Chandrapur Call girls 8617370543 Provides all area service COD available
Castera du pitie 17 janvier 2012 selection
1. Alternatives à la PBH :
mesure de l’élasticité
hépatique
Laurent CASTERA
Service d’Hépatologie,
Hôpital Beaujon, Université Paris VII
DU Hépatites Virales Cytokines et Antiviraux
Pitie, Paris, 17 Janvier 2012
6. over a large bandwidth. In parallel, SWS provides
a refined analysis in a larger box of these dispersive prop-
Elasticité hépatique
erties of tissues by estimating frequency dependence of
the shear wave speed.
Statistical methods
Supersonic shear Imaging The diagnosis performance of FS and SSI are
compared by using receiver operating characteristic
(ROC) curves and box-and-whisker curves on the same
1366 Ultrasound in Medicine and Biology cohort. A patient was assessed as positive or negative ac-
Volume 37, Number 9, 2011
cording to whether the noninvasive marker value was
Contrary to FS, as vibration induced by the radiation greater than or less than to a given cutoff value, respec-
force creates a short transient excitation, the frequency tively. Connected with any cutoff value is the probability
bandwidth of the generated shear wave is large, typically of a true positive (sensitivity) and the probability of a true
ranging from 60 to 600 Hz (Fig. 3). Such wideband negative (specificity). The ROC curve is a plot of
‘‘shear wave spectroscopy’’ can give a refined analysis sensitivity vs. (1-specificity) for all possible cutoff values.
of the complex mechanical behavior of tissue. As shown The most commonly used index of accuracy is the area
in Figure 3, the shear wave dispersion law can be assessed under the ROC curve (AUROC), with values close to
from displacement movies in the region-of-interest. 1.0 indicating high diagnosis accuracy. Optimal cutoff
Thus, the global elasticity imaged by SSI makes use values for liver stiffness were chosen to maximize the
of higher frequency content and is also influenced by the sum of sensitivity and specificity and positive and nega-
dispersive properties of the liver tissues because it aver- tive predictive values were computed for these cutoff
ages the full mechanical response of the liver tissues values. By using these cutoff values, the agreement
between FS and SSI was evaluated. Statistical analyses
over a large bandwidth. In parallel, SWS provides
were performed with Matlab R2007a software (Math-
a refined analysis in a larger box of these dispersive prop-
works, Natick, MA, USA) using the statistical analysis
erties of tissues by estimating frequency dependence of
toolbox and Medcalc software (Mariakerke, Belgium).
the shear wave speed.
RESULTS
Statistical methods
The diagnosis performance of FS and SSI are Liver stiffness mapping using SSI
compared by using receiver operating characteristic The Young’s modulus corresponding to the stiffness
(ROC) curves and box-and-whisker curves on the same of the liver tissues are presented for 4 patients in Figure 4.
cohort. A patient was assessed as positive or negative ac- The elasticity mapping is superimposed with the corre-
cording to whether the noninvasive marker value was sponding B-mode images on which the fat and muscle
greater than or less than to a given cutoff value, respec- region are well differentiated from the liver region and
tively. Connected with any cutoff value is the probability the elasticity is mapped only in the liver region. Fig. 4. Bidimensional liver elasticity maps assessed using the
of a true positive (sensitivity) and the probability of a true Figure 4a, b, c and d show the elasticity mapping et al. UMB 2009; 35: technique superimposed to
supersonic shear imaging (SSI)
Muller for the corresponding B-scan. The Young’s modulus representing
219-29
negative (specificity). The ROC curve is a plot of patients who have been classified as predicted fibrosis the liver stiffness is represented in color levels. (a): patient
sensitivity vs. (1-specificity) for all possible cutoff values. levels F1, F2, F3 and F4, respectively.
The median elasticity derived from these maps areal. UMB 2011;37: 1361-73 (d): patient
Bavu et 59 - F1. E 5 4.78 6 0.83 kPa (b): patient 51 - F2. E 5 10.64 6
The most commonly used index of accuracy is the area 1.10 kPa (c): patient 39 - F3. E 5 14.52 6 2.20 kPa
22 - F4. E 5 27.43 6 2.64 kPa.
