European Journal of Cardiovascular Medicine

Lesions of the orbit are usually classified based on the histological subtypes of the masses or based on their location. The use of conventional imaging modalities such as MRI (magnetic resonance imaging) and MDCT (multidetector computed tomography) have not proved sufficient specificity and sensitivity which can be helpful in the differentiation of benign lesions and malignant orbital lesions with a high chance of misdiagnosis of the cases with unexpected and rare entities.^1,2

With various advancements in the techniques and technologies for imaging in radiodiagnosis, the addition of magnetic resonance imaging techniques such as MRS (magnetic resonance spectroscopy), DWI (diffusion-weighted imaging), and MRS (magnetic resonance spectroscopy) to the conventional MRI sequencing can help provide various forms of the tissue contrast and can help for better characterization of the orbital lesions. However, existing literature data is scarce concerning the same.^3,4 Hence, the present study aimed to evaluate the efficacy of the utility of advanced magnetic resonance techniques in the improvement of the diagnostic ability for differentiation in malignant and benign orbital masses.

The present prospective assessment study aimed to evaluate the efficacy of the utility of advanced magnetic resonance techniques in the improvement of the diagnostic ability for differentiation in malignant and benign orbital masses. The study was done at Department of Radiodiagnosis, Sudha Medical College and Hospital, Jagpura, Kota, Rajasthan. The study subjects were from the Department of Radiology of the Institute. Verbal and written informed consent were taken from all the subjects before participation.

The study assessed 52 subjects 24 males and 28 female subjects with the mean age of 34.6 years that underwent MRI at the Institute within the defined study period. The subjects presented to the Institute with the complaint of reduced visual acuity and/or proptosis. The exclusion criteria for the study were subjects having contraindications for performing MRI as subjects with claustrophobia, metallic implants, subjects with large calcification or necrosis of orbital masses, and subjects that were not willing to participate in the present study.

All the imaging data were assessed by the two radiologists experienced in the field. For DWI, all the regions of interest (ROIs) were manually drawn. ADC (apparent diffusion coefficient) values were calculated after adjusting the size for regions of interest based on the size of the lesion. For lesions of <2cm in maximum diameter, ROI of 0.014 cm2 areas was made, and for lesions of >2cm diameter, a minimum of two or more regions of interest were placed excluding necrotic lesion area, and their mean ADC values were evaluated. ADC values were expressed as 10-3mm2/s. For MRS, CSI (chemical shift imaging) using SVS (single voxel spectroscopy) or multiple voxels were used based on lesion size and morphology. Fat and water suppression was automatically done before all spectroscopic assessments using CHESS and other volume fat suppression modalities.

Concerning DCE, the coronal dataset including lesion was attained immediately before contrast injection, and a further 6 datasets were attained 5 minutes following injection. Various regions of interest were applied and one region of interest was selected that showed maximum enhancement pattern. Lesion size assessed the size for the region of interest. The SI (signal intensity of each slice of the dynamic sequence was assessed from the mean pixel value. Representative ROI and corresponding TIC (time-intensity curve) were attained for each mass. The three types of enhancement curves seen were type I (persistent type) showing continuous progressive enhancement, type II (plateau type) with a sharp rise in enhancement followed by plateau, and type III (washout pattern) depicting a rapid rise in enhancement followed by rapid decline and with the final signal intensity of <90% of peak signal intensity.

Each TIC was used to derive values of baseline signal intensity (SIpre), Simax (maximum signal intensity at the peak of enhancement), and Tpre, Tpeak (times corresponding to these signal intensities) (Table 1). Dependent parameters such as Slopemax, enhancement ratio (Ermax), and PH (peak enhancement) were assessed using these four variables and formulas as

PH=SI_max – SI_pre

ER_max= (SI_max – SI_pre)/ SI_pre X100

Slope_max = (SI_max – SI_pre)/ [SI_pre X (T_peak – T_pre)] 100

Final diagnosis in all cases was attained via histopathological assessment following magnetic resonance imaging. The data gathered were statistically analyzed using SPSS (Statistical Package for the Social Sciences) software version 24.0 (IBM Corp., Armonk. NY, USA) for assessment of descriptive measures, Student t-test, ANOVA (analysis of variance), Fisher's exact test, Mann-Whitney U test, and Chi-square test. The results were expressed as mean and standard deviation and frequency and percentages. The p-value of <0.05 was considered.

