Value of MR imaging in the differentiation of benign and malignant orbital tumors in adults

Evaluation of orbital lesions with DCE-MRI: a literature review

PURPOSE

To provide a major review on the applications of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in evaluating orbital lesions. This review also outlines selected scenarios where DCE-MRI may be helpful.

METHODS

A comprehensive retrospective literature review of all English language publications on PubMed, EMBASE, and Google Scholar between 1994 and 2022. This literature review examined the specific applications and clinical scenarios surrounding the utility of DCE-MRI in orbital lesions and various findings that have been presented in the current literature.

RESULTS

DCE-MRI provides information on tissue physiology and permeability, beyond the anatomical features displayed on static imaging. Various measured parameters (qualitative, semi-quantitative, and quantitative) obtained by DCE-MRI have been used to differentiate between benign and malignant lesions, specific orbital lymphoproliferative diseases (OLPD), lacrimal gland lesions, and various rare orbital tumours. DCE-MRI has a limited role as an initial diagnostic imaging modality. However, DCE-MRI may prove to have benefit in predicting and monitoring treatment response in orbital lymphoma as a critical imaging study, but literature specific to orbital malignancies remains limited.

CONCLUSION

The value of DCE-MRI may be in situations of diagnostic uncertainty, where it may be an additional imaging aid following conventional imaging techniques. It may also act as a critical imaging modality for monitoring of orbital tumour treatment response, but the literature remains limited. Standardisation of imaging protocol, measured parameters, and statistical analysis remain limitations of this imaging technique.

Diagnostic Performance of Dynamic Contrast-Enhanced 3T MR Imaging for Characterization of Orbital Lesions: Validation in a Large Prospective Study

BACKGROUND AND PURPOSE

Orbital lesions are rare but serious. Their characterization remains challenging. Diagnosis is based on biopsy or surgery, which implies functional risks. It is necessary to develop noninvasive diagnostic tools. The goal of this study was to evaluate the diagnostic performance of dynamic contrast-enhanced MR imaging at 3T when distinguishing malignant from benign orbital tumors on a large prospective cohort.

MATERIALS AND METHODS

This institutional review board-approved prospective single-center study enrolled participants presenting with an orbital lesion undergoing a 3T MR imaging before surgery from December 2015 to May 2021. Morphologic, diffusion-weighted, and dynamic contrast-enhanced MR images were assessed by 2 readers blinded to all data. Univariable and multivariable analyses were performed. To assess diagnostic performance, we used the following metrics: area under the curve, sensitivity, and specificity. Histologic analysis, obtained through biopsy or surgery, served as the criterion standard for determining the benign or malignant status of the tumor.

RESULTS

One hundred thirty-one subjects (66/131 [50%] women and 65/131 [50%] men; mean age, 52 [SD, 17.1] years; range, 19-88 years) were enrolled. Ninety of 131 (69%) had a benign lesion, and 41/131 (31%) had a malignant lesion. Univariable analysis showed a higher median of transfer constant from blood plasma to the interstitial environment (K trans) and of transfer constant from the interstitial environment to the blood plasma (minute-1) (Kep) and a higher interquartile range of K trans in malignant-versus-benign lesions (1.1 minute-1 versus 0.65 minute-1, P = .03; 2.1 minute-1 versus 1.1 minute-1, P = .01; 0.81 minute-1 versus 0.65 minute-1, P = .009, respectively). The best-performing multivariable model in distinguishing malignant-versus-benign lesions included parameters from dynamic contrast-enhanced imaging, ADC, and morphology and reached an area under the curve of 0.81 (95% CI, 0.67-0.96), a sensitivity of 0.82 (95% CI, 0.55-1), and a specificity of 0.81 (95% CI, 0.65-0.96).

CONCLUSIONS

Dynamic contrast-enhanced MR imaging at 3T appears valuable when characterizing orbital lesions and provides complementary information to morphologic imaging and DWI.

A signature of structural MRI features at 3 Tesla allows an accurate characterization of orbital cavernous venous malformation

OBJECTIVES

To differentiate OCVM from other orbital lesions using structural MRI.

METHODS

This IRB-approved a historical-prospective cohort single-center analysis of a prospective cohort that included consecutive adult patients presenting with an orbital lesion undergoing a 3T MRI before surgery from December 2015 to May 2021. Two readers blinded to all data read all MRIs assessing structural MRI characteristics. A univariate analysis followed by a stepwise multivariate analysis identified structural MRI features showing the highest sensitivity and specificity when diagnosing OCVM.

RESULTS

One hundred ninety-one patients with 30/191 (16%) OCVM and 161/191 (84%) other orbital lesions were included. OCVM were significantly more likely to present with a higher signal intensity than that of the cortex on T2WI: 26/29 (89.7%) versus 28/160 (17.5%), p < 0.001, or with a chemical shift artifact (CSA): 26/29 (89.7%) versus 16/155 (10.3%), p < 0.001, or to present with a single starting point of enhancement, as compared to other orbital lesions: 18/29 (62.1%) versus 4/159 (2.5%), p = 0.001. The step-wise analysis identified 2 signatures increasing performances. Signature 1 combined a higher signal intensity than that of the cortex on T2WI and a CSA. Signature 2 included these two features and the presence of a single starting point of enhancement. Sensitivity, specificity, and accuracy were 0.83, 0.94, and 0.92 for signature 1 and 0.97, 0.93, and 0.93 for signature 2, respectively.

CONCLUSION

Structural MRI yields high sensitivity and specificity when diagnosing OCVM.

KEY POINTS

• Structural MRI shows high sensitivity and specificity when diagnosing orbital cavernous venous malformation. • We identified two signatures combining structural MRI features which might be used easily in routine clinical practice. • The combination of higher signal intensity of the lesion as compared to the cortex on T2WI and of a chemical shift artifact yields a sensitivity and specificity of 0.83 and 0.94 for the diagnosis of orbital cavernous venous malformation, respectively.

End-to-End Deep-Learning-Based Diagnosis of Benign and Malignant Orbital Tumors on Computed Tomography Images

Determining the nature of orbital tumors is challenging for current imaging interpretation methods, which hinders timely treatment. This study aimed to propose an end-to-end deep learning system to automatically diagnose orbital tumors. A multi-center dataset of 602 non-contrast-enhanced computed tomography (CT) images were prepared. After image annotation and preprocessing, the CT images were used to train and test the deep learning (DL) model for the following two stages: orbital tumor segmentation and classification. The performance on the testing set was compared with the assessment of three ophthalmologists. For tumor segmentation, the model achieved a satisfactory performance, with an average dice similarity coefficient of 0.89. The classification model had an accuracy of 86.96%, a sensitivity of 80.00%, and a specificity of 94.12%. The area under the receiver operating characteristics curve (AUC) of the 10-fold cross-validation ranged from 0.8439 to 0.9546. There was no significant difference on diagnostic performance of the DL-based system and three ophthalmologists (p > 0.05). The proposed end-to-end deep learning system could deliver accurate segmentation and diagnosis of orbital tumors based on noninvasive CT images. Its effectiveness and independence from human interaction allow the potential for tumor screening in the orbit and other parts of the body.