7. Plan
Principe
Performances diagnostiques
Comparaison avec les biomarqueurs
Suivi de la progression de la fibrose
Limites & perspectives
9. Principe
“Plus le foie est dur, plus l’onde se propage vite”
10 5
20
Depth (mm)
30
0
40
50
60 -5
0 20 40 60 %
Time (ms)
VS = 1.0 m/s
S 3.0
E = 27.0kPa
E = 3.0 kPa
F4
F0
Sandrin et al. UMB 2003; 12: 1705-13
10. Mesure de l’élasticité hépatique
Normale
5.5 15 65
3 75 kPa
Roulot et al. J Hepatol 2008; 48: 606-13
11. FibroScan en pratique
Indolore
Rapide (5 min)
Lit du malade/
consultation
Résultats immédiats
Formation courte
(100 exam.)
12. Interprétation des résultats
« recommandations du constructeur »
10 mesures valides
IQR < 30% médiane
Taux de succès > 60%
Castera, Forns & Alberti. J Hepatol 2008; 48: 835-47
13. Plan
Principe
Performances diagnostiques
Comparaison avec les biomarqueurs
Suivi de la progression de la fibrose
Limites & perspectives
14. Objectifs diagnostiques
F0 F1 F2 F3 F4
Indication du traitement antiviral
Dépistage des varices oesophagiennes
Dépistage du carcinome hépatocellulaire
15. PBH: un « gold » standard imparfait
0.99
Bedossa & Carrat. J Hepatol 2009; 50: 1-3. Mehta et al. J Hepatol 2009; 50: 36-41.
16. Hépatite C
Performance Diagnostique
100
Elasticity (kPa)
10
1
F1 F2 F3 F4
Fibrosis stage (Metavir) Fibrosis stage
Fibrosis stage (Metavir)
N = 251 CHC patients N = 183 CHC patients
Ziol et al. Hepatology 2005; 41: 48-54
Castera et al. Gastroenterology 2005; 128: 343-50.
17. Quantité de fibrose vs. Stade de fibrose
Collagen area (%)
Standish et al. Gut 2006; 55: 569-78.
26. Performance diagnostique pour cirrhose
(n=1007 patients avec CLD, 165 cirrhotiques)
Bien classés 92%
83% 17%
3 14.6 75
F<4 F=4
96% 74%
3.5 % 4.5%
Mal classés Mal classés
Ganne-Carrié et al. Hepatology 2006; 44: 1511-7
27. Performance diagnostique pour cirrhose
(n=1307 patients avec hépatites virales, 180 cirrhotiques)
patients bien classés 87 %
AUROC=0.90
81% 19%
3 12.9 75
F<4 F=4
95% 53%
Degos et al. J Hepatol 2010; 53: 1013-21
28. Plan
Principe
Performances diagnostiques
Comparaison avec les biomarqueurs
Suivi de la progression de la fibrose
Limites & perspectives
29. Comparaison des approches
fibrose significative
P=NS P=NS
Castera et al. Gastroenterology 2005; 128: 343-50.
Degos et al. J Hepatol 2010; 53: 1013-21
30. Comparaison des approches
cirrhose
F0123 vs F4
1,0
FS 0.96
0,8
FT 0.84
APRI 0.82
Sensitivity
0,6
Lok 0.82
0,4 P<0.001
Platelet 0.80
0,2 PI 0.76
AAR 0.67
0,0
0,0
0,2
0,4
0,6
0,8
1,0
1 - Specificity
.
N= 298 CHC patients; F4: 25% Castera et al. J Hepatol 2009; 50: 59-68.
31. Comparaison des approches
cirrhose
P<0.0001
.
