Skip to main content

Advertisement

SpringerLink
Log in

Nonsuppressing normal thymus on chemical-shift MR imaging and anterior mediastinal lymphoma: differentiation with diffusion-weighted MR imaging by using the apparent diffusion coefficient

  • Chest
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

To prospectively evaluate usefulness of the apparent diffusion coefficient (ADC) in differentiating anterior mediastinal lymphoma from nonsuppressing normal thymus on chemical-shift MR, and to look at the relationship between patient age and ADC.

Methods

Seventy-three young subjects (25 men, 48 women; age range, 9-29 years), who underwent chemical-shift MR and diffusion-weighted MR were divided into a normal thymus group (group A, 40 subjects), and a lymphoma group (group B, 33 patients). For group A, all subjects had normal thymus with no suppression on opposed-phase chemical-shift MR. Two readers measured the signal intensity index (SII) and ADC. Differences in SII and ADC between groups were tested using t-test. ADC was correlated with age using Pearson correlation coefficient.

Results

Mean SII±standard deviation was 2.7±1.8% for group A and 2.2±2.4% for group B, with no significant difference between groups (P=.270). Mean ADC was 2.48±0.38x10-3mm2/s for group A and 1.24±0.23x10-3mm2/s for group B. A significant difference between groups was found (P<.001), with no overlap in range. Lastly, significant correlation was found between age and ADC (r=0.935, P<.001) in group A.

Conclusions

ADC of diffusion-weighted MR is a noninvasive and accurate parameter for differentiating lymphoma from nonsuppressing thymus on chemical-shift MR in young subjects.

Key Points

• SII cannot differentiate mediastinal lymphoma from nonsuppressing normal thymus at visual assessment

• ADC is useful for distinguishing nonsuppressing normal thymus from mediastinal lymphoma

• ADC is more accurate than transverse-diameter and surface-area in this discrimination

• ADC of normal thymus is age dependent and increases with increasing age

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Abbreviations

ADC:

Apparent diffusion coefficient

AUROC:

Area under the receiving operating characteristic curve

CT:

Computed tomography

MR:

Magnetic resonance

PET:

Positron emission tomography

ROI:

Region of interest

SII:

Signal intensity index

References

  1. MC MI, Flores EJ, Shepard JA, Ackman JB (2016) Pitfalls in the imaging and interpretation of benign thymic lesions: how thymic MRI can help. AJR Am J Roentgenol 206:W1–W8

    Article  Google Scholar 

  2. Priola AM, Gned D, Veltri A, Priola SM (2016a) Chemical shift and diffusion-weighted magnetic resonance imaging of the anterior mediastinum in oncology: current clinical applications in qualitative and quantitative assessment. Crit Rev Oncol Hematol 98:335–357

    Article  PubMed  Google Scholar 

  3. Nishino M, Ashiku SK, Kocher ON, Thurer RL, Boiselle PM, Hatabu H (2006) The thymus: a comprehensive review. Radiographics 26:335–348

    Article  PubMed  Google Scholar 

  4. Priola AM, Priola SM, Ciccone G et al (2015) Differentiation of rebound and lymphoid thymic hyperplasia from anterior mediastinal tumors with dual-echo chemical-shift magnetic resonance imaging in adulthood: reliability of the chemical-shift ratio and signal-intensity index. Radiology 274:238–249

    Article  PubMed  Google Scholar 

  5. Inaoka T, Takahashi K, Iwata K et al (2005) Evaluation of normal fatty replacement of the thymus with chemical-shift MR imaging for identification of the normal thymus. J Magn Reson Imaging 22:341–346

    Article  PubMed  Google Scholar 

  6. Ackman JB, Mino-Kenudson M, Morse CR (2012) Nonsuppressing normal thymus on chemical shift magnetic resonance imaging in a young woman. J Thorac Imaging 27:196–198

    Article  Google Scholar 

  7. Priola AM, Galetto G, Priola SM (2014) Diagnostic and functional imaging of thymic and mediastinal involvement in lymphoproliferative disorders. Clin Imaging 38:771–784