Clinical and imaging clues to the diagnosis and follow-up of ptosis and ophthalmoparesis

Ophthalmoparesis and ptosis can be caused by a wide range of rare or more prevalent diseases, several of which can be successfully treated. In this review, we provide clues to aid in the diagnosis of these diseases, based on the clinical symptoms, the involvement pattern and imaging features of extra-ocular muscles (EOM). Dysfunction of EOM including the levator palpebrae can be due to muscle weakness, anatomical restrictions or pathology affecting the innervation. A comprehensive literature review was performed to find clinical and imaging clues for the diagnosis and follow-up of ptosis and ophthalmoparesis. We used five patterns as a framework for differential diagnostic reasoning and for pattern recognition in symptomatology, EOM involvement and imaging results of individual patients. The five patterns were characterized by the presence of combination of ptosis, ophthalmoparesis, diplopia, pain, proptosis, nystagmus, extra-orbital symptoms, symmetry or fluctuations in symptoms. Each pattern was linked to anatomical locations and either hereditary or acquired diseases. Hereditary muscle diseases often lead to ophthalmoparesis without diplopia as a predominant feature, while in acquired eye muscle diseases ophthalmoparesis is often asymmetrical and can be accompanied by proptosis and pain. Fluctuation is a hallmark of an acquired synaptic disease like myasthenia gravis. Nystagmus is indicative of a central nervous system lesion. Second, specific EOM involvement patterns can also provide valuable diagnostic clues. In hereditary muscle diseases like chronic progressive external ophthalmoplegia (CPEO) and oculo-pharyngeal muscular dystrophy (OPMD) the superior rectus is often involved. In neuropathic disease, the pattern of involvement of the EOM can be linked to specific cranial nerves. In myasthenia gravis this pattern is variable within patients over time. Lastly, orbital imaging can aid in the diagnosis. Fat replacement of the EOM is commonly observed in hereditary myopathic diseases, such as CPEO. In contrast, inflammation and volume increases are often observed in acquired muscle diseases such as Graves' orbitopathy. In diseases with ophthalmoparesis and ptosis specific patterns of clinical symptoms, the EOM involvement pattern and orbital imaging provide valuable information for diagnosis and could prove valuable in the follow-up of disease progression and the understanding of disease pathophysiology.

MRI‐Based Radiomics Nomogram for Preoperative Differentiation Between Ocular Adnexal Lymphoma and Idiopathic Orbital Inflammation

BACKGROUND

Ocular adnexal lymphoma (OAL) and idiopathic orbital inflammation (IOI) are malignant and benign lesions for which radiotherapy and corticosteroids are indicated, but similar clinical manifestations make their differentiation difficult.

PURPOSE

To develop and validate an MRI-based radiomics nomogram for individual diagnosis of OAL vs. IOI.

STUDY TYPE

Retrospective.

POPULATION

A total of 103 patients (46.6% female) with mean age of 56.4 ± 16.3 years having OAL (n = 58) or IOI (n = 45) were divided into an independent training (n = 82) and a testing dataset (n = 21).

FIELD STRENGTH/SEQUENCE

A 3-T, precontrast T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and postcontrast T1WI (T1 + C).

ASSESSMENT

Radiomics features were extracted and selected from segmented tumors and peritumoral regions in MRI before-and-after filtering. These features, alone or combined with clinical characteristics, were used to construct a radiomics or joint signature to differentiate OAL from IOI, respectively. A joint nomogram was built to show the impact of the radiomics signature and clinical characteristics on individual risk of developing OAL.

STATISTICAL TESTS

Area under the curve (AUC) and accuracy (ACC) were used for performance evaluation. Mann-Whitney U and Chi-square tests were used to analyze continuous and categorical variables. Decision curve analysis, kappa statistics, DeLong and Hosmer-Lemeshow tests were also conducted. P < 0.05 was considered statistically significant.

RESULTS

The joint signature achieved an AUC of 0.833 (95% confidence interval [CI]: 0.806-0.870), slightly better than the radiomics signature with an AUC of 0.806 (95% CI: 0.767-0.838) (P = 0.778). The joint and radiomics signatures were comparable to experienced radiologists referencing to clinical characteristics (ACC = 0.810 vs. 0.796-0.806, P > 0.05) or not (AUC = 0.806 vs. 0.753-0.791, P > 0.05), respectively. The joint nomogram gained more net benefits than the radiomics nomogram, despite both showing good calibration and discriminatory efficiency (P > 0.05).

DATA CONCLUSION

The developed radiomics-based analysis might help to improve the diagnostic performance and reveal the association between radiomics features and individual risk of developing OAL.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: 3.

Differentiation of lacrimal gland tumors using the multi-model MRI: classification and regression tree (CART)-based analysis

BACKGROUND

Little is known about the value of dynamic contrast-enhanced (DCE) in combination with diffusion-weighted imaging (DWI) for the differentiation of lacrimal gland tumors.

PURPOSE

To evaluate the ability of DCE and DWI in differentiating lacrimal gland tumors.

MATERIAL AND METHODS

DCE and DWI were performed in 72 patients with lacrimal gland tumors. Time-intensity curve (TIC) patterns were categorized as type A, type B, type C, and type D. Apparent diffusion coefficient (ADC) was measured on DWI. Then, the diagnostic effectiveness of TIC in conjunction with ADC was assessed using classification and regression tree (CART) analysis.

RESULTS

Type A tumors were all epithelial; they could be further separated into pleomorphic adenoma sand carcinomas. Type B tumors were all non-epithelial tumors, which could be further separated into benign inflammatory infiltrates (BIIs) and lymphomas. Type C tumors contained both carcinomas and non-epithelial tumors, which could be diagnosed into carcinomas, BIIs and lymphomas. Type D tumors were all PAs. The mean ADC of epithelial tumors was significantly higher than that of non-epithelial tumors, and the mean ADC values were significantly different between PAs and carcinomas. Besides, the mean ADC value of BIIs was higher than that of lymphomas. Therefore, the CART decision tree made by ADC and TIC had a predictive accuracy of 86.1%, differentiating lacrimal gland tumors effectively.

CONCLUSION

Combined DCE and DWI-MRI can efficiently differentiate lacrimal gland tumors which can be of help to ophthalmologists in the diagnosis and treatment of these tumors.

A deep learning model combining multimodal radiomics, clinical and imaging features for differentiating ocular adnexal lymphoma from idiopathic orbital inflammation

OBJECTIVES

To evaluate the value of deep learning (DL) combining multimodal radiomics and clinical and imaging features for differentiating ocular adnexal lymphoma (OAL) from idiopathic orbital inflammation (IOI).

METHODS

Eighty-nine patients with histopathologically confirmed OAL (n = 39) and IOI (n = 50) were divided into training and validation groups. Convolutional neural networks and multimodal fusion layers were used to extract multimodal radiomics features from the T1-weighted image (T1WI), T2-weighted image, and contrast-enhanced T1WI. These multimodal radiomics features were then combined with clinical and imaging features and used together to differentiate between OAL and IOI. The area under the curve (AUC) was used to evaluate DL models with different features under five-fold cross-validation. The Student t-test, chi-squared, or Fisher exact test was used for comparison of different groups.

RESULTS

In the validation group, the diagnostic AUC of the DL model using combined features was 0.953 (95% CI, 0.895-1.000), higher than that of the DL model using multimodal radiomics features (0.843, 95% CI, 0.786-0.898, p < 0.01) or clinical and imaging features only (0.882, 95% CI, 0.782-0.982, p = 0.13). The DL model built on multimodal radiomics features outperformed those built on most bimodalities and unimodalities (p < 0.05). In addition, the DL-based analysis with the orbital cone area (covering both the orbital mass and surrounding tissues) was superior to that with the region of interest (ROI) covering only the mass area, although the difference was not significant (p = 0.33).

CONCLUSIONS

DL-based analysis that combines multimodal radiomics features with clinical and imaging features may help to differentiate between OAL and IOI.

KEY POINTS

• It is difficult to differentiate OAL from IOI due to the overlap in clinical and imaging manifestations. • Radiomics has shown potential for noninvasive diagnosis of different orbital lymphoproliferative disorders. • DL-based analysis combining radiomics and imaging and clinical features may help the differentiation between OAL and IOI.

MRI-Based Radiomics for Differentiating Orbital Cavernous Hemangioma and Orbital Schwannoma

Aim: The purpose of this work was to develop and evaluate magnetic resonance imaging (MRI)-based radiomics for differentiation of orbital cavernous hemangioma (OCH) and orbital schwannoma (OSC).

Methods: Fifty-eight patients (40 OCH and 18 OSC, confirmed pathohistologically) screened out from 216 consecutive patients who presented between 2015 and 2020 were divided into a training group (28 OCH and 12 OSC) and a validation group (12 OCH and 6 OSC). Radiomics features were extracted from T1-weighted imaging (T1WI) and T2-weighted imaging (T2WI). T-tests, the least absolute shrinkage and selection operator (LASSO), and principal components analysis (PCA) were used to select features for use in the classification models. A logistic regression (LR) model, support vector machine (SVM) model, decision tree (DT) model, and random forest (RF) model were constructed to differentiate OCH from OSC. The models were evaluated according to their accuracy and the area under the receiver operator characteristic (ROC) curve (AUC).