N= 1307 patients; F4: 25% Degos et al. J Hepatol 2010; 53: 1013-21
32. Comparaison des approches
cirrhose
JOURNAL OF HEPATOLOGY
Table 3. Performance of blood tests and Fibroscan™ for the diagnosis of cirrhosis (F4).
n = 436* n = 382‡
AUROC 95% CI p Sidak AUROC 95% CI p Sidak
FIBROMETER® 0.89 [0.86;0.93] 0.90 [0.86;0.93]
FIBROTEST® 0.86 [0.83;0.90] 0.325 0.87 [0.82;0.91] 0.321
APRI
ELFG
HEPASCORE®
0.86
0.88
0.89
[0.81;0.91]
[0.83;0.92]
[0.86;0.93]
ZARSKI
0.141
0.883
1.000
0.87
0.87
0.89
[0.82;0.91]
[0.83;0.92]
[0.85;0.92]
0.410
0.860
0.998
FIB4 0.83 [0.76;0.89] 0.018 0.84 [0.77;0.90] 0.069
FIBROSCAN™ - - - 0.93 [0.89;0.96] 0.559
(interpretable results)
⁄
CHC patients having all blood tests; àCHC patients with all the tests and interpretable Fibroscan™.
superior to the best blood tests or Fibroscan™ alone in the ‘‘per- classified. This percentage increases to 75% for a length of 25 mm
protocol’’ analysis (382 patients). However, when we considered [3]. Also, a 25 mm biopsy is considered the optimal length for
.
the population of 436 436 patients; to diagnose popula-
N= patients (‘‘intention F4: 14%
accurate liver evaluation. Considering this, in our study a sam-
tion’’) the combination of Fibroscan™ plus a blood test markedly pling error for liver biopsy remains2012; 56:50% of patients
Zarski et al. J Hepatol since only 55-62
33. La combinaison augmente
les performances diagnostiques
Bien
+
classés F≥2:
75%
Marqueurs sériques Elastométrie
Castera et al. Gastroenterology 2005; 128: 343-50.
34. Concordance in world without gold standard:
a new way to increase diagnostic accuracy
Poynard et al. Plos One 2008
35. La combinaison augmente
les performances diagnostiques
N= 729 patients with CHC
Boursier et al. Am J Gastroenterol 2011; 106: 1255-63
39. Plan
Principe
Performances diagnostiques
Comparaison avec les biomarqueurs
Suivi de la progression de la fibrose
Limites & perspectives
40. La cirrhose: une entité hétérogène ?
F0 F1 F2 F3 F4
Complications cliniques HVPG>10
Risque significatif de RVO HVPG>12
Garcia-Tsao, Friedman, Iredale & Pinzani. Hepatology 2010; 51: 1444-49
41. Now There Are Many (Stages) Where Before There
Was One: In Search of a Pathophysiological
A-TSAO ET AL.
Classification of Cirrhosis HEPATOLO
Guadalupe Garcia-Tsao,1 Scott Friedman,2 John Iredale,3 and Massimo Pinzani4 HEPATOLOGY, Vol. 51, No. 4, 2010
F
or more than a century and a half, the description changes, and more faithfully reflects its progression, re- hepatic stellate ce
notably activated
of a liver as “cirrhotic” was sufficient to connote versibility and prognosis, ultimately linking broblasts, as well as key cytokines su
these param-
both a pathological and clinical status, and to as- eters to clinically relevant outcomes andgrowth factor and transforming grow
therapeutic
sign the prognosis of a patient with liver disease. How- strategies. The Child-Pugh and Model for End-Stage roles of bone marrow– derived cells a
ever, as our interventions to treat advanced liver disease Liver Disease (MELD) scores are currentlyepithelial-mesenchymal transition a
deployed to
have progressed (e.g., antiviral therapies), the inadequacy define prognosis by modeling hepatic dysfunction, butis unlikely that these sour
tion, but it
do
provide a major contribution to hep
of a simple one-stage description for advanced fibrotic not provide direct evidence of the stage or dynamic state
trix in chronic human liver disease
liver disease has become increasingly evident. Until re- of cirrhosis. The need for more refined cirrhosis staging isdegrade scar and the p
proteases that
cently, refining the diagnosis of cirrhosis into more than especially germane given the increasing use of effective understood. Moreo
them are better
one stage hardly seemed necessary when there were no antiviral treatments in patients with hepatitis B virus of distinctive pathoge
understanding
interventions available to arrest its progression. Now, (HBV) and hepatitis C virus (HCV) cirrhosis different stages and from differ
sis at and the
however, understanding the range of potential outcomes emergence of effective antifibrotic agents,that fibrosiswe be customized acco
wherein may
based on the severity of cirrhosis is essential in order to must define favorable or unfavorable endpoints underlying cause.
