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The accuracy of automated facial landmarking - a comparative study between Cliniface software and patch-based Convoluted Neural Network algorithm
Get PDFBackground:
Automatic landmarking software packages simplify the analysis of the 3D facial images. Their main deficiency is the limited accuracy of detecting landmarks for routine clinical applications. Cliniface is readily available open-access software for automatic facial landmarking, its validity has not been fully investigated.
Objectives:
Evaluate the accuracy of Cliniface software in comparison with the developed patch-based Convoluted Neural Network (CNN) algorithm in identifying facial landmarks.
Materials /Methods:
The study was carried out on 30 3D photographic images; twenty anatomical facial landmarks were used for the analysis. The manual digitization of the landmarks was repeated twice by an expert operator, which considered the ground truth for the analysis. Each 3D facial image was imported into Cliniface software, and the landmarks were detected automatically. The same set of the facial landmarks were automatically detected using the developed patch-based CNN algorithm. The 3D image of the face was subdivided into multiple patches, the trained CNN algorithm detected the landmarks within each patch. Partial Procrustes Analysis was applied to assess the accuracy of automated landmarking. The method allowed the measurement of the Euclidean distances between the manually detected landmarks and the corresponding ones generated by each of the two automated methods. The significance level was set at 0.05 for the differences between the measured distances.
Results:
The overall landmark localization error of Cliniface software was 3.66 ± 1.53 mm, Subalar exhibiting the largest discrepancy of more than 8 mm in comparison with the manual digitization. Stomion demonstrated the smallest error. The patch-based CNN algorithm was more accurate than Cliniface software in detecting the facial landmarks, it reached the same level of the manual precision in identifying the same points. The inaccuracy of Cliniface software in detecting the facial landmarks was significantly higher than the manual landmarking precision.
Limitations:
The study was limited to one centre, one groups of 3D images, and one operator.
Conclusions:
The patch-based CNN algorithm provided a satisfactory accuracy of automatic landmarks detection which is satisfactory for the clinical evaluation of the 3D facial images. Cliniface software is limited in its accuracy in detecting certain landmark which bounds its clinical application
A Numerical and Experimental Investigation of the Richtmyer-Meshkov Instability in a Convergent Geometry
Get PDFThe Richtmyer-Meshkov Instability is investigated numerically and experimentally in a convergent test geometry, utilising a gas lens approach to circularise incident shocks, three strengths of which are considered to provide shock induced flows of 30m/s, 55m/s, and 80m/s. Perturbation amplitude growths, circulation, qualitative numerical Schlieren, and mean interfacial position are discussed, with comparisons made between numerical and experimental cases. The greatest amplitude growths are found for the strongest shock cases, with interfacial developments observed to initially travel approximately linearly with shock induced flows before stabilisation effects halt their motion. Greatest circulations are found in the strongest shock scenarios, suggesting the greatest mixing rates can be expected in fast shock scenarios. Stabilisation effects are observed and result in perturbation reversal and continued growth, occurring at the fastest rates for the fastest shock speeds
Insight, perceptio, and Sosa on firsthand knowledge
Get PDFSosa emphasizes "firsthand intuitive insight" as a distinctive kind of epistemic aim and argues that this is a characteristic epistemic goal of humanistic inquiry. He draws from this some importantly antiskeptical conclusions for the epistemology of disagreement. I try to further develop this idea of insight, which I call ‘perceptio’, in which we "see" some truth to obtain. I agree that it is a distinctive epistemic good, although I think it is central to understanding in general and not just in the humanities. It is also central to a specific kind of knowing-that that does not involve understanding. The precise way in which perceptio is a distinctive epistemic good means that, although it cannot do the antiskeptical work for disagreement that Sosa probably wants, it can do some related work
EuroQol 5-Dimension questionnaire in heart failure with reduced, mildly reduced, and preserved ejection fraction
Get PDFBackground:
The value of generic quality of life (QoL) instruments in heart failure (HF) is uncertain.
