Exploring pelvic floor muscle activity in men with lower urinary tract symptoms

Aim We aimed to explore the utility of the Multiple Array Probe Leiden (MAPLe) device to assess pelvic floor muscle activity in men with lower urinary tract symptoms (LUTS). Methods This was an observational cohort study performed at the urology outpatient department of a large teaching hospital in the Netherlands between April and October 2018. We recruited male patients referred for the assessment of LUTS, without a history of prostate surgery, if they had an International Prostate Symptom Score greater than or equal to 8. The MAPLe device was then used to assess the puborectalis, pubococcygeus, iliococcygeus, urogenital diaphragm, and the internal and external anal sphincters during three tasks: a rest period (1 minute), five maximum voluntary contractions (held for 3 seconds each), and three maximal endurance contractions (held for 15 seconds each). Results In total, 57 patients were included, 5 of which had diabetes mellitus. Muscle activity at rest was significantly lower than during either contraction task and did not differ between the muscle groups. By contrast, the external anal sphincter had significantly less activity than any other muscle group during the endurance task, and the internal anal sphincter and puborectalis had significantly less activity during the maximum voluntary contraction task. No association was found between pelvic floor muscle activity and LUTS severity during any task. Conclusion Pelvic floor muscle activity and LUTS severity appear to be unrelated, but this does not completely exclude the possibility of muscle involvement in the development or experience of symptoms. Further research is needed

Diffusion-weighted MRI with deep learning for visualizing treatment results of MR-guided HIFU ablation of uterine fibroids

ObjectivesNo method is available to determine the non-perfused volume (NPV) repeatedly during magnetic resonance-guided high-intensity focused ultrasound (MR-HIFU) ablations of uterine fibroids, as repeated acquisition of contrast-enhanced T1-weighted (CE-T1w) scans is inhibited by safety concerns. The objective of this study was to develop and test a deep learning-based method for translation of diffusion-weighted imaging (DWI) into synthetic CE-T1w scans, for monitoring MR-HIFU treatment progression. MethodsThe algorithm was retrospectively trained and validated on data from 33 and 20 patients respectively who underwent an MR-HIFU treatment of uterine fibroids between June 2017 and January 2019. Postablation synthetic CE-T1w images were generated by a deep learning network trained on paired DWI and reference CE-T1w scans acquired during the treatment procedure. Quantitative analysis included calculation of the Dice coefficient of NPVs delineated on synthetic and reference CE-T1w scans. Four MR-HIFU radiologists assessed the outcome of MR-HIFU treatments and NPV ratio based on the synthetic and reference CE-T1w scans. ResultsDice coefficient of NPVs was 71% (& PLUSMN; 22%). The mean difference in NPV ratio was 1.4% (& PLUSMN; 22%) and not statistically significant (p = 0.79). Absolute agreement of the radiologists on technical treatment success on synthetic and reference CE-T1w scans was 83%. NPV ratio estimations on synthetic and reference CE-T1w scans were not significantly different (p = 0.27). ConclusionsDeep learning-based synthetic CE-T1w scans derived from intraprocedural DWI allow gadolinium-free visualization of the predicted NPV, and can potentially be used for repeated gadolinium-free monitoring of treatment progression during MR-HIFU therapy for uterine fibroids