Abstract
Aim: Lymphadenopathy (LAP) is one of the most common daily practice clinical findings in children. LAPs that involve more than one region and do not decrease with treatment are a significant cause of anxiety for clinicians and families. In this occurence, ultrasonography, which is the primary imaging method, is insufficient in some cases. Our aim is to make histopathological predictions with apparent diffusion coefficient (ADC) histogram analysis.
Material and Method: A total of thirty-one patients, seventeen male and fourteen female, who underwent magnetic resonance imaging and were diagnosed histopathologically (with tru-cut or excisional biopsy) were included in our study. Magnetic resonance imagings were evaluated retrospectively.
Results: We could not differentiate lymphoma (when considered as a single group), granulomatous LAP and reactive lymphoid hyperplasia with an ADC histogram analysis (p>0.05). However, when the lymphoma subgroups were evaluated separately, we could only distinguish Burkitt’s lymphoma (with ADCmin values) from other pathologies (p<0.05). The optimal cut-off value distinguishing Burkitt’s lymphoma from other groups was 245×10-6 mm2/sec in receiver operating characteristic curve analysis (AUC 0.981, sensitivity 75%, specificity 93%, PPV 67%, NPV 93%). As in recent studies, we did not find significant differences in ADC histogram analysis values of reactive lymphoid hyperplasia, granulomatous LAPs and lymphomas (when considered as a single group). However, when the lymphoma subgroups were considered separately, we were able to distinguish Burkitt’s lymphoma from other subgroups and granulomatous LAP, reactive lymphoid hyperplasia with the ADCmin value.
Conclusion: The ADCmin value in pediatric LAPs may contribute to the diagnosis of Burkitt’s lymphoma.
Keywords
Lymphadenopathy magnetic resonance imaging histogram analysis apparent diffusion coefficient
Project Number
yok
References
- Nield LS, Kamat D. Lymphadenopathy in children: when and how to evaluate. Clin Pediatr (Phila) 2004; 43: 25–33.
- Tower RL, Carmitta BM. Lymphadenopathy. In: Kliegman RM, Stanton BF, St Geme JW, Schor NF (eds). Nelson Textbook of Pediatrics (20th ed). California, 2016: 2413-15.
- Abdel Razek AA, Soliman NY, Elkhamary S, Alsharaway ML, Tawfik A. Role of diffusionweighted MR imaging in cervical lymphadenopathy. Eur Radiol 2006; 16: 1468-77.
- Vandecaveye V, De Keyzer F, Vander Pooten V, et al. Head and neck squamous cell carcinoma: value of diffusion-weighted MR imaging for nodal staging. Radiology 2009; 251: 134-46.
- Wang YJ, Xu XQ, Hu H, et al. Histogram analysis of apparent diffusion coefficient maps for the differentiation between lymphoma and metastatic lymph nodes of squamous cell carcinoma in head and neck region. Acta Radiol 2018; 59: 672-80.
- De Paepe KN, De Keyzer F, Wolter P, et al. Improving lymph node characterization in staging malignant lymphoma using first-order ADC texture analysis from whole-body diffusion-weighted MRI. J Magn Reson Imaging 2018; 48: 897-906.
- Le Bihan D. Molecular diffusion nuclear magnetic resonance imaging. Magn Reson Q 1991; 7: 1-30.
- Koh DM, Collins DJ. Diffusion-weighted MRI in the body: applications and challenges in oncology. AJR Am J Roentgenol 2007; 188: 1622-35.
- Donners R, Blackledge M, Tunariu N, Messiou C, Merkle EM, Koh DM. Quantitative whole-body diffusion- weighted MR imaging. Magn Reson Imaging Clin N Am 2018; 26: 479-94.
- Chang KL, Arber DA, Gaal KK, Weiss LM. Lymph nodes and spleen. In: Silverberg SG, DeLellis RA, Frable WJ, LiVolsi VA, Wick MR, editors. Silverberg’s Principles and practice of surgical pathology and cytopathology. Volume 1. New York: Churchill Livingstone; 2006: 507–607
- Brincker H. Sarcoid reactions in malignant tumours. Cancer Treat Rev 1986; 13: 147-56.
- ElSaid NA, Nada OM, Habib YS, et al. Diagnostic accuracy of diffusion weighted MRI in cervical lymphadenopathy cases correlated with pathology results. Egypt J Radiol Nuclear Med 2014; 45: 1115-25.
