Apparent diffusion coefficient (ADC) does not correlate with different serological parameters in myositis and myopathy

Abstract

Background

Magnetic resonance imaging (MRI) is widely used in several muscle disorders. Diffusion-weighted imaging (DWI) is an imaging modality, which can reflect microstructural tissue composition. The apparent diffusion coefficient (ADC) is used to quantify the random motion of water molecules in tissue.

Purpose

To investigate ADC values in patients with myositis and non-inflammatory myopathy and to analyze possible associations between ADC and laboratory parameters in these patients.

Material and Methods

Overall, 17 patients with several myositis entities, eight patients with non-inflammatory myopathies, and nine patients without muscle disorder as a control group were included in the study (mean age = 55.3 ± 14.3 years). The diagnosis was confirmed by histopathology in every case. DWI was obtained in a 1.5-T scanner using two b-values: 0 and 1000 s/mm². In all patients, the blood sample was acquired within three days to the MRI. The following serological parameters were estimated: C-reactive protein, lactate dehydrogenase, alanine aminotransferase, aspartate aminotransferase, creatine kinase, and myoglobine.

Results

The estimated mean ADC value for the myositis group was 1.89 ± 0.37 × 10^–3mm²/s and for the non-inflammatory myopathy group was 1.79 ± 0.33 × 10^–3 mm²/s, respectively. The mean ADC values (1.15 ± 0.37 × 10^–3 mm²/s) were significantly higher to unaffected muscles (vs. myositis P = 0.0002 and vs. myopathy P = 0.0021). There were no significant correlations between serological parameters and ADC values.

Conclusion

Affected muscles showed statistically significantly higher ADC values than normal muscles. No linear correlations between ADC and serological parameters were identified.

Keywords

Diffusion-weighted imaging (DWI)apparent diffusion coefficient (ADC)myositis myopathy serological parameters correlation

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References

Dalakas

. Inflammatory muscle diseases. N Engl J Med 2015; 372: 1734–1747.

O’Connell

Powell

Brennan

et al.

Whole-body MR imaging in the diagnosis of polymyositis. Am J Roentgenol 2002; 179: 967–971.

Leung

. Magnetic resonance imaging patterns of muscle involvement in genetic muscle diseases: a systematic review. J Neurol 2017; 264: 1320–1333.

Partovi

von Tengg-Kobligk

Bhojwani

et al.

Advanced non-contrast MR imaging in musculoskeletal radiology. Radiol Clin North Am 2015; 53: 549–567.

Fornasa

. Diffusion-weighted magnetic resonance imaging: what makes water run fast or slow? J Clin Imaging Sci 2011; 1: 27–27.

Ran

Liu

Sun

et al.

The diagnostic value of biexponential apparent diffusion coefficients in myopathy. J Neurol 2016; 263: 1296–1302.

Olsen

Price

et al.

Diffusion-weighted imaging of inflammatory myopathies: polymyositis and dermatomyositis. J Magn Reson Imaging 2008; 27: 212–217.

Surov

Nagata

Razek

et al.

Comparison of ADC values in different malignancies of the skeletal musculature: a multicentric analysis. Skeletal Radiol 2015; 44: 995–1000.

Surov

Behrmann

. Diffusion-weighted imaging of skeletal muscle lymphoma. Skeletal Radiol 2014; 43: 899–903.

10.

Harish

Chiavaras

Kotnis

et al.

MR imaging of skeletal soft tissue infection: utility of diffusion-weighted imaging in detecting abscess formation. Skeletal Radiol 2011; 40: 285–294.

11.

Barsotti

Zampa

Talarico

et al.

Thigh magnetic resonance imaging for the evaluation of disease activity in patients with idiopathic inflammatory myopathies followed in a single center. Muscle Nerve 2016; 54: 666–672.

12.

Kim

Laor

Horn

et al.

T2 mapping in Duchenne muscular dystrophy: distribution of disease activity and correlation with clinical assessments. Radiology 2010; 255: 899–908.

13.

Maillard

Jones

Owens

et al.

Quantitative assessment of MRI T2 relaxation time of thigh muscles in juvenile dermatomyositis. Rheumatology (Oxford) 2004; 43: 603–608.

14.

Chen

Liu

Bao

et al.

The correlation between apparent diffusion coefficient and tumor cellularity in patients: a meta-analysis. PLOS One 2013; 11: e79008–e79008.

15.

Le Bihan

Breton

Lallemand

et al.

MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology 1986; 161: 401–407.

16.

Gao

et al.

Diffusion tensor imaging in evaluation of thigh muscles in patients with polymyositis and dermatomyositis. Br J Radiol 2014; 87: 20140261–20140261.

17.

Dalakas

. Pathophysiology of inflammatory and autoimmune myopathies. Presse Med 2011; 40: e237–247.

18.

Huang

Geng

Zhan

et al.

Magnetic resonance imaging characteristics of hepatocyte apoptosis (induced by right portal vein ligation) and necrosis (induced by combined right portal vein and right hepatic artery ligation) in rats. J Int Med Res 2015; 43: 80–92.

19.

Schwarcz

Ursprung

Berente

et al.

In vivo brain edema classification: New insight offered by large b-value diffusion-weighted MR imaging. J Magn Reson Imaging 2007; 25: 26–31.

20.

Ponrartana

Andrade

Wren

et al.

Repeatability of chemical-shift-encoded water-fat MRI and diffusion-tensor imaging in lower extremity muscles in children. Am J Roentgenol 2014; 202: W567–573.

21.

Damon

. Effects of image noise in muscle diffusion tensor (DT)-MRI assessed using numerical simulations. Magn Reson Med 2008; 60: 934–944.

22.

Saupe

White

Stainsby

et al.

Diffusion tensor imaging and fiber tractography of skeletal muscle: optimization of B value for imaging at 1.5 T. Am J Roentgenol 2009; 192: W282–290.

23.

Zeng Q, Dong F, Shi F, et al. Apparent diffusion coefficient maps obtained from high b value diffusion-weighted imaging in the preoperative evaluation of gliomas at 3T: comparison with standard b value diffusion-weighted imaging. Eur Radiol 2017. doi: 10.1007/s00330-017-4910-0.