Dynamic Contrast Material-enhanced Imaging Research Articles

Gallium 68 PSMA-11 PET/MR Imaging in Patients with Intermediate- or High-Risk Prostate Cancer.

Purpose To report the results of dual-time-point gallium 68 (68Ga) prostate-specific membrane antigen (PSMA)-11 positron emission tomography (PET)/magnetic resonance (MR) imaging prior to prostatectomy in patients with intermediate- or high-risk cancer. Materials and Methods Thirty-three men who underwent conventional imaging as clinically indicated and who were scheduled for radical prostatectomy with pelvic lymph node dissection were recruited for this study. A mean dose of 4.1 mCi ± 0.7 (151.7 MBq ± 25.9) of 68Ga-PSMA-11 was administered. Whole-body images were acquired starting 41-61 minutes after injection by using a GE SIGNA PET/MR imaging unit, followed by an additional pelvic PET/MR imaging acquisition at 87-125 minutes after injection. PET/MR imaging findings were compared with findings at multiparametric MR imaging (including diffusion-weighted imaging, T2-weighted imaging, and dynamic contrast material-enhanced imaging) and were correlated with results of final whole-mount pathologic examination and pelvic nodal dissection to yield sensitivity and specificity. Dual-time-point metabolic parameters (eg, maximum standardized uptake value [SUVmax]) were compared by using a paired t test and were correlated with clinical and histopathologic variables including prostate-specific antigen level, Gleason score, and tumor volume. Results Prostate cancer was seen at 68Ga-PSMA-11 PET in all 33 patients, whereas multiparametric MR imaging depicted Prostate Imaging Reporting and Data System (PI-RADS) 4 or 5 lesions in 26 patients and PI-RADS 3 lesions in four patients. Focal uptake was seen in the pelvic lymph nodes in five patients. Pathologic examination confirmed prostate cancer in all patients, as well as nodal metastasis in three. All patients with normal pelvic nodes in PET/MR imaging had no metastases at pathologic examination. The accumulation of 68Ga-PSMA-11 increased at later acquisition times, with higher mean SUVmax (15.3 vs 12.3, P < .001). One additional prostate cancer was identified only at delayed imaging. Conclusion This study found that 68Ga-PSMA-11 PET can be used to identify prostate cancer, while MR imaging provides detailed anatomic guidance. Hence, 68Ga-PSMA-11 PET/MR imaging provides valuable diagnostic information and may inform the need for and extent of pelvic node dissection.

Advanced Imaging Techniques in Evaluation of Colorectal Cancer.

Imaging techniques are clinical decision-making tools in the evaluation of patients with colorectal cancer (CRC). The aim of this article is to discuss the potential of recent advances in imaging for diagnosis, prognosis, therapy planning, and assessment of response to treatment of CRC. Recent developments and new clinical applications of conventional imaging techniques such as virtual colonoscopy, dual-energy spectral computed tomography, elastography, advanced computing techniques (including volumetric rendering techniques and machine learning), magnetic resonance (MR) imaging-based magnetization transfer, and new liver imaging techniques, which may offer additional clinical information in patients with CRC, are summarized. In addition, the clinical value of functional and molecular imaging techniques such as diffusion-weighted MR imaging, dynamic contrast material-enhanced imaging, blood oxygen level-dependent imaging, lymphography with contrast agents, positron emission tomography with different radiotracers, and MR spectroscopy is reviewed, and the advantages and disadvantages of these modalities are evaluated. Finally, the future role of imaging-based analysis of tumor heterogeneity and multiparametric imaging, the development of radiomics and radiogenomics, and future challenges for imaging of patients with CRC are discussed. Online supplemental material is available for this article. ©RSNA, 2018.

Endometrial Carcinoma: MR Imaging-based Texture Model for Preoperative Risk Stratification-A Preliminary Analysis.