    Article  PubMed  Google Scholar 

  8. Ackman JB, Kovacina B, Carter BW et al (2013) Sex difference in normal thymic appearance in adults 20-30 years of age. Radiology 268:245–253

    Article  PubMed  Google Scholar 

  9. Blazic IM, Lilic GB, Gajic MM (2017) Quantitative assessment of rectal cancer response to neoadjuvant combined chemotherapy and radiation therapy: comparison of three methods of positioning region of interest for ADC measurements at diffusion-weighted MR imaging. Radiology 282:418–428

    Article  PubMed  Google Scholar 

  10. DMJ L, Beets GL, Mass M et al (2011) Tumor ADC measurements in rectal cancer: effect of ROI methods on ADC values and interobserver variability. Eur Radiol 21:2567–2574

    Article  Google Scholar 

  11. Fischer MA, Nanz D, Hany T et al (2011) Diagnostic accuracy of whole-body MRI/DWI image fusion for detection of malignant tumours: a comparison with PET/CT. Eur Radiol 21:246–255

    Article  PubMed  Google Scholar 

  12. Filli L, Wurnig MC, Luechinger R, Eberhardt C, Guggenberger R, Boss A (2015) Whole-body intravoxel incoherent motion imaging. Eur Radiol 25:2049–2058

    Article  PubMed  Google Scholar 

  13. Clauser P, Marcon M, Maieron M, Zuiani C, Bazzocchi M, Baltzer PA (2016) Is there a systematic bias of apparent diffusion coefficient (ADC) measurements of the breast if measured on different workstations? An inter- and intra-reader agreement study. Eur Radiol 26:2291–2296

    Article  PubMed  Google Scholar 

  14. Priola AM, Priola SM, Parlatano D et al (2017a) Apparent diffusion coefficient measurements in diffusion-weighted magnetic resonance imaging of the anterior mediastinum: inter-observer reproducibility of five different methods of region-of-interest positioning. Eur Radiol 27:1386–1394

    Article  PubMed  Google Scholar 

  15. Ackman JB (2014) A practical guide to nonvascular thoracic magnetic resonance imaging. J Thorac Imaging 29:17–29

    Article  PubMed  Google Scholar 

  16. Abdel Razek AA, Elmorsy A, Elshafey M, Elhadedy T, Hamza O (2009) Assessment of mediastinal tumors with diffusion weighted single shot echo planar MR imaging. J Magn Reson Imaging 30:535–540

    Article  Google Scholar 

  17. Abdel Razek AA, Elkammary S, Elmorsy AS, Elshafey M, Elhadedy T (2011) Characterization of mediastinal lymphadenopathy with diffusion-weighted imaging. Magn Reson Imaging 29:167–172

    Article  PubMed  Google Scholar 

  18. Gümüștaș S, Inan N, Sarisoy HT et al (2011) Malignant versus benign mediastinal lesions: quantitative assessment with diffusion weighted MR imaging. Eur Radiol 21:2255–2260

    Article  PubMed  Google Scholar 

  19. Gümüștaș S, Inan N, Akansel G, Bașyiğit I, Ciftçi E (2013) Differentiation of lymphoma versus sarcoidosis in the setting of mediastinal-hilar lymphadenopathy: assessment with diffusion-weighted MR imaging. Sarcoidosis Vasc Diffuse Lung Dis 30:52–59

    PubMed  Google Scholar 

  20. Shin KE, Yi CA, Kim TS et al (2014) Diffusion-weighted MRI for distinguishing non-neoplastic cysts from solid masses in the mediastinum: problem-solving in mediastinal masses of indeterminate internal characteristics on CT. Eur Radiol 24:677–684

    Article  PubMed  Google Scholar 

  21. Abdel Razek AA, Khairy M, Nada N (2014) Diffusion-weighted MR imaging in thymic epithelial tumors: correlation with World Health Organization classification and clinical staging. Radiology 273:268–275

    Article  PubMed  Google Scholar 

  22. Priola AM, Priola SM, Giraudo MT et al (2016b) Diffusion-weighted magnetic resonance imaging of thymoma: ability of the apparent diffusion coefficient in predicting the World Health Organization (WHO) classification and the Masaoka-Koga staging system and its prognostic significance on disease-free survival. Eur Radiol 26:2126–2138

