Castera du pitie 17 janvier 2012 selection

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Castera du pitie 17 janvier 2012 selection

  1. 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
  2. 2. Méthodes non invasives disponibles2 approches différentes mais complémentairesApproche « biologique » Approche « physique » Biomarqueurs Elasticité hépatique Castera & Pinzani. Lancet 2010; 375: 419-20
  3. 3. Elasticité hépatique FibroScan Sandrin et al. UMB 2003; 29: 1705-13 Castera, Forns & Alberti. J Hepatol 2008; 48: 835-47
  4. 4. Elasticité hépatiqueAcoustic Radiation Force Impulse Imaging (ARFI) Nightingale et al. UMB 2002 ; 28: 227-35 Friedrich-Rust et al. Radiology 2009 ; 252: 595-604
  5. 5. Elasticité hépatique Elasto-IRM 10 Shear Stiffness (kPa) +90Displacement (µm) 8 6 0 4 2 -90 Elastogram 0 Muthupillai et al. Science 1995; 269: 1854-7 Huwart et al. Gastroenterology 2008; 135: 32-40
  6. 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 same1366 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 probabilitybandwidth of the generated shear wave is large, typically of a true positive (sensitivity) and the probability of a trueranging 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 areain Figure 3, the shear wave dispersion law can be assessed under the ROC curve (AUROC), with values close tofrom 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 theof 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 cutoffages the full mechanical response of the liver tissues values. By using these cutoff values, the agreement between FS and SSI was evaluated. Statistical analysesover 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 analysiserties of tissues by estimating frequency dependence of toolbox and Medcalc software (Mariakerke, Belgium).the shear wave speed. RESULTSStatistical methods The diagnosis performance of FS and SSI are Liver stiffness mapping using SSIcompared 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 musclegreater than or less than to a given cutoff value, respec- region are well differentiated from the liver region andtively. 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 theof 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 219-29negative (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): patientsensitivity 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 6The 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. 7. Plan  Principe  Performances diagnostiques  Comparaison avec les biomarqueurs  Suivi de la progression de la fibrose  Limites & perspectives
  8. 8. Elastométrie (FibroScan) = 100 Volume exploré x 2.5 cm 1 cm ∅ Biopsie foie 4 cm
  9. 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. 10. Mesure de l’élasticité hépatique Normale 5.5 15 653 75 kPa Roulot et al. J Hepatol 2008; 48: 606-13
  11. 11. FibroScan en pratique Indolore Rapide (5 min) Lit du malade/ consultation Résultats immédiats Formation courte (100 exam.)
  12. 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. 13. Plan  Principe  Performances diagnostiques  Comparaison avec les biomarqueurs  Suivi de la progression de la fibrose  Limites & perspectives
  14. 14. Objectifs diagnostiquesF0 F1 F2 F3 F4Indication du traitement antiviral Dépistage des varices oesophagiennes Dépistage du carcinome hépatocellulaire
  15. 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. 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. 17. Quantité de fibrose vs. Stade de fibrose Collagen area (%) Standish et al. Gut 2006; 55: 569-78.
  18. 18. Hépatite C Performance Diagnostique 1 1 0.8 0.8 Sensitivity Sensitivity 0.6 0.6 AUROC AUROC AUROC 0.4 F2 : 0.83 0.4 F2F2 : 0.84 : 0.84 F3 : 0.90 F2 0.2 0.2 F3 : 0.90 F3 : 0.90 F3 F4 : 0.95 F4 F4F4 0.94 : 0.94 0 0 0 0.5 1 0 0.2 0.4 0.6 0.8 1 1-Specificity 1-Specificity Ziol et al. Hepatology 2005; 41: 48-54 Castera et al. Gastroenterology 2005; 128: 343-50.
  19. 19. Hépatite C: seuilsPPV: 88-95% 71-87% 77-78% PPV: PPV:NPV: 48-56% 81-93% 95-97% NPV: NPV: 7.1 / 8.7 9.5 12.5 / 14.53 75 KPa F2 F3 F4 Ziol et al. Hepatology 2005; 41: 48-54 Castera et al. Gastroenterology 2005; 128: 343-50.
