Diagnosis of cirrhosis with intravoxel incoherent motion diffusion MRI and dynamic contrast‐enhanced MRI alone and in combination: Preliminary experience

Purpose:

To report our preliminary experience with the use of intravoxel incoherent motion (IVIM) diffusion‐weighted magnetic resonance imaging (DW‐MRI) and dynamic contrast‐enhanced (DCE)‐MRI alone and in combination for the diagnosis of liver cirrhosis.

Materials and Methods:

Thirty subjects (16 with noncirrhotic liver, 14 with cirrhosis) were prospectively assessed with IVIM DW‐MRI (n = 27) and DCE‐MRI (n = 20). IVIM parameters included perfusion fraction (PF), pseudodiffusion coefficient (D*), true diffusion coefficient (D), and apparent diffusion coefficient (ADC). Model‐free DCE‐MR parameters included time to peak (TTP), upslope, and initial area under the curve at 60 seconds (IAUC60). A dual input single compartmental perfusion model yielded arterial flow (Fa), portal venous flow (Fp), arterial fraction (ART), mean transit time (MTT), and distribution volume (DV). The diagnostic performances for diagnosis of cirrhosis were evaluated for each modality alone and in combination using logistic regression and receiver operating characteristic analyses. IVIM and DCE‐MR parameters were compared using a generalized estimating equations model.

Results:

PF, D*, D, and ADC values were significantly lower in cirrhosis (P = 0.0056–0.0377), whereas TTP, DV, and MTT were significantly increased in cirrhosis (P = 0.0006–0.0154). There was no correlation between IVIM‐ and DCE‐MRI parameters. The highest Az (areas under the curves) values were observed for ADC (0.808) and TTP‐DV (0.952 for each). The combination of ADC with DV and TTP provided 84.6% sensitivity and 100% specificity for diagnosis of cirrhosis.

Conclusion:

The combination of DW‐MRI and DCE‐MRI provides an accurate diagnosis of cirrhosis. J. Magn. Reson. Imaging 2010;31:589–600. © 2010 Wiley‐Liss, Inc.     

Predicting survival and early clinical response to primary chemotherapy for patients with locally advanced breast cancer using DCE‐MRI

Purpose

To evaluate dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) as a tool for early prediction of response to neoadjuvant chemotherapy (NAC) and 5‐year survival in patients with locally advanced breast cancer.

Materials and Methods

DCE‐MRI was performed in patients scheduled for NAC (n = 24) before and after the first treatment cycle. Clinical response was evaluated after completed NAC. Relative signal intensity (RSI) and area under the curve (AUC) were calculated from the DCE‐curves and compared to clinical treatment response. Kohonen and probabilistic neural network (KNN and PNN) analysis were used to predict 5‐year survival.

Results

RSI and AUC were reduced after only one cycle of NAC in patients with clinical treatment response (P = 0.02 and P = 0.08). The mean and 10th percentile RSI values before NAC were significantly lower in patients surviving more than 5 years compared to nonsurvivors (P = 0.05 and 0.02). This relationship was confirmed using KNN, which demonstrated that patients who remained alive clustered in separate regions from those that died. Calibration of contrast enhancement curves by PNN for patient survival at 5 years yielded sensitivity and specificity for training and testing ranging from 80%–92%.

Conclusion

DCE‐MRI in locally advanced breast cancer has the potential to predict 5‐year survival in a small patient cohort. In addition, changes in tumor vascularization after one cycle of NAC can be assessed. J. Magn. Reson. Imaging 2009;29:1300–1307. © 2009 Wiley‐Liss, Inc.     

Multiparametric MRI for prostate cancer localization in correlation to whole‐mount histopathology

Purpose:

To prospectively evaluate multiparametric magnetic resonance imaging (MRI) for accurate localization of intraprostatic tumor nodules, with whole‐mount histopathology as the gold standard.