Results: Six features from T1WI, five features from T2WI, and eight features from combined T1WI and T2WI were finally selected for building the classification models. The models using T2WI features showed superior performance on the validation data than those using T1WI features, especially the LR model and SVM model, which showed accuracy of 93% (85–100%) and 92%, respectively, The SVM model showed high accuracy of 93% (91–96%) on the combined feature group with an AUC of 98% (97–99%). The DT and RF models did not perform as well as the SVM model.

Conclusion: Radiomics analysis using an SVM model achieved an accuracy of 93% for distinguishing OCH and OSC, which may be helpful for clinical diagnosis.

[Differential diagnosis of intraorbital masses - a narrative review]

OBJECTIVE

Intraorbital masses represent a condition that is frequently threatening for the visual system. A rigorous differential diagnosis is essential to promptly initiate appropriate therapy and optimize prognosis.

MATERIALS/METHODS

Narrative review of current literature and expert recommendations. For further illustration we describe the case of a 71-year-old male admitted to our department three months after sinus surgery. Postoperative intraorbital hematoma of the right orbit had been treated conservatively with antibiotics/corticosteroids, leading to a near-complete unilateral visual loss. The immediate surgical intervention aimed at decompression of the orbit and the optical nerve. Due to the delay, the intervention could not prevent formation of a lipogranuloma. Inflammatory phases associated with the lipogranuloma are successfully managed by conservative treatment based on multidisciplinary recommendations.

RESULTS

In the case reported, delay of surgical therapy acted as a cause of intraorbital lipogranuloma formation. Literature supports our recommendation of immediate surgical intervention in case of acute retrobulbar hematoma. Besides acute conditions, intraorbital masses can be a sign of systemic disease. In every case, a multidisciplinary therapeutic approach is required for adequate management.

CONCLUSIONS

Intraorbital masses can occur as a complication of trauma or e.g. sinus surgery. On the other hand they can be a sign of systemic disease. Timely diagnosis and treatment prevents from visual loss. That is why rigorous differential diagnosis is essential for every discipline managing intraorbital lesions.

Imaging of head and neck mucosa-associated lymphoid tissue lymphoma (MALToma)

Marginal zone B-cell lymphoma of mucosa-associated lymphoid tissue (MALToma) arises in extranodal sites in the head and neck. Chronic inflammatory, infectious or autoimmune conditions are implicated in its pathogenesis. Within the head and neck, MALToma is often multifocal and indolent and the imaging appearances may be mistaken for non-malignant disease in the head and neck. The aim of this article is to illustrate the varied radiological and clinical features of MALToma in the head and neck, an awareness of which is needed for timely and correct diagnosis to guide subsequent disease management.

Quantitative characterization of extraocular orbital lesions in children using diffusion-weighted imaging

BACKGROUND

Diffusion-weighted imaging (DWI) has been shown to be helpful in providing information about cellular density and also predicting the histological features of aggressive tumors. Several studies have evaluated this technique for orbital tumors. However, very few articles have focused exclusively on evaluating pediatric orbital masses and, within those, only a small number of patients were included in the study.

OBJECTIVE

This study aimed to evaluate the use of DWI and apparent diffusion coefficient (ADC) values to differentiate between benign and malignant extraocular orbital lesions in children.

MATERIALS AND METHODS

This retrospective study included 73 patients under the age of 18 seen in our hospital between October 2016 and February 2019. The extraocular orbital lesions were evaluated clinically and radiologically using DWI. The diagnosis was confirmed by either histological examination (after biopsy or surgery) or based on clinical and radiologic evaluation.

RESULTS

The malignant lesions were found to have increased diffusion restriction in comparison to the benign lesions. The ADC values of the malignant lesions were significantly lower (P<0.0001). The use of a cutoff value of 0.99×10^-3 mm²/s allowed for the differentiation of the benign lesions and malignant lesions with a sensitivity of 75% and a specificity of 100% while the cutoff point of 1.26×10^-3 mm²/s had a sensitivity of 100% and a specificity of 73%.

CONCLUSION

Measurement of ADC in extraocular orbital lesions in children may help differentiate malignant lesions from benign lesions.

Bag-of-features-based radiomics for differentiation of ocular adnexal lymphoma and idiopathic orbital inflammation from contrast-enhanced MRI

OBJECTIVES

To evaluate the effectiveness of bag-of-features (BOF)-based radiomics for differentiating ocular adnexal lymphoma (OAL) and idiopathic orbital inflammation (IOI) from contrast-enhanced MRI (CE-MRI).

METHODS

Fifty-six patients with pathologically confirmed IOI (28 patients) and OAL (28 patients) were randomly divided into training (n = 42) and testing (n = 14) groups. One hundred sixty texture features extracted from the CE-MR image were encoded into the BOF representation with fewer features. The support vector machine (SVM) with a linear kernel was used as the classifier. Data augmented was performed by cropping orbital lesions in different directions to alleviate the over-fitting problem. Student's t test and the Holm-Bonferroni method were employed to compare the performance of different analysis methods. The chi-square test was used to compare the analysis with MRI and human radiological diagnosis.

RESULTS

In the independent testing group, the differentiation by the BOF features with augmentation achieved an area under the curve (AUC) of 0.803 (95% CI: 0.725-0.880), which was significantly higher than that of the BOF features without augmentation and that of the texture features (p < 0.05). In addition, the same radiomic analysis with pre-contrast MRI obtained an AUC of 0.618 (95% CI: 0.560-0.677), which was significantly lower than that with CE-MRI. The diagnostic performance of the analysis with CE-MRI was significantly better than the radiology resident (p < 0.05) but had no significant difference with the experienced radiologist, even though there was less consistency between the radiomic analysis and the human visual diagnosis.

CONCLUSIONS

The BOF-based radiomics may be helpful for the differentiation between OAL and IOI.

KEY POINTS

• It is challenging to differentiate OAL from IOI due to the similar clinical and image features. • Radiomics has great potential for the noninvasive diagnosis of orbital diseases. • The BOF representation from patch to image may help the differentiation of OAL and IOI.

Intravoxel incoherent motion (IVIM) 3 T MRI for orbital lesion characterization

OBJECTIVES

To determine the diagnostic accuracy of MRI intravoxel incoherent motion (IVIM) when characterizing orbital lesions, which is challenging due to a wide range of locations and histologic types.

METHODS

This IRB-approved prospective single-center study enrolled participants presenting with an orbital lesion undergoing a 3-T MRI prior to surgery from December 2015 to July 2019. An IVIM sequence with 15 b values ranging from 0 to 2000 s/mm² was performed. Two neuroradiologists, blinded to clinical data, individually analyzed morphological MRIs. They drew one region of interest inside each orbital lesion, providing apparent diffusion coefficient (ADC), true diffusion coefficient (D), perfusion fraction (f), and pseudodiffusion coefficient (D*) values. T test, Mann-Whitney U test, and receiver operating characteristic curve analyses were performed to discriminate between orbital lesions and to determine the diagnostic accuracy of the IVIM parameters.

RESULTS

One hundred fifty-six participants (84 women and 72 men, mean age 54.4 ± 17.5 years) with 167 orbital lesions (98/167 [59%] benign lesions including 54 orbital inflammations and 69/167 [41%] malignant lesions including 32 lymphomas) were included in the study. ADC and D were significantly lower in malignant than in benign lesions: 0.8 × 10^-3 mm²/s [0.45] versus 1.04 × 10^-3 mm²/s [0.33], p < 0.001, and 0.75 × 10^-3 mm²/s [0.40] versus 0.98 × 10^-3 mm²/s [0.42], p < 0.001, respectively. D* was significantly higher in malignant lesions than in benign ones: 12.8 × 10^-3 mm²/s [20.17] versus 7.52 × 10^-3 mm²/s [7.57], p = 0.005. Area under curve was of 0.73, 0.74, 0.72, and 0.81 for ADC, D, D*, and a combination of D, f, and D*, respectively.

CONCLUSIONS

Our study showed that IVIM might help better characterize orbital lesions.