- Nomori H, Mori T, Ikeda K, et al. Diffusion-weighted magnetic resonance imaging can be used in place of positron emission tomography for N staging of nonsmall cell lung cancer with fewer false-positive results. J Thorac Cardiovasc Surg 2008; 135: 816-22.
- Abdel Razek AA, Gaballa G, Elashry R, Elkhamary S. Diffusion-weighted MR imaging of mediastinal lymphadenopathy in children. Jpn J Radiol 2015; 33: 449-54.
- Vidiri A, Minosse S, Piludu F, et al. Cervical lymphadenopathy: can the histogram analysis of apparent diffusion coefficient help to differentiate between lymphoma and squamous cell carcinoma in patients with unknown clinical primary tumor? Radiol Med 2019; 124: 19-26.
- Lian S, Zhang C, Chi J, Huang Y, Shi F, Xie C. Differentiation between nasopharyngeal carcinoma and lymphoma at the primary site using whole-tumor histogram analysis of apparent diffusion coefficient maps. Radiol Med 2020; 125: 647-53.
- Song C, Cheng P, Cheng J, Zhang Y, Xie S. Value of apparent diffusion coefficient histogram analysis in the differential diagnosis of nasopharyngeal lymphoma and nasopharyngeal carcinoma based on readout-segmented diffusion-weighted imaging. Front Oncol 2021; 11: 632796.
- Molyneux EM, Rochford R, Griffin B, et al. Burkitt’s lymphoma. Lancet 2012; 379: 1234-44.
- Thomas AG, Vaidhyanath R, Kirke R, Rajesh A. Extranodal lymphoma from head to toe: part 1, the head and spine. AJR Am J Roentgenol 2011; 197: 350–6.
- Gu J, Chan T, Zhang J, Leung AY, Kwong YL, Khong PL. Whole-body diffusion-weighted imaging: the added value to whole-body MRI at initial diagnosis of lymphoma. AJR Am J Roentgenol 2011; 197: W384–91.
- Kwee TC, Ludwig I, Uiterwaal CS, et al. ADC measurements in the evaluation of lymph nodes in patients with non-Hodgkin lymphoma: feasibility study. MAGMA 2011; 24: 1-8.
- Holzapfel K, Duetsch S, Fauser C, Eiber M, Rummeny EJ, Gaa J. Value of diffusion-weighted MR imaging in the differentiation between benign and malignant cervical lymph nodes. Eur J Radiol 2009; 72: 381-7.
- Perrone A, Guerrisi P, Izzo L, et al. Diffusion-weighted MRI in cervical lymph nodes: differentiation between benign and malignant lesions. Eur J Radiol 2011; 77: 281-6.
- De Paepe K, Bevernage C, De Keyzer F, et al. Whole-body diffusion-weighted magnetic resonance imaging at 3 Tesla for early assessment of treatment response in non-Hodgkin lymphoma: a pilot study. Cancer Imaging 2013; 13: 53-62.
- Wu X, Nerisho S, Dastidar P, et al. Comparison of different MRI sequences in lesion detection and early response evaluation of diffuse large B-cell lymphoma--a whole-body MRI and diffusion-weighted imaging study. NMR Biomed 2013; 26: 1186-94.
- Santos FS, Verma N, Marchiori E, et al. MRI-based differentiation between lymphoma and sarcoidosis in mediastinal lymph nodes. J Bras Pneumol 2021; 47: e20200055.
- Sabri YY, Kolta MFF, Khairy MA. MR diffusion imaging in mediastinal masses the differentiation between benign and malignant lesions. Egypt J Radiol Nucl Med 2017; 48: 569–80.
- Sabri YY, Nossair EZB, Assal HH et al. Role of diffusion weighted MR-imaging in the evaluation of malignant mediastinal lesions. Egypt J Radiol Nucl Med 2020; 51: 1-16.
- Sabri YY, Ewis NM, Zawam HE, Khairy MA. Role of diffusion MRI in diagnosis of mediastinal lymphoma: initial assessment and response to therapy. Egyptian Journal of Radiology and Nuclear Medicine 2021; 52: 1-11.
