Literature DB >> 16778627

Evaluating tumors and tumorlike lesions of the nasal cavity, the paranasal sinuses, and the adjacent skull base with diffusion-weighted MRI.

Matthew L White1, Yan Zhang, Robert A Robinson.   

Abstract

PURPOSE: The purpose of this study was to analyze the relationship of apparent diffusion coefficients (ADCs) to the malignant degree and the histopathological features of the lesions in the nasal cavity, the paranasal sinuses, and the adjacent skull base.
METHOD: We evaluated the differences of the ADCs between the malignancies (n=18) and the benign lesions (n=6). The correlations between lesion ADCs and lesion cellularity, stroma, and necrosis were calculated.
RESULTS: The ADCs of the malignancies were significantly lower than the benign lesions (P<0.0125). The ADCs were inversely correlated with tumor cellularity (P<0.01, r=-0.556).
CONCLUSIONS: ADCs provide quantitative information that has limited utility in the differential diagnosis between malignant and benign lesions. The correlation of the histopathology of a lesion with ADCs is quite complex and affected by numerous tumor components besides cellularity including keratin, collagen, myxoid stroma, and necrosis.

Entities:  

Mesh:

Year:  2006        PMID: 16778627     DOI: 10.1097/00004728-200605000-00023

Source DB:  PubMed          Journal:  J Comput Assist Tomogr        ISSN: 0363-8715            Impact factor:   1.826


  23 in total

1.  MR evaluation of sinonasal angiomatous polyp.

Authors:  Y Z Wang; B T Yang; Z C Wang; L Song; J F Xian
Journal:  AJNR Am J Neuroradiol       Date:  2011-12-22       Impact factor: 3.825

Review 2.  [Radiological diagnosis of the paranasal sinuses].

Authors:  M Cohnen
Journal:  Radiologe       Date:  2010-03       Impact factor: 0.635

3.  Intravoxel Incoherent Motion MR Imaging in the Differentiation of Benign and Malignant Sinonasal Lesions: Comparison with Conventional Diffusion-Weighted MR Imaging.

Authors:  Z Xiao; Z Tang; J Qiang; S Wang; W Qian; Y Zhong; R Wang; J Wang; L Wu; W Tang; Z Zhang
Journal:  AJNR Am J Neuroradiol       Date:  2018-01-25       Impact factor: 3.825

4.  Multiparametric MR imaging of sinonasal diseases: time-signal intensity curve- and apparent diffusion coefficient-based differentiation between benign and malignant lesions.

Authors:  M Sasaki; M Sumi; S Eida; Y Ichikawa; T Sumi; T Yamada; T Nakamura
Journal:  AJNR Am J Neuroradiol       Date:  2011-09-15       Impact factor: 3.825

5.  The Added Value of Diffusion Magnetic Resonance Imaging in the Diagnosis and Posttreatment Evaluation of Skull Base Chordomas.

Authors:  Ezgi Guler; Burce Ozgen; Melike Mut; Figen Soylemezoglu; Kader Karli Oguz
Journal:  J Neurol Surg B Skull Base       Date:  2017-01-23

6.  Role of diffusion-weighted MR imaging in assessing malignant versus benign skull-base lesions.

Authors:  A Abdel Razek; A Mossad; M Ghonim
Journal:  Radiol Med       Date:  2010-09-17       Impact factor: 3.469

7.  Functional imaging in head and neck squamous cell carcinoma: correlation of PET/CT and diffusion-weighted imaging at 3 Tesla.

Authors:  Julia Fruehwald-Pallamar; Christian Czerny; Marius E Mayerhoefer; Benjamin S Halpern; Christina Eder-Czembirek; Markus Brunner; Matthias Schuetz; Michael Weber; Laura Fruehwald; Andreas M Herneth
Journal:  Eur J Nucl Med Mol Imaging       Date:  2011-04-05       Impact factor: 9.236

Review 8.  Diffusion-weighted imaging in head and neck cancers.

Authors:  Sanjeev Chawla; Sungheon Kim; Sumei Wang; Harish Poptani
Journal:  Future Oncol       Date:  2009-09       Impact factor: 3.404

9.  Dual-energy CT in differentiating benign sinonasal lesions from malignant ones: comparison with simulated single-energy CT, conventional MRI, and DWI.

Authors:  Peng Wang; Zuohua Tang; Zebin Xiao; Rujian Hong; Rong Wang; Yuzhe Wang; Yang Zhan
Journal:  Eur Radiol       Date:  2021-08-24       Impact factor: 5.315

10.  Machine learning to differentiate small round cell malignant tumors and non-small round cell malignant tumors of the nasal and paranasal sinuses using apparent diffusion coefficient values.

Authors:  Chen Chen; Yuhui Qin; Haotian Chen; Junying Cheng; Bo He; Yixuan Wan; Dongyong Zhu; Fabao Gao; Xiaoyue Zhou
Journal:  Eur Radiol       Date:  2022-01-14       Impact factor: 7.034

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