    Article  PubMed  Google Scholar 

  23. Coolen J, De Keyzer F, Nafteux P et al (2015) Malignant pleural mesothelioma: visual assessment by using pleural pointillism at diffusion-weighted MR imaging. Radiology 274:576–584

    Article  PubMed  Google Scholar 

  24. Priola AM, Priola SM, Gned D et al (2017b) Diffusion-weighted quantitative MRI of pleural abnormalities: intra- and interobserver variability in the apparent coefficient measurements. J Magn Reson Imaging 46:769–782

    Article  PubMed  Google Scholar 

  25. Bossuyt PM, Reitsma JB, Bruns DE et al (2015) STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies. Radiology 277:826–832

    Article  PubMed  Google Scholar 

  26. Araki T, Nishino M, Gao W et al (2016) Normal thymus in adults: appearance on CT and associations with age, sex, BMI and smoking. Eur Radiol 26:15–24

    Article  PubMed  Google Scholar 

  27. Priola AM, Priola SM, Gned D, Giraudo MT, Fornari A, Veltri A (2016c) Comparison of CT and chemical-shift MRI for differentiating thymoma from non-thymomatous conditions in myasthenia gravis: value of qualitative and quantitative assessment. Clin Radiol 71:e157–e169

    Article  CAS  PubMed  Google Scholar 

  28. Priola AM, Priola SM, Gned D et al (2016d) Diffusion-weighted magnetic resonance quantitative imaging to diagnose benign conditions from malignancies of the anterior mediastinum: improvement of diagnostic accuracy by comparing perfusion-free to perfusion-sensitive measurements of the apparent diffusion coefficient. J Magn Reson Imaging 44:758–769

    Article  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Coolen J, Vansteenkiste J, De Keyzer F et al (2014) Characterisation of solitary pulmonary lesions combining visual perfusion and quantitative diffusion MR imaging. Eur Radiol 24:531–541

    Article  PubMed  Google Scholar 

  31. Nougaret S, Vargas HA, Lakhman Y et al (2016) Intravoxel incoherent motion-derived histogram metrics for assessment of response after combined chemotherapy and radiation therapy in rectal cancer: initial experience and comparison between single-section and volumetric analyses. Radiology 280:446–454

    Article  PubMed  PubMed Central  Google Scholar 

  32. Priola AM, Veltri A, Priola SM (2016e) Importance of different region-of-interest protocols for the apparent diffusion coefficient measurement of tumors in diffusion-weighted magnetic resonance imaging. J Magn Reson Imaging 44:1056

    Article  PubMed  Google Scholar 

  33. Ahlawat S, Khandheria P, Del Grande F et al (2016) Interobserver variability of selective region-of-interest measurement protocols for quantitative diffusion weighted imaging in soft tissue masses: comparison with whole tumor volume measurements. J Magn Reson Imaging 43:446–454

    Article  PubMed  Google Scholar 

  34. DeLong ER, DeLong DM, Clarke-Pearson DL (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44:837–845

    Article  CAS  PubMed  Google Scholar 

  35. Littooij AS, Kwee TC, Barber I et al (2014) Whole-body MRI for initial staging of paediatric lymphoma: prospective comparison to an FDG-PET/CT-based reference standard. Eur Radiol 24:1153–1165

    Article  PubMed  Google Scholar 

  36. Punwani S, Taylor SA, Saad ZZ et al (2013) Diffusion-weighted MRI of lymphoma: prognostic utility and implications for PET/MRI? Eur J Nucl Med Mol Imaging 40:373–385

    Article  PubMed  Google Scholar 

  37. Ackman JB, Gaissert HA, Lanuti M et al (2016) Impact of nonvascular thoracic MR imaging on the clinical decision making of thoracic surgeons: a 2-year prospective study. Radiology 280:464–474

    Article  PubMed  Google Scholar 

  38. Adam SZ, Nikolaidis P, Horowitz JM et al (2016) Chemical shift MR of the adrenal gland: principles, pitfalls, and applications. Radiographics 36:414–432

