nach oben

Erschienen in:

10.04.2017 | Magnetic Resonance

Diffusion-weighted (DW) MRI in lung cancers: ADC test-retest repeatability

verfasst von: Alex Weller, Marianthi Vasiliki Papoutsaki, John C. Waterton, Arturo Chiti, Sigrid Stroobants, Joost Kuijer, Matthew Blackledge, Veronica Morgan, Nandita M deSouza

Erschienen in: European Radiology | Ausgabe 11/2017

Einloggen, um Zugang zu erhalten

Abstract

Purpose

To determine the test-retest repeatability of Apparent Diffusion Coefficient (ADC) measurements across institutions and MRI vendors, plus investigate the effect of post-processing methodology on measurement precision.

Methods

Thirty malignant lung lesions >2 cm in size (23 patients) were scanned on two occasions, using echo-planar-Diffusion-Weighted (DW)-MRI to derive whole-tumour ADC (b = 100, 500 and 800smm^-2). Scanning was performed at 4 institutions (3 MRI vendors). Whole-tumour volumes-of-interest were copied from first visit onto second visit images and from one post-processing platform to an open-source platform, to assess ADC repeatability and cross-platform reproducibility.

Results

Whole-tumour ADC values ranged from 0.66-1.94x10^-3mm²s^-1 (mean = 1.14). Within-patient coefficient-of-variation (wCV) was 7.1% (95% CI 5.7–9.6%), limits-of-agreement (LoA) -18.0 to 21.9%. Lesions >3 cm had improved repeatability: wCV 3.9% (95% CI 2.9–5.9%); and LoA -10.2 to 11.4%. Variability for lesions <3 cm was 2.46 times higher. ADC reproducibility across different post-processing platforms was excellent: Pearson’s R² = 0.99; CoV 2.8% (95% CI 2.3-3.4%); and LoA -7.4 to 8.0%.

Conclusion

A free-breathing DW-MRI protocol for imaging malignant lung tumours achieved satisfactory within-patient repeatability and was robust to changes in post-processing software, justifying its use in multi-centre trials. For response evaluation in individual patients, a change in ADC >21.9% will reflect treatment-related change.

Key Points

• In lung cancer, free-breathing DWI-MRI produces acceptable images with evaluable ADC measurement.

• ADC repeatability coefficient-of-variation is 7.1% for lung tumours >2 cm.

• ADC repeatability coefficient-of-variation is 3.9% for lung tumours >3 cm.

• ADC measurement precision is unaffected by the post-processing software used.

• In multicentre trials, 22% increase in ADC indicates positive treatment response.

O'Flynn EA, DeSouza NM (2011) Functional magnetic resonance: biomarkers of response in breast cancer. Breast Cancer Res 13(1):204PubMedPubMedCentralCrossRef

Kyriazi S, Collins DJ, Messiou C, Pennert K, Davidson RL, Giles SL et al (2011) Metastatic ovarian and primary peritoneal cancer: assessing chemotherapy response with diffusion-weighted MR imaging--value of histogram analysis of apparent diffusion coefficients. Radiology 261(1):182–192PubMedCrossRef

Blackledge MD, Collins DJ, Tunariu N, Orton MR, Padhani AR, Leach MO et al (2014) Assessment of treatment response by total tumor volume and global apparent diffusion coefficient using diffusion-weighted MRI in patients with metastatic bone disease: a feasibility study. PLoS One 9(4), e91779PubMedPubMedCentralCrossRef

Concatto NH, Watte G, Marchiori E, Irion K, Felicetti JC, Camargo JJ et al (2016) Magnetic resonance imaging of pulmonary nodules: accuracy in a granulomatous disease–endemic region. Eur Radiol 26(9):2915–2920CrossRef

Shen G, Jia Z, Deng H (2016) Apparent diffusion coefficient values of diffusion-weighted imaging for distinguishing focal pulmonary lesions and characterizing the subtype of lung cancer: a meta-analysis. Eur Radiol 26(2):556–566PubMedCrossRef

