nach oben

European Radiology

Erschienen in:

18.04.2018 | Magnetic Resonance

Accurate IVIM model-based liver lesion characterisation can be achieved with only three b-value DWI

Erschienen in: European Radiology | Ausgabe 10/2018

Einloggen, um Zugang zu erhalten

Abstract

Objective

The objective of this study was to evaluate a simplified intravoxel incoherent motion (IVIM) approach of diffusion-weighted imaging (DWI) with four b-values for liver lesion characterisation at 1.5 T.

Methods

DWI data from a respiratory-gated MRI sequence with b = 0, 50, 250, 800 s/mm² were retrospectively analysed in 173 lesions and 40 healthy livers. The apparent diffusion coefficient ADC = ADC(0,800) and IVIM-based parameters D₁′ = ADC(50,800), D₂′ =ADC(250,800), f₁′, f₂′, D*′, ADC_low = ADC(0,50), and ADC_diff=ADC_low-D₂′ were calculated voxel-wise without fitting procedures. Differences between lesion groups were investigated.

Results

Focal nodular hyperplasias were best discriminated from all other lesions by f₁′ with an area under the curve (AUC) of 0.989. Haemangiomas were best discriminated by D₁′ (AUC of 0.994). For discrimination between malignant and benign lesions, ADC(0,800) and D₁′ were best suited (AUC of 0.915 and 0.858, respectively). Discriminatory power was further increased by using a combination of D₁′ and f₁′.

Conclusion

IVIM parameters D and f approximated from three b-values provided more discriminatory power between liver lesions than ADC determined from two b-values. The use of b = 0, 50, 800 s/mm² was superior to that of b = 0, 250, 800 s/mm². The acquisition of four instead of three b-values has no further benefit for lesion characterisation.

Key Points

• Diffusion and perfusion characteristics are assessable with only three b-values.

• Association of b = 0, 50, 800 s/mm²is superior to b = 0, 250, 800 s/mm².

• A fourth acquired b-value has no benefit for differential diagnosis.

• For liver lesion characterisation, simplified IVIM analysis is superior to ADC determination.

• Simplified IVIM approach guarantees numerically stable, voxel-wise results and short acquisition times.

Taouli B (2012) Diffusion-weighted MR imaging for liver lesion characterization: a critical look. Radiology 262:378–380CrossRef

Taouli B, Koh DM (2010) Diffusion-weighted MR imaging of the liver. Radiology 254:47–66CrossRef

Takahara T, Kwee TC (2012) Low b-value diffusion-weighted imaging: emerging applications in the body. J Magn Reson Imaging 35:1266–1273CrossRef

Kwee TC, Takahara T (2011) Diffusion-weighted MRI for detecting liver metastases: importance of the b-value. Eur Radiol 21:150CrossRef

Coenegrachts K, Delanote J, Ter Beek L et al (2009) Evaluation of true diffusion, perfusion factor, and apparent diffusion coefficient in non-necrotic liver metastases and uncomplicated liver hemangiomas using black-blood echo planar imaging. Eur J Radiol 69:131–138CrossRef

Parikh T, Drew SJ, Lee VS et al (2008) Focal liver lesion detection and characterization with diffusion-weighted MR imaging: comparison with standard breath-hold T2-weighted imaging. Radiology 246:812–822CrossRef

Gourtsoyianni S, Papanikolaou N, Yarmenitis S et al (2008) Respiratory gated diffusion-weighted imaging of the liver: value of apparent diffusion coefficient measurements in the differentiation between most commonly encountered benign and malignant focal liver lesions. Eur Radiol 18:486–492CrossRef

Coenegrachts K, Delanote J, Ter Beek L et al (2007) Improved focal liver lesion detection: comparison of single-shot diffusion-weighted echoplanar and single-shot T2 weighted turbo spin echo techniques. Br J Radiol 80:524–531CrossRef

Padhani AR, Liu G, Koh DM et al (2009) Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia 11:102–125CrossRef

10.