Materials and Methods:

Seventy‐five patients with biopsy‐proven, intermediate, and high‐risk prostate cancer underwent preoperative T2‐weighted (T2w), dynamic contrast‐enhanced (DCE) and diffusion‐weighted (DW) MRI at 1.5T. Localization of suspicious lesions was recorded for each of 24 standardized regions of interest on the different MR images and correlated with the pathologic findings. Generalized estimating equations (GEE) were used to estimate the sensitivity, specificity, accuracy, positive, and negative predictive value for every MRI modality, as well as to evaluate the influence of Gleason score and pT‐stage. Tumor volume measurements on histopathological specimens were correlated with those on the different MR modalities (Pearson correlation).

Results:

DW MRI had the highest sensitivity for tumor localization (31.1% vs. 27.4% vs. 44.5% for T2w, DCE, and DW MRI, respectively; P < 0.005), with more aggressive or more advanced tumors being more easily detected with this imaging modality. Significantly higher sensitivity values were obtained for the combination of T2w, DCE, and DW MRI (58.8%) as compared to each modality alone or any combination of two modalities (P < 0.0001). Tumor volume can most accurately be assessed by means of DW MRI (r = 0.75; P < 0.0001).

Conclusion:

Combining T2w, DCE, and DW imaging significantly improves prostate cancer localization. J. Magn. Reson. Imaging 2013;37:1392–1401. © 2012 Wiley Periodicals, Inc.     

Diffusion‐weighted MRI for monitoring tumor response to photodynamic therapy

Purpose:

To examine diffusion‐weighted MRI (DW‐MRI) for assessing the early tumor response to photodynamic therapy (PDT).

Materials and Methods:

Subcutaneous tumor xenografts of human prostate cancer cells (CWR22) were initiated in athymic nude mice. A second‐generation photosensitizer, Pc 4, was delivered to each animal by a tail vein injection 48 h before laser illumination. A dedicated high‐field (9.4 Tesla) small animal MR scanner was used to acquire diffusion‐weighted MR images pre‐PDT and 24 h after the treatment. DW‐MRI and apparent diffusion coefficients (ADC) were analyzed for 24 treated and 5 control mice with photosensitizer only or laser light only. Tumor size, prostate specific antigen (PSA) level, and tumor histology were obtained at different time points to examine the treatment effect.

Results:

Treated mice showed significant tumor size shrinkage and decrease of PSA level within 7 days after the treatment. The average ADC of the 24 treated tumors increased 24 h after PDT (P < 0.001) comparing with pre‐PDT. The average ADC was 0.511 ± 0.119 × 10^?3 mm²/s pre‐PDT and 0.754 ± 0.181 × 10^?3 mm²/s 24 h after the PDT. There is no significant difference in ADC values pre‐PDT and 24 h after PDT in the control tumors (P = 0.20).

Conclusion:

The change of tumor ADC values measured by DW‐MRI may provide a noninvasive imaging marker for monitoring tumor response to Pc 4‐PDT as early as 24 h. J. Magn. Reson. Imaging 2010;32:409–417. © 2010 Wiley‐Liss, Inc.

     

Time course study on the effects of iodinated contrast medium on intrarenal water transport function using diffusion-weighted MRI

Purpose:

To assess the effects of intravenous‐injected iodinated contrast medium (CM) on intrarenal water diffusion using noninvasive diffusion‐weighted MRI (DW‐MRI).

Materials and Methods:

Ten New Zealand White rabbits were randomized to receive a 6 mL/kg body weight intravenous injection of clinically used iopamidol‐370 (n = 7) or an equivalent amount of 0.9% physiological saline (n = 3). A sequential DW‐MRI was performed to estimate the intrarenal apparent diffusion coefficient (ADC) at 24 h before and 1 h, 24 h, 48 h, and 72 h after administration.

Results:

Iopamidol produced a progressive ADC reduction in inner stripes of the renal outer medulla (IS) by 13.92% (P = 0.05) at 1 h, 17.52% (P = 0.02) at 24 h, 20.23% (P = 0.01) at 48 h and 16.31% (P = 0.04) at 72 h after injection. Cortical ADC was decreased by 14.14% (P = 0.01) at 48 h and 14.12% (P = 0.01) at 72 h after injection. Iopamidol produced slight decrease of ADCs in outer stripes of the outer medulla (OS) and inner medulla (IM) of kidney but without statistical difference. In control group, no significant ADC changes was observed in each anatomic compartment due to saline injection (P > 0.05).

