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We compared the feasibility of quantitative analysis methods using bone SPECT/CT with those using planar bone scans to assess active sacroiliitis.We retrospectively reviewed whole-body bone scans and pelvic bone SPECT/CTs of 8 patients who had clinically confirmed sacroiliitis and enrolled 24 patients without sacroiliitis as references. The volume of interest of each sacroiliac joint, including both the ilium and sacrum, was drawn. Active arthritis zone (AAZ) was defined as the zone of voxels with higher SUV than sacral mean SUV within the VOI of SI joint. Then, the following SPECT/CT quantitative parameters, SUVmax (maximum SUV), SUV50% (mean SUV in highest 50% of SUV), and SUV-AAZ, and the ratio of those values to sacral mean SUV (SUVmax/S, SUV50%/S, SUV-AAZ/S) were calculated. For the planar bone scan, the mean count ratio of SI joint/sacrum (SI/S) was conventionally measured.Most of the SPECT/CT parameters of the sacroiliitis group were significantly higher than the normal group, whereas SI/S of the planar bone scan was not significantly different between the two groups. In receiver operating characteristic curve analysis, SUV-AAZ/S showed the highest AUC of 0.992, followed by SUV50%/S and SUVmax/S. All ratio parameters of the SPECT/CT showed higher AUC values than the SUV parameters of SI joint or SI/S of the planar scan.The quantitative analyses of bone SPECT/CT showed better performance in assessing active sacroiliitis than the planar bone scan. SPECT/CT parameters using the ratio of the SI joint to sacrum showed more favorable results than SUV parameters such as SUVmax, SUV50%, and SUV-AAZ.

Background To facilitate translational drug development for liver fibrosis, preclinical trials need to be run in parallel with clinical research. Liver function estimation by gadoxetate-enhanced dynamic contrast-enhanced MRI (DCE-MRI) is being established in clinical research, but still rarely used in preclinical trials. We aimed to evaluate feasibility of DCE-MRI indices as translatable biomarkers in a liver fibrosis animal model. Methods Liver fibrosis was induced in Sprague-Dawley rats by thioacetamide (200 mg, 150 mg, and saline for the high-dose, low-dose, and control groups, respectively). Subsequently, DCE-MRI was performed to measure: relative liver enhancement at 3-min (RLE-3), RLE-15, initial area-under-the-curve until 3-min (iAUC-3), iAUC-15, and maximum-enhancement (Emax). The correlation coefficients between these MRI indices and the histologic collagen area, indocyanine green retention at 15-min (ICG-R15), and shear wave elastography (SWE) were calculated. Diagnostic performance to diagnose liver fibrosis was also evaluated by receiver-operating-characteristic (ROC) analysis. Results Animal model was successful in that the collagen area of the liver was the largest in the high-dose group, followed by the low-dose group and control group. The correlation between the DCE-MRI indices and collagen area was high for iAUC-15, Emax, iAUC-3, and RLE-3 but moderate for RLE-15 (r, − 0.81, − 0.81, − 0.78, − 0.80, and − 0.51, respectively). The DCE-MRI indices showed moderate correlation with ICG-R15: the highest for iAUC-15, followed by iAUC-3, RLE-3, Emax, and RLE-15 (r, − 0.65, − 0.63, − 0.62, − 0.58, and − 0.56, respectively). The correlation coefficients between DCE-MRI indices and SWE ranged from − 0.59 to − 0.28. The diagnostic accuracy of RLE-3, iAUC-3, iAUC-15, and Emax was 100% (AUROC 1.000), whereas those of RLE-15 and SWE were relatively low (AUROC 0.777, 0.848, respectively). Conclusion Among the gadoxetate-enhanced DCE-MRI indices, iAUC-15 and iAUC-3 might be bidirectional translatable biomarkers between preclinical and clinical research for evaluating histopathologic liver fibrosis and physiologic liver functions in a non-invasive manner.

