Gpu-accelerated JEMRIS for extensive MRI simulations.

Purpose: To enable accelerated Bloch simulations by enhancing the open-source multi-purpose MRI simulation tool JEMRIS with graphic processing units (GPU) parallelization.

Methods: A GPU-compatible version of JEMRIS was built by shifting the computationally expensive parallelizable processes to the GPU to benefit from heterogeneous computing and by adding asynchronous communication and mixed precision support. With key classes reimplemented in CUDA C++, the developed GPU-JEMRIS framework was tested on simulations of common MRI artifacts in numerical phantoms.

Label-free protein-structure-sensitive live-cell microscopy for patient-specific assessment of myeloma therapy.

The efficacy of drug therapy in multiple myeloma is conventionally assessed by whole-cell-population methods, serum analysis of light chains and monoclonal antibodies, immunofixation electrophoresis, or by flow cytometry of bone marrow aspirates and biopsies. These methods provide relevant information on the presence of specific immunoglobulins at high sensitivity and specificity but require a large number of cells, involve long and laborious sample preparation steps, and provide only tumour bulk information. Here we develop a single-cell imaging technique requiring a reduced number of primary cells for longitudinal evaluation of patient-specific treatment and assessment of treatment heterogeneity.