Purpose To evaluate the associations among mathematical modeling with the use of magnetic resonance (MR) imaging-based texture features and deep myometrial invasion (DMI), lymphovascular space invasion (LVSI), and histologic high-grade endometrial carcinoma. Materials and Methods Institutional review board approval was obtained for this retrospective study. This study included 137 women with endometrial carcinomas measuring greater than 1 cm in maximal diameter who underwent 1.5-T MR imaging before hysterectomy between January 2011 and December 2015. Texture analysis was performed with commercial research software with manual delineation of a region of interest around the tumor on MR images (T2-weighted, diffusion-weighted, and dynamic contrast material-enhanced images and apparent diffusion coefficient maps). Areas under the receiver operating characteristic curve and diagnostic performance of random forest models determined by using a subset of the most relevant texture features were estimated and compared with those of independent and blinded visual assessments by three subspecialty radiologists. Results A total of 180 texture features were extracted and ultimately limited to 11 features for DMI, 12 for LVSI, and 16 for high-grade tumor for random forest modeling. With random forest models, areas under the receiver operating characteristic curve, sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were estimated at 0.84, 79.3%, 82.3%, 81.0%, 76.7%, and 84.4% for DMI; 0.80, 80.9%, 72.5%, 76.6%, 74.3%, and 79.4% for LVSI; and 0.83, 81.0%, 76.8%, 78.1%, 60.7%, and 90.1% for high-grade tumor, respectively. Sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of visual assessment for DMI were 84.5%, 82.3%, 83.2%, 77.7%, and 87.8% (reader 3). Conclusion The mathematical models that incorporated MR imaging-based texture features were associated with the presence of DMI, LVSI, and high-grade tumor and achieved equivalent accuracy to that of subspecialty radiologists for assessment of DMI in endometrial cancers larger than 1 cm. However, these preliminary results must be interpreted with caution until they are validated with an independent data set, because the small sample size relative to the number of features extracted may have resulted in overfitting of the models. © RSNA, 2017 Online supplemental material is available for this article.

Multiparametric Assessment of Treatment Response in High-Grade Soft-Tissue Sarcomas with Anatomic and Functional MR Imaging Sequences.

To determine the added value of quantitative diffusion-weighted and dynamic contrast material-enhanced imaging to conventional magnetic resonance (MR) imaging for assessment of the response of soft-tissue sarcomas to neoadjuvant therapy. MR imaging examinations in 23 patients with soft-tissue sarcomas who had undergone neoadjuvant therapy were reviewed by two readers during three sessions: conventional imaging (T1-weighted, fluid-sensitive, static postcontrast T1-weighted), conventional with diffusion-weighted imaging, and conventional with diffusion-weighted and dynamic contrast-enhanced imaging. For each session, readers recorded imaging features and determined treatment response. Interobserver agreement was assessed and receiver operating characteristic analysis was performed to evaluate the accuracy of each session for determining response by using results of the histologic analysis as the reference standard. Good response was defined as less than or equal to 5% residual viable tumor. Of the 23 sarcomas, four (17.4%) showed good histologic response (three of four with >95% granulation tissue and <5% necrosis, one of four with 95% necrosis and <5% viable tumor) and 19 (82.6%) showed poor response (viable tumor range, 10%-100%). Interobserver agreement was substantial or excellent for imaging features in all sequences (k = 0.789-1.000). Receiver operating characteristic analysis showed an increase in diagnostic performance with the addition of diffusion-weighted and dynamic contrast-enhanced MR imaging for prediction of response compared with that for conventional imaging alone (areas under the curve, 0.500, 0.676, 0.821 [reader 1] and 0.506, 0.704, 0.833 [reader 2], respectively). Adding functional sequences to the conventional MR imaging protocol increases the sensitivity of MR imaging for determining treatment response in soft-tissue sarcomas.

Computer-extracted Features Can Distinguish Noncancerous Confounding Disease from Prostatic Adenocarcinoma at Multiparametric MR Imaging.