To develop and validate prediction models to differentiate acute and chronic vertebral compression fractures based on radiologic and radiomic features on CT.This study included acute and chronic compression fractures in patients who underwent both spine CT and MRI examinations. For each fractured vertebra, three CT findings ([1] cortical disruption, [2] hypoattenuating cleft or sclerotic line, and [3] relative bone marrow attenuation) were assessed by two radiologists. A radiomic score was built from 280 radiomic features extracted from non-contrast-enhanced CT images. Weighted multivariable logistic regression analysis was performed to build a radiologic model based on CT findings and an integrated model combining the radiomic score and CT findings. Model performance was evaluated and compared. Models were externally validated using an independent test cohort.A total to 238 fractures (159 acute and 79 chronic) in 122 patients and 58 fractures (39 acute and 19 chronic) in 32 patients were included in the training and test cohorts, respectively. The AUC of the radiomic score was 0.95 in the training and 0.93 in the test cohorts. The AUC of the radiologic model was 0.89 in the training and 0.83 in the test cohorts. The discriminatory performance of the integrated model was significantly higher than the radiologic model in both the training (AUC, 0.97; p0.01) and the test (AUC, 0.95; p=0.01) cohorts.Combining radiomics with radiologic findings significantly improved the performance of CT in determining the acuity of vertebral compression fractures.

We aimed to develop and test a deep learning algorithm (DLA) for fully automated measurement of the volume and signal intensity (SI) of the liver and spleen using gadoxetic acid-enhanced hepatobiliary phase (HBP)-magnetic resonance imaging (MRI) and to evaluate the clinical utility of DLA-assisted assessment of functional liver capacity.The DLA was developed using HBP-MRI data from 1014 patients. Using an independent test dataset (110 internal and 90 external MRI data), the segmentation performance of the DLA was measured using the Dice similarity score (DSS), and the agreement between the DLA and the ground truth for the volume and SI measurements was assessed with a Bland-Altman 95% limit of agreement (LOA). In 276 separate patients (male:female, 191:85; mean age ± standard deviation, 40 ± 15 years) who underwent hepatic resection, we evaluated the correlations between various DLA-based MRI indices, including liver volume normalized by body surface area (LVIn the test dataset, the mean DSS was 0.977 for liver segmentation and 0.946 for spleen segmentation. The Bland-Altman 95% LOAs were 0.08% ± 3.70% for the liver volume, 0.20% ± 7.89% for the spleen volume, -0.02% ± 1.28% for the liver SI, and -0.01% ± 1.70% for the spleen SI. Among DLA-based MRI indices, aLSSR × LVOur DLA can accurately measure the volume and SI of the liver and spleen and may be useful for assessing functional liver capacity using gadoxetic acid-enhanced HBP-MRI.

Purpose To develop and validate a radiomics-based model for staging liver fibrosis by using gadoxetic acid-enhanced hepatobiliary phase MRI. Materials and Methods In this retrospective study, 436 patients (mean age, 51 years; age range, 18-86 years; 319 men [mean age, 51 years; age range, 18-86 years]; 117 women [mean age, 50 years; age range, 18-79 years]) with pathologic analysis-proven liver fibrosis who underwent gadoxetic acid-enhanced MRI from June 2015 to December 2016 were randomized in a three-to-one ratio into development (n = 329) and test (n = 107) cohorts, respectively. In the development cohort, a model was developed to calculate radiomics fibrosis index (RFI) by using logistic regression with elastic net regularization to differentiate stage F3-F4 from stage F0-F2. Optimal RFI cutoffs to diagnose clinically significant fibrosis (stage F2-F4), advanced fibrosis (stage F3-F4), and cirrhosis (stage F4) were determined by receiver operating characteristic curve analysis. In the test cohort, the diagnostic performance of RFI was compared with that of normalized liver enhancement, aspartate transaminase-to-platelet ratio index (APRI), and fibrosis-4 index by using the Obuchowski index. Results In the test cohort, RFI (Obuchowski index, 0.86) significantly outperformed normalized liver enhancement (Obuchowski index, 0.77; P.03), APRI (Obuchowski index, 0.60; P.001), and fibrosis-4 index (Obuchowski index, 0.62; P.001) for staging liver fibrosis. By using the cutoffs, RFI had sensitivities and specificities as follows: 81% (95% confidence interval: 71%, 89%) and 78% (95% confidence interval: 63%, 89%) for diagnosing stage F2-F4, respectively; 79% (95% confidence interval: 67%, 88%) and 82% (95% confidence interval: 69%, 91%), respectively, for diagnosing stage F3-F4; and 92% (95% confidence interval: 79%, 98%) and 75% (95% confidence interval: 62%, 83%), respectively, for diagnosing stage F4. Conclusion Radiomics analysis of gadoxetic acid-enhanced hepatobiliary phase images allows for accurate diagnosis of liver fibrosis. © RSNA, 2018 Online supplemental material is available for this article.