KEY POINTS

• Intravoxel incoherent motion (IVIM) helps clinicians to assess patients with orbital lesions. • Intravoxel incoherent motion (IVIM) helps clinicians to characterize orbital lymphoma versus orbital inflammation. • Management of patients becomes more appropriate.

Value of quantitative multiparametric MRI in differentiating pleomorphic adenomas from malignant epithelial tumors in lacrimal gland

PURPOSE

To evaluate the diagnostic performance of the quantitative parameters derived from diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) MRI in differentiating lacrimal gland pleomorphic adenomas (LGPAs) from lacrimal gland malignant epithelial tumors (LGMETs).

METHODS

Seventy-seven cases with LG epithelial tumors confirmed by histopathology (47 LGPAs and 30 LGMETs) underwent DWI and DCE-MRI. The quantitative parameters including the apparent diffusion coefficient (ADC), the volume transfer constant (K^trans), the efflux rate constant from the extravascular extracellular space (EES) to blood plasma (K_ep), and the extravascular extracellular volume fraction (V_e) were used to differentiate LGPAs from LGMETs. Independent-samples t test was conducted to compare these parameters. The diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis.

RESULTS

Compared with LGPAs, LGMETs had significantly lower ADC value (1.090 ± 0.169mm²/s) (P < 0.001), higher K^trans value (0.892 ± 0.517/min) (P = 0.001), and K_ep value (1.300 ± 1.131/min) (P = 0.002). ADC as a diagnostic index showed a better diagnostic efficacy in predicting malignant tumors (AUC 0.914, sensitivity 90.0%, specificity 85.1%, and accuracy 87.0%) than K^trans and K_ep alone. The combination of ADC and K^trans presented the optimal diagnostic performance for the differentiation (AUC 0.938, sensitivity 93.3%, specificity 87.2%, accuracy 89.6%).

CONCLUSION

The quantitative parameters including ADC, K^trans, and K_ep derived from DWI and DCE-MRI might be potential imaging biomarkers in differentiating LGPAs from LGMETs. The combination of ADC and K^trans is superior to other quantitative parameters in distinguishing LGPAs from LGMETs.

T2 mapping in orbital masses: preliminary study on differential diagnostic ability of T2 relaxation time

Background

T2 mapping has been proven to be useful in tumor characterization. As to orbital masses, its diagnostic value needs to be investigated.

Purpose

To evaluate the usefulness of T2 mapping in orbital masses and the ability of T2 relaxation time in differentiating malignant from benign orbital masses.

Material and Methods

Forty-seven patients with solid orbital masses (33 benign and 14 malignant) who underwent T2 mapping examination for preoperative assessment were enrolled in the current study. T2 mapping was acquired using 16 TE values (range 12–192 ms; delta TE 12 ms). Mean T2 relaxation time was calculated based on the whole mass region of interest and compared between the malignant and benign groups using the unpaired t-test. Receiver operating characteristic curve analysis was adopted to calculate its diagnostic value.

Results

Malignant orbital masses showed significantly lower T2 relaxation time than benign masses (76.4 ± 13.0 ms vs. 119.1 ± 20.4 ms; P < 0.001). If setting a T2 relaxation time of 89.5 ms as the threshold value, optimal differentiating performance could be achieved (area under the curve 0.936; sensitivity 100.0%; specificity 87.9%; accuracy 91.5%; positive predictive value 77.8%; negative predictive value 100%).

Conclusion

T2 mapping and its derived T2 relaxation time could provide quantitative information and serve as a supplementary imaging marker for differentiating malignant from benign orbital masses.

Multi-parametric magnetic resonance imaging characterization of orbital lesions: a triple blind study

Background: Multi-parametric MRI used for preoperative assessment of orbital lesions does not routinely include DCE-MRI, since its accuracy in differential diagnosis of orbital mass is still under debate. Aim of this study is to characterize orbital lesions by multi-parametric MRI, analysing the incremental predictive value of DCE-MRI in differential diagnosis of orbital lesions.Methods: In this prospective triple-blind study, 43 consecutive patients with unilateral orbital lesion underwent conventional multimodal MRI and DCE-MRI before biopsy in a tertiary referral centre. Pre-operative MRI examination including conventional unenhanced MRI protocol, DWI with ADC maps, static CE 3D-T1 w and dynamic CE T1 w sequences, was performed within 1 week from surgery (anterior/lateral orbitotomy depending on location of the lesion, to carry out incisional/excisional biopsy).Results: Comparison between conventional T1 w/T2 w, DWI, CE 3D-T1 w and DCE-MRI groups showed a statistically significant difference in scores distribution (p < .001). Statistically significant difference was found between conventional T1 w/T2 w and DWI (p < .005), as well as between DWI and CE 3D-T1 w (p < .001). Conversely, no significant difference was found between CE 3D-T1 w and DCE (p < .005).Conclusions and Relevance: This study confirmed the positive effect of DWI and CE 3D-T1 w on orbital lesions diagnosis when added to conventional T1 w/T2 w sequences, whereas no substantial impact on diagnostic performance was observed with the further addition of DCE-MRI. DCE does not strongly influence diagnostic performance and inter-rater agreement in characterizing orbital lesions; therefore, it should be recommended in selected patients whose assessment of flow dynamics is particularly useful for management.Abbreviations: US = ultrasonography; MRI = magnetic resonance imaging; CT = computed tomography; STIR = Short-TI Inversion Recovery; DWI = diffusion weighted imaging; DCE-MRI = dynamic contrast-enhanced MRI; SE = Spin-Echo; TSE = Turbo Spin-Echo; THRIVE = T1-weighted high resolution Isotropic Volume Examination (dynamic contrast-enhanced ultrafast spoiled gradient echo); ROI = regions of interest; IRR = inter-rater reliability; TIC = time-intensity curve.

Differentiation between orbital malignant and benign tumors using intravoxel incoherent motion diffusion-weighted imaging: Correlation with dynamic contrast-enhanced magnetic resonance imaging

To evaluate the performance of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) for differentiating orbital malignant from benign tumors, and to assess the correlation between IVIM-DWI parameters and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters.Twenty-seven patients (17 benign and 10 malignant) with orbital tumors underwent 3.0T MRI examination for pre-treatment evaluation, including IVIM-DWI and DCE-MRI. IVIM-DWI parameters (tissue diffusivity, D; pseudo-diffusion coefficient, D; and perfusion fraction, f) were quantified using bi-exponential fitting model. DCE-MRI parameters (K, the volume transfer constant between the plasma and the extracellular extravascular space [EES]; Ve, the volume fraction of the EES, and Kep, the rate constant from EES to blood plasma) were quantified using modified Tofts model. Independent-sample t test, receiver operating characteristic curve analyses and Spearman correlation test were used for statistical analyses.Malignant orbital tumors showed lower D (P <.001) and higher D (P = .002) than benign tumors. Setting a D value of 0.966 × 10 mm/s as the cut-off value, a diagnostic performance (AUC, 0.888; sensitivity, 100%; specificity, 82.35%) could be obtained for diagnosing malignant tumors. While setting a D value of 42.371 × 10 mm/s as cut-off value, a diagnostic performance could be achieved (AUC, 0.847; sensitivity, 90.00%; specificity, 70.59%). Poor or moderated correlations were found between IVIM-DWI and DCE-MRI parameters (D and Kep, r = 0.427, P = .027; D and Ve, r = 0.626, P <.001).IVIM-DWI is potentially useful for differentiating orbital malignant from benign tumors. Poor or moderate correlations exist between IVIM-DWI and DCE-MRI parameters. IVIM-DWI may be a useful adjunctive perfusion technique for the differential diagnosis of orbital tumors.