To determine the best features to discriminate prostate cancer from benign disease and its relationship to benign disease class and cancer grade. The institutional review board approved this study and waived the need for informed consent. A retrospective cohort of 70 patients (age range, 48-70 years; median, 62 years), all of whom were scheduled to undergo radical prostatectomy and underwent preoperative 3-T multiparametric magnetic resonance (MR) imaging, including T2-weighted, diffusion-weighted, and dynamic contrast material-enhanced imaging, were included. The digitized prostatectomy slides were annotated for cancer and noncancerous disease and coregistered to MR imaging with an interactive deformable coregistration scheme. Computer-identified features for each of the noncancerous disease categories (eg, benign prostatic hyperplasia [BPH], prostatic intraepithelial neoplasia [PIN], inflammation, and atrophy) and prostate cancer were extracted. Feature selection was performed to identify the features with the highest discriminatory power. The performance of these five features was evaluated by using the area under the receiver operating characteristic curve (AUC). High-b-value diffusion-weighted images were more discriminative in distinguishing BPH from prostate cancer than apparent diffusion coefficient, which was most suitable for distinguishing PIN from prostate cancer. The focal appearance of lesions on dynamic contrast-enhanced images may help discriminate atrophy and inflammation from cancer. Which imaging features are discriminative for different benign lesions is influenced by cancer grade. The apparent diffusion coefficient appeared to be the most discriminative feature in identifying high-grade cancer. Classification results showed increased performance by taking into account specific benign types (AUC = 0.70) compared with grouping all noncancerous findings together (AUC = 0.62). The best features with which to discriminate prostate cancer from noncancerous benign disease depend on the type of benign disease and cancer grade. Use of the best features may result in better diagnostic performance.

Prostate Cancer: The European Society of Urogenital Radiology Prostate Imaging Reporting and Data System Criteria for Predicting Extraprostatic Extension by Using 3-T Multiparametric MR Imaging

To retrospectively assess the use of the European Society of Urogenital Radiology (ESUR) Prostate Imaging Reporting and Data System (PI-RADS) criteria and 3-T multiparametric magnetic resonance (MR) imaging for detection of extraprostatic extension (EPE) of prostate cancer. The institutional review board approval requirement was waived. Consecutive patients with prostate cancer (n = 133) underwent 3-T multiparametric MR imaging before prostatectomy. Lesions were assessed by using ESUR/PI-RADS criteria for T2-weighted, diffusion-weighted, and dynamic contrast material-enhanced imaging, and by using the sum of these scores. Zonal dominant parameters corresponding to the score of diffusion-weighted imaging for peripheral zone lesions and to T2-weighted imaging scores for transitional zone lesions were calculated. In addition, the presence of EPE in each patient was evaluated on the basis of subjective multiparametric MR imaging features. Histopathologic examination of whole-mount radical prostatectomy specimens was used as the reference standard. Sensitivity, specificity, positive predictive, and negative predictive values; likelihood ratios; and areas under the receiver operating characteristic curve were calculated for each parameter on the basis of its usefulness for prediction of EPE. EPE was found in 60 of 133 (45%) patients. Receiver operating characteristic curve analysis for the prediction of EPE revealed an area under the curve of 0.72 for T2-weighted, 0.67 for diffusion-weighted, and 0.64 for dynamic contrast-enhanced imaging; 0.74 for the dominant parameter; and 0.74 for the sum of the PI-RADS scores, and a score of 5 was defined as the best threshold for the individual parameters, with a score greater than or equal to 13 as the threshold for the sum of the PI-RADS scores. By applying these thresholds, sensitivity, negative predictive value, and negative likelihood ratio (ruling out EPE) were 77%, 77%, and 0.36, respectively, and specificity, positive predictive value, and positive likelihood ratio (ruling in EPE) were 64%, 64%, and 2.15, respectively, for the dominant parameter. Feature analysis showed an area under the curve of 0.72; sensitivity, negative predictive value, and negative likelihood ratio of 63%, 72%, and 0.56, respectively, and specificity, positive predictive value, and positive likelihood ratio of 78%, 70%, and 3.77, respectively. ESUR/PI-RADS criteria showed moderate overall accuracy for use in the prediction of EPE, and these results were similar to those of multiparametric MR imaging assessment of features in this study sample.

Prostate Imaging Reporting and Data System and Likert Scoring System: Multiparametric MR Imaging Validation Study to Screen Patients for Initial Biopsy.

