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Wang-Shu Zhu Si-Ya Shi Ze-Hong Yang Chao Song Jun Shen 《World journal of gastroenterology : WJG》2020,26(11):1208-1220
BACKGROUND Postoperative liver failure is the most severe complication in cirrhotic patients with hepatocellular carcinoma(HCC) after major hepatectomy. Current available clinical indexes predicting postoperative residual liver function are not sufficiently accurate.AIM To determine a radiomics model based on preoperative gadoxetic acid-enhanced magnetic resonance imaging for predicting liver failure in cirrhotic patients with HCC after major hepatectomy.METHODS For this retrospective study, a radiomics-based model was developed based on preoperative hepatobiliary phase gadoxetic acid-enhanced magnetic resonance images in 101 patients with HCC between June 2012 and June 2018. Sixty-one radiomic features were extracted from hepatobiliary phase images and selected by the least absolute shrinkage and selection operator method to construct a radiomics signature. A clinical prediction model, and radiomics-based model incorporating significant clinical indexes and radiomics signature were built using multivariable logistic regression analysis. The integrated radiomics-based model was presented as a radiomics nomogram. The performances of clinical prediction model, radiomics signature, and radiomics-based model for predicting post-operative liver failure were determined using receiver operating characteristics curve, calibration curve, and decision curve analyses.RESULTS Five radiomics features from hepatobiliary phase images were selected to construct the radiomics signature. The clinical prediction model, radiomics signature, and radiomics-based model incorporating indocyanine green clearance rate at 15 min and radiomics signature showed favorable performance for predicting postoperative liver failure(area under the curve: 0.809-0.894). The radiomics-based model achieved the highest performance for predicting liver failure(area under the curve: 0.894; 95%CI: 0.823-0.964). The integrated discrimination improvement analysis showed a significant improvement in the accuracy of liver failure prediction when radiomics signature was added to the clinical prediction model(integrated discrimination improvement = 0.117, P =0.002). The calibration curve and an insignificant Hosmer-Lemeshow test statistic(P = 0.841) demonstrated good calibration of the radiomics-based model. The decision curve analysis showed that patients would benefit more from a radiomics-based prediction model than from a clinical prediction model and radiomics signature alone.CONCLUSION A radiomics-based model of preoperative gadoxetic acid–enhanced MRI can be used to predict liver failure in cirrhotic patients with HCC after major hepatectomy. 相似文献
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Martin R. Späth Malte P. Bartram Nicolàs Palacio-Escat K. Johanna R. Hoyer Cedric Debes Fatih Demir Christina B. Schroeter Amrei M. Mandel Franziska Grundmann Giuliano Ciarimboli Andreas Beyer Jayachandran N. Kizhakkedathu Susanne Brodesser Heike Göbel Jan U. Becker Thomas Benzing Bernhard Schermer Martin Höhne Markus M. Rinschen 《Kidney international》2019,95(2):333-349
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Pradeep Balasubramanian M.D. C. R. Srinivas M.D. Pavai Arunachalam M.S. M.Ch. K. S. Thirumurthy M.S. M.Ch. P. R. Rajkumar M.S. M.Ch. H. Manuvidhya M.B.B.S. 《Pediatric dermatology》2015,32(3):e78-e81
We report on a child with several café au lait spots in association with a lumbar lipomeningomyelocele as an apparently new association. Cutaneous markers, the identification of which plays a crucial role in the early diagnosis and management of spinal malformations, can accompany occult spinal dysraphism. Herein we report a case of lumbar lipomeningomyelocele associated with an overlying café au lait spot that served as a marker of occult spinal dysraphism. The patient also had segmental café au lait spots on the face, making the association unique. 相似文献
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Y.R. Song B. Wu Y.T. Yang J. Chen L.J. Zhang Z.W. Zhang H.Y. Shi C.L. Huang J.X. Pan P. Xie 《Brazilian journal of medical and biological research》2015,48(11):973-982
Bipolar disorder (BD) is a common psychiatric mood disorder affecting more than 1-2%
of the general population of different European countries. Unfortunately, there is no
objective laboratory-based test to aid BD diagnosis or monitor its progression, and
little is known about the molecular basis of BD. Here, we performed a comparative
proteomic study to identify differentially expressed plasma proteins in various BD
mood states (depressed BD, manic BD, and euthymic BD) relative to healthy controls. A
total of 10 euthymic BD, 20 depressed BD, 15 manic BD, and 20 demographically matched
healthy control subjects were recruited. Seven high-abundance proteins were
immunodepleted in plasma samples from the 4 experimental groups, which were then
subjected to proteome-wide expression profiling by two-dimensional electrophoresis
and matrix-assisted laser desorption/ionization-time-of-flight/time-of-flight tandem
mass spectrometry. Proteomic results were validated by immunoblotting and
bioinformatically analyzed using MetaCore. From a total of 32 proteins identified
with 1.5-fold changes in expression compared with healthy controls, 16 proteins were
perturbed in BD independent of mood state, while 16 proteins were specifically
associated with particular BD mood states. Two mood-independent differential
proteins, apolipoprotein (Apo) A1 and Apo L1, suggest that BD pathophysiology may be
associated with early perturbations in lipid metabolism. Moreover, down-regulation of
one mood-dependent protein, carbonic anhydrase 1 (CA-1), suggests it may be involved
in the pathophysiology of depressive episodes in BD. Thus, BD pathophysiology may be
associated with early perturbations in lipid metabolism that are independent of mood
state, while CA-1 may be involved in the pathophysiology of depressive episodes. 相似文献