Diagnostic performance of initial enhancement analysis using ultra-fast dynamic contrast-enhanced MRI for breast lesions

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

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 LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

Ultrafast sequence-based prediction model and nomogram to differentiate additional suspicious lesions on preoperative breast MRI

OBJECTIVES

To investigate whether ultrafast sequence improves the diagnostic performance of conventional dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in differentiating additional suspicious lesions (ASLs) on preoperative breast MRI.

MATERIALS AND METHODS

A retrospective database search identified 668 consecutive patients who underwent preoperative breast DCE-MRI with ultrafast sequence between June 2020 and July 2021. Among these, 107 ASLs from 98 patients with breast cancer (36 multifocal, 42 multicentric, and 29 contralateral) were identified. Clinical, pathological, conventional MRI findings, and ultrafast sequence-derived parameters were collected. A prediction model that adds ultrafast sequence-derived parameters to clinical, pathological, and conventional MRI findings was developed and validated internally. Decision curve analysis and net reclassification index statistics were performed. A nomogram was constructed.

RESULTS

The ultrafast model adding time to peak enhancement, time to enhancement, and maximum slope showed a significantly increased area under the receiver operating characteristic curve compared with the conventional model which includes age, human epidermal growth factor receptor 2 expression of index cancer, size of index cancer, lesion type of index cancer, location of ASL, and size of ASL (0.92 vs. 0.82; p = 0.002). The decision curve analysis showed that the ultrafast model had a higher overall net benefit than the conventional model. The net reclassification index of ultrafast model was 23.3% (p = 0.001).

CONCLUSION

A combination of ultrafast sequence-derived parameters with clinical, pathological, and conventional MRI findings can aid in the differentiation of ASL on preoperative breast MRI.

CLINICAL RELEVANCE STATEMENT

Our prediction model and nomogram that was based on ultrafast sequence-derived parameters could help radiologists differentiate ASLs on preoperative breast MRI.

KEY POINTS

Ultrafast MRI can diminish background parenchymal enhancement and possibly improve diagnostic accuracy for additional suspicious lesions (ASLs). Location of ASL, larger size of ASL, and higher maximum slope were associated with malignant ASL. The ultrafast model and nomogram can help preoperatively differentiate additional malignancies.

Optimizing ultrafast dynamic contrast-enhanced MRI scan duration in the differentiation of benign and malignant breast lesions

OBJECTIVE

To determine the optimal scan duration for ultrafast DCE-MRI in effectively differentiating benign from malignant breast lesions.

METHODS

The study prospectively recruited participants who underwent breast ultrafast DCE-MRI from September 2021 to March 2023. A 30-phase breast ultrafast DCE-MRI on a 3.0-T MRI system was conducted with a 4.5-s temporal resolution. Scan durations ranged from 40.5 s to 135.0 s, during which the analysis is performed at three-phase intervals, forming eight dynamic sets (scan duration [SD]40.5s: 40.5 s, SD54s: 54.0 s, SD67.5s: 67.5 s, SD81s: 81.0 s, SD94.5s: 94.5 s, SD108s: 108.0 s, SD121.5s: 121.5 s, and SD135s: 135.0 s). Two ultrafast DCE-MRI parameters, maximum slope (MS) and initial area under the curve in 60 s (iAUC), were calculated for each dynamic set and compared between benign and malignant lesions. Areas under the receiver operating characteristic curve (AUCs) were used to assess their diagnostic performance.

RESULTS

A total of 140 women (mean age, 47 ± 11 years) with 151 lesions were included. MS and iAUC from eight dynamic sets exhibited significant differences between benign and malignant lesions (all p < 0.05), except iAUC at SD40.5s. The AUC of MS (AUC = 0.804) and iAUC (AUC = 0.659) at SD67.5s were significantly higher than their values at SD40.5s (AUC = 0.606 and 0.516; corrected p < 0.05). No significant differences in AUCs for MS and iAUC were observed from SD67.5s to SD135s (all corrected p > 0.05).

CONCLUSIONS

Ultrafast DCE-MRI with a 67.5-s scan duration appears optimal for effectively differentiating malignant from benign breast lesions.

CRITICAL RELEVANCE STATEMENT

By evaluating scan durations (40.5-135 s) and analyzing two ultrafast DCE-MRI parameters, we found a scan duration of 67.5 s optimal for discriminating between these lesions and offering a balance between acquisition time and diagnostic efficacy.

KEY POINTS

Ultrafast DCE-MRI can effectively differentiate malignant from benign breast lesions. A minimum of 67.5-sec ultrafast DCE-MRI scan duration is required to differentiate benign and malignant lesions. Extending the scan duration beyond 67.5 s did not significantly improve diagnostic accuracy.

The diagnostic performance of ultrafast MRI to differentiate benign from malignant breast lesions: a systematic review and meta-analysis

OBJECTIVES

To assess the diagnostic performance of ultrafast magnetic resonance imaging (UF-DCE MRI) in differentiating benign from malignant breast lesions.

MATERIALS AND METHODS

A comprehensive search was conducted until September 1, 2023, in Medline, Embase, and Cochrane databases. Clinical studies evaluating the diagnostic performance of UF-DCE MRI in breast lesion stratification were screened and included in the meta-analysis. Pooled summary estimates for sensitivity, specificity, diagnostic odds ratio (DOR), and hierarchic summary operating characteristics (SROC) curves were pooled under the random-effects model. Publication bias and heterogeneity between studies were calculated.

RESULTS

A final set of 16 studies analyzing 2090 lesions met the inclusion criteria and were incorporated into the meta-analysis. Using UF-DCE MRI kinetic parameters, the pooled sensitivity, specificity, DOR, and area under the curve (AUC) for differentiating benign from malignant breast lesions were 83% (95% CI 79-88%), 77% (95% CI 72-83%), 18.9 (95% CI 13.7-26.2), and 0.876 (95% CI 0.83-0.887), respectively. We found no significant difference in diagnostic accuracy between the two main UF-DCE MRI kinetic parameters, maximum slope (MS) and time to enhancement (TTE). DOR and SROC exhibited low heterogeneity across the included studies. No evidence of publication bias was identified (p = 0.585).

CONCLUSIONS

UF-DCE MRI as a stand-alone technique has high accuracy in discriminating benign from malignant breast lesions.

CLINICAL RELEVANCE STATEMENT

UF-DCE MRI has the potential to obtain kinetic information and stratify breast lesions accurately while decreasing scan times, which may offer significant benefit to patients.

KEY POINTS

• Ultrafast breast MRI is a novel technique which captures kinetic information with very high temporal resolution. • The kinetic parameters of ultrafast breast MRI demonstrate a high level of accuracy in distinguishing between benign and malignant breast lesions. • There is no significant difference in accuracy between maximum slope and time to enhancement kinetic parameters.