Kessler LG, Barnhart HX, Buckler AJ, Choudhury KR, Kondratovich MV, Toledano A et al (2015) The emerging science of quantitative imaging biomarkers terminology and definitions for scientific studies and regulatory submissions. Stat Methods Med Res 24(1):9–26PubMedCrossRef

Sullivan DC, Obuchowski NA, Kessler LG, Raunig DL, Gatsonis C, Huang EP et al (2015) Metrology standards for quantitative imaging biomarkers. Radiology 277(3):813–825PubMedPubMedCentralCrossRef

Raunig DL, McShane LM, Pennello G, Gatsonis C, Carson PL, Voyvodic JT et al (2015) Quantitative imaging biomarkers: a review of statistical methods for technical performance assessment. Stat Methods Med Res 24(1):27–67PubMedCrossRef

Bernardin L, Douglas NH, Collins DJ, Giles SL, O'Flynn EA, Orton M et al (2014) Diffusion-weighted magnetic resonance imaging for assessment of lung lesions: repeatability of the apparent diffusion coefficient measurement. Eur Radiol 24(2):502–511PubMedCrossRef

10.

Cui L, Yin J-B, Hu C-H, Gong S-C, Xu J-F, Yang J-S (2016) Inter-and intraobserver agreement of ADC measurements of lung cancer in free breathing, breath-hold and respiratory triggered diffusion-weighted MRI. Clin Imaging 40(5):892–896PubMedCrossRef

11.

Reischauer C, Froehlich JM, Pless M, Binkert CA, Koh DM, Gutzeit A (2014) Early treatment response in non-small cell lung cancer patients using diffusion-weighted imaging and functional diffusion maps--a feasibility study. PLoS One 9(10), e108052PubMedPubMedCentralCrossRef

12.

Yu J, Li W, Zhang Z, Yu T, Li D (2014) Prediction of early response to chemotherapy in lung cancer by using diffusion-weighted MR imaging. Sci World J 2014:135841

13.

Tsuchida T, Morikawa M, Demura Y, Umeda Y, Okazawa H, Kimura H (2013) Imaging the early response to chemotherapy in advanced lung cancer with diffusion-weighted magnetic resonance imaging compared to fluorine-18 fluorodeoxyglucose positron emission tomography and computed tomography. J Magnet Resonance Imaging: JMRI 38(1):80–88CrossRef

14.

Yabuuchi H, Hatakenaka M, Takayama K, Matsuo Y, Sunami S, Kamitani T et al (2011) Non-small cell lung cancer: detection of early response to chemotherapy by using contrast-enhanced dynamic and diffusion-weighted MR imaging. Radiology 261(2):598–604PubMedCrossRef

15.

Sun YS, Cui Y, Tang L, Qi LP, Wang N, Zhang XY et al (2011) Early evaluation of cancer response by a new functional biomarker: apparent diffusion coefficient. AJR Am J Roentgenol 197(1):W23–W29PubMedCrossRef

16.

Okuma T, Matsuoka T, Yamamoto A, Hamamoto S, Nakamura K, Inoue Y (2009) Assessment of early treatment response after CT-guided radiofrequency ablation of unresectable lung tumours by diffusion-weighted MRI: a pilot study. Br J Radiol 82(984):989–994PubMedPubMedCentralCrossRef

17.

Chang Q, Wu N, Ouyang H, Huang Y (2012) Diffusion-weighted magnetic resonance imaging of lung cancer at 3.0 T: a preliminary study on monitoring diffusion changes during chemoradiation therapy. Clin Imaging 36(2):98–103PubMedCrossRef

18.

Ohno Y, Koyama H, Yoshikawa T, Matsumoto K, Aoyama N, Onishi Y et al (2012) Diffusion-weighted MRI versus 18F-FDG PET/CT: performance as predictors of tumor treatment response and patient survival in patients with non-small cell lung cancer receiving chemoradiotherapy. AJR Am J Roentgenol 198(1):75–82PubMedCrossRef

19.

