Conventions and nomenclature for double diffusion encoding NMR and MRI.

Stejskal and Tanner's ingenious pulsed field gradient design from 1965 has made diffusion NMR and MRI the mainstay of most studies seeking to resolve microstructural information in porous systems in general and biological systems in particular. Methods extending beyond Stejskal and Tanner's design, such as double diffusion encoding (DDE) NMR and MRI, may provide novel quantifiable metrics that are less easily inferred from conventional diffusion acquisitions. Despite the growing interest on the topic, the terminology for the pulse sequences, their parameters, and the metrics that can be derived from them remains inconsistent and disparate among groups active in DDE. Here, we present a consensus of those groups on terminology for DDE sequences and associated concepts. Furthermore, the regimes in which DDE metrics appear to provide microstructural information that cannot be achieved using more conventional counterparts (in a model-free fashion) are elucidated. We highlight in particular DDE's potential for determining microscopic diffusion anisotropy and microscopic fractional anisotropy, which offer metrics of microscopic features independent of orientation dispersion and thus provide information complementary to the standard, macroscopic, fractional anisotropy conventionally obtained by diffusion MR. Finally, we discuss future vistas and perspectives for DDE.

Enhancing pancreatic adenocarcinoma delineation in diffusion derived intravoxel incoherent motion f-maps through automatic vessel and duct segmentation.

Diffusion-based intravoxel incoherent motion imaging has recently gained interest as a method to detect and characterize pancreatic lesions, especially as it could provide a radiation- and contrast agent-free alternative to existing diagnostic methods. However, tumor delineation on intravoxel incoherent motion-derived parameter maps is impeded by poor lesion-to-pancreatic duct contrast in the f-maps and poor lesion-to-vessel contrast in the D-maps. The distribution of the diffusion and perfusion parameters within vessels, ducts, and tumors were extracted from a group of 42 patients with pancreatic adenocarcinoma. Clearly separable combinations of f and D were observed, and receiver operating characteristic analysis was used to determine the optimal cutoff values for an automated segmentation of vessels and ducts to improve lesion detection and delineation on the individual intravoxel incoherent motion-derived maps. Receiver operating characteristic analysis identified f = 0.28 as the cutoff for vessels (Area under the curve (AUC) = 0.901) versus tumor/duct and D = 1.85 µm(2) /ms for separating duct from tumor tissue (AUC = 0.988). These values were incorporated in an automatic segmentation algorithm and then applied to 42 patients. This yielded clearly improved tumor delineation compared to individual intravoxel incoherent motion-derived maps. Furthermore, previous findings that indicated that the f value in pancreatic cancer is strongly reduced compared to healthy pancreatic tissue were reconfirmed.