Koh DM, Collins DJ, Orton MR (2011) Intravoxel incoherent motion in body diffusion-weighted MRI: reality and challenges. AJR Am J Roentgenol 196:1351–1361CrossRef

11.

Guiu B, Cercueil JP (2011) Liver diffusion-weighted MR imaging: the tower of Babel? Eur Radiol 21:463–467CrossRef

12.

Le Bihan D, Breton E, Lallemand D et al (1988) Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. Radiology 168:497–505CrossRef

13.

Aoyagi T, Shuto K, Okazumi S et al (2012) Apparent diffusion coefficient correlation with oesophageal tumour stroma and angiogenesis. Eur Radiol 22:1172–1177CrossRef

14.

Cho GY, Kim S, Jensen JH et al (2012) A versatile flow phantom for intravoxel incoherent motion MRI. Magn Reson Med 67:1710–1720CrossRef

15.

Lee Y, Lee SS, Kim N et al (2015) Intravoxel incoherent motion diffusion-weighted MR imaging of the liver: effect of triggering methods on regional variability and measurement repeatability of quantitative parameters. Radiology 274:405–415. https://doi.org/10.1148/radiol.14140759 CrossRefPubMed

16.

Luciani A, Vignaud A, Cavet M et al (2008) Liver cirrhosis: intravoxel incoherent motion MR imaging--pilot study. Radiology 249:891–899CrossRef

17.

Cohen AD, Schieke MC, Hohenwalter MD, Schmainda KM (2015) The effect of low b-values on the intravoxel incoherent motion derived pseudodiffusion parameter in liver. Magn Reson Med 73:306–311. https://doi.org/10.1002/mrm.25109 CrossRefPubMed

18.

Parente DB, Paiva FF, Oliveira Neto JA et al (2015) Intravoxel incoherent motion diffusion weighted mr imaging at 3.0 T: assessment of steatohepatitis and fibrosis compared with liver biopsy in type 2 diabetic patients. PLoS One 10:e0125653. https://doi.org/10.1371/journal.pone.0125653 CrossRefPubMedPubMedCentral

19.

Lu P-X, Huang H, Yuan J et al (2014) Decreases in molecular diffusion, perfusion fraction and perfusion-related diffusion in fibrotic livers: a prospective clinical intravoxel incoherent motion MR imaging study. PLoS ONE 9:e113846. https://doi.org/10.1371/journal.pone.0113846 CrossRefPubMedPubMedCentral

20.

Guiu B, Petit JM, Capitan V et al (2012) Intravoxel incoherent motion diffusion-weighted imaging in nonalcoholic fatty liver disease: a 3.0-T MR study. Radiology 265:96–103CrossRef

21.

Wang M, Li X, Zou J et al (2016) Evaluation of hepatic tumors using intravoxel incoherent motion diffusion-weighted MRI. Med Sci Monit 22:702–709. https://doi.org/10.12659/MSM.895909 CrossRefPubMedPubMedCentral

22.

Ichikawa S, Motosugi U, Ichikawa T et al (2013) Intravoxel incoherent motion imaging of focal hepatic lesions. J Magn Reson Imaging 37:1371–1376. https://doi.org/10.1002/jmri.23930 CrossRefPubMed

23.

Doblas S, Wagner M, Leitao HS et al (2013) Determination of malignancy and characterization of hepatic tumor type with diffusion-weighted magnetic resonance imaging: comparison of apparent diffusion coefficient and intravoxel incoherent motion–derived measurements. Invest Radiol 48:722–728CrossRef

24.

Kakite S, Dyvorne H, Besa C et al (2015) Hepatocellular carcinoma: short-term reproducibility of apparent diffusion coefficient and intravoxel incoherent motion parameters at 3.0T. J Magn Reson Imaging 41:149–156. https://doi.org/10.1002/jmri.24538 CrossRefPubMed

25.

Andreou A, Koh DM, Collins DJ et al (2013) Measurement reproducibility of perfusion fraction and pseudodiffusion coefficient derived by intravoxel incoherent motion diffusion-weighted MR imaging in normal liver and metastases. Eur Radiol 23:428–434CrossRef

26.

