Mami Iima

Clinical Intravoxel Incoherent Motion and Diffusion MR Imaging: Past, Present, and Future

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 now also rapidly expanding in oncology, for the detection of malignant lesions and metastases, as well as monitoring. Water diffusion is usually largely decreased in malignant tissues, and body diffusion MR imaging, which does not require any tracer injection, is rapidly becoming a modality of choice to detect, characterize, or even stage malignant lesions, especially for breast or prostate cancer. After a brief summary of the key methodological concepts beyond diffusion MR imaging, this article will give a review of the clinical literature, mainly focusing on current outstanding issues, followed by some innovative proposals for future improvements.

Apparent Diffusion Coefficient as an MR Imaging Biomarker of Low-Risk Ductal Carcinoma in Situ: A Pilot Study

PURPOSE To evaluate the potential of apparent diffusion coefficients (ADCs) obtained at quantitative diffusion-weighted magnetic resonance (MR) imaging of the breast as a biomarker of low-grade ductal carcinoma in situ (DCIS). MATERIALS AND METHODS This retrospective study was approved by an institutional review board, and the requirement to obtain informed consent was waived. Twenty-two women (age range, 36-75 years; mean age, 56.4 years) with pure DCIS (seven with low-grade DCIS, five with intermediate-grade DCIS, and seven with high-grade DCIS) and three with microinvasion underwent breast MR imaging at 1.5 T between January 2008 and November 2010. MR examinations included contrast material-enhanced (gadoteridol) T1-weighted imaging and diffusion-weighted MR imaging with b values of 0 and 1000 sec/mm(2). ADC maps were generated. The distributions of the ADCs in regions of interest covering the lesions were compared among the three grades by using linear mixed-model analysis, and the discriminatory power of the lesion minimum ADC was determined with receiver operating characteristic analysis. RESULTS The mean ADC was 1.42 × 10(-3) mm(2)/sec (95% confidence interval [CI]: 1.31 × 10(-3) mm(2)/sec, 1.54 × 10(-3) mm(2)/sec) for low-grade DCIS, 1.23 × 10(-3) mm(2)/sec (95% CI: 1.10 × 10(-3) mm(2)/sec, 1.36 × 10(-3) mm(2)/sec) for intermediate-grade DCIS, 1.19 × 10(-3) mm(2)/sec (95% CI: 1.08 × 10(-3) mm(2)/sec, 1.30 × 10(-3) mm(2)/sec) for high-grade DCIS, and 2.06 × 10(-3) mm(2)/sec (95% CI: 1.94 × 10(-3) mm(2)/sec, 2.18 × 10(-3) mm(2)/sec) for normal breast tissue. The mean ADCs for high- and intermediate-grade DCIS were significantly lower than that for low-grade DCIS (P < .01 and P = .03, respectively), and the mean ADC for low-grade DCIS was significantly lower than that for normal tissue (P < .001). The lesion minimum ADC for low-grade DCIS was also significantly higher than that for high- and intermediate-grade DCIS (P < .01). A threshold of 1.30 × 10(-3) mm(2)/sec for the minimum ADC in the diagnosis of low-grade DCIS had a specificity of 100% (12 of 12 patients; 95% CI: 73.5%, 100%) and a positive predictive value of 100% (four of four patients; 95% CI: 39.8%, 100%). CONCLUSION These preliminary results suggest that quantitative diffusion-weighted MR imaging could be used to identify patients with low-grade DCIS with very high specificity. If the results of this study are confirmed, this approach could potentially spare those patients from invasive approaches such as mastectomy or axillary lymph node excision.

Diffusion magnetic resonance imaging: What water tells us about biological tissues

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.

Characterization of Glioma Microcirculation and Tissue Features Using Intravoxel Incoherent Motion Magnetic Resonance Imaging in a Rat Brain Model