[Orbital hemangiomas: capabilities of modern neuroradiological diagnostics]

MATERIAL AND METHODS

In the period from 2010 to 2016. 14 patients with cavernous hemangioma (CH) and 2 patients with capillary hemangioma (CapH) of the orbit were examined. The age of CH patients varied from 17 to 67 years (median, 53 years); 8 females and 6 males. The age of CapH patients was 35 and 54 years. All patients underwent surgery with subsequent histological verification. CT-perfusion was performed in 10 CH patients and 2 CapH patients according to a developed low-dose protocol (80 kV, 200 mAs, t_scan=40 s) with allowance for a target localizer (80 kV, 120 mAs) and at a maximum radiation dose of not more than 4.0 mZv. Neoplasm microcirculation was quantitatively assessed by calculating hemodynamic parameters: blood flow velocity (BFV), blood volume (BV), and mean transit time (MTT). MRI without and with contrast enhancement was performed in 11 CH patients and 2 CapH patients according to the ophthalmologic protocol (Signa GE, 3.0 T) accepted at the Institute: without contrast enhancement - T1, T2, and T2-FLAIR modes, T1 and T2 with a Fat Sat technique at a scan thickness of 3 mm, and DWI MRI; contrast enhancement - T1 (three projections) mode, including the Fat Sat technique. SWAN (n=2) and non-contrast MR perfusion ASL (n=3) were also used. Diffusion-weighted images (DWI) were processed with calculation of the apparent diffusion coefficient (ACD).

RESULTS

In all CH patients, CT-perfusion revealed low perfusion parameters of blood flow: BV_CH=0.86±0.37 mL/100 g, BFV_CH= 4.89±2.01 mL/100 g/min with a high mean transit time MTT_CH=10.13±3.05 s compared to the same parameters of blood flow in the normal white matter: CBV_NormWM=1.63±2.22 mL/100 g, CBFV_NormWM=9.72±3.13 mL/100 g/min, and MTT_NormWM=6.76±2.78 s. In CapH cases, significantly increased blood flow velocity and volume values and a low MTT value in the tumor were observed: BV_CapH=10.30±4.10 mL/100 g, BFV_CapH=119.72±53.13 mL/100 g/min, and MTT_CapH=4.35±1.79 s. In the case of orbital hemangiomas, optimal MRI modes were T1 and T2 with the Fat Sat technique, a scan thickness of 3 mm, and intravenous contrast enhancement. The revealed pattern of contrast agent accumulation by CH, initially in the central part and then in the periphery, may be a useful radiographic sign in the differential diagnosis with other orbital tumors.

CONCLUSION

Modern CT- and MRI-based diagnostics of orbital hemangiomas provides not only the exact location, size, and spread of the lesion but also reveals the characteristic structural features of these tumors, and the use of perfusion techniques visualizes hemodynamics of the tumors. CT-perfusion-based hemodynamic parameters of cavernous hemangiomas typical of this type of hemangiomas may be used in the differential diagnosis with other tumors of this location. The use of contrast enhancement and the Fat Sat technique with a scan thickness of not more than 3 mm is optimal for MRI diagnostics of orbital hemangiomas.

Histogram analysis of dynamic contrast-enhanced magnetic resonance imaging for differentiating malignant from benign orbital lymphproliferative disorders

BACKGROUND

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has been used for assessing orbital lymphoproliferative disorders (OLPDs). However, only the mean values of quantitative parameters were obtained in previous studies and tumor heterogeneity was ignored.

PURPOSE

To assess the value of DCE-MRI derived histogram parameters in differentiating malignant from benign OLPDs.

MATERIAL AND METHODS

Forty-eight OLPDs patients (25 malignant and 23 benign) who had undergone DCE-MRI for pre-treatment evaluation were retrospectively included. Histogram parameters of K^trans, k_ep, and v_e were calculated and compared between two groups using the independent sample's t-test. Receiver operating characteristic (ROC) curve analyses were used to determine the diagnostic value of each significant parameter. Multivariate stepwise logistic regression analysis was used to identify the independent predictors of malignant OLPDs.

RESULTS

Tenth k_ep, mean k_ep, median k_ep, and 90th k_ep were significantly higher in the malignant OLPD group than in the benign OLPD group. Tenth v_e was significantly lower in the malignant OLPD group than in the benign OLPD group. Ninetieth k_ep was the only independent predictor of malignant OLPDs ( P = 0.019), with an area under ROC curve of 0.828, a sensitivity of 92.00%, and a specificity of 78.26% at a cut-off value of 1.057 min^-1.

CONCLUSION

Histogram analysis of DCE-MRI derived parameters may help to differentiate malignant from benign OLPDs. The 90th k_ep hold the potential as an independent predictor for malignant OLPDs.

MR-based radiomics signature in differentiating ocular adnexal lymphoma from idiopathic orbital inflammation

OBJECTIVES

To assess the value of the MR-based radiomics signature in differentiating ocular adnexal lymphoma (OAL) and idiopathic orbital inflammation (IOI).

METHODS

One hundred fifty-seven patients with pathology-proven OAL (84 patients) and IOI (73 patients) were divided into primary and validation cohorts. Eight hundred six radiomics features were extracted from morphological MR images. The least absolute shrinkage and selection operator (LASSO) procedure and linear combination were used to select features and build radiomics signature for discriminating OAL from IOI. Discriminating performance was assessed by the area under the receiver-operating characteristic curve (AUC). The predictive results were compared with the assessment of radiologists by chi-square test.

RESULTS

Five radiomics features were included in the radiomics signature, which differentiated OAL from IOI with an AUC of 0.74 and 0.73 in the primary and validation cohorts respectively. There was a significant difference between the classification results of the radiomics signature and those of a radiology resident (p < 0.05), although there was no significant difference between the results of the radiomics signature and those of a more experienced radiologist (p > 0.05).

CONCLUSIONS

Radiomics features have the potential to differentiate OAL from IOI.

KEY POINTS

• Clinical and imaging findings of OAL and IOI often overlap, which makes diagnosis difficult. • Radiomics features can potentially differentiate OAL from IOI non invasively. • The radiomics signature discriminates OAL from IOI at the same level as an experienced radiologist.

How accurate is the clinical and radiological evaluation of orbital lesions in comparison to surgical orbital biopsy?

AIMS

The purpose of the present study is to determine the overall and disease-related accuracy of clinical and radiological diagnosis when compared to the histology result of the surgical orbital biopsy.

METHODS

A retrospective case notes analysis of patients who underwent surgical orbital biopsy during a 12-year period involving more than 100 orbital lesions. The accuracy of clinical and radiological diagnosis was compared with histological diagnosis.

RESULTS

A total of 112 orbital biopsies were carried out in 104 eyes of 101 patients between 2003 and 2015. Correct diagnosis was reached in <50% of cases by both ophthalmologists and radiologists alike. Vascular lesions exhibit characteristic clinical and imaging features that allow for accurate diagnosis and can often be managed conservatively. The greatest challenge, both clinically and on imaging was in differentiating between inflammatory and haematological orbital lesions which represented half of our cases. There was no operative mortality and there were no post-operative complications recorded.

CONCLUSION

Surgical orbital biopsy is a safe and accurate diagnostic tool for orbital lesions of unknown aetiology and, in our opinion, remains the gold standard.

Combined diffusion-weighted imaging and dynamic contrast-enhanced MRI for differentiating radiologically indeterminate malignant from benign orbital masses

AIM

To evaluate the performance of the combination of diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for differentiating radiologically indeterminate malignant from benign orbital masses.

MATERIALS AND METHODS

Sixty-five patients with orbital masses (36 benign and 29 malignant) underwent DW and DCE MRI examinations for pre-treatment evaluation. The apparent diffusion coefficient (ADC) was derived from DW imaging data using the mono-exponential model. The volume transfer constant (K^trans), the flux rate constant between the extravascular extracellular space and the plasma (K_ep), and the extravascular extracellular volume fraction (V_e) were calculated using modified Tofts model. Differences in quantitative metrics were tested using independent-samples t test. Receiver operating characteristic (ROC) curve analyses were used to determine and compare the diagnostic ability of each significant metric.

RESULTS

The malignant group demonstrated significantly lower ADC (0.711±0.260 versus 1.187±0.389, p<0.001) and higher K_ep values (1.265±0.637 versus 0.871±0.610, p=0.008) than the benign group. Optimal diagnostic performance (area under the ROC curve [AUC], 0.941; sensitivity, 0.966; specificity, 0.917) could be achieved using combined ADC and K_ep values as the diagnostic index. The diagnostic performance of the combination of ADC and K_ep was significantly better than K_ep alone (p=0.006). Compared with ADC alone, combined ADC and K_ep values also showed higher AUC (0.941 versus 0.898), although the difference did not reach statistical significance (p=0.220).