Penner A-H, Sprinkart AM, Kukuk GM et al (2013) Intravoxel incoherent motion model-based liver lesion characterisation from three b-value diffusion-weighted MRI. Eur Radiol 23:2773–2783. https://doi.org/10.1007/s00330-013-2869-z CrossRefPubMed

27.

Mürtz P, Penner A-H, Pfeiffer A-K et al (2016) Intravoxel incoherent motion model-based analysis of diffusion-weighted magnetic resonance imaging with 3 b-values for response assessment in locoregional therapy of hepatocellular carcinoma. Onco Targets Ther 9:6425–6433. https://doi.org/10.2147/OTT.S113909 CrossRefPubMedPubMedCentral

28.

Pieper C, Meyer C, Sprinkart AM et al (2016) The value of intravoxel incoherent motion model-based diffusion-weighted imaging for outcome prediction in resin-based radioembolization of breast cancer liver metastases. Onco Targets Ther 9:4089–4098. https://doi.org/10.2147/OTT.S104770 CrossRefPubMedPubMedCentral

29.

Pieper CC, Sprinkart AM, Meyer C et al (2016) Evaluation of a simplified intravoxel incoherent motion (IVIM) analysis of diffusion-weighted imaging for prediction of tumor size changes and imaging response in breast cancer liver metastases undergoing radioembolization: a retrospective single center analysis. Medicine 95:e3275. https://doi.org/10.1097/MD.0000000000003275 CrossRefPubMedPubMedCentral

30.

Pieper CC, Willinek WA, Meyer C et al (2016) Intravoxel incoherent motion diffusion-weighted MR imaging for prediction of early arterial blood flow stasis in radioembolization of breast cancer liver metastases. J Vasc Interv Radiol 27:1320–1328. https://doi.org/10.1016/j.jvir.2016.04.018 CrossRefPubMed

31.

Bruix J, Sherman M (2011) Management of hepatocellular carcinoma: an update. Hepatology 53:1020–1022CrossRef

32.

Liu Y, Ye Z, Sun H, Bai R (2013) Grading of uterine cervical cancer by using the ADC difference value and its correlation with microvascular density and vascular endothelial growth factor. Eur Radiol 23:757–765. https://doi.org/10.1007/s00330-012-2657-1 CrossRefPubMed

33.

Zhu L, Cheng Q, Luo W et al (2015) A comparative study of apparent diffusion coefficient and intravoxel incoherent motion-derived parameters for the characterization of common solid hepatic tumors. Acta Radiol 56:1411–1418. https://doi.org/10.1177/0284185114559426 CrossRefPubMed

34.

Watanabe H, Kanematsu M, Goshima S et al (2014) Characterizing focal hepatic lesions by free-breathing intravoxel incoherent motion MRI at 3.0 T. Acta Radiol 55:1166–1173. https://doi.org/10.1177/0284185113514966 CrossRefPubMed

35.

Colagrande S, Regini F, Pasquinelli F et al (2013) Focal liver lesion classification and characterization in noncirrhotic liver: a prospective comparison of diffusion-weighted magnetic resonance–related parameters. J Comput Assist Tomogr 37:560–567CrossRef

36.

Coenegrachts K (2009) Magnetic resonance imaging of the liver: New imaging strategies for evaluating focal liver lesions. World J Radiol 1:72. https://doi.org/10.4329/wjr.v1.i1.72 CrossRefPubMedPubMedCentral

37.

Moteki T, Horikoshi H (2006) Evaluation of hepatic lesions and hepatic parenchyma using diffusion-weighted echo-planar MR with three values of gradient b-factor. J Magn Reson Imaging 24:637–645CrossRef

38.

Lewin M, Fartoux L, Vignaud A et al (2011) The diffusion-weighted imaging perfusion fraction f is a potential marker of sorafenib treatment in advanced hepatocellular carcinoma: a pilot study. Eur Radiol 21:281–290CrossRef

39.

Kim S, Decarlo L, Cho GY et al (2012) Interstitial fluid pressure correlates with intravoxel incoherent motion imaging metrics in a mouse mammary carcinoma model. NMR Biomed 25:787–794CrossRef

40.