Multiparametric Approach to Breast Cancer With Emphasis on Magnetic Resonance Imaging in the Era of Personalized Breast Cancer Treatment

ABSTRACT

A multiparametric approach to breast cancer imaging offers the advantage of integrating the diverse contributions of various parameters. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is the most important MRI sequence for breast imaging. The vascularity and permeability of lesions can be estimated through the use of semiquantitative and quantitative parameters. The increased use of ultrafast DCE-MRI has facilitated the introduction of novel kinetic parameters. In addition to DCE-MRI, diffusion-weighted imaging provides information associated with tumor cell density, with advanced diffusion-weighted imaging techniques such as intravoxel incoherent motion, diffusion kurtosis imaging, and time-dependent diffusion MRI opening up new horizons in microscale tissue evaluation. Furthermore, T2-weighted imaging plays a key role in measuring the degree of tumor aggressiveness, which may be related to the tumor microenvironment. Magnetic resonance imaging is, however, not the only imaging modality providing semiquantitative and quantitative parameters from breast tumors. Breast positron emission tomography demonstrates superior spatial resolution to whole-body positron emission tomography and allows comparable delineation of breast cancer to MRI, as well as providing metabolic information, which often precedes vascular and morphological changes occurring in response to treatment. The integration of these imaging-derived factors is accomplished through multiparametric imaging. In this article, we explore the relationship among the key imaging parameters, breast cancer diagnosis, and histological characteristics, providing a technical and theoretical background for these parameters. Furthermore, we review the recent studies on the application of multiparametric imaging to breast cancer and the significance of the key imaging parameters.

Ultrafast MRI and T1 and T2 Radiomics for Predicting Invasive Components in Ductal Carcinoma in Situ Diagnosed With Percutaneous Needle Biopsy

OBJECTIVE

This study aimed to investigate the feasibility of ultrafast magnetic resonance imaging (MRI) and radiomic features derived from breast MRI for predicting the upstaging of ductal carcinoma in situ (DCIS) diagnosed using percutaneous needle biopsy.

MATERIALS AND METHODS

Between August 2018 and June 2020, 95 patients with 98 DCIS lesions who underwent preoperative breast MRI, including an ultrafast sequence, and subsequent surgery were included. Four ultrafast MRI parameters were analyzed: time-to-enhancement, maximum slope (MS), area under the curve for 60 s after enhancement, and time-to-peak enhancement. One hundred and seven radiomic features were extracted for the whole tumor on the first post-contrast T1WI and T2WI using PyRadiomics. Clinicopathological characteristics, ultrafast MRI findings, and radiomic features were compared between the pure DCIS and DCIS with invasion groups. Prediction models, incorporating clinicopathological, ultrafast MRI, and radiomic features, were developed. Receiver operating characteristic curve analysis and area under the curve (AUC) were used to evaluate model performance in distinguishing between the two groups using leave-one-out cross-validation.

RESULTS

Thirty-six of the 98 lesions (36.7%) were confirmed to have invasive components after surgery. Compared to the pure DCIS group, the DCIS with invasion group had a higher nuclear grade (P < 0.001), larger mean lesion size (P = 0.038), larger mean MS (P = 0.002), and different radiomic-related characteristics, including a more extensive tumor volume; higher maximum gray-level intensity; coarser, more complex, and heterogeneous texture; and a greater concentration of high gray-level intensity. No significant differences in AUCs were found between the model incorporating nuclear grade and lesion size (0.687) and the models integrating additional ultrafast MRI and radiomic features (0.680-0.732).

CONCLUSION

High nuclear grade, larger lesion size, larger MS, and multiple radiomic features were associated with DCIS upstaging. However, the addition of MS and radiomic features to the prediction model did not significantly improve the prediction performance.

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

OBJECTIVE

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.

MATERIALS AND METHODS

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.

RESULTS

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).

CONCLUSION

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.

CLINICAL RELEVANCE

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.

KEY POINTS

• 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.

Potential Antihuman Epidermal Growth Factor Receptor 2 Target Therapy Beneficiaries: The Role of MRI-Based Radiomics in Distinguishing Human Epidermal Growth Factor Receptor 2-Low Status of Breast Cancer

BACKGROUND

Multiparametric MRI radiomics could distinguish human epidermal growth factor receptor 2 (HER2)-positive from HER2-negative breast cancers. However, its value for further distinguishing HER2-low from HER2-negative breast cancers has not been investigated.

PURPOSE

To investigate whether multiparametric MRI-based radiomics can distinguish HER2-positive from HER2-negative breast cancers (task 1) and HER2-low from HER2-negative breast cancers (task 2).

STUDY TYPE

Retrospective.

POPULATION

Task 1: 310 operable breast cancer patients from center 1 (97 HER2-positive and 213 HER2-negative); task 2: 213 HER2-negative patients (108 HER2-low and 105 HER2-zero); 59 patients from center 2 (16 HER2-positive, 27 HER2-low and 16 HER2-zero) for external validation.

FIELD STRENGTH/SEQUENCE

A 3.0 T/T1-weighted contrast-enhanced imaging (T1CE), diffusion-weighted imaging (DWI)-derived apparent diffusion coefficient (ADC).

ASSESSMENT

Patients in center 1 were assigned to a training and internal validation cohort at a 2:1 ratio. Intratumoral and peritumoral features were extracted from T1CE and ADC. After dimensionality reduction, the radiomics signatures (RS) of two tasks were developed using features from T1CE (RS-T1CE), ADC (RS-ADC) alone and T1CE + ADC combination (RS-Com).

STATISTICAL TESTS

Mann-Whitney U tests, the least absolute shrinkage and selection operator, receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA).

RESULTS

For task 1, RS-ADC yielded higher area under the ROC curve (AUC) in the training, internal, and external validation of 0.767/0.725/0.746 than RS-T1CE (AUC = 0.733/0.674/0.641). For task 2, RS-T1CE yielded higher AUC of 0.765/0.755/0.678 than RS-ADC (AUC = 0.706/0.608/0.630). For both of task 1 and task 2, RS-Com achieved the best performance with AUC of 0.793/0.778/0.760 and 0.820/0.776/0.711, respectively, and obtained higher clinical benefit in DCA compared with RS-T1CE and RS-ADC. The calibration curves of all RS demonstrated a good fitness.

DATA CONCLUSION

Multiparametric MRI radiomics could noninvasively and robustly distinguish HER2-positive from HER2-negative breast cancers and further distinguish HER2-low from HER2-negative breast cancers.

EVIDENCE LEVEL

3.

TECHNICAL EFFICACY

Stage 2.

Magnetic resonance imaging diagnosis of non-mass enhancement of the breast

Breast Imaging Reporting and Data System magnetic resonance imaging (BI-RADS-MRI) classifies lesions as mass, non-mass enhancement (NME), or focus. BI-RADS ultrasound does not currently have the concept of non-mass. Additionally, knowing the concept of NME in MRI is significant. Thus, this study aimed to provide a narrative review of NME diagnosis in breast MRI. Lexicons are defined with distribution (focal, linear, segmental, regional, multiple regions, and diffuse) and internal enhancement patterns (homogenous, heterogeneous, clumped, and clustered ring) in the case of NME. Among these, linear, segmental, clumped, clustered ring, and heterogeneous are the terms that suggest malignancy. Hence, a hand search was conducted for reports of malignancy frequencies. The malignancy frequency in NME is widely distributed, ranging from 25 to 83.6%, and the frequency of each finding varies. Latest techniques, such as diffusion-weighted imaging and ultrafast dynamic MRI, are attempted to differentiate NME. Additionally, attempts are made in the preoperative setting to determine the concordance of lesion spread based on findings and the presence of invasion.