and
that cor-
predict outcomes and individualize therapy. This position Cirrhosis in experimental model
relate with a discrete clinical outcome in patients with 24 Following withd
may be reversible.
paper, rather than providing clinical guidelines, attempts
cirrhosis. stimulus, a dense micronodular cirrh
to catalyze a reformulation of the concept of cirrhosis
The normal liver has only a small amount of fibrous more attenuated, m
modeling to a
from a static to a dynamic one, creating a template for
tissue in relation to its size. As a result of continued liver septa will persist, like
However, some
further refinement of this concept in the future.
injury, however, there is progressive accumulation of early in the injury and ar
laid down ex-
We already make the clinical distinction between com- “mature” (i.e., cross-linked).
pensated and decompensated cirrhosis, and are incremen- tracellular matrix, or scar. Although different chronic liverin experimental mode
Moreover,
tally linking these clinical entities to quantitative variables diseases are1 characterized by distinct patterns of fibrosis of neoangiogenesis.
may be the site
such as portal pressure measurements and emerging non- deposition, the development of cirrhosis already present in chronic inflamm
represents a
invasive diagnostics. Moreover, mounting evidence sug- common outcome leading to similar clinical conse- the fibrogenic proce
concurrent with
gests that cirrhosis encompasses a pathological spectrum quences that impose an increasing burden inaclinical prac- role in the pathogenesis of portal
which is neither static nor relentlessly progressive, but tice. effectiveness of therapeutic angioge
rather dynamic and bidirectional, at least in some pa- only improving fibrosis, but also in
fication of chronic liver disease pressing need to redefine cirrhosis Anatomical-Pathological Context 2010; 51: 1445-9. anima
Garcia-Tsao et al. Hepatology sure, is suggested by data from n
tients. Thus, there is a based on histological, clinical, hemodynamic, and biological parameters. In 27 the
in a manner that better recognizes its the HVPG is below 6 mmHg, and at this stage there is fibrogenesis and ne
underlying relation- been established in humans. Altho
), there is no clinical evidence of cirrhosis,
42. Signification clinique dans la cirrhose?
12.5 / 14.6
3
?
75 KPa
F4
Ziol et al. Hepatology 2005; 41: 48-54
Castera et al. Gastroenterology 2005; 128: 343-50.
43. Complications de la cirrhose
12 27 49 54 63 75 kPa
OV grade II / III
Ascites
HCC
711 patients with liver diseases
Bleeding
F3F4 144
Foucher et al. Gut 2006; 55: 403-8.
45. Correlation élasticité hépatique et HVPG
HEPATOLOGY, Vol. 45, No. 5, 2007
oui… mais
R²= 0.61 periphera
P<0.0001 and port
showed s
when com
R²= 0.67 (P 0.0
P<0.0001 rate of l
14.72%,
R²= 0.17
Relati
P=0.02
ing the w
cant, pos
found (r
regression
Fig. 1. VHC F3-F4 (47); analysis between : 38 % LSM in whole
61 patients Linear regression VO grade II-III HVPG and
patient population. Abbreviations: HVPG, hepatic vein pressure gradient; in the c
Vizzutti et al. Hepatology 2007; 45: 1290-7
kPa, kilopascal. 0.0001).
46. Correlation élasticité hépatique et HVPG
HEPATOLOGY, Vol. 45, No. 5, 2007
oui… mais
R²= 0.61 periphera
P<0.0001 and port
showed s
Au delà d’un gradient >10-12 mmHg when com
R²= 0.67 (P 0.0
P<0.0001
la pression portale devient largement rate of l
14.72%,
indépendante de l’élasticité R²= 0.17
Relati
P=0.02
ing the w
cant, pos
found (r
regression
Fig. 1. VHC F3-F4 (47); analysis between : 38 % LSM in whole
61 patients Linear regression VO grade II-III HVPG and
patient population. Abbreviations: HVPG, hepatic vein pressure gradient; in the c
Vizzutti et al. Hepatology 2007; 45: 1290-7
kPa, kilopascal. 0.0001).
