Ultrafast Dynamic Contrast-Enhanced MRI Using Compressed Sensing: Associations of Early Kinetic Parameters With Prognostic Factors of Breast Cancer

Kim, Jin Joo; Hwangbo, Lee; Suh, Hie Bum; Son, Yohan; Nickel, Dominik; Grimm, Robert

doi:10.2214/ajr.20.23457

Cited by 9 publications

(12 citation statements)

References 32 publications

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“…Ultrafast imaging can fill this gap. The features including maximum slope and time to enhancement derived from ultrafast sequences have shown important value in improving tumor characterization, identifying prognostic factors, and assessing treatment ( 29 , 31 , 48 , 49 ). But the calculation of these parameters requires commercial software that may not be universally available.…”

Section: Discussionmentioning

confidence: 99%

“…All the methods with 3-10 s of temporal resolution can capture kinetic information of a lesion in the very early post-contrast phase. Many studies have demonstrated that the early image features of ultrafast imaging are beneficial for breast cancer diagnosis and characterization ( 27 , 29 , 31 ).…”

Section: Introductionmentioning

confidence: 99%

“…Ultrafast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a newly proposed imaging protocol that can provide improved temporal resolution while maintaining reasonable spatial resolution (26,27). Several fast acquisition techniques have played an important role in ultrafast imaging, consisting of view sharing, sophisticated parallel imaging, and compressed sensing (27)(28)(29). Differential sub-sampling with cartesian ordering (DISCO), which utilizes pseudorandom segmentation of the k-space and twopoint Dixon fat-water separation, is a type of view-sharing technique (30).…”

Section: Introductionmentioning

confidence: 99%

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Combination of ultrafast dynamic contrast-enhanced MRI-based radiomics and artificial neural network in assessing BI-RADS 4 breast lesions: Potential to avoid unnecessary biopsies

et al. 2023

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ObjectivesTo investigate whether combining radiomics extracted from ultrafast dynamic contrast-enhanced MRI (DCE-MRI) with an artificial neural network enables differentiation of MR BI-RADS 4 breast lesions and thereby avoids false-positive biopsies.MethodsThis retrospective study consecutively included patients with MR BI-RADS 4 lesions. The ultrafast imaging was performed using Differential sub-sampling with cartesian ordering (DISCO) technique and the tenth and fifteenth postcontrast DISCO images (DISCO-10 and DISCO-15) were selected for further analysis. An experienced radiologist used freely available software (FAE) to perform radiomics extraction. After principal component analysis (PCA), a multilayer perceptron artificial neural network (ANN) to distinguish between malignant and benign lesions was developed and tested using a random allocation approach. ROC analysis was performed to evaluate the diagnostic performance.Results173 patients (mean age 43.1 years, range 18–69 years) with 182 lesions (95 benign, 87 malignant) were included. Three types of independent principal components were obtained from the radiomics based on DISCO-10, DISCO-15, and their combination, respectively. In the testing dataset, ANN models showed excellent diagnostic performance with AUC values of 0.915-0.956. Applying the high-sensitivity cutoffs identified in the training dataset demonstrated the potential to reduce the number of unnecessary biopsies by 63.33%-83.33% at the price of one false-negative diagnosis within the testing dataset.ConclusionsThe ultrafast DCE-MRI radiomics-based machine learning model could classify MR BI-RADS category 4 lesions into benign or malignant, highlighting its potential for future application as a new tool for clinical diagnosis.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Combination of ultrafast dynamic contrast-enhanced MRI-based radiomics and artificial neural network in assessing BI-RADS 4 breast lesions: Potential to avoid unnecessary biopsies

et al. 2023

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“…However, there is discordance in that they demonstrated persistent enhancement to a more significant predictor of axillary involvement compared to rapid filling, whereas our finding of rapid filling (≤20 s to peak) and washout correlated with axillary status with a stronger association at each rank. The Diagnostics 2023, 13, 3260 9 of 11 difference in temporal resolution may explain the discordant results, as ultrafast DCE-MRI has shown that temporal resolution can yield additional diagnostic information [33].…”

Section: Discussionmentioning

confidence: 99%

Correlation of Perfusion Metrics with Ki-67 Proliferation Index and Axillary Involvement as a Prognostic Marker in Breast Carcinoma Cases: A Dynamic Contrast-Enhanced Perfusion MRI Study

