Integration of DCE-MRI and DW-MRI Quantitative Parameters for Breast Lesion Classification

Objective. The purpose of our study was to evaluate the diagnostic value of an imaging protocol combining dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted MRI (DW-MRI) in patients with suspicious breast lesions.Materials and Methods. A total of 31 breast lesions (15 malignant and 16 benign proved by histological examination) in 26 female patients were included in this study. For both DCE-MRI and DW-MRI model free and model based parameters were computed pixel by pixel on manually segmented ROIs. Statistical procedures included conventional linear analysis and more advanced techniques for classification of lesions in benign and malignant.Results. Our findings indicated no strong correlation between DCE-MRI and DW-MRI parameters. Results of classification analysis show that combining of DCE parameters or DW-MRI parameter, in comparison of single feature, does not yield a dramatic improvement of sensitivity and specificity of the two techniques alone. The best performance was obtained considering a full combination of all features. Moreover, the classification results combining all features are dominated by DCE-MRI features alone.Conclusion. The combination of DWI and DCE-MRI does not show a potential to dramatically increase the sensitivity and specificity of breast MRI. DCE-MRI alone gave the same performance as in combination with DW-MRI.

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Diffusion tensor imaging on 3-T MRI breast: diagnostic performance in comparison to diffusion-weighted imaging

Egyptian Journal of Radiology and Nuclear Medicine ◽

10.1186/s43055-021-00473-6 ◽

2021 ◽

Vol 52 (1) ◽

Author(s):

Dalia Abdelhady ◽

Amany Abdelbary ◽

Ahmed H. Afifi ◽

Alaa-eldin Abdelhamid ◽

Hebatallah H. M. Hassan

Keyword(s):

Breast Cancer ◽

Diffusion Tensor Imaging ◽

Sensitivity And Specificity ◽

Diffusion Weighted Imaging ◽

Diffusion Tensor ◽

Breast Mri ◽

Breast Lesions ◽

Dce Mri ◽

Additional Tool ◽

Diffusion Weighted

Abstract Background Breast cancer is the most prevalent cancer among females. Dynamic contrast-enhanced MRI (DCE-MRI) breast is highly sensitive (90%) in the detection of breast cancer. Despite its high sensitivity in detecting breast cancer, its specificity (72%) is moderate. Owing to 3-T breast MRI which has the advantage of a higher signal to noise ratio and shorter scanning time rather than the 1.5-T MRI, the adding of new techniques as diffusion tensor imaging (DTI) to breast MRI became more feasible. Diffusion-weighted imaging (DWI) which tracks the diffusion of the tissue water molecule as well as providing data about the integrity of the cell membrane has been used as a valuable additional tool of DCE-MRI to increase its specificity. Based on DWI, more details about the microstructure could be detected using diffusion tensor imaging. The DTI applies diffusion in many directions so apparent diffusion coefficient (ADC) will vary according to the measured direction raising its sensitivity to microstructure elements and cellular density. This study aimed to investigate the diagnostic accuracy of DTI in the assessment of breast lesions in comparison to DWI. Results By analyzing the data of the 50 cases (31 malignant cases and 19 benign cases), the sensitivity and specificity of DWI in differentiation between benign and malignant lesions were about 90% and 63% respectively with PPV 90% and NPV 62%, while the DTI showed lower sensitivity and specificity about 81% and 51.7%, respectively, with PPV 78.9% and NPV 54.8% (P-value ≤ 0.05). Conclusion While the DWI is still the most established diffusion parameter, DTI may be helpful in the further characterization of tumor microstructure and differentiation between benign and malignant breast lesions.

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The role of contrast-enhanced ultrasound in the diagnosis of malignant non-mass breast lesions and exploration of diagnostic criteria

British Journal of Radiology ◽

10.1259/bjr.20200880 ◽

2021 ◽

Vol 94 (1120) ◽

pp. 20200880

Author(s):

Fan Zhang ◽

Lifang Jin ◽

Gang Li ◽

Chao Jia ◽

Qiusheng Shi ◽

...