Oxidative stress is a key mediator of neuronal death in acute brain injuries, such as epilepsy, trauma, and stroke. Although it is accompanied by diverse cellular changes, increases in levels of intracellular zinc ion (Zn2+) and calcium ion (Ca2+) may play a critical causative role in oxidative neuronal death. However, the mechanistic link between Zn2+ and Ca2+ dyshomeostasis in neurons during oxidative stress is not well-understood. Here, we show that the exposure of cortical neurons to H2O2 led to a zinc-triggered calcium influx, which resulted in neuronal death. The cyclin-dependent kinase inhibitor, NU6027, inhibited H2O2-induced Ca2+ increases and subsequent cell death in cortical neurons, without affecting the early increase in Zn2+. Therefore, we attempted to identify the zinc-regulated Ca2+ pathway that was inhibited by NU6027. The expression profile in cortical neurons identified transient receptor potential cation channel 5 (TRPC5) as a candidate that is known to involve in the generation of epileptiform burst firing and epileptic neuronal death (Phelan KD et al. 2012a; Phelan KD et al. 2013b). NU6027 inhibited basal and zinc-augmented TRPC5 currents in TRPC5-overexpressing HEK293 cells. Consistently, cortical neurons from TRPC5 knockout mice were highly resistant to H2O2-induced death. Moreover, NU6027 is neuroprotective in kainate-treated epileptic rats. Our results demonstrate that TRPC5 is a novel therapeutic target against oxidative neuronal injury in prolonged seizures and that NU6027 is a potent inhibitor of TRPC5.

Purpose To evaluate the robustness of MR transverse relaxation times of trabecular bone from spin-echo and gradient-echo acquisitions at multiple spatial resolutions of 7 T. Methods The effects of MRI resolutions to T2 and T2* of trabecular bone were numerically evaluated by Monte Carlo simulations. T2 , T2*, and trabecular structural indices from multislice multi-echo and UTE acquisitions were measured in defatted human distal femoral condyles on a 7 T scanner. Reference structural indices were extracted from high-resolution microcomputed tomography images. For bovine knee trabecular samples with intact bone marrow, T2 and T2* were measured by degrading spatial resolutions on a 7 T system. Results In the defatted trabecular experiment, both T2 and T2* values showed strong ( |r| > 0.80) correlations with trabecular spacing and number, at a high spatial resolution of 125 µm3 . The correlations for MR image-segmentation-derived structural indices were significantly degraded ( |r| 0.85). In the bovine trabecular experiments with intact marrow, low-resolution (approximately 1 mm3 , 2 minutes) T2 values did not shorten ( |r| > 0.95 with respect to approximately 0.4 mm3 , 11 minutes) and maintained consistent correlations ( |r| > 0.70) with respect to trabecular spacing (turbo spin echo, 22.5 minutes). Conclusion T2 measurements of trabeculae at 7 T are robust with degrading spatial resolution and may be preferable in assessing trabecular spacing index with reduced scan time, when high-resolution 3D micro-MRI is difficult to obtain.

