Purpose To assess the diagnostic accuracy of magnetic resonance (MR) imaging for differentiating stage T1 or lower tumors from stage T2 or higher tumors and to analyze the influence of different imaging protocols in patients with bladder cancer. Materials and Methods A systematic literature search for original diagnostic studies was performed in PubMed, Medline, the Cochrane Library, and Web of Science. The methodologic quality of each study was evaluated by two independent reviewers who used the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Data necessary to complete 2 × 2 tables were obtained, and patient, study, and imaging characteristics were extracted. Statistical analysis included data pooling, heterogeneity testing, sensitivity analyses, and forest plot construction. Results Seventeen studies (1449 patients with bladder cancer) could be analyzed. The pooled sensitivity and specificity of MR imaging were 0.90 (95% confidence interval [CI]: 0.83, 0.94) and 0.88 (95% CI: 0.77, 0.94), respectively, for differentiating tumors staged T1 or lower from those staged T2 or higher. Diffusion-weighted imaging and use of higher field strengths (3 T) improved sensitivity (0.92; 95% CI: 0.86, 0.96) and specificity (0.96; 95% CI: 0.93, 0.98). Conclusion This meta-analysis demonstrated high diagnostic performance of MR imaging for differentiating T1 or lower tumors from T2 or higher tumors in patients with bladder cancer. Higher field strength (3 T) and the use of diffusion-weighted imaging can slightly help improve sensitivity and specificity. RSNA, 2017.

Purpose To determine if tumor stiffness by MR Elastography (MRE) is associated with hepatocellular carcinoma (HCC) pathologic features. Material and Methods A retrospective review was undertaken of all patients with pathologically confirmed HCC who underwent MRE prior to locroregional therapy, surgical resection or transplant between 1/1/2007 to 12/31/2015. An independent observer measured tumor stiffness (kilopascals, kPa) by drawing regions of interest (ROI) covering the HCC and in the case of HCCs with non-enhancing/necrotic components, only the solid portion was included in the ROI. HCC tumor grade (WHO criteria), vascular invasion and tumor encapsulation were assessed from retrievable pathology specimens by an expert hepatobiliary pathologist. Tumor stiffness was compared by tumor grade, size, presence of capsule and vascular invasion using student’s t-test (or Exact Mann-Whitney test). Results 21 patients were identified who had pathologically confirmed HCC and tumor MRE data. 17 patients (81.0%) had underlying chronic liver disease. The mean±SD tumor size (cm) was 5.3±3.9 cm. The mean±SD tumor stiffness was 5.9±1.4 kPa. Tumors were graded as well differentiated (N=2), moderately differentiated (N=11) and poorly differentiated (N=8). There was a trend toward increased tumor stiffness in well/moderately differentiated HCC (6.5k±1.2 kPa; N=13) compared to poorly differentiated HCC (4.9±1.2 kPa; N=8) (p<0.01). There was no significant correlation between tumor stiffness and liver stiffness or tumor size. There was no significant difference in tumor stiffness by presence or etiology of chronic liver disease, vascular invasion or tumor encapsulation. Conclusion Preliminary data suggest that tumor stiffness by MRE may be able to differentiate HCC tumor grade.

Stereo-electroencephalography (SEEG) implantation before epilepsy surgery is critical for precise localization and complete resection of the seizure onset zone (SOZ). Combined metabolic and morphological imaging using hybrid PET/MRI may provide supportive information for the optimization of the SEEG coverage of brain structures. In this study, we originally imported PET/MRI images into the SEEG positioning system to evaluate the application of PET/MRI in guiding SEEG implantation in refractory epilepsy patients. Materials: Forty-two patients undergoing simultaneous PET/MRI examinations were recruited. All the patients underwent SEEG implantation guided by hybrid PET/MRI and surgical resection or ablation of epileptic lesion. Surgery outcome was assessed using a modified Engel classification one year (13.60 ± 2.49 months) after surgery. Areas of SOZ were identified using hybrid PET/MRI and concordance with SEEG was evaluated. Logistic regression analysis was used to predict the presence of a favorable outcome with the coherence of concordance of PET/MRI and SEEG. Results: Hybrid PET/MRI (including visual PET, MRI, plus MI Neuro) identified SOZ lesions in 38 epilepsy patients (90.47 %). PET/MRI showed the same SOZ localization with SEEG in 29 patients (69.05 %), which was considered to be concordant. The concordance between the PET/MRI and SEEG findings was significantly predictive of a successful surgery outcome (odds ratio = 20.41; 95 % CI = 2.75-151.4, P = 0.003**). Conclusion: Hybrid PET/MRI combined visual PET, multiple sequences MRI and SPM PET helps identify epilepsy lesions particularly in subtle hypometabolic areas. Patients with concordant epileptic lesion localization on PET/ MRI and SEEG demonstrated a more favorable outcome than those with inconsistent localization between modalities.

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