  20. 20. Fibrose significative(n=1307 patients atteints d’hépatites virales, 746 F≥2) Bien classés 68 % AUROC=0.76 50% 50%3 7.1 75 F<2 F≥2 61% 75% Degos et al. J Hepatol 2010; 53: 1013-21
  21. 21. Hépatite B performance diagnostique AUROCs AUROCs F≥2 0.81 F≥1 0.80 F≥3 0.93 F≥3 0.87 F=4 0.93 F=4 0.93N= 173 HBV patients; N= 161 HBV patients;F2-F4: 50%; F4: 8% F2-F4: 77%; F4: 25% Marcellin et al. Liver Int 2009; 29: 242-7 Chan et al. J Viral Hepat 2009 ; 16: 36-44
  22. 22. Performances diagnostiques pour F≥2 Meta-analyse Seuil optimal: 7.6 kPa AUROC: 0.84 (0.82-0.86) Friedrich-Rust et al. Gastroenterology 2008; 134: 960-74
  23. 23. Performances diagnostiques pour F≥2 Meta-analyseSensibilité: 70% (67-73) Spécificité: 84% (80-88) Talwalkar et al. Clin Gastroenterol Hepatol 2007; 5: 1214-20
  24. 24. Performances diagnostiques pour F4 Meta-analyse Optimal cut-off: 13.0 kPa AUROC: 0.94 (0.93-0.95) Friedrich-Rust et al. Gastroenterology 2008; 134: 960-74
  25. 25. Performances diagnostiques pour F4 Meta-analyseSensibilité: 87% (84-90) Specificité: 91% (89-92) Talwalkar et al. Clin Gastroenterol Hepatol 2007; 5: 1214-20
  26. 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. 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. 28. Plan  Principe  Performances diagnostiques  Comparaison avec les biomarqueurs  Suivi de la progression de la fibrose  Limites & perspectives
  29. 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. 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. 31. Comparaison des approches cirrhose P<0.0001 .N= 1307 patients; F4: 25% Degos et al. J Hepatol 2010; 53: 1013-21
  32. 32. Comparaison des approches cirrhose JOURNAL OF HEPATOLOGYTable 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 mmprotocol’’ 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. 33. La combinaison augmenteles performances diagnostiques Bien + classés F≥2: 75%Marqueurs sériques Elastométrie Castera et al. Gastroenterology 2005; 128: 343-50.
  34. 34. Concordance in world without gold standard: a new way to increase diagnostic accuracy Poynard et al. Plos One 2008
  35. 35. La combinaison augmenteles performances diagnostiques N= 729 patients with CHC Boursier et al. Am J Gastroenterol 2011; 106: 1255-63
  36. 36. Combinaison des marqueurs sériques Sequential Algorithm for Fibrosis Evaluation APRI F0-F1 Unclassified F2-F3-F4 (20-30% false -) (>95% accuracy) FIBROTEST F0-F1 F2-F3-F4 (20-30% false -) (>95% accuracy) LIVER BIOPSY Liver biopsy not needed Sebastiani et al. J Hepatol 2006; 44: 686-93.
  37. 37. Comparaison des algorithmes fibrose significative Padoue Bordeaux P<0.001PBH évitées: 48% ? < PBH évités: 72% Sebastiani et al. J Hepatol 2006; 44: 686-93.N=302 HCV patients Castéra et al. J Hepatol 2010; 52: 191-8.
  38. 38. Comparaison entre algorithmes Cirrhose Padova BordeauxPBH évitées: 75% ? = PBH évitées: 79% Sebastiani et al. J Hepatol 2006; 44: 686-93.N=302 HCV patients Castéra et al. J Hepatol 2010; 52: 191-8.