The effectiveness of an ultrafast breast MRI protocol in the differentiation of benign and malignant breast lesions

AIM

To evaluate the effectiveness of an ultrafast breast magnetic resonance imaging (MRI) protocol in differentiating benign and malignant breast lesions.

MATERIALS AND METHODS

Fifty-four patients with Breast Imaging Reporting and Data System (BI-RADS) 4 or 5 lesions were recruited between July 2020 to May 2021. A standard breast MRI was performed with the inclusion of the ultrafast protocol between the unenhanced sequence and the first contrast-enhanced sequence. Three radiologists performed image interpretation in consensus. Ultrafast kinetic parameters analysed included the maximum slope (MS), time to enhancement (TTE), and arteriovenous index (AVI). These parameters were compared using receiver operating characteristics with p-values of <0.05 considered to indicate statistical significance.

RESULTS

Eighty-three histopathological proven lesions from 54 patients (mean age 53.87 years, SD 12.34, range 26-78 years) were analysed. Forty-one per cent (n=34) were benign and 59% (n=49) were malignant. All malignant and 38.2% (n=13) benign lesions were visualised on the ultrafast protocol. Of the malignant lesions, 77.6% (n=53) were invasive ductal carcinoma (IDC) and 18.4% (n=9) were ductal carcinoma in situ (DCIS). The MS for malignant lesions (13.27%/s) were significantly larger than for benign (5.45%/s; p<0.0001). No significant differences were seen for TTE and AVI. The area under the ROC curve (AUC) for the MS, TTE, and AVI were 0.836, 0.647, and 0.684, respectively. Different types of invasive carcinoma had similar MS and TTE. The MS of high-grade DCIS was also similar to that of IDC. Lower MS values were observed for low-grade (5.3%/s) compared to high-grade DCIS (14.8%/s) but the results were not significant statistically.

CONCLUSION

The ultrafast protocol showed potential to discriminate between malignant and benign breast lesions with high accuracy using MS.

Multiple parameters from ultrafast dynamic contrast-enhanced magnetic resonance imaging to discriminate between benign and malignant breast lesions: Comparison with apparent diffusion coefficient

PURPOSE

The purpose of this study was first to assess the diagnostic performance of ultrafast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters compared to apparent diffusion coefficient (ADC) for distinguishing benign from malignant breast lesions and second to investigate the complementarity of ultrafast DCE-MRI with DWI in that task.

MATERIALS AND METHODS

A total of 142 women (mean age, 48.42 ± 11.03 [SD]) years; range: 14-78 years) with 150 breast lesions who underwent breast ultrafast DCE-MRI were prospectively recruited. Ultrafast DCE-MRI semi-quantitative parameters (maximum slope [MS], time to peak [TTP], time to enhancement [TTE], and initial area under curve in 60 s [iAUC]), ultrafast DCE-MRI quantitative parameters (K_ep, K_trans, and V_e), and the ADC were estimated and compared between benign and malignant breast lesions. Classification performances were assessed using area under the receiver operating characteristic curve (AUC) and compared using Delong test.

RESULTS

The ultrafast DCE-MRI semi-quantitative multiparameters (AUC, 0.913; 95% CI: 0.856-0.953) showed better classification performance than the quantitative multiparameters (AUC, 0.818; 95% CI: 0.747-0.876) (P = 0.022). No differences in AUC were found between ultrafast DCE-MRI semi-quantitative multiparameters and ADC (AUC, 0.912; 95% CI: 0.855-0.952) (P = 0.990). The combination of ultrafast DCE-MRI semi-quantitative multiparameters and ADC (AUC, 0.960; 95% CI: 0.915-0.985) showed better classification performance than the ultrafast DCE-MRI semi-quantitative multiparameters (P = 0.014) and quantitative multiparameters (P < 0.001).

CONCLUSION

Ultrafast DCE-MRI can be used as an accurate method for discriminating benign from malignant breast lesions. The combination of ultrafast DCE-MRI and DWI significantly increases the diagnostic value of ultrafast DCE-MRI.

Time to enhancement of breast lesions and normal breast parenchyma in light of menopausal status and menstrual cycle for ultrafast dynamic contrast-enhanced MRI using compressed sensing

PURPOSE

To assess the dependency of the Time to enhancement (TTE) of breast lesions and normal breast parenchyma from menopausal status and menstrual cycle using ultrafast compressed sensing (CS) -accelerated dynamic contrast-enhanced (DCE) MRI.

METHODS

This institutional review board approved retrospective study included 89 breast cancers, 22 benign lesions and 131 normal breast parenchymal foci. A prototypical ultrafast DCE sequence obtained 30 phases with 2.9 s temporal resolution. Mean and median TTE of all breast cancers, benign lesions and normal breast parenchymal foci were assessed. we also assessed whether there were any differences in TTE regarding the menopausal status and menstrual cycle.

RESULTS

The TTE of breast cancer was significantly shorter than that of benign lesions and normal breast parenchymal foci in both the premenopausal status (5.8 vs. 8.7 and 8.7 s, respectively) (p = 0.0028 and < 0.0001, respectively) and postmenopausal status (5.8 vs. 11.6 and 11.6 s, respectively) (p < 0.0001 in both). The TTE of parenchymal foci in the premenopausal status was significantly shorter than that in the postmenopausal status (p = 0.0025). Although the TTE interval between cancer and parenchymal foci in premenopausal status is shorter than that in postmenopausal status, the AUCs in the pre- and postmenopausal status for differentiating breast cancer and parenchymal foci were comparable with using different cutoff TTE values. There were no differences in TTE regarding the menstrual cycle.

CONCLUSIONS

The TTE derived from ultrafast CS-accelerated DCE MRI was useful to differentiate breast cancer from benign lesions and normal breast parenchymal foci in both pre- and postmenopausal status.

Assessment of Enhancement Kinetics Improves the Specificity of Abbreviated Breast MRI: Performance in an Enriched Cohort

Objective: To investigate the added value of kinetic information for breast lesion evaluation on abbreviated breast MRI (AB-MRI). Methods: This retrospective study analyzed 207 breast lesions with Breast Imaging Reporting and Data System categories 3, 4, or 5 on AB-MRI in 198 consecutive patients who had breast MRI for screening after breast cancer surgery between January 2017 and December 2019. All lesions were pathologically confirmed or stable on follow-up images for 2 years or more. Kinetic information of the lesions regarding the degree and rate of enhancement on the first post-contrast-enhanced image and the enhancement curve type from two post-contrast-enhanced images were analyzed on a commercially available computer-assisted diagnosis system. The diagnostic performances of AB-MRI with morphological analysis alone and with the addition of kinetic information were compared using the McNemar test. Results: Of 207 lesions, 59 (28.5%) were malignant and 148 (71.5%) were benign. The addition of an enhancement degree of ≥90% to the morphological analysis significantly increased the specificity of AB-MRI (29.7% vs. 52.7%, p < 0.001) without significantly reducing the sensitivity (94.9% vs. 89.8%, p = 0.083) compared to morphological analysis alone. Unnecessary biopsy could have been avoided in 34 benign lesions, although three malignant lesions could have been missed. For detecting invasive cancer, adding an enhancement degree ≥107% to the morphological analysis significantly increased the specificity (26.5% vs. 57.6%, p < 0.001) without significantly decreasing the sensitivity (94.6% vs. 86.5%, p = 0.083). Conclusion: Adding the degree of enhancement on the first post-contrast-enhanced image to the morphological analysis resulted in higher AB-MRI specificity without compromising its sensitivity.

