Conventional Dynamic Contrast-enhanced MRI Research Articles

Ultrafast DCE-MRI for discriminating pregnancy-associated breast cancer lesions from lactation related background parenchymal enhancement.

To investigate the utility of ultrafast dynamic-contrast-enhanced (DCE) MRI in visualization and quantitative characterization of pregnancy-associated breast cancer (PABC) and its differentiation from background-parenchymal-enhancement (BPE) among lactating patients. Twenty-nine lactating participants, including 10 PABC patients and 19 healthy controls, were scanned on 3-T MRI using a conventional DCE protocol interleaved with a golden-angle radial sparse parallel (GRASP) ultrafast sequence for the initial phase. The timing of the visualization of PABC lesions was compared to lactational BPE. Contrast-noise ratio (CNR) was compared between the ultrafast and conventional DCE sequences. The differences in each group's ultrafast-derived kinetic parameters including maximal slope (MS), time to enhancement (TTE), and area under the curve (AUC) were statistically examined using the Mann-Whitney test and receiver operator characteristic (ROC) curve analysis. On ultrafast MRI, breast cancer lesions enhanced earlier than BPE (p < 0.0001), enabling breast cancer visualization freed from lactation BPE. A higher CNR was found for ultrafast acquisitions vs. conventional DCE (p < 0.05). Significant differences in AUC, MS, and TTE values were found between the tumor and BPE (p < 0.05), with ROC-derived AUC of 0.86 ± 0.06, 0.82 ± 0.07, and 0.68 ± 0.08, respectively. The BPE grades of the lactating PABC patients were reduced as compared with the healthy lactating controls (p < 0.005). Ultrafast DCE MRI allows BPE-free visualization of lesions, improved tumor conspicuity, and kinetic quantification of breast cancer during lactation. Implementation of this method may assist in the utilization of breast MRI for lactating patients. The ultrafast sequence appears to be superior to conventional DCE MRI in the challenging evaluation of the lactating breast. Thus, supporting its possible utilization in the setting of high-risk screening during lactation and the diagnostic workup of PABC. • Differences in the enhancement slope of cancer relative to BPE allowed the optimal visualization of PABC lesions on mid-acquisitions of ultrafast DCE, in which the tumor enhanced prior to the background parenchyma. • The conspicuity of PABC lesions on top of the lactation-related BPE was increased using an ultrafast sequence as compared with conventional DCE MRI. • Ultrafast-derived maps provided further characterization and parametric contrast between PABC lesions and lactation-related BPE.

Dynamic contrast-enhanced MRI and Apparent diffusion coefficient mapping in the characterization of Palpable breast lesions: A prospective observational study

BackgroundBreast MRI is the imaging modality of choice in patients with palpable breast lesions unequivocal on mammography and ultrasonography. This study aims to evaluate the role of dynamic contrast-enhanced MRI (DCE-MRI) and apparent diffusion coefficient mapping in the characterization and differentiation of various palpable breast lesions. This prospective observational study was conducted in a tertiary care hospital between July 2019 and June 2021. Sixty-six patients with palpable breast lesions were undergone MRI scans of the breasts. The various palpable breast lesions were categorized according to the 5th edition BI-RADS lexicon. The sensitivity of ADC mapping and DCE-MRI was determined for differentiation of various palpable breast lesions according to the BI-RADS category and gold standard histopathological findings.ResultsOf 66 patients with palpable breast lesions, 36 patients (54.5%) were benign and 30 patients (45.5%) were malignant lesions. Malignant palpable breast lesions had a mean ADC value of 0.939 ± 0.166[SD] × 10−3 mm2/s, and benign lesions had 1.891 ± 0.524[SD] × 10−3 mm2/s where unpaired Student t-test showed statistically significant difference of P value 0.0005. BI-RADS 2 lesions had a mean ADC value of 2.056 ± 0.471[SD] × 10−3 mm2/s, BI-RADS 3 had 1.314 ± 0.151[SD] × 10−3 mm2/s, BI-RADS 4 had 0.935 ± 0.119[SD] × 10−3 mm2/s, and BI-RADS 5 had 0.930 ± 0.943[SD] × 10−3 mm2/s. BI-RADS 2 category showed optimal cutoff mean ADC of 1.508 × 10−3 mm2/s with a sensitivity of 85.7% and specificity of 94.7%, BI-RADS 3 lesions had 1.208 × 10−3 mm2/s with a sensitivity of 75% and specificity of 55.2%, BI-RADS 4 lesions had 1.064 × 10−3 mm2/s with a sensitivity 80% and specificity of 67.9%, and BI-RADS 5 lesions had 1.013 × 10−3 mm2/s with a sensitivity of 80% and specificity of 82.6%.ConclusionsBreast MRI is superior to the other imaging modalities for the characterization and differentiation of various palpable breast lesions. The combined use of ADC mapping and DCE-MRI had more sensitivity than conventional MRI, ADC mapping or DCE-MRI alone.

