Single shot zonal oblique multislice SE-EPI diffusion-weighted imaging with low to ultra-high b-values for the differentiation of benign and malignant vertebral spinal fractures. (2021) - Sartoretti, Elisabeth; Sartoretti-Schefer, Sabine; van Smoorenburg, Luuk; Eichenberger, Barbara; Schwenk, Árpád; Czell, David; Alfieri, Alex; Gutzeit, Andreas; Mannil, Manoj; Binkert, Christoph A.; Wyss, Michael; Sartoretti, Thomas
Abstract: Purpose: To investigate the diagnostic yield of low to ultra-high b-values for the differentiation of benign from malignant vertebral fractures using a state-of-the-art single-shot zonal-oblique-multislice spin-echo echo-planar diffusion-weighted imaging sequence (SShot ZOOM SE-EPI DWI). Materials and Methods: 66 patients (34 malignant, 32 benign) were examined on 1.5 T MR scanners. ADC maps were generated from b-values of 0, 400; 0, 1000 and 0, 2000s/mm 2 . ROIs were placed into the fracture of interest on ADC maps and trace images and into adjacent normal vertebral bodies on trace images. The ADC of fractures and the Signal-Intensity-Ratio (SIR) of fractures relative to normal vertebral bodies on trace images were considered quantitative metrics. The appearance of the fracture of interest was graded qualitatively as iso-, hypo-, or hyperintense relative to normal vertebrae. Results: ADC achieved an area under the curve (AUC) of 0.785/0.698/0.592 for b = 0, 400/0, 1000/0, 2000s/mm 2 ADC maps respectively. SIR achieved an AUC of 0.841/0.919/0.917 for b = 400/1000/2000s/mm 2 trace images respectively. In qualitative analyses, only b = 2000s/mm 2 trace images were diagnostically valuable (sensitivity:1, specificity:0.794). Machine learning models incorporating all qualitative and quantitative metrics achieved an AUC of 0.95/0.98/0.98 for b-values of 400/1000/2000s/mm 2 respectively. The model incorporating only qualitative metrics from b = 2000s/mm 2 achieved an AUC of 0.97. Conclusion: By using quantitative and qualitative metrics from SShot ZOOM SE-EPI DWI, benign and malignant vertebral fractures can be differentiated with high diagnostic accuracy. Importantly qualitative analysis of ultra-high b-value images may suffice for differentiation as well.