Regier M, Derlin T, Schwarz D, Laqmani A, Henes FO, Groth M et al (2012) Diffusion weighted MRI and 18F-FDG PET/CT in non-small cell lung cancer (NSCLC): does the apparent diffusion coefficient (ADC) correlate with tracer uptake (SUV)? Eur J Radiol 81(10):2913–2918PubMedCrossRef

20.

Weiss E, Ford JC, Olsen KM, Karki K, Saraiya S, Groves R et al (2016) Apparent diffusion coefficient (ADC) change on repeated diffusion-weighted magnetic resonance imaging during radiochemotherapy for non-small cell lung cancer: a pilot study. Lung Cancer 96:113–119PubMedCrossRef

21.

O’Connor JP, Aboagye EO, Adams JE, Aerts HJ, Barrington SF, Beer AJ, et al (2016) Imaging biomarker roadmap for cancer studies. Nat Rev Clin Oncol

22.

Douglas N, Winfield J, deSouza NM, Collins DJ, Orton MO (2013) Development of a phantom for quality assurance in multicentre clinical trials with diffusion-weighted MRI. Proc Int Soc Magnet Resonance Med. Presentation number 3114

23.

Satoh S, Kitazume Y, Ohdama S, Kimula Y, Taura S, Endo Y (2008) Can malignant and benign pulmonary nodules be differentiated with diffusion-weighted MRI? AJR Am J Roentgenol 191(2):464–470PubMedCrossRef

24.

Blackledge MD, Leach MO, Collins DJ, Koh DM (2011) Computed diffusion-weighted MR imaging may improve tumor detection. Radiology 261(2):573–581PubMedCrossRef

25.

Forkman J (2009) Estimator and tests for common coefficients of variation in normal distributions. Comm Stat—Theory Methods 38(2):233–251CrossRef

26.

Weller A, O'Brien ME, Ahmed M, Popat S, Bhosle J, McDonald F et al (2016) Mechanism and non-mechanism based imaging biomarkers for assessing biological response to treatment in non-small cell lung cancer. Eur J Cancer 59:65–78PubMedCrossRef

27.

Liu Y, de Souza NM, Shankar LK, Kauczor HU, Trattnig S, Collette S et al (2015) A risk management approach for imaging biomarker-driven clinical trials in oncology. Lancet Oncol 16(16):e622–e628PubMedCrossRef

28.

Wade O (1954) Movements of the thoracic cage and diaphragm in respiration. J Physiol 124(2):193–212PubMedPubMedCentralCrossRef

29.

Plathow C, Fink C, Ley S, Puderbach M, Eichinger M, Zuna I et al (2004) Measurement of tumor diameter-dependent mobility of lung tumors by dynamic MRI. Radiother Oncol: J Eur Soc Ther Radiol Oncol 73(3):349–354CrossRef

30.

Hogg N, Winfield J, Collins DJ, de Souza NM, Orton M (2012) Development of a perfusion insensitivemeasurement of the apparent diffusion coefficient: a simulation. ESMRMB 2012, 29th Annual Scientific Meeting, Lisbon. Book of Abstracts (57)

31.

Taouli B, Beer AJ, Chenevert T, Collins D, Lehman C, Matos C et al (2016) Diffusion-weighted imaging outside the brain: Consensus statement from an ISMRM-sponsored workshop. J Magnet Resonance Imaging: JMRI 44(3):521–540CrossRef

32.

Brihuega‐Moreno O, Heese FP, Hall LD (2003) Optimization of diffusion measurements using Cramer‐Rao lower bound theory and its application to articular cartilage. Magn Reson Med 50(5):1069–1076PubMedCrossRef

33.

Saritas EU, Lee JH, Nishimura DG (2011) SNR dependence of optimal parameters for apparent diffusion coefficient measurements. IEEE Trans Med Imaging 30(2):424–437PubMedCrossRef

34.