Visual Evaluation of Ultrafast MRI in the Assessment of Residual Breast Cancer after Neoadjuvant Systemic Therapy: A Preliminary Study Association with Subtype

The purpose of this study was to investigate the diagnostic performance of ultrafast DCE (UF-DCE) MRI after the completion of neoadjuvant systemic therapy (NST) in breast cancer. In this study, MR examinations of 55 post-NST breast cancers were retrospectively analyzed. Residual tumor sizes were measured in the 20th phase of UF-DCE MRI, early and delayed phases of conventional DCE MRI, and high spatial-resolution CE MRI (UF, early, delayed, and HR, respectively). The diagnostic performance for the detection of residual invasive cancer was calculated by ROC analysis. The size difference between MRI and pathological findings was analyzed using the Wilcoxon signed-rank test with the Bonferroni correction. The overall AUC was highest for UF (0.86 and 0.88 for readers 1 and 2, respectively). The difference in imaging and pathological sizes for UF (5.7 ± 8.2 mm) was significantly smaller than those for early, delayed, and HR (p < 0.01). For luminal subtype breast cancer, the size difference was significantly smaller for UF and early than for delayed (p < 0.01). UF-DCE MRI demonstrated higher AUC and specificity for the more accurate detection of residual cancer and the visualization of tumor extent than conventional DCE MRI.

Comparison of Contrast-Enhanced Spectral Mammography and Contrast-Enhanced MRI in Screening Multifocal and Multicentric Lesions in Breast Cancer Patients

Objectives

We aimed to determine the difference between contrast-enhanced spectral mammography (CESM) and contrast-enhanced magnetic resonance imaging (CE-MRI) in detecting multifocal and multicentric breast cancer (MMBC).

Methods

: This study was conducted among breast cancer patients between July 1, 2017, and May 30, 2021. The sensitivity, specificity, and accuracy of CESM and CE-MRI in the diagnosis of MMBC were evaluated with pathological results as the gold standard.

Results

A total of 188 lesions were detected in 54 patients with MMBC, including 177 breast cancer and 11 benign lesions. Based on CESM and CE-MRI, 4 false-positive cases and 3 false-negative cases and 7 false-positive cases and 1 false-negative case, respectively, were found. The accuracy of CESM was higher than that of MRI (96.3% vs 95.7%), and the specificity was higher than that of MRI (63.6% vs 36.4%). There were no significant differences in the sensitivity, specificity, and accuracy for the detection of MMBC between CESM and CE-MRI (p = 0.500; p = 0.250; p = 0.792).

Conclusion

CESM is an effective method for the detection of MMBC, which is consistent with the sensitivity and accuracy of CE-MRI.

Estimation of the capillary level input function for dynamic contrast-enhanced MRI of the breast using a deep learning approach

PURPOSE

To develop a deep learning approach to estimate the local capillary-level input function (CIF) for pharmacokinetic model analysis of DCE-MRI.

METHODS

A deep convolutional network was trained with numerically simulated data to estimate the CIF. The trained network was tested using simulated lesion data and used to estimate voxel-wise CIF for pharmacokinetic model analysis of breast DCE-MRI data using an abbreviated protocol from women with malignant (n = 25) and benign (n = 28) lesions. The estimated parameters were used to build a logistic regression model to detect the malignancy.

RESULT

The pharmacokinetic parameters estimated using the network-predicted CIF from our breast DCE data showed significant differences between the malignant and benign groups for all parameters. Testing the diagnostic performance with the estimated parameters, the conventional approach with arterial input function (AIF) showed an area under the curve (AUC) between 0.76 and 0.87, and the proposed approach with CIF demonstrated similar performance with an AUC between 0.79 and 0.81.

CONCLUSION

This study shows the feasibility of estimating voxel-wise CIF using a deep neural network. The proposed approach could eliminate the need to measure AIF manually without compromising the diagnostic performance to detect the malignancy in the clinical setting.

Breast Tumor Identification in Ultrafast MRI Using Temporal and Spatial Information

Simple Summary

The diagnosis of breast cancer with MRI is based on both morphological evaluation and kinetic curve assessment. Current computer-aided diagnosis methods for malignancy determination mainly focus on morphology features but ignored the temporal information in dynamic contrast-enhanced MRI sequences. Malignant and benign lesions usually have different enhancement patterns during the wash-in phase. Ultrafast breast MRI with high temporal resolution can capture the inflow of contrast in breast lesions. This advantage of ultrafast MRI enables the combination of both temporal and spatial information for automatic breast lesion analysis model development. We found that temporal information helps to significantly improve the performance of breast lesion classification. This suggests that ultrafast MRI provides useful information for malignancy identification and temporal information, which is indispensable for similar model development.

Abstract

Purpose: To investigate the feasibility of using deep learning methods to differentiate benign from malignant breast lesions in ultrafast MRI with both temporal and spatial information. Methods: A total of 173 single breasts of 122 women (151 examinations) with lesions above 5 mm were retrospectively included. A total of 109 out of 173 lesions were benign. Maximum intensity projection (MIP) images were generated from each of the 14 contrast-enhanced T1-weighted acquisitions in the ultrafast MRI scan. A 2D convolutional neural network (CNN) and a long short-term memory (LSTM) network were employed to extract morphological and temporal features, respectively. The 2D CNN model was trained with the MIPs from the last four acquisitions to ensure the visibility of the lesions, while the LSTM model took MIPs of an entire scan as input. The performance of each model and their combination were evaluated with 100-times repeated stratified four-fold cross-validation. Those models were then compared with models developed with standard DCE-MRI which followed the same data split. Results: In the differentiation between benign and malignant lesions, the ultrafast MRI-based 2D CNN achieved a mean AUC of 0.81 ± 0.06, and the LSTM network achieved a mean AUC of 0.78 ± 0.07; their combination showed a mean AUC of 0.83 ± 0.06 in the cross-validation. The mean AUC values were significantly higher for ultrafast MRI-based models than standard DCE-MRI-based models. Conclusion: Deep learning models developed with ultrafast breast MRI achieved higher performances than standard DCE-MRI for malignancy discrimination. The improved AUC values of the combined models indicate an added value of temporal information extracted by the LSTM model in breast lesion characterization.

Ultrafast Dynamic Contrast-enhanced MRI of the Breast: How Is It Used?

