A Stacked Generalization of 3D Orthogonal Deep Learning Convolutional Neural Networks for Improved Detection of White Matter Hyperintensities in 3D FLAIR Images

BACKGROUND AND PURPOSE:Accurate and reliable detection of white matter hyperintensities and their volume quantification can provide valuable clinical information to assess neurologic disease progression. In this work, a stacked generalization ensemble of orthogonal 3D convolutional neural networks, StackGen-Net, is explored for improving automated detection of white matter hyperintensities in 3D T2-FLAIR images.MATERIALS AND METHODS:Individual convolutional neural networks in StackGen-Net were trained on 2.5D patches from orthogonal reformatting of 3D-FLAIR (n = 21) to yield white matter hyperintensity posteriors. A meta convolutional neural network was trained to learn the functional mapping from orthogonal white matter hyperintensity posteriors to the final white matter hyperintensity prediction. The impact of training data and architecture choices on white matter hyperintensity segmentation performance was systematically evaluated on a test cohort (n = 9). The segmentation performance of StackGen-Net was compared with state-of-the-art convolutional neural network techniques on an independent test cohort from the Alzheimer’s Disease Neuroimaging Initiative-3 (n = 20).RESULTS:StackGen-Net outperformed individual convolutional neural networks in the ensemble and their combination using averaging or majority voting. In a comparison with state-of-the-art white matter hyperintensity segmentation techniques, StackGen-Net achieved a significantly higher Dice score (0.76 [SD, 0.08], F1-lesion (0.74 [SD, 0.13]), and area under precision-recall curve (0.84 [SD, 0.09]), and the lowest absolute volume difference (13.3% [SD, 9.1%]). StackGen-Net performance in Dice scores (median = 0.74) did not significantly differ (P = .22) from interobserver (median = 0.73) variability between 2 experienced neuroradiologists. We found no significant difference (P = .15) in white matter hyperintensity lesion volumes from StackGen-Net predictions and ground truth annotations.CONCLUSIONS:A stacked generalization of convolutional neural networks, utilizing multiplanar lesion information using 2.5D spatial context, greatly improved the segmentation performance of StackGen-Net compared with traditional ensemble techniques and some state-of-the-art deep learning models for 3D-FLAIR.

White matter hyperintensities (WMHs) correspond to pathologic features of axonal degeneration, demyelination, and gliosis observed within cerebral white matter.¹ Clinically, the extent of WMHs in the brain has been associated with cognitive impairment, Alzheimer’s disease and vascular dementia, and increased risk of stroke.^2,3 The detection and quantification of WMH volumes to monitor lesion burden evolution and its correlation with clinical outcomes have been of interest in clinical research.^4,5 Although the extent of WMHs can be visually scored,⁶ the categoric nature of such scoring systems makes quantitative evaluation of disease progression difficult. Manually segmenting WMHs is tedious, prone to inter- and intraobserver variability, and is, in most cases, impractical. Thus, there is an increased interest in developing fast, accurate, and reliable computer-aided automated techniques for WMH segmentation.Convolutional neural network (CNN)-based approaches have been successful in several semantic segmentation tasks in medical imaging.⁷ Recent works have proposed using deep learning–based methods for segmenting WMHs using 2D-FLAIR images.^8-11 More recently, a WMH segmentation challenge¹² was also organized (http://wmh.isi.uu.nl/) to facilitate comparison of automated segmentation of WMHs of presumed vascular origin in 2D multislice T2-FLAIR images. Architectures that used an ensemble of separately trained CNNs showed promising results in this challenge, with 3 of the top 5 winners using ensemble-based techniques.¹²Conventional 2D-FLAIR images are typically acquired with thick slices (3–4 mm) and possible slice gaps. Partial volume effects from a thick slice are likely to affect the detection of smaller lesions, both in-plane and out-of-plane. 3D-FLAIR images, with isotropic resolution, have been shown to achieve higher resolution and contrast-to-noise ratio¹³ and have shown promising results in MS lesion detection using 3D CNNs.¹⁴ Additionally, the isotropic resolution enables viewing and evaluation of the images in multiple planes. This multiplanar reformatting of 3D-FLAIR without the use of interpolating kernels is only possible due to the isotropic nature of the acquisition. Network architectures that use information from the 3 orthogonal views have been explored in recent works for CNN-based segmentation of 3D MR imaging data.¹⁵ The use of data from multiple planes allows more spatial context during training without the computational burden associated with full 3D training.¹⁶ The use of 3 orthogonal views simultaneously mirrors how humans approach this segmentation task.Ensembles of CNNs have been shown to average away the variances in the solution and the choice of model- and configuration-specific behaviors of CNNs.¹⁷ Traditionally, the solutions from these separately trained CNNs are combined by averaging or using a majority consensus. In this work, we propose the use of a stacked generalization framework (StackGen-Net) for combining multiplanar lesion information from 3D CNN ensembles to improve the detection of WMH lesions in 3D-FLAIR. A stacked generalization¹⁸ framework learns to combine solutions from individual CNNs in the ensemble. We systematically evaluated the performance of this framework and compared it with traditional ensemble techniques, such as averaging or majority voting, and state-of-the-art deep learning techniques.     