Conclusion:

As demonstrated by DW‐MRI, intravenous iopamidol injection resulted in a successive reduction of intrarenal water diffusion, particularly in IS of kidney. This MR technique may be used as a noninvasive tool to perform a time course study of the pathogenesis associated with contrast‐induced nephropathy (CIN). J. Magn. Reson. Imaging 2012;35:1139‐1144. © 2012 Wiley Periodicals, Inc.     

Optimization of b value in diffusion-weighted MRI for characterization of benign and malignant gynecological lesions

Purpose:

To explore the optimal b value in diffusion‐weighted (DW)‐MRI for differentiation of benign and malignant gynecological lesions.

Materials and Methods:

Consecutive 58 patients (66 lesions) with pathologically confirmed diagnosis of gynecological disease were included in the study. Routine pelvic MRI sequences were used for defining the lesions and reviewed independently for benignity/ malignity. Single‐shot echoplanar imaging (SH‐EPI) DW‐MRI with eight b values and nine apparent diffusion coefficient (ADC) maps were obtained. The lesions were analyzed qualitatively on DW‐MRI for benignity/malignity on a five‐point‐scale and quantitatively by measurement of apparent diffusion coefficient (ADC) values. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic accuracy of ADC values for differentiating between benign and malignant lesions. Pathology results were the reference standard.

Results:

Differentiation between benign and malignant gynecological lesions using visual scoring was found to be successful with b values of 600, 800, or 1000 s/mm². The mean ADC values of malignant lesions were significantly lower than those of benign lesions for all b value (P < 0.005). The ADCs with b = 0 and 600, 0 and 1000 s/mm², 0, 600, 800 and 1000 s/mm², and all b values were more effective for distinguishing malignant from benign gynecological lesions (Az = 0.851, 0.847, 0.848, 0.849, respectively). Using ADC with b = 0, 600, 800, and 1000 s/mm², a threshold value of 1.20 × 10^?3 mm²/s permitted this distinction with a sensitivity of 83%, a specificity of 81%.

Conclusion:

DW‐MRI is an important method, and the optimal b values are between 600 and 1000 s/mm² for differentiation between benign and malignant gynecological lesions. J. Magn. Reson. Imaging 2012;35:650‐659. © 2011 Wiley Periodicals, Inc.

     

Differentiation of malignant and benign breast lesions using magnetization transfer imaging and dynamic contrast‐enhanced MRI

Purpose:

To evaluate feasibility of using magnetization transfer ratio (MTR) in conjunction with dynamic contrast‐enhanced MRI (DCE‐MRI) for differentiation of benign and malignant breast lesions at 3 Tesla.

Materials and Methods:

This prospective study was IRB and HIPAA compliant. DCE‐MRI scans followed by MT imaging were performed on 41 patients. Regions of interest (ROIs) were drawn on co‐registered MTR and DCE postcontrast images for breast structures, including benign lesions (BL) and malignant lesions (ML). Initial enhancement ratio (IER) and delayed enhancement ratio (DER) were calculated, as were normalized MTR, DER, and IER (NMTR, NDER, NIER) values. Diagnostic accuracy analysis was performed.

Results:

Mean MTR in ML was lower than in BL (P < 0.05); mean DER and mean IER in ML were significantly higher than in BL (P < 0.01, P < 0.001). NMTR, NDER, and NIER were significantly lower in ML versus BL (P < 0.007, P < 0.001, P < 0.001). IER had highest diagnostic accuracy (77.6%), sensitivity (86.2%), and area under the ROC curve (.879). MTR specificity was 100%. Logistic regression modeling with NMTR and NIER yielded best results for BL versus ML (sensitivity 93.1%, specificity 80%, AUC 0.884, accuracy 83.7%).

Conclusion:

Isolated quantitative DCE analysis may increase specificity of breast MR for differentiating BL and ML. DCE‐MRI with NMTR may produce a robust means of evaluating breast lesions. J. Magn. Reson. Imaging 2013;37:138–145. © 2012 Wiley Periodicals, Inc.     