Ultrafast dynamic contrast-enhanced (UF-DCE) MRI is a new approach to capture kinetic information in the very early post-contrast period with high temporal resolution while keeping reasonable spatial resolution. The detailed timing and shape of the upslope in the time–intensity curve are analyzed. New kinetic parameters obtained from UF-DCE MRI are useful in differentiating malignant from benign lesions and in evaluating prognostic markers of the breast cancers. Clinically, UF-DCE MRI contributes in identifying hypervascular lesions when the background parenchymal enhancement (BPE) is marked on conventional dynamic MRI. This review starts with the technical aspect of accelerated acquisition. Practical aspects of UF-DCE MRI include identification of target hypervascular lesions from marked BPE and diagnosis of malignant and benign lesions based on new kinetic parameters derived from UF-DCE MRI: maximum slope (MS), time to enhance (TTE), bolus arrival time (BAT), time interval between arterial and venous visualization (AVI), and empirical mathematical model (EMM). The parameters derived from UF-DCE MRI are compared in terms of their diagnostic performance and association with prognostic markers. Pitfalls of UF-DCE MRI in the clinical situation are also covered. Since UF-DCE MRI is an evolving technique, future prospects of UF-DCE MRI are discussed in detail by citing recent evidence. The topic covers prediction of treatment response, multiparametric approach using DWI-derived parameters, evaluation of tumor-related vessels, and application of artificial intelligence for UF-DCE MRI. Along with comprehensive literature review, illustrative clinical cases are used to understand the value of UF-DCE MRI.

Economic potential of abbreviated breast MRI for screening women with dense breast tissue for breast cancer

OBJECTIVES

Abbreviated breast MRI (AB-MRI) was introduced to reduce both examination and image reading times and to improve cost-effectiveness of breast cancer screening. The aim of this model-based economic study was to analyze the cost-effectiveness of full protocol breast MRI (FB-MRI) vs. AB-MRI in screening women with dense breast tissue for breast cancer.

METHODS

Decision analysis and a Markov model were designed to model the cumulative costs and effects of biennial screening in terms of quality-adjusted life years (QALYs) from a US healthcare system perspective. Model input parameters for a cohort of women with dense breast tissue were adopted from recent literature. The impact of varying AB-MRI costs per examination as well as specificity on the resulting cost-effectiveness was modeled within deterministic sensitivity analyses.

RESULTS

At an assumed cost per examination of $ 263 for AB-MRI (84% of the cost of a FB-MRI examination), the discounted cumulative costs of both MR-based strategies accounted comparably. Reducing the costs of AB-MRI below $ 259 (82% of the cost of a FB-MRI examination, respectively), the incremental cost-effectiveness ratio of FB-MRI exceeded the willingness to pay threshold and the AB-MRI-strategy should be considered preferable in terms of cost-effectiveness.

CONCLUSIONS

Our preliminary findings indicate that AB-MRI may be considered cost-effective compared to FB-MRI for screening women with dense breast tissue for breast cancer, as long as the costs per examination do not exceed 82% of the cost of a FB-MRI examination.

KEY POINTS

• Cost-effectiveness of abbreviated breast MRI is affected by reductions in specificity and resulting false positive findings and increased recall rates. • Abbreviated breast MRI may be cost-effective up to a cost per examination of 82% of the cost of a full protocol examination. • Abbreviated breast MRI could be an economically preferable alternative to full protocol breast MRI in screening women with dense breast tissue.

Implementation of Abbreviated Breast MRI for Screening: AJR Expert Panel Narrative Review

Abbreviated breast MRI (AB-MRI) is being rapidly adopted to harness the high sensitivity of screening MRI while addressing issues related to access, cost, and workflow. The successful implementation of an ABI-MRI program requires collaboration across administrative, operational, financial, technical, and clinical providers. Institutions must be thoughtful in defining AB-MRI patient eligibility and providing recommendations for screening intervals, as existing practices are heterogeneous. Similarly, there is no universally accepted AB-MRI protocol, though guiding principles should harmonize abbreviated and full protocols while being mindful of scan duration and table time. The interpretation of AB-MRI will be a new experience for many radiologists and may require a phased rollout as well as a careful audit of performance metrics over time to ensure benchmark metrics are achieved. AB-MRI finances, which are driven by patient self-payment, will require buy-in from hospital administration with the recognition that downstream revenues will be needed to support initial costs. Finally, successful startup of an AB-MRI program requires active engagement with the larger community of patients and referring providers. As AB-MRI becomes more widely accepted and available, best practices and community standards will continue to evolve to ensure high quality patient care.

Feasibility of Velocity-Selective Arterial Spin Labeling in Breast Cancer Patients for Noncontrast-Enhanced Perfusion Imaging

Background

Dynamic contrast‐enhanced (DCE) MRI is the most sensitive method for detection of breast cancer. However, due to high costs and retention of intravenously injected gadolinium‐based contrast agent, screening with DCE‐MRI is only recommended for patients who are at high risk for developing breast cancer. Thus, a noncontrast‐enhanced alternative to DCE is desirable.

Purpose

To investigate whether velocity selective arterial spin labeling (VS‐ASL) can be used to identify increased perfusion and vascularity within breast lesions compared to surrounding tissue.

Study Type

Prospective.

Population

Eight breast cancer patients.

Field Strength/Sequence

A 3 T; VS‐ASL with multislice single‐shot gradient‐echo echo‐planar‐imaging readout.

Assessment

VS‐ASL scans were independently assessed by three radiologists, with 3–25 years of experience in breast radiology. Scans were scored on lesion visibility and artifacts, based on a 3‐point Likert scale. A score of 1 corresponded to “lesions being distinguishable from background” (lesion visibility), and “no or few artifacts visible, artifacts can be distinguished from blood signal” (artifact score). A distinction was made between mass and nonmass lesions (based on BI‐RADS lexicon), as assessed in the standard clinical exam.

Statistical Tests

Intra‐class correlation coefficient (ICC) for interobserver agreement.

Results

The ICC was 0.77 for lesion visibility and 0.84 for the artifact score. Overall, mass lesions had a mean score of 1.27 on lesion visibility and 1.53 on the artifact score. Nonmass lesions had a mean score of 2.11 on lesion visibility and 2.11 on the artifact score.

Data Conclusion

We have demonstrated the technical feasibility of bilateral whole‐breast perfusion imaging using VS‐ASL in breast cancer patients.

Evidence Level

1

Technical Efficacy

Stage 1

Maximum slope using ultrafast breast DCE-MRI at 1.5 Tesla: a potential tool for predicting breast lesion aggressiveness

OBJECTIVES

We evaluated the relationship between the maximum slope (MS) based on ultrafast breast DCE-MRI sequences, and the clinical parameters and routine prognostic factors of breast cancer.

METHODS

210 lesions were retrospectively evaluated: 150 malignant (30 each of luminal A invasive carcinoma, luminal B invasive carcinoma, HER2 overexpression (HER2), triple negative (TN), invasive lobular carcinoma (ILC)), and 60 benign. For each lesion, the MS was obtained with an ultrafast sequence and semi-quantitative curves were classified into three types with a conventional DCE sequence. The correlation between MS and age, body mass index (BMI), menopause, and routine prognostic factors were analyzed.