Abstract
Keywords
Lymphadenopathy; pediatric; magnetic resonance imaging; histogram analysis; apparent diffusion coefficient Lymphadenopathy magnetic resonance imaging histogram analysis apparent diffusion coefficient
Supporting Institution
yok
Project Number
yok
References
- Nield LS, Kamat D. Lymphadenopathy in children: when and how to evaluate. Clin Pediatr (Phila) 2004; 43: 25–33.
- Tower RL, Carmitta BM. Lymphadenopathy. In: Kliegman RM, Stanton BF, St Geme JW, Schor NF (eds). Nelson Textbook of Pediatrics (20th ed). California, 2016: 2413-15.
- Abdel Razek AA, Soliman NY, Elkhamary S, Alsharaway ML, Tawfik A. Role of diffusionweighted MR imaging in cervical lymphadenopathy. Eur Radiol 2006; 16: 1468-77.
- Vandecaveye V, De Keyzer F, Vander Pooten V, et al. Head and neck squamous cell carcinoma: value of diffusion-weighted MR imaging for nodal staging. Radiology 2009; 251: 134-46.
- Wang YJ, Xu XQ, Hu H, et al. Histogram analysis of apparent diffusion coefficient maps for the differentiation between lymphoma and metastatic lymph nodes of squamous cell carcinoma in head and neck region. Acta Radiol 2018; 59: 672-80.
- De Paepe KN, De Keyzer F, Wolter P, et al. Improving lymph node characterization in staging malignant lymphoma using first-order ADC texture analysis from whole-body diffusion-weighted MRI. J Magn Reson Imaging 2018; 48: 897-906.
- Le Bihan D. Molecular diffusion nuclear magnetic resonance imaging. Magn Reson Q 1991; 7: 1-30.
- Koh DM, Collins DJ. Diffusion-weighted MRI in the body: applications and challenges in oncology. AJR Am J Roentgenol 2007; 188: 1622-35.
- Donners R, Blackledge M, Tunariu N, Messiou C, Merkle EM, Koh DM. Quantitative whole-body diffusion- weighted MR imaging. Magn Reson Imaging Clin N Am 2018; 26: 479-94.
- Chang KL, Arber DA, Gaal KK, Weiss LM. Lymph nodes and spleen. In: Silverberg SG, DeLellis RA, Frable WJ, LiVolsi VA, Wick MR, editors. Silverberg’s Principles and practice of surgical pathology and cytopathology. Volume 1. New York: Churchill Livingstone; 2006: 507–607
- Brincker H. Sarcoid reactions in malignant tumours. Cancer Treat Rev 1986; 13: 147-56.
- ElSaid NA, Nada OM, Habib YS, et al. Diagnostic accuracy of diffusion weighted MRI in cervical lymphadenopathy cases correlated with pathology results. Egypt J Radiol Nuclear Med 2014; 45: 1115-25.
- Nomori H, Mori T, Ikeda K, et al. Diffusion-weighted magnetic resonance imaging can be used in place of positron emission tomography for N staging of nonsmall cell lung cancer with fewer false-positive results. J Thorac Cardiovasc Surg 2008; 135: 816-22.
- Abdel Razek AA, Gaballa G, Elashry R, Elkhamary S. Diffusion-weighted MR imaging of mediastinal lymphadenopathy in children. Jpn J Radiol 2015; 33: 449-54.
- Vidiri A, Minosse S, Piludu F, et al. Cervical lymphadenopathy: can the histogram analysis of apparent diffusion coefficient help to differentiate between lymphoma and squamous cell carcinoma in patients with unknown clinical primary tumor? Radiol Med 2019; 124: 19-26.
- Lian S, Zhang C, Chi J, Huang Y, Shi F, Xie C. Differentiation between nasopharyngeal carcinoma and lymphoma at the primary site using whole-tumor histogram analysis of apparent diffusion coefficient maps. Radiol Med 2020; 125: 647-53.
- Song C, Cheng P, Cheng J, Zhang Y, Xie S. Value of apparent diffusion coefficient histogram analysis in the differential diagnosis of nasopharyngeal lymphoma and nasopharyngeal carcinoma based on readout-segmented diffusion-weighted imaging. Front Oncol 2021; 11: 632796.
- Molyneux EM, Rochford R, Griffin B, et al. Burkitt’s lymphoma. Lancet 2012; 379: 1234-44.
