Liver segmentation in MRI: a fully automatic method based on stochastic partitions

There are few fully automated methods for liver segmentation in magnetic resonance images (MRI) despite the benefits of this type of acquisition in comparison to other radiology techniques such as computed tomography (CT). Motivated by medical requirements, liver segmentation in MRI has been carried out. For this purpose, we present a new method for liver segmentation based on the watershed transform and stochastic partitions. The classical watershed over-segmentation is reduced using a marker-controlled algorithm. To improve accuracy of selected contours, the gradient of the original image is successfully enhanced by applying a new variant of stochastic watershed. Moreover, a final classifier is performed in order to obtain the final liver mask. Optimal parameters of the method are tuned using a training dataset and then they are applied to the rest of studies (17 datasets). The obtained results (a Jaccard coefficient of 0.91 +/- 0.02) in comparison to other methods demonstrate that the new variant of stochastic watershed is a robust tool for automatic segmentation of the liver in MRI. (C) 2014 Elsevier Ireland Ltd. All rights reserved.This work has been supported by the MITYC under the project NaRALap (ref. TSI-020100-2009-189), partially by the CDTI under the project ONCOTIC (IDI-20101153), by Ministerio de Educacion y Ciencia Spain, Project Game Teen (TIN2010-20187) projects Consolider-C (SEJ2006-14301/PSIC), "CIBER of Physiopathology of Obesity and Nutrition, an initiative of ISCIII" and Excellence Research Program PROMETEO (Generalitat Valenciana. Conselleria de Educacion, 2008-157). We would like to express our gratitude to the Hospital Clinica Benidorm, for providing the MR datasets and to the radiologist team of Inscanner for the manual segmentation of the MR images.López-Mir, F.; Naranjo Ornedo, V.; Angulo, J.; Alcañiz Raya, ML.; Luna, L. (2014). Liver segmentation in MRI: a fully automatic method based on stochastic partitions. Computer Methods and Programs in Biomedicine. 114(1):11-28. https://doi.org/10.1016/j.cmpb.2013.12.022S1128114

The diagnostic accuracy of US, CT, MRI and 1H-MRS for the evaluation of hepatic steatosis compared with liver biopsy: a meta-analysis

OBJECTIVE: To meta-analyse the diagnostic accuracy of US, CT, MRI and (1)H-MRS for the evaluation of hepatic steatosis. METHODS: From a comprehensive literature search in MEDLINE, EMBASE, CINAHL and Cochrane (up to November 2009), articles were selected that investigated the diagnostic performance imaging techniques for evaluating hepatic steatosis with histopathology as the reference standard. Cut-off values for the presence of steatosis on liver biopsy were subdivided into four groups: (1) >0, >2 and >5% steatosis; (2) >10, >15 and >20%; (3) >25, >30 and >33%; (4) >50, >60 and >66%. Per group, summary estimates for sensitivity and specificity were calculated. The natural-logarithm of the diagnostic odds ratio (lnDOR) was used as a single indicator of test performance. RESULTS: 46 articles were included. Mean sensitivity estimates for subgroups were 73.3-90.5% (US), 46.1-72.0% (CT), 82.0-97.4% (MRI) and 72.7-88.5% ((1)H-MRS). Mean specificity ranges were 69.6-85.2% (US), 88.1-94.6% (CT), 76.1-95.3% (MRI) and 92.0-95.7% ((1)H-MRS). Overall performance (lnDOR) of MRI and (1)H-MRS was better than that for US and CT for all subgroups, with significant differences in groups 1 and 2. CONCLUSION: MRI and (1)H-MRS can be considered techniques of choice for accurate evaluation of hepatic steatosi

Applications of artificial intelligence and machine learning for the hip and knee surgeon: current state and implications for the future

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Fast Timing Detectors and Applications in Cosmic Ray Physics and Medical Science

We use fast silicon detectors and the fast sampling method originally developed for high energy physics for two applications: cosmic ray measurements in collaboration with NASA and dose measurements during flash beam cancer treatment. The cosmic ray measurement will benefit from the fast sampling method to measure the Bragg peak where the particle stops in the silicon detector and the dose measurement is performed by counting the number of particles that enter the detector

Simultaneous assessment of liver volume and whole liver fat content : a step towards one-stop shop preoperative MRI protocol