RESULTS

A MS cut-off at 6.5%/s could discriminate benign from malignant lesions, with sensitivity and specificity of 84% and 90%, respectively, whereas analysis of semi-quantitative curves showed sensitivity and specificity of 89.3% and 55%, respectively. In multivariate analysis, MS values decreased with BMI increasing (p = 0.035), postmenopausal status (p < 0.001), and positive ER status (p < 0.001) and increased with tumor size (p < 0.001). The MS was significantly lower for the pooled luminal A + ILC group than for the pooled luminal B + HER2 + TN group featuring tumors with poorer prognoses (p < 0.001). With a threshold of 11%/s, the sensitivity and specificity to identify invasive carcinoma subtypes with poorer prognoses were 71% and 68%, respectively.

CONCLUSION

The MS allows better tumor characterization and identifies factors of poor prognosis for breast cancer.

KEY POINTS

• Maximum slope calculated from ultrafast breast DCE-MRI differentiates benign from malignant breast lesions better than semi-quantitative curves of conventional DCE-MRI. • Maximum slope calculated from ultrafast breast DCE-MRI identifies breast cancers with poor prognoses. • In the case of multiple lesions, the most aggressive may be identified and targeted by measuring the maximum slope.

Preoperative breast magnetic resonance imaging in patients with ductal carcinoma in situ: a systematic review for the European Commission Initiative on Breast Cancer (ECIBC)

Objective

To evaluate the impact of preoperative MRI in the management of Ductal carcinoma in situ (DCIS).

Methods

We searched the PubMed, EMBASE and Cochrane Library databases to identify randomised clinical trials (RCTs) or cohort studies assessing the impact of preoperative breast MRI in surgical outcomes, treatment change or loco-regional recurrence. We provided pooled estimates for odds ratios (OR), relative risks (RR) and proportions and assessed the certainty of the evidence using the GRADE approach.

Results

We included 3 RCTs and 23 observational cohorts, corresponding to 20,415 patients. For initial breast-conserving surgery (BCS), the RCTs showed that MRI may result in little to no difference (RR 0.95, 95% CI 0.90 to 1.00) (low certainty); observational studies showed that MRI may have no difference in the odds of re-operation after BCS (OR 0.96; 95% CI 0.36 to 2.61) (low certainty); and uncertain evidence from RCTs suggests little to no difference with respect to total mastectomy rate (RR 0.91; 95% CI 0.65 to 1.27) (very low certainty). We also found that MRI may change the initial treatment plans in 17% (95% CI 12 to 24%) of cases, but with little to no effect on locoregional recurrence (aHR = 1.18; 95% CI 0.79 to 1.76) (very low certainty).

Conclusion

We found evidence of low to very low certainty which may suggest there is no improvement of surgical outcomes with pre-operative MRI assessment of women with DCIS lesions. There is a need for large rigorously conducted RCTs to evaluate the role of preoperative MRI in this population.

Key Points

• Evidence of low to very low certainty may suggest there is no improvement in surgical outcomes with pre-operative MRI.

• There is a need for large rigorously conducted RCTs evaluating the role of preoperative MRI to improve treatment planning for DCIS.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-021-07873-2.

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

OBJECTIVE. The purpose of this study was to investigate whether early kinetic parameters derived from ultrafast dynamic contrast-enhanced MRI (DCE-MRI) using compressed sensing are associated with prognostic factors for breast cancer. MATERIALS AND METHODS. We evaluated 201 consecutive women (mean age, 54.6 years) with breast cancer (168 invasive, 33 ductal carcinoma in situ) who underwent both ultrafast DCE-MRI using compressed sensing (temporal resolution, 4.7 seconds; spatial resolution, 0.8 × 1.1 × 0.9 mm) and surgery between 2018 and 2019. Early kinetic parameters (time to enhancement [TTE] and maximum slope [MS]) were measured in breast lesions by two radiologists using a software program and were correlated with histopathologic prognostic factors. The Mann-Whitney U test and linear regression analysis were used. RESULTS. The median TTE and MS values for breast cancer were 11.9 seconds and 7.7%/s, respectively. The median MS was significantly larger in invasive cancer lesions than in ductal carcinoma in situ lesions (8.4%/s vs 4.7%/s, p < .001). In women with invasive cancer, multivariate linear regression analyses showed that a larger tumor size (> 2 cm) (p = .048) and estrogen receptor-negative status (p < .001) were significantly associated with a shorter TTE. A higher histologic grade (grade 3) (p = .01) was significantly associated with a larger MS. We observed excellent interobserver agreement between two readers in the measurements of TTE and MS (intraclass correlation coefficients, 0.943 and 0.890, respectively). CONCLUSION. Ultrafast MRI-derived early enhancement parameters, such as TTE and MS, are associated with histopathologic prognostic factors in women with breast cancer.

Cost-Effectiveness of Digital Breast Tomosynthesis vs. Abbreviated Breast MRI for Screening Women with Intermediate Risk of Breast Cancer-How Low-Cost Must MRI Be?

BACKGROUND

Digital breast tomosynthesis (DBT) and abbreviated breast MRI (AB-MRI) offer superior diagnostic performance compared to conventional mammography in screening women with intermediate risk of breast cancer due to dense breast tissue. The aim of this model-based economic evaluation was to analyze whether AB-MRI is cost-effective in this cohort compared to DBT.

METHODS

Decision analysis and Markov simulations were used to model the cumulative costs and quality-adjusted life-years (QALYs) over a time horizon of 30 years. Model input parameters were adopted from recent literature. Deterministic and probabilistic sensitivity analyses were applied to test the stability of the model.

RESULTS

In the base-case scenario, the costs of an AB-MRI examination were defined to equal the costs of a full protocol acquisition. Two-yearly screening of women with dense breasts resulted in cumulative discounted costs of $8798 and $9505 for DBT and AB-MRI, and cumulative discounted effects of 19.23 and 19.27 QALYs, respectively, with an incremental cost-effectiveness ratio of $20,807 per QALY gained in the base-case scenario. By reducing the cost of an AB-MRI examination below a threshold of $241 in sensitivity analyses, AB-MRI would become cost-saving compared to DBT.

CONCLUSION

In comparison to DBT, AB-MRI can be considered cost-effective up to a price per examination of $593 in screening patients at intermediate risk of breast cancer.

Additive value of texture analysis based on breast MRI for distinguishing between benign and malignant non-mass enhancement in premenopausal women

BACKGROUND

Non-mass enhancement (NME) is a diagnostic dilemma and highly reliant on the experience of the radiologists. Texture analysis (TA) could serve as an objective method to quantify lesion characteristics. However, it remains unclear what role TA plays in a predictive model based on routine MRI characteristics. The purpose of this study was to explore the value of TA in distinguishing between benign and malignant NME in premenopausal women.