- Thomas AG, Vaidhyanath R, Kirke R, Rajesh A. Extranodal lymphoma from head to toe: part 1, the head and spine. AJR Am J Roentgenol 2011; 197: 350–6.
- Gu J, Chan T, Zhang J, Leung AY, Kwong YL, Khong PL. Whole-body diffusion-weighted imaging: the added value to whole-body MRI at initial diagnosis of lymphoma. AJR Am J Roentgenol 2011; 197: W384–91.
- Kwee TC, Ludwig I, Uiterwaal CS, et al. ADC measurements in the evaluation of lymph nodes in patients with non-Hodgkin lymphoma: feasibility study. MAGMA 2011; 24: 1-8.
- Holzapfel K, Duetsch S, Fauser C, Eiber M, Rummeny EJ, Gaa J. Value of diffusion-weighted MR imaging in the differentiation between benign and malignant cervical lymph nodes. Eur J Radiol 2009; 72: 381-7.
- Perrone A, Guerrisi P, Izzo L, et al. Diffusion-weighted MRI in cervical lymph nodes: differentiation between benign and malignant lesions. Eur J Radiol 2011; 77: 281-6.
- De Paepe K, Bevernage C, De Keyzer F, et al. Whole-body diffusion-weighted magnetic resonance imaging at 3 Tesla for early assessment of treatment response in non-Hodgkin lymphoma: a pilot study. Cancer Imaging 2013; 13: 53-62.
- Wu X, Nerisho S, Dastidar P, et al. Comparison of different MRI sequences in lesion detection and early response evaluation of diffuse large B-cell lymphoma--a whole-body MRI and diffusion-weighted imaging study. NMR Biomed 2013; 26: 1186-94.
- Santos FS, Verma N, Marchiori E, et al. MRI-based differentiation between lymphoma and sarcoidosis in mediastinal lymph nodes. J Bras Pneumol 2021; 47: e20200055.
- Sabri YY, Kolta MFF, Khairy MA. MR diffusion imaging in mediastinal masses the differentiation between benign and malignant lesions. Egypt J Radiol Nucl Med 2017; 48: 569–80.
- Sabri YY, Nossair EZB, Assal HH et al. Role of diffusion weighted MR-imaging in the evaluation of malignant mediastinal lesions. Egypt J Radiol Nucl Med 2020; 51: 1-16.
- Sabri YY, Ewis NM, Zawam HE, Khairy MA. Role of diffusion MRI in diagnosis of mediastinal lymphoma: initial assessment and response to therapy. Egyptian Journal of Radiology and Nuclear Medicine 2021; 52: 1-11.
Details
| Primary Language | English |
|---|---|
| Subjects | Health Care Administration |
| Journal Section | Research Articles |
| Authors | |
| Project Number | yok |
| Publication Date | March 27, 2023 |
| Published in Issue | Year 2023 Volume: 5 Issue: 2 |
TR DİZİN ULAKBİM and International Indexes (1b)
Interuniversity Board (UAK) Equivalency: Article published in Ulakbim TR Index journal [10 POINTS], and Article published in other (excuding 1a, b, c) international indexed journal (1d) [5 POINTS]
Note: Our journal is not WOS indexed and therefore is not classified as Q.
You can download Council of Higher Education (CoHG) [Yüksek Öğretim Kurumu (YÖK)] Criteria) decisions about predatory/questionable journals and the author's clarification text and journal charge policy from your browser. https://dergipark.org.tr/tr/journal/3449/file/4924/show
Journal Indexes and Platforms:
TR Dizin ULAKBİM, Google Scholar, Crossref, Worldcat (OCLC), DRJI, EuroPub, OpenAIRE, Turkiye Citation Index, Turk Medline, ROAD, ICI World of Journal's, Index Copernicus, ASOS Index, General Impact Factor, Scilit.The indexes of the journal's are;
|
|
|
|
The platforms of the journal's are;
|
|
|
|
The indexes/platforms of the journal are;
TR Dizin Ulakbim, Crossref (DOI), Google Scholar, EuroPub, Directory of Research Journal İndexing (DRJI), Worldcat (OCLC), OpenAIRE, ASOS Index, ROAD, Turkiye Citation Index, ICI World of Journal's, Index Copernicus, Turk Medline, General Impact Factor, Scilit
EBSCO, DOAJ, OAJI is under evaluation.
Journal articles are evaluated as "Double-Blind Peer Review"