Dataset Information

Breast Dynamic Contrast Enhanced MRI: Fibrocystic Changes Presenting as a Non-mass Enhancement Mimicking Malignancy.

ABSTRACT: BACKGROUND:We aimed to analyse the morphokinetic features of breast fibrocystic changes (nonproliferative lesions, proliferative lesions without atypia and proliferative lesions with atypia) presenting as a non-mass enhancement (NME)in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) examination. PATIENTS AND METHODS:Forty-six patients with histologically proven fibrocystic changes (FCCs) were retrospectively reviewed, according to Breast Imaging Reporting and Data System (BI-RADS) lexicon. Prior to DCE-MRI examination, a unilateral breast lesion suspicious of malignancy was detected clinically, on mammography or breast ultrasonography. RESULTS:The predominant features of FCCs presenting as NME in DCE-MRI examination were: unilateral regional or diffuse distribution (in 35 patients or 76.1%), heterogeneous or clumped internal pattern of enhancement (in 36 patients or 78.3%), plateau time-intensity curve (in 25 patients or 54.3%), moderate or fast wash-in (in 31 patients or 67.4%).Nonproliferative lesions were found in 11 patients (24%), proliferative lesions without atypia in 29 patients (63%) and lesions with atypia in six patients (13%), without statistically significant difference of morphokinetic features, except of the association of clustered microcysts with proliferative dysplasia without atypia. CONCLUSIONS:FCCs presenting as NME in DCE-MRI examination have several morphokinetic features suspicious of malignancy, therefore requiring biopsy (BI-RADS 4). Nonproliferative lesions, proliferative lesions without atypia and proliferative lesions with atypia predominantly share the same predefined DCE-MRI morphokinetic features.

SUBMITTER: Milosevic ZC

PROVIDER: S-EPMC5514652 | biostudies-other | 2017 Jun

REPOSITORIES: biostudies-other

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Breast Dynamic Contrast Enhanced MRI: Fibrocystic Changes Presenting as a Non-mass Enhancement Mimicking Malignancy.

Milosevic Zorica C ZC Nadrljanski Mirjan M MM Milovanovic Zorka M ZM Gusic Nina Z NZ Vucicevic Slavko S SS Radulovic Olga S OS

Radiology and oncology 20170507 2

<h4>Background</h4>We aimed to analyse the morphokinetic features of breast fibrocystic changes (nonproliferative lesions, proliferative lesions without atypia and proliferative lesions with atypia) presenting as a non-mass enhancement (NME)in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) examination.<h4>Patients and methods</h4>Forty-six patients with histologically proven fibrocystic changes (FCCs) were retrospectively reviewed, according to Breast Imaging Reporting and Data S ...[more]

PMID: 28740447

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Project description:BACKGROUND:Available data proving the value of DWI for breast cancer diagnosis is mainly for enhancing masses; DWI may be less sensitive and specific in non-mass enhancement (NME) lesions. The objective of this study was to assess the diagnostic accuracy of DWI using different ROI measurement approaches and ADC metrics in breast lesions presenting as NME lesions on dynamic contrast-enhanced (DCE) MRI. METHODS:In this retrospective study, 95 patients who underwent multiparametric MRI with DCE and DWI from September 2007 to July 2013 and who were diagnosed with a suspicious NME (BI-RADS 4/5) were included. Twenty-nine patients were excluded for lesion non-visibility on DWI (n?=?24: 12 benign and 12 malignant) and poor DWI quality (n?=?5: 1 benign and 4 malignant). Two readers independently assessed DWI and DCE-MRI findings in two separate randomized readings using different ADC metrics and ROI approaches. NME lesions were classified as either benign (>?1.3?×?10-3?mm2/s) or malignant (??1.3?×?10-3?mm2/s). Histopathology was the standard of reference. ROC curves were plotted, and AUCs were determined. Concordance correlation coefficient (CCC) was measured. RESULTS:There were 39 malignant (59%) and 27 benign (41%) lesions in 66 (65 women, 1 man) patients (mean age, 51.8?years). The mean ADC value of the darkest part of the tumor (Dptu) achieved the highest diagnostic accuracy, with AUCs of up to 0.71. Inter-reader agreement was highest with Dptu ADC max (CCC 0.42) and lowest with the point tumor (Ptu) ADC min (CCC?=?-?0.01). Intra-reader agreement was highest with Wtu ADC mean (CCC?=?0.44 for reader 1, 0.41 for reader 2), but this was not associated with the highest diagnostic accuracy. CONCLUSIONS:Diagnostic accuracy of DWI with ADC mapping is limited in NME lesions. Thirty-one percent of lesions presenting as NME on DCE-MRI could not be evaluated with DWI, and therefore, DCE-MRI remains indispensable. Best results were achieved using Dptu 2D ROI measurement and ADC mean.