    Article  PubMed  Google Scholar 

  39. Priola AM, Priola SM (2014) Imaging of thymus in myasthenia gravis: from thymic hyperplasia to thymic tumor. Clin Radiol 69:e230–e245

    Article  CAS  PubMed  Google Scholar 

  40. Inaoka T, Takahashi K, Mineta M et al (2007) Thymic hyperplasia and thymus gland tumors: differentiation with chemical shift MR imaging. Radiology 243:869–876

    Article  PubMed  Google Scholar 

  41. Priola AM, Priola SM (2009) Primary mediastinal Hodgkin lymphoma and rebound thymic hyperplasia: differentiation with chemical-shift magnetic resonance imaging after treatment. Int J Hematol 90:8–10

    Article  PubMed  Google Scholar 

  42. Gawande RS, Khurana A, Messing S et al (2012) Differentiation of normal thymus from anterior mediastinal lymphoma and lymphoma recurrence at pediatric PET/CT. Radiology 262:613–622

    Article  PubMed  Google Scholar 

  43. Jerushalmi J, Frenkel A, Bar-Shalom R, Khoury J, Israel O (2009) Physiologic thymic uptake of 18F-FDG in children and young adults: a PET-CT evaluation of incidence, patterns, and relationship to treatment. J Nucl Med 50:849–853

    Article  PubMed  Google Scholar 

  44. Yabuuchi H, Matsuo Y, Abe K et al (2015) Anterior mediastinaal solid tumours in adults: characterization using dynamic contrast-enhanced MRI, diffusion-weighted MRI, and FDG-PET/CT. Clin Radiol 70:1289–1298

    Article  CAS  PubMed  Google Scholar 

  45. Seki S, Koyama H, Ohno Y et al (2014) Diffusion-weighted MR imaging vs. multi-detector row-CT: direct comparison of capability for assessment of management needs for anterior mediastinal solitary tumors. Eur J Radiol 83:835–842

    Article  PubMed  Google Scholar 

  46. Park BK, Kim CK, Kim B, Lee JH (2007) Comparison of delayed enhanced CT and chemical shift MR for evaluating hyperattenuating incidental adrenal masses. Radiology 243:760–765

    Article  PubMed  Google Scholar 

  47. Liu D, Kitajima M, Awai K et al (2006) Ectopic cervical thymus in an infant. Radiat Med 24:452–455

    Article  PubMed  Google Scholar 

Download references

Funding

The authors state that this work has not received any funding.

Author information

Authors and Affiliations

  1. Department of Diagnostic Imaging, San Luigi Gonzaga University Hospital, Regione Gonzole 10, 10043, Orbassano, Torino, Italy

    Adriano Massimiliano Priola, Sandro Massimo Priola, Dario Gned & Andrea Veltri

  2. Department of Mathematics, “Giuseppe Peano”, University of Torino, Via Carlo Alberto 10, 10123, Torino, Italy

    Maria Teresa Giraudo

Authors
  1. Adriano Massimiliano Priola
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sandro Massimo Priola
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dario Gned
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Maria Teresa Giraudo
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Andrea Veltri
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Adriano Massimiliano Priola.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Adriano M. Priola.

Conflict of interest

The authors of this manuscript declare no relationships with any companies, with products or services that may be related to the subject matter of the article.

Statistics and biometry

One of the authors (Maria T. Giraudo) has significant statistical expertise.

Ethical approval

Institutional Review Board approval was obtained.

Informed consent

Written informed consent was obtained from all subjects (patients) in this study.

Methodology

1. prospective

2. observational

3. performed at one institution

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Priola, A.M., Priola, S.M., Gned, D. et al. Nonsuppressing normal thymus on chemical-shift MR imaging and anterior mediastinal lymphoma: differentiation with diffusion-weighted MR imaging by using the apparent diffusion coefficient. Eur Radiol 28, 1427–1437 (2018). https://doi.org/10.1007/s00330-017-5142-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-017-5142-z

Keywords

Search

Navigation