CONCLUSION

K_ep and ADC could help to differentiate radiologically indeterminate malignant from benign orbital masses. The combination of DW and DCE MRI might improve the differentiating performance.

T1-weighted dynamic contrast-enhanced brain magnetic resonance imaging: A preliminary study with low infusion rate in pediatric patients

Background The aim of this preliminary study is to evaluate the results of T1-weighted dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in pediatric patients at 1.5T, with a low peripheral intravenous gadoteric acid injection rate of 1 ml/s. Materials and methods Children with neurological symptoms were examined prospectively with conventional MRI and T1-weighted DCE MRI. An magnetic resonance perfusion analysis method was used to obtain time-concentration curves (persistent pattern, type-I; plateau pattern, type-II; washout pattern, type-III) and to calculate pharmacokinetic parameters. A total of two radiologists manually defined regions of interest (ROIs) in the part of the lesion exhibiting the greatest contrast enhancement and in the surrounding normal or contralateral tissue. Lesion/surrounding tissue or contralateral tissue pharmacokinetic parameter ratios were calculated. Tumors were categorized by grade (I-IV) using the World Health Organization (WHO) Grade. Mann-Whitney testing and receiver-operating characteristic (ROC) curves were performed. Results A total of nine boys and nine girls (mean age 10.5 years) were included. Lesions consisted of 10 brain tumors, 3 inflammatory lesions, 3 arteriovenous malformations and 2 strokes. We obtained analyzable concentration-time curves for all patients (6 type-I, 9 type-II, 3 type-III). K^trans between tumor tissue and surrounding or contralateral tissue was significantly different ( p = 0.034). K^trans ratios were significantly different between grade I tumors and grade IV tumors ( p = 0.027) and a K^trans ratio value superior to 0.63 appeared to be discriminant to determine a grade IV of malignancy. Conclusions Our results confirm the feasibility of pediatric T1-weighted DCE MRI at 1.5T with a low injection rate, which could be of great value in differentiating brain tumor grades.

Utility of histogram analysis of ADC maps for differentiating orbital tumors

PURPOSE

We aimed to evaluate the role of histogram analysis of apparent diffusion coefficient (ADC) maps for differentiating benign and malignant orbital tumors.

METHODS

Fifty-two patients with orbital tumors were enrolled from March 2013 to November 2014. Pretreatment diffusion-weighted imaging was performed on a 3T magnetic resonance scanner with b factors of 0 and 800 s/mm2, and the corresponding ADC maps were generated. Whole-tumor regions of interest were drawn on all slices of the ADC maps to obtain histogram parameters, including ADCmean, ADCmedian, standard deviation (SD), skewness, kurtosis, quartile, ADC10, ADC25, ADC75, and ADC90. Histogram parameter differences between benign and malignant orbital tumors were compared. The diagnostic value of each significant parameter in predicting malignant tumors was established.

RESULTS

Age, ADCmean, ADCmedian, quartile, kurtosis, ADC10, ADC25, ADC75, and ADC90 parameters were significantly different between benign and malignant orbital tumor groups, while gender, location, SD, and skewness were not significantly different. The best diagnostic performance in predicting malignant orbital tumors was achieved at the threshold of ADC10=0.990 (AUC, 0.997; sensitivity, 96.2%; specificity, 100%).

CONCLUSION

Histogram analysis of ADC maps holds promise for differentiating benign and malignant orbital tumors. ADC10 has the potential to be the most significant parameter for predicting malignant orbital tumors.

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

PURPOSE

To determine the optimal combination of parameters derived from 3T multiparametric (conventional magnetic resonance imaging [MRI], diffusion-weighted [DW] and dynamic contrast-enhanced [DCE]) MRI for differentiating malignant from benign orbital lymphoproliferative disorders (OLPDs).

MATERIALS AND METHODS

Forty patients with OLPDs (18 benign and 22 malignant) underwent conventional 3.0T MR, DW, and DCE-MRI examination for presurgery evaluation. Conventional MRI features (including tumor laterality, shape, number of involved quadrants, signal intensity on T₁ -weighted imaging (WI) and T₂ WI, flow void sign on T₂ WI, and findings suggestive of sinusitis) were reviewed, and multivariate logistic regression analysis was used to identify the most significant conventional MRI features. Apparent diffusion coefficient (ADC) and DCE-MRI derived parameters (area under curve [AUC], time to peak [TTP], maximum rise slope [Slope_max ]) were measured and compared between two groups. Receiver operating characteristic (ROC) curve analyses were used to determine the diagnostic ability of each combination that was established based on identified qualitative and quantitative parameters.

RESULTS

Multivariate logistic regression analysis showed that the presence of flow void sign on T₂ WI significantly associated with benign OLPDs (P = 0.034). Malignant OLPDs demonstrated significantly lower ADC (P = 0.001) and AUC (P = 0.002) than benign mimics. ROC analyses indicted that, ADC alone showed the optimal sensitivity (threshold value, 0.886 × 10^-3 mm² /s; sensitivity, 90.9%), while a combination of no presence of flow void sign on T₂ WI + ADC ≤ 0.886 × 10^-3 mm² /s + AUC ≤ 7.366 showed optimal specificity (88.9%) in differentiating benign from malignant OLPDs.

CONCLUSION

Multiparametric MRI can help to differentiate malignant from benign OLPDs. DWI offers optimal sensitivity, while the combination of conventional MRI, DWI, and DCE-MRI offers optimal specificity.

LEVEL OF EVIDENCE

3 J. Magn. Reson. Imaging 2017;45:167-176.

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

PURPOSE

To investigate the diagnostic performance of diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), and the combination of both in the differential diagnosis of lymphoma and inflammation in the orbit.

MATERIALS AND METHODS

This retrospective study was approved by the Institutional Review Board and the informed consent requirement was waived. A total of 53 patients underwent preoperative 3T MRI. Parameters of DWI and DCE MRI were evaluated in these 30 patients with orbital lymphoma and 23 patients with orbital inflammation. The diagnostic performance was evaluated using receiver operating characteristic curve analysis.

RESULTS

Apparent diffusion coefficient (ADC) values and parameters derived from DCE MRI of orbital lymphoma and orbital inflammation differed significantly (ADC, T_max , contrast index [CI], enhancement ratio [ER], and washout ratio [WR]: P < 0.001, P = 0.008, P < 0.001, P < 0.001, and P = 0.005 for reviewer 1, respectively; P < 0.001, P = 0.004, P < 0.001, P < 0.001, and P < 0.001 for reviewer 2, respectively). Sensitivity, specificity, and accuracy values of DWI were 76.67%, 100%, and 86.79% for reviewer 1; 70%, 95.65%, and 81.13% for reviewer 2, respectively. The combination of both were 90%, 86.96%, and 88.68% for reviewer 1; 93.33%, 78.26%, and 86.79% for reviewer 2, respectively. The combination of both was significantly superior to DWI for differentiation of orbital lymphoma from orbital inflammation (P = 0.016 for reviewer 1; P = 0.001 for reviewer 2).

CONCLUSION

The combination of DWI and DCE MRI can improve diagnostic performance in differentiating lymphoma from inflammation in the orbit compared with DWI alone.

LEVEL OF EVIDENCE

3 J. MAGN. RESON. IMAGING 2017;45:1438-1445.

Diffusion Weighted Imaging for Differentiating Benign from Malignant Orbital Tumors: Diagnostic Performance of the Apparent Diffusion Coefficient Based on Region of Interest Selection Method

Objective

To evaluate the differences in the apparent diffusion coefficient (ADC) measurements based on three different region of interest (ROI) selection methods, and compare their diagnostic performance in differentiating benign from malignant orbital tumors.