Application of a biodegradable macromolecular contrast agent in dynamic contrast‐enhanced MRI for assessing the efficacy of indocyanine green‐enhanced photothermal cancer therapy

Purpose

To investigate the effectiveness of a polydisulfide‐based biodegradable macromolecular contrast agent, (Gd‐DTPA)‐cystamine copolymers (GDCC), in assessing the efficacy of indocyanine green‐enhanced photothermal cancer therapy using dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI).

Materials and Methods

Breast cancer xenografts in mice were injected with indocyanine green and irradiated with a laser. The efficacy was assessed using DCE‐MRI with GDCC of 40 kDa (GDCC‐40) at 4 hours and 7 days after the treatment. The uptake of GDCC‐40 by the tumors was fit to a two‐compartment model to obtain tumor vascular parameters, including fractional plasma volume (f^PV), endothelium transfer coefficient (K^PS), and permeability surface area product (PS).

Results

GDCC‐40 resulted in similar tumor vascular parameters at three doses, with larger standard deviations at lower doses. The values of f^PV, K^PS, and PS of the treated tumors were smaller (P < 0.05) than those of untreated tumors at 4 hours after the treatment and recovered to pretreatment values (P > 0.05) at 7 days after the treatment.

Conclusion

DCE‐MRI with GDCC‐40 is effective for assessing tumor early response to dye‐enhanced photothermal therapy and detecting tumor relapse after the treatment. GDCC‐40 has a potential to noninvasively monitor anticancer therapies with DCE‐MRI. J. Magn. Reson. Imaging 2009;30:401–406. © 2009 Wiley‐Liss, Inc.     

Monitoring neoadjuvant chemotherapy in breast cancer patients: Improved MR assessment at 3 T?

Purpose:

To investigate possible improvements in predicting the response to neoadjuvant chemotherapy (NAC) at 3 T for locally advanced breast cancer (LABC).

Materials and Methods:

Dynamic contrast‐enhanced magnetic resonance (DCE‐MR) images acquired before and during NAC were retrospectively analyzed in 85 patients. Tumor volume and diameter, three volumes based on the shape of the enhancement curve, relative signal intensity, area under the curve, and the signal‐to‐noise ratio were extracted. Differences between responders and nonresponders at the same and between MR timepoints during treatment were evaluated.

Results:

A higher signal‐to‐noise ratio was observed on 3 T images compared to 1.5 T, and 3 T revealed more significant findings related to response compared to 1.5 T. The DCE‐MRI‐derived volume parameters were the earliest predictors of response at both 1.5 and 3 T.

Conclusion:

Our results show that 3 T provides an improved assessment of the response to NAC in LABC patients, where the MR determined tumor volume reduction before the second cycle of NAC was the strongest and earliest predictor of a response. J. Magn. Reson. Imaging 2011;. © 2011 Wiley‐Liss, Inc.     

Impact of nonrigid motion correction technique on pixel-wise pharmacokinetic analysis of free-breathing pulmonary dynamic contrast-enhanced MR imaging

Purpose:

To investigates the impact of nonrigid motion correction on pixel‐wise pharmacokinetic analysis of free‐breathing DCE‐MRI in patients with solitary pulmonary nodules (SPNs). Misalignment of focal lesions due to respiratory motion in free‐breathing dynamic contrast‐enhanced MRI (DCE‐MRI) precludes obtaining reliable time–intensity curves, which are crucial for pharmacokinetic analysis for tissue characterization.

Materials and Methods:

Single‐slice 2D DCE‐MRI was obtained in 15 patients. Misalignments of SPNs were corrected using nonrigid B‐spline image registration. Pixel‐wise pharmacokinetic parameters K^trans, v_e, and k_ep were estimated from both original and motion‐corrected DCE‐MRI by fitting the two‐compartment pharmacokinetic model to the time–intensity curve obtained in each pixel. The “goodness‐of‐fit” was tested with χ²‐test in pixel‐by‐pixel basis to evaluate the reliability of the parameters. The percentages of reliable pixels within the SPNs were compared between the original and motion‐corrected DCE‐MRI. In addition, the parameters obtained from benign and malignant SPNs were compared.

