Literature DB >> 33616764

In vivo assessment of Lauren classification for gastric adenocarcinoma using diffusion MRI with a fractional order calculus model.

M Muge Karaman1,2, Lei Tang3, Ziyu Li4, Yu Sun5, Jia-Zheng Li3, Xiaohong Joe Zhou6,7,8,9.   

Abstract

OBJECTIVES: To evaluate the performance of a fractional order calculus (FROC) diffusion model for imaging-based assessment of Lauren classification in gastric adenocarcinoma.
METHODS: In this study, 43 patients (15 females, 28 males) with gastric adenocarcinoma underwent MRI at 1.5 T. According to pathology-based Lauren classification, 10 patients had diffuse-type, 20 had intestinal-type, and 13 had mixed-type lesions. The diffuse and mixed types were combined as diffuse-and-mixed type to be differentiated from the intestinal type using diffusion MRI. Diffusion-weighted images were acquired by using eleven b-values (0-2000 s/mm2). Three FROC model parameters comprising diffusion coefficient D, intravoxel diffusion heterogeneity β, and a microstructural quantity μ, together with a conventional apparent diffusion coefficient (ADC), were estimated. The mean parameter values in the tumour were computed by using a percentile histogram analysis. Individual or linear combinations of the mean parameters in the tumour were used to differentiate the diffuse-and-mixed type from the intestinal type using descriptive statistics and receiver operating characteristic (ROC) analyses.
RESULTS: Significant differences were observed between diffuse-and-mixed-type and intestinal-type lesions in D (0.99 ± 0.20 μm2/ms vs. 1.11 ± 0.23 μm2/ms; p = 0.036), β (0.37 ± 0.08 vs. 0.43 ± 0.11; p = 0.043), μ (7.92 ± 2.79 μm vs. 9.87 ± 1.52 μm; p = 0.038), and ADC (0.81 ± 0.34 μm2/ms vs. 0.96 ± 0.19 μm2/ms; p = 0.033). Among the individual parameters, μ produced the largest area under the ROC curve (0.739). The combinations of (D, β, μ) and (β and μ) produced the best overall performance with a sensitivity of 0.739, specificity of 0.750, accuracy of 0.744, and area under the curve of 0.793 (95% confidence interval: 0.657-0.929).
CONCLUSION: Diffusion MRI with the FROC model holds promise for non-invasive assessment of Lauren classification for gastric adenocarcinoma. KEY POINTS: • High b-value diffusion MRI with a FROC model that is sensitive to tissue microstructures can differentiate the diffuse-and-mixed type from intestinal type of gastric adenocarcinoma. • The combination of FROC parameters produced the best result for distinguishing the diffuse-and-mixed type from the intestinal type with an area under the receiver operating characteristic curve of 0.793. • The FROC model parameters, individually or conjointly, hold promise for repeated, non-invasive evaluations of gastric adenocarcinoma at various time points throughout disease progression or regression to complement conventional Lauren classification.
© 2021. European Society of Radiology.

Entities:  

Keywords:  Diagnosis; Diffusion magnetic resonance imaging; Histology; Magnetic resonance imaging; Stomach neoplasms

Mesh:

Year:  2021        PMID: 33616764     DOI: 10.1007/s00330-021-07694-3

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  1 in total

1.  Intravoxel water diffusion heterogeneity imaging of human high-grade gliomas.

Authors:  Thomas C Kwee; Craig J Galbán; Christina Tsien; Larry Junck; Pia C Sundgren; Marko K Ivancevic; Timothy D Johnson; Charles R Meyer; Alnawaz Rehemtulla; Brian D Ross; Thomas L Chenevert
Journal:  NMR Biomed       Date:  2010-02       Impact factor: 4.044

  1 in total
  2 in total

1.  Cervical Carcinoma: Evaluation Using Diffusion MRI With a Fractional Order Calculus Model and its Correlation With Histopathologic Findings.

Authors:  Xian Shao; Li An; Hui Liu; Hui Feng; Liyun Zheng; Yongming Dai; Bin Yu; Jin Zhang
Journal:  Front Oncol       Date:  2022-04-05       Impact factor: 5.738

2.  A comparison study of monoexponential and fractional order calculus diffusion models and 18F-FDG PET in differentiating benign and malignant solitary pulmonary lesions and their pathological types.

Authors:  Yu Luo; Han Jiang; Nan Meng; Zhun Huang; Ziqiang Li; Pengyang Feng; Ting Fang; Fangfang Fu; Jianmin Yuan; Zhe Wang; Yang Yang; Meiyun Wang
Journal:  Front Oncol       Date:  2022-07-21       Impact factor: 5.738

  2 in total

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