Materials and Methods

Diffusion-weighted imaging data of sixty-four patients with orbital tumors (33 benign and 31 malignant) were retrospectively analyzed. Two readers independently measured the ADC values using three different ROIs selection methods including whole-tumor (WT), single-slice (SS), and reader-defined small sample (RDSS). The differences of ADC values (ADC-ROI_WT, ADC-ROI_SS, and ADC-ROI_RDSS) between benign and malignant group were compared using unpaired t test. Receiver operating characteristic curve was used to determine and compare their diagnostic ability. The ADC measurement time was compared using ANOVA analysis and the measurement reproducibility was assessed using Bland-Altman method and intra-class correlation coefficient (ICC).

Results

Malignant group showed significantly lower ADC-ROI_WT, ADC-ROI_SS, and ADC-ROI_RDSS than benign group (all p < 0.05). The areas under the curve showed no significant difference when using ADC-ROI_WT, ADC-ROI_SS, and ADC-ROI_RDSS as differentiating index, respectively (all p > 0.05). The ROI_SS and ROI_RDSS required comparable measurement time (p > 0.05), while significantly shorter than ROI_WT (p < 0.05). The ROI_SS showed the best reproducibility (mean difference ± limits of agreement between two readers were 0.022 [-0.080–0.123] × 10^-3 mm²/s; ICC, 0.997) among three ROI methods.

Conclusion

Apparent diffusion coefficient values based on the three different ROI selection methods can help to differentiate benign from malignant orbital tumors. The results of measurement time, reproducibility and diagnostic ability suggest that the ROI_SS method are potentially useful for clinical practice.

Orbital Indeterminate Lesions in Adults: Combined Magnetic Resonance Morphometry and Histogram Analysis of Apparent Diffusion Coefficient Maps for Predicting Malignancy

RATIONALE AND OBJECTIVES

The aim of this study was to evaluate the added value of histogram analysis of apparent diffusion coefficient (ADC) maps in differentiating indeterminate orbital malignant tumors from benign tumors, compared to using magnetic resonance (MR) morphological features alone.

MATERIALS AND METHODS

We retrospectively evaluated 54 patients with orbital tumors from March 2013 to February 2015. All the patients were assessed by both routine MR and diffusion-weighted imaging, and divided into benign group and malignant group. Routine MR imaging features and histogram parameters derived from ADC maps, including mean ADC (ADCmean), median ADC (ADCmedian), standard deviation, skewness, kurtosis, and 10th and 90th percentiles of ADC (ADC10 and ADC90), were compared between two groups. Univariate and multivariate logistic regression analyses were used to identify the most valuable variables in predicting malignancy. Receiver operating characteristic (ROC) curve analysis was used to determine the diagnostic value of significant variables.

RESULTS

Multivariate logistic regression analysis indicated that two or more quadrants involved, iso-intense on T2-weighted imaging (T2WI), and ADC10 were significant predictors for orbital malignancy. By using model 2 (iso-intense on T2WI + two or more quadrants involved + ADC10 < 0.990) as the criterion, higher AUC and specificity could be achieved than by using model 1 (iso-intense on T2WI + two or more quadrants involved) alone, (model 2 vs model 1; area under curve (AUC), 0.827 vs 0.793; sensitivity, 65.4% vs 69.2%; specificity, 100% vs 89.3%).

CONCLUSIONS

Iso-intense on T2WI, two or more quadrants involved, and ADC10 are risk factors for orbital malignancy. Histogram analysis of ADC map might provide added value in predicting orbital malignancy.

Improved performance in differentiating benign from malignant sinonasal tumors using diffusion-weighted combined with dynamic contrast-enhanced magnetic resonance imaging

Background:

Differentiating benign from malignant sinonsal lesions is essential for treatment planning as well as determining the patient's prognosis, but the differentiation is often difficult in clinical practice. The study aimed to determine whether the combination of diffusion-weighted (DW) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can improve the performance in differentiating benign from malignant sinonasal tumors.

Methods:

This retrospective study included 197 consecutive patients with sinonasal tumors (116 malignant tumors and 81 benign tumors). All patients underwent both DW and DCE-MRI in a 3-T magnetic resonance scanner. Two different settings of b values (0,700 and 0,1000 s/mm²) and two different strategies of region of interest (ROI) including whole slice (WS) and partial slice (PS) were used to calculate apparent diffusion coefficients (ADCs). A DW parameter with WS ADCs_b0,1000 and two DCE-MRI parameters (time intensity curve [TIC] and time to peak enhancement [Tpeak]) were finally combined to use in differentiating the benign from the malignant tumors in this study.

Results:

The mean ADCs of malignant sinonasal tumors (WS ADCs_b0,1000 = 1.084 × 10⁻³ mm²/s) were significantly lower than those of benign tumors (WS ADCs_b0,1000 = 1.617 × 10⁻³ mm²/s, P < 0.001). The accuracy using WS ADCs_b0,1000 alone was 83.7% in differentiating the benign from the malignant tumors (85.3% sensitivity, 81.2% specificity, 86.4% positive predictive value [PPV], and 79.5% negative predictive value [NPV]). The accuracy using DCE with Tpeak and TIC alone was 72.1% (69.1% sensitivity, 74.1% specificity, 77.5% PPV, and 65.1% NPV). Using DW-MRI parameter was superior than using DCE parameters in differentiation between benign and malignant sinonasal tumors (P < 0.001). The accuracy was 87.3% (90.5% sensitivity, 82.7% specificity, 88.2% PPV, and 85.9% NPV) using DW-MRI combined with DCE-MRI, which was superior than that using DCE-MRI alone or using DW-MRI alone (both P < 0.001) in differentiating the benign from the malignant tumors.

Conclusions:

Diffusion-weighted combined with DCE-MRI can improve imaging performance in differentiating benign from malignant sinonasal tumors, which has the potential to improve diagnostic accuracy and to provide added value in the management for these tumors.

Orbital lymphoma mimicking lacrimal gland pleomorphic adenoma

Purpose

To describe the case of a patient affected by orbital lymphoma mimicking pleomorphic adenoma of the lacrimal gland.

Methods

This was a retrospective case report.

Results

We present the case of a patient with 15-year history of slowly progressive left proptosis and inferomedial bulbar dislocation who had the presumptive diagnosis of lacrimal gland pleomorphic adenoma based on clinical and radiological features. The patient underwent lateral orbitotomy and lacrimal gland excision. Postoperative histological features were consistent with low-grade B-cell non-Hodgkin lymphoma.

Conclusion

The accepted clinico-radiological criteria used for the diagnosis of lacrimal gland fossa lesions might have a certain false-positive rate, even in recent years. The initial surgical approach with the appropriate choice between fine-needle aspiration biopsies, intraoperative biopsies and lacrimal gland excisions might be a challenge.

Orbital masses: the usefulness of diffusion-weighted imaging in lesion categorization

INTRODUCTION

Diffusion-weighted imaging (DWI) produces contrast among different kinds of tissues according to their diffusibility characteristics. The purpose of our study was to evaluate the role of DWI including measurement of apparent diffusion coefficient (ADC) values in recognizing benignancy or malignancy of orbital masses.

METHODS

A total of 39 orbital masses were evaluated visually for signal characteristics on DWI and ADC maps. ADC values were calculated for each lesion. Visual signal characteristics were compared using the Fisher exact test. Receiver operating characteristic (ROC) analysis was carried out to determine sensitivity and specificity for distinguishing malignant from benign lesions using ADC values. The Mann-Whitney U test was applied to compare the ADC values between orbital lymphomas and idiopathic orbital inflammatory (IOI) lesions, and between optic nerve sheath meningiomas and gliomas.

RESULTS

Visual assessment revealed no significant difference between benign and malignant lesions on DWI (p-value = 0.66). However, visual assessment of ADC maps revealed a statistically significant (p-value ≤ 0.0001) between benign and malignant lesions. ROC analysis showed a sensitivity of 83.33 % and a specificity of 85.71 % when using an optimal cut off ADC value of 0.84 × 10(-3) mm(2)/s for differentiating malignant from benign lesions. Significant differences in mean ADC values were observed between lymphomas and IOI lesions (p-value = 0.05), and between optic nerve sheath meningiomas and gliomas (p-value = 0.03).

CONCLUSION

DWI is useful for differentiating malignant and benign orbital tumors if accompanied by visual assessment of ADC maps and ADC value calculations.