Predicting Upgrade of Ductal Carcinoma In Situ to Invasive Breast Cancer at Surgery With Ultrafast Imaging.

BACKGROUND. Biopsy-proven ductal carcinoma in situ (DCIS) lesions are often upgraded to invasive cancer at surgery. Therefore, accurate prediction of the likelihood of invasion is helpful for surgical planning, including the need for sentinel lymph node biopsy (SLNB). OBJECTIVE. The purpose of the present study was to investigate whether kinetic features of clinically available ultrafast MRI (UF-MRI) can predict upgrade of biopsy-proven DCIS to invasive cancer at surgical excision. METHODS. Consecutive patients with biopsy-proven pure DCIS lesions who underwent UF-MRI with conventional dynamic contrast-enhanced MRI (DCE-MRI) and subsequently underwent surgery between August 2019 and January 2021 were identified. Patient and lesion characteristics, biopsy method and pathology, and lesion features on mammography, ultrasound, DCE-MRI, and UF-MRI were assessed to determine predictors of upgrade to invasive cancer. The Fisher exact test and Kruskal-Wallis test were used for association analysis. RESULTS. In 68 patients (median age, 52.0 years; range, 31-79 years) with 68 biopsy-proven pure DCIS lesions, 26 lesions (38%) were upgraded from in situ to invasive cancer. An upgrade of DCIS to invasive cancer was significantly associated with a shorter time to enhancement (TTE) on preoperative UF-MRI (p = .03), with a threshold of 11 seconds providing maximum specificity (50%) and sensitivity (76%) for upgrade. Larger lesion size on DCE-MRI (p = .001) and mammography (p = .04) was also significantly associated with upgrade; an optimal predictive threshold of 4.4 cm on DCE-MRI yielded sensitivity of 88% and specificity of 56%. No other specific variables were significantly associated with upgrade after surgery. Logistic regression of selected features combined with TTE produced a higher AUC (0.85) in predicting upgrade to invasive disease than did each factor alone, but this result was not statistically significant. CONCLUSION. Preoperative UF-MRI TTE and lesion size on DCE-MRI and mammography show potential in predicting upgrade of DCIS to invasive cancer at surgery. CLINICAL IMPACT. UF-MRI provides useful information that can be used in surgical planning, including determination of the need to perform SLNB.

Comparison of Ultrafast Dynamic Contrast-Enhanced (DCE) MRI with Conventional DCE MRI in the Morphological Assessment of Malignant Breast Lesions