Melatonin reduces oxidative stress and improves vascular function in pulmonary hypertensive newborn sheep

Pulmonary hypertension of the newborn (PHN) constitutes a critical condition with severe cardiovascular and neurological consequences. One of its main causes is hypoxia during gestation, and thus, it is a public health concern in populations living above 2500 m. Although some mechanisms are recognized, the pathophysiological facts that lead to PHN are not fully understood, which explains the lack of an effective treatment. Oxidative stress is one of the proposed mechanisms inducing pulmonary vascular dysfunction and PHN. Therefore, we assessed whether melatonin, a potent antioxidant, improves pulmonary vascular function. Twelve newborn sheep were gestated, born, and raised at 3600 meters. At 3 days old, lambs were catheterized and daily cardiovascular measurements were recorded. Lambs were divided into two groups, one received daily vehicle as control and another received daily melatonin (1 mg/kg/d), for 8 days. At 11 days old, lung tissue and small pulmonary arteries (SPA) were collected. Melatonin decreased pulmonary pressure and resistance for the first 3 days of treatment. Further, melatonin significantly improved the vasodilator function of SPA, enhancing the endothelial‐ and muscular‐dependent pathways. This was associated with an enhanced nitric oxide‐dependent and nitric oxide independent vasodilator components and with increased nitric oxide bioavailability in lung tissue. Further, melatonin reduced the pulmonary oxidative stress markers and increased enzymatic and nonenzymatic antioxidant capacity. Finally, these effects were associated with an increase of lumen diameter and a mild decrease in the wall of the pulmonary arteries. These outcomes support the use of melatonin as an adjuvant in the treatment for PHN.     

Systematic review of drug–drug interactions between rifamycins and anticoagulant and antiplatelet agents and considerations for management

Rifamycins (rifampin, rifabutin, and rifapentine) play an essential role in the treatment of mycobacterial and some nonmycobacterial infections. They also induce the activity of various drug transporting and metabolizing enzymes, which can impact the concentrations and efficacy of substrates. Many anticoagulant and antiplatelet (AC/AP) agents are substrates of these enzymes and have narrow therapeutic indices, leading to risks of thrombosis or bleeding when coadministered with rifamycins. The objective of this systematic review was to evaluate the effects on AC/AP pharmacokinetics, laboratory markers, and clinical safety and efficacy of combined use with rifamycins. A systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidance was performed. The PubMed, Embase, and Web of Science databases were queried for English-language reports on combination use of rifamycins and AC/AP agents from database inception through August 2021. The 29 studies identified examined warfarin (n = 17), direct oral anticoagulants (DOACs) (n = 8), and antiplatelet agents (n = 4) combined with rifampin (n = 28) or rifabutin (n = 1). Eleven studies were case reports or small case series; 14 reported on pharmacokinetic or laboratory markers in healthy volunteers. Rifampin-warfarin combinations led to reductions in warfarin area under the curve (AUC) of 15%–74%, with variability by warfarin isomer and study. Warfarin dose increases of up to 3–5 times prerifampin doses were required to maintain coagulation parameters in the therapeutic range. DOAC AUCs were decreased by 20%–67%, with variability by individual agent and with rifampin versus rifabutin. The active metabolite of clopidogrel increased substantially with rifampin coadministration, whereas prasugrel was largely unaffected and ticagrelor saw decreases. Our review suggests most combinations of AC/AP agents and rifampin are problematic. Further studies are required to determine whether rifabutin or rifapentine could be safe alternatives for coadministration with AC/AP drugs.     