Assessment of dynamic contrast-enhanced magnetic resonance imaging in the differentiation of malignant from benign orbital masses

OBJECTIVE

Dynamic contrast enhanced MR imaging (DCE-MRI) allows imaging of the physiology of the microcirculation. The purpose of this study was to determine the diagnostic efficacy of time intensity curve (TIC) and DCE parameters for characterization of orbital masses.

METHODS

Fifty-nine patients with untreated orbital lesions underwent DCE-MRI before surgery. For each lesion, peak height (PH), maximum enhancement ratio (ERmax), time of peak enhancement (Tpeak) and maximum rise slope (Slopemax) were plotted and calculated. Receiver operator characteristics (ROC) analysis was conducted to assess the appropriate cut-off value.

RESULTS

All 26 lesions that demonstrated persistent pattern (type-I) TICs were benign. Most of the masses with the washout pattern (type-III) TIC were malignant (10/14), including lymphoma (n=6) and melanoma (n=4). The Slopemax of benign lesions was statistically lower than malignant ones, while the ERmax and Tpeak values of benign lesions were significantly higher. No statistical difference was found in PH (P=0.121). The AUC for ERmax, Tpeak and Slopemax in differentiating benign orbital lesions from malignant ones were 0.683, 0.837 and 0.738, respectively. In the three DCE parameters, Slopemax cut-off value of 1.10 provided the highest sensitivity of 93.8%; however, the corresponding specificity was low (58.1%). The ERmax cut-off value of 1.37 and Tpeak cut-off value of 35.14 respectively offered the best diagnostic performances.

CONCLUSION

DCE-MRI, especially the qualitative TIC pattern and quantitative value of Slopemax, ERmax and Tpeak, could be a complementary investigation in distinguishing malignant orbital tumor from benign ones.

Value of MR imaging in differentiation between solitary fibrous tumor and schwannoma in the orbit

BACKGROUND AND PURPOSE

Orbital SFT is a rare tumor, often misdiagnosed as orbital schwannoma preoperatively but with different prognosis and treatment. Our aim was to evaluate MR imaging features that might distinguish orbital SFT from schwannoma.

MATERIALS AND METHODS

MR imaging including DCE scanning was performed in 9 patients with SFT and 22 patients with schwannoma in the orbit confirmed by pathology. Location, shape, margin, signal intensity, homogeneity, enhancement pattern, ER, and TIC of the tumors were retrospectively evaluated.

RESULTS

There was a statistically significant difference between SFT and schwannoma in location and T2 signal intensity (P < .05). A statistically significant difference was also found regarding the enhancement pattern of the very high-signal-intensity areas shown on T2-weighted imaging and the type of TICs (P < .01).

CONCLUSIONS

MR imaging is useful in differentiating orbital SFT and schwannoma. The enhancement pattern of the very high-signal-intensity areas shown on T2-weighted imaging and the type of TICs on DCE MR imaging played an important role in differentiating orbital SFT from schwannoma.

Primary extranodal Non-Hodgkin lymphoma of the orbital and paranasal region-a retrospective study

PURPOSE

Primary extranodal lymphomas of the orbit and sinonasal region are rare and occur almost only as Non-Hodgkin lymphoma (NHL). The purpose of this study was to determine the frequency of different subtypes of NHL in these regions and to describe their radiological features.

MATERIALS AND METHODS

Between January 2005 and January 2010, 567 patients with malignant immunoproliferative diseases (MID) were treated at our institution. Primary sinonasal and orbital manifestation was diagnosed in 36 cases. There were 13 women and 23 men with a median age of 67 years. CT and MRI were performed in 14 and 24 patients, respectively. Imaging was re-interpretated and histological subtypes were listed.

RESULTS

Among all MID primary sinonasal and orbital NHL occurred with a frequency of 6%. Diffuse large cell lymphoma was identified in 11 cases (30%), marginal cell lymphoma in 6 (16%), and extranodal plasmacytoma in 5 (14%). Other subtypes were rare. On CT, lesions of soft tissue attenuation with homogeneous moderate contrast enhancement were seen in all cases. On T2-weighted fat saturated images 52% of the lesions were slightly hyperintense in comparison to unaffected musculature, 41% were isointense, and 7% slightly hypointense. On T1-weighted sequences most lesions (81%) were homogeneously isointense. After contrast administration marked enhancement was seen in 41%, moderate in 52%, and slight enhancement in 7%.

CONCLUSION

The identified radiological features should be included in the differential analysis of lesions in the orbital and sinonasal regions, but they are not specific enough. For exact therapeutic planning histopathological diagnosis of the subtype is required.

Orbital lymphoma: imaging features and differential diagnosis

Purpose

Patterns of orbital lymphoma at diagnosis and follow-up are described. We also discuss differential diagnosis of orbital masses.

Materials and methods

This pictorial review contains 19 cases of orbital lymphoma before and after treatment. Superior-lateral quadrant and extra-conal location were observed predominantly. Effective response after treatment was presented on follow-up imaging, although few local relapses were found. Further follow-up showed no changes of residual images.

Discussion

Location of orbital masses can help in the differential diagnosis. Moreover, imaging features of lymphoma at diagnosis can be useful in planning surgical biopsy. Pattern of follow-up described may be relevant on monitoring imaging.

Teaching points

• Orbital lymphoma involves mainly superior-lateral quadrant and the orbital structures inside.

• Location of retrobulbar mass-like lesions are useful information in the differential diagnosis.

• Satisfactory response is detected after treatment, however relapse is noted, so follow-up is needed.

Differentiation between benign and malignant orbital tumors at 3-T diffusion MR-imaging

INTRODUCTION

To differentiate between malignant and benign orbital tumors at 3-T diffusion MR imaging.

METHODS

A retrospective study was conducted on 47 patients (34 males and 13 females aged 4-74 years) with orbital masses. They underwent echo-planar diffusion-weighted MR imaging of the orbit with b-factor of 0, 500, and 1,000 s/mm(2) at 3-T MR unit. Apparent diffusion coefficient (ADC) maps were reconstructed, and the ADC value of the orbital mass was calculated.

RESULTS

The mean ADC value of the malignant orbital tumors (0.84 ± 0.34 × 10(-3) mm(2)/s) was significantly lower (P = 0.001) than that of the benign orbital tumors (1.57 ± 0.33 × 10(-3) mm(2)/s). The selection of an ADC value of 1.15 × 10(-3) mm(2)/s as a threshold value for differentiating malignant orbital tumors from benign lesions has a sensitivity of 95%, a specificity of 91%, and an accuracy of 93%. There was a significant difference in the ADC value between well- and poorly differentiated malignancies (P = 0.005).

CONCLUSION

Apparent diffusion coefficient value at 3 T is an additional noninvasive imaging parameter that can be used for the differentiation of malignant orbital tumors from benign lesions, the characterization of some orbital tumors, as well as the grading of orbital malignancy.

Evaluation of MR imaging findings differentiating cavernous haemangiomas from schwannomas in the orbit

Objective

It is important to distinguish between orbital cavernous haemangioma and schwannoma because the treatments of choice for the two tumours are different. The aim was to evaluate MR imaging findings distinguishing the two tumours.

Methods

Magnetic resonance imaging including T1- and T2-weighted imaging and contrast-enhanced MR imaging was performed in 43 patients with cavernous haemangiomas and 16 patients with schwannomas confirmed by pathology. Location, configuration, margins, signal intensity, homogeneity and enhancement pattern of the tumour were retrospectively evaluated.

Results

There was a significant difference between cavernous haemangiomas and schwannomas regarding the location, configuration and margins of the mass, signal intensity and homogeneity on T1- and T2-weighted imaging, the spread pattern of contrast enhancement, the enhancement pattern and the type of time–intensity curve (P < 0.05). Markedly homogeneous hyperintensity signal on T2-weighted imaging and the spread pattern of the contrast enhancement favoured cavernous haemangioma rather than schwannoma (P < 0.01).

Conclusion

Cavernous haemangiomas and schwannomas have different MR imaging features that could be helpful in the differentiation between the tumours. The spread pattern of the contrast enhancement on dynamic contrast-enhanced MR imaging is the most reliable finding distinguishing cavernous haemangiomas from schwannomas.