The present prospective assessment study aimed to evaluate the efficacy of the utility of advanced magnetic resonance techniques in the improvement of the diagnostic ability for differentiation in malignant and benign orbital masses. The present study assessed 52 subjects 24 males and 28 females with a mean age of 34.6 years that presented with the orbital masses to the Institute within the defined study period. The location for orbital masses is described in Table 2. Among 52 subjects assessed in the study, there were 69.2% (n=36) orbital masses were histologically benign, and 30.7% (n=16) lesions were malignant. The histopathological distribution of lesions is summarized in Table 3. Mean ADC values for benign and malignant orbital masses are separately assessed (Table 4). In differentiating benign orbital masses from malignant masses, MRI had sensitivity, specificity, positive predictive values, and negative predictive values of 72.2%, 75%, 86.6%, and 54.5% respectively.

Table 1: Parameters used for MRI in study subjects

Table 2: location of the lesions in the orbit

Table 3: Histopathological distribution of malignant and benign orbital masses

Table 4: Distribution of mean ADC (10³ mm2/sec) values for malignant and benign lesions

Table 5: DCE parameters distribution with corresponding p-values

Table 6: Number of lesions depicting different enhancement curves

Table 7: Agreement test between histopathology and MRS

It was seen that for DCE parameters of malignant and benign lesions (Table 5), Slope and Tp depicted statistically significant differences in benign and malignant lesions with p<0.001. Slope had sensitivity, specificity, positive predictive values, and negative predictive values of 100%, 78%, 66.6%, and 100% respectively, whereas, Tp had sensitivity, specificity, positive predictive values, and negative predictive values of 94.45, 87.5%, 94.4%, and 87.5% respectively (Table 6).

Concerning the number of lesions depicting different enhancement curves, all lesions that depicted type I pattern were benign and type III lesions were malignant. Among 20 lesions showing type II curves, 14 were benign and 6 were malignant. The malignant lesions showing a type II curve were one MPNST, carcinoma NOS, and lymphoma. An o-value of 0.002 is seen for the type I and III curves. A significant difference was not seen in benign and malignant lesions using values of ER, PH, SI (max), and SI (pre).  

In all subjects, MRS data were assessed. The generated kappa value was 0.875 which depicted nearly a perfect agreement of malignancy with choline peak. Using choline peak, sensitivity, specificity, positive predictive values, and negative predictive values of 62.5%, 94.4%, 83.3%, and 85% were attained for malignancy.

The present study assessed 52 subjects 24 males and 28 females with a mean age of 34.6 years that presented with the orbital masses to the Institute within the defined study period. The location for orbital masses is described in Table 2. Among 52 subjects assessed in the study, there were 69.2% (n=36) orbital masses were histologically benign, and 30.7% (n=16) lesions were malignant. The histopathological distribution of lesions is summarized in Table 3. Mean ADC values for benign and malignant orbital masses are separately assessed (Table 4). In differentiating benign orbital masses from malignant masses, MRI had sensitivity, specificity, positive predictive values, and negative predictive values of 72.2%, 75%, 86.6%, and 54.5% respectively. These data were comparable to the studies of Roshdy N et al⁵ in 2010 and Wang CK et al⁶ in 2004 where authors reported similar MRI results for benign and malignant orbital lesions in their study subjects as seen in the results of the present study.

The study results showed that for DCE parameters of malignant and benign lesions (Table 5), Slope and Tp depicted statistically significant differences in benign and malignant lesions with p<0.001. The slope had sensitivity, specificity, positive predictive values, and negative predictive values of 100%, 78%, 66.6%, and 100% respectively, whereas, Tp had sensitivity, specificity, positive predictive values, and negative predictive values of 94.45, 87.5%, 94.4%, and 87.5% respectively. These results were in agreement with the findings of Yuan Y et al⁷ in 2013 and Razek AA et al⁸ in 2011 where DCE parameters of malignant and benign orbital lesions reported in the present study were comparable to the results reported by the authors.

