Benign and malignant orbital lymphoproliferative disorders: Differentiating using multiparametric MRI at 3.0T

Section: Discussioncontrasting

confidence: 97%

Section: Discussionmentioning

confidence: 98%

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Lymphoma and inflammation in the orbit: Diagnostic performance with diffusion‐weighted imaging and dynamic contrast‐enhanced MRI

Sun

Song

Wang

et al. 2016

“…Orbital lymphoproliferative disorders (OLPDs) represent a wide spectrum of benign and malignant diseases, including lymphoid hyperplasia, atypical lymphoid hyperplasia, idiopathic inflammatory pseudotumor, orbital IgG4‐related disease and lymphoma . Orbital lymphoma usually exhibits good response to low‐dose radiation therapy, while corticosteroid therapy is usually the first choice for benign OLPDs; therefore, accurate pretreatment differentiation of benign and malignant OLPDs is crucial for the determination of individual treatment strategies …”

mentioning

confidence: 99%

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

Qian

et al. 2017

Self Cite

“…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%

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

Balvay

Cuénod

Marais

et al. 2019

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.