Intravoxel incoherent motion and non-Gaussian diffusion MR imaging have the potential to give a semi-automatic diagnosis of lesions with high accuracy without using ionizing radiation and injection of radioisotopes or contrast agents. The concept of diffusion magnetic resonance (MR) imaging emerged in the mid-1980s, together with the first images of water diffusion in the human brain, as a way to probe tissue structure at a microscopic scale, although the images were acquired at a millimetric scale. Since then, diffusion MR imaging has become a pillar of modern clinical imaging. Diffusion MR imaging has mainly been used to investigate neurologic disorders. A dramatic application of diffusion MR imaging has been acute brain ischemia, providing patients with the opportunity to receive suitable treatment at a stage when brain tissue might still be salvageable, thus avoiding terrible handicaps. On the other hand, it was found that water diffusion is anisotropic in white matter, because axon membranes limit molecular movement perpendicularly to the nerve fibers. This feature can be exploited to produce stunning maps of the orientation in space of the white matter tracts and brain connections in just a few minutes. Diffusion MR imaging is no...

Since its introduction in the mid-1980s, diffusion magnetic resonance imaging (MRI), which measures the random motion of water molecules in tissues, revealing their microarchitecture, has become a pillar of modern neuroimaging. Its main clinical domain has been the diagnosis of acute brain stroke and neurogical disorders, but it is also used in the body for the detection and management of cancer lesions. It can also produce stunning maps of white matter tracks in the brain, with the potential to aid in the understanding of some psychiatric disorders. However, in order to exploit fully the potential of this method, a deeper understanding of the mechanisms that govern the diffusion of water in tissues is needed.

The purpose of this study was to explore the potential of non-Gaussian diffusion and perfusion magnetic resonance imaging (MRI) using intravoxel incoherent motion (IVIM) MRI for the diagnosis of breast lesions. This study included 26 women with breast lesions. Diffusion-weighted images were acquired using 16 b values up to 2500 s/mm and analyzed using a kurtosis diffusion model (apparent diffusion coefficient [ADC0] and kurtosis [K]) for the diffusion component and IVIM model (perfusion fraction [fIVIM] and pseudodiffusion coefficient [D*]) for the perfusion component. Diagnostic performance of diffusion and perfusion parameters was evaluated from receiver operating characteristic analyses. The ADC0 in malignant lesions was significantly lower than that in benign lesions and normal tissue (P < 0.001, P < 0.001), whereas K was significantly higher (P < 0.05, P < 0.001), as well as fIVIM (P < 0.05, P < 0.01). No significant difference was found in D*. The receiver operating characteristic analysis gave high area under the curve values for ADC0, K, and fIVIM for distinguishing malignant from benign lesions (0.99, 0.85, and 0.82, respectively). The ADC0 allowed benign tumors to be identified with 100% negative predictive value and malignant tumors with 100% sensitivity. The malignant/benign diagnosis thresholds were 1.4 × 10 mm/s as well as 0.6 and 7%, respectively, for ADC0, K, and fIVIM. With a proper methodological framework, IVIM MRI can provide valuable information on tissue structure and microvasculature beneficial for the diagnosis of breast cancer lesions.

Intravoxel incoherent motion and non-Gaussian diffusion parameters through their combination as integrated markers can allow for differentiation of malignant and benign breast lesions with a diagnostic accuracy almost comparable to Breast Imaging and Reporting Data System categories without the need of contrast agents, and these parameters may provide prognostic guidance. PurposeTo investigate the performance of integrated approaches that combined intravoxel incoherent motion (IVIM) and non-Gaussian diffusion parameters compared with the Breast Imaging and Reporting Data System (BI-RADS) to establish multiparameter thresholds scores or probabilities by using Bayesian analysis to distinguish malignant from benign breast lesions and their correlation with molecular prognostic factors.Materials and MethodsBetween May 2013 and March 2015, 411 patients were prospectively enrolled and 199 patients (allocated to training [n = 99] and validation [n = 100] sets) were included in this study. IVIM parameters (flowing blood volume fraction [fIVIM] and pseudodiffusion coefficient [D*]) and non-Gaussian diffusion parameters (theoretical apparent diffusion coefficient [ADC] at b value of 0 sec/mm2 [ADC0] and kurtosis [K]) by using IVIM and kurtosis models were estimated from diffusion-weighted image series (16 b values up to 2500 sec/mm2), as well as a synthetic ADC (sADC) calculated by ...

Recent developments in MR hardware and software have allowed a surge of interest in intravoxel incoherent motion (IVIM) MRI in oncology. Beyond diffusion-weighted imaging (and the standard apparent diffusion coefficient mapping most commonly used clinically), IVIM provides information on tissue microcirculation without the need for contrast agents. In oncology, perfusion-driven IVIM MRI has already shown its potential for the differential diagnosis of malignant and benign tumors, as well as for detecting prognostic biomarkers and treatment monitoring. Current developments in IVIM data processing, and its use as a method of scanning patients who cannot receive contrast agents, are expected to increase further utilization. This paper reviews the current applications, challenges, and future trends of perfusion-driven IVIM in oncology.