Ultrafast (UF) dynamic contrast-enhanced (DCE)-MRI offers the potential for a faster and, therefore, less expensive examination of breast lesions; however, there are no reports that have evaluated whether UF DCE-MRI can be used the same as conventional DCE-MRI in the reading of morphological information. This study evaluated the agreement in morphological information obtained from malignant breast mass lesions between UF DCE-MRI and conventional DCE-MRI. UF DCE-MRI data were obtained over the first 60 s post-contrast injection, followed by the conventional DCE images. Two readers evaluated the size and morphology of the lesions in the final phase of the UF DCE-MRI and the early phase of the conventional DCE-MRI. Inter-method agreement in morphological information was evaluated for the two readers using the intraclass correlation coefficient for size, and the kappa statistics for the morphological descriptors. Differences in the proportion of each descriptor were examined using Fisher's test of independence. Most inter-method agreements were higher than substantial. UF DCE-MRI showed a circumscribed margin and homogeneous enhancement more often than conventional imaging. However, the percentages of readings showing the same morphology assessment between the UF DCE-MRI and conventional DCE-MRI were 71.2% (136/191) for Reader 1 and 69.1% (132/191) for Reader 2. We conclude that UF DCE-MRI may replace conventional DCE-MRI to evaluate the morphological information of malignant breast mass lesions.

Conventional, diffusion, and dynamic contrast-enhanced MRI findings for differentiating metaplastic Warthin's tumor of the parotid gland.

The purpose of this study was to explore conventional, diffusion, and dynamic contrast-enhanced MRI (DCE-MRI) characteristics for differentiating metaplastic Warthin's tumor (MWT) from other tumor types of the parotid gland, including non-metaplastic Warthin's tumor (non-MWT), pleomorphic adenoma (PA), and malignant tumor (MT). A total of 178 patients with histologically proven tumors of the parotid gland, including 21 MWTs, 49 non-MWTs, 66 PAs, and 42 MTs, were enrolled in the study. Conventional MRI was performed in all patients. One hundred and fifty patients had preoperative diffusion-weighted MR imaging (DWI), and 62 patients had preoperative DCE-MRI. The differences in the conventional, DCE-MRI, and DWI records between MWTs and the other three tumor types were statistically evaluated. Compared with non-MWTs and PAs, there was a statistically significant difference in circumscription (p < 0.01). The ill-defined circumscription was more common in MWTs than non-MWTs and PAs. Compared with PAs, there was a statistically significant difference in morphology (p < 0.05). The lobulated morphology was more common in PAs than MWTs. Compared with PAs and MTs, there was a statistically significant difference in the T2 signal of the solid component (p < 0.01). The T2 moderate intensity of solid components was more common in MWTs than PAs and MTs. The solid components of PAs mostly showed hyperintense on T2-weighted imaging. Cyst/necrosis was more common in MWTs than PAs and MTs. Hyperintense of cyst/necrosis was more common in MWTs and non-MWTs. With respect to contrast enhancement, 52.4% MWTs exhibited moderate or marked enhancement, and most non-MWTs (81.6%) exhibited mild enhancement. Most PAs (84.8%) exhibited marked enhancement. The mean ADC value of MWTs (0.94 × 10-3 ± 0.11 mm2/s) was significantly lower than that of the PAs (1.60 × 10-3 ± 0.17 mm2/s) (p < 0.001). On DCE-MRI, six of eight MWTs demonstrated TIC of type B. Although MWT is rare, conventional MRI characteristics, DWI and DCE-MRI can provide useful information for differentiating MWT from other parotid mass.

Functional Tumor Volume by Fast Dynamic Contrast-Enhanced MRI for Predicting Neoadjuvant Systemic Therapy Response in Triple-Negative Breast Cancer.

