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.     

Are Dermatophytid Reactions in Patients with Kerion Celsi Much More Common Than Previously Thought? A Prospective Study

Dermatophytid reactions are secondary eruptions in response to dermatophytosis. Only a few cases demonstrating an association between dermatophytid reactions and tinea capitis have been reported. Dermatophytid reactions were evaluated in patients diagnosed with kerion celsi. Patients admitted to the dermatology clinic of Van Regional Training and Research Hospital between November 22, 2012, and July 1, 2013, diagnosed with kerion celsi were evaluated for dermatophytid reactions. Six girls (32%) and 13 boys (68%) were included in this study. Dermatophytid reactions were detected in 13 of the 19 patients (68%). Seven patients (36.84%) had eczematous patches or plaques and three (15.8%) had papules. Eczematous lesions, papules, and pustules were noted in two patients (10.5%) and one (5.3%) had signs of an angioedema‐like reaction. Dermatophytid reactions in all patients were observed before the initiation of therapy. According to our clinical experiences, dermatophytid reactions in patients with kerion celsi were more common than reported. Eczematous scaly patches or plaques were the most frequently seen forms of dermatophytid in patients with kerion celsi. Dermatophytid reactions may occur before or after initiation of systemic antifungal therapy. Recognition of this reaction is important so that dermatophytids can be distinguished from drug reactions and the decision can be made whether to continue or to stop the systemic antifungal treatment.     

The effect of metoclopramide on gastric emptying in traumatic brain injury.

OBJECTIVE: Gastric paresis in traumatic brain injury (TBI) hinders the effectiveness of enteral support in this patient group. In this study we have investigated the effect of metoclopramide on gastric emptying in TBI patients. METHOD: In this prospective, randomized, controlled, double-blind study, 19 TBI patients with Glasgow Coma Scale scores of 3-11 were included. In all patients, enteral nutrition was commenced with a nasogastric feeding tube within 48 hours of trauma. Patients were randomized into two groups. In the metoclopramide (M) group, 10 mg metoclopramide was delivered intravenously three times daily for 5 days. In the control (C) group, an equal volume of saline was administered. Besides demographics, gastric emptying according to a paracetamol absorption test at days 0 and 5, time to reach target nutritional requirements, gastric residues, intolerance to feeding, nutritional complications, and clinical outcomes were recorded for each patient. RESULTS: The gastric residue rates were 2.7+/-7.4 mL and 8.1+/-17.7 mL per 100 patient days for groups C and M respectively (p=0.408). Similarly, feeding intolerance and complication rates did not significantly differ between groups C and M, (respectively p=0.543 and 0.930). Gastric emptying parameters also were similar between the study groups. CONCLUSION: We were unable to document any advantage to using metoclopramide in TBI patients. Simple intragastric enteral feeding with close monitoring of the possible complications seems to be sufficient with acceptable morbidity rates.     

Cerebellar abscess and syringomyelia due to isoniazid-resistant Mycobacterium tuberculosis.

A 19-year-old immunocompetent man was admitted to hospital with diplopia, nausea, vomiting and change in mental status. The patient had a history of tuberculous meningitis that was diagnosed at another hospital 6 months before the present admission, and at that time anti-tuberculosis treatment was initiated using a first-line drug combination. A computed tomography (CT) scan of the brain revealed non-communicating hydrocephalus. A ventriculo-peritoneal shunt was inserted surgically. Two months later, the patient was hospitalized again for fever, dysphagia and left hemiparesis. At that time, his cranial CT findings were within normal limits; however, magnetic resonance imaging (MRI) revealed an irregular multilocular peripheral contrast-enhancing lesion in the posterior fossa. The abscess was surgically drained. The presence of acid-fast bacilli in the abscess material was demonstrated by Ziehl-Neelsen staining. Mycobacterium tuberculosis grew on Lowenstein-Jensen culture medium, and the strain was found to be resistant to isoniazid. One month after the operation, the patient became quadriparetic. Cervical MRI revealed a cervico-thoracic syringomyelitic cavity, after which a syringoperitoneal shunt was placed. Treatment with four drugs was continued for 10 months, and then treatment with three drugs for a total period of 18 months. The patient recovered, with residual quadriparesis. Even though very rare, isoniazid-resistant M. tuberculosis may be the causative agent of progressive tuberculosis.     

Rheumatoid arthritis and membranoproliferative glomerulonephritis: an unusual case

SUMMARY: Renal involvement is not uncommon in rheumatoid arthritis (RA). Many RA patients have renal dysfunction either secondary to the drugs used to treat arthritis or because of the chronic inflammation. Renal pathologies have often included amyloidosis, drug-related renal disease and mesangial glomerulonephritis. However, membranoproliferative glomerulonephritis has only been rarely reported. We report a case of rheumatoid arthritis associated with membranoproliferative glomerulonephritis that rapidly progressed to end-stage renal disease.     

Optimization of self-reference thermometry using complex field estimation.

Referenceless, or self-reference, thermometry is a technique for mapping temperature differences in the region of interest (ROI) using the baseline phase estimated by extrapolating the field in the surrounding region for estimation (RFE) and subtracting the estimated baseline from the measured field. In the present work a self-reference technique based on complex field estimation using 2D polynomials comprising complex-valued coefficients was proposed and optimized. Numerical simulations with a Gaussian-profiled phase distribution demonstrated that the ROI radius had to be 2.3-2.5 times the standard deviation (SD) of the Gaussian function in order to keep the error below 8% of the peak phase change. The area ratio between the ROI and the RFE had to be larger than 2.0 to maintain the error level. Based on the simulations, and phantom and volunteer experiments, the complex-based method with independently optimized polynomial orders for the two spatial dimensions was compared with the phase-based method using the similar-order optimization strategy. The complex-based method appeared to be useful when phase unwrapping was not removed. Otherwise, the phase-based method yielded equivalent results with less polynomial orders.     

Intracoronary shunt reduces postoperative troponin leaks: a prospective randomized study.

OBJECTIVE: The purpose of this study was to evaluate whether intracoronary shunt usage reduced the myocardial damage on the basis of the cardiac markers when compared with the shuntless anastomosis in off-pump coronary artery bypass grafting (OPCABG) surgery of isolated left anterior descending artery lesions. METHODS: Forty patients who had stable angina with isolated left anterior descending (LAD) coronary artery lesion undergoing OPCABG surgery were randomized into two groups. Shunt group consisted of 20 patients who had OPCABG using intracoronary shunt, whereas the shuntless group consisted of 20 patients who underwent OPCABG without using intracoronary shunt. Cardiac troponin I, CK, and CK-MB before and 24h after the surgery were assessed in the groups. RESULTS: There were no deaths in the study. The two groups were similar with respect to sex and age. Duration of LIMA-LAD anastomosis was significantly higher in the shunt group (p=0.01). There was no significant difference between the groups concerning the preoperative and postoperative CK and CK-MB levels. The preoperative troponin I levels of the groups were not different (p=0.238; NS), whereas postoperative levels of this marker was significantly higher in the shuntless group (p=0.003). CONCLUSION: Intracoronary shunt reduced the postoperative troponin I levels significantly, so it may be indicated in the patients who are thought to be susceptible to transient ischemia.