Radiomics and deep learning have recently gained attention in the imaging assessment of various liver diseases. Recent research has demonstrated the potential utility of radiomics and deep learning in staging liver fibroses, detecting portal hypertension, characterizing focal hepatic lesions, prognosticating malignant hepatic tumors, and segmenting the liver and liver tumors. In this review, we outline the basic technical aspects of radiomics and deep learning and summarize recent investigations of the application of these techniques in liver disease.

Coordinated expression of guidance molecules and their signal transduction are critical for correct brain wiring. Previous studies have shown that phospholipase C gamma1 (PLCγ1), a signal transducer of receptor tyrosine kinases, plays a specific role in the regulation of neuronal cell morphology and motility in vitro . However, several questions remain regarding the extracellular stimulus that triggers PLCγ1 signaling and the exact role PLCγ1 plays in nervous system development. Here, we demonstrate that PLCγ1 mediates axonal guidance through a netrin‐1/deleted in colorectal cancer (DCC) complex. Netrin‐1/DCC activates PLCγ1 through Src kinase to induce actin cytoskeleton rearrangement. Neuronal progenitor‐specific knockout of Plcg1 in mice causes axon guidance defects in the dorsal part of the mesencephalon during embryogenesis. Adult Plcg1 ‐deficient mice exhibit structural alterations in the corpus callosum, substantia innominata, and olfactory tubercle. These results suggest that PLCγ1 plays an important role in the correct development of white matter structure by mediating netrin‐1/DCC signaling.

Oxidative stress is a key mediator of neuronal death in acute brain injuries, such as epilepsy, trauma, and stroke. Although it is accompanied by diverse cellular changes, increases in levels of intracellular zinc ion (Zn

OBJECTIVE To identify potential imaging biomarkers of Alzheimer's disease by combining brain cortical thickness (CThk) and functional connectivity and to validate this model's diagnostic accuracy in a validation set. MATERIALS AND METHODS Data from 98 subjects was retrospectively reviewed, including a study set (n = 63) and a validation set from the Alzheimer's Disease Neuroimaging Initiative (n = 35). From each subject, data for CThk and functional connectivity of the default mode network was extracted from structural T1-weighted and resting-state functional magnetic resonance imaging. Cortical regions with significant differences between patients and healthy controls in the correlation of CThk and functional connectivity were identified in the study set. The diagnostic accuracy of functional connectivity measures combined with CThk in the identified regions was evaluated against that in the medial temporal lobes using the validation set and application of a support vector machine. RESULTS Group-wise differences in the correlation of CThk and default mode network functional connectivity were identified in the superior temporal (p < 0.001) and supramarginal gyrus (p = 0.007) of the left cerebral hemisphere. Default mode network functional connectivity combined with the CThk of those two regions were more accurate than that combined with the CThk of both medial temporal lobes (91.7% vs. 75%). CONCLUSION Combining functional information with CThk of the superior temporal and supramarginal gyri in the left cerebral hemisphere improves diagnostic accuracy, making it a potential imaging biomarker for Alzheimer's disease.