Dynamic contrast-enhanced (DCE) MRI is useful for diagnosis and assessment of treatment response in breast cancer. Fast DCE MRI offers a higher sampling rate of contrast enhancement curves in comparison to conventional DCE MRI, potentially characterizing tumor perfusion kinetics more accurately for measurement of functional tumor volume (FTV) as a predictor of treatment response. To investigate FTV by fast DCE MRI as a predictor of neoadjuvant systemic therapy (NAST) response in triple-negative breast cancer (TNBC). Prospective. Sixty patients with biopsy-confirmed TNBC between December 2016 and September 2020. A 3.0 T/3D fast spoiled gradient echo-based DCE MRI ASSESSMENT: Patients underwent MRI at baseline and after four cycles (C4) of NAST, followed by definitive surgery. DCE subtraction images were analyzed in consensus by two breast radiologists with 5 (A.H.A.) and 2 (H.S.M.) years of experience. Tumor volumes (TV) were measured on early and late subtractions. Tumors were segmented on 1 and 2.5-minute early phases subtractions and FTV was determined using optimized signal enhancement thresholds. Interpolated enhancement curves from segmented voxels were used to determine optimal early phase timing. Tumor volumes were compared between patients who had a pathologic complete response (pCR) and those who did not using the area under the receiver operating curve (AUC) and Mann-Whitney U test. About 26 of 60 patients (43%) had pCR. FTV at 1 minute after injection at C4 provided the best discrimination between pCR and non-pCR, with AUC (95% confidence interval [CI])=0.85 (0.74,0.95) (P < 0.05). The 1-minute timing was optimal for FTV measurements at C4 and for the change between C4 and baseline. TV from the early phase at C4 also yielded a good AUC (95%CI) of 0.82 (0.71,0.93) (P < 0.05). FTV and TV measured at 1 minute after injection can predict response to NAST in TNBC. 1 TECHNICAL EFFICACY: 4.

Background parenchymal enhancement and its effect on lesion detectability in ultrafast dynamic contrast-enhanced MRI

PurposeBackground parenchymal enhancement (BPE) often affects interpretation of dynamic contrast-enhanced (DCE) MRI. There is limited evidence that reduced BPE is a feature of ultrafast DCE (UF-DCE) MRI. We aimed to evaluate the effect of BPE levels on lesion detectability on UF-DCE MRI in comparison with conventional DCE MRI. MethodMRIs of 70 patients with histologically proven breast lesions were retrospectively evaluated. The total number of analyzed lesions was 84 (56 malignant and 28 benign). Using 3 T MRI, 20 phases of UF-DCE MRI based on the three-dimensional gradient-echo VIBE sequence combined with a compressed sensing reconstruction were acquired followed by conventional DCE MRI. Three maximum intensity projection (MIP) images were generated from the 12th phase, the 20th phase of UF-DCE MRI and the initial phase of conventional DCE MRI. Two radiologists independently evaluated the degree of BPE and lesion detectability of the three MIP images for each breast with histologically confirmed lesions. The degree of BPE was scored on a four-point scale and lesion detectability (conspicuity and confidence levels) was scored on a three-point scale. Data were analyzed using the Wilcoxon signed-rank test with Bonferroni correction. ResultsBPE was lower on UF-DCE MRI than on conventional DCE MRI. Lesion detectability was higher on UF-DCE MRI among patients with higher BPE on conventional DCE MRI or premenopausal women. ConclusionsImages with lower BPE can be achieved using UF-DCE MRI and may be advantageous when assessing breast lesions among patients with higher BPE or premenopausal women.

The value of tumor hemodynamics and morphological features in predicting the postoperative recurrence time of breast cancer based on dynamic contrast-enhanced MRI