Keyword(s):

Diagnostic Criteria ◽

Sensitivity And Specificity ◽

Breast Imaging ◽

Diagnostic Value ◽

Binary Logistic Regression Analysis ◽

Lower Sensitivity ◽

Breast Lesions ◽

Contrast Enhanced Ultrasound ◽

Contrast Enhanced ◽

Histopathological Results

Objectives: To assess the value of contrast-enhanced ultrasound (CEUS) for diagnosing malignant non-mass breast lesions (NMLs) and to explore the CEUS diagnostic criteria. Methods: A total of 116 patients with 119 NMLs detected by conventional US were enrolled. Histopathological results were used as the reference standard. The enhancement characteristics of NMLs in CEUS were compared between malignant and benign NMLs. The CEUS diagnostic criteria for malignant NMLs were established using independent diagnostic indicators identified by binary logistic regression analysis. The diagnostic performance of Breast Imaging Reporting and Data System-US (BI-RADS-US), CEUS, and BI-RADS-US combined with CEUS was evaluated and compared. Results: Histopathological results showed 63 and 56 benign and malignant NMLs. Enhancement degree (OR = 5.75, p = 0.003), enhancement area (OR = 4.25, p = 0.005), and radial or penetrating vessels (OR = 7.54, p = 0.003) were independent diagnostic indicators included to establish the CEUS diagnostic criteria. The sensitivity and specificity of BI-RADS-US, CEUS, and BI-RADS-US combined with CEUS were 100 and 30.2%, 80.4 and 74.6%, and 94.6 and 77.8%, respectively; the corresponding areas under the receiver operating characteristic curve (AUC) were 0.819, 0.775, and 0.885, respectively. Conclusions: CEUS has a high specificity in malignant NML diagnosis based on the diagnostic criteria including enhancement degree, enhancement area, and radial or penetrating vessels, but with lower sensitivity than BI-RADS-US. The combination of CEUS and BI-RADS-US is an effective diagnostic tool with both high sensitivity and specificity for the diagnosis of malignant NMLs. Advances in knowledge: In this study, we assessed the diagnostic value of CEUS for malignant NMLs and constructed a feasible diagnostic criterion. We further revealed that the combination of CEUS and BI-RADS-US has a high diagnostic value for malignant NMLs.

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Breast MRI Does Not Help Differentiating Radial Scar With and Without Associated Atypia or Malignancy

Canadian Association of Radiologists Journal ◽

10.1177/0846537120930360 ◽

2020 ◽

pp. 084653712093036

Author(s):

Shaza Alsharif ◽

Ann Aldis ◽

Ahmad Subahi ◽

Mona El Khoury ◽

Benoit Mesurolle

Keyword(s):

Magnetic Resonance Imaging ◽

Magnetic Resonance ◽

Breast Imaging ◽

Breast Mri ◽

Radial Scar ◽

Resonance Imaging ◽

Imaging Protocol ◽

Mri Features ◽

Significant Difference ◽

Heterogeneous Enhancement

Purpose: To review breast magnetic resonance imaging (MRI) features of radial scar (RS) with and without associated atypia/malignancy. Methods: Twenty-eight (mean age 56.8) patients diagnosed with 30 biopsy-proven RS (n = 25, ultrasound-guided 14-gauge, n = 5, stereotactically guided 9-gauge) subsequently underwent breast MRI followed by surgery. Magnetic resonance imaging protocol included axial T1, axial fat sat T2, and postgadolinium in axial and sagittal planes. Two radiologists reviewed the mammographic and MRI findings in consensus according to the Breast Imaging Reporting and Data System lexicon. Results: Of the 30 RSs excised surgically, 14 (14/30, 47.7%) were not associated with atypia/malignancy while atypia/malignancy was found in 16 (16/30, 53.3%) RSs. Three (3/30, 10%) RS lesions did not enhance on dynamic MR. Mean lesion size on MRI was 1.4 cm (range, 0.5-5 cm). Seventeen (17/30, 56.7%) lesions presented as nonmass enhancement and 9 (9/30, 30%) as masses. Nonmass lesions showed focal distribution (13/17, 76.5%) and heterogeneous enhancement (15/17, 88.2%). Masses showed irregular shape and margins (6/9, 67%) and heterogeneous enhancement (8/9, 89%). Multivariate analysis did not show any significant difference in MRI presentation between RS only and RS associated with atypia/malignancy. Conclusion: Breast MRI does not help differentiate between RS with or without associated atypia/malignancy.

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Artificial Intelligence–Based Classification of Breast Lesions Imaged With a Multiparametric Breast MRI Protocol With Ultrafast DCE-MRI, T2, and DWI

Investigative Radiology ◽

10.1097/rli.0000000000000544 ◽

2019 ◽

Vol 54 (6) ◽

pp. 325-332 ◽

Cited By ~ 17

Author(s):

Mehmet U. Dalmiş ◽

Albert Gubern-Mérida ◽

Suzan Vreemann ◽

Peter Bult ◽

Nico Karssemeijer ◽

...