47. Corrélation avec les Varices
Oesophagiennes
P<0.0001
None grade I grade II grade III
n=91 n=27 n=41 n=6
165 patients cirrhotiques; VO grade≥ II: 28 %
Kazemi et al. J Hepatol 2006; 45: 230-5
48. Prédiction des VO grade II-III
Fibroscopie évitée 69 %
AUROC = 0.83
46% 54%
3 19 75
VO < II VO ≥ II
95% 48%
4 patients 47 patients
Mal classés Mal classés
Kazemi et al. J Hepatol 2006; 45: 230-5
50. Performance pour la prédiction des VO
Biomarqueurs vs. FibroScan
Endoscopies évitées
VO VO II-III
Ratio ASAT/ALAT 81% 76%
Index de Lok 77% 77%
FibroScan 73% 79%
Fibrotest 70% 64%
Taux de Prothrombine 70% 79%
Taux de plaquettes 69% 76%
APRI 66% 63%
N=70 patients cirrhose C Castera et al. J Hepatol 2009; 50: 59-68.
51. Combinaison élasticité hépatique
taille de la rate + plaquettes = LSPS
Liver stiffness Spleen diameter to Platelet ratio Score
LSM (kPa) x Spleen diameter (cm)
LSPS =
Platelet (109/L)
N = 401 patients VHB cirrhotiques (evaluation 280; validation 121)
VO « haut risque » (Baveno V): 32%
Kim et al. Am J Gastroenterol 2010; 105:1382-90
52. LSPS
Performance détection VO à «haut risque »
Fibroscopie évitée 83%
AUROC 0.95
62.8% 24.8%
3.5 5.5
Absence de VOHR VOHR +
95% 93%
Kim et al. Am J Gastroenterol 2010; 105:1382-90
53. 1658 Kim et al. Entire population (n = 577)
1658 Kim et al.
1.0
LSPS
Patients with LSPS ≥ 5.5
1
Risque Entire population (n = 577) de VO
de rupture
LIVERLIVER
Patients with LSPS 3.5–5.5
0.8 0
Entire population (n = 577)
Patients with LSPS < 3.5
Cumulative EV bleeding risk
1.0
Cumulative EV bleeding risk
1.0
Patients with LSPS ≥ 5.5
1.0
Patients with LSPS 3.5–5.5 LSPS ≥ 5.5
Patients with
0.6 0
0.8
LIVER
0.8
Patients with LSPS < 3.5
Cumulative EV bleeding risk
Cumulative EV bleeding risk
Patients with LSPS 3.5–5.5
0.8
Patients with LSPS < 3.5
Cumulative EV bleeding risk
0
0.6 0.4 0.6
0.6
0.4 0.2 0.4 0
0.4
0.2 0.0 0.2 0
0 1 2 3 4
0.2
No. at 0.0
risk Years 0.0
No. at risk
Patients with
0 107 1 76 2 51 3 33 4 18 0
N=577 patients
LSPS ≥ 5.5 VHB Subgroup 2
Kim et al. Am J Gastroenterol 2011; 106:1654-62
No. at risk 0.0 Years
Patients with Subgroup 1
54. Résumé
L’élasticité hépatique est bien corrélée avec le
gradient portal et la présence (taille?) des VO.
Les performances de l’élastométrie sont
cependant insuffisantes pour remplacer la
fibroscopie pour la recherche de VO.
55. factors considered significant are older age, male gender,
and serum albumin level.
Elasticité hépatique & cancer du foie L
Liaisons dangereuses ? chro
liver
adva
p<0.001
error
risk o
corre
ture.
twee
stud
pros
V
velop
N= 866 HCV patients Masuzaki et al. Hepatology 2009; 49: 1954 6
56. Elasticité hépatique & cancer du foie
890 JUNG, KIM, ET AL. Hépatite B
using LSM an
ferences in the
nalysis, we ass
histology at en
patients had L
>13 kPa. In p
of HCC estim
cantly differe
5.1%) and p
(0.87% versus
contrast, amo
developed m
diagnosed ac
N= 1130 patients VHB Jung et al. Hepatology 2011; 53: 885-94 w
55.9%) than
57. Suivi de la fibrose
Traitement antiviral
Ogawa et al. Antiviral Res 2009; 83: 127-34.
Vergniol et al. JVH 2009; 16: 132-40.