  39. 39. Plan  Principe  Performances diagnostiques  Comparaison avec les biomarqueurs  Suivi de la progression de la fibrose  Limites & perspectives
  40. 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. 41. Now There Are Many (Stages) Where Before There Was One: In Search of a PathophysiologicalA-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 infication 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. 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. 43. Complications de la cirrhose 12 27 49 54 63 75 kPa OV grade II / III Ascites HCC711 patients with liver diseases BleedingF3F4 144 Foucher et al. Gut 2006; 55: 403-8.
  44. 44. Corrélation élasticité hépatique et HVPG Pearson’s coefficient = 0.84 30 24 p < 0.001 HVPG (mm Hg) 18 12 6 0 0 8 16 24 32 40 48 56 64 72 80 Liver stiffness (kPa) N= 124 patients avec récidive VHC post TH Carrion et al. Liver Transpl 2006; 12: 1791-8.
  45. 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. 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. 47. Corrélation avec les Varices Oesophagiennes P<0.0001 None grade I grade II grade III n=91 n=27 n=41 n=6165 patients cirrhotiques; VO grade≥ II: 28 % Kazemi et al. J Hepatol 2006; 45: 230-5
  48. 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
  49. 49. Performance pour la prédiction des VO FibroScan,tients Patients Etiologies Study Etiologies Study Authors, Child-PughStudy End Prevalence Cut-offs AUC Se AUC Cut-offs Sp Patients Etiologies Child-Pugh End Child-Pugh End Prevalence Cut-offs Sp Se Prevalence PPV AUC PPV NPV +LR -LR Saved NPV Se +LR Sp -LR Saved NPV +LR PPV (n) [Ref.] design design(%) (n) A point Adesign (%) OV(%) A (%) OV (%) point (kPa) point (kPa) (%) (%) (%) (%) (%) (%) OV (%) (%) (%) (%) endoscopy endos (kPa) (%) (%) (%) (%)5 CLD 165 Retro. Kazemi CLD 165 n.a. Retro. CLD n.a.OV Retro. 45 OV n.a. 45 13.9 OV 0.83 95 0.83 13.9 13.9 45 43 9557 4391 1.7 43 1.7 0.83 57 0.13 66 95 91 57 0.13 91 66 1.75] et al., [45] mono. mono. LOV mono. 28 LOV 28 19.0 LOV 0.84 91 0.84 19.0 19.0 28 60 9148 6095 2.3 60 2.3 0.84 48 0.14 69 91 95 48 0.14 95 69 2.3 HCV 47 Pro. Vizzutti HCV 47 Pro. 60 HCV 60 OV Pro. 66 OV 60 66 17.6 OV 0.76 90 0.76 17.6 17.6 66 43 9077 4366 1.6 43 1.6 0.76 77 0.23 74 90 66 77 0.23 66 74 1.66] et al., [36] mono. mono. mono.1t CLD 211 Retro. Pritchett CLD 211 n.a. Retro. CLD n.a.OV Retro. n.a. OV n.a. 19.5 n.a. OV 0.74 76 0.74 19.5 19.5 n.a. 66 7656 6682 2.2 66 2.2 0.74 56 0.36 n.a. 0.36 76 82 56 82 n.a. 2.2 8] et al., [48] mono. mono. mono. LOV LOV 37 37 19.8 LOV 0.76 91 0.76 19.8 19.8 37 56 9191 56 0.76 91 55 91 55 2.1 56 2.1 0.16 69 0.16 91 55 69 2.1 89 Bureau CLD 89 CLD Pro. Pro. 34 CLD 34 OV Pro. OV 34 72 72 21.1 OV 0.85 84 0.85 21.1 21.1 72 71 84 71 0.85 84 2.9 71 2.9 0.22 81 0.22 81 2.97] et al., [37] mono. mono. mono. LOV LOV 48 48 29.3 LOV 0.76 81 0.76 29.3 29.3 48 61 81 61 0.76 81 2.1 61 2.1 0.31 71 0.31 71 2.1 70 Castera HCV 70 HCV Retro. Retro. HCV 100 100OV Retro. OV 100 36 36 21.5 OV 0.84 76 0.84 21.5 21.5 36 78 7668 78 0.84 68 84 76 84 3.5 78 3.5 68 0.31 73 0.31 84 73 3.56] et al., [46] mono. mono. mono. LOV LOV 19 19 30.5 LOV 0.87 77 0.87 30.5 30.5 19 85 7756 85 0.87 56 94 77 94 5.1 85 5.1 56 0.27 79 0.27 94 79 5.12 102 Pineda, HIV-HCV HIV-HCV Pro. 102 Pro. 76 HIV-HCV 76 CROV* Pro. CROV* 76 13 13 21.0 CROV* 0.71 100 0.71 21.0 21.0 13 32 100 32 25 0.71 25 100 100 100 1.5 