Keyword(s):

Artificial Intelligence ◽

Breast Mri ◽

Breast Lesions ◽

Dce Mri ◽

Mri Protocol

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Unenhanced breast MRI: could it replace dynamic breast MRI in detecting and characterizing breast lesions?

Egyptian Journal of Radiology and Nuclear Medicine ◽

10.1186/s43055-019-0103-y ◽

2020 ◽

Vol 51 (1) ◽

Cited By ~ 2

Author(s):

Reham Khalil ◽

Noha Mohamed Osman ◽

Nivine Chalabi ◽

Enas Abdel Ghany

Keyword(s):

Positive Predictive Value ◽

Diagnostic Accuracy ◽

Negative Predictive Value ◽

Predictive Value ◽

Breast Mri ◽

Breast Lesions ◽

Dce Mri ◽

Contrast Enhanced ◽

Mri Protocol ◽

Sensitivity Specificity

Abstract Background We aimed to evaluate the unenhanced MRI of the breast (UE-MRI) as an effective substitute for dynamic contrast-enhanced breast MRI (DCE-MRI) in both detecting and characterizing breast lesions. We enrolled in our retrospective study 125 females (232 breasts, as 18 patients had unilateral mastectomy) with breast mass at MRI of variable pathologies. Routine DCE-MRI protocol of the breast was conducted. We compared the conventional unenhanced images including STIR, T2, and DWIs to the DCE-MRI by two blinded radiologists, to detect and characterize breast lesions, and then we compared their results with the final reference diagnoses supplied by the histopathology or serial negative follow-ups. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy for UE-MRI and DCE-MRI were calculated. UE-MRI results of each observer were also compared with DCE- MRI. Results The calculated UE-MRI sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy for the first observer were 95%, 80%, 83%, 94%, and 89% respectively, and for the second observer, they were 94%, 79%, 81%, 93%, and 86%. On the other hand, those for the DCE-MRI by the first observer were 98%, 82%, 84%, 98%, and 90% and were 97%, 81%, 84%, 97%, and 89% by the second observer. The intraobserver agreement between the UE-MRI and DCE-MRI results of each observer was 94% and 95%, while the interobserver agreement for each section was 97.4% for UE-MRI and 98.3% for DCE-MRI. Conclusion UE-MRI of the breast can be a reliable and effective substitute for breast DCE-MRI. It can be used with comparable accuracy to DCE-MRI whenever contrast administration is not feasible or contraindicated.

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Prediction of nipple-areolar complex involvement by breast cancer: role of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)

Egyptian Journal of Radiology and Nuclear Medicine ◽

10.1186/s43055-021-00516-y ◽

2021 ◽

Vol 52 (1) ◽

Author(s):

Mohamed Ali EL-Adalany ◽

Ahmed Abd El-Khalek Abd EL-Razek ◽

Dina EL-Metwally

Keyword(s):

Breast Cancer ◽

Radical Mastectomy ◽

Breast Mri ◽

Preoperative Assessment ◽

Dce Mri ◽

Nipple Areolar Complex ◽

Areolar Complex ◽

Mri Features ◽

Nipple Sparing

Abstract Background Skin-sparing and nipple-sparing mastectomies were considered as alternative techniques for modified radical mastectomy. In patients who are candidates for nipple-sparing mastectomy, preoperative assessment of the nipple-areolar complex (NAC) is essential for adequate surgical planning. Breast MRI is highly sensitive for cancer detection and has an important role in disease staging. The aim of this study was to estimate the role of DCE-MRI in predicting malignant NAC invasion by underlying breast cancer and assess the best predictors on MRI that can suspect malignant NAC invasion. Results Out of the 125 patients with breast cancer, 33 patients (26.4%) showed malignant NAC invasion. On basis of multivariate analysis, abnormal nipple enhancement, tumor nipple enhancement, tumor nipple distance ≤ 2 cm, and abnormal and asymmetric nipple morphology were all significant predictors of malignant NAC invasion (P < 0.001) with abnormal unilateral nipple enhancement as the most important independent MRI predictor of malignant NAC invasion (odds ratio = 61.07, 95% CI 12.81–291.22, P < 0.001). When combining more than positive suspicious MRI features, DCE-MRI had 66.6% sensitivity, 76% specificity, 50% PPV, 86.4% NPV, and 73.6% accuracy in prediction of malignant NAC invasion. Conclusion DCE-MRI could predict malignant NAC invasion with abnormal unilateral nipple enhancement as the most important independent MRI predictor.