Objective To investigate the value of tumor hemodynamics and morphological features from conventional dynamic contrast-enhanced MRI (DCE-MRI) scan before surgery in predicting postoperative recurrence time in breast cancer patients. Methods A retrospective analysis of 58 patients with breast cancer who had recurred after operation from November 2012 to December 2014 in Liaoning Cancer Hospital was performed. According to the recurrence time, the patients were divided into early recurrence group (≤2 years after surgery, 33 cases) and late recurrence group (>2 years after surgery, 25 cases). All patients underwent routine DCE-MRI scans before surgery, and hemodynamic features of the three-dimensional volume of the tumor and the morphological and textural features of the tumor in each phase were extracted by computer. The counts and measurement data of patients in early recurrence group and late recurrence group were compared by Fisher′s exact probability method and Mann-Whitney U test, and receiver operating characteristic (ROC) curves were drawn. The multivariate logistic regression was used to calculate the combined efficacy in predicting early recurrence and late recurrence. Kaplan-Meier method was used to analyze the survival prognosis, and Log-Rank test was used to compare the differences in survival curves between groups. Results There was no significant difference in background parenchymal enhancement, lesion margin, lesion internal enhancement characteristics, lesion morphology, time-signal intensity curve type and the degree of whole-breast vascularity increase between early recurrence and late recurrence groups (P>0.05).There were significant differences in the maximum concentration of contrast (Max Conc), the area under the time signal curve (AUC) and the maximum slope value of the time signal curve (Max Slope) (P<0.05). Comparative analysis of the radiomics parameters of 8 phases DCE-MRI found that the sphericity of morphological characteristic parameters in the phase 3 was statistically different between the early recurrence and late recurrence groups (P=0.03). Area under the ROC curve of AUC, Max Conc, Max Slope and parameter sphericity of phase 3 morphological characteristics for predicting early and late recurrence were 0.664, 0.659, 0.684 and 0.670, respectively. The area under the ROC combined with the above four parameters for prediction was 0.765, with a specificity of 63.6% and a sensitivity of 84.0%; the predictive efficacy was higher than that of univariate. Fifty-eight patients were followed up for 17 to 64 months with a median follow-up of 47 months. The disease-free survival and overall survival in the early recurrence group were significantly lower than those in the late recurrence group, and the difference was statistically significant (P<0.05). Conclusion It is of certain value to predict the postoperative recurrence time of breast cancer based on the tumor hemodynamic characteristics combined with morphological characteristics from preoperative non-invasive conventional DCE-MRI. Key words: Breast neoplasms; Magnetic resonance imaging; Texture analysis; Recurrence

Diagnostic Performance of Mass Enhancement on Dynamic Contrast-Enhanced MRI for Predicting Clinically Significant Peripheral Zone Prostate Cancer.

OBJECTIVE. Current criteria for positive findings on dynamic contrast-enhanced MRI (DCE-MRI) are unclear. We compared the diagnostic performance of mass enhancement on DCE-MRI versus conventional DCE-MRI criteria for identifying clinically significant prostate cancer (csPCa) in the peripheral zone (PZ). MATERIALS AND METHODS. A total of 173 consecutive patients with MRI- and surgically proven prostate cancer (PCa) were evaluated. Two readers independently interpreted DCE-MRI examinations of the PZ. Criteria denoting a positive DCE-MRI examination included conventional criteria from the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) and mass enhancement. The diagnostic performance of and interreader agreement for the two types of enhancement criteria in identifying csPCa in the PZ that met Epstein criteria were investigated. RESULTS. The proportion of csPCa in the PZ was 69.3% (120/173). For both readers, the specificity and positive predictive value of mass enhancement were increased compared with conventional enhancement criteria (specificity, 75.5% vs 5.7% [for reader 1] and 84.9% vs 30.2% [for reader 2], respectively; positive predictive value, 87.1% vs 70.6% [for reader 1] and 91.5% vs 75.3% [for reader 2], respectively). The AUC value of mass enhancement was higher than that of conventional criteria (for reader 1, 0.744 [95% CI, 0.672-0.807] vs 0.528 [95% CI, 0.451-0.605] [p < 0.001], respectively; for reader 2, 0.783 [95% CI, 0.714-0.842] vs 0.602 [95% CI, 0.497-0.700] [p < 0.001], respectively). The weighted kappa value for agreement between the two readers was 0.206 for conventional criteria and 0.613 for mass enhancement. CONCLUSION. PZ lesions with mass enhancement on DCE-MRI are more likely to be csPCa. This enhancement pattern may need to be considered as one of the criteria in PI-RADS.