Objectives:
In this study, the authors sought to quantify individual dimension scores and the EuroQol 5-Dimension questionnaire (EQ-5D) Level Sum Score (LSS) in patients with HF with reduced, mildly reduced, or preserved ejection fraction, the association between those scores and outcomes, and the impact of treatment with dapagliflozin on the scores.
Methods:
Analyses were conducted using patient-level data from DAPA-HF and DELIVER trials. Cox proportional hazards regression models were used to assess the association between EQ-5D scores (each dimension and LSS) and clinical outcomes. Sankey diagrams were used to illustrate changes in individual patient EQ-5D dimensions from baseline to 8 months’ follow-up.
Results:
Of the 11,007 patients randomized in DAPA-HF and DELIVER, 10,135 (92.1%) completed the instrument at baseline. Scores varied markedly by question with 37%, 30%, and 33% of patients reporting no, slight, or moderate or greater problem, respectively for mobility; 67%, 20%, and 13% for self-care; 40%, 33%, and 27% for usual activities; 45%, 32%, and 23% for pain/discomfort; and 57%, 27%, and 16% for anxiety/depression. Patients with higher (worse) EQ-5D-LSS were more frequently female, had more comorbidities, and had worse HF status. Compared with patients free from any problem across all dimensions (ie, an EQ-5D-LSS of 5), the HRs for the composite outcome of time to first cardiovascular death or worsening HF were 1.27 (95% CI: 1.10-1.47), 1.70 (95% CI: 1.46-1.98), and 2.31 (95% CI: 1.88-2.85) in patients with EQ-5D-LSS of 6-10, 11-15, and 16-25 points, respectively. Dapagliflozin led to greater improvement and less worsening in mobility (OR: 1.13 [95% CI: 1.04-1.23]; P = 0.004), self-care (OR: 1.13 [95% CI: 1.02-1.24]; P = 0.016), usual activities (OR: 1.11 [95% CI: 1.02-1.21]; P = 0.015), and anxiety/depression (OR: 1.10 [95% CI: 1.01-1.21]; P = 0.034) after 8 months. The number needed to treat for 1 patient to report improvement in EQ-5D-LSS was 31 (95% CI: 20-72).
Conclusions:
The EQ-5D revealed problems not often associated (eg, pain) with HF or commonly quantified in HF (eg, anxiety/depression). Dapagliflozin improved multiple QoL dimensions, and possibly anxiety/depression. (Study to Evaluate the Effect of Dapagliflozin on the Incidence of Worsening Heart Failure or Cardiovascular Death in Patients With Chronic Heart Failure [DAPA-HF]; NCT03036124; Dapagliflozin Evaluation to Improve the Lives of Patients With Preserved Ejection Fraction Heart Failure [DELIVER]; NCT03619213)
In-time conditional handover for B5G/6G
No full textConditional Handover (CHO) by the 3rd Generation Partnership Project (3GPP) enables efficient user mobility between Base Stations (BSs) by preselecting and preparing Target BSs (T-BSs). However, CHO relies on signal strength for T-BS selection, leading to resource blocking on multiple T-BSs due to signal fluctuations. Existing state-of-the-art methods use deep learning to narrow the list of T-BSs but still lack an effective method for resource reservation timing. This paper presents in-time CHO (iCHO) which exploits historical mobility data to estimate user dwell time at the current BS to reduce resource reservation duration. The proposed iCHO employs a Multivariate Multi-output Single-step Prediction (MMSP) model that leverages a multi-task learning approach to simultaneously predict the minimal list of required T-BSs together with the user dwell time. The model demonstrates remarkable performance across two mobility datasets of different scales, achieving T-BS prediction accuracies of 98% and 95%. It also ensures a 100% handover success rate with a minimum of three and four predicted T-BSs for both datasets, respectively, significantly limiting the list of T-BSs. Moreover, the MMSP model achieves a Mean Absolute Error (MAE) of 19 s and 45 s when predicting the user’s dwell time at the current BS. By utilizing these predictions, iCHO reserves resources at the minimum number of T-BSs immediately before handover. Thus, iCHO can save up to 99% of resources from blockage as compared to the CHO, enabling operators to increase revenue by serving up to eighteen more users with the saved resources
Changes in frailty status and discharge destination post emergency laparotomy
