Dynamic contrast-enhanced MRI of orbital and anterior visual pathway lesions

Jittapiromsak, Nutchawan; Hou, Ping; Ho-Ling, Liu; Sun, Jia; Schiffman, Jade S.; Linda, T.

doi:10.1016/j.mri.2018.04.016

Cited by 12 publications

(12 citation statements)

References 23 publications

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“…They also showed that Ve was lower in malignant lesions without reaching significance, whereas our results and those of Hu et al showed a significant difference. On the contrary, Jittapiromsak et al showed that Ve was higher in malignant lesions. However, direct comparisons between studies should be viewed with caution, given the heterogeneity of their subjects: mixed intraocular and orbital tumors, a subpopulation of orbital lymphoproliferative disorders, and orbital and anterior visual pathway lesions.…”

Section: Discussionmentioning

confidence: 93%

“…There are a small number of studies in the literature regarding both DCE imaging of orbital lesions and comparison of pharmacokinetic models. Only a few DCE MRI studies have previously evaluated orbital lesions, and a majority of them used only model‐free analysis or an arbitrary chosen model to discriminate between benign and malignant lesions . All three studies evaluating a pharmacokinetic model used a two‐compartment ET model with discordant results .…”

Section: Discussionmentioning

confidence: 99%

“…However, direct comparisons between studies should be viewed with caution, given the heterogeneity of their subjects: mixed intraocular and orbital tumors, a subpopulation of orbital lymphoproliferative disorders, and orbital and anterior visual pathway lesions. We included a wide range or orbital lesions excluding intraocular ones …”

Section: Discussionmentioning

confidence: 99%

“…Of note, ET is the most often studied model and is installed on many commercially available posttreatment software packages . Some publications recommend this model, which allows for easier comparisons between study results from different centers.…”

Section: Discussionmentioning

confidence: 99%

“…[10][11][12] Only a few studies have evaluated DCE-MRI in the orbit, showing its usefulness when detecting and diagnosing orbital lesions, either alone or in combination with diffusion-weighted imaging. [12][13][14][15][16][17][18] However, these studies used an arbitrary pharmacokinetic model, without evaluating the most appropriate one for this specific application.…”

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confidence: 99%

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Quality‐based pharmacokinetic model selection on DCE‐MRI for characterizing orbital lesions

Balvay

Cuénod

Marais

et al. 2019

Magnetic Resonance Imaging

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Background Although several studies have evaluated dynamic contrast‐enhanced (DCE) MRI in the orbit, showing its utility when detecting and diagnosing orbital lesions, none have evaluated the pharmacokinetic models. Purpose To provide a quality‐based pharmacokinetic model selection for characterizing orbital lesions using DCE‐MRI at 3.0T. Study Type Prospective. Population From December 2015 to April 2017, 151 patients with an orbital lesion underwent MRI prior to surgery, including a high temporal resolution DCE sequence, divided into one training and one test dataset with 100 and 51 patients, respectively. Field Strength/Sequence 3T/DCE. Assessment Six different pharmacokinetic models were tested. Statistical Tests Univariate and multivariate analyses were performed using Wilcoxon‐2‐sample tests and a logistic regression to compare parameters between malignant and benign tumors for each pharmacokinetic model for the whole cohort. Receiver operating characteristic (ROC) curve analyses were performed on the training dataset to determine area under curve (AUC) and optimal cutoff values for each pharmacokinetic model, then validated on the test dataset to calculate sensitivity, specificity, and accuracy. Results Regardless of the model, tissue blood flow and tissue blood volume values were significantly higher in malignant vs. benign lesions: 103.8–195.1 vs. 65–113.8, P [<10‐4–2.10‐4] and 21.3–36.9 vs. 15.6–33.6, P [<10‐4–0.03] respectively. Extracellular volume fraction and permeability–surface area product or transfer constant appeared to be less relevant: 17.3–27.5 vs. 22.8–28.2, P [0.01–0.7], 1.7–4.9, P [0.2–0.9] and 9.5–38.8 vs. 8.1–22.8, P [<10‐4–0.6], respectively. ROC curves showed no significant differences in AUC between the different models. The two‐compartment exchange (2CX) model ranked first for quality. Data Conclusion DCE MRI pharmacokinetic model‐derived parameters appeared to be useful for discriminating benign from malignant orbital lesions. The 2CX model provided the best quality of modeling and should be recommended. Perfusion‐related DCE parameters appeared to be significantly more relevant to the diagnostic process. Level of Evidence 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1514–1525.

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Section: Discussionmentioning

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

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Quality‐based pharmacokinetic model selection on DCE‐MRI for characterizing orbital lesions

Balvay

Cuénod

Marais

et al. 2019

Magnetic Resonance Imaging

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Imaging of the Orbit: “Current Concepts”

de Win

2023

Surgery in and Around the Orbit

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Orbital imaging with CT or MRI can be essential in the evaluation of many orbital conditions. Because of its superior bony characterization and fast acquisition, CT is imaging method of first choice in urgent situations like trauma, infection, and evaluation of lesions arising from the orbital wall. Through recent years, CT has also gained a prominent role in (pre)operative planning and navigation, especially through the development of postprocessing software. For the evaluation of more complex orbital disease, MRI is the preferred modality. With its superior soft-tissue differentiation, MRI is useful for determining the extent of orbital lesions, like inflammatory disease, vascular malformations, and orbital tumors. By adding functional MRI techniques, like diffusion and perfusion-weighted imaging, and by combining parameters of different imaging techniques in multiparametric imaging, it is possible to further improve characterization of orbital lesions. In this chapter, the optimal approach to orbital imaging is described, combining knowledge of orbital imaging techniques and imaging indications, together with a structured way of reviewing the orbital images, knowledge of radiological features of common, and more uncommon orbital pathology, and integrating this with the clinical features of the patient.

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