Objective To simulate the B1-inhomogeneity-induced variation of pharmacokinetic parameters on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Materials and Methods B1-inhomogeneity-induced flip angle (FA) variation was estimated in a phantom study. Monte Carlo simulation was performed to assess the FA-deviation-induced measurement error of the pre-contrast R1, contrast-enhancement ratio, Gd-concentration, and two-compartment pharmacokinetic parameters (Ktrans, ve, and vp). Results B1-inhomogeneity resulted in −23–5% fluctuations (95% confidence interval [CI] of % error) of FA. The 95% CIs of FA-dependent % errors in the gray matter and blood were as follows: −16.7–61.8% and −16.7–61.8% for the pre-contrast R1, −1.0–0.3% and −5.2–1.3% for the contrast-enhancement ratio, and −14.2–58.1% and −14.1–57.8% for the Gd-concentration, respectively. These resulted in −43.1–48.4% error for Ktrans, −32.3–48.6% error for the ve, and −43.2–48.6% error for vp. The pre-contrast R1 was more vulnerable to FA error than the contrast-enhancement ratio, and was therefore a significant cause of the Gd-concentration error. For example, a −10% FA error led to a 23.6% deviation in the pre-contrast R1, −0.4% in the contrast-enhancement ratio, and 23.6% in the Gd-concentration. In a simulated condition with a 3% FA error in a target lesion and a −10% FA error in a feeding vessel, the % errors of the pharmacokinetic parameters were −23.7% for Ktrans, −23.7% for ve, and −23.7% for vp. Conclusion Even a small degree of B1-inhomogeneity can cause a significant error in the measurement of pharmacokinetic parameters on DCE-MRI, while the vulnerability of the pre-contrast R1 calculations to FA deviations is a significant cause of the miscalculation.

Purpose To investigate the feasibility of diffusion-weighted imaging (DWI) in the differentiation of metastatic from nonmetastatic lymph nodes. Materials and Methods In 125 patients who underwent lymph node dissection for uterine cervical cancer, DWI was performed at b value of 0 and 1000 s/mm2. By referring to the surgical maps of the pelvic lymph nodes, the apparent diffusion coefficient (ADC) was compared in the metastatic and nonmetastatic lymph nodes, and receiver-operating-characteristics analysis was performed to evaluate the diagnostic performance of the ADC in differentiating metastatic from nonmetastatic lymph nodes. Results The ADC were significantly lower in the metastatic lymph nodes (0.7651 × 10−3 mm2/s ± 0.1137) than in the nonmetastatic lymph nodes (1.0021 × 10−3 mm2/s ± 0.1859; P < 0.001). The area-under-the-curve of ADC for differentiating metastatic from nonmetastatic lymph nodes, was 0.902. The sensitivity and specificity of ADC for differentiating metastatic from nonmetastatic lymph nodes, were 87% for the ADC and 80%, respectively. Conclusion DWI is feasible for differentiating metastatic from nonmetastatic lymph nodes in patients with uterine cervical cancer. J. Magn. Reson. Imaging 2008;28:714–719. © 2008 Wiley-Liss, Inc.

Objective To simulate the B1-inhomogeneity-induced variation of pharmacokinetic parameters on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Materials and methods B1-inhomogeneity-induced flip angle (FA) variation was estimated in a phantom study. Monte Carlo simulation was performed to assess the FA-deviation-induced measurement error of the pre-contrast R1, contrast-enhancement ratio, Gd-concentration, and two-compartment pharmacokinetic parameters (Ktrans, ve, and vp). Results B1-inhomogeneity resulted in -23-5% fluctuations (95% confidence interval [CI] of % error) of FA. The 95% CIs of FA-dependent % errors in the gray matter and blood were as follows: -16.7-61.8% and -16.7-61.8% for the pre-contrast R1, -1.0-0.3% and -5.2-1.3% for the contrast-enhancement ratio, and -14.2-58.1% and -14.1-57.8% for the Gd-concentration, respectively. These resulted in -43.1-48.4% error for Ktrans, -32.3-48.6% error for the ve, and -43.2-48.6% error for vp. The pre-contrast R1 was more vulnerable to FA error than the contrast-enhancement ratio, and was therefore a significant cause of the Gd-concentration error. For example, a -10% FA error led to a 23.6% deviation in the pre-contrast R1, -0.4% in the contrast-enhancement ratio, and 23.6% in the Gd-concentration. In a simulated condition with a 3% FA error in a target lesion and a -10% FA error in a feeding vessel, the % errors of the pharmacokinetic parameters were -23.7% for Ktrans, -23.7% for ve, and -23.7% for vp. Conclusion Even a small degree of B1-inhomogeneity can cause a significant error in the measurement of pharmacokinetic parameters on DCE-MRI, while the vulnerability of the pre-contrast R1 calculations to FA deviations is a significant cause of the miscalculation.