To compare the diagnostic performance of the magnetic resonance (MR) imaging-based Prostate Imaging Reporting and Data System (PI-RADS) and a Likert scale in the detection of prostate cancer in a cohort of patients undergoing initial prostate biopsy. This institutional review board-approved two-center prospective study included 118 patients with normal digital rectal examination (DRE) results but elevated prostate-specific antigen (PSA) levels (4-20 ng/mL) who were referred for initial prostate biopsies and had one suspicious (Likert scale score, ≥3) focus at prebiopsy 1.5-T multiparametric MR imaging performed with T2-weighted, diffusion-weighted [DW], and dynamic contrast material-enhanced imaging. Targeted core biopsies and random systematic core biopsies were performed. The elementary unit for analysis was the core. Relationships were assessed by using the Mann-Whitney U test. Yates corrected and Pearson χ(2) tests were used to evaluate categoric variables. A training set was randomly drawn to construct the receiver operating characteristic curves for the summed PI-RADS scores and for the Likert scale scores. The thresholds to recommend biopsy were obtained from the Youden J statistics and were tested in the remaining validation set in terms of predictive characteristics. Interobserver variability was analyzed by using weighed κ statistics in a random set of 50 patients. Higher T2-weighted, DW, and dynamic contrast-enhanced imaging PI-RADS scores were observed in areas that yielded cancer-positive cores. The percentage of positive cores increased with the sum of scores aggregated in five classes as follows: For summed PI-RADS scores of 3-5, the percentage of positive cores was 2.3%; for scores of 6-8, it was 5.8%; for scores of 9 or 10, it was 24.7%; for scores of 11 or 12, it was 51.8%; and for scores of 13-15, it was 72.1% (P for trend, <.0001). For the threshold of summed PI-RADS scores of 9 or greater, sensitivity was 86.6%, specificity was 82.4%, the positive predictive value was 52.4%, the negative predictive value was 96.5%, and accuracy was 83.2%. The respective data for Likert scale scores of 3 or greater were 93.8%, 73.6%, 44.3%, 98.1%, and 73.3%. Good interobserver agreement was observed for the Likert scale (κ = 0.80) and the summed PI-RADS (κ = 0.73) scoring systems. PI-RADS provided the site-specific stratified risk of cancer-positive cores in biopsy-naive men with normal DRE results and elevated PSA levels. There was no significant difference between summed PI-RADS scores of 9 or greater and Likert scale scores of 3 or greater in the detection of cancer in the peripheral zone.

Luminal-type breast cancer: correlation of apparent diffusion coefficients with the Ki-67 labeling index.

To evaluate the correlation between apparent diffusion coefficient ( ADC apparent diffusion coefficient ) values and the Ki-67 labeling index for luminal-type (estrogen receptor-positive) breast cancer not otherwise specified ( NOS not otherwise specified ) diagnosed by means of biopsy. The institutional review board approved this retrospective study, and the requirement for informed consent was waived. Between December 2009 and December 2012, 86 patients with 86 lesions with luminal-type invasive breast cancer NOS not otherwise specified underwent magnetic resonance imaging, including dynamic contrast material-enhanced imaging and diffusion-weighted imaging with b values of 0 and 1000 sec/mm(2). Conventional measurement of the minimum and mean ADC apparent diffusion coefficient s by placing regions of interest and histogram analysis of pixel-based ADC apparent diffusion coefficient data of the entire tumor were performed by two observers independently and correlated with the Ki-67 labeling index of surgical specimens. For the interobserver reliability, interclass correlation coefficients for all parameters with the exception of the minimum ADC apparent diffusion coefficient exceeded 0.8, indicating almost perfect agreement. The minimum ADC apparent diffusion coefficient and mean ADC apparent diffusion coefficient and the 25th, 50th, and 75th percentiles of the histograms showed negative correlations with the Ki-67 labeling index (r = -0.49, -0.55, -0.54, -0.53, and -0.48, respectively). Receiver operating characteristic curve analysis for the differential diagnosis between the high-proliferation (Ki-67 ≥ 14; n = 44) and low-proliferation (Ki-67 < 14; n = 42) groups revealed that the most effective threshold for the mean ADC apparent diffusion coefficient was lower than 1097 × 10(-6) mm(2)/sec, with sensitivity and specificity of 82% and 71%, respectively. The area under the receiver operating characteristic curve (AUC) was 0.81 for the mean ADC apparent diffusion coefficient . There were no significant differences in the AUC among the parameters. Considering convenience for routine practice, the authors suggest that the mean ADC apparent diffusion coefficient of the conventional method would be practical to use for estimating the Ki-67 labeling index.