58. Plan
Principe
Performances diagnostiques
Comparaison avec les biomarqueurs
Suivi de la progression de la fibrose
Limites & perspectives
59. Reproductibilité ?
Inter-observer variability (ICC= 0.98) Intra-observer variability (ICC= 0.98)
Second observer
Second measure
First observer First measure
200 patients with CLD (800 measurements)
Fraquelli et al. Gut 2007; 56: 968-73.
65. Limites: résultats non fiables
(n=12 949)
7.2%
15.6% 15.8% 60.4%
30.5%
SR < 60%
8.1%
Woman
VS < 10 Age > 52
Man
> 500
Age < 52 3.1% < 500
BMI > 30
Diabetes
exams
BMI < 25 exams
Hypertension
No Diabetes
IQR/LSM > 30%
No hypertension
9.2%
Castéra et al. Hepatology 2010; 51: 828-35
66. Applicabilité de l’élastométrie
Echec 3.1% Non fiable 15.8%
SR < 60%
FibroScan 8.1%
Valid shot = 0
non applicable
VS < 10
3.1%
dans 20%
des cas IQR/LSM > 30%
9.2%
N=13669 examinations
Castéra et al. Hepatology 2010; 51: 828-35
67. Sonde XL :
la réponse aux limites du FibroScan?
Echec sonde XL vs. M :
1% vs. 16%
N= 276 patients with BMI > 28 kg/m2
Myers et al. Hepatology 2012; 55:199-208.
68. Sonde XL :
la réponse aux limites du FibroScan?
Résultats non fiables sonde XL vs. M :
27% vs. 50%
N= 276 patients with BMI > 28 kg/m2
Myers et al. Hepatology 2012; 55:199-208.
69. Sonde XL :
la réponse aux limites du FibroScan?
AUC F2 0.83 vs 0.86 (NS)
AUC F4 0.94 vs 0.91 (NS)
Median: 6.8 vs. 7.8 kPa
(p<0.0001)
N= 276 patients with BMI >
28 kg/m 2
Myers et al. Hepatology 2012; 55:199-208.
70. Unreliable 3.33 0.007 2.09 0.16 agre
LSM# (1.39-7.94) (0.75-5.82)
#
Discordances avec la sonde XL
<10 valid shots, SR <60%, or IQR/M >30%.
our
ciati
clini
Research Article
11% In
in ap
Table 4. Logistic regression analysis of factors associated with discordance. discordances du
prob
Stiffness <7.0 kPa Stiffness ≥7.0 kPa study has severa
nant
Variable Univariate analysis Multivariate analysis to different class
p = 0.35 p = 0.03 40 be in
40 Odds ratio p value Odds ratio p value and viral hepatit
(95% CI) (95% CI) high
are not directly
discordance (%)
BMI 30 may
fibrosis), sensitiv
Prevalence of
1.13 <0.0005 1.09 0.04
(per kg/m2) (1.06-1.21) (1.01-1.18) whom the deci
XL pr
Skin- 20 10.0 0.002 3.33 19 0.17 similar findings.
and
capsular (2.30-43.3) 15 (0.59-18.9) with viral at ri
hepat
distance 10 11 incorporate diffe
≥35 mm 10
HBV and HCV. A
Liver 1.98 3.2 0.009 1.73 0.08 a similar prevale
0 0
stiffness 0 (1.18-3.31) (0.95-3.18) consider this iss
Fina
(log10-
0
30 30
35 4.9
9
0
30 30
35 4.9
9
conditions with
≥4
≥4
9.
9.
<
<
transformed) -3
-3
-3
-3
nostic accuracy
Unreliable 3.33 0.007 2.09 0.16 This
agreement and
LSM# (1.39-7.94)
Body mass index (kg/m2)(0.75-5.82) supp
our study was cr
#
<10 valid shots, SR <60%, or IQR/M >30%. tute
ciation between
n = 20 63 20 6 13 47 16 25
Albe
clinical outcome
Percentage of patients with discordance of at least two stages between In conclusion
Fig. 1. N= 210 patients BMI > 28 kg/m2 Inno
Myers et al. Jand BMI. 2012; 20: 2390-6.