The purpose of this article is to quantitatively assess the rate of resolution of clot burden detected on pulmonary CT angiography (CTA) in patients with acute pulmonary embolism (PE).We evaluated 111 consecutive patients (55 men and 56 women) in a retrospective cohort who were diagnosed with PE by pulmonary CTA and had at least one follow-up pulmonary CTA within 1 year. Two radiologists in consensus measured the volume of each clot using a semiautomated quantification program. Semiquantitative measures of clot burden were also computed. The resolution rates of the total clot volume, as well as clot volumes of the central (main and lobar) and peripheral vessels (segmental and subsegmental), were analyzed.The mean (± SD) clot volume per study was 3403.3 ± 6505.6 mm(3) at baseline and 531.6 ± 2383.5 mm(3) at the follow-up pulmonary CTA. Overall, 85 patients (77% ) showed complete resolution at the follow-up pulmonary CTA. Complete resolution was seen in 17 of 30 patients (56.7%) at a follow-up interval of 1-14 days, in 24 of 31 patients (77.4%) at 29-90 days, and in 32 of 34 patients (94.1%) after 90 days. The total clot volume measurements summed for all patients decreased by 78% (central clot, 69.4%; peripheral clot, 86.0%) at 14 days, by 96.6% (central clot, 93.4%; peripheral clot, 100%) at 90 days, and by 97.7% (central clot, 95.9%; peripheral clot, 100%) after 90 days.Clot burden resolved completely in 77% of patients during the follow-up period. Our analysis showed that clots resolved faster in the peripheral arteries than in the central pulmonary arteries.

To evaluate the performance of a semi-automated method for the segmentation of individual renal cysts from magnetic resonance (MR) images in patients with autosomal dominant polycystic kidney disease (ADPKD).This semi-automated method was based on a morphologic watershed technique with shape-detection level set for segmentation of renal cysts from MR images. T2-weighted MR image sets of 40 kidneys were selected from 20 patients with mild to moderate renal cyst burden (kidney volume1500 ml) in the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP). The performance of the semi-automated method was assessed in terms of two reference metrics in each kidney: the total number of cysts measured by manual counting and the total volume of cysts measured with a region-based thresholding method. The proposed and reference measurements were compared using intraclass correlation coefficient (ICC) and Bland-Altman analysis.Individual renal cysts were successfully segmented with the semi-automated method in all 20 cases. The total number of cysts in each kidney measured with the two methods correlated well (ICC, 0.99), with a very small relative bias (0.3% increase with the semi-automated method; limits of agreement, 15.2% reduction to 17.2% increase). The total volume of cysts measured using both methods also correlated well (ICC, 1.00), with a small relative bias of10% (9.0% decrease in the semi-automated method; limits of agreement, 17.1% increase to 43.3% decrease).This semi-automated method to segment individual renal cysts in ADPKD kidneys provides a quantitative indicator of severity in early and moderate stages of the disease.