Functional Imaging for Radiation Treatment Planning, Response Assessment, and Adaptive Therapy in Head and Neck Cancer

Patients with squamous cell carcinomas (SCCs) of the head and neck are increasingly treated nonsurgically. Imaging plays a critical role in helping define the targets for radiation therapy, especially intensity-modulated radiation therapy, in which the dose gradients are steep. Anatomic imaging with conventional modalities, particularly computed tomography (CT), has been used in patients with head and neck SCCs, but this approach has limitations. Functional imaging techniques, including positron emission tomography (PET) combined with CT or magnetic resonance (MR) imaging, offer complementary information and can be used noninvasively to assess a range of biomarkers in patients with head and neck SCCs, including hypoxia, cell proliferation and apoptosis, and epidermal growth factor receptor status. These biologic markers can be monitored before, during, and after treatment to improve patient selection for specific therapeutic strategies, guide adaptation of therapy, and potentially facilitate more accurate assessment of disease response. This article discusses the practical aspects of integrating functional imaging into head-and-neck radiation therapy planning and reviews the potential of molecular imaging biomarkers for response assessment and therapy adaptation. The uses of PET tracers for imaging cellular processes such as metabolism, proliferation, hypoxia, and cell membrane synthesis are explored, and applications for MR techniques such as dynamic contrast material-enhanced imaging, diffusion-weighted imaging, blood oxygenation level-dependent imaging, and MR spectroscopy are reviewed. The potential of integrated PET/CT perfusion imaging and hybrid PET/MR imaging also is highlighted. These developments may allow more individualized treatment planning in patients with head and neck SCCs in the emerging era of personalized medicine.

Prostate Cancer Localization Using Multiparametric MR Imaging: Comparison of Prostate Imaging Reporting and Data System (PI-RADS) and Likert Scales

To compare the recently proposed Prostate Imaging Reporting and Data System (PI-RADS) scale that incorporates fixed criteria and a standard Likert scale based on overall impression in prostate cancer localization using multiparametric magnetic resonance (MR) imaging. This retrospective study was HIPAA compliant and institutional review board approved. Seventy patients who underwent 3-T pelvic MR imaging, including T2-weighted imaging, diffusion-weighted imaging, and dynamic contrast material-enhanced imaging, with a pelvic phased-array coil before radical prostatectomy were included. Three radiologists, each with 6 years of experience, independently scored 18 regions (12 peripheral zone [PZ], six transition zone [TZ]) using PI-RADS (range, scores 3-15) and Likert (range, scores 1-5) scales. Logistic regression for correlated data was used to compare scales for detection of tumors larger than 3 mm in maximal diameter at prostatectomy. Maximal accuracy was achieved with score thresholds of 8 and higher and of 3 and higher for PI-RADS and Likert scales, respectively. At these thresholds, in the PZ, similar accuracy was achieved with the PI-RADS scale and the Likert scale for radiologist 1 (89.0% vs 88.2%, P = .223) and radiologist 3 (88.5% vs 88.2%, P = .739) and greater accuracy was achieved with the PI-RADS scale than the Likert scale for radiologist 2 (89.6% vs 87.1%, P = .008). In the TZ, accuracy was lower with the PI-RADS scale than with the Likert scale for radiologist 1 (70.0% vs 87.1%, P < .001), radiologist 2 (87.6% vs 92.6%, P = .002), and radiologist 3 (82.9% vs 91.2%, P < .001). For tumors with Gleason score of at least 7, sensitivity was higher with the PI-RADS scale than with the Likert scale for radiologist 1 (88.6% vs 82.6%, P = .032), and sensitivity was similar for radiologist 2 (78.0% vs 76.5, P = .467) and radiologist 3 (77.3% vs 81.1%, P = .125). Radiologists performed well with both PI-RADS and Likert scales for tumor localization, although, in the TZ, performance was better with the Likert scale than the PI-RADS scale. http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.13122233/-/DC1.

