Magnetic resonance conditionality of abandoned leads from active implantable medical devices at 1.5 T.

PURPOSE: During MR scans, abandoned leads from active implantable medical devices (AIMDs) can experience excessive heating at the lead tip, depending on the type of termination applied to the proximal contacts (proximal end treatment). The influence of different proximal end treatments (ie, [1] freely exposed in the tissue, [2] terminated with metal in contact with the tissue, or [3] capped with plastic, and thereby fully insulated, on the RF-induced lead-tip heating) are studied. A technique to ensure that MR Conditional AIMD leads remain MR Conditional even when abandoned is recommended. METHODS: Abandoned leads from three MR Conditional AIMDs ([1] a sacral neuromodulation system, [2] a cardiac rhythm management pacemaker system, and [3] a deep brain stimulator system) were investigated in this study. The computational lead models (ie, the transfer functions) for different proximal end treatments were measured and used to assess the in vivo lead-tip heating for four virtual human models (FATS, Duke, Ella, and Billie) and compared with the lead-tip heating of the complete MR Conditional AIMD system. RESULT: The average and maximum lead-tip heating for abandoned leads proximally capped with metal is always lower than that from the complete AIMD system. Abandoned leads proximally insulated could lead to an average in vivo temperature rise up to 3.5 times higher than that from the complete AIMD system. CONCLUSION: For the three investigated AIMDs under 1.5T MR scanning, our results indicate that RF-induced lead-tip heating of abandoned leads strongly depends on the proximal lead termination. A metallic cap applied to the proximal termination of the tested leads could significantly reduce the RF-induced lead-tip heating.

Classification of hyperactivated spermatozoa using a robust Minimum Bounding Square Ratio algorithm.

A method for automatically identifying and classifying hyperactivated spermatozoa trajectories is described. This physiologically-based computerized algorithm captures the motion behavior of sperm during hyperactivation. A novel Minimum Bounding Square Ratio (MBSR) algorithm classifies spermatoza as hyperactivated, transitional or progressive. Classification boundaries were established on selected trajectory data from a single stallion and then tested on random trajectories of sperm from other stallions. MBSR classified sperm in a robust and effective manner.