1.5 32 0.0 25 44 0.0 100 44 1.57] et al., [47] multi. multi. multi.3 183 Nguyen CLD 183 Retro. CLD Retro. CLD 63 63 LOV Retro. LOV 63 22 22 48.0 LOV 0.76 73 0.76 48.0 48.0 22 73 7344 73 0.76 44 90 73 90 2.7 73 2.7 44 0.37 73 0.37 90 73 2.79] 58 al. [49]HCV/HBV mono. et HCV/HBV mono.58 HCV/HBV mono. 17 17 19.8 0.73 89 0.73 19.8 19.8 17 55 8927 55 0.73 27 97 89 97 2.0 55 2.0 27 0.20 60 0.20 97 60 2.03 103 Alcohol Alcohol 103 Alcohol 25 25 47.2 0.77 85 0.77 47.2 47.2 25 64 8544 64 0.77 44 93 85 93 2.4 64 2.4 44 0.23 69 0.23 93 69 2.44 124 Malik CLD CLD 124 Retro. Retro. CLD n.a. n.a.OV Retro. OV n.a. 51 51 20.0 OV 0.85 n.a. 0.85 20.0 20.0 51 n.a. n.a. n.a. 80 80 0.85 n.a. 75 75 n.a. n.a. n.a. n.a. n.a. 75 80 n.a. n.a.0] et al., [50] mono. mono. mono. Thabut, Moreau & Lebrec. Hepatology 2011; 53: 683-94 Castera, Pinzani & Bosch. J Hepatol 2012; in press
  50. 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. 51. Combinaison élasticité hépatiquetaille 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. 52. LSPSPerformance 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. 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 ruptureLIVERLIVER 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. 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. 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. 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. 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. 58. Plan  Principe  Performances diagnostiques  Comparaison avec les biomarqueurs  Suivi de la progression de la fibrose  Limites & perspectives
  59. 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.
  60. 60. Reproductibilité ?u  Moindre reproductibilité: ICC ―  Mild fibrosis (F0-F1) 0.60 ―  Steatosis (>25% hepatocytes) 0.90 ―  Increased BMI (>25) 0.94 Fraquelli et al. Gut 2007; 56: 968-73.
  61. 61. Influence de la stéatose ? Wong et al. Hepatology 2010; 51: 454-62. Gaia et al. J Hepatology 2011; 54: 64-71.
  62. 62. Elastométrie« recommandations du constructeur » 10 mesures valides IQR < 30% médiane Taux de succès > 60% Castera, Forns & Alberti. J Hepatol 2008; 48: 835-47
  63. 63. Limites : echec n=13369 Echec: 3.1 % - Experience operateur - BMI > 30 Castéra et al. Hepatology 2010; 51: 828-35
  64. 64. Limites : echecLSM failure rates n=13369 80% 60% 41.7% 40% 24.9% 20% 16.9% 12.4% 8.1% 1.0% 0% < 25 ≥ 25 ≥ 28 ≥ 30 ≥ 35 ≥ 40 (n=4172) (n=3089) (N=1568) (n=967) (n=225) (n=48) BMI (kg/m²) Castéra et al. Hepatology 2010; 51: 828-35
  65. 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. 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. 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. 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. 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. 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 conclusionFig. 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. 71. Facteurs confondantsCongestion Inflammation aigueMillonig et al. Coco et al. J Viral Hepat 2007J Hepatol 2010 Arena et al. Hepatology 2008 Sagir et al. Hepatology 2008 Cholestase extra-hepatique Millonig et al. Hepatology 2008
  72. 72. FibroScan : quels seuils? 10.3 12.5 14.5 17.13 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. 73. AUROC standardisationaccording to fibrosis prevalence AUC = 0.98 DANA = 4DANA = 1 AUC = 0.67 Poynard et al. Clin Chem 2007; 53: 1615-22.