TE using the XL probe and biopsy according to liver stiffness Hepatol in approximately
71. Facteurs confondants
Congestion Inflammation aigue
Millonig et al. Coco et al. J Viral Hepat 2007
J Hepatol 2010 Arena et al. Hepatology 2008
Sagir et al. Hepatology 2008
Cholestase extra-hepatique
Millonig et al. Hepatology 2008
72. FibroScan : quels seuils?
10.3 12.5 14.5 17.1
3 75 KPa
HBV HCV HCV PBC/PSC
F4: 8% 25% 19% 19%
Marcellin et al. Liver Int 2008 Castera et al. Gastroenterology 2005; 128: 343-50.
Ziol et al. Hepatology 2005; 41: 48-54 Corpechot et al. Hepatology 2006; 43: 1118-24.
73. AUROC standardisation
according to fibrosis prevalence
AUC = 0.98
DANA = 4
DANA = 1 AUC = 0.67
Poynard et al. Clin Chem 2007; 53: 1615-22.
74. FibroScan :
un nouvel outil pour un nouveau concept
3 7.0 9.5 12.5 75 KPa
fibrose fibrose fibrose Cirrhose
Absente significative Severe
minime
Castera, Forns & Alberti. J Hepatol 2008; 48: 835-47
75. Biomarqueurs vs. FibroScan
Avantages & inconvénients
Critères Biomarqueurs FibroScan
Bonnes Meilleures
Détection cirrhose performances performances
Applicabilité 95% 81%
Rapidité résultats 1-3 jours 10 min
Castera L. Gastroenterology 2012; in press
77. a
C: 0.815 (0.727-0.903)
0.2
Elasticité hépatique
1.0
survie sans complications 0.0
0 200 400 600 800
Days
the prediction of liver
B 1.0
84.1%, respectively LS <21.1 kPa
f any complication 0.8
85.4%, respectively,
any complications
Survival free of
p <0.001) (Fig. 2B).
0.6
risk of PHT related
LS ≥21.1 kPa
0.4
ng PHT related com-
0.845 [0.767–0.923] 0.2
tic patients, HVPG
values being 0.725
ectively. (Fig. 3B). 0.0
e of significant PHT 0 200 400 600 800
remaining free of
Days
pectively (Log Rank
e patients with a Fig. 2. Risk of liver related complications according to HVPG or liver stiffness.
mplications. In the N=100 Probability of remaining free of liver related complications according to the
(A) patients CLD
a 10 mmHg thresh- 10 mmHg-threshold for HVPG. (B) Probability of remaining free al. J Hepatol
Robic et of liver related 2011; 55: 1017-24
complications according to the 21.1 kPa-threshold for liver stiffness.
78. NCREAS, AND
LIARY TRACT
NICAL–LIVER,
PANCREAS, AND
CLINICAL–LIVER,
BILIARY TRACT
Elasticité hépatique & survie
Figure 2. Overall survival probability according to liver stiffness, biomarkers, and liver biopsy. (A) O
N=1457 patients VHC fibrosis or cirrhosis. (B) Overall survival according to different cut-offsbiops
Figure 2. Overall survival probability according to liver stiffness, biomarkers, and liver of live
the diagnosis of severe Vergniol et al. Gastroenterology 2011;
80. Measurement failure and m
24 strongest predictor for the diagnosis of liver cirrhosis
25
26 ARFI performances diagnostiques
(P < 0.0001) and also age is an additional significant pre-
dictor (P = 0.0073).
Acoustic Radiation Force Im
patients from three studies
27
28
Meta-analyse
29 Table 3 Diagnostic accuracy and optimal cut-offs of ARFI for the diagnosis of liver fibrosis in
30 effect analysis
31
32 Cut-off Sensitivity Specificity PP
33 ARFI AUROC (m/s) (%) (%) (%
34
35 F‡2 0.87 1.34 79 85 91
F‡3 0.91 1.55 86 86 82
36
F=4 0.93 1.80 92 86 71
37
38
ARFI, Acoustic Radiation Force Impulse; F, fibrosis stage; AUROC, area under the ROC curv
39
positive predictive value; NPV, negative predictive value; LR, likelihood ratio.