It was seen that concerning several lesions depicting different enhancement curves, all lesions that depicted a type I pattern were benign and type III lesions were malignant. Among 20 lesions showing type II curves, 14 were benign and 6 were malignant. The malignant lesions showing a type II curve were one MPNST, carcinoma NOS, and lymphoma. A p-value of 0.002 is seen for the type I and III curves. A significant difference was not seen in benign and malignant lesions using values of ER, PH, SI (max), and SI (pre). These findings were consistent with the results of Xu XQ et al⁹ in 2016 and Sepahdari AR et al¹⁰ in 2010 where lesions depicting different enhancement curves comparable to the present study were also reported by the authors in their respective studies.  

It was also seen that in all subjects, MRS data were assessed. The generated kappa value was 0.875 which depicted nearly a perfect agreement of malignancy with choline peak. Using choline peak, sensitivity, specificity, positive predictive values, and negative predictive values of 62.5%, 94.4%, 83.3%, and 85% were attained for malignancy. These results were in line with the findings of Xu XQ et al¹¹ in 2017 and Lecler A et al¹² in 2017 where MRS data reported by the authors in their studies was comparable to the results of the present study

The present study, within its limitations, concludes that the usage of advanced MRI (magnetic resonance imaging) with the inclusion of perfusion parameters, MRS, and DW can significantly improve the diagnostic performance of radiologists in the differentiation of malignant and benign orbital masses. However, further multi-institutional studies with a larger sample size will help in reaching definitive conclusions

1. Nemec SF, Peloschek P, Schmook MT, Krestan CR, Hauff W, et al. CT-MR image data fusion for computer-assisted navigated surgery of orbital tumors. Eur J Radiol. 2010;73:224-9.
2. Xian J, Zhang Z, Wang Z, Li J, Yang B, et al. Value of MR imaging in the differentiation of benign and malignant orbital tumors in adults. Eur Radiol. 2010;20:1692-702.
3. Ro SR, Asbach P, Siebert E, Bertelmann E, Hamm B, Erb-Eigner K. Characterization of orbital masses by multiparametric MRI. Eur J Radiol. 2016;85:324-36.
4. Tailor TD, Gupta D, Dalley RW, Keene CD, Anzai Y. Orbital neoplasms in adults: clinical, radiologic, and pathologic review. Radiographics. 2013;33:1739- 58.
5. Roshdy N, Shahin M, Kishk H, El-Khouly S, Mousa A, et al. Role of new magnetic resonance imaging modalities in the diagnosis of orbital masses: a clinicopathologic correlation. Middle East Afr J Ophthalmol. 2010;17:175-9.
6. Wang CK, Li CW, Hsieh TJ, Chien SH, Liu GC, et al. Characterization of bone and soft-tissue tumors with in vivo 1H MR spectroscopy: initial results. Radiology. 2004;232:599-605.
7. Yuan Y, Kuai XP, Chen XS, Tao XF. Assessment of dynamic contrast-enhanced magnetic resonance imaging in the differentiation of malignant from benign orbital masses. Eur J Radiol. 2013;82:1506-11.
8. Razek AA, Elkhamary S, Mousa A. Differentiation between benign and malignant orbital tumors at 3-T diffusion MR-imaging. Neuroradiol. 2011;53:517-22.
9. Xu XQ, Hu H, Su GY, et al. Orbital indeterminate lesions in adults: combined magnetic resonance morphometry and histogram analysis of apparent diffusion coefficient maps for predicting malignancy. Acad Radiol 2016;23:200–8.
10. Sepahdari AR, Aakalu VK, Setabutr P, et al. Indeterminate orbital masses: restricted diffusion at MR imaging with echo-planar diffusion-weighted imaging predicts malignancy. Radiology 2010;256:554–64.
11. Xu XQ, Hu H, Liu H, et al. Benign and malignant orbital lymphoproliferative disorders: differentiating using multiparametric MRI at 3.0T. J Magn Reson Imaging. 2017;45:167–76.
12. Lecler A, Savatovsky J, Balvay D, et al. Repeatability of the apparent diffusion coefficient and intravoxel incoherent motion parameters at 3.0 Tesla in orbital lesions. Eur Radiol 2017;27:5094–103.