Simple and Reliable Determination of Intravoxel Incoherent Motion Parameters for the Differential Diagnosis of Head and Neck Tumors

Intravoxel incoherent motion (IVIM) imaging can characterize diffusion and perfusion of normal and diseased tissues, and IVIM parameters are authentically determined by using cumbersome least-squares method. We evaluated a simple technique for the determination of IVIM parameters using geometric analysis of the multiexponential signal decay curve as an alternative to the least-squares method for the diagnosis of head and neck tumors. Pure diffusion coefficients (D), microvascular volume fraction (f), perfusion-related incoherent microcirculation (D), and perfusion parameter that is heavily weighted towards extravascular space (P) were determined geometrically (Geo D, Geo f, and Geo P) or by least-squares method (Fit D, Fit f, and Fit D) in normal structures and 105 head and neck tumors. The IVIM parameters were compared for their levels and diagnostic abilities between the 2 techniques. The IVIM parameters were not able to determine in 14 tumors with the least-squares method alone and in 4 tumors with the geometric and least-squares methods. The geometric IVIM values were significantly different (p<0.001) from Fit values (+2±64% and 7±24% for D and f values, respectively). Geo D and Fit D differentiated between lymphomas and SCCs with similar efficacy (78% and 80% accuracy, respectively). Stepwise approaches using combinations of Geo D and Geo P, Geo D and Geo f, or Fit D and Fit Ddifferentiated between pleomorphic adenomas, Warthin tumors, and malignant salivary gland tumors with the same efficacy (91% accuracy = 21/ 23). However, a stepwise differentiation using Fit D and Fit f was less effective (83% accuracy = 19/23). Considering cumbersome procedures with the least squares method compared with the geometric method, we concluded that the geometric determination of IVIM parameters can be an alternative to least-squares method in the diagnosis of head and neck tumors

Relational and Contractual Governance for Innovation

This is the author accepted manuscript. The final version is available from Springer via the DOI in this recordWhile the early years of Information Technology (IT) and business process outsourcing (BPO) were mainly characterized by a quest for cost savings (Loh and Venkatraman 1992; Lacity and Hirschheim 1993) and a focus on core competences (Quinn and Hilmer 1994), evidence from 2000 onwards suggests that client firms have been seeking added value from outsourcing by accessing suppliers’ competences (e.g. Dyer and Nobeoka 2000; Quinn 2000; Whitley and Willcocks 2011). Mol (2005) argued that “firms are increasingly relying on partnering relationships with outside suppliers that can act as an effective substitute to the internal generation of knowledge and innovation”. Similarly, Linder et al. (2003) and Weeks and Feeny (2008) argued that client firms rely on external suppliers in the search for new ideas. Accepting that innovation is outsourced and offshored, Lewin et al. (2009) studied the determinants driving firms to offshore innovations only to conclude that firms have been entering a global race for talent in which solutions will be sought wherever skills are available. Such observations suggest that innovation may be considered as one of the possible outcomes of outsourcing engagements