Results:

The percentage of reliable pixels in the motion‐corrected DCE‐MRI was significantly larger than the original DCE‐MRI (P = 4 × 10^?7). Both K^trans and k_ep derived from the motion‐corrected DCE‐MRI showed significant differences between benign and malignant SPNs (P = 0.024, 0.015).

Conclusion:

The study demonstrated the impact of nonrigid motion correction technique on pixel‐wise pharmacokinetic analysis of free‐breathing DCE‐MRI in SPNs. J. Magn. Reson. Imaging 2011;33:968–973. © 2011 Wiley‐Liss, Inc.

     

Washout gradient in dynamic contrast-enhanced MRI is associated with tumor aggressiveness of prostate cancer

Purpose:

To investigate the associations between dynamic contrast‐enhanced magnetic resonance imaging (DCE MRI) parameters and the Gleason score (GS) for prostate cancer (PCA) with localization information provided by concurrent apparent diffusion coefficient (ADC) maps.

Materials and Methods:

Forty‐three male patients received MR scans, including diffusion tensor imaging (DTI) and DCE MRI, on a 1.5 T MR system. All patients were confirmed to have PCA in the following biopsy within 2 weeks. ADC maps calculated from DTI were used to colocalize cancerous and noncancerous regions on DCE MRI for perfusion analysis retrospectively. Semiquantitative parameters (peak enhancement, initial gradient, and washout gradient [WG] and quantitative parameters [K^trans, ν_e, and k_ep]) were calculated and correlated with the GS. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of the perfusion parameters in assessing the aggressiveness of PCA.

Results:

A total of 41 PCA nodules were included in the analysis. Among all quantitative and semiquantitative parameters, only WG showed significant correlation with GS (r = ?0.75, P < 0.0001). By defining tumor aggressiveness as a GS >6, WG demonstrated a good diagnostic performance, with the area under the ROC curve being 0.88. Under a cutoff point of WG = 0.125 min^?1, the sensitivity and specificity were 0.87 and 0.78, respectively.

Conclusion:

WG shows a significant association with GS and good diagnostic performance in assessing tumor aggressiveness. Therefore, WG is a potential marker of GS. J. Magn. Reson. Imaging 2012;36:912–919. © 2012 Wiley Periodicals, Inc.

     

Diffusion-weighted MRI in rectal cancer: apparent diffusion coefficient as a potential noninvasive marker of tumor aggressiveness

Purpose:

To assess the value of diffusion‐weighted MR imaging (DWI) as a potential noninvasive marker of tumor aggressiveness in rectal cancer, by analyzing the relationship between tumoral apparent diffusion coefficient (ADC) values and MRI and histological prognostic parameters.

Materials and Methods:

Fifty rectal cancer patients underwent primary staging MRI including DWI before surgery and neo‐adjuvant therapy. In 47, surgery was preceded by short‐course radiation therapy (n = 28) or long‐course chemoradiation therapy (n = 19). Mean tumor ADC was measured and compared between subgroups based on pretreatment CEA levels, MRI parameters (mesorectal fascia ‐ MRF ‐ status; T‐stage; N‐stage) and histological parameters (differentiation grade: poorly differentiated, poorly moderately differentiated, moderately differentiated, moderately well differentiated, well‐differentiated; lymphangiovascular invasion).

Results:

Mean tumor ADCs differ between MRF‐free versus MRF‐invaded tumors (P = 0.013), the groups of cN0 versus cN+ cancers (P = 0.011), and between the several groups of histological differentiation grades (P = 0.025). There was no significant difference in mean ADCs between the various groups of CEA levels, the T stage, and the presence of lymphangiovascular invasion.

Conclusion:

Lower ADC values were associated with a more aggressive tumor profile. Significant correlations were found between mean ADC values and radiological MRF status, N stage and differentiation grade. ADC has the potential to become an imaging biomarker of tumor aggressiveness profile. J. Magn. Reson. Imaging 2012;35:1365–1371. © 2012 Wiley Periodicals, Inc.     

Diffusion‐weighted imaging of breast cancer: Correlation of the apparent diffusion coefficient value with prognostic factors

Purpose

To evaluate the role of diffusion‐weighted imaging (DWI) in the detection of breast cancers, and to correlate the apparent diffusion coefficient (ADC) value with prognostic factors.