Objective: The purpose of this study was to evaluate the ability of a whole liver volume (WLV) segmentation algorithm to measure fat fraction (FF). Methods: Twenty consecutive patients with histologically proven fatty liver disease underwent dual-echo in-phase/out-of-phase MRI and magnetic resonance spectroscopy (MRS) at 1.5 T. Two readers independently performed semiautomatic 3D liver segmentation on the out-of-phase sequences using an active contour model. FF was calculated for voxels, segments and WLV. Segmentation inter-observer reproducibility was assessed by intra-class correlation coefficient (ICC) for WLV and FF. Fat fraction correlation and agreement as determined by histology, MRS and MRI were determined. Results: ICC was 0.999 (95% CI: 0.999-1, P<0.001) for WLV FF calculation and 0.996 (95% CI: 0.990-0.998, P<0.001) for whole liver volume calculations. Strong correlations were found between FF measured by histology, MRS and WLV-MRI. A Bland-Altman analysis showed a good agreement between FF measured by MRS and WLV-MRI. No systematic variations of FF was found between segments when analyzed by ANOVA (F = 1.78, P= 0.096). Conclusion: This study shows that a reproducible whole liver volume segmentation method to measure fat fraction can be performed. This strategy may be integrated to a “one-stop shop” protocol in liver surgery planning

Necro-inflammatory activity grading in chronic viral hepatitis with three-dimensional multifrequency MR elastography

International audienceAbstract The purpose of this study was to assess the diagnostic value of multifrequency MR elastography for grading necro-inflammation in the liver. Fifty participants with chronic hepatitis B or C were recruited for this institutional review board-approved study. Their liver was examined with multifrequency MR elastography. The storage, shear and loss moduli, and the damping ratio were measured at 56 Hz. The multifrequency wave dispersion coefficient of the shear modulus was calculated. The measurements were compared to reference markers of necro-inflammation and fibrosis with Spearman correlations and multiple regression analysis. Diagnostic accuracy was assessed. At multiple regression analysis, necro-inflammation was the only determinant of the multifrequency dispersion coefficient, whereas fibrosis was the only determinant of the storage, loss and shear moduli. The multifrequency dispersion coefficient had the largest AUC for necro-inflammatory activity A ≥ 2 [0.84 (0.71–0.93) vs. storage modulus AUC: 0.65 (0.50–0.79), p = 0.03], whereas the storage modulus had the largest AUC for fibrosis F ≥ 2 [AUC (95% confidence intervals) 0.91 (0.79–0.98)] and cirrhosis F4 [0.97 (0.88–1.00)]. The measurement of the multifrequency dispersion coefficient at three-dimensional MR elastography has the potential to grade liver necro-inflammation in patients with chronic vial hepatitis

Assessment of liver iron overload by 3 T MRI

International audiencePurpose - To evaluate the performance and limitations of the signal intensity ratio method for quantifying liver iron overload at 3 T. Methods - Institutional review board approval and written informed consent from all participants were obtained. One hundred and five patients were included prospectively. All patients underwent a liver biopsy with biochemical assessment of hepatic iron concentration and a 3 T MRI scan with 5 breath-hold single-echo gradient-echo sequences. Linear correlation between liver-to-muscle signal intensity ratio and liver iron concentration was calculated. The algorithm for calculating magnetic resonance hepatic iron concentration was adapted from the method described by Gandon et al. with echo times divided by 2. Sensitivity and specificity were calculated. Results - Five patients were excluded (coil selection failure or missing sequence) and 100 patients were analyzed, 64 men and 36 women, 52 ± 13.3 years old, with a biochemical hepatic iron concentration range of 0-630 µmol/g. Linear correlation between biochemical hepatic iron concentration and MR-hepatic iron concentration was excellent with a correlation coefficient = 0.96, p < 0.0001. Sensitivity and specificity were, respectively, 83% (0.70-0.92) and 96% (0.85-0.99), with a pathological threshold of 36 µmol/g. Conclusion - Signal intensity ratio method for quantifying liver iron overload can be used at 3 T with echo times divided by 2

Quantification of triglyceride fatty acid composition in the liver, subcutaneous and visceral adipose tissue with 3.0T MRI

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