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2 results on '"Alexandra Flores"'

1. Machine Learning Quantification of Amyloid Deposits in Histological Images of Ligamentum Flavum

Author

Andy Y. Wang, Vaishnavi Sharma, Harleen Saini, Joseph N. Tingen, Alexandra Flores, Diang Liu, Mina G. Safain, James Kryzanski, Ellen D. McPhail, Knarik Arkun, and Ron I. Riesenburger

Subjects
Wild-type transthyretin amyloid, Ligamentum flavum, Trainable Weka Segmentation, Machine learning, Color thresholding, Computer applications to medicine. Medical informatics, R858-859.7, Pathology, RB1-214
Abstract

Wild-type transthyretin amyloidosis (ATTRwt) is an underdiagnosed and potentially fatal disease. Interestingly, ATTRwt deposits have been found to deposit in the ligamentum flavum (LF) of patients with lumbar spinal stenosis before the development of systemic and cardiac amyloidosis. In order to study this phenomenon and its possible relationship with LF thickening and systemic amyloidosis, a precise method of quantifying amyloid deposits in histological slides of LF is critical. However, such a method is currently unavailable. Here, we present a machine learning quantification method with Trainable Weka Segmentation (TWS) to assess amyloid deposition in histological slides of LF. Images of ligamentum flavum specimens stained with Congo red are obtained from spinal stenosis patients undergoing laminectomies and confirmed to be positive for ATTRwt. Amyloid deposits in these specimens are classified and quantified by TWS through training the algorithm via user-directed annotations on images of LF. TWS can also be automated through exposure to a set of training images with user-directed annotations, and then applied] to a set of new images without additional annotations. Additional methods of color thresholding and manual segmentation are also used on these images for comparison to TWS. We develop the use of TWS in images of LF and demonstrate its potential for automated quantification. TWS is strongly correlated with manual segmentation in the training set of images with user-directed annotations (R = 0.98; p = 0.0033) as well as in the application set of images where TWS was automated (R = 0.94; p = 0.016). Color thresholding was weakly correlated with manual segmentation in the training set of images (R = 0.78; p = 0.12) and in the application set of images (R = 0.65; p = 0.23). TWS machine learning closely correlates with the gold-standard comparator of manual segmentation and outperforms the color thresholding method. This novel machine learning method to quantify amyloid deposition in histological slides of ligamentum flavum is a precise, objective, accessible, high throughput, and powerful tool that will hopefully pave the way towards future research and clinical applications.

Published
2022
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2. The prognostic Role of hepatic venous pressure gradient in cirrhotic patients undergoing elective extrahepatic surgery

Author

Antoni M. de Lacy, Annalisa Berzigotti, Josep Fuster, Juan G. Abraldes, Enric Reverter, Annabel Blasi, W. Debernardi-Venon, Agustín Albillos, Jaume Bosch, Javier Martínez, Graciela Martínez-Pallí, Fanny Turon, Elba Llop, Isabel Cirera, Juan Carlos García-Valdecasas, Virginia Hernández-Gea, Alexandra Flores, and Joan Carles García-Pagán

Subjects
Liver Cirrhosis, Male, Risk, 0301 basic medicine, medicine.medical_specialty, Cirrhosis, Cirrosi hepàtica, Post-operative complications, Portal venous pressure, Pressió venosa, 03 medical and health sciences, 0302 clinical medicine, Hypertension, Portal, medicine, Mortalitat, Humans, Decompensation, Prospective Studies, Mortality, Portal hypertension, Digestive System Surgical Procedures, Aged, Retrospective Studies, Hepatology, business.industry, Mortality rate, Hemodynamics, Modeling, Middle Aged, medicine.disease, Prognosis, Portal Pressure, Surgery, Transplantation, Treatment Outcome, 030104 developmental biology, Hepatic cirrhosis, Elective Surgical Procedures, Orthopedic surgery, Venous pressure, Female, 030211 gastroenterology & hepatology, Liver function, HVPG, business, Surgical risk, Follow-Up Studies
Abstract

Background & Aims: Surgery in cirrhosis is associated with a high morbidity and mortality. Retrospectively reported prognostic factors include emergency procedures, liver function (MELD/Child-Pugh scores) and portal hypertension (assessed by indirect markers). This study assessed the prognostic role of hepatic venous pressure gradient (HVPG) and other variables in elective extrahepatic surgery in patients with cirrhosis. Methods: A total of 140 patients with cirrhosis (Child-Pugh A/B/C: 59/37/4%), who were due to have elective extrahepatic surgery (121 abdominal; 9 cardiovascular/thoracic; 10 orthopedic and others), were prospectively included in 4 centers (2002–2011). Hepatic and systemic hemodynamics (HVPG, indocyanine green clearance, pulmonary artery catheterization) were assessed prior to surgery, and clinical and laboratory data were collected. Patients were followed-up for 1 year and mortality, transplantation, morbidity and post-surgical decompensation were studied. Results: Ninety-day and 1-year mortality rates were 8% and 17%, respectively. Variables independently associated with 1-year mortality were ASA class (American Society of Anesthesiologists), high-risk surgery (defined as open abdominal and cardiovascular/thoracic) and HVPG. These variables closely predicted 90-, 180- and 365-day mortality (C-statistic >0.8). HVPG values >16 mmHg were independently associated with mortality and values ≥20 mmHg identified a subgroup at very high risk of death (44%). Twenty-four patients presented persistent or de novo decompensation at 3 months. Low body mass index, Child-Pugh class and high-risk surgery were associated with death or decompensation. No patient with HVPG 0.63 developed decompensation. Conclusions: ASA class, HVPG and high-risk surgery were prognostic factors of 1-year mortality in cirrhotic patients undergoing elective extrahepatic surgery. HVPG values >16 mmHg, especially ≥20 mmHg, were associated with a high risk of post-surgical mortality. Lay summary: The hepatic venous pressure gradient is associated with outcomes in patients with cirrhosis undergoing elective extrahepatic surgery. It enables a better stratification of risk in these patients and provides the foundations for potential interventions to improve post-surgical outcomes.

Published
2019

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