Get PDFBackground: Pre-operative frailty adversely affects morbidity and mortality after emergency laparotomy (EmLap), especially in older adults (65 years and above). Little is known about frailty after EmLap. We explored the change in frailty status from pre- to post-EmLap and any influence on discharge destination. Methods: EmLap patients aged ≥ 65years from an acute surgical site were recruited from May 2022 to April 2023. Prospective data collection included demographics, frailty, mortality and discharge destination. Frailty was assessed using the Rockwood Clinical Frailty Scale at pre-EmLap and day-90 post-EmLap (< 4 as non-frail, 4 as pre-frail and > 4 as frail). EmLap patients with no 90-day follow-up were excluded. A p-value of < 0.05 was considered significant. Results: 63 EmLap patients were included in the study. The median age was 75 years (range 65–91 years) with 36 (57.1%) females. Eleven (17.5%) were living with frailty pre-EmLap, and 10 (15.9%) developed new frailty by day-90 post-EmLap. Pre-EmLap, all patients came from home with 20.6% of the frail and pre-frail group having a package of care service (POC) in place. On 90-day post-EmLap, 1 was still an inpatient but 25.8% had a change in discharge destination: care home (n = 1), home with new POC (n = 2) and home with increased POC (n = 13). Of the 16 patients with change of discharge destination, 9 (56.3%) were frail pre-EmLap. There was a significant association between pre-EmLap frailty and change in home circumstances on discharge (p < 0.00001). Conclusions: Emergency surgery can increase a patient’s frailty status and significantly increases care requirements and social support after hospital discharge. Frailty assessment needs to be performed before and after admission in all EmLap patients to improve post-EmLap care planning and patient expectations
The cardiology community begins to embrace obesity as an important target for cardiovascular health
Get PDFNaveed Sattar and Martin K Rutter discuss the contributory role of obesity in the development and progression of cardiovascular disease, and prospects for tackling the obesity epidemic
Breaking through: immunotherapy innovations in pleural mesothelioma
Get PDFThe prognosis of pleural mesothelioma (PM) is poor and conventional chemotherapy regimens have shown limited antitumor activity. Recent use of immune checkpoint inhibitors (ICIs) has shown promise, with CheckMate-743 trial establishing nivolumab plus ipilimumab as first line treatment in unresectable PM. Nevertheless, real-world applicability as well as differential benefit of immunotherapy according to histologic are areas of active debate. In addition, increased incidence of immune-related adverse events (IRAEs) and high discontinuation rates highlight the need for careful patient selection. While ICIs represent a significant advancement in PM treatment, ongoing research is necessary to refine their use, potentially through biomarker-informed approaches, and manage associated toxicities. This review highlights the evolving landscape of immunotherapy and associated controversies in PM
Targeting PIKfyve-driven lipid metabolism in pancreatic cancer
Get PDFPancreatic ductal adenocarcinoma (PDAC) subsists in a nutrient-deregulated microenvironment, making it particularly susceptible to treatments that interfere with cancer metabolism1, 2. For example, PDAC uses, and is dependent on, high levels of autophagy and other lysosomal processes3, 4–5. Although targeting these pathways has shown potential in preclinical studies, progress has been hampered by the difficulty in identifying and characterizing favourable targets for drug development6. Here, we characterize PIKfyve, a lipid kinase that is integral to lysosomal functioning7, as a targetable vulnerability in PDAC. Using a genetically engineered mouse model, we established that PIKfyve is essential to PDAC progression. Furthermore, through comprehensive metabolic analyses, we found that PIKfyve inhibition forces PDAC to upregulate a distinct transcriptional and metabolic program favouring de novo lipid synthesis. In PDAC, the KRAS–MAPK signalling pathway is a primary driver of de novo lipid synthesis. Accordingly, simultaneously targeting PIKfyve and KRAS–MAPK resulted in the elimination of the tumour burden in numerous preclinical human and mouse models. Taken together, these studies indicate that disrupting lipid metabolism through PIKfyve inhibition induces synthetic lethality in conjunction with KRAS–MAPK-directed therapies for PDAC
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