MR Imaging of Prostate Cancer in Radiation Oncology: What Radiologists Need to Know

Radiation therapy (RT) is one of the principal treatment modalities for localized or locally advanced prostate cancer. The two major forms of RT for prostate cancer are external-beam RT (EBRT) with a photon or proton beam and brachytherapy. With modern conformal techniques for EBRT (three-dimensional conformal RT, intensity-modulated RT, and image-guided RT) and advanced computer-based planning systems for brachytherapy, the dose can be more precisely delivered to the prostate while reducing unnecessary radiation to normal tissue. The dominant intraprostatic tumor can be targeted with a higher dose, so-called dose painting. Magnetic resonance (MR) imaging plays a pivotal role in pretreatment assessment of prostate cancer. Multiparametric MR imaging, a combination of anatomic and functional MR imaging techniques (diffusion-weighted imaging, dynamic contrast material-enhanced imaging, and MR spectroscopy), significantly improves the accuracy of tumor localization and local staging. For pretreatment planning, anatomic MR imaging provides highly accurate local staging information, particularly about extraprostatic extension and seminal vesicle invasion. The dominant intraprostatic tumor and local recurrence in the prostatectomy bed can be better localized with multiparametric MR imaging for dose painting. MR imaging allows excellent delineation of the contours of the prostate and surrounding structures. It can also be used in early posttreatment evaluation after brachytherapy.

Multiparametric Prostate MR Imaging with T2-weighted, Diffusion-weighted, and Dynamic Contrast-enhanced Sequences: Are All Pulse Sequences Necessary to Detect Locally Recurrent Prostate Cancer after Radiation Therapy?

To compare diagnostic accuracy of T2-weighted magnetic resonance (MR) imaging with that of multiparametric (MP) MR imaging combining T2-weighted imaging with diffusion-weighted (DW) MR imaging, dynamic contrast material-enhanced (DCE) MR imaging, or both in the detection of locally recurrent prostate cancer (PCa) after radiation therapy (RT). This retrospective HIPAA-compliant study was approved by the institutional review board; informed consent was waived. Fifty-three men (median age, 70 years) suspected of having post-RT recurrence of PCa underwent MP MR imaging, including DW and DCE sequences, within 6 months after biopsy. Two readers independently evaluated the likelihood of PCa with a five-point scale for T2-weighted imaging alone, T2-weighted imaging with DW imaging, T2-weighted imaging with DCE imaging, and T2-weighted imaging with DW and DCE imaging, with at least a 4-week interval between evaluations. Areas under the receiver operating characteristic curve (AUC) were calculated. Interreader agreement was assessed, and quantitative parameters (apparent diffusion coefficient [ADC], volume transfer constant [K(trans)], and rate constant [k(ep)]) were assessed at sextant- and patient-based levels with generalized estimating equations and the Wilcoxon rank sum test, respectively. At biopsy, recurrence was present in 35 (66%) of 53 patients. In detection of recurrent PCa, T2-weighted imaging with DW imaging yielded higher AUCs (reader 1, 0.79-0.86; reader 2, 0.75-0.81) than T2-weighted imaging alone (reader 1, 0.63-0.67; reader 2, 0.46-0.49 [P ≤ .014 for all]). DCE sequences did not contribute significant incremental value to T2-weighted imaging with DW imaging (reader 1, P > .99; reader 2, P = .35). Interreader agreement was higher for combinations of MP MR imaging than for T2-weighted imaging alone (κ = 0.34-0.63 vs κ = 0.17-0.20). Medians of quantitative parameters differed significantly (P < .0001 to P = .0233) between benign tissue and PCa (ADC, 1.64 × 10(-3) mm(2)/sec vs 1.13 × 10(-3) mm(2)/sec; K(trans), 0.16 min(-1) vs 0.33 min(-1); k(ep), 0.36 min(-1) vs 0.62 min(-1)). MP MR imaging has greater accuracy in the detection of recurrent PCa after RT than T2-weighted imaging alone, with no additional benefit if DCE is added to T2-weighted imaging and DW imaging.

In Vivo Assessment of Ductal Carcinoma in Situ Grade: A Model Incorporating Dynamic Contrast-enhanced and Diffusion-weighted Breast MR Imaging Parameters