薄层色谱法在当前中药质量标准中的应用探讨

薄层色谱鉴别在历版《中国药典》中的应用经历了从无到有、从少到多的过程；而薄层扫描含量测定在最近几版《中国药典》中的应用比例逐渐降低。随着对中药质量标准体系要求的进一步提高，薄层色谱法的不足之处陆续显现，如仪器普及率低、设备并不简单、结果重复性和稳定性较差、鉴别速度及准确性不及高效液相色谱法、展开剂毒性大等，逐渐不合时宜。在制定中药质量标准时，研究者不应该墨守成规，薄层色谱鉴别也不应该是雷打不动的定性鉴别必备选项。高效液相色谱法具备完全取代薄层色谱法的可行性，薄层色谱法可作为高效液相色谱法的补充。为充分降低检测成本、缩短检测周期、提高鉴别效率，笔者建议中药质量标准体系应该大幅减少薄层色谱鉴别方法的应用，增加高效液相特征图谱鉴定，尽量做到“一个条件，一张图谱”；除非确有必要，《中国药典》等国家质量标准体系应将薄层色谱鉴别作为推荐方法，而非强制标准。     

Pathophysiology and management of sensitive skin: position paper from the special interest group on sensitive skin of the International Forum for the Study of Itch (IFSI)

The special interest group on sensitive skin of the International Forum for the Study of Itch previously defined sensitive skin as a syndrome defined by the occurrence of unpleasant sensations (stinging, burning, pain, pruritus and tingling sensations) in response to stimuli that normally should not provoke such sensations. This additional paper focuses on the pathophysiology and the management of sensitive skin. Sensitive skin is not an immunological disorder but is related to alterations of the skin nervous system. Skin barrier abnormalities are frequently associated, but there is no cause and direct relationship. Further studies are needed to better understand the pathophysiology of sensitive skin – as well as the inducing factors. Avoidance of possible triggering factors and the use of well-tolerated cosmetics, especially those containing inhibitors of unpleasant sensations, might be suggested for patients with sensitive skin. The role of psychosocial factors, such as stress or negative expectations, might be relevant for subgroups of patients. To date, there is no clinical trial supporting the use of topical or systemic drugs in sensitive skin. The published data are not sufficient to reach a consensus on sensitive skin management. In general, patients with sensitive skin require a personalized approach, taking into account various biomedical, neural and psychosocial factors affecting sensitive skin.     

Gastric volvulus and giant Bochdalek hernia in an adult patient that were safely repaired by endoscopic reduction and elective laparoscopic surgery

A Bochdalek hernia (BH) is a congenital abnormality with incomplete closure of the diaphragm. It is usually manifested in infants but rarely in adults. Here, we report an adult patient with gastric volvulus and giant BH that were safely repaired by endoscopic reduction and elective laparoscopic surgery, respectively. A 79-year-old woman presented with left upper abdominal pain but no history of trauma. CT revealed a giant BH with gastric volvulus. After emergency endoscopic reduction of the volvulus, elective laparoscopic repair of the BH was performed. The 8 × 8-cm defect was repaired with interrupted nonabsorbable sutures and a mesh. The patient's postoperative course was uneventful, and no complications or recurrence were observed in the 6 months that followed.