The additional utility of ultrafast MRI on conventional DCE-MRI in evaluating preoperative MRI of breast cancer patients

PurposeTo investigate whether the additional use of ultrafast MRI can improve the diagnostic performance of conventional dynamic contrast-enhanced MRI (DCE-MRI) in evaluating MRI-detected lesions in breast cancer patients. MethodsThis retrospective study enrolled 101 consecutive breast cancer patients with 202 breast lesions (62 benign and 140 malignant) who underwent preoperative DCE-MRI with ultrafast imaging (9 image sets with 6.5-second temporal resolution). Two reviewers assessed the BI-RADS categories of breast lesions using conventional DCE-MRI and assessed the following parameters using the ultrafast MRI: initial enhancement phase, maximum relative enhancement, slope, and maximum slope (slopemax) on the kinetic curve. Interobserver agreement was analyzed between the two reviewers. The ultrafast MRI parameters were compared between benign and malignant tumors, and cut-off values were determined. For 97 additional MRI-detected lesions, the BI-RADS category was re-assessed using cut-off values, and the diagnostic performance was compared between the conventional DCE-MRI and the combined conventional and ultrafast DCE-MRI. ResultsAll ultrafast MRI parameters differed significantly between malignant and benign tumors (p < 0.001). Initial enhancement phase by reviewer and slopemax were the top two parameters showing significant differences between benign and malignant tumors with high reliability. With the use of cut-off values for initial enhancement phase (≤phase 2) and slopemax (>9.8%/sec), the specificity of conventional DCE-MRI was significantly increased (29.4% vs 64.7%, p < 0.001) without significant loss of sensitivity (100% vs 88.2%, p = 0.157) in evaluating masses. ConclusionsThe additional use of ultrafast MRI can improve the specificity of conventional DCE-MRI when evaluating MRI-detected masses in breast cancer patients.

The diagnostic value of combining conventional, diffusion-weighted imaging and dynamic contrast-enhanced MRI for salivary gland tumors.

To determine the diagnostic value of combining conventional MRI, diffusion-weighted imaging (DWI) and dynamic contrast enhanced MRI (DCE-MRI) in salivary gland tumors. 45 patients with salivary gland tumors were evaluated with conventional MRI, DWI and DCE-MRI prior to surgery and confirmed by pathologic findings. The apparent diffusion coefficient (ADC) was calculated from DWI that was obtained with a factor of 0 and 1000 smm-2. A time-intensity curve (TIC) was obtained from DCE-MRI. In conventional MRI, benign tumors often showed well-defined and clear margins, malignant tumors showed irregular margins or infiltration into the surrounding tissue. There were significant differences with regard to the ADC values between pleomorphic adenoma (1.72 ± 0.29×10-3 mm2s-1) and malignant tumors (0.95 ± 0.09×10-3 mm2s-1, p < 0.05) and between adenolymphoma (0.74 ± 0.05×10-3 mm2s-1) and malignant tumors (p < 0.05). However, there was no significant differences in term of the ADC values between benign tumors (1.33 ± 0.52×10-3 mm2s-1) and malignant tumors. DCE-MRI showed benign tumors with A-type, B-type and D-type of TICs, and the malignant tumors with C-type TICs. A combination of all of these parameters yielded sensitivity, specificity, accuracy, and positive and negative predictive values of 90%, 97%, 95%, 90 and 97%, respectively. An evaluation combining MRI morphologic findings and functional MRI (ADCs and TIC) appears to be useful in differentiating benign from malignant tumors in salivary gland tumors. Advances in knowledge: The study firstly dealt with the combination of conventional MRI, DWI-MRI with DCE-MRI in salivary gland tumors.

Textural features of dynamic contrast-enhanced MRI derived model-free and model-based parameter maps in glioma grading.