To develop a model incorporating dynamic contrast material-enhanced (DCE) and diffusion-weighted (DW) magnetic resonance (MR) imaging features to differentiate high-nuclear-grade (HNG) from non-HNG ductal carcinoma in situ (DCIS) in vivo. This HIPAA-compliant study was approved by the institutional review board and requirement for informed consent was waived. A total of 55 pure DCIS lesions (19 HNG, 36 non-HNG) in 52 women who underwent breast MR imaging at 1.5 T with both DCE and DW imaging (b = 0 and 600 sec/mm(2)) were retrospectively reviewed. The following lesion characteristics were recorded or measured: DCE morphology, DCE maximum lesion size, peak initial enhancement at 90 seconds, worst-curve delayed enhancement kinetics, apparent diffusion coefficient (ADC), contrast-to-noise ratio (CNR) at DW imaging with b values of 0 and 600 sec/mm(2), and T2 signal effects (measured with CNR at b = 0 sec/mm(2)). Univariate and stepwise multivariate logistic regression modeling was performed to identify MR imaging features that optimally discriminated HNG from non-HNG DCIS. Discriminative abilities of models were compared by using the area under the receiver operating characteristic curve (AUC). HNG lesions exhibited larger mean maximum lesion size (P = .02) and lower mean CNR for images with b value of 600 sec/mm(2) (P = .004), allowing discrimination of HNG from non-HNG DCIS (AUC = 0.71 for maximum lesion size, AUC = 0.70 for CNR at b = 600 sec/mm(2)). Differences in CNR for images with b value of 0 sec/mm(2) (P = .025) without corresponding differences in ADC values were observed between HNG and non-HNG lesions. Peak initial enhancement was the only kinetic variable to approach significance (P = .05). No differences in lesion morphology (P = .11) or worst-curve delayed enhancement kinetics (P = .97) were observed. A multivariate model combining CNR for images with b value of 600 sec/mm(2) and maximum lesion size most significantly discriminated HNG from non-HNG (AUC = 0.81). The preliminary findings suggest that DCE and DW MR imaging features may aid in identifying patients with high-risk DCIS. Further study may yield a model combining MR characteristics with histopathologic data to facilitate lesion-specific targeted therapies. © RSNA, 2012.

Renal Perfusion 3-T MR Imaging: A Comparative Study of Arterial Spin Labeling and Dynamic Contrast-enhanced Techniques

To investigate the feasibility of and correlation between arterial spin-labeling (ASL) and dynamic contrast material-enhanced (DCE) 3-T magnetic resonance (MR) imaging in the measurement of renal blood flow (RBF). The review board approved this study. Nineteen healthy volunteers (seven women, 12 men; age range, 25-68 years) were recruited, and each provided written informed consent. MR imaging was performed with a 3-T whole-body system. Each subject underwent back-to-back ASL and DCE MR imaging. Ten runs of ASL imaging were performed by using the pseudocontinuous tagging scheme, and each run required an 18-second breath hold. For DCE imaging, a gadopentetate dimeglumine bolus (0.0125 mmol per kilogram of body weight) was administrated intravenously in all subjects except two; in the latter subjects, a 0.025 mmol/kg gadopentetate dimeglumine bolus was administered to evaluate the T1 saturation effect. RBF was quantified with both techniques and in both the cortex and the medulla. Agreement was evaluated for RBF measurements obtained with ASL imaging and those obtained with DCE imaging by using correlation analysis. RBF was apparently overestimated with 0.025 mmol/kg gadopentetate dimeglumine, which is a concentration that is commonly adopted for 1.5-T DCE. RBF was 227 mL/100 mL/min ± 30 (standard deviation) in the cortex and 101 mL/100 mL/min ± 21 in the medulla, as measured with ASL imaging, and 272 mL/100 mL/min ± 60 in the cortex and 122 mL/100 mL/min ± 30 in the medulla, as measured with DCE imaging. In the cortex, measurements obtained with ASL and DCE imaging exhibited a linear correlation (r = 0.66; statistical power, 0.8 at the 5% significance level) and fair agreement (intraclass correlation coefficient, 0.41). ASL and DCE 3-T MR imaging are feasible in the quantification of cortical renal perfusion, yielding measurements that are correlated but not entirely comparable. Intermodality differences have yet to be solved.

Signal-to-Noise Ratio Improvement in Dynamic Contrast-enhanced CT and MR Imaging with Automated Principal Component Analysis Filtering

