Artifact reduction of coaxial needles in magnetic resonance imaging-guided abdominal interventions at 1.5 T: a phantom study.

Needle artifacts pose a major limitation for MRI-guided interventions, as they impact the visually perceived needle size and needle-to-target-distance. The objective of this agar liver phantom study was to establish an experimental basis to understand and reduce needle artifact formation during MRI-guided abdominal interventions. Using a vendor-specific prototype fluoroscopic T1-weighted gradient echo sequence with real-time multiplanar acquisition at 1.5 T, the influence of 6 parameters (flip angle, bandwidth, matrix, slice thickness, read-out direction, intervention angle relative to B0) on artifact formation of 4 different coaxial MR-compatible coaxial needles (Nitinol, 16G-22G) was investigated. As one parameter was modified, the others remained constant. For each individual parameter variation, 2 independent and blinded readers rated artifact diameters at 2 predefined positions (15 mm distance from the perceived needle tip and at 50% of the needle length). Differences between the experimental subgroups were assessed by Bonferroni-corrected non-parametric tests. Correlations between continuous variables were expressed by the Bravais-Pearson coefficient and interrater reliability was quantified using the intraclass classification coefficient. Needle artifact size increased gradually with increasing flip angles (p = 0.002) as well as increasing intervention angles (p < 0.001). Artifact diameters differed significantly between the chosen matrix sizes (p = 0.002) while modifying bandwidth, readout direction, and slice thickness showed no significant differences. Interrater reliability was high (intraclass correlation coefficient 0.776-0.910). To minimize needle artifacts in MRI-guided abdominal interventions while maintaining optimal visibility of the coaxial needle, we suggest medium-range flip angles and low intervention angles relative to B0.

Diagnostic performance of qualitative and radiomics approach to parotid gland tumors: which is the added benefit of texture analysis?

OBJECTIVE: To investigate whether MRI-based texture analysis improves diagnostic performance for the diagnosis of parotid gland tumors compared to conventional radiological approach. METHODS: Patients with parotid gland tumors who underwent salivary glands MRI between 2008 and 2019 were retrospectively selected. MRI analysis included a qualitative assessment by two radiologists (one of which subspecialized on head and neck imaging), and texture analysis on various sequences. Diagnostic performances including sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) of qualitative features, radiologists' diagnosis, and radiomic models were evaluated. RESULTS: Final study cohort included 57 patients with 74 tumors (27 pleomorphic adenomas, 40 Warthin tumors, 8 malignant tumors). Sensitivity, specificity, and AUROC for the diagnosis of malignancy were 75%, 97% and 0.860 for non-subspecialized radiologist, 100%, 94% and 0.970 for subspecialized radiologist and 57.2%, 93.4%, and 0.927 using a MRI radiomics model obtained combining texture analysis on various MRI sequences. Sensitivity, specificity, and AUROC for the differential diagnosis between pleomorphic adenoma and Warthin tumors were 81.5%, 70%, and 0.757 for non-subspecialized radiologist, 81.5%, 95% and 0.882 for subspecialized radiologist and 70.8%, 82.5%, and 0.808 using a MRI radiomics model based on texture analysis of T2 weighted sequence. A combined radiomics model obtained with all MRI sequences yielded a sensitivity of 91.5% for the diagnosis of pleomorphic adenoma. CONCLUSION: MRI qualitative radiologist assessment outperforms radiomic analysis for the diagnosis of malignancy. MRI predictive radiomics models improves the diagnostic performance of non-subspecialized radiologist for the differential diagnosis between pleomorphic adenoma and Warthin tumor, achieving similar performance to the subspecialized radiologist. ADVANCES IN KNOWLEDGE: Radiologists outperform radiomic analysis for the diagnosis of malignant parotid gland tumors, with some MRI qualitative features such as ill-defined margins, perineural spread, invasion of adjacent structures and enlarged lymph nodes being highly specific for malignancy. A radiomic model based on texture analysis of T2 weighted images yields higher specificity for the diagnosis of pleomorphic adenoma compared to a radiologist non-subspecialized in head and neck radiology, thus minimizing false-positive pleomorphic adenoma diagnosis rate and reducing unnecessary surgical complications.