ORIGINAL PAPER
Application of the apparent diffusion coefficient in magnetic resonance imaging in an assessment of the early response to treatment in Hodgkin’s and non-Hodgkin’s lymphoma – pilot study
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Publication date: 2018-05-12
Pol J Radiol, 2018; 83: 210-214
KEYWORDS
ABSTRACT
Purpose:
Lymphoproliferative neoplasms are the largest and most frequently diagnosed entities in the group of haematological malignancies. The aim of the study was to assess whether apparent diffusion coefficient (ADC) measured on the first day of the second cycle of chemotherapy could be a predictor of prognosis and of the final treatment’s outcome.
Material and methods:
The study included 27 patients with diagnosed Hodgkin’s and non-Hodgkin’s lymphoma, who had magnetic resonance (MR) performed with diffusion weighted imaging/apparent diffusion coefficient (DWI/ADC) before and on the first day of the second cycle of chemotherapy. Imaging was performed using a 1.5 T MR scanner. ADC was measured in lymphoma infiltration in the area of the lowest signal in the ADC map and the highest signal on β 800 images in post-treatment study. After that, the corresponding area was determined in a pre-treatment study and an ADC value was measured.
Results:
The difference between ADC values in pre-treatment (ADC = 720 mm2/s) and post-treatment (ADC = 1059 mm2/s) studies was statistically significant (p < 0.001). Cutoff values for estimating response to treatment were established at the level of ADC 1080 mm2/s, and ADC to muscle ratio at 0.82 in post-treatment study. Patients with ADC > 752 mm2/s before treatment manifested lower probability of progression than patients with ADC < 752 mm2/s.
Conclusions:
ADC measurement’s before treatment and on the first day of the second cycle of chemotherapy can be used as a prognostic marker in lymphoma therapy. ADC values lower than 1080 mm2/s and an increase of the ratio after the treatment can be considered as a marker of disease progression.
REFERENCES (17)
1.
Cheson BD, Fisher RI, Barrington SF, et al. Recommendations for initial evaluation, staging, and response assessment of hodgkin and non-hodgkin lymphoma: The lugano classification. J Clin Oncol 2014; 32: 3059-3067.
2.
Campo E, Swerdlow SH, Harris NL, et al. The 2008 WHO classification of lymphoid neoplasms and beyond : evolving concepts and practical applications The 2008 WHO classification of lymphoid neoplasms and beyond : evolving concepts and practical applications. 2014; 117: 5019-5033.
3.
Juweid ME, Stroobants S, Hoekstra OS, et al. Use of positron emission tomography for response assessment of lymphoma: Consensus of the imaging subcommittee of international harmonization project in lymphoma. J Clin Oncol 2007; 25: 571-578.
4.
Asenbaum U, Nolz R, Karanikas G, et al. Evaluation of [18F]-FDG-based hybrid imaging combinations for assessment of bone marrow involvement in lymphoma at initial staging. PLoS One 2016; 11: 1-12.
5.
Albano D, Patti C, La Grutta L, et al. Comparison between whole-body MRI with diffusion-weighted imaging and PET/CT in staging newly diagnosed FDG-avid lymphomas. Eur J Radiol 2016; 85: 313-318.
6.
Azzedine B, Kahina MB, Dimitri P, et al. Whole-body diffusion- weighted MRI for staging lymphoma at 3.0T: Comparative study with MR imaging at 1.5T. Clin Imaging 2015; 39: 104-109.
7.
Lin C, Itti E, Luciani A, et al. Whole-body diffusion-weighted imaging in lymphoma. Cancer Imaging 2010; 10: 172-178.
8.
Johnson SA, Kumar A, Matasar MJ, et al. Imaging for Staging and Response Assessment in Lymphoma. Radiology 2015; 276: 323-338.
9.
Wu X, Pertovaara H, Korkola P, et al. Correlations between functional imaging markers derived from PET/CT and diffusion-weighted MRI in diffuse large B-cell lymphoma and follicular lymphoma. PLoS One 2014; 9: 1-8.
10.
Kwee TC, Takahara T, Ochiai R, et al. Diffusion-weighted whole-body imaging with background body signal suppression (DWIBS): Features and potential applications in oncology. Eur Radiol 2008; 18: 1937-1952.
11.
Kwee TC, Basu S, Torigian DA, et al. Evolving importance of diffusion-weighted magnetic resonance imaging in lymphoma. PET Clin 2012; 7: 73-82.
12.
Padhani AR, Koh DM, Collins DJ. Whole-Body Diffusion-weighted MR Imaging in Cancer: Current Status and Research Directions. Radiology 2011; 261: 700-718.
13.
Chen Y, Zhong J, Wu H, et al. The clinical application of whole-body diffusion-weighted imaging in the early assessment of chemotherapeutic effects in lymphoma: The initial experience. Magn Reson Imaging 2012; 30: 165-170.
14.
Stéphane V, Samuel B, Vincent D, et al. Comparison of PET-CT and magnetic resonance diffusion weighted imaging with body suppression (DWIBS) for initial staging of malignant lymphomas. Eur J Radiol 2013; 82: 2011-2017.
15.
Frampas E. Lymphomas: Basic points that radiologists should know. Diagn Interv Imaging 2013; 94: 131-144.
16.
Mosavi F, Wassberg C, Selling J, et al. Whole-body diffusion-weighted MRI and 18F-FDG PET/CT can discriminate between different lymphoma subtypes. Clin Radiol 2015; 70: 1229-1236.
17.
Usuda K, Maeda S, Motono N, et al. Diffusion weighted imaging can distinguish benign from malignant mediastinal tumors and mass lesions: Comparison with positron emission tomography. Asian Pacific J Cancer Prev 2015; 16: 6469-6475.