Epithelioid Vascular Lesions: The Differential Diagnosis and Approach in Cytology and Small Biopsies.

Vascular neoplasms are rare tumors with a multitude of clinical presentations and behavior, which make accurate identification and subclassification challenging on limited small biopsies. Within the spectrum of these lesions, the ones with epithelioid morphology, such as epithelioid hemangioendothelioma and epithelioid angiosarcoma, are particularly challenging given the morphologic overlap with nonvascular lesions and the limited cells due to hemodilution on sampling. Herein, we review the differential diagnosis of epithelioid vascular neoplasms, with a focus on the cytomorphology, differential diagnoses, and ancillary studies that pathologists should be aware of when evaluating small biopsies and aspirates, including novel translocations, and associated monoclonal immunohistochemistry antibodies, that can help in the diagnosis of some of these tumors. Awareness of these morphologic and ancillary study findings in these rare tumors will hopefully allow pathologists to recognize and render-specific diagnoses on limited samples of these challenging lesions.

Antemortem detection of Parkinson's disease pathology in peripheral biopsies using artificial intelligence.

The diagnosis of Parkinson's disease (PD) is challenging at all stages due to variable symptomatology, comorbidities, and mimicking conditions. Postmortem assessment remains the gold standard for a definitive diagnosis. While it is well recognized that PD manifests pathologically in the central nervous system with aggregation of α-synuclein as Lewy bodies and neurites, similar Lewy-type synucleinopathy (LTS) is additionally found in the peripheral nervous system that may be useful as an antemortem biomarker. We have previously found that detection of LTS in submandibular gland (SMG) biopsies is sensitive and specific for advanced PD; however, the sensitivity is suboptimal especially for early-stage disease. Further, visual microscopic assessment of biopsies by a neuropathologist to identify LTS is impractical for large-scale adoption. Here, we trained and validated a convolutional neural network (CNN) for detection of LTS on 283 digital whole slide images (WSI) from 95 unique SMG biopsies. A total of 8,450 LTS and 35,066 background objects were annotated following an inter-rater reliability study with Fleiss Kappa = 0.72. We used transfer learning to train a CNN model to classify image patches (151 × 151 pixels at 20× magnification) with and without the presence of LTS objects. The trained CNN model showed the following performance on image patches: sensitivity: 0.99, specificity: 0.99, precision: 0.81, accuracy: 0.99, and F-1 score: 0.89. We further tested the trained network on 1230 naïve WSI from the same cohort of research subjects comprising 42 PD patients and 14 controls. Logistic regression models trained on features engineered from the CNN predictions on the WSI resulted in sensitivity: 0.71, specificity: 0.65, precision: 0.86, accuracy: 0.69, and F-1 score: 0.76 in predicting clinical PD status, and 0.64 accuracy in predicting PD stage, outperforming expert neuropathologist LTS density scoring in terms of sensitivity but not specificity. These findings demonstrate the practical utility of a CNN detector in screening for LTS, which can translate into a computational tool to facilitate the antemortem tissue-based diagnosis of PD in clinical settings.

Artificial intelligence in neuropathology: deep learning-based assessment of tauopathy.

Accumulation of abnormal tau in neurofibrillary tangles (NFT) occurs in Alzheimer disease (AD) and a spectrum of tauopathies. These tauopathies have diverse and overlapping morphological phenotypes that obscure classification and quantitative assessments. Recently, powerful machine learning-based approaches have emerged, allowing the recognition and quantification of pathological changes from digital images. Here, we applied deep learning to the neuropathological assessment of NFT in postmortem human brain tissue to develop a classifier capable of recognizing and quantifying tau burden. The histopathological material was derived from 22 autopsy brains from patients with tauopathies. We used a custom web-based informatics platform integrated with an in-house information management system to manage whole slide images (WSI) and human expert annotations as ground truth. We utilized fully annotated regions to train a deep learning fully convolutional neural network (FCN) implemented in PyTorch against the human expert annotations. We found that the deep learning framework is capable of identifying and quantifying NFT with a range of staining intensities and diverse morphologies. With our FCN model, we achieved high precision and recall in naive WSI semantic segmentation, correctly identifying tangle objects using a SegNet model trained for 200 epochs. Our FCN is efficient and well suited for the practical application of WSIs with average processing times of 45 min per WSI per GPU, enabling reliable and reproducible large-scale detection of tangles. We measured performance on test data of 50 pre-annotated regions on eight naive WSI across various tauopathies, resulting in the recall, precision, and an F1 score of 0.92, 0.72, and 0.81, respectively. Machine learning is a useful tool for complex pathological assessment of AD and other tauopathies. Using deep learning classifiers, we have the potential to integrate cell- and region-specific annotations with clinical, genetic, and molecular data, providing unbiased data for clinicopathological correlations that will enhance our knowledge of the neurodegeneration.

Methamphetamine Use and Emergency Department Utilization: 20 Years Later.

BACKGROUND: Methamphetamine (MAP) users present to the emergency department (ED) for myriad reasons, including trauma, chest pain, and psychosis. The purpose of this study is to determine how their prevalence, demographics, and resource utilization have changed. METHODS: Retrospective review of MAP patients over 3 months in 2016. Demographics, mode of arrival, presenting complaints, disposition, and concomitant cocaine/ethanol use were compared to a 1996 study at the same ED. RESULTS: 638 MAP-positive patients, 3,013 toxicology screens, and 20,203 ED visits represented an increase in prevalence compared to 1996: 461 MAP-positive patients, 3,102 screens, and 32,156 visits. MAP patients were older compared to the past. Mode of arrival was most frequently by ambulance but at a lower proportion than 1996, as was the proportion of MAP patients with positive cocaine toxicology screens and ethanol coingestion. Admission rate was lower compared to the past, as was discharge to jail. The proportion of MAP patients presenting with blunt trauma was lower compared to the past and higher for chest pain. CONCLUSION: A significant increase in the prevalence of MAP-positive patients was found. Differences in presenting complaints and resource utilization may reflect the shifting demographics of MAP users, as highlighted by an older patient population relative to the past.

Acute Toxicity from Topical Cocaine for Epistaxis: Treatment with Labetalol.

BACKGROUND: Topical cocaine is sometimes used for the treatment of epistaxis, as it has both potent anesthetic and vasoconstrictive properties. Cocaine has unpredictable cardiovascular effects, such as sudden hypertension, tachycardia, coronary arterial vasoconstriction, and dysrhythmia. CASE REPORT: We report a case of acute iatrogenic cardiovascular toxicity from the use of topical cocaine in a 56-year-old man presenting to the Emergency Department with profound epistaxis. To prepare for cauterization and nasal packing, the patient received 4% topical cocaine-soaked nasal pledgets. He became hypertensive, tachypneic, tachycardic, and dysphoric immediately after administration. To directly counter these adverse hyperadrenergic effects, the patient was given 10 mg intravenous labetalol, a mixed ß- and α-blocker. This instantly normalized his vital signs and adverse subjective effects. His epistaxis was successfully treated, and he was discharged 1 h later. WHY SHOULD AN EMERGENCY PHYSICIAN BE AWARE OF THIS?: We believe that emergency physicians should be aware of the unpredictable acute cardiovascular toxicity of topical cocaine. Labetalol represents an effective first-line treatment, which, unlike benzodiazepines, directly counters the pharmacologic effects of cocaine and has no respiratory or sedative side effects. Labetalol, with its mixed ß/α-blocking properties, also mitigates the potential for "unopposed α-stimulation."