Literature DB >> 33777787

Value of Apparent Diffusion Coefficient Histogram Analysis in the Differential Diagnosis of Nasopharyngeal Lymphoma and Nasopharyngeal Carcinoma Based on Readout-Segmented Diffusion-Weighted Imaging.

Chengru Song1, Peng Cheng2, Jingliang Cheng1, Yong Zhang1, Shanshan Xie1.   

Abstract

BACKGROUND: This study aims to explore the utility of whole-lesion apparent diffusion coefficient (ADC) histogram analysis for differentiating nasopharyngeal lymphoma (NPL) from nasopharyngeal carcinoma (NPC) following readout-segmented echo-planar diffusion-weighted imaging (RESOLVE sequence).
METHODS: Thirty-eight patients with NPL and 62 patients with NPC, who received routine head-and-neck MRI and RESOLVE (b-value: 0 and 1,000 s/mm2) examinations, were retrospectively evaluated as derivation cohort (February 2015 to August 2018); another 23 patients were analyzed as validation cohort (September 2018 to December 2019). The RESOLVE data were obtained from the MAGNETOM Skyra 3T MR system (Siemens Healthcare, Erlangen, Germany). Fifteen parameters derived from the whole-lesion histogram analysis (ADCmean, variance, skewness, kurtosis, ADC1, ADC10, ADC20, ADC30, ADC40, ADC50, ADC60, ADC70, ADC80, ADC90, and ADC99) were calculated for each patient. Then, statistical analyses were performed between the two groups to determine the statistical significance of each histogram parameter. A receiver operating characteristic curve (ROC) analysis was conducted to assess the diagnostic performance of each histogram parameter for distinguishing NPL from NPC and further tested in the validation cohort; calibration of the selected parameter was tested with Hosmer-Lemeshow test.
RESULTS: NPL exhibited significantly lower ADCmean, variance, ADC1, ADC10, ADC20, ADC30, ADC40, ADC50, ADC60, ADC70, ADC80, ADC90 and ADC99, when compared to NPC (all, P < 0.05), while no significant differences were found on skewness and kurtosis. Furthermore, ADC99 revealed the highest diagnostic efficiency, followed by ADC10 and ADC20. Optimal diagnostic performance (AUC = 0.790, sensitivity = 91.9%, and specificity = 63.2%) could be achieved when setting ADC99 = 1,485.0 × 10-6 mm2/s as the threshold value. The predictive performance was maintained in the validation cohort (AUC = 0.817, sensitivity = 94.6%, and specificity = 56.2%).
CONCLUSION: Whole-lesion ADC histograms based on RESOLVE are effective in differentiating NPC from NPL.
Copyright © 2021 Song, Cheng, Cheng, Zhang and Xie.

Entities:  

Keywords:  diffusion magnetic resonance imaging; histogram; lymphoma; magnetic resonance imaging; nasopharyngeal carcinoma

Year:  2021        PMID: 33777787      PMCID: PMC7996088          DOI: 10.3389/fonc.2021.632796

Source DB:  PubMed          Journal:  Front Oncol        ISSN: 2234-943X            Impact factor:   6.244


  32 in total

1.  Readout-segmented echo-planar imaging in the evaluation of sinonasal lesions: A comprehensive comparison of image quality in single-shot echo-planar imaging.

Authors:  Menglong Zhao; Zhuang Liu; Yan Sha; Shenjiang Wang; Xinpei Ye; Yucheng Pan; Shaoyu Wang
Journal:  Magn Reson Imaging       Date:  2015-11-02       Impact factor: 2.546

2.  Differentiation of Cerebellar Hemisphere Tumors: Combining Apparent Diffusion Coefficient Histogram Analysis and Structural MRI Features.