Lee HJ, Rha SY, Chung YE et al (2014) Tumor perfusion-related parameter of diffusion-weighted magnetic resonance imaging: correlation with histological microvessel density. Magn Reson Med 71:1554–1558. https://doi.org/10.1002/mrm.24810 CrossRefPubMed

41.

Wagner M, Doblas S, Daire JL et al (2012) Diffusion-weighted MR imaging for the regional characterization of liver tumors. Radiology 264:464–472. https://doi.org/10.1148/radiol.12111530 CrossRefPubMed

42.

Yoon JH, Lee JM, Yu MH et al (2014) Evaluation of hepatic focal lesions using diffusion-weighted MR imaging: comparison of apparent diffusion coefficient and intravoxel incoherent motion-derived parameters. J Magn Reson Imaging 39:276–285. https://doi.org/10.1002/jmri.24158 CrossRefPubMed

43.

Yamada I, Aung W, Himeno Y et al (1999) Diffusion coefficients in abdominal organs and hepatic lesions: evaluation with intravoxel incoherent motion echo-planar MR imaging. Radiology 210:617–623CrossRef

44.

Zhang JL, Sigmund EE, Rusinek H et al (2012) Optimization of b-value sampling for diffusion-weighted imaging of the kidney. Magn Reson Med 67:89–97. https://doi.org/10.1002/mrm.22982 CrossRefPubMed

45.

Cercueil J-P, Petit J-M, Nougaret S et al (2015) Intravoxel incoherent motion diffusion-weighted imaging in the liver: comparison of mono-, bi- and tri-exponential modelling at 3.0-T. Eur Radiol 25:1541–1550. https://doi.org/10.1007/s00330-014-3554-6 CrossRefPubMed

Titel: Accurate IVIM model-based liver lesion characterisation can be achieved with only three b-value DWI
Publikationsdatum: 18.04.2018
Erschienen in: European Radiology / Ausgabe 10/2018
Print ISSN: 0938-7994
Elektronische ISSN: 1432-1084
DOI: https://doi.org/10.1007/s00330-018-5401-7

Neu im Fachgebiet Radiologie

23.04.2024 | Pankreaskarzinom | Nachrichten

Update Radiologie

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.

Newsletter bestellen

Springer Medizin

Accurate IVIM model-based liver lesion characterisation can be achieved with only three b-value DWI

Abstract

Objective

Methods

Results

Conclusion

Key Points

Neu im Fachgebiet Radiologie

S3-Leitlinie zu Pankreaskrebs aktualisiert

Fünf Dinge, die im Kindernotfall besser zu unterlassen sind

„Nur wer sich gut aufgehoben fühlt, kann auch für Patientensicherheit sorgen“

Wie toxische Männlichkeit der Gesundheit von Männern schadet

Update Radiologie

Springer Medizin

Abstract

Objective

Methods

Results

Conclusion

Key Points

Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten

Weitere Artikel der Ausgabe 10/2018

Non-contrast-enhanced magnetic resonance angiography: a reliable clinical tool for evaluating transplant renal artery stenosis

Increased unenhanced bowel-wall attenuation: a specific sign of bowel necrosis in closed-loop small-bowel obstruction

Use of whole body CT to detect patterns of CPR-related injuries after sudden cardiac arrest

Magnetic resonance guided focused high frequency ultrasound ablation for focal therapy in prostate cancer – phase 1 trial

Quantitative parameters of CT texture analysis as potential markersfor early prediction of spontaneous intracranial hemorrhage enlargement

Oesophageal squamous cell carcinoma: histogram-derived ADC parameters are not predictive of tumour response to chemoradiotherapy

Neu im Fachgebiet Radiologie

S3-Leitlinie zu Pankreaskrebs aktualisiert

Fünf Dinge, die im Kindernotfall besser zu unterlassen sind

„Nur wer sich gut aufgehoben fühlt, kann auch für Patientensicherheit sorgen“

Wie toxische Männlichkeit der Gesundheit von Männern schadet

Update Radiologie