METHODS

Women in whom NME was histologically proven (n = 147) were enrolled (benign: 58; malignant: 89) was retrospective. Then, 102 and 45 patients were classified as the training and validation groups, respectively. Scanning sequences included Fat-suppressed T2-weighted and fat-suppressed contrast-enhanced T1-weighted which were acquired on a 1.5T MRI system. Clinical and routine MR characteristics (CRMC) were evaluated by two radiologists according to the Breast Imaging and Reporting and Data system (2013). Texture features were extracted from all post-contrast sequences in the training group. The combination model was built and then assessed in the validation group. Pearson's chi-square test and Mann-Whitney U test were used to compare categorical variables and continuous variables, respectively. Logistic regression analysis and receiver operating characteristic curve were employed to assess the diagnostic performance of CRMC, TA, and their combination model in NME diagnosis.

RESULTS

The combination model showed superior diagnostic performance in differentiating between benign and malignant NME compared to that of CRMC or TA alone (AUC, 0.887 vs 0.832 vs 0.74). Moreover, compared to CRMC, the model showed high specificity (72.5% vs 80%). The results obtained in the validation group confirmed the model was promising.

CONCLUSIONS

With the combined use of TA and CRMC could afford an improved diagnostic performance in differentiating between benign and malignant NME.

The usefulness of ultrafast MRI evaluation for predicting histologic upgrade of ductal carcinoma in situ

PURPOSE

The purpose of this study was to investigate the usefulness of ultrafast MRI with conventional dynamic contrast-enhanced (DCE)-MRI for predicting histologic upgrade of ductal carcinoma in situ (DCIS) to invasive cancer.

METHODS

This retrospective study enrolled 53 biopsy-proven DCIS lesions in 53 patients and divided into two groups based on postoperative histopathologic diagnoses: non-upgrade and upgrade to invasive cancer groups. Imaging features of conventional DCE-MRI and ultrafast MRI, and histopathologic features were reviewed and compared between the two groups. Interobserver agreements for MRI features were analyzed by two radiologists. The radiologic and histopathologic parameters for predicting histologic upgrade of DCIS were identified using multiple linear regression.

RESULTS

Seventeen lesions (32.1 %) were histologically upgraded to invasive cancer after surgery. The interobserver agreement for ultrafast MRI parameters was excellent, and maximum slope (MS) and maximum enhancement (ME) showed the highest reliability (intraclass correlation coefficients, 0.907 and 0.897, respectively). The upgrade group showed significantly larger lesion size on MRI (median 40 mm [25^th to 75^th percentiles 16.0-83.0] vs. 18.5 mm [10.0-29.8], p < 0.001), higher MS (12.1 %/s [8.2-13.9] vs. 8.7 %/s [6.4-11.1], p = 0.004), and higher ME (236.5 % [153.7-253.7] vs. 175.4 % [140.1-207.7], p = 0.027) than non-upgrade group. Lesion size (≥ 20 mm), MS (> 11.5 %), and ME (> 229.1 %) were significant predictors for histologic upgrade, which could predict 10 cases of histologic upgrade (10/17, 58.8 %) without a false-positive case.

CONCLUSION

Preoperative ultrafast MRI with conventional DCE-MRI could be useful in management decisions for DCIS patients.

Abbreviated magnetic resonance imaging in breast cancer: A systematic review of literature

BACKGROUND

: magnetic resonance imaging (MRI) has been increasingly used to study breast cancer for screening high-risk cases, pre-operative staging, and problem-solving because of its high sensitivity. However, its cost-effectiveness is still debated. Thus, the concept of abbreviated MRI (ABB-MRI) protocols was proposed as a possible solution for reducing MRI costs.

PURPOSE

: to investigate the role of the abbreviated MRI protocols in detecting and staging breast cancer.

METHODS

: a systematic search of the literature was carried out in the bibliographic databases: Scopus, PubMed, Medline, and Science Direct.

RESULTS

: forty-one articles were included, which described results of the assessment of fifty-three abbreviated protocols for screening, staging, recurrence assessing, and problem-solving or clarification.

CONCLUSIONS

: the use of ABB-MRI protocols allows reducing the acquisition and reading times, maintaining a high concordance with the final interpretation, in comparison to a complete protocol. However, larger prospective and multicentre trials are necessary to validate the performance in specific clinical environments.

Ultrafast Dynamic Contrast-Enhanced Breast MRI: Lesion Conspicuity and Size Assessment according to Background Parenchymal Enhancement

Objective

To evaluate the clinical utility of ultrafast dynamic contrast-enhanced (DCE)-MRI compared to conventional DCE-MRI by studying lesion conspicuity and size according to the level of background parenchymal enhancement (BPE).

Materials and Methods

This study included 360 women (median age, 54 years; range, 26–82 years) with 361 who had undergone breast MRI, including both ultrafast and conventional DCE-MRI before surgery, between January and December 2017. Conspicuity was evaluated using a five-point score. Size was measured as the single maximal diameter. The Wilcoxon signed-rank test was used to compare median conspicuity score. To identify factors associated with conspicuity, multivariable logistic regression was performed. Absolute agreement between size at MRI and histopathologic examination was assessed using the intraclass correlation coefficient (ICC).

Results

The median conspicuity scores were 5 at both scans, but the interquartile ranges were significantly different (5-5 at ultrafast vs. 4-5 at conventional, p < 0.001). Premenopausal status (odds ratio [OR] = 2.2, p = 0.048), non-mass enhancement (OR = 4.1, p = 0.001), moderate to marked BPE (OR = 7.5, p < 0.001), and shorter time to enhancement (OR = 0.9, p = 0.043) were independently associated with better conspicuity at ultrafast scans. Tumor size agreement between MRI and histopathologic examination was similar for both scans (ICC = 0.66 for ultrafast vs. 0.63 for conventional).

Conclusion

Ultrafast DCE-MRI could improve lesion conspicuity compared to conventional DCE-MRI, especially in women with premenopausal status, non-mass enhancement, moderate to marked BPE or short time to enhancement.

Maximum slope of ultrafast dynamic contrast-enhanced MRI of the breast: Comparisons with prognostic factors of breast cancer

PURPOSE

To determine the relationship between the maximum slope (MS) of ultrafast dynamic contrast-enhanced (DCE)-MRI and prognostic factors of breast cancer.

METHODS

One hundred thirteen patients with 118 breast cancers were included in this study. The ultrafast DCE sequence was acquired using a higher parallel imaging factor. Its spatial resolution was 0.9 × 0.9 × 2.5 mm and its temporal resolution was 8.3 s/phase. Each lesion was automatically segmented, and the ROI of highest enhancement in the lesion was identified. In this ROI, the MS was calculated. The MS of each lesion was compared with various prognostic factors of breast cancer.

RESULTS

The MS of invasive cancer (median: 9.81%/sec) was significantly higher than that of ductal carcinoma in situ (median: 7.26%/sec) (p = 0.001). In the ROC analysis, the area under the ROC curve (AUC) was 0.7295. The MS of invasive cancer with axillary lymph node (LN) metastasis (median: 11.97%/sec) was significantly higher than that without axillary LN metastasis (median: 9.425%/sec) (p = 0.0024). In the ROC analysis, the AUC was 0.7177. In addition, the MS became significantly higher as the level of the proliferation marker ki-67 increased (correlation coefficient: 0.3317) (p = 0.0009).