Tan ET, Marinelli L, Slavens ZW, King KF, Hardy CJ (2013) Improved correction for gradient nonlinearity effects in diffusion-weighted imaging. J Magnet Resonance Imaging: JMRI 38(2):448–453CrossRef

35.

Rata M, Collins DJ, Darcy J, Messiou C, Tunariu N, Desouza N et al (2015) Assessment of repeatability and treatment response in early phase clinical trials using DCE-MRI: comparison of parametric analysis using MR- and CT-derived arterial input functions. Eur Radiol

36.

Ashton E, Raunig D, Ng C, Kelcz F, McShane T, Evelhoch J (2008) Scan-rescan variability in perfusion assessment of tumors in MRI using both model and data-derived arterial input functions. J Magnet Resonance Imaging: JMRI 28(3):791–796CrossRef

37.

Rata M, Collins DJ, Darcy J, Messiou C, Tunariu N, Desouza N et al (2016) Assessment of repeatability and treatment response in early phase clinical trials using DCE-MRI: comparison of parametric analysis using MR- and CT-derived arterial input functions. Eur Radiol 26(7):1991–1998PubMedCrossRef

38.

Scaranelo AM, Eiada R, Jacks LM, Kulkarni SR, Crystal P (2012) Accuracy of unenhanced MR imaging in the detection of axillary lymph node metastasis: study of reproducibility and reliability. Radiology 262(2):425–434PubMedCrossRef

39.

Padhani AR, Liu G, Koh DM, Chenevert TL, Thoeny HC, Takahara T et al (2009) Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia (New York, NY) 11(2):102–125CrossRef

Titel: Diffusion-weighted (DW) MRI in lung cancers: ADC test-retest repeatability
verfasst von: Alex Weller
Marianthi Vasiliki Papoutsaki
John C. Waterton
Arturo Chiti
Sigrid Stroobants
Joost Kuijer
Matthew Blackledge
Veronica Morgan
Nandita M deSouza
Publikationsdatum: 10.04.2017
Verlag: Springer Berlin Heidelberg
Erschienen in: European Radiology / Ausgabe 11/2017
Print ISSN: 0938-7994
Elektronische ISSN: 1432-1084
DOI: https://doi.org/10.1007/s00330-017-4828-6

Neu im Fachgebiet Radiologie

18.04.2024 | Pädiatrische Notfallmedizin | Nachrichten

Update Radiologie

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

Newsletter bestellen

Springer Medizin

Diffusion-weighted (DW) MRI in lung cancers: ADC test-retest repeatability

Abstract

Purpose

Methods

Results

Conclusion

Key Points

Neu im Fachgebiet Radiologie

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

Studie bestätigt Potenzial von KI in der Radiologie

Update Radiologie

Springer Medizin

Abstract

Purpose

Methods

Results

Conclusion

Key Points

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

Weitere Artikel der Ausgabe 11/2017

Percutaneous MR-guided focal cryoablation for recurrent prostate cancer following radiation therapy: retrospective analysis of iceball margins and outcomes

MRI findings in men on active surveillance for prostate cancer: does dutasteride make MRI visible lesions less conspicuous? Results from a placebo-controlled, randomised clinical trial

Severity-specific alterations in CBF, OEF and CMRO2 in cirrhotic patients with hepatic encephalopathy

Investigation of reference levels and radiation dose associated with abdominal EVAR (endovascular aneurysm repair) procedures across several European Centres

Interim heterogeneity changes measured using entropy texture features on T2-weighted MRI at 3.0 T are associated with pathological response to neoadjuvant chemotherapy in primary breast cancer

Do we need 3D tube current modulation information for accurate organ dosimetry in chest CT? Protocols dose comparisons

Neu im Fachgebiet Radiologie

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

Studie bestätigt Potenzial von KI in der Radiologie

Update Radiologie