Purpose: To evaluate the effect of diffusion-weighted imaging (DWI) methods, apparent diffusion coefficient (ADC) calculation methods, and selection of b-values on the ADCs and the measurement reproducibility of malignant hepatic tumors. Materials and Methods: Nineteen patients with pathologically confirmed malignant hepatic tumors underwent breath-hold DWI (b-values = 0, 50, 500 s/mm2) and respiratory-triggered DWI (0, 50, 300, 500, 1000 s/mm2) twice on a 1.5 T magnetic resonance imaging (MRI) scanner. ADCs were calculated using a two b-value and/or a multiple b-value method. The reproducibility of the ADC measurements was evaluated from the intraclass correlation coefficients (ICCs) and the 95% Bland–Altman limit-of-agreement (LOA). Results: The ADCs were different according to the DWI methods (P = 0.040–0.282), ADC calculation methods (P = 0.003–0.825), and the choice of b-values (P < 0.001). The ADC tended to be more reproducible with use of breath-hold DWI (ICC: 0.898–0.933; LOA, 18.8%–24.0%) than respiratory-triggered DWI (ICC: 0.684–0.928; LOA, 15.0%–31.9%) (P = 0.008–0.122). For respiratory-triggered DWI, the multiple b-value method using five b-values had better reproducibility than the two b-value method for measurement of ADC (P = 0.009–0.221). Conclusion: The DWI method, ADC calculation method, and selection of b-values potentially influence the ADCs and the reproducibility of malignant hepatic tumors. ADCs calculated from breath-hold DWI are more reproducible than from respiratory-triggered DWI. A multiple b-value method may improve the reproducibility of respiratory-triggered DWI. J. Magn. Reson. Imaging 2012;36:1131–1138. © 2012 Wiley Periodicals, Inc.

Purpose: To evaluate the feasibility of flow-sensitive alternating inversion recovery (FAIR) for measuring blood flow in tumor models. Materials and Methods: In eight mice tumor models, FAIR and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was performed. The reliability for measuring blood flow on FAIR was evaluated using the coefficient of variation of blood flow on psoas muscle. Three regions of interest (ROIs) were drawn in the peripheral, intermediate, and central portions within each tumor. The location of ROI was the same on FAIR and DCE-MR images. The correlation between the blood flow on FAIR and perfusion-related parameters on DCE-MRI was evaluated using the Pearson correlation coefficient. Results: The coefficient of variation for measuring blood flow was 9.8%. Blood flow on FAIR showed a strong correlation with Kep (r = 0.77), percent relative enhancement (r = 0.73), and percent enhancement ratio (r = 0.81). The mean values of blood flow (mL/100 g/min) (358 vs. 207), Kep (sec−1) (7.46 vs. 1.31), percent relative enhancement (179% vs. 134%), and percent enhancement ratio (42% vs. 26%) were greater in the peripheral portion than in the central portion (P < 0.01). Conclusion: As blood flow measurement on FAIR is reliable and closely related with that on DCE-MR, FAIR is feasible for measuring tumor blood flow. J. Magn. Reson. Imaging 2010;32:738–744. © 2010 Wiley-Liss, Inc.

Purpose To evaluate diagnostic performance of apparent diffusion coefficient (ADC) in differentiating prostate cancer from noncancerous tissue according to anatomical region. Materials and Methods In 47 patients with diffusion-weighted-MR (b-value, 0 and 1000 sec/mm2) on a 1.5 T unit, ADCs were measured in prostate cancer and in three noncancerous tissues (transitional zone, peripheral zone, and prostatic base). Diagnostic performance of ADC for differentiating cancer from noncancerous tissue was evaluated using receiver-operating-characteristics (ROC) analysis. Results Mean ADC of prostate cancer (0.963 × 10−3 mm2/s) was lower than those of all noncancerous tissues (P < 0.001). In noncancerous tissue, ADC differed according to anatomical region (peripheral zone, 1.572 × 10−3 mm2/sec; transitional zone, 1.441 × 10−3 mm2/sec; prostatic base, 1.146 × 10−3 mm2/sec) (P < 0.01). ADC was lower in prostate cancer than in all noncancerous tissues in 34 (72%) patients. Area under the ROC curve for differentiating cancer from noncancerous tissue in prostatic base (0.725) was less than those for differentiating cancer from noncancerous tissue in peripheral (0.952) and transitional zones (0.906) (P < 0.05). Sensitivity differed according to anatomical region (peripheral zone, 98%; transitional zone, 82%; prostatic base, 66%) (P < 0.05). Conclusion Variable ADC in noncancerous tissue according to anatomical region may limit diagnostic performance of ADC for cancer detection. J. Magn. Reson. Imaging 2008. © 2008 Wiley-Liss, Inc.