthermore, when gill water flow was stopped, fish exhibited pronounced hypoxic bradycardia, which alleviated all ECG abnormalities in coronary ligated fish. This is the first study to provide a detailed characterization of electrocardiographic markers of myocardial ischemia in fish. Our study shows that hypoxic bradycardia improves cardiac electrical conductivity, presumably by reducing mismatches in myocardial oxygen supply and demand. Yet, the importance of avoiding hypoxic bradycardia in experimental and biomedical studies on anaesthetized fish is highlighted as it can potentially lead to incorrect ECG interpretations.
Learning Skill Characteristics From Manipulations Zhou, Xiao-Hu; Xie, Xiao-Liang; Liu, Shi-Qi ...
IEEE transaction on neural networks and learning systems,
12/2023, Volume:
34, Issue:
12
Journal Article
Percutaneous coronary intervention (PCI) has increasingly become the main treatment for coronary artery disease. The procedure requires high experienced skills and dexterous manipulations. However, ...there are few techniques to model PCI skill so far. In this study, a learning framework with local and ensemble learning is proposed to learn skill characteristics of different skill-level subjects from their PCI manipulations. Ten interventional cardiologists (four experts and six novices) were recruited to deliver a medical guidewire to two target arteries on a porcine model for in vivo studies. Simultaneously, translation and twist manipulations of thumb, forefinger, and wrist are acquired with electromagnetic (EM) and fiber-optic bend (FOB) sensors, respectively. These behavior data are then processed with wavelet packet decomposition (WPD) under 1-10 levels for feature extraction. The feature vectors are further fed into three candidate individual classifiers in the local learning layer. Furthermore, the local learning results from different manipulation behaviors are fused in the ensemble learning layer with three rule-based ensemble learning algorithms. In subject-dependent skill characteristics learning, the ensemble learning can achieve 100% accuracy, significantly outperforming the best local result (90%). Furthermore, ensemble learning can also maintain 73% accuracy in subject-independent schemes. These promising results demonstrate the great potential of the proposed method to facilitate skill learning in surgical robotics and skill assessment in clinical practice.
Objectives
Virtual monoenergetic images (VMIs) from photon-counting CT (PCCT) may change quantitative coronary plaque volumes. We aimed to assess how plaque component volumes change with respect to ...VMIs.
Methods
Coronary CT angiography (CTA) images were acquired using a dual-source PCCT and VMIs were reconstructed between 40 and 180 keV in 10-keV increments. Polychromatic images at 120 kVp (T3D) were used as reference. Quantitative plaque analysis was performed on T3D images and segmentation masks were copied to VMI reconstructions. Calcified plaque (CP; > 350 Hounsfield units, HU), non-calcified plaque (NCP; 30 to 350 HU), and low-attenuation NCP (LAP; − 100 to 30 HU) volumes were calculated using fixed thresholds.
Results
We analyzed 51 plaques from 51 patients (67% male, mean age 65 ± 12 years). Average attenuation and contrast-to-noise ratio (CNR) decreased significantly with increasing keV levels, with similar values observed between T3D and 70 keV images (299 ± 209 vs. 303 ± 225 HU,
p
= 0.15 for mean HU; 15.5 ± 3.7 vs. 15.8 ± 3.5,
p
= 0.32 for CNR). Mean NCP volume was comparable between T3D and 100–180-keV reconstructions. There was a monotonic decrease in mean CP volume, with a significant difference between all VMIs and T3D (
p
< 0.05). LAP volume increased with increasing keV levels and all VMIs showed a significant difference compared to T3D, except for 50 keV (28.0 ± 30.8 mm
3
and 28.6 ± 30.1 mm
3
, respectively,
p
= 0.63).
Conclusions
Estimated coronary plaque volumes significantly differ between VMIs. Normalization protocols are needed to have comparable results between future studies, especially for LAP volume which is currently defined using a fixed HU threshold.
Clinical relevance statement
Different virtual monoenergetic images from photon-counting CT alter attenuation values and therefore corresponding plaque component volumes. New clinical standards and protocols are required to determine the optimal thresholds to derive plaque volumes from photon-counting CT.
Key Points
•
Utilizing different VMI energy levels from photon-counting CT for the analysis of coronary artery plaques leads to substantial changes in attenuation values and corresponding plaque component volumes.
•
Low-energy images (40–70 keV) improved contrast-to-noise ratio, however also increased image noise.
•
Normalization protocols are needed to have comparable results between future studies, especially for low-attenuation plaque volume which is currently defined using a fixed HU threshold.
Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to ...radiological data. With the recent advent of whole slide digital scanners, tissue histopathology slides can now be digitized and stored in digital image form. Consequently, digitized tissue histopathology has now become amenable to the application of computerized image analysis and machine learning techniques. Analogous to the role of computer-assisted diagnosis (CAD) algorithms in medical imaging to complement the opinion of a radiologist, CAD algorithms have begun to be developed for disease detection, diagnosis, and prognosis prediction to complement the opinion of the pathologist. In this paper, we review the recent state of the art CAD technology for digitized histopathology. This paper also briefly describes the development and application of novel image analysis technology for a few specific histopathology related problems being pursued in the United States and Europe.
Intravascular lithotripsy can be used as an effective therapy for lesion preparation in severely calcified lesions. The mechanism, as shown by optical coherence tomography, is calcium fractures. The ...aforementioned modification is performed with minimal risk of perforation, no-reflow and a low incidence of flow-limiting dissection and myocardial infarctions. Other techniques, such as cutting or scoring balloons and rotational atherectomy have also been shown to increase luminal diameter, but other complications, such as distal embolization, induced by these treatment modalities, are a source of concern. This review describes a single-center study of all-comer patients, including those with complex characteristics. This therapy is very effective, with a very low risk of complications. In this article, we characterize the mechanism of action of the intravascular lithotripsy catheter, its optical coherence tomography validation, clinical applications, and comparison with other calcium-modifying technologies, as well as future directions, which can be used to improve the technology.