Authors:  Seyedmehdi Payabvash; Tarik Tihan; Soonmee Cha
Journal:  J Neuroimaging       Date:  2018-08-01       Impact factor: 2.486

3.  Whole-Lesion Histogram Analysis of Apparent Diffusion Coefficient for the Assessment of Cervical Cancer.

Authors:  Yue Guan; Hua Shi; Ying Chen; Song Liu; Weifeng Li; Zhuoran Jiang; Huanhuan Wang; Jian He; Zhengyang Zhou; Yun Ge
Journal:  J Comput Assist Tomogr       Date:  2016 Mar-Apr       Impact factor: 1.826

4.  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.

Authors:  Yan-Jun Wang; Xiao-Quan Xu; Hao Hu; Guo-Yi Su; Jie Shen; Hai-Bin Shi; Fei-Yun Wu
Journal:  Acta Radiol       Date:  2017-09-04       Impact factor: 1.990

5.  Locally advanced rectal cancer: post-chemoradiotherapy ADC histogram analysis for predicting a complete response.

Authors:  Seung Hyun Cho; Gab Chul Kim; Yun-Jin Jang; Hunkyu Ryeom; Hye Jung Kim; Kyung-Min Shin; Jun Seok Park; Gyu-Seog Choi; See Hyung Kim
Journal:  Acta Radiol       Date:  2014-09-30       Impact factor: 1.990

6.  Utility of histogram analysis of apparent diffusion coefficient maps obtained using 3.0T MRI for distinguishing uterine carcinosarcoma from endometrial carcinoma.

Authors:  Masahiro Takahashi; Eito Kozawa; Megumi Tanisaka; Kousei Hasegawa; Masanori Yasuda; Fumikazu Sakai
Journal:  J Magn Reson Imaging       Date:  2015-11-25       Impact factor: 4.813

7.  Quantitative dynamic contrast-enhanced and diffusion-weighted MRI for differentiation between nasopharyngeal carcinoma and lymphoma at the primary site.

Authors:  Xiao-ping Yu; Jing Hou; Fei-ping Li; Wang Xiang; Qiang Lu; Yin Hu; Hui Wang
Journal:  Dentomaxillofac Radiol       Date:  2016-02-05       Impact factor: 2.419

8.  Histogram Analysis of Diffusion Weighted Imaging at 3T is Useful for Prediction of Lymphatic Metastatic Spread, Proliferative Activity, and Cellularity in Thyroid Cancer.

Authors:  Stefan Schob; Hans Jonas Meyer; Julia Dieckow; Bhogal Pervinder; Nikolaos Pazaitis; Anne Kathrin Höhn; Nikita Garnov; Diana Horvath-Rizea; Karl-Titus Hoffmann; Alexey Surov
Journal:  Int J Mol Sci       Date:  2017-04-12       Impact factor: 5.923

9.  Diffusion-Weighted Imaging Using a Readout-Segmented, Multishot EPI Sequence at 3 T Distinguishes between Morphologically Differentiated and Undifferentiated Subtypes of Thyroid Carcinoma-A Preliminary Study.

Authors:  Stefan Schob; Peter Voigt; Lionel Bure; Hans-Jonas Meyer; Claudia Wickenhauser; Curd Behrmann; Annekathrin Höhn; Paul Kachel; Henning Dralle; Karl-Titus Hoffmann; Alexey Surov
Journal:  Transl Oncol       Date:  2016-09-20       Impact factor: 4.243

10.  Apparent Diffusion Coefficient for Distinguishing Between Malignant and Benign Lesions in the Head and Neck Region: A Systematic Review and Meta-Analysis.

Authors:  Alexey Surov; Hans Jonas Meyer; Andreas Wienke
Journal:  Front Oncol       Date:  2020-01-08       Impact factor: 6.244

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  1 in total

1.  The value of whole-lesion histogram analysis based on field‑of‑view optimized and constrained undistorted single shot (FOCUS) DWI for predicting axillary lymph node status in early-stage breast cancer.

Authors:  Shu Fang; Jun Zhu; Yafeng Wang; Jie Zhou; Guiqian Wang; Weiwei Xu; Wei Zhang
Journal:  BMC Med Imaging       Date:  2022-09-10       Impact factor: 2.795

  1 in total

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