To develop a new automated filtering technique and to evaluate its ability to compensate for the known low contrast-to-noise ratio (CNR) in dynamic contrast material-enhanced (DCE) magnetic resonance (MR) and computed tomographic (CT) data, without substantial loss of information. Clinical data acquisition for this study was approved by the institutional review board. Principal component analysis (PCA) was combined with the fraction of residual information (FRI) criterion to optimize the balance between noise reduction efficiency and information conservation. The PCA FRI filter was evaluated in 15 DCE MR imaging data sets and 15 DCE CT data sets by two radiologists who performed visual analysis and quantitative assessment of noise reduction after filtering. Visual evaluation revealed a substantial noise reduction while conserving information in 90% of MR imaging cases and 87% of CT cases for image analysis and in 93% of MR imaging cases and 90% of CT cases for signal analysis. Efficient denoising enabled improvement in structure characterization in 60% of MR imaging cases and 77% of CT cases. After filtering, CNR was improved by 2.06 ± 0.89 for MR imaging (P < .01) and by 5.72 ± 4.82 for CT (P < .01). This PCA FRI filter demonstrates noise reduction efficiency and information conservation for both DCE MR data and DCE CT data. FRI analysis enabled automated optimization of the parameters for the PCA filter and provided an optional visual control of residual information losses. The robust and fast PCA FRI filter may improve qualitative or quantitative analysis of DCE imaging in a clinical context. http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.10100231/-/DC1.

Dysferlin-deficient Muscular Dystrophy: Gadofluorine M Suitability at MR Imaging in a Mouse Model

To compare the usefulness of gadofluorine M with that of Gadomer in assessment of dysferlin-deficient muscular dystrophy at 7.0-T magnetic resonance (MR) imaging. All experiments were approved by local review boards. SJL/J mice (n = 24) with dysferlin-deficient muscular dystrophy and C57BL/6 control mice (n = 24) were imaged at 12-15 weeks (young) or older than 30 weeks (old) by using dynamic contrast material-enhanced imaging with inversion-prepared steady-state free-precession sequence before, during, and after administration of gadofluorine M at 2 micromol or Gadomer at 4 micromol intravenously. After imaging, regions of interest were determined from the upper extremity and left ventricular chamber; fractional extravascular extracellular volume, v(e), and permeability surface tissue density product, PS rho, were measured by using a two-compartment pharmacokinetic model. The natural history of muscular dystrophy was assessed histologically in 70 mice (seven five-mouse groups each of SJL/J mice and of control mice) at 4-week intervals from 8 to 32 weeks. In addition, three SJL/J mice and three control mice at age 33 weeks were sacrificed, and fluorescence microscopy was performed for visualization of intravenously administered carbocyanine-labeled gadofluorine M in muscle cells. Statistical analysis was performed by using the t test. Gadofluorine M enhancement was significantly greater in skeletal muscle of 30-week-old mice with dysferlin-deficient muscular dystrophy, compared with control mice. Gadofluorine M demonstrated both increased rate of enhancement (PS rho sec(-1) +/- standard error of the mean: 0.004 e(-)(4) +/- 3 vs 0.002 e(-)(4) +/- 3; P < .05) and increased level of enhancement (v(e) +/- standard error of the mean: 0.035 +/- 0.004 vs 0.019 +/- 0.004; P < .05). Gadomer showed no differential enhancement in the two mouse groups. Histologic examination confirmed the presence of labeled gadofluorine M in muscle cells. Gadofluorine M-enhanced MR imaging may be of value in monitoring dysferlin-deficient muscular dystrophy disease progression in this animal model and could prove to be a useful tool in following the course of chronic muscle diseases in humans.

AAPM/RSNA physics tutorials for residents: MR imaging: brief overview and emerging applications.

Magnetic resonance (MR) imaging has become established as a diagnostic and research tool in many areas of medicine because of its ability to provide excellent soft-tissue delineation in different areas of interest. In addition to T1- and T2-weighted imaging, many specialized MR techniques have been designed to extract metabolic or biophysical information. Diffusion-weighted imaging gives insight into the movement of water molecules in tissue, and diffusion-tensor imaging can reveal fiber orientation in the white matter tracts. Metabolic information about the object of interest can be obtained with spectroscopy of protons, in addition to imaging of other nuclei, such as sodium. Dynamic contrast material-enhanced imaging and recently proton spectroscopy play an important role in oncologic imaging. When these techniques are combined, they can assist the physician in making a diagnosis or monitoring a treatment regimen. One of the major advantages of the different types of MR imaging is the ability of the operator to manipulate image contrast with a variety of selectable parameters that affect the kind and quality of the information provided. The elements used to obtain MR images and the factors that affect formation of an MR image include MR instrumentation, localization of the MR signal, gradients, k-space, and pulse sequences.