Toward Precision Diagnosis: Machine Learning in Identifying Malignant Orbital Tumors With Multiparametric 3 T MRI.

BACKGROUND: Orbital tumors present a diagnostic challenge due to their varied locations and histopathological differences. Although recent advancements in imaging have improved diagnosis, classification remains a challenge. The integration of artificial intelligence in radiology and ophthalmology has demonstrated promising outcomes. PURPOSE: This study aimed to evaluate the performance of machine learning models in accurately distinguishing malignant orbital tumors from benign ones using multiparametric 3 T magnetic resonance imaging (MRI) data. MATERIALS AND METHODS: In this single-center prospective study, patients with orbital masses underwent presurgery 3 T MRI scans between December 2015 and May 2021. The MRI protocol comprised multiparametric imaging including dynamic contrast-enhanced (DCE), diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), as well as morphological imaging acquisitions. A repeated nested cross-validation strategy using random forest classifiers was used for model training and evaluation, considering 8 combinations of explanatory features. Shapley additive explanations (SHAP) values were used to assess feature contributions, and the model performance was evaluated using multiple metrics. RESULTS: One hundred thirteen patients were analyzed (57/113 [50.4%] were women; average age was 51.5 ± 17.5 years, range: 19-88 years). Among the 8 combinations of explanatory features assessed, the performance on predicting malignancy when using the most comprehensive model, which is the most exhaustive one incorporating all 46 explanatory features-including morphology, DWI, DCE, and IVIM, achieved an area under the curve of 0.9 [0.73-0.99]. When using the streamlined "10-feature signature" model, performance reached an area under the curve of 0.88 [0.71-0.99]. Random forest feature importance graphs measured by the mean of SHAP values pinpointed the 10 most impactful features, which comprised 3 quantitative IVIM features, 4 quantitative DCE features, 1 quantitative DWI feature, 1 qualitative DWI feature, and age. CONCLUSIONS: Our findings demonstrate that a machine learning approach, integrating multiparametric MRI data such as DCE, DWI, IVIM, and morphological imaging, offers high-performing models for differentiating malignant from benign orbital tumors. The streamlined 10-feature signature, with a performance close to the comprehensive model, may be more suitable for clinical application.

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.

Recent Experience and Follow-Up After Surgical Closure of Secundum Atrial Septal Defect in 120 Children.

While percutaneous catheter closure proves an effective treatment for secundum atrial septal defect (ASD2), some child patients require surgical closure. We assessed the risks associated with isolated surgical ASD2 closure by reviewing the outcomes of 120 children operated on between 1999 and 2011 (mean age 4.6 ± 3.9 years, mean weight 17 ± 12 kg). Direct sutures were performed in 4% and patch closures in 96%. The mean cardiopulmonary bypass duration was 38 ± 14 min, aortic cross-clamp time 19 ± 9 min, intensive care unit length of stay 1.6 ± 1.1 days, hospital stay 11.2 ± 5.1 days. There were no complications in 60 patients (50%) and major complications in 8 (6.7%), with 1 patient (0.8%) dying of pneumonia-induced sepsis, 2 (1.7%) requiring revision surgery, 3 (2.5%) requiring invasive treatment (2 pericardial drainage, 1 successful resuscitation), and 2 (1.7%) presenting thromboembolisms (1 cerebral stroke, 1 cardiac thrombus). In hospital minor complications occurred in 22 patients: 17 pericardial effusions (15%), 15 infections requiring treatment (12.5%), 1 sternal instability (0.8%), 4 anemias requiring transfusion (3.3%), 7 pulmonary atelectasis (6%), and 2 post-extubation glottis edema (1.7%). At early outpatient follow-up, complications occurred in 21 patients: 16 (13.3%) pericardial effusions, 4 (3.3%) infections requiring treatment, and 3 (2.5%) keloid scarring. No complications occurred during long-term follow-up. In line with published data, mortality was low (0.8%), yet major complications (6.7%) were more common in these cases than those following percutaneous ASD2 closure. Minor complications were frequent (43%) with no long-term sequelae.