Materials and Methods

Sixty‐seven women with invasive cancer underwent breast MRI. Histological specimens were analyzed for tumor size and grade, and expression of estrogen receptors (ER), progesterone receptors, c‐erbB‐2, p53, Ki‐67, and epidermal growth factor receptors. The computed mean ADC values of breast cancer and normal breast parenchyma were compared. Relationships between the ADC values and prognostic factors were determined using Wilcoxon signed rank test and Kruskal‐Wallis test.

Results

DWI detected breast cancer as a hyperintense area in 62 patients (92.5 %). A statistically significant difference in the mean ADC values of breast cancer (1.09 ± 0.27 × 10^?5 mm²/s) and normal parenchyma (1.59 ± 0.27 × 10^?5 mm²/s) was detected (P < 0.0001). There were no correlations between the ADC value and prognostic factors. However, the median ADC value was lower in the ER‐positive group than the ER negative group, and this difference was marginally significant (1.09 × 10^?5 mm²/s versus 1.15 × 10^?5 mm²/s, P = 0.053).

Conclusion

The ADC value was a helpful parameter in detecting malignant breast tumors, but ADC value could not predict patient prognosis. J. Magn. Reson. Imaging 2009;30:615–620. © 2009 Wiley‐Liss, Inc.

     

Temporal sampling requirements for reference region modeling of DCE‐MRI data in human breast cancer

Purpose

To assess the temporal sampling requirements needed for quantitative analysis of dynamic contrast‐enhanced MRI (DCE‐MRI) data with a reference region (RR) model in human breast cancer.

Materials and Methods

Simulations were used to study errors in pharmacokinetic parameters (K^trans and v_e) estimated by the RR model using six DCE‐MRI acquisitions over a range of pharmacokinetic parameter values, arterial input functions, and temporal samplings. DCE‐MRI data were acquired on 12 breast cancer patients and parameters were estimated using the native resolution data (16.4 seconds) and compared to downsampled 32.8‐second and 65.6‐second data.

Results

Simulations show that, in the majority of parameter combinations, the RR model results in an error less than 20% in the extracted parameters with temporal sampling as poor as 35.6 seconds. The experimental results show a high correlation between K^trans and v_e estimates from data acquired at 16.4‐second temporal resolution compared to the downsampled 32.8‐second data: the slope of the regression line was 1.025 (95% confidence interval [CI]: 1.021, 1.029), Pearson's correlation r = 0.943 (95% CI: 0.940, 0.945) for K^trans, and 1.023 (95% CI: 1.021. 1.025), r = 0.979 (95% CI: 0.978, 0.980) for v_e. For the 64‐second temporal resolution data the results were: 0.890 (95% CI: 0.894, 0.905), r = 0.8645, (95% CI: 0.858, 0.871) for K^trans, and 1.041 (95% CI: 1.039, 1.043), r = 0.970 (95% CI: 0.968, 0.971) for v_e.

Conclusion

RR analysis allows for a significant reduction in temporal sampling requirements and this lends itself to analyze DCE‐MRI data acquired in practical situations. J. Magn. Reson. Imaging 2009;30:121–134. © 2009 Wiley‐Liss, Inc.     

Prostate cancer detection with multi‐parametric MRI: Logistic regression analysis of quantitative T2, diffusion‐weighted imaging,and dynamic contrast‐enhanced MRI

Purpose

To develop a multi‐parametric model suitable for prospectively identifying prostate cancer in peripheral zone (PZ) using magnetic resonance imaging (MRI).

Materials and Methods

Twenty‐five radical prostatectomy patients (median age, 63 years; range, 44–72 years) had T2‐weighted, diffusion‐weighted imaging (DWI), T2‐mapping, and dynamic contrast‐enhanced (DCE) MRI at 1.5 Tesla (T) with endorectal coil to yield parameters apparent diffusion coefficient (ADC), T2, volume transfer constant (K^trans) and extravascular extracellular volume fraction (v_e). Whole‐mount histology was generated from surgical specimens and PZ tumors delineated. Thirty‐eight tumor outlines, one per tumor, and pathologically normal PZ regions were transferred to MR images. Receiver operating characteristic (ROC) curves were generated using all identified normal and tumor voxels. Step‐wise logistic‐regression modeling was performed, testing changes in deviance for significance. Areas under the ROC curves (A_z) were used to evaluate and compare performance.