Presurgical glioma grading by dynamic contrast-enhanced MRI (DCE-MRI) has unresolved issues. The aim of this study was to investigate the ability of textural features derived from pharmacokinetic model-based or model-free parameter maps of DCE-MRI in discriminating between different grades of gliomas, and their correlation with pathological index. Retrospective. Forty-two adults with brain gliomas. 3.0T, including conventional anatomic sequences and DCE-MRI sequences (variable flip angle T1-weighted imaging and three-dimensional gradient echo volumetric imaging). Regions of interest on the cross-sectional images with maximal tumor lesion. Five commonly used textural features, including Energy, Entropy, Inertia, Correlation, and Inverse Difference Moment (IDM), were generated. All textural features of model-free parameters (initial area under curve [IAUC], maximal signal intensity [Max SI], maximal up-slope [Max Slope]) could effectively differentiate between grade II (n = 15), grade III (n = 13), and grade IV (n = 14) gliomas (P < 0.05). Two textural features, Entropy and IDM, of four DCE-MRI parameters, including Max SI, Max Slope (model-free parameters), vp (Extended Tofts), and vp (Patlak) could differentiate grade III and IV gliomas (P < 0.01) in four measurements. Both Entropy and IDM of Patlak-based Ktrans and vp could differentiate grade II (n = 15) from III (n = 13) gliomas (P < 0.01) in four measurements. No textural features of any DCE-MRI parameter maps could discriminate between subtypes of grade II and III gliomas (P < 0.05). Both Entropy and IDM of Extended Tofts- and Patlak-based vp showed highest area under curve in discriminating between grade III and IV gliomas. However, intraclass correlation coefficient (ICC) of these features revealed relatively lower inter-observer agreement. No significant correlation was found between microvascular density and textural features, compared with a moderate correlation found between cellular proliferation index and those features. Textural features of DCE-MRI parameter maps displayed a good ability in glioma grading. 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1099-1111.

Large coverage black-bright blood interleaved imaging sequence (LaBBI) for 3D dynamic contrast-enhanced MRI of vessel wall.

To propose a large coverage black-bright blood interleaved imaging sequence (LaBBI) for 3D dynamic contrast-enhanced MRI (DCE-MRI) of the vessel wall. LaBBI consists of a 3D black-blood stack-of-stars golden angle radial acquisition with high spatial resolution for vessel wall imaging and a 2D bright-blood Cartesian acquisition with high temporal resolution for arterial input function estimation. The two acquisitions were performed in an interleaved fashion within a single scan. Simulations, phantom experiments, and in vivo tests in three patients were performed to investigate the feasibility and performance of the proposed LaBBI. In simulation tests, the estimated Ktrans and vp by LaBBI were more accurate than conventional bright-blood DCE-MRI with lower root mean square error in all the tested conditions. In phantom test, no signal interference was found on the 2D scan in LaBBI. Pharmacokinetic analysis of the patients' data acquired by LaBBI showed that Ktrans was higher in fibrous tissue (0.0717 ± 0.0279 min-1 ), while lower in necrotic core (0.0206 ± 0.0040 min-1 ) and intraplaque hemorrhage (0.0078 ± 0.0007 min-1 ), compared with normal vessel wall (0.0273 ± 0.0052 min-1 ). The proposed LaBBI sequence, with high spatial and temporal resolution, and large coverage blood suppression, was promising to probe the perfusion properties of vessel wall lesions. Magn Reson Med 79:1334-1344, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Studies of the perfusion and permeability characteristic in the brain lesions of patients with relapsing-remitting multiple sclerosis using dynamic contrast-enhanced MRI