  74. 74. FibroScan : un nouvel outil pour un nouveau concept3 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. 75. Biomarqueurs vs. FibroScan Avantages & inconvénientsCritères Biomarqueurs FibroScan Bonnes MeilleuresDétection cirrhose performances performancesApplicabilité 95% 81%Rapidité résultats 1-3 jours 10 min Castera L. Gastroenterology 2012; in press
  76. 76. Perspectives
  77. 77. aC: 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 ofp <0.001) (Fig. 2B). 0.6risk of PHT related LS ≥21.1 kPa 0.4ng PHT related com-0.845 [0.767–0.923] 0.2tic patients, HVPG values being 0.725ectively. (Fig. 3B). 0.0e of significant PHT 0 200 400 600 800 remaining free of Days pectively (Log Ranke 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. 78. NCREAS, ANDLIARY TRACTNICAL–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;
  79. 79. Nouvelles techniques ARFIAcoustic Radiation Force Impulse Imaging Velocity: meter/secN=112 HCV patients Lupsor et al. J Gastrointestin Llver Dis 2009; 18: 303-10
  80. 80. Measurement failure and m24 strongest predictor for the diagnosis of liver cirrhosis2526 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 studies2728 Meta-analyse29 Table 3 Diagnostic accuracy and optimal cut-offs of ARFI for the diagnosis of liver fibrosis in30 effect analysis3132 Cut-off Sensitivity Specificity PP33 ARFI AUROC (m/s) (%) (%) (%3435 F‡2 0.87 1.34 79 85 91 F‡3 0.91 1.55 86 86 8236 F=4 0.93 1.80 92 86 713738 ARFI, Acoustic Radiation Force Impulse; F, fibrosis stage; AUROC, area under the ROC curv39 positive predictive value; NPV, negative predictive value; LR, likelihood ratio.4041 N=518 patients424344 Friedrich-Rust et al. J Viral Hepat 2012 ; in press
  81. 81. ARFI vs. TE Significant fibrosis Cirrhosis AUROC AUROC ARFI: 0.82 ARFI: 0.91 TE: 0.84 TE: 0.91N=81 patients with viral hepatitis Friedrich-Rust et al. Radiology 2009 ; 252: 595-604.
  82. 82. Quels seuils en pratique?N=81 patients with viral hepatitis Friedrich-Rust et al. Radiology 2009 ; 252: 595-604.
  83. 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 0.99N= 96 patients with various chronic liver diseases: F≥2 54%; F4 19% Huwart et al. Gastroenterology 2008; 135: 32-40.
  84. 84. Nouvelles techniques Supersonic shear Imaging vs. TE1368 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 F54SSI 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 0.0193P 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 eand 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. Thelevel. Although the predicted fibrosis level is not exclu- seriquessively derived from the gold standard method (LB exam- AUROCs values for SSI and FS are, respectively, 0.948ination), this preliminary study allows the comparison of and 0.846 for the diagnosis of significant fibrosisboth 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 severefibrosis level, which is derived from the blood markers fibrosis (F $ 3); for the diagnosis of cirrhosis (F 5 4),
  85. 85. Perspectives: Dépistage de lafibrose dans la population générale ? Castera L Pinzani M. Lancet 2010; 375: 419-20.
  86. 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. 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. 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. 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.

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