PurposeOur aim was to investigate the pertinence of diffusion and perfusion magnetic resonance imaging (MRI) parameters obtained at 17.2 T in a 9L glioma rat brain tumor model to evaluate tumor tissue characteristics. Materials and MethodsThe local animal ethics advisory committee approved this study. 9L glioma cells were injected intracerebrally to 14 Fischer rats. The animals were imaged at 7 or 12 days after implantation on a 17.2-T MRI scanner, using 72 different b values (2–3025 s/mm2). The signal attenuation, S/So, was fitted using a kurtosis diffusion model (ADCo and K) and a biexponential diffusion model (fractions ffast and fslow and diffusion coefficients Dfast and Dslow) using b values greater than 300 s/mm2. To bridge the 2 models, an average diffusion coefficient and a biexponential index were estimated from the biexponential model as ADCo and K equivalents, respectively. Intravoxel incoherent motion perfusion–related parameters were obtained from the residual signal at low b values, after the diffusion component has been removed. Diffusion and perfusion maps were generated for each fitted parameter on a pixel-by-pixel basis, and regions of interest were drawn in the tumor and contralateral side to retrieve diffusion and perfusion parameters. All rats were killed and cellularity and vascularity were quantitatively assessed using histology for comparison with diffusion and perfusion parameters. ResultsIntravoxel incoherent motion maps clearly highlighted tumor areas as generally heterogeneous, as confirmed by histology. For diffusion parameters, ADCo and were not significantly different between the tumor and contralateral side, whereas K in the tumor was significantly higher than in contralateral basal ganglia (P < 0.0001), as well as biexponential index (P < 0.001). ADCo and in the tumor at day 7 were significantly higher than at day 12 (P < 0.01 and P < 0.001, respectively). fIVIM in the tumor from the kurtosis diffusion model was significantly higher than in contralateral basal ganglia (P < 0.001). fIVIM in the tumor at day 7 was significantly higher than in the tumor at day 12 (P < 0.0001). There was no significant difference for D* between the tumor and contralateral side (P = 0.06). A significant negative correlation was found between tumor vascularity and fIVIM (P < 0.05) as well as between tumor cell count and (P < 0.01). ConclusionQuantitative non-Gaussian diffusion and perfusion MRI can provide valuable information on microvasculature and tissue structure to improve characterization of brain tumors.

Clinical Performance of 2 Dedicated PET Scanners for Breast Imaging: Initial Evaluation

The purpose of this study was to investigate the diagnostic performance of 2 newly developed dedicated breast PET scanners in patients with known or suspected breast cancer. Methods: Two types of scanner were evaluated, an O-shaped scanner and a C-shaped scanner. The O scanner was designed for imaging patients who were prone, and the C scanner was designed for those patients positioned leaning forward. Sixty-nine women with known or suspected breast carcinoma (80 lesions: 72 invasive carcinomas, 4 noninvasive carcinomas [ductal carcinoma in situ, or DCIS], 1 case of adenomatous ductal hyperplasia, and 3 benign lesions) were enrolled in this study. All patients underwent a conventional whole-body PET/CT scan, followed by breast scanning using both dedicated devices. The diagnostic performance of each scanner was assessed. Results: The maximal diameter of invasive tumors ranged from 4 to 112 mm, with an average of 26 mm. With the O scanner, 62 of 76 malignant lesions (including 3 DCIS) were detected, 5 lesions were not detected, and the remaining 9 lesions were outside the field of view. With the C scanner, 63 of 76 malignant lesions (including 2 DCIS) were detected, 7 lesions were not detected, and the remaining 6 lesions were outside the field of view. The lesion-based sensitivities of the O and C scanners were 82% (62/76) and 83% (63/76), respectively; sensitivities excluding lesions outside the field of view were 93% (62/67) and 90% (63/70), respectively. The sensitivity of conventional PET/CT was 92% (70/76). All lesions outside the field of view were close to the chest wall. The breast-based specificities of the O, C, and conventional scanners were 98% (48/49), 98% (56/57), and 100% (70/70), respectively. Conclusion: Our preliminary study indicates that both dedicated breast PET scanners are clinically feasible and yield reasonably high sensitivity. More detailed information was obtained with these scanners than with the conventional scanner.

Apparent diffusion coefficient as a potential surrogate marker for Ki-67 index in mucinous breast carcinoma

To examine the association between apparent diffusion coefficient (ADC), cellularity, and Ki‐67 index in mucinous breast carcinoma (MBC) compared with invasive carcinoma of no special type (NST). ADCs ability to identify lesions with highly proliferating MBC was also examined.

