Importantly, it has been shown that an evenly distributed sampling of b-values is not necessarily optimal for the biexponential model ( 38, 39). Better estimation of vascular diffusion effects can be made when sampling includes lower b-values (0 1000 s/mm 2) can affect quantification even with the simple ADC model ( 28, 35– 37).Ĭonsequently, quantification of DWI data with the biexponential IVIM fitting model can be numerically nontrivial, and a variety of methods have been developed to address this challenging quantification including optimal sampling ( 38, 39), Bayesian fitting ( 18, 40, 41), maximum likelihood estimation (MLE) ( 33, 42), or fusion bootstrap moves (FBM) ( 43). Questions remain as to whether b-values should be adjusted based on conditions such as tumor type or location. Previous literature has shown that different ranges of b-value selections sensitize the signal to different components of diffusion and can affect the calculation of the diffusion coefficients in different systems for a variety of reasons ( 32– 34). Currently, many DWI protocols for breast cancer subjects calculate ADC values using b-values between 500 and 800 s/mm 2 ( 4, 9, 15, 29– 31). Various approaches have also been used in the selection of diffusion gradients or b-values. For example, oncological studies apply the IVIM model to distinguish hypervascularity and hypercellularity components in malignant neoplasms ( 20– 28) including breast cancer ( 15– 17), particularly in comparison with the weakly perfused and much less structurally dense fibro-glandular tissue. Ideally, use of these approaches should be guided by awareness of the underlying tissue physiology. Many different approaches to DWI analysis have been proposed over the years, motivated by empirical data representation, biophysical modeling, or a hybrid of both. A better understanding of these IVIM coefficients can result in clinically useful biomarkers. Presently, there is a growing need to optimize the precision of these IVIM metrics, comprehend their impact, and identify their relationships with cancer physiology. In the IVIM model, tissue diffusion and pseudo-diffusion coefficients are separated through biexponential analysis. Recently, use of intravoxel incoherent motion (IVIM) ( 10) in DWI has gained attention for its sensitivity to both cellularity and microvascular flow ( 11– 19). Therefore, ADC has become a widely accepted marker of cellularity ( 4– 9). In aggressive tumors, the proliferating cellularity tends to increase restriction by decreasing the extracellular space, and consequently, decrease the apparent diffusion coefficient (ADC). Extensive literature has shown DWI to be useful when characterizing features such as tumor cellularity and tissue organization ( 1– 3). Diffusion-weighted imaging (DWI), which is sensitive to the mobility of water molecules in the tissue environment, is a noninvasive, endogenous-contrast imaging tool that provides imaging biomarkers for cancer diagnosis and characterization ( 1).
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