CONCLUSIONS

MS of ultrafast DCE-MRI is useful for predicting the prognostic factors of breast cancer. Higher maximum slope (MS) is significantly associated with an invasive breast cancer component. Higher MS is significantly associated with an axillary lymph node metastasis. MS becomes significantly higher with increasing ki-67 (a proliferation marker). Ultrafast MRI is useful for predicting the prognostic factors of breast cancer.

Ultrafast dynamic contrast-enhanced breast MRI may generate prognostic imaging markers of breast cancer

Background

Ultrafast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)-derived kinetic parameters have demonstrated at least equivalent accuracy to standard DCE-MRI in differentiating malignant from benign breast lesions. However, it is unclear if they have any efficacy as prognostic imaging markers. The aim of this study was to investigate the relationship between ultrafast DCE-MRI-derived kinetic parameters and breast cancer characteristics.

Methods

Consecutive breast MRI examinations between February 2017 and January 2018 were retrospectively reviewed to determine those examinations that meet the following inclusion criteria: (1) BI-RADS 4–6 MRI performed on a 3T scanner with a 16-channel breast coil and (2) a hybrid clinical protocol with 15 phases of ultrafast DCE-MRI (temporal resolution of 2.7–4.6 s) followed by early and delayed phases of standard DCE-MRI. The study included 125 examinations with 142 biopsy-proven breast cancer lesions. Ultrafast DCE-MRI-derived kinetic parameters (maximum slope [MS] and bolus arrival time [BAT]) were calculated for the entire volume of each lesion. Comparisons of these parameters between different cancer characteristics were made using generalized estimating equations, accounting for the presence of multiple lesions per patient. All comparisons were exploratory and adjustment for multiple comparisons was not performed; P values < 0.05 were considered statistically significant.

Results

Significantly larger MS and shorter BAT were observed for invasive carcinoma than ductal carcinoma in situ (DCIS) (P < 0.001 and P = 0.008, respectively). Significantly shorter BAT was observed for invasive carcinomas with more aggressive characteristics than those with less aggressive characteristics: grade 3 vs. grades 1–2 (P = 0.025), invasive ductal carcinoma vs. invasive lobular carcinoma (P = 0.002), and triple negative or HER2 type vs. luminal type (P < 0.001).

Conclusions

Ultrafast DCE-MRI-derived parameters showed a strong relationship with some breast cancer characteristics, especially histopathology and molecular subtype.

Time-to-enhancement at ultrafast breast DCE-MRI: potential imaging biomarker of tumour aggressiveness

OBJECTIVES

This study was conducted in order to investigate whether there is a correlation between the time-to-enhancement (TTE) in ultrafast MRI and histopathological characteristics of breast cancers.

METHODS

Between January and August 2017, 274 consecutive breast cancer patients (mean age, 53.5 years; range, 25-80 years) who underwent ultrafast MRI and subsequent surgery were included for analysis. Ultrafast MRI scans were acquired using TWIST-VIBE or 4D TRAK-3D TFE sequences. TTE and maximum slope (MS) were derived from the ultrafast MRI. The repeated measures ANOVA, Mann-Whitney U test and Kruskal-Wallis H test were performed to compare the median TTE, MS and SER according to histologic type, histologic grade, ER/PR/HER2 positivity, level of Ki-67 and tumour subtype. For TTE calculation, intraclass correlation coefficient (ICC) was used to evaluate interobserver variability.

RESULTS

The median TTE of invasive cancers was shorter than that of in situ cancers (p < 0.001). In invasive cancers, large tumours showed shorter TTE than small tumours (p = 0.001). High histologic/nuclear grade cancers had shorter TTE than low to intermediate grade cancers (p < 0.001 and p < 0.001). HER2-positive cancers showed shorter TTE than HER2-negative cancers (p = 0.001). The median TTE of cancers with high Ki-67 was shorter than that of cancers with low Ki-67 (p < 0.001). ICC between two readers showed moderate agreement (0.516). No difference was found in the median MS or SER values according to the clinicopathologic features.

CONCLUSIONS

The median TTE of breast cancer in ultrafast MRI was shorter in invasive or aggressive tumours than in in situ cancer or less aggressive tumours, respectively.

KEY POINTS

• Invasive breast tumours show a shorter TTE in ultrafast DCE-MRI than in situ cancers. • A shorter TTE in ultrafast DCE-MRI is associated with breast tumours of a large size, high histologic or nuclear grade, PR negativity, HER2 positivity and high Ki-67 level.

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

PURPOSE

To 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.

METHODS

This 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 (slope_max) 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.

RESULTS

All ultrafast MRI parameters differed significantly between malignant and benign tumors (p < 0.001). Initial enhancement phase by reviewer and slope_max 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 slope_max (>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.

CONCLUSIONS

The additional use of ultrafast MRI can improve the specificity of conventional DCE-MRI when evaluating MRI-detected masses in breast cancer patients.

Differentiation between subcentimeter carcinomas and benign lesions using kinetic parameters derived from ultrafast dynamic contrast-enhanced breast MRI

OBJECTIVES

This study aims to evaluate ultrafast DCE-MRI-derived kinetic parameters that reflect contrast agent inflow effects in differentiating between subcentimeter BI-RADS 4-5 breast carcinomas and benign lesions.

METHODS

We retrospectively reviewed consecutive 3-T MRI performed from February to October 2017, during which ultrafast DCE-MRI was performed as part of a hybrid clinical protocol with conventional DCE-MRI. In total, 301 female patients with 369 biopsy-proven breast lesions were included. Ultrafast DCE-MRI was acquired continuously over approximately 60 s (temporal resolution, 2.7-7.1 s/phase) starting simultaneously with the start of contrast injection. Four ultrafast DCE-MRI-derived kinetic parameters (maximum slope [MS], contrast enhancement ratio [CER], bolus arrival time [BAT], and initial area under gadolinium contrast agent concentration [IAUGC]) and one conventional DCE-MRI-derived kinetic parameter (signal enhancement ratio [SER]) were calculated for each lesion. Wilcoxon rank sum test or Fisher's exact test was performed to compare kinetic parameters, volume, diameter, age, and BI-RADS morphological descriptors between subcentimeter carcinomas and benign lesions. Univariate/multivariate logistic regression analyses were performed to determine predictive parameters for subcentimeter carcinomas.

RESULTS

In total, 125 lesions (26 carcinomas and 99 benign lesions) were identified as BI-RADS 4-5 subcentimeter lesions. Subcentimeter carcinomas demonstrated significantly larger MS and SER and shorter BAT than benign lesions (p = 0.0117, 0.0046, and 0.0102, respectively). MS, BAT, and age were determined as significantly predictive for subcentimeter carcinoma (p = 0.0208, 0.0023, and < 0.0001, respectively).

CONCLUSIONS

Ultrafast DCE-MRI-derived kinetic parameters may be useful in differentiating subcentimeter BI-RADS 4 and 5 carcinomas from benign lesions.

KEY POINTS

• Ultrafast DCE-MRI can generate kinetic parameters, effectively differentiating breast carcinomas from benign lesions. • Subcentimeter carcinomas demonstrated significantly larger maximum slope and shorter bolus arrival time than benign lesions. • Maximum slope and bolus arrival time contribute to better management of suspicious subcentimeter breast lesions.