Reduced-Distortion Diffusion MRI of the Craniovertebral Junction

BACKGROUND AND PURPOSE: CVJ lesion suffers from a high sensitivity to susceptibility and distortion artifacts, which sometimes makes diffusion image difficult to interpret. Our purpose was to evaluate the potential for diffusion MR imaging using RS-EPI compared with SS-EPI in the assessment of the CVJ. MATERIALS AND METHODS: RS-EPI and SS-EPI DTI images were acquired from 10 healthy volunteers using 3T MRI with a 32-channel head coil. For both sequences, the following parameters were used: 1-mm2 in-plane resolution; 3-mm section thickness; TR = 5200 ms; 1 acquisition at b = 0 and 12 different encoding directions at b = 1000 seconds/mm2. The RS-EPI sequence scan time was 9.44 minutes (1 average). The SS-EPI sequence was 9.37 minutes (8 averages). Diffusion tensor calculation and image analysis were performed using DTIStudio software. Diffusion trace images and color-coded fiber orientation maps were evaluated by 2 independent readers for distortion and delineation of fine structure using a semiquantitative scale in selected landmark locations. The absolute distances between the temporal base and the cerebellar contour between the T2-weighted images and the diffusion trace images obtained with RS-EPI and SS-EPI were also compared. RESULTS: The contours of the temporal lobe and cerebellum were better delineated and distortion artifacts were clearly reduced with the RS-EPI sequence. More fine structures were also visible in the brain stem and cerebellum with the RS-EPI sequence. The amount of distortion was significantly reduced with RS-EPI compared with SS-EPI (P < .01). CONCLUSIONS: The RS-EPI DTI sequence was less prone to geometric distortion than the SS-EPI sequence and allowed a better delineation of CVJ internal structure. Although the acquisition time is still relatively long, the RS-EPI appears as a promising approach to perform DTI studies in CVJ lesions, such as brain stem ischemia, neurodegenerative diseases, brain and skull base tumors, or inflammation.

Intravoxel incoherent motion and quantitative non-Gaussian diffusion MR imaging: Evaluation of the diagnostic and prognostic value of several markers of malignant and benign Breast lesions

Purpose To 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 Methods Between 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 using b values of 200 and 1500 (sADC200-1500) and a standard ADC calculated by using b values of 0 and 800 sec/mm2 (ADC0-800). The performance of two diagnostic approaches (combined parameter thresholds and Bayesian analysis) combining IVIM and diffusion parameters was evaluated and compared with BI-RADS performance. The Mann-Whitney U test and a nonparametric multiple comparison test were used to compare their performance to determine benignity or malignancy and as molecular prognostic biomarkers and subtypes of breast cancer. Results Significant differences were found between malignant and benign breast lesions for IVIM and non-Gaussian diffusion parameters (ADC0, K, fIVIM, fIVIM · D*, sADC200-1500, and ADC0-800; P < .05). Sensitivity and specificity for the validation set by radiologists A and B were as follows: sensitivity, 94.7% and 89.5%, and specificity, 75.0% and 79.2% for sADC200-1500, respectively; sensitivity, 94.7% and 96.1%, and specificity, 75.0% and 66.7%, for the combined thresholds approach, respectively; sensitivity, 92.1% and 92.1%, and specificity, 83.3% and 66.7%, for Bayesian analysis, respectively; and sensitivity and specificity, 100% and 79.2%, for BI-RADS, respectively. The significant difference in values of sADC200-1500 in progesterone receptor status (P = .002) was noted. sADC200-1500 was significantly different between histologic subtypes (P = .006). Conclusion Approaches that combined various IVIM and non-Gaussian diffusion MR imaging parameters may provide BI-RADS-equivalent scores almost comparable to BI-RADS categories without the use of contrast agents. Non-Gaussian diffusion parameters also differed by biologic prognostic factors.

Detection of axillary lymph node metastasis with diffusion-weighted MR imaging

The feasibility of detecting axillary lymph node (LN) metastases with diffusion-weighted MR imaging was retrospectively evaluated. The relative ADC (with b values of 0 and 1000 s/mm(2)) between LNs in each axillary space was calculated (n=75). The area, the long and short diameter of the metastatic LNs were compared to those of non-metastatic LNs. The relative ADC value of metastatic LNs was significantly lower than that of non-metastatic LNs (P=.00). The long and short diameter LN diagnostic performance was superior to that of mean ADC and relative ADC (AUC: 0.84, 0.80 versus 0.64, 0.03), suggesting usefulness of diameter over ADC.

Ultrafast dynamic contrast-enhanced mri of the breast using compressed sensing: breast cancer diagnosis based on separate visualization of breast arteries and veins

To evaluate the feasibility of ultrafast dynamic contrast‐enhanced (UF‐DCE) magnetic resonance imaging (MRI) with compressed sensing (CS) for the separate identification of breast arteries/veins and perform temporal evaluations of breast arteries and veins with a focus on the association with ipsilateral cancers.