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Dynamic contrast-enhanced breast MRI features correlate with invasive breast cancer angiogenesis

npj Breast Cancer ◽

10.1038/s41523-021-00247-3 ◽

2021 ◽

Vol 7 (1) ◽

Author(s):

Jennifer Xiao ◽

Habib Rahbar ◽

Daniel S. Hippe ◽

Mara H. Rendi ◽

Elizabeth U. Parker ◽

...

Keyword(s):

Breast Cancer ◽

Invasive Breast Cancer ◽

Characteristic Curve ◽

Breast Mri ◽

Texture Features ◽

Dce Mri ◽

Dynamic Contrast Enhanced ◽

Mri Features ◽

Contrast Enhanced ◽

Initial Peak

AbstractAngiogenesis is a critical component of breast cancer development, and identification of imaging-based angiogenesis assays has prognostic and treatment implications. We evaluated the association of semi-quantitative kinetic and radiomic breast cancer features on dynamic contrast-enhanced (DCE)-MRI with microvessel density (MVD), a marker for angiogenesis. Invasive breast cancer kinetic features (initial peak percent enhancement [PE], signal enhancement ratio [SER], functional tumor volume [FTV], and washout fraction [WF]), radiomics features (108 total features reflecting tumor morphology, signal intensity, and texture), and MVD (by histologic CD31 immunostaining) were measured in 27 patients (1/2016–7/2017). Lesions with high MVD levels demonstrated higher peak SER than lesions with low MVD (mean: 1.94 vs. 1.61, area under the receiver operating characteristic curve [AUC] = 0.79, p = 0.009) and higher WF (mean: 50.6% vs. 22.5%, AUC = 0.87, p = 0.001). Several radiomics texture features were also promising for predicting increased MVD (maximum AUC = 0.84, p = 0.002). Our study suggests DCE-MRI can non-invasively assess breast cancer angiogenesis, which could stratify biology and optimize treatments.

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The Role of Combined Diffusion-Weighted Imaging and Dynamic Contrast-Enhanced MRI for Differentiating Malignant From Benign Breast Lesions Presenting Washout Curve

Canadian Association of Radiologists Journal ◽

10.1177/0846537120907098 ◽

2020 ◽

pp. 084653712090709

Author(s):

Sehnaz Tezcan ◽

Funda Ulu Ozturk ◽

Nihal Uslu ◽

Eda Yilmaz Akcay

Keyword(s):

Breast Mri ◽

Breast Lesions ◽

Benign Lesions ◽

Cutoff Value ◽

Dce Mri ◽

Dynamic Contrast Enhanced Mri ◽

Dynamic Contrast Enhanced ◽

Enhanced Mri ◽

Contrast Enhanced ◽

Contrast Enhanced Mri

Purpose: The aim of this study is to evaluate the diagnostic performance of combined breast magnetic resonance imaging (MRI) protocol including dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imaging (DWI) in patients with enhancing lesions that demonstrated washout curve and to determine whether applying apparent diffusion coefficient (ADC) cutoff value could improve the diagnostic value of breast MRI. Methods: The retrospective study included 116 patients with 116 suspicious breast lesions, which showed washout curve on DCE-MRI, who underwent subsequent biopsy. Morphologic characteristics on DCE-MRI and ADC values on DWI were evaluated. Apparent diffusion coefficient values and morphologic features of benign and malignant lesions were compared. Diagnostic values of DCE-MRI and combined MRI, including DCE-MRI and DWI (applying an ADC cutoff value) for distinguishing malignancy from benign lesions, were calculated. Results: Of the 116 breast lesions, 79 were malignant and 37 were benign. The ADC value of malignant tumors (median ADC, 0.72 × 10−3 mm2/s) was significantly lower than that of benign lesions (median ADC, 1.03 × 10−3 mm2/s; P < .000). The sensitivity and specificity of an ADC cutoff value of 0.89 × 10−3 mm2/s were 92% and 95%, respectively. Dynamic contrast-enhanced MRI alone presented 100% sensitivity and 59.4% specificity. Adding an ADC cutoff value of 0.89 × 10−3 mm2/s provided 100% sensitivity and 81% specificity, which would have prevented biopsy for 21.6% of benign lesions without missing any malignancies. Conclusion: Applying an ADC cutoff value to DCE-MRI provides an improvement in the diagnostic value of breast MRI for differentiating among lesions presenting washout curve.

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