Objective To evaluate dynamic contrast-enhanced MRI (DCE-MRI) with Patlak model for depicting the perfusion and permeability characteristics of lesions and normal-appearing white matter (NAWM) regions in patients with relapsing-remitting multiple sclerosis (RRMS). Methods Twenty-three patients with clinical confirmed RRMS were retrospectively analyzed, who had underwent conventional MRI and DCE-MRI using a 3.0 T MR scanner . The clinical characteristics and imaging data were collected. Post-processing was performed using the Patlak model. Volume transfer constant (Ktrans), fractional plasma volume (Vp) and perfusion parameters including cerebral blood flow (CBF) and cerebral blood volume (CBV) were represented as median and interquartile range(IQR). The four parameters of non-enhanced(NE) lesions, NAWM regions located close to NE lesions(NAWM close) and NAWM regions located far from NE lesions (NAWM far) were compared using the Kruskal-Wallis H rank sum test. Artificial color mappings were also proceeded. Results MR imaging biomarkers Ktrans was 0.132(0.064, 0.233) min-1 for NE lesions, 0.111 (0.060, 0.233) min-1 for NAWM close and 0.077(0.044, 0.185) min-1 for NAWM far, respectively. CBV was 10.660(5.555, 22.193) ml·100 g-1 for NE lesions, 9.359(4.883, 16.290) ml·100 g-1 for NAWM close, 6.814 (4.699, 13.623) ml·100 g-1 for NAWM far, respectively. Ktrans and CBV of NE lesions was significantly higher than that of NAWM far(χ2=7.582, P 0.05). Conclusion DCE-MRI with Patlak model can measure perfusion and permeability characteristics and hemodynamic abnormalities of NE lesions and NAWM regions in patients with multiple sclerosis. Key words: Multiple sclerosis, relapsing-remitting; Magnetic resonance imaging; Diagnosis, differential

Diffusion magnetic resonance imaging of breast lesions: Initial experience at Alexandria University

ObjectiveThe purpose of our study was to investigate whether adding diffusion weighted imaging (DWI) to dynamic contrast-enhanced MRI (DCE-MRI) could improve specificity and the positive predictive value (PPV) of breast MRI in differentiating benign and malignant focal breast mass lesions. Materials and methodsThe prospective study included 71 females with 103 focal breast lesions on DCE-MRI who underwent subsequent biopsy. DWI was acquired during diagnostic breast MRI using b = 0, 400 and 800 s/mm2. Apparent diffusion coefficient (ADC) values were compared for benign and malignant lesions. Sensitivity and PPV were calculated for DCE-MRI alone (based on biopsy recommendations) and DCE-MRI plus DWI (adding an ADC threshold) for the same set of lesions. ResultsOn pathological basis, 57 out of 103 focal lesions were benign and the remaining revealed, 45 were malignant and one borderline. Malignant lesions exhibited lower mean ADC (<1.3 × 10−3 mm2/s) than benign lesions (>1.3 × 10−3 mm2/s). Applying an ADC threshold of 1.3 × 10−3 mm2/s sensitivity increased (on conventional DCE-MRI basis) from 86.95% up to 93.47% and the specificity from 91.22% to 96.49% in detection of malignancy with PPV of 95.55% in comparison to 86.95% for enhancement kinetics alone, which would have avoided biopsy for 10.5% (6/57) of benign lesions without missing any cancers. ConclusionDWI shows potential for improving the PPV of breast MRI for detection of malignant breast lesions. RecommendationFurthermore, larger studies should be made to use it as a monitor for tumor response to chemotherapy.

Pixel-by-pixel analysis of DCE MRI curve patterns and an illustration of its application to the imaging of the musculoskeletal system

Dynamic contrast enhanced (DCE) MRI is a widespread method that has found broad application in the imaging of the musculoskeletal (MSK) system. A common way of analyzing DCE MRI images is to look at the shape of the time-intensity curve (TIC) in pixels selected after drawing an ROI in a highly enhanced area. Although often applied to a number of MSK affections, shape analysis has so far not led to a unanimous correlation between these TIC patterns and pathology. We hypothesize that this might be a result of the subjective ROI approach. To overcome the shortcomings of the ROI approach (sampling error and interuser variability, among others), we created a method for a fast and simple classification of DCE MRI where time-curve enhancement shapes are classified pixel by pixel according to their shape. The result of the analysis is rendered in multislice, 2D color-coded images. With this approach, we show not only that differences on a short distance range of the TIC patterns are significant and cannot be appreciated with a conventional ROI analysis but also that the information that shape maps and conventional standard DCE MRI parameter maps convey are substantially different.