Uncu,

Aydin Aksu

2023

Diagnostics

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Our study aims to reveal clinically helpful prognostic markers using quantitative radiologic data from perfusion magnetic resonance imaging for patients with locally advanced carcinoma, using the Ki-67 index as a surrogate. Patients who received a breast cancer diagnosis and had undergone dynamic contrast-enhanced magnetic resonance imaging of the breast for pretreatment evaluation and follow-up were searched retrospectively. We evaluated the MRI studies for perfusion parameters and various categories and compared them to the Ki-67 index. Axillary involvement was categorized as low (N0–N1) or high (N2–N3) according to clinical stage. A total sum of 60 patients’ data was included in this study. Perfusion parameters and Ki-67 showed a significant correlation with the transfer constant (Ktrans) (ρ = 0.554 p = 0.00), reverse transfer constant (Kep) (ρ = 0.454 p = 0.00), and initial area under the gadolinium curve (IAUGC) (ρ = 0.619 p = 0.00). The IAUGC was also significantly different between axillary stage groups (Z = 2.478 p = 0.013). Outside of our primary hypothesis, associations between axillary stage and contrast enhancement (x2 = 8.023 p = 0.046) and filling patterns (x2 = 8.751 p = 0.013) were detected. In conclusion, these parameters are potential prognostic markers in patients with moderate Ki-67 indices, such as those in our study group. The relationship between axillary status and perfusion parameters also has the potential to determine patients who would benefit from limited axillary dissection.

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“…In fact, many studies have reported higher MS or shorter TTE (and BAT) in invasive cancers than in in situ cancers. 8,10,11,18,26 Some studies found that among biopsy-proven DCIS patients, upgrade to invasive cancer was significantly associated with higher MS or shorter TTE on preoperative UF-DCE MRI. 27,35 Parameters derived from UF-DCE MRI can further subdivide invasive breast cancer.…”

Section: Kinetic Parameters As Prognostic Factors For Breast Cancer A...mentioning

confidence: 99%

Ultrafast Dynamic Contrast‐Enhanced MRI of the Breast: From Theory to Practice

Kataoka,

Honda,

Sagawa

et al. 2023

Magnetic Resonance Imaging

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The development of ultrafast dynamic contrast‐enhanced (UF‐DCE) MRI has occurred in tandem with fast MRI scan techniques, particularly view‐sharing and compressed sensing. Understanding the strengths of each technique and optimizing the relevant parameters are essential to their implementation. UF‐DCE MRI has now shifted from research protocols to becoming a part of clinical scan protocols for breast cancer. UF‐DCE MRI is expected to compensate for the low specificity of abbreviated MRI by adding kinetic information from the upslope of the time‐intensity curve. Because kinetic information from UF‐DCE MRI is obtained from the shape and timing of the initial upslope, various new kinetic parameters have been proposed. These parameters may be associated with receptor status or prognostic markers for breast cancer. In addition to the diagnosis of malignant lesions, more emphasis has been placed on predicting and evaluating treatment response because hyper‐vascularity is linked to the aggressiveness of breast cancers. In clinical practice, it is important to note that breast lesion images obtained from UF‐DCE MRI are slightly different from those obtained by conventional DCE MRI in terms of morphology. A major benefit of using UF‐DCE MRI is avoidance of the marked or moderate background parenchymal enhancement (BPE) that can obscure the target enhancing lesions. BPE is less prominent in the earlier phases of UF‐DCE MRI, which offers better lesion‐to‐noise contrast. The excellent contrast of early‐enhancing vessels provides a key to understanding the detailed pathological structure of tumor‐associated vessels. UF‐DCE MRI is normally accompanied by a large volume of image data for which automated/artificial intelligence‐based processing is expected to be useful. In this review, both the theoretical and practical aspects of UF‐DCE MRI are summarized.Evidence Level5Technical EfficacyStage 2

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Ultrafast Dynamic Contrast-Enhanced MRI Using Compressed Sensing: Associations of Early Kinetic Parameters With Prognostic Factors of Breast Cancer

Cited by 9 publications

References 32 publications

Combination of ultrafast dynamic contrast-enhanced MRI-based radiomics and artificial neural network in assessing BI-RADS 4 breast lesions: Potential to avoid unnecessary biopsies

Combination of ultrafast dynamic contrast-enhanced MRI-based radiomics and artificial neural network in assessing BI-RADS 4 breast lesions: Potential to avoid unnecessary biopsies

Correlation of Perfusion Metrics with Ki-67 Proliferation Index and Axillary Involvement as a Prognostic Marker in Breast Carcinoma Cases: A Dynamic Contrast-Enhanced Perfusion MRI Study

Ultrafast Dynamic Contrast‐Enhanced MRI of the Breast: From Theory to Practice

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