Project description:ObjectivesTo determine the added discriminative value of detailed quantitative characterization of background parenchymal enhancement in addition to the tumor itself on dynamic contrast-enhanced (DCE) MRI at 3.0 Tesla in identifying "triple-negative" breast cancers.Materials and methodsIn this Institutional Review Board-approved retrospective study, DCE-MRI of 84 women presenting 88 invasive carcinomas were evaluated by a radiologist and analyzed using quantitative computer-aided techniques. Each tumor and its surrounding parenchyma were segmented semi-automatically in 3-D. A total of 85 imaging features were extracted from the two regions, including morphologic, densitometric, and statistical texture measures of enhancement. A small subset of optimal features was selected using an efficient sequential forward floating search algorithm. To distinguish triple-negative cancers from other subtypes, we built predictive models based on support vector machines. Their classification performance was assessed with the area under receiver operating characteristic curve (AUC) using cross-validation.ResultsImaging features based on the tumor region achieved an AUC of 0.782 in differentiating triple-negative cancers from others, in line with the current state of the art. When background parenchymal enhancement features were included, the AUC increased significantly to 0.878 (p<0.01). Similar improvements were seen in nearly all subtype classification tasks undertaken. Notably, amongst the most discriminating features for predicting triple-negative cancers were textures of background parenchymal enhancement.ConclusionsConsidering the tumor as well as its surrounding parenchyma on DCE-MRI for radiomic image phenotyping provides useful information for identifying triple-negative breast cancers. Heterogeneity of background parenchymal enhancement, characterized by quantitative texture features on DCE-MRI, adds value to such differentiation models as they are strongly associated with the triple-negative subtype. Prospective validation studies are warranted to confirm these findings and determine potential implications.

Project description:PurposeThe present study aimed to determine the reliable imaging features to distinguish atypical hepatocellular carcinoma (HCC) with peripheral rim-like enhancement from intrahepatic mass-forming cholangiocarcinoma (IMCC) on contrast-enhanced magnetic resonance imaging (MRI).MethodsA total of 168 patients (130 male, 57.10 ± 10.53 years) pathological confirmed HCC or IMCC who underwent contrast-enhanced MRI between July 2019 and February 2022 were retrospectively included. Univariate and multivariate logistic regression analyses were used to determine independent differential factors for distinguishing HCC from IMCC, and the model was established. Bootstrap resampling 1000 times was used to verify the model, which was visualized by nomograms. The predictive performance of the model was evaluated based on discrimination, calibration, and clinical utility.ResultsRadiological capsule (OR 0.024, 95% CI: 0.006, 0.095, P<0.001), heterogeneous signal intensity (SI) on T1WI (OR 0.009, 95%CI: 0.001,0.056, P<0.001) were independent differential factors for predicting HCC over IMCC. A lobulated contour (OR 11.732, 95%CI: 2.928,47.007, P = 0.001), target sign on DP (OR 14.269, 95%CI: 2.849,82.106, P = 0.007), bile duct dilatation (OR 12.856, 95%CI: 2.013, P = 0.001) were independent differential factors for predicting IMCCs over HCCs. The independent differential factors constituted a model to distinguish atypical HCCs and IMCCs. The area under receiver operating characteristic (ROC) curve, sensitivity, and specificity values of the model were 0.964(0.940,0.987), 0.88, and 0.906, indicating that the model had an excellent differential diagnostic performance. The decision curve analysis (DCA) curve showed that the model obtained a better net clinical benefit.ConclusionThe present study identified reliable imaging features for distinguishing atypical HCCs with peripheral rim-like enhancement from IMCCs on contrast-enhanced MRI. Our findings may help radiologists provide clinicians with more accurate preoperative imaging diagnoses to select appropriate treatment options.

Dataset Information

Breast Dynamic Contrast Enhanced MRI: Fibrocystic Changes Presenting as a Non-mass Enhancement Mimicking Malignancy.

Publications

Breast Dynamic Contrast Enhanced MRI: Fibrocystic Changes Presenting as a Non-mass Enhancement Mimicking Malignancy.

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