Results

The best‐performing single‐parameter was ADC (mean A_z [95% confidence interval]: A_z,ADC: 0.689 [0.675, 0.702]; A_z,T2: 0.673 [0.659, 0.687]; A_z,Ktrans: 0.592 [0.578, 0.606]; A_z,ve: 0.543 [0.528, 0.557]). The optimal multi‐parametric model, LR‐3p, consisted of combining ADC, T2 and K^trans. Mean A_z,LR‐3p was 0.706 [0.692, 0.719], which was significantly higher than A_z,T2, A_z,Ktrans, and A_z,ve (P < 0.002). A_z,LR‐3p tended to be greater than A_z,ADC, however, this result was not statistically significant (P = 0.090).

Conclusion

Using logistic regression, an objective model capable of mapping PZ tumor with reasonable performance can be constructed. J. Magn. Reson. Imaging 2009;30:327–334. © 2009 Wiley‐Liss, Inc.     

Correlation of perfusion parameters on dynamic contrast-enhanced MRI with prognostic factors and subtypes of breast cancers

Purpose:

To investigate whether a correlation exists between perfusion parameters obtained from dynamic contrast‐enhanced (DCE) magnetic resonance imaging (MRI) and prognostic factors or immunohistochemical subtypes of breast cancers.

Materials and Methods:

Quantitative parameters (K^trans, k_ep, and v_e) of 70 invasive ductal carcinomas were obtained using DCE‐MRI as a postprocessing procedure. Correlations between parameters and prognostic factors, including tumor size, axillary nodal status, histologic grade, nuclear grade, expression of estrogen receptor (ER), progesterone receptor (PR), Ki‐67, p53, bcl‐2, and human epidermal growth factor receptor 2 (HER2) and subtypes categorized as luminal (ER or PR‐positive), triple negative (ER or PR‐negative, HER2‐negative), and HER2 (ER and PR‐negative, HER2 overexpression) were analyzed.

Results:

Mean K^trans was higher in tumors with a high histologic grade than with a low histologic grade (P = 0.007), with a high nuclear grade than with a low nuclear grade (P = 0.002), and with ER negativity than ER positivity (P = 0.056). Mean k_ep was higher in tumors with a high histologic grade than with a low histologic grade (P = 0.005), with a high nuclear grade than with a low nuclear grade (P = 0.001), and with ER negativity than with ER positivity (P = 0.043). Mean v_e was lower in tumors with a high histologic grade than with a low histologic grade (P = 0.038) and with ER negativity than with ER positivity (P = 0.015). Triple‐negative cancers showed a higher mean k_ep than the luminal type (P = 0.015).

Conclusion:

Breast cancers with higher K^trans and k_ep, or lower v_e, had poor prognostic factors and were often of the triple‐negative subtype. J. Magn. Reson. Imaging 2012;36:145–151. © 2012 Wiley Periodicals, Inc.     

Diffusion-weighted MRI of fatty liver

Purpose:

To investigate the effect of fat infiltration on the apparent diffusion coefficient (ADC) of liver, and assess the relationship between ADC and hepatic fat fraction (HFF).

Materials and Methods:

MRI scans of 120 consecutive patients were included in this retrospective study. Of these, 42 patients were included in the fatty liver group and 78 in the control group. ADC values were measured from a pair of diffusion‐weighted (DW) images (b = 0 mm²/s and 1000 mm²/s). HFFs were measured using T1W GRE dual‐echo images. The difference between the ADCs of the two groups was assessed with the t‐test. The relationship between HFF and ADC was determined using linear regression analysis and the Pearson correlation coefficient (r).

Results:

Mean HFFs were 0.85 ± 2.86 and 13.67 ± 8.62 in the control and fatty liver groups, respectively. The mean ADC of fatty liver group 1.20 ± 0.22 × 10^?3 mm²/s was significantly lower than that of the control group 1.32 ± 0.23 × 10^?3 mm²/s (P = 0.02). Linear regression analysis revealed an inverse relationship between ADC and HFF (r = ?0.39, P < 0.0001).

