Dynamic contrast‐enhanced MRI in orbital lymphoproliferative disorders: Effects of region of interest selection methods on time efficiency, measurement reproducibility, and diagnostic ability

Qian, Wei-Liang; Xu, Xiao‐Quan; Hu, Hao; Su, Guo‐Yi; Wu, Jiangfen; Shi, Haibin

doi:10.1002/jmri.25859

Cited by 11 publications

(9 citation statements)

References 21 publications

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“…In agreement with previous studies [1,2,4,18,19], we found that orbital lymphoma has a male predominance and most orbital lymphomas were MALT lymphoma. In agreement with results of other investigators, the age of patients with orbital lymphoma was significantly higher than those with inflammatory mass [1,3,15].…”

Section: Discussionsupporting

confidence: 93%

“…However, Braunagel et al [17] reported that there were no significant differences on the quantitative parameters when different ROI selection methods were used. Qian et al [3] compared the quantitative parameters' diagnostic performance and also no significant differences were found. Similarly in our study, the two methods of selecting ROI showed no significant difference in distinguishing lymphoma from inflammatory mass of orbit.…”

Section: Discussionmentioning

confidence: 97%

“…The quantitative data derived from DCE-MRI are not absolute. They can be affected by MRI scan equipment, MRI acquisition parameters, post-processing software as well as the method of selecting region of interest (ROI) [3,17]. However, Braunagel et al [17] reported that there were no significant differences on the quantitative parameters when different ROI selection methods were used.…”

Section: Discussionmentioning

confidence: 99%

“…They have similar imaging findings: both appear as isointense or hypointense on T 1 -and T 2 -weighted images and both show moderate enhancement after injection of gadolinium-based MR contrast agents [1,2]. Low-dose radiation therapy is the first-line treatment for orbital lymphoma, whereas patients with orbital inflammatory masses undergo corticosteroid therapy [1,2].As treatment of these disease entities are different, it is important to establish accurate diagnosis to guide therapy [2,3].…”

Section: Introductionmentioning

confidence: 99%

“…These quantitative parameters include K trans (the volume transfer constant between the blood plasma and extravascular extracellular space (EES) per unit volume of tissue), K ep (the rate constant between the EES and blood plasma) and V e (the volume of EES per unit volume of tissue) [16]. However, DCE-MRI quantitative parameters can be affected by several factors, including MRI scan equipment, MRI acquisition parameters, post-processing software, and the method of selecting the region of interest (ROI) [3,17]. Previously, Braunagel et al [17] explored the effects of ROI selection methods on the measurement of DCE-MRI derived parameters in patients with renal cell carcinoma.…”

Section: Introductionmentioning

confidence: 99%

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Quantitative analysis of dynamic contrast enhancement MRI between orbital lymphoma and inflammatory mass based on different regions of interest selection

et al. 2020

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Purpose To assess the value of dynamic contrast enhanced MRI (DCE-MRI) quantitative parameters in differentiating orbital lymphoma from inflammatory mass based on different regions of interest selection. Materials and methods The study population consists of 83 patients with histologically proven orbital masses (39 lymphomas and 44 inflammatory masses). Two methods of selecting regions of interest (ROI) were compared to obtain quantitative parameters: (a) a round or ovoid region of 8 mm 2 covering the most enhanced area, and (b) covering the lesion but excluding areas of hemorrhage or necrosis on the slice with the largest tumor area. Parametric maps were obtained for quantitative parameters including K trans , V e and K ep. Quantitative parameters that distinguish orbital lymphoma from orbital inflammatory mass were analyzed by receiver operating characteristic curves (ROC). Results K ep values (ROI selection method a) were significantly higher in orbital lymphoma compared with orbital inflammatory mass (p = 0.003) and V e values (ROI selection method a and b) of orbital lymphoma were significantly lower than orbital inflammatory mass (p = 0.01, p = 0.006, respectively). K ep (ROI selection method a) could distinguish lymphoma from inflammatory mass with sensitivity (97.4%, 38/39), specificity (52.3%, 23/44), positive predictive value (64.4%, 38/59), negative predictive value (95.8%, 23/24) and accuracy (73.5%, 61/83). V e (ROI selection method a) could distinguish lymphoma from inflammatory mass with sensitivity (54.5%, 24/44), specificity (79.5%, 31/39), positive predictive value (75%, 24/32), negative predictive value (60.8%, 31/51) and accuracy (66.3%, 55/83). V e (ROI selection method b) distinguished lymphoma from inflammatory mass with sensitivity (48.7%, 21/44), specificity (86.4%, 34/39), positive predictive value (80.8%, 21/26), negative predictive value (59.6%, 34/57), and accuracy (66.3%, 55/83). The pairwise comparison of the AUCs among these significant quantitative parameters showed no difference in distinguishing orbital lymphoma from orbital inflammatory mass (Z = 1.066, p = 0.286, Z = 0.998, p = 0.318 and Z = 0.370, p = 0.711, respectively). Conclusion Quantitative parameters can differentiate orbital lymphoma from inflammatory mass. ROI selection methods had no definite effect on the diagnostic performance. Keywords Orbit • Lymphoma • Inflammatory mass • ROI • Quantitative parameters Abbreviations DCE-MRI Dynamic contrast enhancement magnetic resonance imaging DWI Diffusion weighted imaging ADC Apparent diffusion coefficient ROI Region of interest ROC Receiver operating characteristic AUC Area under the curve EES Extravascular extracellular space MALT Mucosa-associated lymphoid tissue DLBCL Diffuse large B-cell lymphoma ICC Intraclass correlation coefficient Liyuan Song first author.

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