Display omitted
•Earlier treatment modalities for calcified lesions are associated with an increased risk of complications.•IVL can be used wide across the spectrum of calcified lesions defined by the imaging.•The use of IVL in early experience seems to decrease the complications versus other modalities.•The IVL catheter system can be modified in various ways to improve its clinical applicability.
Coronary arteriosclerosis is a common feature of both wild and farmed salmonid fishes and may be linked to stress-induced cardiac pathologies. Yet, the plasticity and capacity for long-term ...myocardial restructuring and recovery following a restriction in coronary blood supply are unknown. Here, we analyzed the consequences of acute (3 days) and chronic (from 33 to 62 days) coronary occlusion (i.e. coronary artery ligation) on cardiac morphological characteristics and in vivo function in juvenile rainbow trout, Oncorhynchus mykiss. Acute coronary artery occlusion resulted in elevated resting heart rate and decreased inter-beat variability, which are both markers of autonomic dysfunction following acute myocardial ischemia, along with severely reduced heart rate scope (maximum-resting heart rate) relative to sham-operated trout. We also observed a loss of myocardial interstitial collagen and compact myocardium. Following long-term coronary artery ligation, resting heart rate and heart rate scope normalized relative to sham-operated trout. Moreover, a distinct fibrous collagen layer separating the compact myocardium into two layers had formed. This may contribute to maintain ventricular integrity across the cardiac cycle or, alternatively, demark a region of the compact myocardium that continues to receive oxygen from the luminal venous blood. Taken together, we demonstrate that rainbow trout may cope with the aversive effects caused by coronary artery obstruction through plastic ventricular remodeling, which, at least in part, restores cardiac performance and myocardium oxygenation.
Objectives
To investigate the incremental prognostic value of left ventricular (LV) entropy in a large multi-center population with coronary atherosclerotic heart disease (CAD).
Background
Current ...risk stratification of patients with CAD is imprecise and not accurate enough.
Methods
A total of 314 CAD patients who underwent cardiovascular magnetic resonance (CMR) late gadolinium enhancement (LGE) at two medical centers in China between October 2015 and July 2022 were included in this study. Additionally, the 193 patients under 3.0-T field also underwent CMR T1 mapping. LV entropy and extracellular volume (ECV) were calculated from the LGE image of LV myocardium, and major adverse cardiac events (MACEs) were analyzed.
Results
Among 314 patients, 110 experienced MACE during a median follow-up of 13 months. The risk of MACE was significantly increased in the high entropy group (log-rank
p
< 0.001). Entropy maintained an independent association with MACE in a multivariable model including left ventricular ejection fraction (LVEF) and LGE (HR = 1.78;
p
= 0.001). In addition, the primary endpoint events prognostic value was significantly improved by adding LV entropy to the baseline multivariable model (C-statistic improvement: 0.785–0.818, Delong test:
p
= 0.001). Similarly, among 193 3.0-T field patients, adding LV entropy to the multivariable baseline model significantly improved the prognostic value of the model for MACE (C-statistic improvement: 0.820–0.898, Delong test:
p
= 0.004).
Conclusion
CMR-assessed LV entropy is a powerful independent predictor of MACE in patients with CAD, incremental to common clinical and CMR risk factors, including LVEF, LGE, Native T1, and ECV.
Clinical relevance statement
Left ventricular entropy is a powerful independent predictor of major adverse cardiac events in patients with coronary atherosclerotic heart disease, incremental to common clinical and cardiac magnetic resonance risk factors.
Key Points
• Left ventricular entropy, a novel cardiac magnetic resonance parameter of myocardial heterogeneity, demonstrated a robust prognostic association with major adverse cardiac events beyond guideline-based, clinical risk markers.
• Entropy can have an important role in the primary prevention of major adverse cardiac events in patients with coronary atherosclerotic heart disease.
• Compared with late gadolinium enhancement, extracellular volume, and native T1, entropy could be used to more comprehensively characterize the heterogeneity of left ventricular myocardium.
Percutaneous coronary intervention (PCI) is an effective treatment for normalizing blood flow in coronary arteries narrowed by stent implantation. Guidewire insertion during PCI requires considerable ...precision and expertise, and two X-ray videos, a cine loop of angiography and a real-time video of live fluoroscopy, are used to aid guidewire navigation to the target location without entering the wrong blood vessel branches. However, simultaneously watching and interpreting two radiographic videos warrants increased mental effort and intervention time. Additionally, more contrast agents may have to be injected to verify the insertion. Although deep-learning-based dynamic coronary roadmapping (DCR) has been suggested to provide registered images from two different X-ray sources, existing methods may not be suitable for irregular heartbeats or may vary in effectiveness depending on the patient, posing challenges in time-critical situations. To address these challenges, we propose a patient-specific approach for DCR using similarity-based patient data matching in transfer learning with a residual U-Net. The proposed method leverages the anatomical similarities between newly acquired and pre-acquired angiograms by utilizing principal component analysis and cosine similarity to facilitate efficient transfer learning. Moreover, a residual U-Net architecture that incorporates residual blocks and leaky ReLU activation functions to accelerate patient-specific transfer learning is proposed. These advanced techniques resulted in significantly fast transfer learning of less than five minutes from a pre-trained model, as well as high registration image quality with over 30 dB in peak signal-to-noise ratio, while maintaining a registration error of 1.04±0.19 mm.
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