Conclusion:

ADC significantly decreases in patients with >5% HFF, and ADC and HFF exhibit an inverse relationship. J. Magn. Reson. Imaging 2012;35:1109‐1111. © 2011 Wiley Periodicals, Inc.

     

Assessing liver function using dynamic Gd‐EOB‐DTPA‐enhanced MRI with a standard 5‐phase imaging protocol

Purpose:

To evaluate liver function obtained by tracer‐kinetic modeling of dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) data acquired with a routine gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd‐EOB‐DTPA)‐enhanced protocol.

Materials and Methods:

Data were acquired from 25 cases of nonchronic liver disease and 94 cases of cirrhosis. DCE‐MRI was performed with a dose of 0.025 mmol/kg Gd‐EOB‐DTPA injected at 2 mL/sec. A 3D breath‐hold sequence acquired 5 volumes of 72 slices each: precontrast, double arterial phase, portal phase, and 4‐minute postcontrast. Regions of interest (ROIs) were selected semiautomatically in the aorta, portal vein, and whole liver on a middle slice. A constrained dual‐inlet two‐compartment uptake model was fitted to the ROI curves, producing three parameters: intracellular uptake rate (UR), extracellular volume (Ve), and arterial flow fraction (AFF).

Results:

Median UR dropped from 4.46 10^?2 min^?1 in the noncirrhosis to 3.20 in Child–Pugh A (P = 0.001), and again to 1.92 in Child–Pugh B (P < 0.0001). Median Ve dropped from 6.64 mL 100 mL^?1 in the noncirrhosis to 5.80 in Child–Pugh A (P = 0.01). Other combinations of Ve and AFF changes were not significant for any group.

Conclusion:

UR obtained from tracer kinetic analysis of a routine DCE‐MRI has the potential to become a novel index of liver function. J. Magn. Reson. Imaging 2013;37:1109–1114. © 2012 Wiley Periodicals, Inc.

     

Differential diagnosis of mammographically and clinically occult breast lesions on diffusion‐weighted MRI

Purpose:

To investigate the diagnostic performance of diffusion‐weighted imaging (DWI) for mammographically and clinically occult breast lesions.

Materials and Methods:

The study included 91 women with 118 breast lesions (91 benign, 12 ductal carcinoma in situ [DCIS], 15 invasive carcinoma) initially detected on dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) and assigned BI‐RADS category 3, 4, or 5. DWI was acquired with b = 0 and 600 s/mm². Lesion visibility was assessed on DWI. Apparent diffusion coefficient (ADC) values were compared between malignancies, benign lesions, and normal (no abnormal enhancement on DCE‐MRI) breast tissue, and the diagnostic performance of DWI was assessed based on ADC thresholding.

Results:

Twenty‐four of 27 (89%) malignant and 74/91 (81%) benign lesions were hyperintense on the b = 600 s/mm² diffusion‐weighted images. Both DCIS (1.33 ± 0.19 × 10^?3 mm²/s) and invasive carcinomas (1.30 ± 0.27 × 10^?3mm²/s) were lower in ADC than benign lesions (1.71 ± 0.43 × 10^?3mm²/s; P < 0.001), and each lesion type was lower in ADC than normal tissue (1.90 ± 0.38 × 10^?3mm²/s, P ≤ 0.001). Receiver operating curve (ROC) analysis showed an area under the curve (AUC) of 0.77, and sensitivity = 96%, specificity = 55%, positive predictive value (PPV) = 39%, and negative predictive value (NPV) = 98% for an ADC threshold of 1.60 × 10^?3mm²/s.

Conclusion:

Many mammographically and clinically occult breast carcinomas were visibly hyperintense on diffusion‐weighted images, and ADC enabled differentiation from benign lesions. Further studies evaluating DWI while blinded to DCE‐MRI are necessary to assess the potential of DWI as a noncontrast breast screening technique. J. Magn. Reson. Imaging 2010;1:562–570. © 2010 Wiley‐Liss, Inc.