40
41 N=518 patients
42
43
44 Friedrich-Rust et al. J Viral Hepat 2012 ; in press
81. ARFI vs. TE
Significant fibrosis Cirrhosis
AUROC AUROC
ARFI: 0.82 ARFI: 0.91
TE: 0.84 TE: 0.91
N=81 patients with viral hepatitis
Friedrich-Rust et al. Radiology 2009 ; 252: 595-604.
82. Quels seuils en pratique?
N=81 patients with viral hepatitis
Friedrich-Rust et al. Radiology 2009 ; 252: 595-604.
83. Nouvelles techniques
Elasto-IRM vs. TE
Transient elastography MR elastography
AUROC AUROC
F≥2 0.84 F≥2 0.99
F=4 0.93 F=4 0.99
N= 96 patients with various chronic liver diseases: F≥2 54%; F4 19%
Huwart et al. Gastroenterology 2008; 135: 32-40.
84. Nouvelles techniques
Supersonic shear Imaging vs. TE
1368 Ultrasound in Medicine and Biology Volume 37, Number 9, 2011
Table 1. AUROC and 95% confidence interval for SSI and FS according to METAVIR fibrosis stages
Method F$2 F$3 F54
SSI 0.95 [0.91;0.99] 0.96 [0.92;1] 0.97 [0.90;1]
FS 0.85 [0.77;0.92] 0.86 [0.77;0.93] 0.94 [0.85;1]
FS (Castra et al. 2005)
e 0.83 [0.76;0.88] 0.90 [0.85;0.94] 0.95 [0.91;0.98]
D 0.102 6 0.0367 0.105 6 0.0407 0.027 6 0.0193
P 0.005 0.001 0.154
SSI 5 supersonic shear imaging; FS 5 FibroScan; AUROC 5 area under the receiver operating characteristic curve.
The results from a previous study (Castra et al. 2005) on fibrosis staging using FS are shown for reference. D, the difference between AUROC for SSI
e
and FS are also presented. The significance level P of the comparison between ROC curves is also given.
andn=113 Patients VHC predicted liver fibrosis
FS elasticity values for each As shown in Table 1, the FS examination gives worse
Reference = combinaison de marqueursAUROCs for each predicted fibrosis level than SSI. The
level. Although the predicted fibrosis level is not exclu- seriques
sively derived from the gold standard method (LB exam- AUROCs values for SSI and FS are, respectively, 0.948
ination), this preliminary study allows the comparison of and 0.846 for the diagnosis of significant fibrosis
both techniques with a unique reference: the predicted (F $ 2),Bavu et al. UMB 2011;37: 1361-73
0.962 and 0.857 for the diagnosis of severe
fibrosis level, which is derived from the blood markers fibrosis (F $ 3); for the diagnosis of cirrhosis (F 5 4),
85. Perspectives: Dépistage de la
fibrose dans la population générale ?
Castera L Pinzani M. Lancet 2010; 375: 419-20.
86. Dépistage population générale ?
7463 healthy subjects 1190 healthy subjects
FibroTest FibroScan
Fibrosis (≥2) 2.8 % Fibrosis (≥2) 7.5 %
Cirrhosis 0.3% Cirrhosis 0.7%
Poynard et al. BMC Gastroenterol 2010 Roulot et al. Gut 2011
87. Take Home messages (1)
L’élastométrie a été principalement validée dans les
hépatites virales mais nécessitent d’étre validée dans
d’autres etiologies (NAFLD, etc..).
La combinaison de l’élastométrie et des marqueurs
sanguins est la stratégie de choix pour la détection de la
fibrose en 1ère intention dans l’hépatite C (HAS).
88. Take Home messages (2)
La principale limite de l’élastométrie est son
applicablité limitée (80%) en cas d’obésité.
L’élastométrie est actuellement la méthode la plus
performante pour le diagnostic de cirrhose mais du fait
de sa moins bonne applicabilité ses performances sont
comparables aux biomarqueurs.
89. Take Home messages (3)
Les performances de l’élastométrie sont insuffisantes
pour remplacer la fibroscopie pour le dépistage des
VO.
La mesure de l’élasticité hépatique a une valeur
pronostique au cours de la cirrhose.
Malgré ses limites, l’élastométrie est une technique
prometteuse pour le suivi des maladies du foie mais
nécessite d’être mieux évaluée de façon longitudinale.
